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学术插件快速索引 + +问题开始时间：2026-06-11-03-26-41 + +资料来源： +- GitHub 仓库： +- 本地下载目录：`文档润色流和知识库构建流/claude-scholar` +- 本次核对的 GitHub HEAD：`34d0cdb48a03080c7243841e19ff03ef30967d97` +- 重点阅读文件：`README.zh-CN.md`、`CLAUDE.zh-CN.md`、`MCP_SETUP.zh-CN.md`、`OBSIDIAN_SETUP.zh-CN.md`、`agents/*.md`、`skills/*/SKILL.md`、`commands/*.md`、`rules/*.md` + +## 1. 总体定位 + +`claude-scholar` 是面向学术研究和软件开发的半自动研究助手插件。它的核心路线是： + +```text +问题 -> 证据 -> 实验 -> 分析 -> 论断 -> 写作 +``` + +它不负责替代研究者做最终判断，而是把文献整理、证据台账、项目知识库、论文或标书写作、引用核验、审稿回复、结果分析等重复但高要求的环节结构化。 + +对“文档润色流”的价值主要有五点： +- 把模糊主题拆成研究问题、证据需求、假设和下一步动作； +- 用 Zotero 和 Obsidian 把资料沉淀成可追溯知识库； +- 用 claim-evidence gate 防止无证据论断进入正式文本； +- 用 paper-miner、writing-anti-ai、nature-polishing 等技能辅助润色； +- 用 paper-self-review、citation-verification 做提交前自审。 + +## 2. 安装与使用入口 + +### 2.1 完整安装 + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +bash /tmp/claude-scholar/scripts/setup.sh +``` + +说明： +- `main` 分支面向 Claude Code； +- Codex CLI 应参考仓库的 `codex` 分支； +- Kimi Code CLI 和 OpenCode 也分别有对应分支； +- 完整安装会安装 skills、commands、agents、rules、hooks 等组件，并尽量保留用户已有配置。 + +### 2.2 插件市场安装 + +```text +/plugin marketplace add Galaxy-Dawn/claude-scholar +/plugin install claude-scholar@claude-scholar +``` + +注意： +- 插件市场会加载 skills、commands、agents 和 hooks； +- `rules/` 需要手动复制； +- 插件不会自动合并已有 `CLAUDE.md` 或自动配置 `settings.json`； +- Zotero MCP、Obsidian vault 等外部集成仍需手动配置。 + +### 2.3 手动选择性安装 + +适合只需要文档润色与学术写作能力时： + +```bash +cp -r /tmp/claude-scholar/skills/research-ideation ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/ml-paper-writing ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/citation-verification ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/writing-anti-ai ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/paper-self-review ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/doc-coauthoring ~/.claude/skills/ +cp /tmp/claude-scholar/agents/paper-miner.md ~/.claude/agents/ +cp /tmp/claude-scholar/agents/literature-reviewer.md ~/.claude/agents/ +``` + +## 3. Agent 快速索引 + +Agent 通常由 Claude Code 根据触发描述自动调度。用户侧最稳妥的调用方式是自然语言明确说明任务，或使用相应 slash command 间接触发。 + +| Agent | 主要功能 | 何时使用 | 典型调用 | +|---|---|---|---| +| `literature-reviewer` | 检索论文、导入 Zotero、创建主题 collection、读取全文、综合文献、识别 research gap | 新研究主题、文献综述、研究空白分析、proposal 前期 | “请围绕 X 做系统文献综述”；`/research-init "topic" focused both`；`/zotero-review "collection" deep` | +| `paper-miner` | 从 PDF、DOCX、arXiv 或论文网页中提炼写作模式、段落结构、venue-specific signals、rebuttal 策略 | 学习优秀论文、获批标书、Nature/NeurIPS 写法 | `/mine-writing-patterns path/to/paper.pdf introduction`；“请从这篇论文中提炼可复用写作结构” | +| `rebuttal-writer` | 解析审稿意见，分类 Major/Minor/typo/misunderstanding，选择 Accept/Defend/Clarify/Experiment 策略，写逐点回复 | 审稿回复、修改说明、专家意见答复 | `/rebuttal review-comments.md`；“请帮我逐条回应评审意见” | +| `kaggle-miner` | 从 Kaggle 竞赛和优胜方案中抽取工程路线、模型策略、best practices、代码模板 | 需要从竞赛方案学习技术路径 | “Learn from this Kaggle competition: URL” | +| `code-reviewer` | 审查 git diff 中的安全、质量、性能、测试覆盖、硬编码密钥等问题 | 修改代码后、提交前 | `/code-review`；“请 review 当前改动” | +| `tdd-guide` | 以 RED -> GREEN -> REFACTOR 推进测试驱动开发 | 明确要求 TDD 或风险较高功能 | `/tdd 实现 X`；“请先写失败测试再实现” | + +## 4. 学术写作与文档润色 Skill 索引 + +| Skill | 功能 | 文档润色中的用法 | +|---|---|---| +| `research-ideation` | 5W1H、研究问题定义、gap analysis、method selection、research planning | 把标题或方向拆成科学问题、研究假设、证据需求、证伪条件和最小下一步 | +| `doc-coauthoring` | 大型文档协作写作，包含上下文收集、结构搭建、逐节打磨、读者测试 | 用于标书、proposal、技术方案、决策文档的分节共写 | +| `ml-paper-writing` | 面向顶会论文的写作、相关工作、引用核验和 claim ledger | 借用其 claim-evidence 纪律，避免把计划、动机或猜测写成已证实结论 | +| `nature-writing` | 根据 claims、figures、results、notes 或中文草稿重建 Nature 风格章节 | 起草 abstract、introduction、results narrative、discussion | +| `nature-polishing` | 将稿件润色、重组或翻译为更接近 Nature 风格的精炼英文 | 中英文学术段落精炼、hedging、逻辑顺序调整 | +| `nature-response` | Nature 系修回逐点回复 | 处理 editor letter、reviewer comments、revision notes | +| `nature-data` | Data Availability、repository plan、FAIR metadata | 写数据可用性、数据仓库方案和受限数据说明 | +| `citation-verification` | 核验 DOI、arXiv、CrossRef、Semantic Scholar、Zotero 元数据和论断-引用对齐 | 写作时逐条核查参考文献是否真实、是否支撑对应论断 | +| `writing-anti-ai` | 去除中英文 AI 写作痕迹，减少空泛套话、机械排比和过度连接词 | 标书和论文润色最后一轮使用，使表达自然但不过度口语化 | +| `paper-self-review` | 投稿或提交前结构、逻辑、引用、图表、合规性、过度声称检查 | 提交标书或论文前做 claim audit 和结构自审 | +| `review-response` | 审稿意见分析与 rebuttal 工作流 | 对评审意见、专家修改建议做分类和逐条回应 | +| `publication-chart-skill` | 论文级图表和表格工作流 | 机制图、技术路线图、实验结果图表的质量控制 | +| `latex-conference-template-organizer` | 整理会议 LaTeX 模板为 Overleaf-ready 结构 | 论文投稿模板整理 | +| `zotero-obsidian-bridge` | 把 Zotero 作为文献源，向 Obsidian KB 写入 `Sources/Papers`、`Knowledge`、`Writing` | 文献笔记、证据记录、相关工作草稿联动 | + +## 5. Slash Command 快速索引 + +### 5.1 研究启动与文献 + +| Command | 用途 | 示例 | +|---|---|---| +| `/research-init` | 初始化研究主题，创建或审计 Zotero collection，生成 research question card，证据足够时才生成 proposal | `/research-init "static magnetic field exosome macrophage polarization" focused both` | +| `/zotero-review` | 读取 Zotero collection，生成文献综述、方法分类、研究空白、相关工作草稿 | `/zotero-review "ATC-MagneticField" deep` | +| `/zotero-notes` | 批量读取 Zotero collection 并写详细论文笔记 | `/zotero-notes "ATC-MagneticField" detailed` | +| `/mine-writing-patterns` | 从论文或标书中抽取写作模式并更新 paper-miner 全局写作记忆 | `/mine-writing-patterns path/to/grant.pdf proposal` | + +### 5.2 写作、润色与回复 + +| Command | 用途 | 示例 | +|---|---|---| +| `/rebuttal` | 生成带证据锚点的逐点审稿回复 | `/rebuttal review-comments.md` | +| `/presentation` | 生成会议报告结构和讲解指导 | `/presentation paper.md 20min` | +| `/poster` | 整理论文内容并生成海报版式与内容指导 | `/poster paper.md` | +| `/promote` | 起草社交媒体、博客或外部传播摘要 | `/promote paper.md` | + +### 5.3 Obsidian 项目知识库 + +| Command | 用途 | +|---|---| +| `/kb-init` | 初始化 `Research/{project-slug}/` 项目知识库 | +| `/kb-status` | 汇总当前 KB 绑定、registry 和关键路径 | +| `/kb-ingest` | 将新资料路由到 `Sources/Papers`、`Sources/Web`、`Sources/Docs` 等 | +| `/kb-log` | 更新当天 `Daily/`、必要时更新 plan/hub/project memory | +| `/kb-sync` | 确定性刷新 scaffold、registry、index、daily、绑定状态 | +| `/kb-links` | 修复或增强 canonical notes 之间的 wikilink | +| `/kb-promote` | 将稳定内容从 Daily 或 source note 提升到 `Knowledge`、`Writing` 等 | +| `/kb-index` | 刷新 `02-Index.md` 自动索引块 | +| `/kb-lint` | 检查断链、registry 覆盖、index 覆盖、canvas 有效性 | +| `/kb-archive` | archive、detach、purge、rename KB 对象 | +| `/kb-map` | 生成或修复 literature canvas、可选 Bases 或其他显式图谱 | +| `/kb-literature-review` | 从 `Sources/Papers` 生成证据门槛下的文献综合和 `Maps/literature.canvas` | + +### 5.4 代码、验证与项目维护 + +| Command | 用途 | +|---|---| +| `/analyze-results` | blocker-first 实验分析，证据足够时生成统计、图表和结果报告 | +| `/verify` | 类型检查、lint、测试、安全扫描、git 状态 | +| `/code-review` | 对未提交改动做安全和质量审查 | +| `/tdd` | 测试驱动开发 | +| `/commit` | 本地 Conventional Commit，不推送 | +| `/update-github` | commit 并推送到远程 | +| `/checkpoint` | 创建或验证工作流 checkpoint | + +## 6. Zotero MCP 调用方法 + +Zotero MCP 是 `literature-reviewer`、`/research-init`、`/zotero-review`、`/zotero-notes` 的核心外部能力。 + +Codex CLI 配置示例： + +```toml +[mcp_servers.zotero] +command = "zotero-mcp" +args = ["serve"] +enabled = true + +[mcp_servers.zotero.env] +ZOTERO_API_KEY = "your-api-key" +ZOTERO_LIBRARY_ID = "your-user-id" +ZOTERO_LIBRARY_TYPE = "user" +UNPAYWALL_EMAIL = "your-email@example.com" +UNSAFE_OPERATIONS = "all" +NO_PROXY = "localhost,127.0.0.1" +``` + +常用工具： +- 导入：`zotero_add_items_by_identifier`、`zotero_add_items_by_doi`、`zotero_add_items_by_arxiv`、`zotero_add_item_by_url` +- 读取：`zotero_get_collections`、`zotero_get_collection_items`、`zotero_search_items`、`zotero_get_item_metadata`、`zotero_get_item_fulltext` +- 更新：`zotero_create_collection`、`zotero_move_items_to_collection`、`zotero_reconcile_collection_duplicates` +- PDF：`zotero_find_and_attach_pdfs`、`zotero_add_linked_url_attachment` + +默认导入策略： +1. 优先抽取 DOI、arXiv ID、publisher landing page 或 PDF URL； +2. 使用 `zotero_add_items_by_identifier` 导入； +3. 导入时尝试自动附加 PDF； +4. 导入后运行 collection 去重； +5. abstract-only 或 webpage-placeholder 不能支撑稳定写作论断。 + +## 7. 推荐的文档润色流程 + +### 7.1 标书或论文初稿前 + +```text +research-ideation + -> Research Question Card + -> Evidence Records + -> Gap Analysis + -> Proposal Readiness Gate +``` + +建议口令： + +```text +请使用 research-ideation，把这个题目拆成研究问题、研究假设、证据需求、证伪条件、研究内容和最小下一步。 +``` + +### 7.2 资料与文献入库 + +```text +Zotero / local PDFs / web sources + -> Sources/Papers 或 Sources/Docs + -> Evidence Record + -> Knowledge synthesis + -> Writing draft +``` + +建议口令： + +```text +请把这些论文作为 Sources/Papers 入库，逐篇生成 Evidence Record。只有证据足够的论断才能提升到 Knowledge 或 Writing。 +``` + +### 7.3 学习优秀文本 + +```text +paper-miner + -> structure signals + -> reusable phrasing + -> venue-specific signals + -> global writing memory +``` + +建议口令： + +```text +请用 paper-miner 分析这份获批标书，提炼可迁移的章节结构、论证节奏和常用表达。不要复制具体疾病背景或未核实数据。 +``` + +### 7.4 段落润色 + +先做证据检查，再做语言润色： + +```text +paper-self-review / citation-verification + -> claim audit + -> writing-anti-ai / nature-polishing + -> final wording +``` + +建议口令： + +```text +请先检查这段话中哪些论断需要证据，给出 keep / weaken / revise / remove，再用 writing-anti-ai 风格润色，保留学术严谨性。 +``` + +## 8. 对本项目的使用建议 + +- 不要直接把 `claude-scholar` 当成“医学标书自动生成器”；它原生偏 CS/AI 研究，更适合借用流程纪律。 +- 对标书写作，最重要的是 `research-ideation`、`doc-coauthoring`、`citation-verification`、`paper-self-review`、`writing-anti-ai`、`paper-miner`。 +- 任何疾病背景、材料性能、实验结论、政策数据或文献事实都应进入 Evidence Record，再进入正文。 +- 可以复用优秀标书的结构、论证顺序、段落功能和语气，但不要复用未经核实的事实性论断。 +- 文档最终提交前至少做三轮检查：引用核验、claim audit、AI 痕迹润色。 + +## 9. 最小调用清单 + +```text +1. 新主题： + /research-init "topic" focused both + +2. 文献集合综述： + /zotero-review "collection-name" deep + +3. 批量论文笔记： + /zotero-notes "collection-name" detailed + +4. 学习优秀写法： + /mine-writing-patterns path/to/source.pdf proposal + +5. 知识库入库： + /kb-ingest path/to/source.pdf + +6. 文献综合： + /kb-literature-review + +7. 标书/论文自审： + 请使用 paper-self-review 做 claim audit。 + +8. 去除 AI 痕迹： + 请使用 writing-anti-ai 润色以下段落。 +``` diff --git 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z@bpQ`+I6<^?mZTUEtYXv_BqVtk)z{;!2Q{@sql$Q!_nKe^}+J&8Jy@x5mVKZunaRD z>1A3ibz^t>9cNV}~Ic8OXr13_*|=K~;ssRWzQTA_?j6&Ds9!^95!t3TNf zUzA9g6ZuGK==^&h=?ZYahhFGr7eKM@E@9n+DWuay*;6S5PS0~JbFeu6cQ6jWpo0xuP`cASA0!<6XV0simspmCCU$tIz z!UPY$iFebm$B$>2_*U#ve?Z)y!|s}Zub-F<+7IV8d}RG_LpNX|`vj>{Wp1YO?hN91J2;xV mc1xw~*_)@>ODB8UG(XLJAcC literal 0 HcmV?d00001 diff --git a/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.ja-JP.md b/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.ja-JP.md new file mode 100644 index 0000000..a8febe6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.ja-JP.md @@ -0,0 +1,190 @@ +# MCPサーバー セットアップガイド + +Claude Scholarは拡張機能のためにMCP（Model Context Protocol）サーバーを利用します。MCPサーバーはこのリポジトリには**含まれていません** — ユーザーが個別にインストールおよび設定する必要があります。 + +## 必須MCPサーバー + +### 1. Zotero MCP（研究ワークフロー） + +**使用先**: `literature-reviewer`エージェント、`/research-init`、`/zotero-review`、`/zotero-notes`コマンド + +**パッケージ**: [Galaxy-Dawn/zotero-mcp](https://github.com/Galaxy-Dawn/zotero-mcp) — ローカルZoteroデスクトップとWeb APIモードを自動検出。Web認証情報はリモートアクセスまたは書き込みツールの場合にのみ必要。 + +#### 機能 + +| カテゴリ | ツール | +|---------|-------| +| **インポート** | `zotero_add_items_by_doi`, `zotero_add_items_by_arxiv`, `zotero_add_item_by_url` | +| **読み取り** | `zotero_get_collections`, `zotero_get_collection_items`, `zotero_search_items`, `zotero_semantic_search` | +| **更新** | `zotero_update_item`, `zotero_update_note`, `zotero_create_collection`, `zotero_move_items_to_collection` | +| **削除** | `zotero_delete_items`（ゴミ箱へ移動）, `zotero_delete_collection` | +| **PDF** | `zotero_find_and_attach_pdfs`（Unpaywall経由）, `zotero_add_linked_url_attachment` | + +#### 前提条件 + +1. Web API認証情報なしでローカル読み取り専用アクセスを行う場合は[Zotero](https://www.zotero.org/)をインストール +2. 書き込みツールまたはリモートWeb APIアクセスの場合は、[Zotero設定 -> セキュリティ -> アプリケーション](https://www.zotero.org/settings/security#applications)を開く +3. `Create new private key`をクリックしてAPIキーを生成 +4. 同じページでボタンの下に表示される`User ID`をコピー。個人ライブラリの場合、この数値を`ZOTERO_LIBRARY_ID`として使用 + +#### インストール + +```bash +# uv経由でインストール（推奨） +uv tool install git+https://github.com/Galaxy-Dawn/zotero-mcp.git +``` + +#### 設定 + +以下からプラットフォームを選択してください: + +##### Claude Code + +Claude Code v2.1.5以降の場合、`~/.claude.json`の`mcpServers`に追加。 + +それ以前のバージョンの場合、`~/.claude/settings.json`の`mcpServers`に追加: + +```json +{ + "mcpServers": { + "zotero": { + "command": "zotero-mcp", + "args": ["serve"], + "env": { + "ZOTERO_API_KEY": "your-api-key", + "ZOTERO_LIBRARY_ID": "your-user-id", + "ZOTERO_LIBRARY_TYPE": "user", + "UNPAYWALL_EMAIL": "your-email@example.com", + "UNSAFE_OPERATIONS": "all" + } + } + } +} +``` + +##### Codex CLI + +`~/.codex/config.toml`に追加: + +```toml +[mcp_servers.zotero] +command = "zotero-mcp" +args = ["serve"] +enabled = true + +[mcp_servers.zotero.env] +ZOTERO_API_KEY = "your-api-key" +ZOTERO_LIBRARY_ID = "your-user-id" +ZOTERO_LIBRARY_TYPE = "user" +UNPAYWALL_EMAIL = "your-email@example.com" +UNSAFE_OPERATIONS = "all" +NO_PROXY = "localhost,127.0.0.1" +``` + +##### OpenCode + +`~/.opencode/opencode.jsonc`に追加: + +```jsonc +{ + "mcp": { + "zotero": { + "type": "local", + "command": ["zotero-mcp", "serve"], + "enabled": true + } + } +} +``` + +次に`~/.zshrc`で環境変数を設定: + +```bash +# Zotero MCP +export ZOTERO_API_KEY="your-api-key" +export ZOTERO_LIBRARY_ID="your-user-id" +export ZOTERO_LIBRARY_TYPE="user" +export UNPAYWALL_EMAIL="your-email@example.com" +export UNSAFE_OPERATIONS="all" +``` + +#### 環境変数 + +| 変数 | 必須 | 説明 | +|------|-----|------| +| `ZOTERO_API_KEY` | ローカル読み取り専用: 不要、Web/書き込みツール: 必要 | Zotero APIキー | +| `ZOTERO_LIBRARY_ID` | ローカル読み取り専用: 不要、Web/書き込みツール: 必要 | 個人ライブラリ用のZotero `User ID`（数値） | +| `ZOTERO_LIBRARY_TYPE` | 必要 | `user`または`group` | +| `UNPAYWALL_EMAIL` | 不要 | Unpaywall PDF検索用メールアドレス | +| `UNSAFE_OPERATIONS` | 不要 | `items`（delete_items）、`all`（delete_collection） | +| `NO_PROXY` | 不要 | localhostのプロキシをバイパス | + +注意: +- 最小限のローカルセットアップは`command = "zotero-mcp"`と`args = ["serve"]`のみです。 +- 本番設定に`your-api-key`、`your-user-id`、`your-email@example.com`などのプレースホルダー値を残さないでください。 + +#### 利用可能なツール + +| ツール | 用途 | +|-------|------| +| `zotero_get_collections` | 全コレクションを一覧表示 | +| `zotero_get_collection_items` | コレクション内のアイテムを取得 | +| `zotero_search_items` | キーワードでライブラリを検索 | +| `zotero_search_by_tag` | タグで検索 | +| `zotero_get_item_metadata` | アイテムのメタデータとアブストラクトを取得 | +| `zotero_get_item_fulltext` | PDFフルテキストを読解 | +| `zotero_get_annotations` | PDFアノテーションを取得 | +| `zotero_get_notes` | ノートを取得 | +| `zotero_semantic_search` | セマンティック検索（埋め込みを使用） | +| `zotero_advanced_search` | 高度な検索 | +| `zotero_add_items_by_doi` | DOIで論文をインポート | +| `zotero_add_items_by_arxiv` | arXiv IDでプレプリントをインポート | +| `zotero_add_item_by_url` | Webページをアイテムとして保存 | +| `zotero_update_item` | アイテムのフィールドを更新 | +| `zotero_update_note` | ノートの内容を更新 | +| `zotero_create_collection` | コレクションを作成 | +| `zotero_move_items_to_collection` | コレクション間でアイテムを移動 | +| `zotero_update_collection` | コレクション名を変更 | +| `zotero_delete_collection` | コレクションを削除 | +| `zotero_delete_items` | アイテムをゴミ箱に移動 | +| `zotero_find_and_attach_pdfs` | OA PDFを検索して添付 | +| `zotero_add_linked_url_attachment` | リンクURL添付ファイルを追加 | + +### 2. ブラウザオートメーションMCP（任意） + +用途: Chromeブラウザ制御、Webページインタラクション。 + +#### 設定 + +```json +{ + "mcpServers": { + "streamable-mcp-server": { + "type": "streamable-http", + "url": "http://127.0.0.1:12306/mcp" + } + } +} +``` + +## 検証 + +設定後、CLIを再起動してMCPサーバーの接続を確認: + +``` +# Zoteroの例: +> List my Zotero collections + +``` + +ツールがデータ（例: コレクション）を返せば、セットアップは完了です。 + +## トラブルシューティング + +| 問題 | 解決方法 | +|------|---------| +| ツールがエラーを返す | APIキーとライブラリIDが正しいか確認 | +| PDF添付が失敗する | `UNPAYWALL_EMAIL`が設定されているか確認 | +| 削除操作がブロックされる | `UNSAFE_OPERATIONS=items`または`all`を設定 | +| HTTPエラー | `NO_PROXY`にlocalhostが含まれているか確認 | +| APIレート制限（429） | 一度に10件以下の論文をバッチ処理し、バッチ間に遅延を追加 | diff --git a/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.md b/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.md new file mode 100644 index 0000000..9e788c3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.md @@ -0,0 +1,194 @@ +# MCP Server Setup Guide + +Claude Scholar relies on MCP (Model Context Protocol) servers for extended capabilities. MCP servers are **not included** in this repository — users must install and configure them separately. + +## Required MCP Servers + +### 1. Zotero MCP (Research Workflow) + +**Used by**: `literature-reviewer` agent, `/research-init`, `/zotero-review`, `/zotero-notes` commands + +**Package**: [Galaxy-Dawn/zotero-mcp](https://github.com/Galaxy-Dawn/zotero-mcp) — auto-detects local Zotero desktop vs Web API mode; Web credentials are only required for remote access or write tools. + +#### Features + +| Category | Tools | +|----------|-------| +| **Import** | `zotero_add_items_by_identifier`, `zotero_add_items_by_doi`, `zotero_add_items_by_arxiv`, `zotero_add_item_by_url` | +| **Read** | `zotero_get_collections`, `zotero_get_collection_items`, `zotero_search_items`, `zotero_semantic_search` | +| **Update** | `zotero_update_item`, `zotero_update_note`, `zotero_create_collection`, `zotero_move_items_to_collection`, `zotero_reconcile_collection_duplicates` | +| **Delete** | `zotero_delete_items` (to trash), `zotero_delete_collection` | +| **PDF** | `zotero_find_and_attach_pdfs` (source-aware PDF cascade), `zotero_add_linked_url_attachment` | + +#### Prerequisites + +1. Install [Zotero](https://www.zotero.org/) if you want local read-only access without Web API credentials +2. For write tools or remote Web API access, open [Zotero Settings -> Security -> Applications](https://www.zotero.org/settings/security#applications) +3. Click `Create new private key` to generate your API key +4. On the same page, copy the `User ID` shown below the button. Use this numeric value as `ZOTERO_LIBRARY_ID` for personal libraries + +#### Installation + +```bash +# Install via uv (recommended) +uv tool install git+https://github.com/Galaxy-Dawn/zotero-mcp.git +``` + +#### Configuration + +Choose your platform below: + +##### Claude Code + +For Claude Code v2.1.5+, add to your `~/.claude.json` under `mcpServers`. + +For earlier versions, add to your `~/.claude/settings.json` under `mcpServers`: + +```json +{ + "mcpServers": { + "zotero": { + "command": "zotero-mcp", + "args": ["serve"], + "env": { + "ZOTERO_API_KEY": "your-api-key", + "ZOTERO_LIBRARY_ID": "your-user-id", + "ZOTERO_LIBRARY_TYPE": "user", + "UNPAYWALL_EMAIL": "your-email@example.com", + "UNSAFE_OPERATIONS": "all" + } + } + } +} +``` + +##### Codex CLI + +Add to your `~/.codex/config.toml`: + +```toml +[mcp_servers.zotero] +command = "zotero-mcp" +args = ["serve"] +enabled = true + +[mcp_servers.zotero.env] +ZOTERO_API_KEY = "your-api-key" +ZOTERO_LIBRARY_ID = "your-user-id" +ZOTERO_LIBRARY_TYPE = "user" +UNPAYWALL_EMAIL = "your-email@example.com" +UNSAFE_OPERATIONS = "all" +NO_PROXY = "localhost,127.0.0.1" +``` + +##### OpenCode + +Add to your `~/.opencode/opencode.jsonc`: + +```jsonc +{ + "mcp": { + "zotero": { + "type": "local", + "command": ["zotero-mcp", "serve"], + "enabled": true + } + } +} +``` + +Then set environment variables in `~/.zshrc`: + +```bash +# Zotero MCP +export ZOTERO_API_KEY="your-api-key" +export ZOTERO_LIBRARY_ID="your-user-id" +export ZOTERO_LIBRARY_TYPE="user" +export UNPAYWALL_EMAIL="your-email@example.com" +export UNSAFE_OPERATIONS="all" +``` + +#### Environment Variables + +| Variable | Required | Description | +|----------|----------|-------------| +| `ZOTERO_API_KEY` | No for local read-only; Yes for Web/write tools | Your Zotero API key | +| `ZOTERO_LIBRARY_ID` | No for local read-only; Yes for Web/write tools | Your Zotero `User ID` (numeric) for personal libraries | +| `ZOTERO_LIBRARY_TYPE` | Yes | `user` or `group` | +| `UNPAYWALL_EMAIL` | No | Email for Unpaywall PDF search | +| `UNSAFE_OPERATIONS` | No | `items` (delete_items), `all` (delete_collection) | +| `NO_PROXY` | No | Bypass proxy for localhost | + +Notes: +- The minimal local setup is just `command = "zotero-mcp"` plus `args = ["serve"]`. +- Do not leave placeholder values such as `your-api-key`, `your-user-id`, or `your-email@example.com` in your live config. + +#### Available Tools + +| Tool | Purpose | +|------|---------| +| `zotero_get_collections` | List all collections | +| `zotero_get_collection_items` | Get items in a collection | +| `zotero_search_items` | Search library by keyword | +| `zotero_search_by_tag` | Search by tag | +| `zotero_get_item_metadata` | Get item metadata and abstract | +| `zotero_get_item_fulltext` | Read PDF full text | +| `zotero_get_annotations` | Get PDF annotations | +| `zotero_get_notes` | Get notes | +| `zotero_semantic_search` | Semantic search (uses embeddings) | +| `zotero_advanced_search` | Advanced search | +| `zotero_add_items_by_identifier` | Smart paper import from DOI, arXiv, landing pages, or direct PDF URLs; when web upload hits storage quota and Zotero Desktop is running, it can fall back to a local connector copy (`pdf_source=local_zotero_copy`) or reuse an existing local copy (`pdf_source=local_zotero_existing_copy`), exposing `local_item_key=...` when available | +| `zotero_add_items_by_doi` | Import papers by DOI | +| `zotero_add_items_by_arxiv` | Import preprints by arXiv ID | +| `zotero_add_item_by_url` | Save webpage as item | +| `zotero_update_item` | Update item fields | +| `zotero_update_note` | Update note content | +| `zotero_create_collection` | Create collection | +| `zotero_move_items_to_collection` | Move items between collections | +| `zotero_update_collection` | Rename collection | +| `zotero_delete_collection` | Delete collection | +| `zotero_delete_items` | Move items to trash | +| `zotero_find_and_attach_pdfs` | Re-run the source-aware PDF cascade for existing items | +| `zotero_reconcile_collection_duplicates` | Post-import dedupe and collection-level cleanup | +| `zotero_add_linked_url_attachment` | Add linked URL attachment | + +Workflow note: Claude Scholar's current research startup path prefers `zotero_add_items_by_identifier` for import, then `zotero_reconcile_collection_duplicates` as the standard post-import cleanup. Import ledger and local-copy reconcile remain internal diagnostics rather than default public MCP tools. + +### 2. Browser Automation MCP (Optional) + +Used for: Chrome browser control, web page interaction. + +#### Configuration + +```json +{ + "mcpServers": { + "streamable-mcp-server": { + "type": "streamable-http", + "url": "http://127.0.0.1:12306/mcp" + } + } +} +``` + +## Verification + +After configuration, restart your CLI and verify MCP servers are connected: + +``` +# Zotero example: +> List my Zotero collections + +``` + +If the tool responds with your data (for example collections), the setup is complete. + +## Troubleshooting + +| Issue | Solution | +|-------|----------| +| Tools return error | Check API key and library ID are correct | +| PDF attach fails | Ensure `UNPAYWALL_EMAIL` is set | +| Delete operations blocked | Set `UNSAFE_OPERATIONS=items` or `all` | +| HTTP errors | Check `NO_PROXY` includes localhost | +| API rate limit (429) | Batch ≤10 papers at a time, add delays between batches | diff --git a/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.zh-CN.md b/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.zh-CN.md new file mode 100644 index 0000000..7289191 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/MCP_SETUP.zh-CN.md @@ -0,0 +1,194 @@ +# MCP 服务配置指南 + +Claude Scholar 依赖 MCP（Model Context Protocol）服务器提供扩展能力。MCP 服务器**不包含**在本仓库中，用户需自行安装和配置。 + +## 所需 MCP 服务 + +### 1. Zotero MCP（研究工作流） + +**使用场景**: `literature-reviewer` agent、`/research-init`、`/zotero-review`、`/zotero-notes` 命令 + +**安装包**: [Galaxy-Dawn/zotero-mcp](https://github.com/Galaxy-Dawn/zotero-mcp) — 可自动识别本地 Zotero desktop 与 Web API 模式；只有远程访问或写操作时才需要 Web 凭证。 + +#### 功能 + +| 类别 | 工具 | +|------|------| +| **导入** | `zotero_add_items_by_identifier`, `zotero_add_items_by_doi`, `zotero_add_items_by_arxiv`, `zotero_add_item_by_url` | +| **读取** | `zotero_get_collections`, `zotero_get_collection_items`, `zotero_search_items`, `zotero_semantic_search` | +| **更新** | `zotero_update_item`, `zotero_update_note`, `zotero_create_collection`, `zotero_move_items_to_collection`, `zotero_reconcile_collection_duplicates` | +| **删除** | `zotero_delete_items`（移至回收站）, `zotero_delete_collection` | +| **PDF** | `zotero_find_and_attach_pdfs`（基于来源感知的 PDF cascade）, `zotero_add_linked_url_attachment` | + +#### 前置条件 + +1. 如果你希望在没有 Web API 凭证的情况下使用本地只读能力，请安装 [Zotero](https://www.zotero.org/) +2. 如果你要使用写操作或远程 Web API，请打开 [Zotero 设置 -> Security -> Applications](https://www.zotero.org/settings/security#applications) +3. 点击 `Create new private key` 生成 API key +4. 在同一页面按钮下方可以看到 `User ID`，个人库场景下这个数字就是 `ZOTERO_LIBRARY_ID` + +#### 安装 + +```bash +# 通过 uv 安装（推荐） +uv tool install git+https://github.com/Galaxy-Dawn/zotero-mcp.git +``` + +#### 配置 + +选择您的平台： + +##### Claude Code + +Claude Code v2.1.5+：在 `~/.claude.json` 的 `mcpServers` 中添加。 + +更早版本：在 `~/.claude/settings.json` 的 `mcpServers` 中添加： + +```json +{ + "mcpServers": { + "zotero": { + "command": "zotero-mcp", + "args": ["serve"], + "env": { + "ZOTERO_API_KEY": "your-api-key", + "ZOTERO_LIBRARY_ID": "your-user-id", + "ZOTERO_LIBRARY_TYPE": "user", + "UNPAYWALL_EMAIL": "your-email@example.com", + "UNSAFE_OPERATIONS": "all" + } + } + } +} +``` + +##### Codex CLI + +在 `~/.codex/config.toml` 中添加： + +```toml +[mcp_servers.zotero] +command = "zotero-mcp" +args = ["serve"] +enabled = true + +[mcp_servers.zotero.env] +ZOTERO_API_KEY = "your-api-key" +ZOTERO_LIBRARY_ID = "your-user-id" +ZOTERO_LIBRARY_TYPE = "user" +UNPAYWALL_EMAIL = "your-email@example.com" +UNSAFE_OPERATIONS = "all" +NO_PROXY = "localhost,127.0.0.1" +``` + +##### OpenCode + +在 `~/.opencode/opencode.jsonc` 中添加： + +```jsonc +{ + "mcp": { + "zotero": { + "type": "local", + "command": ["zotero-mcp", "serve"], + "enabled": true + } + } +} +``` + +然后在 `~/.zshrc` 中设置环境变量： + +```bash +# Zotero MCP +export ZOTERO_API_KEY="your-api-key" +export ZOTERO_LIBRARY_ID="your-user-id" +export ZOTERO_LIBRARY_TYPE="user" +export UNPAYWALL_EMAIL="your-email@example.com" +export UNSAFE_OPERATIONS="all" +``` + +#### 环境变量 + +| 变量 | 必需 | 说明 | +|------|------|------| +| `ZOTERO_API_KEY` | 本地只读可不填；Web/写操作必填 | 您的 Zotero API 密钥 | +| `ZOTERO_LIBRARY_ID` | 本地只读可不填；Web/写操作必填 | 个人库场景下填写 Zotero 页面显示的 `User ID`（数字） | +| `ZOTERO_LIBRARY_TYPE` | 是 | `user` 或 `group` | +| `UNPAYWALL_EMAIL` | 否 | 用于 Unpaywall PDF 搜索的邮箱 | +| `UNSAFE_OPERATIONS` | 否 | `items`（delete_items）, `all`（delete_collection） | +| `NO_PROXY` | 否 | 绕过本地代理 | + +说明： +- 最小本地配置只需要 `command = "zotero-mcp"` 和 `args = ["serve"]`。 +- 不要把 `your-api-key`、`your-user-id`、`your-email@example.com` 这类占位符直接保留在正式配置里。 + +#### 可用工具 + +| 工具 | 功能 | +|------|------| +| `zotero_get_collections` | 列出所有集合 | +| `zotero_get_collection_items` | 获取集合中的条目 | +| `zotero_search_items` | 按关键词搜索库 | +| `zotero_search_by_tag` | 按标签搜索 | +| `zotero_get_item_metadata` | 获取条目元数据和摘要 | +| `zotero_get_item_fulltext` | 读取 PDF 全文 | +| `zotero_get_annotations` | 获取 PDF 标注 | +| `zotero_get_notes` | 获取笔记 | +| `zotero_semantic_search` | 语义搜索（使用嵌入向量） | +| `zotero_advanced_search` | 高级搜索 | +| `zotero_add_items_by_identifier` | 通过 DOI、arXiv、落地页或直链 PDF 智能导入论文；若 Web 上传撞到存储配额且本地 Zotero Desktop 正在运行，可回退为本地 connector copy（`pdf_source=local_zotero_copy`），或复用已有本地副本（`pdf_source=local_zotero_existing_copy`），并在可用时返回 `local_item_key=...` | +| `zotero_add_items_by_doi` | 通过 DOI 导入论文 | +| `zotero_add_items_by_arxiv` | 通过 arXiv ID 导入预印本 | +| `zotero_add_item_by_url` | 将网页保存为条目 | +| `zotero_update_item` | 更新条目字段 | +| `zotero_update_note` | 更新笔记内容 | +| `zotero_create_collection` | 创建集合 | +| `zotero_move_items_to_collection` | 在集合间移动条目 | +| `zotero_update_collection` | 重命名集合 | +| `zotero_delete_collection` | 删除集合 | +| `zotero_delete_items` | 将条目移至回收站 | +| `zotero_find_and_attach_pdfs` | 为已有条目重新运行来源感知 PDF cascade | +| `zotero_reconcile_collection_duplicates` | 导入后的去重与 collection 级清理 | +| `zotero_add_linked_url_attachment` | 添加链接 URL 附件 | + +工作流说明：Claude Scholar 当前默认使用 `zotero_add_items_by_identifier` 做论文导入，并使用 `zotero_reconcile_collection_duplicates` 作为标准导入后清理步骤。import ledger 与 local-copy reconcile 属于内部诊断能力，不是默认公开 MCP tools。 + +### 2. 浏览器自动化 MCP（可选） + +用途: Chrome 浏览器控制、网页交互。 + +#### 配置 + +```json +{ + "mcpServers": { + "streamable-mcp-server": { + "type": "streamable-http", + "url": "http://127.0.0.1:12306/mcp" + } + } +} +``` + +## 验证 + +配置完成后，重启您的 CLI 并验证 MCP 服务是否连接： + +``` +# Zotero 示例： +> 列出我的 Zotero 集合 + +``` + +如果工具返回了数据（如集合列表），说明配置成功。 + +## 常见问题 + +| 问题 | 解决方案 | +|------|---------| +| 工具返回错误 | 检查 API 密钥和库 ID 是否正确 | +| PDF 附加失败 | 确保已设置 `UNPAYWALL_EMAIL` | +| 删除操作被阻止 | 设置 `UNSAFE_OPERATIONS=items` 或 `all` | +| HTTP 错误 | 检查 `NO_PROXY` 是否包含 localhost | +| API 速率限制 (429) | 每批 ≤10 篇论文，批次间添加延迟 | diff --git a/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.ja-JP.md b/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.ja-JP.md new file mode 100644 index 0000000..5b6a109 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.ja-JP.md @@ -0,0 +1,161 @@ +# Obsidianプロジェクトナレッジベース セットアップ + +Claude Scholarには、Obsidian研究ナレッジベースワークフローが内蔵されています。MCPやAPIキーは不要です。 + +## このワークフローでできること + +Obsidianは単なる論文ライブラリではなく、研究プロジェクトの既定ナレッジレイヤとして扱われます。保存対象は次の通りです。 + +- 安定したプロジェクト背景と研究課題 +- 論文ノートと文献統合 +- 実験 runbook と結果要約 +- 日次研究ログ、scratch notes、同期キュー +- draft、slides、proposal、rebuttal などの執筆資産 +- 主作業面に残し続けるべきでない履歴知識 + +## Requirements + +### Required +- ローカルの Obsidian vault パス +- `OBSIDIAN_VAULT_PATH` を環境変数で設定するか、bootstrap 時に明示的に渡すこと + +### Optional +- ナビゲーション用に Obsidian Desktop をインストールして開いておくこと +- open/search/daily 操作用の `obsidian` CLI +- きれいな `obsidian://` リンクや CLI targeting 用の `OBSIDIAN_VAULT_NAME` + +## 内蔵 skills + +Claude Scholar には project-scoped な Obsidian KB workflow が含まれています。 + +既定ワークフローの中心は次の skills です。 + +- `obsidian-project-kb-core` +- `obsidian-source-ingestion` +- `obsidian-literature-workflow` +- `obsidian-kb-artifacts` +- `defuddle` + +既定ワークフローは `.base`、MCP、API サービスに依存しません。既定で自動保守されるグラフ artifact は `Maps/literature.canvas` のみで、追加の `.base` view や project / experiment canvas は explicit-only です。 + +## 既定の挙動 + +Claude Scholar が `.claude/project-memory/registry.yaml` を含むリポジトリ内で実行されている場合、そのリポジトリを Obsidian プロジェクトナレッジベースにバインド済みとして扱い、既定で更新を行います。 + +まだバインドされていなくても、`.git`、`README.md`、`docs/`、`notes/`、`plan/`、`results/`、`outputs/`、`src/`、`scripts/` などから研究リポジトリらしいと判断できる場合は、自動で bootstrap します。 + +## Vault 内の既定ディレクトリ構成 + +```text +Research/{project-slug}/ + 00-Hub.md + 01-Plan.md + 02-Index.md + Sources/ + Papers/ + Web/ + Docs/ + Data/ + Interviews/ + Notes/ + Knowledge/ + Experiments/ + Results/ + Reports/ + Writing/ + Daily/ + Maps/ + Archive/ + _system/ + registry.md + schema.md + lint-report.md +``` + +よく生成されるファイルは次の通りです。 + +- `02-Index.md` +- `_system/registry.md` +- `_system/schema.md` +- `_system/lint-report.md` +- `.claude/project-memory/{project_id}.md` +- 文献ワークフローで必要な場合の `Maps/literature.canvas` + +## Repo-local binding metadata + +各研究リポジトリは次を持ちます。 + +```text +.claude/project-memory/ + registry.yaml + {project_id}.md +``` + +- `registry.yaml` は repo ↔ vault の binding を保持 +- `{project_id}.md` は assistant-facing な runtime project memory を保持 + +## ノート言語 + +生成・同期ノートの言語は次の優先順位で決まります。 +1. `.claude/project-memory/registry.yaml` の project config +2. 環境変数 `OBSIDIAN_NOTE_LANGUAGE` +3. 既定値 `en` + +注意：`registry.yaml` は repo-local runtime binding file のままです。プロジェクト内で見える source of truth は `_system/registry.md` です。 + +## 主なコマンド + +- `/kb-init` — vault-first の project KB を初期化 +- `/kb-status` — バインド済み KB の状態を要約 +- `/kb-ingest` — 新しい source material を canonical notes にルーティング +- `/kb-log` — 当日の `Daily/` と関連サーフェスを更新 +- `/kb-sync` — 決定論的な KB メンテナンスと再同期を実行 +- `/kb-links` — canonical notes 間の wikilink を修復または強化 +- `/kb-promote` — 安定した内容を canonical note に昇格 +- `/kb-index` — `02-Index.md` を再生成 +- `/kb-lint` — 決定論的な KB 健全性チェックを実行し `_system/lint-report.md` を更新 +- `/kb-archive` — KB オブジェクトを archive、detach、purge、rename する +- `/kb-map` — 既定の literature canvas 以外の artifact を明示要求時に生成 +- `/kb-literature-review` — `Sources/Papers` から文献統合を生成し `Knowledge`、`Writing`、`Maps/literature.canvas` に反映する + +## バインド済み repo の最小メンテナンス面 + +リポジトリが `.claude/project-memory/registry.yaml` で既にバインドされている場合、Claude Scholar は保守を保守的に行います。 + +- 研究状態が変わったら `Daily/YYYY-MM-DD.md` を確認する +- project のトップレベル状態が本当に変わったときだけ `00-Hub.md` を更新する +- project 状態が変わったら `.claude/project-memory/{project_id}.md` を更新する +- `Knowledge/`、`Experiments/`、`Results/`、`Writing/` は毎回自動で書き換えず agent-first を維持する + +## オプション: Obsidian CLI のインストール + +公式 Obsidian CLI は新しいデスクトップインストーラーに内蔵されています。`obsidian ...` を使うには： + +1. CLI 登録をサポートする Obsidian Desktop を使う +2. Obsidian Desktop で `Settings -> General -> Advanced` を開く +3. **Command line interface** を有効にする +4. macOS では `/Applications/Obsidian.app/Contents/MacOS` を `PATH` に追加する（例: `~/.zprofile`） +5. ターミナルを再起動して次で確認する + +```bash +obsidian help +obsidian search query="diffusion" limit=5 +``` + +`Command line interface is not enabled` と出る場合、シェル側の PATH は正しいが Obsidian アプリ内のトグルがまだオフです。 + +## Lifecycle actions + +### Detach +- 自動同期を停止する +- vault 内容は残す +- project memory file も残す + +### Archive +- **note archive** は canonical note を `Research/{project-slug}/Archive/` に移動する +- **project archive** はプロジェクト全体を `Research/_archived/{project-slug}-{date}/` に移動する +- archive は履歴を保持し、project archive では同期も無効化する + +### Purge +- binding、project memory、vault 内の project folder を永久削除する +- 明示的に永久削除を求められた場合のみ使う diff --git a/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.md b/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.md new file mode 100644 index 0000000..d61d837 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.md @@ -0,0 +1,233 @@ +# Obsidian Project Knowledge Base Setup + +Claude Scholar ships with a built-in Obsidian research knowledge-base workflow. It does **not** require MCP or an API key. + +## What this provides + +Obsidian is treated as the default knowledge base for a research project, not just a paper library. A project knowledge base can store: + +- stable project background and research questions +- paper notes and literature syntheses +- experiment runbooks and result summaries +- daily research logs, scratch notes, and sync queues +- writing assets such as drafts, slides, proposals, and rebuttal material +- archived project knowledge that should not stay on the main working surface + +## Requirements + +### Required +- A local Obsidian vault path +- `OBSIDIAN_VAULT_PATH` set in your environment, or passed explicitly when bootstrapping a project + +### Optional +- Obsidian Desktop installed and open for navigation +- `obsidian` CLI available for open/search/daily actions +- `OBSIDIAN_VAULT_NAME` for cleaner `obsidian://` links and CLI targeting + +## Built-in skills + +Claude Scholar includes a project-scoped Obsidian KB workflow. + +Most relevant for the default workflow: + +- `obsidian-project-kb-core` +- `obsidian-source-ingestion` +- `obsidian-literature-workflow` +- `obsidian-kb-artifacts` +- `defuddle` + +Some optional graph-oriented helpers may still exist in the repo, but the default workflow does **not** depend on `.base`, MCP, or API services. The main default graph artifact is `Maps/literature.canvas`; additional `.base` views or project/experiment canvases are explicit-only. + +## Default behavior + +When Claude Scholar is running inside a repository that contains `.claude/project-memory/registry.yaml`, it should treat the repository as bound to an Obsidian project knowledge base and update it by default. + +If the repository is not yet bound, but it looks like a research project (for example it contains `.git`, `README.md`, `docs/`, `notes/`, `plan/`, `results/`, `outputs/`, `src/`, or `scripts/`), Claude Scholar should bootstrap a project knowledge base automatically. + +## Project structure in the vault + +```text +Research/{project-slug}/ + 00-Hub.md + 01-Plan.md + 02-Index.md + Sources/ + Papers/ + Web/ + Docs/ + Data/ + Interviews/ + Notes/ + Knowledge/ + Experiments/ + Results/ + Reports/ + Writing/ + Daily/ + Maps/ + Archive/ + _system/ + registry.md + schema.md + lint-report.md +``` + +Key generated files commonly include: + +- `02-Index.md` +- `_system/registry.md` +- `_system/schema.md` +- `_system/lint-report.md` +- `.claude/project-memory/{project_id}.md` +- `Maps/literature.canvas` when literature workflow needs it + +## Repository-local memory binding + +Each research repo gets a local binding under: + +```text +.claude/project-memory/ + registry.yaml + {project_id}.md +``` + +- `registry.yaml` stores the repo ↔ vault binding +- `{project_id}.md` stores the assistant-facing project memory for incremental syncs + +## Note language + +Generated and synced notes resolve their language with this priority: +1. project config in `.claude/project-memory/registry.yaml` +2. environment variable `OBSIDIAN_NOTE_LANGUAGE` +3. default `en` + +Note: `registry.yaml` remains a repo-local runtime binding file. The visible project source of truth stays in `_system/registry.md`. + +Supported values: +- `en` +- `zh-CN` + +Per-project example: + +```json +{ + "projects": { + "my-project": { + "project_id": "my-project", + "vault_root": "/path/to/vault/Research/my-project", + "note_language": "zh-CN" + } + } +} +``` + +Existing English and Chinese headings remain compatible during sync, so changing the configured language does not break older notes. + +## Main commands + +- `/kb-init` — initialize the vault-first project KB +- `/kb-status` — summarize the bound KB state +- `/kb-ingest` — route new source material into canonical notes +- `/kb-log` — update the current Daily note and related project surfaces +- `/kb-sync` — run deterministic KB maintenance and resync project surfaces +- `/kb-links` — repair or strengthen wikilinks among canonical notes +- `/kb-promote` — promote durable content into canonical notes +- `/kb-index` — rebuild `02-Index.md` +- `/kb-lint` — run deterministic KB health checks and rewrite `_system/lint-report.md` +- `/kb-archive` — archive, detach, purge, or rename KB objects +- `/kb-map` — generate explicit-only artifact outputs beyond the default literature canvas +- `/kb-literature-review` — synthesize literature from `Sources/Papers` into `Knowledge`, `Writing`, and `Maps/literature.canvas` + +## Minimum bound-repo maintenance + +When a repo is already bound through `.claude/project-memory/registry.yaml`, Claude Scholar should keep automatic maintenance conservative: + +- always verify `Daily/YYYY-MM-DD.md` when the turn changes research state, +- update `00-Hub.md` only when top-level project status actually changes, +- update `.claude/project-memory/{project_id}.md` whenever project state changes, +- keep `Knowledge/`, `Experiments/`, `Results/`, and `Writing/` agent-first rather than automatically rewriting them every turn. + +## Optional Obsidian CLI installation + +The official Obsidian CLI is built into newer desktop installers. To use `obsidian ...` commands: + +1. Use an Obsidian desktop build that supports CLI registration. +2. In Obsidian Desktop, open `Settings -> General -> Advanced`. +3. Turn on **Command line interface**. +4. Ensure `/Applications/Obsidian.app/Contents/MacOS` is on your `PATH` on macOS (for example via `~/.zprofile`). +5. Restart your terminal, then verify: + +```bash +obsidian help +obsidian search query="diffusion" limit=5 +``` + +If you see `Command line interface is not enabled`, the shell path is fine but the Obsidian in-app toggle is still off. + +## Lifecycle actions + +### Detach +- stop automatic syncing +- keep vault content +- keep project memory file + +### Archive +- **note archive** moves a canonical note into `Research/{project-slug}/Archive/` +- **project archive** moves the whole project into `Research/_archived/{project-slug}-{date}/` +- archive keeps history and disables syncing for project-level archive + +### Purge +- permanently delete the binding, project memory, and vault project folder +- only use when the user explicitly asks for permanent deletion + +## Optional CLI and URI usage + +Claude Scholar can optionally use the official Obsidian CLI and URI scheme: + +- CLI docs: +- URI docs: + +Examples: + +```bash +obsidian help +obsidian search query="diffusion" limit=10 +obsidian daily:append content="- [ ] Follow up on experiment" +``` + +```text +obsidian://open?vault=My%20Vault&file=Research%2Fproject-slug%2F00-Hub +obsidian://search?vault=My%20Vault&query=%23experiment +``` + +## Troubleshooting + +| Issue | Solution | +|-------|----------| +| Bootstrap fails with missing vault path | Set `OBSIDIAN_VAULT_PATH` or pass a vault path explicitly | +| Project keeps re-importing | Check `.claude/project-memory/registry.yaml` exists and points to the correct repo root | +| The vault still shows older topologies | Those are from older docs or older project generations; the current default workflow uses the structure above and only keeps `Maps/literature.canvas` by default | +| CLI commands fail | Check that `Settings -> General -> Advanced -> Command line interface` is enabled; otherwise continue with filesystem-only sync | +| “Remove project knowledge” is too destructive | Use archive or detach; purge is only for permanent deletion | + +## WSL -> Windows mirror workflow + +If you run Claude Scholar inside WSL but prefer opening Obsidian through native Windows for more stable window behavior, use a two-copy setup: + +- keep the WSL vault as the source of truth (for example `/obsidian-vault`) +- keep a Windows-local mirror directory mounted in WSL (for example ``) +- open the mirrored Windows-local directory in Windows Obsidian + +Sync with: + +```bash +bash scripts/sync_obsidian_to_windows.sh --windows-path +``` + +Preview first if needed: + +```bash +bash scripts/sync_obsidian_to_windows.sh --windows-path --dry-run +``` + +By default the sync deletes mirror-only files that no longer exist in the WSL source. Add `--no-delete` if you want to keep extra files in the Windows mirror. diff --git a/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.zh-CN.md b/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.zh-CN.md new file mode 100644 index 0000000..c74bd6d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/OBSIDIAN_SETUP.zh-CN.md @@ -0,0 +1,182 @@ +# Obsidian 项目知识库配置指南 + +Claude Scholar 内置了 Obsidian 研究知识库工作流，不需要 MCP，也不需要 API key。 + +## 这套工作流提供什么 + +Obsidian 在这里不是单纯的论文库，而是研究项目的默认知识层，可以统一沉淀： + +- 稳定的项目背景与研究问题 +- 论文笔记与文献综合 +- 实验 runbook 与结果总结 +- 每日研究日志、scratch notes 与同步队列 +- 草稿、slides、proposal、rebuttal 等写作资产 +- 不应继续留在主工作面的历史知识 + +## Requirements + +### Required +- 一个本地 Obsidian vault 路径 +- 通过环境变量设置 `OBSIDIAN_VAULT_PATH`，或在 bootstrap 时显式传入 + +### Optional +- 安装并打开 Obsidian Desktop，便于跳转与查看 +- 可用的 `obsidian` CLI，用于 open/search/daily 等辅助操作 +- `OBSIDIAN_VAULT_NAME`，便于生成更干净的 `obsidian://` 链接和 CLI targeting + +## 内置 skills + +Claude Scholar 内置了面向项目作用域的 Obsidian KB 工作流。 + +默认主线最相关的是： + +- `obsidian-project-kb-core` +- `obsidian-source-ingestion` +- `obsidian-literature-workflow` +- `obsidian-kb-artifacts` +- `defuddle` + +默认工作流不依赖 `.base`、MCP 或 API 服务。默认自动维护的图谱产物只有 `Maps/literature.canvas`；其他 `.base` 视图或项目/实验 canvas 都是 explicit-only。 + +## 默认行为 + +当 Claude Scholar 运行在一个包含 `.claude/project-memory/registry.yaml` 的仓库里时，应默认把这个仓库视为已经绑定到 Obsidian 项目知识库，并在任务过程中自动维护它。 + +如果仓库还没有绑定，但看起来像研究项目（例如包含 `.git`、`README.md`、`docs/`、`notes/`、`plan/`、`results/`、`outputs/`、`src/` 或 `scripts/`），Claude Scholar 应自动 bootstrap 一个项目知识库。 + +## Vault 中的默认目录结构 + +```text +Research/{project-slug}/ + 00-Hub.md + 01-Plan.md + 02-Index.md + Sources/ + Papers/ + Web/ + Docs/ + Data/ + Interviews/ + Notes/ + Knowledge/ + Experiments/ + Results/ + Reports/ + Writing/ + Daily/ + Maps/ + Archive/ + _system/ + registry.md + schema.md + lint-report.md +``` + +常见生成文件包括： + +- `02-Index.md` +- `_system/registry.md` +- `_system/schema.md` +- `_system/lint-report.md` +- `.claude/project-memory/{project_id}.md` +- 文献工作流需要时生成 `Maps/literature.canvas` + +## Repo-local binding metadata + +每个研究仓库都会在本地维护： + +```text +.claude/project-memory/ + registry.yaml + {project_id}.md +``` + +- `registry.yaml` 存 repo ↔ vault 的绑定关系 +- `{project_id}.md` 存 assistant-facing 的运行时项目记忆 + +## 笔记语言 + +生成和同步笔记时，语言按以下优先级解析： +1. `.claude/project-memory/registry.yaml` 中的项目配置 +2. 环境变量 `OBSIDIAN_NOTE_LANGUAGE` +3. 默认 `en` + +注意：`registry.yaml` 仍然只是 repo-local runtime binding 文件。项目内真正可见的 source of truth 仍然是 `_system/registry.md`。 + +支持的值： +- `en` +- `zh-CN` + +## 主命令 + +- `/kb-init` — 初始化 vault-first 项目知识库 +- `/kb-status` — 汇总当前已绑定 KB 的状态 +- `/kb-ingest` — 将新的 source material 路由到 canonical notes +- `/kb-log` — 更新当天 `Daily/` 和相关项目表面 +- `/kb-sync` — 运行确定性的 KB 维护并重同步项目表面 +- `/kb-links` — 修复或增强 canonical notes 之间的 wikilink +- `/kb-promote` — 将稳定内容提升为 canonical note +- `/kb-index` — 重建 `02-Index.md` +- `/kb-lint` — 运行确定性的 KB 健康检查并重写 `_system/lint-report.md` +- `/kb-archive` — 归档、detach、purge 或重命名 KB 对象 +- `/kb-map` — 在默认 literature canvas 之外按需生成 artifact +- `/kb-literature-review` — 从 `Sources/Papers` 合成文献并写入 `Knowledge`、`Writing`、`Maps/literature.canvas` + +## 已绑定仓库的最小维护面 + +当仓库已经通过 `.claude/project-memory/registry.yaml` 绑定时，Claude Scholar 应保持保守维护： + +- 只要研究状态发生变化，就检查 `Daily/YYYY-MM-DD.md` +- 只有项目顶层状态真正变化时才更新 `00-Hub.md` +- 只要项目状态变化，就更新 `.claude/project-memory/{project_id}.md` +- `Knowledge/`、`Experiments/`、`Results/`、`Writing/` 默认保持 agent-first，而不是每轮都自动重写 + +## 可选的 Obsidian CLI 安装 + +官方 Obsidian CLI 是内置在较新的桌面版安装器里的。要使用 `obsidian ...` 命令： + +1. 使用支持 CLI 注册的 Obsidian Desktop 版本。 +2. 在 Obsidian Desktop 中打开 `Settings -> General -> Advanced`。 +3. 打开 **Command line interface**。 +4. 在 macOS 上确保 `/Applications/Obsidian.app/Contents/MacOS` 已加入 `PATH`（例如写入 `~/.zprofile`）。 +5. 重启终端后验证： + +```bash +obsidian help +obsidian search query="diffusion" limit=5 +``` + +如果提示 `Command line interface is not enabled`，通常说明 shell 路径已经配置好，但 Obsidian 应用内的开关还没打开。 + +## Lifecycle actions + +### Detach +- 停止自动同步 +- 保留 vault 内容 +- 保留 project memory 文件 + +### Archive +- **note archive**：把 canonical note 移到 `Research/{project-slug}/Archive/` +- **project archive**：把整个项目移到 `Research/_archived/{project-slug}-{date}/` +- archive 会保留历史记录；project archive 会同时禁用同步 + +### Purge +- 永久删除 binding、project memory 和 vault 中的项目目录 +- 只有在用户明确要求永久删除时才使用 + +## 可选的 CLI 与 URI 用法 + +Claude Scholar 可选使用官方 Obsidian CLI 与 URI： + +- CLI 文档： +- URI 文档： + +## Troubleshooting + +| 问题 | 解决方式 | +|------|----------| +| Bootstrap 缺少 vault path | 设置 `OBSIDIAN_VAULT_PATH` 或显式传入 vault path | +| 项目反复重新导入 | 检查 `.claude/project-memory/registry.yaml` 是否存在且 repo root 正确 | +| vault 里仍出现旧目录拓扑 | 那通常来自旧文档或旧项目生成；当前默认结构以上述目录为准，默认只自动维护 `Maps/literature.canvas` | +| CLI 命令失败 | 检查 `Settings -> General -> Advanced -> Command line interface` 是否已打开；否则继续使用 filesystem-only sync | +| “删除项目知识” 看起来过于危险 | 优先使用 archive 或 detach；purge 仅用于永久删除 | diff --git a/文档润色流和知识库构建流/claude-scholar/README.ja-JP.md b/文档润色流和知识库构建流/claude-scholar/README.ja-JP.md new file mode 100644 index 0000000..5c4e2ea --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/README.ja-JP.md @@ -0,0 +1,660 @@ +

    + Claude Scholar Logo + +

    + Stars + GitCode Stars + Forks + Last Commit + License +

    + +

    + + + Kimi Open Source Friends + +

    + + 言語: English | 中文 | 日本語 +

    対応プラットフォーム: Claude Code | Codex CLI | Kimi Code CLI | OpenCode

    + +
    + +> 学術研究とソフトウェア開発のための半自動リサーチアシスタント。特にコンピュータサイエンスおよびAI研究者向け。[Claude Code](https://github.com/anthropics/claude-code)、[Codex CLI](https://github.com/openai/codex)、[Kimi Code CLI](https://github.com/MoonshotAI/kimi-code)、[OpenCode](https://github.com/opencode-ai/opencode)をサポートし、文献レビュー、コーディング、実験、レポート作成、論文執筆、プロジェクトナレッジ管理に対応。 + +

    ブランチについて: mainブランチはClaude Codeワークフロー用です。Codex CLIをご利用の場合はcodexブランチを、Kimi Code CLIをご利用の場合はkimiブランチを、OpenCodeをご利用の場合はopencodeブランチをご参照ください。

    + +## 最新ニュース + +- **2026-06-03**: **Kimi Code CLI ブランチを追加し、Kimi からの力強い支援に感謝** — `kimi` ブランチを Claude Scholar の Kimi Code CLI 版として追加しました。本プロジェクトへの Kimi チームの継続的で力強い支援に感謝します。 +- **2026-05-14**: **`expression-skill` を中核のコミュニケーション層に据え、`planning-with-files` を既定の永続 planning 層として戻し、Nature 執筆スタックも拡張** — [`expression-skill`](./skills/expression-skill/README.md) を、報告・計画・ファイル操作・多段の技術作業における結論先行の表現規律として明示しました。さらに [`planning-with-files`](./skills/planning-with-files/SKILL.md) を、複雑な作業で `task_plan.md` / `notes.md` を使う既定の on-disk planning / progress-tracking workflow として再導入しました。あわせて、章構成の起草と論証構築向けに [`nature-writing`](./skills/nature-writing/README.md) を導入し、[`nature-polishing`](./skills/nature-polishing/README.md) を上流の最新 article-pattern 版へ更新し、[`nature-response`](./skills/nature-response/README.md) と [`nature-data`](./skills/nature-data/README.md) も journal-writing スタックに維持しています。 +- **2026-05-13**: **根拠ゲート付き研究ワークフローと `Sources/Papers` ルーティングを整理** — Evidence Records、claim strength、Claim Promotion Gate を共有する `research-contract.md` を追加しました。研究アイデア出し、Zotero 取り込み、文献統合、結果レポート、論文執筆、rebuttal ワークフローを同じ根拠契約に接続し、プロジェクトの論文ソースノートはまず `Sources/Papers` に置き、根拠ゲートを通った主張だけを `Knowledge` や `Writing` へ進める方針を明確にしました。 +- **2026-04-24**: **プロジェクト単位の Obsidian KB ワークフローを統合** — Obsidian のプロジェクト知識管理を vault 中心のワークフローとして再構成し、重複していた記憶系スキルを 4 つの中核スキルに統合しました。リポジトリ内のプロジェクト紐付けメタデータは実行時レイヤーとして残し、プロジェクトナビゲーションは機械向けの登録表ではなく、人間が読みやすい形にしました。 +- **2026-04-22**: **軽量なコア指示、既定 agent の整理、安全なインストール管理、汎用的な論文発見フロー** — 常時読み込まれる大きな `CLAUDE.md` / `AGENTS.md` をコンパクトなコア指示に置き換え、既定 agent 集合を主経路に必要なものへ整理し、インストール状態に基づく安全なアンインストールを追加しました。`daily-paper-generator` は汎用トピック向けの arXiv / bioRxiv 検索と Top 10 -> Top 3 -> Top 1 の固定選定フローへ拡張し。 +- **2026-04-15**: **pubfig と pubtab という 2 つの Python パッケージを導入** — [`pubfig`](https://github.com/Galaxy-Dawn/pubfig) を論文品質の科学図向け、[`pubtab`](https://github.com/Galaxy-Dawn/pubtab) を発表可能な表と Excel↔LaTeX 変換向けの Python パッケージとして打ち出し、論文図、ベンチマーク表、書き出し制御、最終 QA までの生産経路をより明確にしました。 + +
    +過去の更新履歴を表示 + +- **2026-04-15**: **[`publication-chart-skill`](./skills/publication-chart-skill/SKILL.md) を Claude Scholar に統合** — [`pubfig`](https://github.com/Galaxy-Dawn/pubfig) + [`pubtab`](https://github.com/Galaxy-Dawn/pubtab) を [`publication-chart-skill`](./skills/publication-chart-skill/SKILL.md) としてまとめてリポジトリに追加し、Claude Scholar の分析/執筆スタックの境界に接続しました。これにより、論文品質の図表作業を汎用分析や文章作成スキルに混ぜず、明示的な引き渡し経路で扱えるようになりました。 +- **2026-03-31**: **Zotero smart-importワークフロー文書を整合** — 最新の`zotero-mcp`公開インターフェースに合わせて、Claude Scholarの研究向けドキュメントを更新しました。`zotero_add_items_by_identifier`を標準の論文インポート経路として明示し、`zotero_reconcile_collection_duplicates`を標準的なインポート後クリーンアップ手順に位置づけ、source-awareなPDF cascadeの挙動もより正確に説明し直しました。公開機能と内部診断機能の境界も整理しています。 +- **2026-03-31**: **READMEの導入案内を刷新** — Claude Scholarが特にコンピュータサイエンスおよびAI研究者に適していることを明確にし、インストール後すぐ使える実践的な導入シナリオを追加しました。前提条件やブランチ案内も整理し、「既存のローカルmdファイルは手動で統合する必要がある」点をより明確にしました。 +- **2026-03-31**: **インストーラーとhooksの挙動を整理** — インストーラーは既存のローカル`CLAUDE.md`を保持しつつ、リポジトリ版を`CLAUDE.scholar.md`として追加するようになりました。あわせて、デフォルトhooksの要約出力も整理し、temp filesやuncommitted filesのノイズを抑えつつ、より安全な書き込みガードは維持しています。 +- **2026-03-31**: **日本語ドキュメントを追加** — メインREADMEに加え、`AGENTS`、`MCP_SETUP`、`OBSIDIAN_SETUP`の日本語版も追加し、OpenCodeブランチ全体の多言語ドキュメント導線をより充実させました。 + +- **2026-02-25**: **Codex CLI** サポート — `codex` 分岐を追加し、[OpenAI Codex CLI](https://github.com/openai/codex) をサポート。config.toml、40 個の skills、14 個の agents、sandbox 安全機構を含む +- **2026-02-23**: `setup.sh` インストーラー追加 — 既存 `~/.opencode` 向けのバックアップ付き増分更新、`opencode.jsonc` の自動バックアップ、`agent/mcp/permission/plugin` の追加統合に対応 +- **2026-02-21**: **OpenCode** サポート — Claude Scholar は [OpenCode](https://github.com/opencode-ai/opencode) を代替 CLI としてサポート。互換設定は `opencode` 分岐で提供 +- **2026-02-20**: バイリンガル文書 — 英文と中文の入口文書を整備し、異なる読者層が読みやすいよう改善 +- **2026-02-15**: Zotero MCP 統合 — `/zotero-review` と `/zotero-notes` を追加し、`research-ideation` skill に Zotero ガイドを追加、`literature-reviewer` agent を Zotero MCP 対応へ強化 +- **2026-02-14**: Hooks 最適化 — `security-guard` を二層化し、`skill-forced-eval` を 6 分類 + 静音スキャンへ変更、`session-start` を上位 5 件表示に制限、`session-summary` に 30 日ログ自動清理を追加、`stop-summary` で追加/変更/削除を分離表示 +- **2026-02-11**: 大型アップデート — 10 個の skills、7 個の agents、8 個の研究ワークフロー command、2 個の新ルールを追加し、主設定文書を再構成 +- **2026-01-26**: すべての Hooks をクロスプラットフォーム Node.js 版へ書き換え、README を全面更新、ML 論文執筆知識ベースを拡張 +- **2026-01-25**: プロジェクト正式公開、v1.0.0 リリース + +
    + +## クイックナビゲーション + +| セクション | 内容 | +|---|---| +| [Claude Scholarとは](#claude-scholarとは) | プロジェクトの位置づけとターゲットユースケース | +| [コアワークフロー](#コアワークフロー) | アイデア創出から出版までのエンドツーエンド研究パイプライン | +| [クイックスタート](#クイックスタート) | フル、ミニマル、選択的、プラグインマーケットプレイス経由のインストール | +| [使い始めのシナリオ](#使い始めのシナリオ) | インストール後の代表的な使い始め方を見る | +| [連携ツール](#連携ツール) | ZoteroとObsidianのワークフロー統合 | +| [主要ワークフロー](#主要ワークフロー) | 研究・開発の主要ワークフロー一覧 | +| [サポートワークフロー](#サポートワークフロー) | 主要ワークフローを支えるバックグラウンドシステム | +| [ドキュメント](#ドキュメント) | セットアップ、設定、テンプレートへのリンク | +| [引用](#引用) | 論文やレポートでのClaude Scholarの引用方法 | + +## Claude Scholarとは + +Claude Scholarは、研究者を置き換えようとするエンドツーエンドの自律研究システムでは**ありません**。 + +コアとなるアイデアはシンプルです: + +> **意思決定の中心は人間に置き、アシスタントはその周辺のワークフローを加速する。** + +つまりClaude Scholarは、研究の中で繰り返し発生する重い作業や構造に敏感な作業 — 文献整理、ノートテイキング、実験分析、レポート作成、ライティング支援 — を支援するよう設計されていますが、重要な判断は常に人間の手に委ねられます: + +- どの問題が追求に値するか +- どの論文が本当に重要か +- どの仮説をテストすべきか +- どの結果が説得力があるか +- 何を書き、投稿し、あるいは断念すべきか + +言い換えれば、Claude Scholarは**半自動リサーチアシスタント**であり、「完全自動化された科学者」ではありません。 + +## 対象ユーザー + +Claude Scholarは特に以下のような方に適しています: + +- 文献レビュー、コーディング、実験、論文執筆を行き来する**コンピュータサイエンス研究者** +- アイデア創出、実装、分析、レポート作成、リバッタルまで一つのアシスタントワークフローが必要な**AI/ML研究者** +- 人間の判断を手放さずにワークフローの構造を強化したい**研究エンジニアや大学院生** +- Zotero、Obsidian、CLIオートメーション、再現可能なプロジェクトメモリの恩恵を受ける**ソフトウェア中心の学術プロジェクト** + +他の研究分野でも利用できますが、現在のワークフロー設計はコンピュータサイエンス、AI、および隣接する計算研究に最適化されています。 + +## コアワークフロー + +- **アイデア創出**: 漠然としたトピックを具体的な研究課題、研究ギャップ、初期計画に変換 +- **文献**: Zoteroコレクションを通じて論文を検索、インポート、整理、読解 +- **論文ノート**: 論文を構造化されたリーディングノートと再利用可能な知見に変換 +- **ナレッジベース**: `Sources / Knowledge / Experiments / Results / Results/Reports / Writing / Daily / Maps`にわたる永続的な知識をObsidianにルーティング +- **実験**: 仮説、実験ライン、実行履歴、知見、次のアクションを追跡 +- **分析**: `results-analysis`で厳密な統計、科学的図表、分析アーティファクトを生成 +- **レポート**: `results-report`で実験後の完全なレポートを作成し、Obsidianに書き戻し +- **執筆と出版**: 安定した知見をレビュー、論文、リバッタル、スライド、ポスター、プロモーションに展開 + +## クイックスタート + +### 前提条件 + +- [Claude Code](https://github.com/anthropics/claude-code) +- Git +- (任意) Python + [uv](https://docs.astral.sh/uv/) — Python開発用 +- (任意) [Zotero](https://www.zotero.org/) + [Galaxy-Dawn/zotero-mcp](https://github.com/Galaxy-Dawn/zotero-mcp) — 文献ワークフロー用 +- (任意) [Obsidian](https://obsidian.md/) — プロジェクトナレッジベースワークフロー用 + +### オプション1: フルインストール（推奨） + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +bash /tmp/claude-scholar/scripts/setup.sh +``` + +**Windows**: インストーラーの実行にはGit BashまたはWSLをご使用ください。 + +インストーラーは**バックアップ対応かつインクリメンタルアップデートに対応**しています: +- リポジトリ管理の`skills/commands/agents/rules/hooks/scripts/CLAUDE*.md`を更新 +- 上書きされるファイルを`~/.claude/.claude-scholar-backups//`にバックアップ +- `settings.json`を`settings.json.bak`にバックアップ +- 既存の`~/.claude/CLAUDE.md`を保持し、リポジトリ版を`~/.claude/CLAUDE.scholar.md`としてインストール +- 既存の`~/.claude/CLAUDE.zh-CN.md`を保持し、リポジトリ版を`~/.claude/CLAUDE.zh-CN.scholar.md`としてインストール +- 既存の`env`、モデル/プロバイダー設定、APIキー、パーミッション、現在の`mcpServers`値を保持 +- 既存のフックセットを置き換えるのではなく、不足しているフックエントリを追加 + +**CLAUDEに関する重要事項**: 既に独自の`~/.claude/CLAUDE.md`や`~/.claude/CLAUDE.zh-CN.md`をお持ちの場合、インストール後に`~/.claude/CLAUDE.scholar.md`と`~/.claude/CLAUDE.zh-CN.scholar.md`を確認し、必要なClaude Scholarのセクションを手動で統合してください。別名で配置された補助ファイルは自動的には適用されません。 + +アップデート方法: + +```bash +cd /tmp/claude-scholar +git pull --ff-only +bash scripts/setup.sh +``` + +アンインストールする場合: + +```bash +cd /tmp/claude-scholar +bash scripts/uninstall.sh +``` + +インストーラーは次のファイルも書き込みます: +- `~/.claude/.claude-scholar-manifest.txt`: Claude Scholar が実際に管理するファイル一覧 +- `~/.claude/.claude-scholar-install-state`: 安全なアンインストールに使う ownership メタデータ + +アンインストーラーは install state に記録されたファイルと settings エントリだけを削除し、現在のリポジトリ内容から所有権を推測しません。 + +### オプション2: ミニマルインストール + +研究にフォーカスした最小限のサブセットのみをインストール: + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +mkdir -p ~/.claude/hooks ~/.claude/skills +cp /tmp/claude-scholar/hooks/*.js ~/.claude/hooks/ +cp -r /tmp/claude-scholar/skills/ml-paper-writing ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/research-ideation ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/results-analysis ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/results-report ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/review-response ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/writing-anti-ai ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/git-workflow ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/bug-detective ~/.claude/skills/ +``` + +**インストール後**: ミニマル/手動インストールでは`settings.json`の自動統合は行われません。`settings.json.template`から必要なhooksやMCPエントリのみをコピーしてください。既に独自の`~/.claude/CLAUDE.md`や`~/.claude/CLAUDE.zh-CN.md`をお持ちの場合は、上書きせずにこのリポジトリのCLAUDEファイルから関連セクションを統合してください。 + +### オプション3: 選択的インストール + +必要な部分のみをコピー: + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +cd /tmp/claude-scholar + +cp hooks/*.js ~/.claude/hooks/ +cp -r skills/latex-conference-template-organizer ~/.claude/skills/ +cp -r skills/architecture-design ~/.claude/skills/ +cp agents/paper-miner.md ~/.claude/agents/ +cp rules/coding-style.md ~/.claude/rules/ +cp rules/agents.md ~/.claude/rules/ +``` + +**インストール後**: 選択的/手動インストールでは`settings.json`の自動統合は行われません。`settings.json.template`から実際に必要なhooksやMCPエントリのみをコピーしてください。既に独自の`~/.claude/CLAUDE.md`や`~/.claude/CLAUDE.zh-CN.md`をお持ちの場合は、上書きせずに関連セクションを統合してください。 + +### オプション4: プラグインマーケットプレイス経由のインストール + +**ステップ1: プラグインをインストール** + +```bash +/plugin marketplace add Galaxy-Dawn/claude-scholar +/plugin install claude-scholar@claude-scholar +``` + +これにより、skills、commands、agents、hooks が自動で読み込まれます。インストール時に、適用範囲として user（全プロジェクト）または project（単一プロジェクト）を選択できます。 + +**ステップ2: ルールをインストール（必須）** + +Claude Code のプラグインは rules を自動配布できないため、手動で追加してください: + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar + +# ユーザー全体（全プロジェクト） +mkdir -p ~/.claude/rules +cp /tmp/claude-scholar/rules/*.md ~/.claude/rules/ + +# あるいはプロジェクト単位（現在のプロジェクトのみ） +mkdir -p .claude/rules +cp /tmp/claude-scholar/rules/*.md .claude/rules/ +``` + +**インストール後**: プラグインインストールでは `CLAUDE.md` の自動読み込みや `settings.json` の自動設定は行われません。既に独自の `~/.claude/CLAUDE.md` や `~/.claude/CLAUDE.zh-CN.md` をお持ちの場合は、プラグインが自動適用すると考えず、Claude Scholar 側の関連セクションを手動で統合してください。Zotero MCP などの連携が必要な場合は、[連携ツール](#連携ツール) セクションを参照してください。 + +## 使い始めのシナリオ + +インストール後は、システム全体を先に覚えようとするよりも、自然言語で今やりたいことをそのまま伝えるのがいちばん簡単です。ここでは、最初の一歩として使いやすい代表的なシナリオをいくつか挙げます。 + +### 1. 新しい研究テーマを立ち上げる +**たとえばこう言えます:** +> [あなたの研究テーマ]について研究を始めたいです。文献に基づいた初期プラン、重要な未解決問題、次にやるべき具体的なステップを整理してください。 + +**Claude Scholarがよく支援する内容:** +- テーマを明確化して研究課題を絞り込む +- 優先して見るべき文献の方向を整理する +- 初期計画や仮説候補をまとめる +- 必要ならZoteroやObsidianにも流し込む + +### 2. Zotero文献コレクションをレビューする +**たとえばこう言えます:** +> Zoteroにある brain foundation models 関連の文献コレクションをレビューして、主な流れ、研究ギャップ、次に有望な方向をまとめてください。 + +**典型的な出力:** +- テーマ別の論文整理 +- 簡潔な文献総括 +- ギャップ分析 +- 次に掘る価値のある研究方向 + +### 3. 完了した実験結果を分析する +**たとえばこう言えます:** +> この実験フォルダの結果を分析して、各runで何が変わったのかを確認し、意思決定に使える要約を書いてください。 + +**典型的な出力:** +- 指標比較 +- アブレーションやエラー分析の提案 +- 何が堅い結論で、何がまだ弱く、次に何を走らせるべきかを整理した結果要約 + +### 4. 論文の節やrebuttal草稿を書く +**たとえばこう言えます:** +> このプロジェクトの現時点の知見と論文メモに基づいて、関連研究の節の草稿を書いてください。 + +または: + +> これらの査読コメントに対するrebuttal草稿を手伝ってください。 + +**典型的な出力:** +- 構造化された節ドラフト +- より明確な論理展開 +- 主張と根拠の対応整理 +- 追加で検証や補強が必要な論点 + +### 実用上のメモ +- 最初は「全部やって」ではなく、具体的な一つのタスクから始めるのがおすすめです。 +- すでに自分用のローカル`CLAUDE.md`を運用している場合は、Claude Scholarの必要な内容を手動で統合してください。別名で配置されたファイルが自動適用されるわけではありません。 +- ZoteroとObsidianは必須ではありませんが、単発のチャット出力ではなく、継続的な文献ノートやプロジェクトメモリを残したい場合にはかなり有用です。 + +## プラットフォームサポート + +Claude Scholarは以下のプラットフォームをサポートしています: + +- **Claude Code** — 主要なインストール対象 +- **Codex CLI** — サポートされたワークフローとドキュメントがこのリポジトリエコシステムで利用可能 +- **OpenCode** — 代替CLIワークフローとしてサポート + +トップレベルのワークフローは共通: 研究、コーディング、実験、レポート作成、プロジェクトナレッジ管理。 + +## 連携ツール + +### Zotero + +以下の用途でClaude ScholarにZoteroを連携できます: +- DOI / arXiv / URLによる論文インポート +- コレクションベースのリーディングワークフロー +- Zotero MCPを通じたフルテキストアクセス +- 詳細な論文ノートと文献合成 + +詳細は [MCP_SETUP.ja-JP.md](./MCP_SETUP.ja-JP.md) を参照。 + +### Obsidian + +ファイルシステムファーストの研究ナレッジベースとしてObsidianを利用できます: +- `Sources/` +- `Knowledge/` +- `Experiments/` +- `Results/` +- `Results/Reports/` +- `Writing/` +- `Daily/` +- `Maps/` + +詳細は [OBSIDIAN_SETUP.ja-JP.md](./OBSIDIAN_SETUP.ja-JP.md) を参照。 + +## 主要ワークフロー + +アイデアから出版まで — 7段階の学術研究ライフサイクル。 + +### 1. リサーチアイデア創出（Zotero連携） + +アイデア生成から文献管理までのエンドツーエンド研究スタートアップ。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `research-ideation` | 漠然としたトピックを構造化された研究課題、ギャップ分析、初期研究計画に変換 | +| Agent | `literature-reviewer` | 論文を検索、分類、合成し、実用的な文献全体像を構築 | +| Command | `/research-init` | 文献検索、Zotero整理、研究質問カードを開始し、根拠ゲートを通った場合のみ提案書草稿を生成 | +| Command | `/zotero-review` | 既存のZoteroコレクションをレビューし、構造化された文献合成を生成 | +| Command | `/zotero-notes` | Zoteroコレクションを一括読解し、構造化された論文リーディングノートを作成 | + +**仕組み** +- **5W1Hブレインストーミング**: 漠然としたトピックを構造化された問い（What / Why / Who / When / Where / How）に変換 +- **文献検索とインポート**: 論文を検索、DOI/arXiv/URLを抽出、Zoteroにインポートし、テーマ別コレクションに整理 +- **PDFとフルテキスト**: 可能な場合はPDFを添付・フルテキストを読解、必要に応じてアブストラクトレベルの分析にフォールバック +- **ギャップ分析**: 文献的、方法論的、応用的、学際的、時間的ギャップを特定 +- **研究課題と計画**: レビューを具体的な研究課題、初期仮説、次ステップ計画に変換 +- **根拠ゲート**: 主張を `Knowledge`、`Writing`、提案書に昇格する前に、弱いソース、プロジェクト仮説、不足している根拠を明示 + +**典型的な出力** +- 仮説、必要エビデンス、反証条件、次アクションを含む研究質問カード +- 文献レビューノート +- 構造化されたZoteroコレクション +- 根拠が十分な場合のみプロジェクト提案書。それ以外は研究方向性または初期整理ドラフト + +### 2. MLプロジェクト開発 + +実験コードとイテレーションのための保守性の高いMLプロジェクト構造。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `architecture-design` | 新しい登録可能なコンポーネントやモジュール導入時に保守性の高いMLプロジェクト構造を定義 | +| Skill | `git-workflow` | ブランチ管理、コミット規約、安全なコラボレーションワークフローを適用 | +| Skill | `bug-detective` | スタックトレース、シェルエラー、コードパスの問題を体系的にデバッグ | +| Agent | `code-reviewer` | 変更されたコードの正確性、保守性、実装品質をレビュー | +| Agent | `tdd-guide` | 明示的に TDD が必要な場面で、絞ったテスト駆動の実装ガイドを出す。 | +| Command | `/plan` | コーディング前に実装計画を作成・改善 | +| Command | `/commit` | 現在の変更に対してConventional Commitを準備 | +| Command | `/code-review` | 現在のコード変更に対するフォーカスレビューを実行 | +| Command | `/tdd` | テスト駆動の小さな実装ステップで機能開発を推進 | + +**仕組み** +- **構造**: 適切な場合にFactory / Registryパターンを使用 +- **コード品質**: ファイルを保守可能、型付き、設定駆動に維持 +- **デバッグ**: スタックトレース、シェルエラー、コードパスの問題を体系的に調査 +- **Git規律**: ブランチ管理、Conventional Commits、安全な統合/rebaseワークフロー + +### 3. 実験分析 + +科学的図表とレポート用アーティファクトを伴う厳密な実験結果分析。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `results-analysis` | 厳密な統計、科学的図表、分析アーティファクトを含む分析バンドルを生成 | +| Skill | `results-report` | 分析アーティファクトを、意思決定、限界、次アクションを含む完全な実験後レポートに変換 | +| Command | `/analyze-results` | ブロッカー優先の実験後ワークフローを実行。根拠を検証し、可能な場合に厳密分析、十分な場合にレポート生成 | + +**仕組み** +- **データ処理**: 実験ログ、メトリクスファイル、結果ディレクトリを読解 +- **ブロッカー優先ゲート**: 分析単位、主要指標、seeds/folds/runs、出所追跡、比較族を先に固定 +- **統計検定**: 適切な場合にt検定 / ANOVA / Wilcoxon等の厳密な統計チェックを実行 +- **可視化**: 曖昧なプロット提案ではなく、解釈ガイダンス付きの科学的図表を生成 +- **アブレーションと比較**: コンポーネント寄与度、パフォーマンストレードオフ、安定性を分析 +- **実験後レポート**: 分析バンドルを結論、限界、次アクションを含む完全な振り返りレポートに変換 + +**典型的な出力** +- `analysis-report.md` +- `stats-appendix.md` +- `figure-catalog.md` +- `figures/` +- Obsidian `Results/Reports/`内の実験後サマリーレポート +- 根拠不足時のブロッカー要約または監査メモ + +### 4. 論文執筆 + +構造セットアップからドラフト改善までの体系的な学術ライティング。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `ml-paper-writing` | リポジトリコンテキスト、エビデンス、文献からML/AI論文を執筆 | +| Skill | [`nature-writing`](./skills/nature-writing/README.md) | claims、figures、results、notes、または中国語草稿から Nature スタイルの論文セクションを起草・再構成する | +| Skill | [`nature-polishing`](./skills/nature-polishing/README.md) | 原稿を推敲・再構成・翻訳し、Nature寄りの簡潔な英語へ整える | +| Skill | [`nature-response`](./skills/nature-response/README.md) | Nature系修正投稿向けの point-by-point reviewer response を作成・監査・改稿する | +| Skill | [`nature-data`](./skills/nature-data/README.md) | Nature向け Data Availability、repository plan、FAIR metadata チェックを準備する | +| Skill | `citation-verification` | 参考文献、メタデータ、主張と引用の整合性をチェックし引用ミスを防止 | +| Skill | `writing-anti-ai` | 機械的な表現を減らし、明瞭さ、リズム、人間的な学術トーンを改善 | +| Skill | `latex-conference-template-organizer` | 乱雑な学会テンプレートをOverleaf対応のライティング構造に整理 | +| Agent | `paper-miner` | 優れた論文から再利用可能なライティングパターン、構造、学会の期待値を抽出 | +| Command | `/mine-writing-patterns` | 論文を読み込み、再利用可能なライティング知識を現在インストール済みのpaper-minerメモリに統合 | + +**仕組み** +- **テンプレート準備**: 学会テンプレートをOverleaf対応構造に整理 +- **ジャーナル寄りの推敲**: 必要に応じて段落ロジック、hedging、section moves を整え、Nature寄りの文体へ近づける +- **査読返信**: major/minor revision コメントを監査可能な point-by-point response package に整理する +- **データ可用性**: Nature向けの repository plan、dataset citation、availability statement を準備する +- **引用検証**: 参考文献、メタデータ、主張と引用の整合性を検証 +- **体系的執筆**: リポジトリコンテキスト、実験根拠、文献ノートからセクションを執筆し、未支持の主張は明示的に残す +- **主張台帳**: 貢献、結果、関連研究との差分は根拠へ追跡し、そうでなければ推測的な表現として扱う +- **スタイル改善**: 機械的な表現を減らし、リズム、明瞭さ、トーンを改善 + +### 5. 論文セルフレビュー + +投稿前の品質保証。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `paper-self-review` | 投稿前に構造、ロジック、引用、図表、コンプライアンスを監査 | + +**仕組み** +- **構造チェック**: 論理的な流れ、セクションバランス、物語の一貫性 +- **ロジック検証**: 主張とエビデンスの整合性、前提の明確さ、議論の一貫性 +- **引用監査**: 参考文献の正確性と完全性 +- **図表品質**: キャプションの完全性、可読性、アクセシビリティ +- **コンプライアンス**: ページ制限、フォーマット、開示要件 + +### 6. 投稿とリバッタル + +投稿準備とレビュー対応ワークフロー。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `review-response` | レビューアコメントをエビデンスベースのリバッタルワークフローに構造化 | +| Agent | `rebuttal-writer` | 利用可能な実行時では、プロフェッショナルで敬意あるリバッタル文面を補助 | +| Command | `/rebuttal` | レビューコメントと根拠から、根拠アンカー付きのリバッタルドラフトを生成し、未解決点を明示 | + +**仕組み** +- **投稿前チェック**: 学会固有のフォーマット、匿名化、チェックリスト要件 +- **レビュー分析**: レビューアコメントをアクション可能なカテゴリに分類 +- **対応戦略**: 受け入れ、反論、明確化、新実験の提案を判断 +- **リバッタル執筆**: プロフェッショナルなトーンで構造化された回答を作り、根拠アンカーと未解決項目を保持 + +### 7. アクセプト後処理 + +アクセプト後の学会準備と研究プロモーション。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `post-acceptance` | アクセプト後の発表、ポスター、研究プロモーションをサポート | +| Command | `/presentation` | アクセプトされた研究の発表構成とスピーキングガイダンスを生成 | +| Command | `/poster` | 研究内容をポスター用コンテンツとレイアウトガイダンスに整理 | +| Command | `/promote` | サマリー、投稿、スレッドなどの外部向けプロモーションコンテンツを作成 | + +**仕組み** +- **プレゼンテーション**: 発表構成とスライドガイダンスを準備 +- **ポスター**: コンテンツをポスター用レイアウトと階層に整理 +- **プロモーション**: ソーシャルメディア、ブログ、サマリー素材を生成 + +## サポートワークフロー + +主要ワークフローを強化するバックグラウンドワークフロー。 + +### Obsidianプロジェクトナレッジベース + +Obsidianを単なるノート置き場ではなく、プロジェクト単位で長期利用できる知識基盤として使う。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `obsidian-project-kb-core` | プロジェクト単位のKBに対する初期化、ルーティング、登録表、索引、日次記録、ライフサイクルを統括 | +| Skill | `obsidian-source-ingestion` | 外部資料を `Sources/Papers`、`Sources/Web`、`Sources/Docs`、`Sources/Data`、`Sources/Interviews`、`Sources/Notes` に取り込む | +| Skill | `obsidian-literature-workflow` | `Sources/Papers` から `Knowledge`、`Writing`、`Maps/literature.canvas` へ進む文献ワークフローを担当 | +| Skill | `obsidian-kb-artifacts` | wikilink、登録表、canvas、明示指定の `.base`、リンク修復などの Obsidian ネイティブ成果物を扱う | +| Command | `/kb-init` | `Research/{project-slug}/` 配下に vault 中心の KB を初期化 | +| Command | `/kb-status` | バインド済みプロジェクトKBの現在状態を要約 | +| Command | `/kb-ingest` | 新しいソース素材を正しい標準ノートにルーティング | +| Command | `/kb-log` | 当日の `Daily/` と関連サーフェスを保守的に更新 | +| Command | `/kb-sync` | 決定論的な KB メンテナンスを実行し、登録表・索引・日次記録・実行時の紐付け状態を更新 | +| Command | `/kb-links` | 標準 KB ノート間の wikilink を修復または強化 | +| Command | `/kb-promote` | Daily やソースノートの安定した内容を標準ノートに昇格 | +| Command | `/kb-index` | 人間向けナビゲーションページ `02-Index.md` を再生成 | +| Command | `/kb-lint` | 決定論的なKB健全性チェックを実行し `_system/lint-report.md` を更新 | +| Command | `/kb-archive` | KBオブジェクトのアーカイブ、切り離し、削除、リネームを行い、リンクと登録表を整合させる | +| Command | `/kb-map` | 既定の literature canvas 以外のKB成果物を明示要求時に生成または修復 | +| Command | `/kb-literature-review` | `Sources/Papers` から根拠ゲート付きの文献統合を作り、`Knowledge`、必要時の `Writing`、`Maps/literature.canvas` に書き戻す | + +**仕組み** +- 既存リポジトリをObsidianのvaultにバインド +- 安定した知識を `Sources / Knowledge / Experiments / Results / Results/Reports / Writing / Daily / Maps` にルーティング +- `Daily/` とリポジトリ内の紐付けメタデータを保守的に更新 +- 新しいソース素材を正しい標準ノートに取り込む +- アブストラクトのみのソースやWebページのプレースホルダーが安定した主張を支えないようにする +- 追加の `.base` や canvas は明示要求時のみ生成 +- 決定論的な再同期には `/kb-sync`、単独のリンク修復には `/kb-links` を使う + +**ノート言語設定** + +生成・同期されるObsidianノートの言語は以下の優先順位で決定: +1. プロジェクト設定: `.claude/project-memory/registry.yaml` -> `note_language` +2. 環境変数: `OBSIDIAN_NOTE_LANGUAGE` +3. デフォルト: `en` + +注: ファイルは歴史的な理由で`registry.yaml`という名前ですが、実際のフォーマットはJSONです。 + +プロジェクトごとの設定例: + +```json +{ + "projects": { + "my-project": { + "project_id": "my-project", + "vault_root": "/path/to/vault/Research/my-project", + "note_language": "zh-CN" + } + } +} +``` + +英語と中国語のセクション見出しは同期時に相互互換性があるため、言語設定を切り替えた後でもどちらの言語の既存ノートも安全に更新できます。 + +### 自動化ワークフロー + +クロスプラットフォームフックによるルーティンワークフローチェックとリマインダーの自動化。 + +**Hooks** +- `skill-forced-eval.js` +- `session-start.js` +- `session-summary.js` +- `stop-summary.js` +- `security-guard.js` + +**仕組み** +- **プロンプト前**: 適用可能なスキルを評価し、関連するワークフローヒントを表示 +- **セッション開始時**: Git状態、利用可能なコマンド、プロジェクトメモリコンテキストを表示 +- **セッション終了/停止時**: 作業を要約し、最低限のメンテナンスタスクをリマインド +- **セキュリティ**: 壊滅的なコマンドをブロックし、危険だが正当なコマンドには確認を要求 + +### 表現と報告の規律レイヤー + +結論先行の報告、具体的なエビデンス、可視化されたリスク、または簡潔な次アクションが必要なときは、再利用可能なコミュニケーションレイヤーを使います。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | [`expression-skill`](./skills/expression-skill/README.md) | 技術作業、執筆、ドキュメント、ファイル操作、多段タスク向けに、結論先行で具体的かつ検証可能な表現規律を適用する | +| Skill | [`planning-with-files`](./skills/planning-with-files/SKILL.md) | 複雑な作業を `task_plan.md`、`notes.md`、成果物ファイルへ持続化し、一時的な会話 context だけに依存しないようにする | + +**仕組み** +- 経緯説明ではなく結論から始める +- 抽象的なプロセス語より、コマンド、パス、件数、チェック結果、観測可能な挙動を優先する +- 結果が変わるときだけ確認質問をする +- リスク、不確実性、破壊的境界を早めに明示する +- 長時間作業では step / checkpoint 形式の可視化された進捗目印を出す +- 多段タスクでは `task_plan.md` と `notes.md` に計画と途中知見を残し、一時的な context だけに依存しない + +### 知識抽出ワークフロー + +専門エージェントが論文やコンペティションから再利用可能な知識をマイニング。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Agent | `paper-miner` | 優れた論文から再利用可能なライティング知識、構造パターン、学会ヒューリスティクスを抽出 | +| Agent | `kaggle-miner` | 優れたKaggleワークフローからエンジニアリングプラクティスとソリューションパターンを抽出 | + +**仕組み** +- 論文からライティングパターン、学会の期待値、リバッタル戦略を抽出 +- Kaggleワークフローからエンジニアリングパターンとソリューション構造を抽出 +- これらの知見をスキルや参考資料にフィードバック + +### スキル進化システム + +Claude Scholar自身のスキルに対する自己改善ループ。 + +| 種類 | 名前 | 概要 | +|---|---|---| +| Skill | `skill-development` | 明確なトリガー、構造、段階的開示を持つ新スキルを作成 | +| Skill | `skill-quality-reviewer` | コンテンツ品質、構成、スタイル、構造的完全性にわたってスキルをレビュー | +| Skill | `skill-improver` | 構造化された改善計画を適用して既存スキルを進化 | + +**仕組み** +- 明確なトリガー説明を持つ新スキルを作成 +- 品質の各次元にわたってレビュー +- 構造化された改善を適用し、イテレーション + +## ドキュメント + +- [MCP_SETUP.ja-JP.md](./MCP_SETUP.ja-JP.md) — Zotero/ブラウザMCPセットアップ（日本語） +- [OBSIDIAN_SETUP.ja-JP.md](./OBSIDIAN_SETUP.ja-JP.md) — Obsidianナレッジベースワークフロー（日本語） +- [CLAUDE.ja-JP.md](./CLAUDE.ja-JP.md) — 軽量な Claude Code コア指示の日本語版 +- [CLAUDE.md](./CLAUDE.md) — 軽量な Claude Code コア指示（英語版） +- [CLAUDE.zh-CN.md](./CLAUDE.zh-CN.md) — 軽量コア指示の中国語版補助ファイル +- [settings.json.template](./settings.json.template) — hooks/plugins/MCP用のオプション設定テンプレート + +## プロジェクトルール + +Claude Scholarには以下のプロジェクトルールが含まれています: +- コーディングスタイル +- エージェントオーケストレーション +- セキュリティ +- 実験再現性 + +これらはシッピングされたルールと`CLAUDE.md`に反映されています。 + +## コントリビューション + +Issue、PR、ワークフローの改善を歓迎します。 + +インストーラーの動作、Zoteroワークフロー、Obsidianルーティングへの変更を提案する場合は、以下を含めてください: +- ユーザーシナリオ +- 現在の制限事項 +- 期待される動作 +- 互換性に関する懸念事項 + +## ライセンス + +MIT License。 + +## 引用 + +Claude Scholarがあなたの研究やエンジニアリングワークフローに役立った場合、以下のようにリポジトリを引用できます: + +```bibtex +@misc{claude_scholar_2026, + title = {Claude Scholar: Semi-automated research assistant for academic research and software development}, + author = {Gaorui Zhang}, + year = {2026}, + howpublished = {\url{https://github.com/Galaxy-Dawn/claude-scholar}}, + note = {GitHub repository} +} +``` + +## 謝辞 + +Claude Code CLIで構築され、オープンソースコミュニティによって強化されています。 + +### 参考プロジェクト + +本プロジェクトは、コミュニティの優れた成果からインスピレーションを受け、それらを基盤としています: + +- **[everything-claude-code](https://github.com/anthropics/everything-claude-code)** - Claude Code CLIの包括的なリソース +- **[AI-research-SKILLs](https://github.com/zechenzhangAGI/AI-research-SKILLs)** - 研究に特化したスキルと設定 +- **[expression-skill](https://github.com/Galaxy-Dawn/expression-skill)** - 報告と応答の規律に使う公開の結論先行コミュニケーション skill +- **[nature-skills](https://github.com/Yuan1z0825/nature-skills)** - Nature スタイルの章起草、学術推敲、査読返信、データ可用性 skills をここで再利用し、出典を明記 + +これらのプロジェクトは、Claude Scholarの研究指向機能に貴重な知見と基盤を提供しました。 + +--- + +**データサイエンス、AI研究、学術ライティングのために。** + +リポジトリ: [https://github.com/Galaxy-Dawn/claude-scholar](https://github.com/Galaxy-Dawn/claude-scholar) diff --git a/文档润色流和知识库构建流/claude-scholar/README.md b/文档润色流和知识库构建流/claude-scholar/README.md new file mode 100644 index 0000000..5a81e8a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/README.md @@ -0,0 +1,666 @@ +
    + Claude Scholar Logo + +

    + Stars + GitCode Stars + Forks + Last Commit + License +

    + + +

    + + + Kimi Open Source Friends + +

    + + Language: English | 中文 | 日本語 +

    Supported Platforms: Claude Code | Codex CLI | Kimi Code CLI | OpenCode

    + +
    + +> Semi-automated research assistant for academic research and software development, especially for computer science and AI researchers. Supports [Claude Code](https://github.com/anthropics/claude-code), [Codex CLI](https://github.com/openai/codex), [Kimi Code CLI](https://github.com/MoonshotAI/kimi-code), and [OpenCode](https://github.com/opencode-ai/opencode) across literature review, coding, experiments, reporting, writing, and project knowledge management. + +

    Branch note: the main branch is the Claude Code workflow. If you use Codex CLI, please see the codex branch. If you use Kimi Code CLI, please see the kimi branch. If you use OpenCode, please see the opencode branch.

    + + +## Recent News + +- **2026-06-03**: **Kimi Code CLI branch added with strong support from Kimi** — added the `kimi` branch as the Kimi Code CLI edition of Claude Scholar and thank the Kimi team for their strong support of this project. +- **2026-05-14**: **`expression-skill` made the communication core, `planning-with-files` restored as the default persistence layer, and the Nature writing stack expanded** — made [`expression-skill`](./skills/expression-skill/README.md) the explicit conclusion-first discipline for reporting, planning, file operations, and multi-step technical work; reintroduced [`planning-with-files`](./skills/planning-with-files/SKILL.md) as the default on-disk planning and progress-tracking workflow for complex tasks; introduced [`nature-writing`](./skills/nature-writing/README.md) for section drafting and argument construction; refreshed [`nature-polishing`](./skills/nature-polishing/README.md) to the latest upstream article-pattern release; and kept [`nature-response`](./skills/nature-response/README.md) plus [`nature-data`](./skills/nature-data/README.md) in the journal-writing stack. +- **2026-05-13**: **Evidence-gated research workflow and `Sources/Papers` routing tightened** — added a shared `research-contract.md` for Evidence Records, claim strength, and Claim Promotion Gates; connected research ideation, Zotero ingestion, literature synthesis, results reporting, writing, and rebuttal workflows to that contract; and clarified that project paper notes live under `Sources/Papers` before promoted claims move into `Knowledge` or `Writing`. +- **2026-04-24**: **Project-scoped Obsidian KB workflow consolidated** — rebuilt Obsidian project knowledge management into a vault-first workflow, consolidated the older overlapping memory skills into four focused skills, kept repo-local project binding metadata as a runtime layer, and made project navigation human-first instead of a machine registry dump. +- **2026-04-22**: **Lean core, pruned default agents, safer install lifecycle, and cleaner paper discovery** — replaced large always-on `CLAUDE.md` / `AGENTS.md` files with compact core instructions, pruned the default agent set to the retained core agents, added safe install-state based uninstall support, generalized `daily-paper-generator` to broader topics with arXiv / bioRxiv support and a fixed Top 10 -> Top 3 -> Top 1 selection flow. +- **2026-04-15**: **pubfig and pubtab introduced** — introduced [`pubfig`](https://github.com/Galaxy-Dawn/pubfig), a Python package for publication-grade scientific figures, and [`pubtab`](https://github.com/Galaxy-Dawn/pubtab), a Python package for publication-ready tables and Excel↔LaTeX workflows. Together they provide a cleaner production stack for paper figures, benchmark tables, export control, and final artifact QA. + +
    +View older changelog + +- **2026-04-15**: **[`publication-chart-skill`](./skills/publication-chart-skill/SKILL.md) integrated into Claude Scholar** — wrapped [`pubfig`](https://github.com/Galaxy-Dawn/pubfig) + [`pubtab`](https://github.com/Galaxy-Dawn/pubtab) into [`publication-chart-skill`](./skills/publication-chart-skill/SKILL.md), added the skill to the repository, and connected it to Claude Scholar's analysis and writing boundaries so publication-grade figure/table work now has an explicit handoff route instead of being mixed into general analysis or prose skills. +- **2026-03-31**: **Zotero smart-import workflow docs aligned** — updated Claude Scholar's research-facing docs around the latest `zotero-mcp` public surface: `zotero_add_items_by_identifier` is now the default paper-import path, `zotero_reconcile_collection_duplicates` is the standard post-import cleanup step, source-aware PDF cascade behavior is documented more accurately, and public vs internal diagnostics are now clearly separated. +- **2026-03-31**: **README onboarding refreshed** — clarified that Claude Scholar is especially well-suited to computer science and AI researchers, added practical getting-started scenarios after installation, improved prerequisite and branch guidance, and made the “existing local md files must be manually merged” expectation much more explicit. +- **2026-03-31**: **Installer and hook behavior tightened** — the installer now preserves existing local `CLAUDE.md` while installing the repo-managed version as `CLAUDE.scholar.md`, and the default hook summaries were trimmed to reduce noisy temp-file / uncommitted-file output while keeping safer write-guard behavior. +- **2026-03-31**: **Japanese documentation added** — added Japanese docs for the main README plus `AGENTS`, `MCP_SETUP`, and `OBSIDIAN_SETUP`, so the OpenCode branch now has a more complete multilingual documentation surface. + +- **2026-02-25**: **Codex CLI** support — added `codex` branch supporting [OpenAI Codex CLI](https://github.com/openai/codex) with config.toml, 40 skills, 14 agents, and sandbox security +- **2026-02-23**: Added `setup.sh` installer — backup-aware incremental updates for existing `~/.opencode`, auto-backup `opencode.jsonc`, additive `agent/mcp/permission/plugin` merge +- **2026-02-21**: **OpenCode** support — Claude Scholar now supports [OpenCode](https://github.com/opencode-ai/opencode) as an alternative CLI; switch to the `opencode` branch for OpenCode-compatible configuration +- **2026-02-20**: Bilingual docs — maintained English and Chinese entry documents for broader readability +- **2026-02-15**: Zotero MCP integration — added `/zotero-review` and `/zotero-notes` commands, updated `research-ideation` skill with Zotero integration guide, enhanced `literature-reviewer` agent with Zotero MCP support for automated paper import, collection management, full-text reading, and citation export +- **2026-02-14**: Hooks optimization — restructured `security-guard` to two-tier system (Block + Confirm), `skill-forced-eval` now groups skills into 6 categories with silent scan mode, `session-start` limits display to top 5, `session-summary` adds 30-day log auto-cleanup, `stop-summary` shows separate added/modified/deleted counts; removed deprecated shell scripts (lib/common.sh, lib/platform.sh) +- **2026-02-11**: Major update — added 10 new skills (research-ideation, results-analysis, citation-verification, review-response, paper-self-review, post-acceptance, daily-coding, frontend-design, ui-ux-pro-max, web-design-reviewer), 7 new agents, 8 research workflow commands, 2 new rules (security, experiment-reproducibility); restructured the main configuration docs; 89 files changed +- **2026-01-26**: Rewrote all Hooks to cross-platform Node.js; completely rewrote README; expanded ML paper writing knowledge base; merged PR #1 (cross-platform support) +- **2026-01-25**: Project open-sourced, v1.0.0 released with 25 skills (architecture-design, bug-detective, git-workflow, kaggle-learner, scientific-writing, etc.), 2 agents (paper-miner, kaggle-miner), 30+ commands (including SuperClaude suite), 5 Shell Hooks, and 2 rules (coding-style, agents) + +
    + +## Quick Navigation + +| Section | What it helps with | +|---|---| +| [Why Claude Scholar](#why-claude-scholar) | Understand the project positioning and target use cases. | +| [Core Workflow](#core-workflow) | See the end-to-end research pipeline from ideation to publication. | +| [Quick Start](#quick-start) | Install Claude Scholar in full, minimal, or selective mode. | +| [Getting Started Scenarios](#getting-started-scenarios) | See a few realistic first-use scenarios after installation. | +| [Integrations](#integrations) | Learn how Zotero and Obsidian fit into the workflow. | +| [Primary Workflows](#primary-workflows) | Browse the main research and development workflows. | +| [Supporting Workflows](#supporting-workflows) | See the background systems that strengthen the main workflow. | +| [Documentation](#documentation) | Jump to setup docs, configuration, and templates. | +| [Citation](#citation) | Cite Claude Scholar in papers, reports, or project docs. | + +## Why Claude Scholar + +Claude Scholar is **not** an end-to-end autonomous research system that tries to replace the researcher. + +Its core idea is simple: + +> **human decision-making stays at the center; the assistant accelerates the workflow around it.** + +That means Claude Scholar is designed to help with the heavy, repetitive, and structure-sensitive parts of research — literature organization, note-taking, experiment analysis, reporting, and writing support — while still keeping the key judgments in human hands: + +- which problem is worth pursuing, +- which papers actually matter, +- which hypotheses are worth testing, +- which results are convincing, +- and what should be written, submitted, or abandoned. + +In other words, Claude Scholar is a **semi-automated research assistant**, not a “fully automated scientist.” + +## Who This Is For + +Claude Scholar is especially well-suited to: + +- **computer science researchers** who move between literature review, coding, experiments, and paper writing, +- **AI / ML researchers** who need one assistant workflow spanning ideation, implementation, analysis, reporting, and rebuttal, +- **research engineers and graduate students** who want stronger workflow structure without giving up human judgment, +- and **software-heavy academic projects** that benefit from Zotero, Obsidian, CLI automation, and reproducible project memory. + +It can still help in other research settings, but its current workflow design is most aligned with computer science, AI, and adjacent computational research. + +## Core Workflow + +Claude Scholar routes research work through a traceable path: +`question -> evidence -> experiment -> analysis -> claim -> writing`. +Each stage should preserve what is known, what is uncertain, and what decision should happen next. + +- **Ideation**: turn a vague topic into concrete questions, research gaps, and an initial plan. +- **Literature**: search, import, organize, and read papers through Zotero collections. +- **Paper notes**: convert papers into structured reading notes and reusable claims. +- **Knowledge base**: route durable knowledge into Obsidian across `Sources / Knowledge / Experiments / Results / Results/Reports / Writing / Daily / Maps`. +- **Experiments**: track hypotheses, experiment lines, run history, findings, and next actions. +- **Analysis**: generate strict statistics, real scientific figures, and analysis artifacts with `results-analysis`. +- **Reporting**: produce a complete post-experiment report with `results-report`, then write it back into Obsidian. +- **Writing and publication**: carry stable findings into literature reviews, papers, rebuttals, slides, posters, and promotion. + +## Quick Start + +### Requirements + +- [Claude Code](https://github.com/anthropics/claude-code) +- Git +- (Optional) Python + [uv](https://docs.astral.sh/uv/) for Python development +- (Optional) [Zotero](https://www.zotero.org/) + [Galaxy-Dawn/zotero-mcp](https://github.com/Galaxy-Dawn/zotero-mcp) for literature workflows +- (Optional) [Obsidian](https://obsidian.md/) for project knowledge-base workflows + +### Option 1: Full Installation (Recommended) + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +bash /tmp/claude-scholar/scripts/setup.sh +``` + +**Windows**: please use Git Bash or WSL to run the installer. + +The installer is **backup-aware and incremental-update friendly**: +- updates repo-managed `skills/commands/agents/rules/hooks/scripts/CLAUDE*.md`, +- backs up overwritten files to `~/.claude/.claude-scholar-backups//`, +- backs up `settings.json` to `settings.json.bak`, +- preserves an existing `~/.claude/CLAUDE.md` and installs the repo-managed version as `~/.claude/CLAUDE.scholar.md`, +- preserves an existing `~/.claude/CLAUDE.zh-CN.md` and installs the repo-managed version as `~/.claude/CLAUDE.zh-CN.scholar.md`, +- preserves your existing `env`, model/provider settings, API keys, permissions, and current `mcpServers` values, +- adds missing hook entries instead of replacing your entire hook set. + +**Important CLAUDE note**: if you already maintain your own `~/.claude/CLAUDE.md` or `~/.claude/CLAUDE.zh-CN.md`, review `~/.claude/CLAUDE.scholar.md` and `~/.claude/CLAUDE.zh-CN.scholar.md` after installation and manually merge the Claude Scholar sections you want into your own files. Do not assume the sidecar files are applied automatically. + +To update later: + +```bash +cd /tmp/claude-scholar +git pull --ff-only +bash scripts/setup.sh +``` + +To uninstall later: + +```bash +cd /tmp/claude-scholar +bash scripts/uninstall.sh +``` + +The installer now writes: +- `~/.claude/.claude-scholar-manifest.txt` for the exact files managed by Claude Scholar +- `~/.claude/.claude-scholar-install-state` for install ownership metadata used by safe uninstall + +The uninstaller removes only files and settings entries recorded in that install state. It does not guess ownership from the current repo checkout. + +### Option 2: Minimal Installation + +Install only a small research-focused subset: + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +mkdir -p ~/.claude/hooks ~/.claude/skills +cp /tmp/claude-scholar/hooks/*.js ~/.claude/hooks/ +cp -r /tmp/claude-scholar/skills/ml-paper-writing ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/research-ideation ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/results-analysis ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/results-report ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/review-response ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/writing-anti-ai ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/git-workflow ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/bug-detective ~/.claude/skills/ +``` + +**Post-install**: minimal/manual install does **not** auto-merge `settings.json`; copy only the hooks or MCP entries you want from `settings.json.template`. If you already have your own `~/.claude/CLAUDE.md` or `~/.claude/CLAUDE.zh-CN.md`, also merge the relevant sections from this repo's Claude files into yours instead of blindly overwriting them. + +### Option 3: Selective Installation + +Copy only the parts you need: + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +cd /tmp/claude-scholar + +cp hooks/*.js ~/.claude/hooks/ +cp -r skills/latex-conference-template-organizer ~/.claude/skills/ +cp -r skills/architecture-design ~/.claude/skills/ +cp agents/paper-miner.md ~/.claude/agents/ +cp rules/coding-style.md ~/.claude/rules/ +cp rules/agents.md ~/.claude/rules/ +``` + +**Post-install**: selective/manual install does **not** auto-merge `settings.json`; copy only the hooks or MCP entries you actually want from `settings.json.template`. If you already have your own `~/.claude/CLAUDE.md` or `~/.claude/CLAUDE.zh-CN.md`, merge the relevant sections from this repo's Claude files into yours instead of blindly overwriting them. + +### Option 4: Plugin Marketplace Installation + +**Step 1: Install the Plugin** + +```bash +/plugin marketplace add Galaxy-Dawn/claude-scholar +/plugin install claude-scholar@claude-scholar +``` + +This auto-loads all skills, commands, agents, and hooks. During installation, you can choose the scope: user (all projects) or project (single project). + +**Step 2: Install Rules (Required)** + +Claude Code plugins cannot distribute rules automatically. Install them manually: + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar + +# User-level (all projects) +mkdir -p ~/.claude/rules +cp /tmp/claude-scholar/rules/*.md ~/.claude/rules/ + +# Or project-level (current project only) +mkdir -p .claude/rules +cp /tmp/claude-scholar/rules/*.md .claude/rules/ +``` + +**Post-install**: plugin installation does **not** auto-load `CLAUDE.md` or configure `settings.json`; if you already have your own `~/.claude/CLAUDE.md` or `~/.claude/CLAUDE.zh-CN.md`, merge the relevant Claude Scholar sections into yours instead of assuming the plugin applies them automatically. If you need Zotero MCP or other integrations, see the [Integrations](#integrations) section for manual setup. + +## Getting Started Scenarios + +After installation, the simplest way to begin is to describe your task in natural language. You do not need to memorize the whole system first. Below are a few realistic starting points. + +### 1. Start a New Research Topic +**You can say:** +> Help me start research on [your topic]. I want a literature-grounded plan, the key open questions, and the next concrete steps. + +**What Claude Scholar will typically help with:** +- clarify the topic and narrow the research question, +- identify promising literature directions, +- suggest an initial plan or hypothesis list, +- optionally route the work into Zotero or Obsidian if you use them. + +### 2. Review a Zotero Collection +**You can say:** +> Review my Zotero collection on brain foundation models and summarize the main directions, gaps, and promising next steps. + +**Typical output:** +- paper grouping by theme, +- a short literature synthesis, +- gap analysis, +- candidate research directions worth pursuing next. + +### 3. Analyze Finished Experiment Results +**You can say:** +> Analyze the results in this experiment folder, check what changed across runs, and write a decision-oriented summary. + +**Typical output:** +- metric comparison, +- ablation or error-analysis suggestions, +- a result summary that highlights what is solid, what is weak, and what to run next. + +### 4. Draft a Paper or Rebuttal Section +**You can say:** +> Help me draft the related work section for this project based on the current findings and paper notes. + +or: + +> Help me write a rebuttal draft for these reviewer comments. + +**Typical output:** +- a structured section draft, +- improved argument flow, +- clearer claims and evidence mapping, +- follow-up points that still need support or verification. + +### Practical Notes +- Start with one concrete task, not a vague request for "everything." +- If you already maintain your own local `CLAUDE.md` files, merge the Claude Scholar sections you want into them instead of assuming sidecar files apply automatically. +- Zotero and Obsidian are optional, but they become much more useful when you want durable literature notes or project memory rather than one-off chat output. + +## Platform Support + +Claude Scholar is maintained for: + +- **Claude Code** — the primary installation target. +- **Codex CLI** — supported workflow and documentation are available in this repo ecosystem. +- **OpenCode** — supported as an alternative CLI workflow. + +The top-level workflow is the same: research, coding, experiments, reporting, and project knowledge management. + +## Integrations + +### Zotero + +Use Zotero when you want Claude Scholar to help with: +- paper import via DOI / arXiv / URL, +- collection-based reading workflows, +- full-text access through Zotero MCP, +- detailed paper notes and literature synthesis. + +See [MCP_SETUP.md](./MCP_SETUP.md). + +### Obsidian + +Use Obsidian when you want Claude Scholar to maintain a filesystem-first research knowledge base: +- `Sources/` +- `Knowledge/` +- `Experiments/` +- `Results/` +- `Results/Reports/` +- `Writing/` +- `Daily/` +- `Maps/` + +See [OBSIDIAN_SETUP.md](./OBSIDIAN_SETUP.md). + +## Primary Workflows + +Complete academic research lifecycle — 7 stages from idea to publication. + +### 1. Research Ideation (Zotero-Integrated) + +End-to-end research startup from idea generation to literature management. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `research-ideation` | Turn vague topics into structured questions, gap analysis, and an initial research plan. | +| Agent | `literature-reviewer` | Search, classify, and synthesize papers into an actionable literature picture. | +| Command | `/research-init` | Start a new topic with literature search, Zotero organization, research question cards, and proposal drafting only when the evidence gate passes. | +| Command | `/zotero-review` | Review an existing Zotero collection and generate a structured literature synthesis. | +| Command | `/zotero-notes` | Batch-read a Zotero collection and create structured paper reading notes. | + +**How it works** +- **5W1H Brainstorming**: turn a vague topic into structured questions (`What / Why / Who / When / Where / How`). +- **Literature Search & Import**: search papers, extract DOI/arXiv/URLs, import them into Zotero, and organize them into themed collections. +- **PDF & Full Text**: attach PDFs when available, read full text when possible, and fall back to abstract-level analysis when necessary. +- **Gap Analysis**: identify literature, methodological, application, interdisciplinary, or temporal gaps. +- **Research Question & Planning**: convert the review into concrete questions, initial hypotheses, and next-step planning. +- **Evidence Gate**: keep weak sources, project hypotheses, and missing evidence explicit before promoting a claim into `Knowledge`, `Writing`, or a proposal. + +**Typical output** +- research question cards with hypotheses, evidence needs, falsification criteria, and next actions +- literature review notes +- structured Zotero collection +- project proposal only when the selected question has enough verified evidence; otherwise a research direction / intake draft + +### 2. ML Project Development + +Maintainable ML project structure for experiment code and iteration. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `architecture-design` | Define maintainable ML project structure when new registrable components or modules are introduced. | +| Skill | `git-workflow` | Enforce branch hygiene, commit conventions, and safer collaboration workflows. | +| Skill | `bug-detective` | Debug stack traces, shell failures, and code-path issues systematically. | +| Agent | `code-reviewer` | Review modified code for correctness, maintainability, and implementation quality. | +| Agent | `tdd-guide` | Provide focused test-driven implementation guidance when a TDD path is explicitly needed. | +| Command | `/plan` | Create or refine an implementation plan before coding. | +| Command | `/commit` | Prepare a conventional commit for the current changes. | +| Command | `/code-review` | Run a focused review on the current code changes. | +| Command | `/tdd` | Drive feature work through small, test-backed implementation steps. | + +**How it works** +- **Structure**: use Factory / Registry patterns for new ML components when appropriate. +- **Code Quality**: keep files maintainable, typed, and config-driven. +- **Debugging**: inspect stack traces, shell failures, and code-path issues systematically. +- **Git Discipline**: use branch hygiene, conventional commits, and safer merge/rebase workflows. + +### 3. Experiment Analysis + +Strict analysis of experimental results with scientific figures and report-ready artifacts. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `results-analysis` | Produce a strict analysis bundle with rigorous statistics, real scientific figures, and analysis artifacts. | +| Skill | `results-report` | Turn analysis artifacts into a complete post-experiment report with decisions, limitations, and next actions. | +| Command | `/analyze-results` | Run a blocker-first experiment workflow: validate evidence, run strict analysis when possible, then generate a report only when the bundle is sufficient. | + +**How it works** +- **Data Processing**: read experiment logs, metrics files, and result directories. +- **Blocker-First Gate**: lock unit of analysis, primary metric, seeds/folds/runs, provenance, and comparison family before producing claims. +- **Statistical Testing**: run strict statistical checks such as t-test / ANOVA / Wilcoxon where appropriate. +- **Visualization**: generate real scientific figures with interpretation guidance, not just vague plotting suggestions. +- **Ablation & Comparison**: analyze component contribution, performance tradeoffs, and stability. +- **Post-Experiment Reporting**: turn the analysis bundle into a full retrospective report with conclusions, limitations, and next actions. + +**Typical output** +- `analysis-report.md` +- `stats-appendix.md` +- `figure-catalog.md` +- `figures/` +- post-experiment summary report in Obsidian `Results/Reports/` +- blocker summary / audit note when evidence is incomplete + +### 4. Paper Writing + +Systematic academic writing from structure setup to draft refinement. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `ml-paper-writing` | Draft publication-oriented ML/AI papers from repo context, evidence, and literature. | +| Skill | [`nature-writing`](./skills/nature-writing/README.md) | Draft or rebuild Nature-style manuscript sections from claims, figures, results, notes, or Chinese drafts. | +| Skill | [`nature-polishing`](./skills/nature-polishing/README.md) | Polish, restructure, or translate manuscript prose into concise Nature-leaning English. | +| Skill | [`nature-response`](./skills/nature-response/README.md) | Draft, audit, or revise point-by-point reviewer response letters for Nature-family revisions. | +| Skill | [`nature-data`](./skills/nature-data/README.md) | Prepare Nature-ready Data Availability statements, repository plans, and FAIR metadata checks. | +| Skill | `citation-verification` | Check references, metadata, and claim-citation alignment to prevent citation mistakes. | +| Skill | `writing-anti-ai` | Reduce robotic phrasing and improve clarity, rhythm, and human academic tone. | +| Skill | `latex-conference-template-organizer` | Clean messy conference templates into an Overleaf-ready writing structure. | +| Agent | `paper-miner` | Mine strong papers for reusable writing patterns, structure, and venue expectations. | +| Command | `/mine-writing-patterns` | Read a paper and merge reusable writing knowledge into the active installed paper-miner writing memory. | + +**How it works** +- **Template Preparation**: clean conference templates into an Overleaf-ready structure. +- **Journal-Style Polishing**: tighten paragraph logic, hedging, and section moves for Nature-leaning prose when needed. +- **Reviewer Response**: structure major/minor revision comments into an auditable point-by-point response package. +- **Data Availability**: prepare Nature-ready repository plans, dataset citations, and availability statements. +- **Citation Verification**: verify references, metadata, and claim-citation alignment. +- **Systematic Writing**: draft sections from repo context, experiment evidence, and literature notes, while keeping unsupported claims marked instead of polished. +- **Claim Ledger**: every contribution, result, and contrast should trace to evidence or remain explicitly speculative. +- **Style Refinement**: reduce robotic phrasing and improve rhythm, clarity, and tone. + +### 5. Paper Self-Review + +Quality assurance before submission. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `paper-self-review` | Audit structure, logic, citations, figures, and compliance before submission. | + +**How it works** +- **Structure Check**: logical flow, section balance, and narrative coherence. +- **Logic Validation**: claim-evidence alignment, assumption clarity, and argument consistency. +- **Claim Audit**: verify that main claims are supported by evidence, weaken over-strong language, and preserve uncertainty when needed. +- **Citation Audit**: reference correctness and completeness. +- **Figure Quality**: caption completeness, readability, and accessibility. +- **Compliance**: page limits, formatting, and disclosure requirements. + +### 6. Submission & Rebuttal + +Submission preparation and review response workflow. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `review-response` | Structure reviewer comments into an evidence-based rebuttal workflow. | +| Agent | `rebuttal-writer` | Optional specialist for professional, respectful, and strategically organized rebuttal text when available. | +| Command | `/rebuttal` | Generate an evidence-anchored rebuttal draft from review comments, with unresolved points marked instead of hidden. | + +**How it works** +- **Pre-submission Checks**: venue-specific formatting, anonymization, and checklist requirements. +- **Review Analysis**: classify reviewer comments into actionable categories. +- **Response Strategy**: decide whether to accept, defend, clarify, or propose new experiments. +- **Rebuttal Writing**: generate structured responses with professional tone, evidence anchors, and explicit unresolved items. + +### 7. Post-Acceptance Processing + +Conference preparation and research promotion after acceptance. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `post-acceptance` | Support talks, posters, and research promotion after acceptance. | +| Command | `/presentation` | Generate presentation structure and speaking guidance for the accepted work. | +| Command | `/poster` | Organize the work into poster-ready content and layout guidance. | +| Command | `/promote` | Draft public-facing promotion content such as summaries, posts, or threads. | + +**How it works** +- **Presentation**: prepare talk structure and slide guidance. +- **Poster**: organize content into poster-ready layout and hierarchy. +- **Promotion**: generate social media, blog, or summary material for broader communication. + +## Supporting Workflows + +These workflows run in the background to strengthen the primary workflows. + +### Obsidian Project Knowledge Base + +Use Obsidian as the project-scoped durable knowledge surface, not just as a note dump. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `obsidian-project-kb-core` | Main authority for project-scoped KB bootstrap, routing, registry, index, daily, and lifecycle updates. | +| Skill | `obsidian-source-ingestion` | Ingest external material into `Sources/Papers`, `Sources/Web`, `Sources/Docs`, `Sources/Data`, `Sources/Interviews`, or `Sources/Notes`. | +| Skill | `obsidian-literature-workflow` | Run the paper-note to synthesis workflow from `Sources/Papers` into `Knowledge`, `Writing`, and `Maps/literature.canvas`. | +| Skill | `obsidian-kb-artifacts` | Handle Obsidian-native artifacts such as wikilinks, registry tables, canvas files, optional Bases, and link repair. | +| Command | `/kb-init` | Initialize the vault-first KB under `Research/{project-slug}/`. | +| Command | `/kb-status` | Summarize the current KB state from the bound project root. | +| Command | `/kb-ingest` | Route new source material into the correct canonical KB destination. | +| Command | `/kb-log` | Update the current Daily note and related project surfaces conservatively. | +| Command | `/kb-sync` | Run deterministic KB maintenance to refresh registry, index, daily, and runtime binding state. | +| Command | `/kb-links` | Repair or strengthen wikilinks among canonical KB notes. | +| Command | `/kb-promote` | Promote durable content from Daily or source notes into canonical notes. | +| Command | `/kb-index` | Regenerate `02-Index.md` as the human-readable project navigator. | +| Command | `/kb-lint` | Run deterministic KB health checks and update `_system/lint-report.md`. | +| Command | `/kb-archive` | Archive, detach, purge, or rename KB objects while keeping links and registry consistent. | +| Command | `/kb-map` | Generate or repair explicit-only KB artifacts beyond the default literature canvas. | +| Command | `/kb-literature-review` | Generate evidence-gated literature synthesis from `Sources/Papers` into `Knowledge`, optional `Writing`, and `Maps/literature.canvas`. | + +**How it works** +- bind an existing repo to an Obsidian vault, +- route stable knowledge into `Sources / Knowledge / Experiments / Results / Results/Reports / Writing / Daily / Maps`, +- keep `Daily/` and repo-local binding metadata updated conservatively, +- ingest new source material into the correct canonical destination, +- keep abstract-only and webpage-placeholder sources from supporting durable claims, +- only generate extra Bases or canvases on explicit request. +- use `/kb-sync` for deterministic resyncs and `/kb-links` for standalone link repair. + +**Note language configuration** + +Generated and synced Obsidian notes resolve their language with this priority: +1. project config: `.claude/project-memory/registry.yaml` -> `note_language` +2. environment variable: `OBSIDIAN_NOTE_LANGUAGE` +3. default: `en` + +Note: the file is currently named `registry.yaml` for historical reasons, but its on-disk format is JSON. + +Per-project example: + +```json +{ + "projects": { + "my-project": { + "project_id": "my-project", + "vault_root": "/path/to/vault/Research/my-project", + "note_language": "zh-CN" + } + } +} +``` + +English and Chinese section headings remain mutually compatible during sync, so older notes in either language can still be updated safely after switching configuration. + +### Automated Enforcement Workflow + +Cross-platform hooks automate routine workflow checks and reminders. + +**Hooks** +- `skill-forced-eval.js` +- `session-start.js` +- `session-summary.js` +- `stop-summary.js` +- `security-guard.js` + +**How it works** +- **Before prompts**: evaluate applicable skills and surface relevant workflow hints. +- **At session start**: show Git state, available commands, and project-memory context. +- **At session end/stop**: summarize work and remind the user about minimum maintenance tasks. +- **Security**: block catastrophic commands and require confirmation for dangerous but legitimate ones. + +### Communication and Reporting Discipline + +Use a reusable communication layer when the task needs conclusion-first reporting, concrete evidence, visible risk, or compact next-step guidance. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | [`expression-skill`](./skills/expression-skill/README.md) | Enforces conclusion-first, concrete, checkable communication for technical work, writing, documentation, file operations, and multi-step tasks. | +| Skill | [`planning-with-files`](./skills/planning-with-files/SKILL.md) | Makes complex work persistent on disk with `task_plan.md`, `notes.md`, and deliverable files instead of relying only on transient chat context. | + +**How it works** +- lead with the conclusion instead of narration, +- prefer commands, paths, counts, checks, and observable behavior over abstract process language, +- ask clarifying questions only when ambiguity changes the outcome, +- surface risk, uncertainty, and destructive boundaries early, +- keep long-running work visible with step / checkpoint style roadmarks, +- persist multi-step work to disk with `task_plan.md` and `notes.md` instead of relying only on transient context. + +### Knowledge Extraction Workflow + +Specialized agents can mine reusable knowledge from papers and competitions. + +| Type | Name | One-line explanation | +|---|---|---| +| Agent | `paper-miner` | Extract reusable writing knowledge, structure patterns, and venue heuristics from strong papers. | +| Agent | `kaggle-miner` | Extract engineering practices and solution patterns from strong Kaggle workflows. | + +**How it works** +- extract writing patterns, venue expectations, and rebuttal strategies from papers, +- extract engineering patterns and solution structure from Kaggle workflows, +- feed those insights back into skills and reference material. + +### Skill Evolution System + +Claude Scholar also contains a self-improvement loop for its own skills. + +| Type | Name | One-line explanation | +|---|---|---| +| Skill | `skill-development` | Create new skills with clear triggers, structure, and progressive disclosure. | +| Skill | `skill-quality-reviewer` | Review skills across content quality, organization, style, and structural integrity. | +| Skill | `skill-improver` | Apply structured improvement plans to evolve existing skills. | + +**How it works** +- create new skills with clear trigger descriptions, +- review them across quality dimensions, +- apply structured improvements and iterate. + +## Documentation + +- [MCP_SETUP.md](./MCP_SETUP.md) — Zotero/browser MCP setup +- [OBSIDIAN_SETUP.md](./OBSIDIAN_SETUP.md) — Obsidian knowledge base workflow +- [CLAUDE.md](./CLAUDE.md) — lightweight Claude Code core instructions +- [CLAUDE.zh-CN.md](./CLAUDE.zh-CN.md) — Chinese companion for the lightweight core instructions +- [settings.json.template](./settings.json.template) — optional settings template for hooks/plugins/MCP + +## Project Rules + +Claude Scholar includes project rules for: +- coding style, +- agent orchestration, +- security, +- experiment reproducibility. + +These are reflected in the shipped rules and in `CLAUDE.md`. + +## Contributing + +Issues, PRs, and workflow improvements are welcome. + +If you propose changes to installer behavior, Zotero workflows, or Obsidian routing, please include: +- the user scenario, +- the current limitation, +- the expected behavior, +- and any compatibility concerns. + +## License + +MIT License. + +## Citation + +If Claude Scholar helps your research or engineering workflow, you can cite the repository as: + +```bibtex +@misc{claude_scholar_2026, + title = {Claude Scholar: Semi-automated research assistant for academic research and software development}, + author = {Gaorui Zhang}, + year = {2026}, + howpublished = {\url{https://github.com/Galaxy-Dawn/claude-scholar}}, + note = {GitHub repository} +} +``` + +## Acknowledgments + +Built with Claude Code CLI and enhanced by the open-source community. + +### References + +This project is inspired by and builds upon excellent work from the community: + +- **[everything-claude-code](https://github.com/anthropics/everything-claude-code)** - Comprehensive resource for Claude Code CLI +- **[AI-research-SKILLs](https://github.com/zechenzhangAGI/AI-research-SKILLs)** - Research-focused skills and configurations +- **[expression-skill](https://github.com/Galaxy-Dawn/expression-skill)** - Public conclusion-first communication skill reused here for reporting and response discipline +- **[nature-skills](https://github.com/Yuan1z0825/nature-skills)** - Nature-oriented writing, polishing, reviewer-response, and data-availability skills reused here with attribution + +These projects provided valuable insights and foundations for the research-oriented features in Claude Scholar. + +--- + +**For data science, AI research, and academic writing.** + +Repository: [https://github.com/Galaxy-Dawn/claude-scholar](https://github.com/Galaxy-Dawn/claude-scholar) diff --git a/文档润色流和知识库构建流/claude-scholar/README.zh-CN.md b/文档润色流和知识库构建流/claude-scholar/README.zh-CN.md new file mode 100644 index 0000000..ea9c66f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/README.zh-CN.md @@ -0,0 +1,662 @@ +
    + Claude Scholar Logo + +

    + Stars + GitCode Stars + Forks + Last Commit + License +

    + + +

    + + + Kimi Open Source Friends + +

    + + 语言: English | 中文 | 日本語 +

    支持平台: Claude Code | Codex CLI | Kimi Code CLI | OpenCode

    + +
    + +> 面向学术研究和软件开发的半自动研究助手，尤其适合计算机科学与 AI 研究者。支持 [Claude Code](https://github.com/anthropics/claude-code)、[Codex CLI](https://github.com/openai/codex)、[Kimi Code CLI](https://github.com/MoonshotAI/kimi-code) 和 [OpenCode](https://github.com/opencode-ai/opencode)，覆盖文献管理、编码、实验分析、结果报告、写作与项目知识库维护。 + +

    分支说明：main 分支对应 Claude Code 工作流。如果你使用 Codex CLI，请查看 codex 分支；如果你使用 Kimi Code CLI，请查看 kimi 分支；如果你使用 OpenCode，请查看 opencode 分支。

    + +## 最新动态 + +- **2026-06-03**: **新增 Kimi Code CLI 分支，并感谢 Kimi 对本项目的大力支持** — 已将 `kimi` 分支作为 Claude Scholar 的 Kimi Code CLI 版本纳入支持平台；感谢 Kimi 团队对本项目的持续支持与帮助。 +- **2026-05-14**: **将 `expression-skill` 提升为核心表达层，把 `planning-with-files` 恢复为默认持久规划层，并继续扩展 Nature 写作栈** — 把 [`expression-skill`](./skills/expression-skill/README.md) 明确为汇报、规划、文件操作和多步骤技术任务的结论先行表达纪律；将 [`planning-with-files`](./skills/planning-with-files/SKILL.md) 重新接回默认的落盘规划与进度跟踪工作流，用 `task_plan.md` / `notes.md` 管理复杂任务；引入用于章节起草与论证构建的 [`nature-writing`](./skills/nature-writing/README.md)；将 [`nature-polishing`](./skills/nature-polishing/README.md) 刷新到上游最新 article-pattern 版本；并继续保留 [`nature-response`](./skills/nature-response/README.md) 与 [`nature-data`](./skills/nature-data/README.md) 作为 journal-writing 栈的一部分。 +- **2026-05-13**: **证据门槛研究工作流与 `Sources/Papers` 路由完成收紧** — 新增共享的 `research-contract.md`，统一 Evidence Records、claim strength 和 Claim Promotion Gate；将研究构思、Zotero 导入、文献综合、结果报告、论文写作与 rebuttal 工作流接入同一证据契约；并明确项目论文源笔记先放在 `Sources/Papers`，通过证据门槛后再进入 `Knowledge` 或 `Writing`。 +- **2026-04-24**: **项目级 Obsidian KB 工作流完成合并** — 将 Obsidian 项目知识管理重构为以 vault 为中心的工作流，把旧的重叠记忆技能合并为四个核心技能，保留仓库本地的项目绑定元数据作为运行时层，并把项目导航改成人类优先，而不是机器注册表清单。 +- **2026-04-22**: **精简核心指令、裁剪默认 agents、安全安装生命周期与通用论文发现流程** — 将大型常驻 `CLAUDE.md` / `AGENTS.md` 改为紧凑核心指令，裁剪默认 agent 集合并保留主链路所需的核心 agents，新增基于安装状态的安全卸载支持，将 `daily-paper-generator` 扩展为面向通用主题的 arXiv / bioRxiv 检索与 Top 10 -> Top 3 -> Top 1 固定筛选流程。 +- **2026-04-15**: **提出 pubfig 与 pubtab 两个 Python package** — 推出了 [`pubfig`](https://github.com/Galaxy-Dawn/pubfig)（用于论文级 scientific figures）和 [`pubtab`](https://github.com/Galaxy-Dawn/pubtab)（用于 publication-ready tables 与 Excel↔LaTeX workflows）两个独立 Python package，为研究者提供更清晰的论文图、benchmark 表、导出控制与最终 QA 生产路径。 + +
    +查看历史更新日志 + +- **2026-04-15**: **将 [`publication-chart-skill`](./skills/publication-chart-skill/SKILL.md) 融入 Claude Scholar** — 把 [`pubfig`](https://github.com/Galaxy-Dawn/pubfig) + [`pubtab`](https://github.com/Galaxy-Dawn/pubtab) 封装成 [`publication-chart-skill`](./skills/publication-chart-skill/SKILL.md)，加入仓库，并接到 Claude Scholar 的分析/写作边界里，让论文级图表工作有了明确的交接路径，而不是继续混在通用分析或文本写作技能里。 +- **2026-03-31**: **Zotero smart-import 工作流文档完成对齐** — 围绕最新 `zotero-mcp` 的公开能力，系统更新了 Claude Scholar 的研究工作流文档：将 `zotero_add_items_by_identifier` 明确为默认论文导入入口，把 `zotero_reconcile_collection_duplicates` 设为标准导入后清理步骤，更准确地说明了来源感知 PDF cascade，同时把公开工具与内部诊断能力的边界重新讲清楚了。 +- **2026-03-31**: **README 上手路径完成刷新** — 明确了 Claude Scholar 尤其适合计算机科学与 AI 研究者，在安装说明后补充了更贴近真实使用的上手场景，进一步收紧了前置条件和分支说明，并把“如果用户本地已有 md 文件，需要手动合并”这件事写得更明确。 +- **2026-03-31**: **安装器与 hooks 行为进一步收口** — 安装器现在会保留已有的本地 `CLAUDE.md`，并把仓库版本作为 `CLAUDE.scholar.md` 旁路文件安装；同时默认 hooks 的摘要输出进一步降噪，减少临时文件和未提交文件提示的噪声，同时保留更安全的写入守卫边界。 +- **2026-03-31**: **日文文档补齐** — 为主 README 以及 `AGENTS`、`MCP_SETUP`、`OBSIDIAN_SETUP` 补充了日文文档，使 OpenCode 分支的多语言文档入口更完整。 + +- **2026-02-25**: **Codex CLI** 支持 — 新增 `codex` 分支，支持 [OpenAI Codex CLI](https://github.com/openai/codex)，包含 config.toml、40 个 skills、14 个 agents 和 sandbox 安全机制 +- **2026-02-23**: 新增 `setup.sh` 安装脚本 — 面向已有 `~/.opencode` 的带备份增量更新，自动备份 `opencode.jsonc`，以追加方式合并 `agent/mcp/permission/plugin` +- **2026-02-21**: **OpenCode** 支持 — Claude Scholar 现已支持 [OpenCode](https://github.com/opencode-ai/opencode) 作为替代 CLI；切换到 `opencode` 分支获取兼容配置 +- **2026-02-20**: 双语文档 — 维护英文与中文入口文档，便于不同读者阅读 +- **2026-02-15**: Zotero MCP 集成 — 新增 `/zotero-review` 和 `/zotero-notes` 命令，更新 `research-ideation` skill 添加 Zotero 集成指南，增强 `literature-reviewer` agent 支持 Zotero MCP 自动论文导入、集合管理、全文阅读和引用导出 +- **2026-02-14**: Hooks 优化 — `security-guard` 重构为两层系统（Block + Confirm），`skill-forced-eval` 按 6 类分组并切换为静默扫描模式，`session-start` 限制显示前 5 项，`session-summary` 新增 30 天日志自动清理，`stop-summary` 分别显示新增/修改/删除计数；移除废弃的 shell 脚本（lib/common.sh、lib/platform.sh） +- **2026-02-11**: 大版本更新 — 新增 10 个 skills（research-ideation、results-analysis、citation-verification、review-response、paper-self-review、post-acceptance、daily-coding、frontend-design、ui-ux-pro-max、web-design-reviewer）、7 个 agents、8 个研究工作流命令、2 条新规则（security、experiment-reproducibility）；重构主配置文档；涉及 89 个文件 +- **2026-01-26**: 所有 Hooks 重写为跨平台 Node.js 版本；README 完全重写；扩展 ML 论文写作知识库；合并 PR #1（跨平台支持） +- **2026-01-25**: 项目正式开源，v1.0.0 发布，包含 25 个 skills（architecture-design、bug-detective、git-workflow、kaggle-learner、scientific-writing 等）、2 个 agents（paper-miner、kaggle-miner）、30+ 个命令（含 SuperClaude 命令套件）、5 个 Shell Hooks、2 条规则（coding-style、agents） + +
    + +## 快速导航 + +| 部分 | 作用 | +|---|---| +| [为什么使用 Claude Scholar](#为什么使用-claude-scholar) | 快速理解项目定位和适用场景。 | +| [核心工作流](#核心工作流) | 查看从研究构思到发表的主链路。 | +| [快速开始](#快速开始) | 选择完整、最小或选择性安装方式。 | +| [上手场景](#上手场景) | 查看安装完成后几种最常见的上手场景。 | +| [集成能力](#集成能力) | 了解 Zotero 和 Obsidian 如何接入工作流。 | +| [主要工作流](#主要工作流) | 查看核心研究与开发工作流。 | +| [支撑工作流](#支撑工作流) | 查看支撑主工作流的后台机制。 | +| [文档入口](#文档入口) | 快速跳转到 setup、配置和模板文档。 | +| [引用](#引用) | 在论文、报告或项目文档中引用 Claude Scholar。 | + +## 为什么使用 Claude Scholar + +Claude Scholar **不是**那种试图替代研究者、追求端到端全自动化科研的系统。 + +它的核心思想很简单： + +> **以人的决策为中心，让助手去加速科研流程，而不是替人做最终判断。** + +这意味着 Claude Scholar 更适合承担科研中那些高重复、重结构、但仍需要人来把关的环节，例如文献整理、知识沉淀、实验分析、结果汇报和写作辅助；而真正关键的判断始终应该由研究者自己做出： + +- 这个问题值不值得做， +- 哪些文献真正重要， +- 哪些假设值得继续验证， +- 哪些结果足够可信， +- 以及什么应该继续推进、写成论文、投稿，或者及时放弃。 + +换句话说，Claude Scholar 是一个**以人类决策为中心的半自动研究助手**，而不是一个“全自动科研代理”。 + +## 更适合谁 + +Claude Scholar 当前尤其适合： + +- **计算机科学研究者**：需要在文献、代码、实验和论文写作之间频繁切换； +- **AI / ML 研究者**：希望用一套工作流串起构思、实现、分析、报告和 rebuttal； +- **研究工程师与研究生**：希望引入更强的流程结构，但不放弃人的判断； +- **偏软件与计算驱动的学术项目**：能够直接受益于 Zotero、Obsidian、CLI 自动化和可追踪的项目记忆。 + +它当然也可以帮助其他研究场景，但当前这套工作流的设计重心，最贴近计算机科学、AI 以及相邻的计算型研究。 + +## 核心工作流 + +Claude Scholar 将研究工作路由为一条可追踪路径： +`问题 -> 证据 -> 实验 -> 分析 -> 论断 -> 写作`。 +每个阶段都应该保留：已知什么、不确定什么、下一步该做什么决定。 + +- **研究构思**：把模糊主题收敛成具体研究问题、研究空白和初步计划。 +- **文献工作流**：通过 Zotero 文献集合检索、导入、组织并阅读论文。 +- **论文笔记**：把论文转成结构化阅读笔记和可复用论点。 +- **知识库沉淀**：将稳定知识写入 Obsidian，并按 `Sources / Knowledge / Experiments / Results / Results/Reports / Writing / Daily / Maps` 路由整理。 +- **实验推进**：跟踪假设、实验线、运行历史、关键发现和下一步动作。 +- **严格分析**：使用 `results-analysis` 生成严谨统计、真实科研图和分析产物。 +- **结果报告**：使用 `results-report` 生成完整实验复盘报告，并写回 Obsidian。 +- **写作与发表**：把稳定结论延伸到综述、论文、rebuttal、演示文稿、海报和传播材料中。 + +## 快速开始 + +### 系统要求 + +- [Claude Code](https://github.com/anthropics/claude-code) +- Git +- （可选）Python + [uv](https://docs.astral.sh/uv/) 用于 Python 开发 +- （可选）[Zotero](https://www.zotero.org/) + [Galaxy-Dawn/zotero-mcp](https://github.com/Galaxy-Dawn/zotero-mcp) 用于文献工作流 +- （可选）[Obsidian](https://obsidian.md/) 用于项目知识库工作流 + +### 选项 1：完整安装（推荐） + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +bash /tmp/claude-scholar/scripts/setup.sh +``` + +**Windows**：请使用 Git Bash / WSL 运行安装脚本。 + +安装器现在支持**带备份的安全增量更新**： +- 更新仓库托管的 `skills/commands/agents/rules/hooks/scripts/CLAUDE*.md` +- 将被覆盖的文件备份到 `~/.claude/.claude-scholar-backups//` +- 同时把 `settings.json` 备份为 `settings.json.bak` +- 如果已存在 `~/.claude/CLAUDE.md`，则保留原文件，并把仓库版本另存为 `~/.claude/CLAUDE.scholar.md` +- 如果已存在 `~/.claude/CLAUDE.zh-CN.md`，则保留原文件，并把仓库版本另存为 `~/.claude/CLAUDE.zh-CN.scholar.md` +- 保留已有的 `env`、模型/provider 配置、API key、permissions，以及当前 `mcpServers` 的现有取值 +- 对 hooks 采用追加缺失项的方式，而不是整体替换 + +**重要 CLAUDE 说明**：如果你原来就有自己的 `~/.claude/CLAUDE.md` 或 `~/.claude/CLAUDE.zh-CN.md`，安装后请查看 `~/.claude/CLAUDE.scholar.md` 和 `~/.claude/CLAUDE.zh-CN.scholar.md`，并将其中你需要的 Claude Scholar 内容按需合并到你自己的文件里；不要假设这些旁路文件会自动生效。 + +以后做增量更新时： + +```bash +cd /tmp/claude-scholar +git pull --ff-only +bash scripts/setup.sh +``` + +以后如果要卸载： + +```bash +cd /tmp/claude-scholar +bash scripts/uninstall.sh +``` + +安装器现在还会写入： +- `~/.claude/.claude-scholar-manifest.txt`：记录 Claude Scholar 实际管理的文件 +- `~/.claude/.claude-scholar-install-state`：记录安全卸载所需的 ownership 元数据 + +卸载脚本只会删除 install state 中明确记录的文件和 settings 条目，不会再根据当前 repo 工作树去猜测所有权。 + +### 选项 2：最小化安装 + +只安装一组较小的研究工作流子集： + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +mkdir -p ~/.claude/hooks ~/.claude/skills +cp /tmp/claude-scholar/hooks/*.js ~/.claude/hooks/ +cp -r /tmp/claude-scholar/skills/ml-paper-writing ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/research-ideation ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/results-analysis ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/results-report ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/review-response ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/writing-anti-ai ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/git-workflow ~/.claude/skills/ +cp -r /tmp/claude-scholar/skills/bug-detective ~/.claude/skills/ +``` + +**安装后**：最小化/手动安装**不会自动合并** `settings.json`；请按需从 `settings.json.template` 复制你需要的 hooks 或 MCP 条目。如果你已经有自己的 `~/.claude/CLAUDE.md` 或 `~/.claude/CLAUDE.zh-CN.md`，也请把仓库提供的相关内容按需合并到你的文件里，而不是直接覆盖。 + +### 选项 3：选择性安装 + +只复制你需要的部分： + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar +cd /tmp/claude-scholar + +cp hooks/*.js ~/.claude/hooks/ +cp -r skills/latex-conference-template-organizer ~/.claude/skills/ +cp -r skills/architecture-design ~/.claude/skills/ +cp agents/paper-miner.md ~/.claude/agents/ +cp rules/coding-style.md ~/.claude/rules/ +cp rules/agents.md ~/.claude/rules/ +``` + +**安装后**：选择性/手动安装**不会自动合并** `settings.json`；请按需从 `settings.json.template` 复制你需要的 hooks 或 MCP 条目。如果你已经有自己的 `~/.claude/CLAUDE.md` 或 `~/.claude/CLAUDE.zh-CN.md`，也请把仓库提供的相关内容按需合并到你的文件里，而不是直接覆盖。 + +### 选项 4：插件市场安装 + +**第一步：安装插件** + +```bash +/plugin marketplace add Galaxy-Dawn/claude-scholar +/plugin install claude-scholar@claude-scholar +``` + +自动加载所有 skills、commands、agents 和 hooks。安装时可选择作用范围：user（所有项目）或 project（单个项目）。 + +**第二步：安装 Rules（必须）** + +Claude Code 插件无法自动分发 rules，需要手动安装： + +```bash +git clone https://github.com/Galaxy-Dawn/claude-scholar.git /tmp/claude-scholar + +# 用户级（所有项目生效） +mkdir -p ~/.claude/rules +cp /tmp/claude-scholar/rules/*.md ~/.claude/rules/ + +# 或项目级（仅当前项目生效） +mkdir -p .claude/rules +cp /tmp/claude-scholar/rules/*.md .claude/rules/ +``` + +**安装后**：插件安装**不会**自动加载 `CLAUDE.md` 或配置 `settings.json`；如果你已经有自己的 `~/.claude/CLAUDE.md` 或 `~/.claude/CLAUDE.zh-CN.md`，也请把仓库提供的相关内容按需合并到你的文件里，而不是假设插件会自动应用。如需 Zotero MCP 或其他集成，请参阅[集成能力](#集成能力)部分手动设置。 + +## 上手场景 + +安装完成后，最简单的上手方式就是直接用自然语言描述你的任务，不需要先把整套系统全部背下来。下面给几种最常见、也最实用的起步场景。 + +### 1. 启动一个新的研究主题 +**你可以这样说：** +> 帮我围绕[你的研究主题]启动研究。我想先得到一个基于文献的初步计划、关键开放问题，以及接下来最具体的推进步骤。 + +**Claude Scholar 通常会帮助你：** +- 澄清主题并收敛研究问题， +- 给出值得优先看的文献方向， +- 形成初始研究计划或假设列表， +- 如果你在用 Zotero / Obsidian，还可以把工作进一步路由进去。 + +### 2. 回顾一个 Zotero 文献集合 +**你可以这样说：** +> 帮我回顾我在 Zotero 里关于 brain foundation models 的文献集合，并总结其中的主要方向、研究空白，以及最值得继续推进的下一步。 + +**典型输出包括：** +- 按主题分组的论文图景， +- 一段简明文献综合， +- research gap 分析， +- 值得继续推进的候选研究方向。 + +### 3. 分析已经完成的实验结果 +**你可以这样说：** +> 帮我分析这个实验目录里的结果，看看不同 runs 之间到底变了什么，并输出一份面向决策的总结。 + +**典型输出包括：** +- 指标对比， +- ablation 或 error analysis 建议， +- 一份结果总结，说明哪些结论比较稳、哪些还不够稳、下一步该跑什么。 + +### 4. 起草论文段落或 rebuttal 回复 +**你可以这样说：** +> 请基于这个项目当前已有的发现和论文笔记，帮我起草相关工作这一节。 + +或者： + +> 请根据这些审稿人意见，帮我起草一版 rebuttal。 + +**典型输出包括：** +- 结构化的段落草稿， +- 更清楚的论证链条， +- 论断与证据的对应关系， +- 还需要补验证或补材料的点。 + +### 使用建议 +- 先从一个具体任务开始，而不是一上来让系统”把所有事情都做了”。 +- 如果你已经有自己的本地 `CLAUDE.md` 文件，请把你需要的 Claude Scholar 内容按需合并进去，不要假设旁路文件会自动生效。 +- Zotero 和 Obsidian 都不是强制的，但如果你希望得到可长期复用的文献笔记或项目记忆，而不是一次性聊天输出，它们会非常有帮助。 + +## 平台支持 + +Claude Scholar 目前面向以下 CLI 工作流： + +- **Claude Code** — 主安装目标 +- **Codex CLI** — 支持对应工作流与文档 +- **OpenCode** — 作为替代 CLI 支持 + +顶层目标一致：研究、编码、实验、报告、写作、项目知识库维护。 + +## 集成能力 + +### Zotero + +适合这些场景： +- 通过 DOI / arXiv / URL 导入论文 +- 按 collection 批量阅读论文 +- 通过 Zotero MCP 读取全文 +- 生成详细论文笔记与文献综合分析 + +详见 [MCP_SETUP.zh-CN.md](./MCP_SETUP.zh-CN.md)。 + +### Obsidian + +适合这些场景： +- 维护以文件系统为核心的项目知识库 +- 管理 `Sources/` 与 `Knowledge/` +- 管理 `Experiments/` +- 管理 `Results/` 与 `Results/Reports/` +- 管理 `Writing/`、`Daily/` 与 `Maps/` + +详见 [OBSIDIAN_SETUP.zh-CN.md](./OBSIDIAN_SETUP.zh-CN.md)。 + +## 主要工作流 + +完整学术研究生命周期 —— 从研究构思到发表的 7 个阶段。 + +### 1. 研究构思（Zotero 集成） + +从想法生成到文献管理的一体化研究启动流程。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `research-ideation` | 把模糊研究主题收敛成结构化问题、研究空白分析和初始研究计划。 | +| Agent | `literature-reviewer` | 搜索、分类并综合论文，形成可执行的文献图景。 | +| Command | `/research-init` | 从文献检索、Zotero 组织到研究问题卡片；只有通过证据门槛时才生成研究提案草稿。 | +| Command | `/zotero-review` | 对已有 Zotero collection 做结构化文献综述与比较。 | +| Command | `/zotero-notes` | 批量阅读 Zotero collection，并生成结构化论文阅读笔记。 | + +**工作方式** +- **5W1H 头脑风暴**：把模糊主题收敛成结构化问题。 +- **文献检索与导入**：搜索论文、提取 DOI/arXiv/URL、导入 Zotero，并组织到主题文献集合。 +- **PDF 与全文**：能挂 PDF 就挂 PDF，能读全文就读全文，必要时回退到摘要分析。 +- **研究空白分析**：识别文献型、方法型、应用型、跨学科型、时间型等不同类型的研究空白。 +- **研究问题与规划**：把文献综述进一步转成明确研究问题、初始假设和下一步计划。 +- **证据门槛**：在论断进入 `Knowledge`、`Writing` 或研究提案之前，保留弱来源、项目假设和缺失证据。 + +**典型产出** +- 带有假设、证据需求、证伪条件和下一步动作的研究问题卡片 +- 文献综述笔记 +- 结构化 Zotero 文献集合 +- 证据足够时生成研究提案；否则只生成研究方向或初步整理草稿 + +### 2. ML 项目开发 + +面向实验代码的可维护 ML 项目开发工作流。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `architecture-design` | 在新增可注册组件或模块时设计可维护的 ML 项目结构。 | +| Skill | `git-workflow` | 约束分支规范、commit 规范和更安全的协作流程。 | +| Skill | `bug-detective` | 系统化排查 stack trace、shell 报错和代码路径问题。 | +| Agent | `code-reviewer` | 审查改动代码的正确性、可维护性和实现质量。 | +| Agent | `tdd-guide` | 当任务明确需要 TDD 路径时，提供聚焦的测试驱动实现指导。 | +| Command | `/plan` | 在编码前创建或细化实现计划。 | +| Command | `/commit` | 为当前改动生成符合规范的 commit。 | +| Command | `/code-review` | 对当前代码改动执行一次聚焦审查。 | +| Command | `/tdd` | 以小步、测试驱动的方式推进功能实现。 | + +**工作方式** +- **结构设计**：在合适场景下使用 Factory / Registry 模式组织 ML 组件。 +- **代码质量**：保持文件规模、类型提示与配置驱动设计。 +- **问题排查**：系统化处理 stack trace、shell 报错和代码路径问题。 +- **Git 纪律**：维持分支策略、commit 规范和更安全的合并/rebase 流程。 + +### 3. 实验分析 + +严格实验分析工作流：统计、科研图、分析产物与实验后报告。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `results-analysis` | 生成由严格统计、真实科研图和分析附录组成的严格分析产物包。 | +| Skill | `results-report` | 把分析产物组织成完整实验总结报告，明确结论、限制和下一步动作。 | +| Command | `/analyze-results` | 执行阻塞项优先的实验后工作流：先验证证据，能严格分析时再分析，证据包足够时才生成报告。 | + +**工作方式** +- **数据处理**：读取实验日志、metrics 文件和结果目录。 +- **阻塞项优先门槛**：先锁定分析单位、主指标、seeds/folds/runs、来源追踪和比较族。 +- **统计检验**：在合适前提下执行 t-test / ANOVA / Wilcoxon 等严格统计检验。 +- **科研可视化**：生成真实科研图和解释线索，而不是只给模糊的绘图建议。 +- **消融与比较**：分析组件贡献、性能取舍和稳定性。 +- **实验后报告**：把分析产物包转成完整实验后总结报告，包含结论、限制和下一步动作。 + +**典型产出** +- `analysis-report.md` +- `stats-appendix.md` +- `figure-catalog.md` +- `figures/` +- 写入 Obsidian `Results/Reports/` 的实验总结报告 +- 证据不足时生成阻塞项摘要或审计笔记 + +### 4. 论文写作 + +从结构准备到草稿迭代的系统化论文写作工作流。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `ml-paper-writing` | 基于 repo、实验结果和文献上下文撰写投稿导向的 ML/AI 论文。 | +| Skill | [`nature-writing`](./skills/nature-writing/README.md) | 根据 claims、figures、results、notes 或中文草稿起草或重建 Nature 风格的论文章节。 | +| Skill | [`nature-polishing`](./skills/nature-polishing/README.md) | 将稿件内容润色、重组或翻译为更接近 Nature 风格的精炼英文。 | +| Skill | [`nature-response`](./skills/nature-response/README.md) | 为 Nature 系修回撰写、审查或重写逐点 reviewer response。 | +| Skill | [`nature-data`](./skills/nature-data/README.md) | 准备 Nature 风格的 Data Availability、repository plan 和 FAIR 元数据检查。 | +| Skill | `citation-verification` | 检查参考文献、元数据和论断-引用对齐，避免引用错误。 | +| Skill | `writing-anti-ai` | 减少机械化表述，提升清晰度、节奏和更自然的学术语气。 | +| Skill | `latex-conference-template-organizer` | 把混乱的会议模板整理成 Overleaf-ready 写作结构。 | +| Agent | `paper-miner` | 从高质量论文中提炼可复用的写作模式、结构和投稿经验。 | +| Command | `/mine-writing-patterns` | 读取论文并把可复用写作知识合并进当前已安装的 paper-miner 写作记忆。 | + +**工作方式** +- **模板准备**：把会议模板清理成 Overleaf-ready 结构。 +- **期刊风格润色**：在需要时加强段落逻辑、hedging 和 section moves，使表达更接近 Nature 风格。 +- **审稿回复**：把大修/小修意见组织成可审计的逐点 response package。 +- **数据可用性**：准备 Nature 风格的数据仓库方案、dataset citation 和 availability statement。 +- **引用核验**：检查参考文献、元数据和论断-引用对齐。 +- **系统化写作**：基于 repo、实验结果和文献上下文逐节写作，但未被证据支持的论断必须显式标记。 +- **论断台账**：贡献、结果和相关工作对比都应能追溯到证据；否则保留为推测性表述。 +- **风格打磨**：减少 AI 痕迹，改善节奏、清晰度和学术语气。 + +### 5. 论文自审 + +投稿前的质量保障工作流。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `paper-self-review` | 在投稿前系统检查结构、逻辑、引用、图表和合规性。 | + +**工作方式** +- **结构检查**：检查逻辑流、章节平衡和叙事连贯性。 +- **逻辑校验**：检查论断-证据对齐、假设清晰度和论证一致性。 +- **论断审计**：检查主要论断是否被证据支持，削弱过强表述，并在证据不足时保留不确定性。 +- **引用审计**：检查引用准确性与完整性。 +- **图表质量**：检查图注/表注完整性、可读性和可访问性。 +- **合规性检查**：检查页数限制、格式和披露要求。 + +### 6. 投稿与 Rebuttal + +投稿准备和审稿回复工作流。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `review-response` | 把审稿意见组织成基于证据的 rebuttal 工作流。 | +| Agent | `rebuttal-writer` | 如果当前运行时可用，可作为起草专业、礼貌且结构清晰 rebuttal 的辅助 agent。 | +| Command | `/rebuttal` | 基于审稿意见和现有证据生成带证据锚点的 rebuttal 草稿，未解决项必须显式标出。 | + +**工作方式** +- **投稿前检查**：检查会议/期刊格式、匿名化和清单要求。 +- **审稿意见分析**：把审稿意见分类成可执行的问题。 +- **回复策略**：决定是接受、反驳、澄清还是补实验。 +- **Rebuttal 写作**：生成结构化、基于证据、语气专业的回复文档，并保留证据锚点与未解决项。 + +### 7. 录用后处理 + +论文录用后的会议准备与研究传播工作流。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `post-acceptance` | 支持论文录用后的报告、海报和传播材料准备。 | +| Command | `/presentation` | 生成会议报告的结构和讲解指导。 | +| Command | `/poster` | 整理论文内容并生成海报版式与内容指导。 | +| Command | `/promote` | 起草面向外部传播的摘要、帖子或长帖内容。 | + +**工作方式** +- **报告准备**：准备报告结构和演示文稿指导。 +- **海报整理**：整理海报内容层级和版式。 +- **传播内容**：生成社交媒体、博客或简明研究摘要。 + +## 支撑工作流 + +这些工作流运行在主工作流背后，用来增强整体使用体验。 + +### Obsidian 项目知识库 + +把 Obsidian 当作项目作用域的稳定知识层，而不是随手堆放笔记的地方。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `obsidian-project-kb-core` | 负责项目级 KB 的初始化、路由、注册表、索引、每日记录和生命周期。 | +| Skill | `obsidian-source-ingestion` | 把外部材料写入 `Sources/Papers`、`Sources/Web`、`Sources/Docs`、`Sources/Data`、`Sources/Interviews` 或 `Sources/Notes`。 | +| Skill | `obsidian-literature-workflow` | 管理从 `Sources/Papers` 到 `Knowledge`、`Writing`、`Maps/literature.canvas` 的文献工作流。 | +| Skill | `obsidian-kb-artifacts` | 处理 wikilink、注册表表格、canvas、可选 `.base` 和链接修复等 Obsidian 原生产物。 | +| Command | `/kb-init` | 在 `Research/{project-slug}/` 下初始化以 vault 为中心的 KB。 | +| Command | `/kb-status` | 汇总当前已绑定项目 KB 的状态。 | +| Command | `/kb-ingest` | 将新的来源材料路由到正确的规范位置。 | +| Command | `/kb-log` | 保守更新当天 `Daily/` 和相关项目表面。 | +| Command | `/kb-sync` | 运行确定性的 KB 维护，刷新注册表、索引、每日记录和运行时绑定状态。 | +| Command | `/kb-links` | 修复或增强规范 KB 笔记之间的 wikilink。 | +| Command | `/kb-promote` | 将 Daily 或来源笔记中稳定的内容提升为规范笔记。 | +| Command | `/kb-index` | 重建 `02-Index.md` 这个人类导航页。 | +| Command | `/kb-lint` | 运行确定性的 KB 健康检查并更新 `_system/lint-report.md`。 | +| Command | `/kb-archive` | 归档、分离、清除或重命名 KB 对象，并保持链接与注册表一致。 | +| Command | `/kb-map` | 在默认 literature canvas 之外，按需生成或修复显式请求的 KB 产物。 | +| Command | `/kb-literature-review` | 从 `Sources/Papers` 生成经过证据门槛的文献综合，并写入 `Knowledge`、可选 `Writing` 和 `Maps/literature.canvas`。 | + +**工作方式** +- 将已有 repo 绑定到 Obsidian vault +- 把稳定知识路由进 `Sources / Knowledge / Experiments / Results / Results/Reports / Writing / Daily / Maps` +- 以保守方式维护 `Daily/` 和仓库本地绑定元数据 +- 把新的来源材料路由进正确的规范笔记 +- 防止只有摘要或网页占位来源支撑稳定论断 +- 只有在显式请求时才生成额外的 `.base` 或 canvas +- 用 `/kb-sync` 做确定性重同步，用 `/kb-links` 做独立的链接修复 + +**笔记语言配置** + +生成和同步 Obsidian 笔记时，语言按以下优先级解析： +1. 项目配置：`.claude/project-memory/registry.yaml` 中的 `note_language` +2. 环境变量：`OBSIDIAN_NOTE_LANGUAGE` +3. 默认值：`en` + +说明：文件名目前仍叫 `registry.yaml`，但其磁盘格式实际上是 JSON。 + +项目级示例： + +```json +{ + "projects": { + "my-project": { + "project_id": "my-project", + "vault_root": "/path/to/vault/Research/my-project", + "note_language": "zh-CN" + } + } +} +``` + +同步时会同时兼容英文和中文 section heading，因此切换配置后，历史英文/中文笔记都可以继续安全更新。 + +### 自动化约束工作流 + +跨平台 hooks 自动执行日常检查与提醒。 + +**Hook 列表** +- `skill-forced-eval.js` +- `session-start.js` +- `session-summary.js` +- `stop-summary.js` +- `security-guard.js` + +**工作方式** +- **用户提问前**：评估当前 prompt 应该触发哪些 skills，并补充相关工作流提示。 +- **会话开始时**：显示 Git 状态、可用命令和项目记忆上下文。 +- **会话结束或停止时**：总结工作内容，并提醒最小维护动作。 +- **安全防护**：拦截灾难性命令，并对危险但合理的操作要求确认。 + +### 表达与汇报约束层 + +当任务需要结论先行汇报、具体证据、可见风险或紧凑下一步时，使用可复用的沟通表达层。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | [`expression-skill`](./skills/expression-skill/README.md) | 为技术工作、写作、文档、文件操作和多步骤任务提供结论先行、具体、可核查的表达约束。 | +| Skill | [`planning-with-files`](./skills/planning-with-files/SKILL.md) | 让复杂任务把计划、进度与中间发现落到 `task_plan.md`、`notes.md` 和交付文件里，而不是只依赖瞬时对话上下文。 | + +**工作方式** +- 先给结论，不先叙述过程， +- 优先使用命令、路径、数量、检查结果和可观察行为，而不是抽象过程词， +- 只有在歧义会改变结果时才追问， +- 尽早暴露风险、不确定性和破坏性边界， +- 对长任务持续给出 step / checkpoint 形式的可见路标， +- 对多步骤任务用 `task_plan.md` 和 `notes.md` 做持久化规划，而不是只依赖瞬时上下文。 + +### 知识提炼工作流 + +专门的 agents 可持续提炼论文和竞赛中的可复用知识。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Agent | `paper-miner` | 从高质量论文中提炼可复用的写作知识、结构模式和投稿经验。 | +| Agent | `kaggle-miner` | 从优秀 Kaggle 工作流中提炼工程实践和解决方案模式。 | + +**工作方式** +- 从论文中提炼写作模式、会议要求和 rebuttal 策略 +- 从 Kaggle 工作流中提炼工程模式和解决方案结构 +- 再把这些知识回流进 skills 与 references 中。 + +### 技能进化系统 + +Claude Scholar 也内置了自我改进的 skill 工作流。 + +| 类型 | 名字 | 一句话解释 | +|---|---|---| +| Skill | `skill-development` | 创建具备清晰触发条件、结构和渐进展开方式的新技能模块。 | +| Skill | `skill-quality-reviewer` | 从内容质量、组织方式、表达风格和结构完整性审查 skill。 | +| Skill | `skill-improver` | 根据结构化改进计划持续优化已有 skills。 | + +**工作方式** +- 创建带有清晰触发描述的新 skill +- 按多个质量维度审查 skill +- 合并改进建议并持续迭代 + +## 文档入口 + +- [MCP_SETUP.zh-CN.md](./MCP_SETUP.zh-CN.md) — Zotero / 浏览器 MCP 配置 +- [OBSIDIAN_SETUP.zh-CN.md](./OBSIDIAN_SETUP.zh-CN.md) — Obsidian 项目知识库工作流 +- [CLAUDE.md](./CLAUDE.md) — 轻量版 Claude Code 核心指令 +- [CLAUDE.zh-CN.md](./CLAUDE.zh-CN.md) — 轻量核心指令的中文 companion 文件 +- [settings.json.template](./settings.json.template) — hooks / plugins / MCP 的可选模板 + +## 项目规则 + +Claude Scholar 包含以下方面的项目规则： +- 代码风格 +- agent 编排 +- 安全约束 +- 实验可复现性 + +这些规则体现在仓库附带的 rules 以及 `CLAUDE.md` 中。 + +## 贡献 + +欢迎提交 issue、PR 和工作流改进建议。 + +如果你想改 installer、Zotero 工作流或 Obsidian 路由，建议在提案中说明： +- 用户场景 +- 当前限制 +- 预期行为 +- 兼容性影响 + +## 许可证 + +MIT 许可证。 + +## 引用 + +如果 Claude Scholar 对你的研究或工程工作流有帮助，你可以按下面方式引用： + +```bibtex +@misc{claude_scholar_2026, + title = {Claude Scholar: Semi-automated research assistant for academic research and software development}, + author = {Gaorui Zhang}, + year = {2026}, + howpublished = {\url{https://github.com/Galaxy-Dawn/claude-scholar}}, + note = {GitHub repository} +} +``` + +## 致谢 + +使用 Claude Code CLI 构建，并由开源社区增强。 + +### 参考资料 + +本项目受到社区优秀工作的启发和构建： + +- **[everything-claude-code](https://github.com/anthropics/everything-claude-code)** - Claude Code CLI 的综合资源 +- **[AI-research-SKILLs](https://github.com/zechenzhangAGI/AI-research-SKILLs)** - 研究导向的技能和配置 +- **[expression-skill](https://github.com/Galaxy-Dawn/expression-skill)** - 这里复用了其公开的结论先行表达 skill，用于汇报和回应约束 +- **[nature-skills](https://github.com/Yuan1z0825/nature-skills)** - 这里统一复用了其 Nature 风格的章节起草、学术润色、审稿回复和数据可用性 skills，并保留来源引用 + +这些项目为 Claude Scholar 的研究导向功能提供了宝贵的见解和基础。 + +--- + +**面向数据科学、AI 研究和学术写作。** + +仓库：[https://github.com/Galaxy-Dawn/claude-scholar](https://github.com/Galaxy-Dawn/claude-scholar) diff --git a/文档润色流和知识库构建流/claude-scholar/agents/code-reviewer.md b/文档润色流和知识库构建流/claude-scholar/agents/code-reviewer.md new file mode 100644 index 0000000..ad4d1b7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/agents/code-reviewer.md @@ -0,0 +1,107 @@ +--- +name: code-reviewer +description: Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code. MUST BE USED for all code changes. +tools: ["Read", "Grep", "Glob", "Bash"] +model: opus +--- + +You are a senior code reviewer ensuring high standards of code quality and security. + +When invoked: +1. Run git diff to see recent changes +2. Focus on modified files +3. Begin review immediately + +Review checklist: +- Code is simple and readable +- Functions and variables are well-named +- No duplicated code +- Proper error handling +- No exposed secrets or API keys +- Input validation implemented +- Good test coverage +- Performance considerations addressed +- Time complexity of algorithms analyzed +- Licenses of integrated libraries checked + +Provide feedback organized by priority: +- Critical issues (must fix) +- Warnings (should fix) +- Suggestions (consider improving) + +Include specific examples of how to fix issues. + +## Security Checks (CRITICAL) + +- Hardcoded credentials (API keys, passwords, tokens) +- SQL injection risks (string concatenation in queries) +- XSS vulnerabilities (unescaped user input) +- Missing input validation +- Insecure dependencies (outdated, vulnerable) +- Path traversal risks (user-controlled file paths) +- CSRF vulnerabilities +- Authentication bypasses + +## Code Quality (HIGH) + +- Large functions (>50 lines) +- Large files (>800 lines) +- Deep nesting (>4 levels) +- Missing error handling (try/except) +- print() statements in production code +- Mutable default arguments +- Missing tests for new code +- Missing type hints (Python 3.6+) + +## Performance (MEDIUM) + +- Inefficient algorithms (O(n²) when O(n log n) possible) +- GIL contention in multi-threaded code +- Memory leaks (circular references, unclosed resources) +- Missing lru_cache for repeated function calls +- Inefficient data structure choices (list vs set vs dict) +- N+1 database queries +- Blocking I/O in async functions +- Unnecessary list comprehensions when generators suffice + +## Best Practices (MEDIUM) + +- Emoji usage in code/comments +- TODO/FIXME without tickets +- Missing docstrings for public APIs +- Accessibility issues (missing ARIA labels, poor contrast) +- Poor variable naming (x, tmp, data) +- Magic numbers without explanation +- Inconsistent formatting +- Missing if __name__ == "__main__" guards + +## Review Output Format + +For each issue: +``` +[CRITICAL] Hardcoded API key +File: src/api/client.py:42 +Issue: API key exposed in source code +Fix: Move to environment variable + +api_key = "sk-abc123" # ❌ Bad +api_key = os.getenv("API_KEY") # ✓ Good +``` + +## Approval Criteria + +- ✅ Approve: No CRITICAL or HIGH issues +- ⚠️ Warning: MEDIUM issues only (can merge with caution) +- ❌ Block: CRITICAL or HIGH issues found + +## Project-Specific Guidelines (Example) + +Add your project-specific checks here. Examples: +- Follow MANY SMALL FILES principle (200-400 lines typical) +- No emojis in codebase +- Use immutability patterns (spread operator) +- Verify database RLS policies +- Check AI integration error handling +- Validate cache fallback behavior + +Customize based on your project's `CLAUDE.md` or skill files. diff --git a/文档润色流和知识库构建流/claude-scholar/agents/kaggle-miner.md b/文档润色流和知识库构建流/claude-scholar/agents/kaggle-miner.md new file mode 100644 index 0000000..c2f7d90 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/agents/kaggle-miner.md @@ -0,0 +1,166 @@ +--- +name: kaggle-miner +description: Use this agent when the user provides a Kaggle competition URL or asks to learn from Kaggle winning solutions. Examples: + + +Context: User wants to extract knowledge from a Kaggle competition +user: "Learn from this Kaggle competition: https://www.kaggle.com/competitions/xxx" +assistant: "I'll dispatch the kaggle-miner agent to analyze the winning solutions and extract knowledge." + +The kaggle-miner agent specializes in extracting technical knowledge from Kaggle competitions. + + + + +Context: User asks about Kaggle best practices +user: "What are the latest techniques for NLP competitions on Kaggle?" +assistant: "Dispatching kaggle-miner to search and extract knowledge from recent Kaggle NLP competitions." + +The agent can proactively search and learn from multiple competitions. + + + +model: inherit +color: blue +--- + +You are the Kaggle Knowledge Miner, specializing in extracting and organizing technical knowledge from Kaggle competition winning solutions. + +**Your Core Responsibilities:** +1. Fetch and analyze Kaggle competition discussions and winning solutions +2. Extract technical knowledge following the kaggle-learner skill's Knowledge Extraction Standard: + - **Competition Brief**: competition background, task description, data scale, evaluation metrics + - **Original Summaries**: brief overview of top solutions + - **Detailed Technical Analysis of Top Solutions**: core techniques and implementation details of Top 20 solutions ⭐ + - **Code Templates**: reusable code templates + - **Best Practices**: best practices and common pitfalls + - **Metadata**: data source tags and dates +3. Categorize knowledge by domain (NLP/CV/Time Series/Tabular/Multimodal) +4. Update the kaggle-learner skill's knowledge files with new findings + +**Analysis Process:** +1. Use mcp__web_reader__webReader to fetch the Kaggle competition discussion page +2. Extract comprehensive competition information: + - **Competition Brief**: competition background, organizer, task description, dataset scale, evaluation metrics, competition constraints + - Search for top solutions (Top 20 or as many as possible), identify keywords like "1st Place", "Gold", "Winner" +3. Extract front-runner detailed technical analysis for each top solution: + - Ranking and team/author + - Core techniques list (3-6 key technical points) + - Implementation details (specific parameters, model configurations, data, experimental results) +4. Extract additional content: + - Original summaries (brief overview of top solutions) + - Reusable code templates and patterns + - Best practices and common pitfalls +5. Determine the category (NLP/CV/Time Series/Tabular/Multimodal) +6. Generate a filename for the competition (lowercase, hyphen-separated, e.g., "birdclef-plus-2025.md") +7. Create a new knowledge file at `~/.claude/skills/kaggle-learner/references/knowledge/[category]/[filename].md` +8. Write the extracted content following the competition file template + +**Quality Standards:** +- Extract accurate, actionable technical knowledge +- **Detailed technical analysis format for top solutions**: + ```markdown + **Nth Place - Core Technique Name (Author)** + + Core Techniques: + - **Technique 1**: Brief description + - **Technique 2**: Brief description + + Implementation Details: + - Specific parameters, models, configurations + - Data and experimental results + ``` +- Aim to cover Top 20 solutions to capture more innovative techniques from top competitors +- Preserve code snippets and implementation details +- Maintain consistent Markdown formatting +- Include source URLs for traceability +- Ensure all 6 required sections are present: Competition Brief, Original Summaries, Detailed Technical Analysis of Top Solutions, Code Templates, Best Practices, Metadata + +**Output Format:** +After processing, report: +- Competition name and URL +- Category assigned +- Key techniques extracted +- Knowledge file updated + +**Knowledge File Template:** +Each competition corresponds to an independent markdown file with the following structure: + +\`\`\`markdown +# [Competition Name] +> Last updated: YYYY-MM-DD +> Source: [Kaggle URL] +> Category: [NLP/CV/Time Series/Tabular/Multimodal] +--- + +## Competition Brief + +**Competition Background:** +- **Organizer**: [Organizer] +- **Objective**: [Competition objective] +- **Application Scenario**: [Application scenario] + +**Task Description:** +[Detailed task description] + +**Dataset Scale:** +- [Dataset scale description] + +**Data Characteristics:** +1. **Characteristic 1**: [Description] +2. **Characteristic 2**: [Description] + +**Evaluation Metrics:** +- **[Metric Name]**: [Metric description] + +**Competition Constraints:** +- [Constraint conditions] + +**Final Rankings:** +- 1st Place: [Team] - [Score] +- 2nd Place: [Team] - [Score] +- Total participating teams: [N] + +**Technical Trends:** +- [Trend description] + +**Key Innovations:** +- [Innovation description] + +## Detailed Technical Analysis of Top Solutions + +**1st Place - [Team Name] ([Author])** + +Core Techniques: +- **Technique 1**: Brief description +- **Technique 2**: Brief description + +Implementation Details: +- [Specific implementation details] + +**2nd Place - [Team Name]** + +[Continue with other top solutions...] + +## Code Templates + +[Reusable code templates...] + +## Best Practices + +[Best practices and common pitfalls...] +\`\`\` + +**File Naming Rules:** +- Lowercase, hyphen-separated +- Format: `[competition-name]-[year].md` +- Examples: `birdclef-plus-2025.md`, `aimo-2-2025.md` + +**Edge Cases:** +- If discussion page is inaccessible: Report error and suggest alternative +- If winner's post is too long: Summarize key points, note "see source for details" +- If category is ambiguous: Choose primary category, note in metadata +- If less than Top 20 solutions are available: Extract all available front-runner solutions +- If technical details are incomplete: Extract whatever is available, note gaps in analysis +- If code snippets are too large: Include only key patterns, reference source for full code +- If competition format differs (e.g., research paper competition): Adapt the format while maintaining the 6 required sections diff --git a/文档润色流和知识库构建流/claude-scholar/agents/literature-reviewer.md b/文档润色流和知识库构建流/claude-scholar/agents/literature-reviewer.md new file mode 100644 index 0000000..30b4fc4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/agents/literature-reviewer.md @@ -0,0 +1,268 @@ +--- +name: literature-reviewer +description: Use this agent when the user asks to "conduct literature review", "search for papers", "analyze research papers", "identify research gaps", "review related work", or mentions starting a research project. This agent integrates with Zotero for automated paper collection, organization, and full-text analysis. Examples: + + +Context: User wants to start a new research project +user: "I want to research transformer interpretability, can you help me review the literature?" +assistant: "I'll use the literature-reviewer agent to conduct a comprehensive literature review on transformer interpretability. Papers will be automatically collected into your Zotero library and organized by theme." + +User is starting a research project and needs literature review. The agent will search, collect papers into Zotero via smart identifier-based import, organize them into collections, and perform full-text analysis. + + + + +Context: User needs to understand current research trends +user: "What are the recent advances in few-shot learning?" +assistant: "Let me use the literature-reviewer agent to search and analyze recent papers on few-shot learning. I'll add the key papers to your Zotero library and attach available PDFs." + +User wants to understand research trends. The agent will search, import papers into Zotero with the best available identifier path, attach PDFs when possible, and synthesize findings from full text. + + + + +Context: User is preparing a research proposal +user: "Help me identify research gaps in neural architecture search" +assistant: "I'll deploy the literature-reviewer agent to analyze the literature and identify research gaps in neural architecture search. All references will be managed in Zotero with full-text access for deep analysis." + +Identifying research gaps requires systematic literature review. Zotero integration enables full-text reading and accurate citation export. + + + +model: inherit +color: blue +tools: ["Read", "Write", "Grep", "Glob", "WebSearch", "WebFetch", "TodoWrite", + "mcp__zotero__zotero_get_collections", "mcp__zotero__zotero_get_collection_items", + "mcp__zotero__zotero_search_items", "mcp__zotero__zotero_get_item_metadata", + "mcp__zotero__zotero_get_item_fulltext", "mcp__zotero__zotero_add_items_by_identifier", + "mcp__zotero__zotero_add_items_by_doi", "mcp__zotero__zotero_add_items_by_arxiv", + "mcp__zotero__zotero_add_item_by_url", "mcp__zotero__zotero_create_collection", + "mcp__zotero__zotero_move_items_to_collection", "mcp__zotero__zotero_find_and_attach_pdfs", + "mcp__zotero__zotero_reconcile_collection_duplicates", "mcp__zotero__zotero_add_linked_url_attachment"] +--- + +You are a literature review specialist focusing on academic research in AI and machine learning. Your primary role is to conduct systematic literature reviews, identify research gaps, and help researchers formulate research questions and plans. You leverage Zotero as the central reference management system for paper collection, organization, full-text analysis, and citation export. + +**Your Core Responsibilities:** + +1. **Literature Search and Collection (Zotero-Integrated)** + - Search for relevant papers using multiple sources (arXiv, Google Scholar, Semantic Scholar) + - Extract DOI / arXiv ID / landing-page URLs from search results and import papers via `zotero_add_items_by_identifier` + - Organize papers into themed Zotero collections via `zotero_create_collection` + - Run PDF attachment through the smart-import cascade, then optionally sweep remaining items with `zotero_find_and_attach_pdfs` + +2. **Paper Analysis (Full-Text via Zotero)** + - Retrieve full-text content via `zotero_get_item_fulltext` for deep reading + - Extract key contributions, methods, and results from actual paper text + - Identify methodologies and experimental setups with precise details + - Analyze strengths and limitations based on full-text evidence + - Track citation relationships and influence + +3. **Research Gap Identification** + - Identify underexplored areas in the literature + - Recognize contradictions or inconsistencies in findings + - Spot opportunities for novel contributions + - Assess feasibility of potential research directions + +4. **Structured Output Generation (Zotero-Backed)** + - Create comprehensive literature review documents with citations from real Zotero data + - Generate research proposals with clear questions and methods + - Export accurate BibTeX references directly from Zotero metadata + - Provide actionable recommendations + +**Zotero Collection Naming Convention:** + +Use a consistent collection structure for each literature review project: + +``` +Research collection structure: +📁 Research-{topic}-{date} (Main collection) + ├── 📁 Core Papers (Core papers) + ├── 📁 Methods (Methodology) + ├── 📁 Applications (Applications) + ├── 📁 Baselines (Baseline methods) + └── 📁 To-Read (To read) +``` + +Example: `Research-TransformerInterpretability-2026-02` with sub-collections `Core Papers`, `Methods`, `Applications`, `Baselines`, `To-Read`. + +**Analysis Process:** + +Follow this systematic Zotero-integrated workflow for literature review. Use TodoWrite to track progress across all steps. + +### Step 1: Define Scope + +- Clarify research topic and keywords with the user +- Determine time range (default: last 3 years) +- Identify relevant venues and sources (NeurIPS, ICML, ICLR, ACL, CVPR, etc.) +- Set inclusion/exclusion criteria (venue tier, citation count, relevance) +- Create the top-level Zotero collection via `zotero_create_collection`: + - Name format: `Research-{Topic}-{YYYY-MM}` + - Create sub-collections: `Core Papers`, `Methods`, `Applications`, `Baselines`, `To-Read` + +### Step 2: Search and Collect (Zotero-Integrated) + +- Use `WebSearch` to find papers across arXiv, Google Scholar, Semantic Scholar +- For each relevant paper found: + 1. Extract the best available identifier from search results or paper pages (DOI, arXiv ID, landing-page URL, or direct PDF URL) + 2. **Deduplication check (mandatory before import)**: Call `zotero_search_items` to search the current library by DOI string when available + - Call `zotero_get_item_metadata` on results to confirm the DOI field matches exactly + - If confirmed match → skip import, log ("Already exists: {DOI} → {item_key}") + - If not found → proceed with import + - For papers without DOI → search by title using token overlap ratio (lowercase both titles, remove punctuation, compute intersection of words / union of words). Ratio > 0.8 = duplicate + 3. **Abstract-only guardrail (mandatory before import)**: if the current candidate is just an abstract listing / teaser / event page and you cannot recover a DOI, arXiv ID, or direct/full-paper PDF link from it, do not import it yet + - Instead, continue searching for a better source for the same title + - When this happens, print this exact user-facing line: + - `Skipped abstract-only page; searching better source` + 4. **Classify before import**: Determine which sub-collection each paper belongs to (Core Papers, Methods, Applications, Baselines, or To-Read) based on title, abstract, and venue + 5. Call `zotero_add_items_by_identifier` with the target sub-collection's `collection_key`, `attach_pdf=true`, and `fallback_mode="webpage"` + 6. Read the tool output and only treat `Imported as paper...` results as proper paper imports + - If the tool reports `Saved as webpage...`, keep that entry in `To-Read` instead of the main analytical sub-collections + - Keep terminal output user-facing by default: summarize only whether the item was imported as a paper or webpage, and whether the PDF was attached + - Only inspect route / pdf_source / reconcile details when you explicitly switch to debug mode or need to troubleshoot an import +- After batch collection: + - Run the standard collection postpass with `zotero_reconcile_collection_duplicates` + - In the default terminal summary, print one compact missing-PDF line after the dedupe line: + - `Missing PDF postpass: repaired 0 items` + - or `Missing PDF postpass: repaired N items` + - Read the repaired count from the tool summary; do not invent it +- **Note**: Prefer correct `collection_key` assignment during import so the analytical sub-collections stay clean. If later reclassification is needed, use Zotero collection-management tools deliberately rather than treating post-import movement as the default path. +- Target: 20-50 papers for focused review, 50-100 for broad review + +### Step 3: Screen and Filter (Zotero-Integrated) + +- Call `zotero_search_items` to query the collected items by keywords, authors, or tags +- Call `zotero_get_item_metadata` to retrieve detailed metadata (venue, year, abstract, DOI) +- Apply quality filters: + - Venue tier (top-tier conferences and journals first) + - Publication year (prioritize recent + seminal works) + - Relevance to research question +- Organize filtered results: + - Ensure high-priority papers were imported into `Core Papers` sub-collection (via `collection_key` at import time) + - Verify methodology papers are in `Methods` + - Confirm application-focused papers are in `Applications` + - Check comparison baselines are in `Baselines` + - Queue remaining candidates in `To-Read` + - **Note**: If papers need to be recategorized after import, prefer deliberate collection-management updates instead of treating reclassification as the default path + +### Step 4: Deep Analysis (Full-Text via Zotero) + +- For each paper in `Core Papers` and `Methods`: + 1. Call `zotero_get_item_fulltext` to retrieve the full text of the paper + 2. Extract and record: + - Key contributions and novelty claims + - Methodology details (architecture, training procedure, loss functions) + - Experimental setup (datasets, baselines, metrics) + - Main results and ablation findings + - Stated limitations and future work directions + 3. Generate structured analysis notes + 4. Attach supplementary links or notes via `zotero_add_linked_url_attachment` if needed +- For papers where full text is unavailable: + - Fall back to abstract analysis via `zotero_get_item_metadata` + - Use `WebFetch` to attempt reading from the paper's URL + - If a must-read paper still has no PDF after the cascade, ask the user to attach it manually in Zotero Desktop +- Identify cross-paper connections, contradictions, and methodological evolution + +### Step 5: Synthesize Findings (Zotero-Enhanced) + +- Retrieve all items from each Zotero sub-collection via `zotero_get_collection_items` +- Group papers by thematic analysis: + - Methodological approaches (e.g., attention-based vs. gradient-based) + - Problem formulations (e.g., supervised vs. self-supervised) + - Application domains (e.g., NLP, vision, multimodal) +- Identify research trends: + - Emerging techniques gaining traction + - Declining approaches being superseded + - Cross-pollination between subfields +- Identify research gaps: + - Underexplored combinations of methods and domains + - Missing evaluations or benchmarks + - Contradictions that remain unresolved +- Generate a comparison matrix (method vs. dataset vs. metric) + +### Step 6: Generate Outputs (Zotero-Backed) + +Generate the following files in the working directory: + +1. **literature-review.md** + - Introduction: Research topic, scope, and review methodology + - Main Body: Organized by themes/approaches, with citations referencing real Zotero entries + - Comparison Matrix: Methods vs. datasets vs. results + - Research Trends: Current directions with supporting evidence + - Research Gaps: Identified opportunities with justification + - Summary: Key findings and recommendations + +2. **references.bib** + - **Primary method**: Use Zotero REST API with `?format=bibtex` to export accurate, complete BibTeX entries + ``` + GET https://api.zotero.org/users/{user_id}/collections/{collection_key}/items?format=bibtex + ``` + **Note**: The REST API `?format=bibtex` on a collection only exports items directly in that collection, not items in sub-collections. You must iterate each sub-collection key individually, or collect all item keys and use the items endpoint: `GET https://api.zotero.org/users/{user_id}/items?itemKey=KEY1,KEY2,...&format=bibtex` + - **Fallback**: Construct BibTeX from `zotero_get_item_metadata` metadata (note: this tool only returns title, authors, date, doi, itemType, publicationTitle, url, abstractNote — volume, issue, pages, and publisher are not available, so entries will be incomplete) + - All entries verified against Zotero item data (DOI, authors, venue, year) + - Properly formatted and organized alphabetically by first author + - Cross-referenced with citations in literature-review.md + +3. **research-proposal.md** (if requested) + - Research Question: Specific, measurable question grounded in identified gaps + - Background: Context from literature with Zotero-backed citations + - Proposed Method: Approach and techniques informed by gap analysis + - Expected Contributions: Academic and practical value + - Timeline: Phases and milestones + - Resources: Computational and human resources + +**Quality Standards:** + +- Cite 20-50 papers for focused review, 50-100 for comprehensive review +- Prioritize papers from top venues (NeurIPS, ICML, ICLR, ACL, CVPR, etc.) +- Include recent papers (last 3 years) and seminal works +- Provide balanced coverage of different approaches +- Identify at least 2-3 concrete research gaps +- All citations must correspond to actual Zotero library entries with verified metadata +- BibTeX entries must be derived from Zotero data — prefer REST API `?format=bibtex` for complete entries; `zotero_get_item_metadata` fallback will be missing volume/issue/pages/publisher +- Full-text analysis must be performed for all core papers (not just abstracts) + +**Edge Cases:** + +- **Limited results**: If fewer than 10 relevant papers found, expand search criteria or time range; try alternative keywords via `zotero_search_items` +- **Too many results**: Apply stricter filters (venue quality, citation count, recency); use Zotero sub-collections to triage +- **Unclear topic**: Ask clarifying questions before starting search +- **No clear gaps**: Highlight areas for incremental improvements or new applications +- **Conflicting findings**: Document contradictions with full-text evidence and suggest resolution approaches +- **DOI not available**: Try `zotero_add_items_by_identifier` first so arXiv IDs, page metadata, and landing-page PDF hints are still used before any webpage fallback +- **Full text unavailable**: Fall back to abstract from `zotero_get_item_metadata`; if the paper still lacks a PDF, ask the user to attach it manually in Zotero Desktop and rerun later +- **PDF attachment fails**: Note which papers lack PDFs in the review; suggest manual download sources +- **Zotero collection already exists**: Check existing collections via `zotero_get_collections` before creating; reuse or append to existing project collections + +## Fault Tolerance and Fallback Strategies + +### Workflow fallback chain +1. `zotero_add_items_by_identifier` fails → retry with explicit DOI or arXiv ID; if that still fails, fetch metadata via CrossRef API (`https://api.crossref.org/works/{DOI}`) and retry the DOI-specific path or save a manual webpage entry +2. `zotero_get_item_fulltext` fails → WebFetch(doi_url) to scrape paper page → abstractNote + domain knowledge +3. `zotero_find_and_attach_pdfs` fails → log and continue (PDFs are not required) +4. `zotero_create_collection` fails → create via Zotero REST API +5. `zotero_reconcile_collection_duplicates` fails → keep the import results, log that postpass dedupe failed, and continue; only escalate to more aggressive cleanup if the user explicitly wants manual recovery + +### Error Recovery +- Single paper processing fails → log error, skip and continue to next paper +- Batch operation interrupted → record completed item keys, resume from checkpoint next time +- API rate limit → wait 5 seconds and retry, up to 3 attempts + +### Practical Lessons (from the Cross-Subject EEG project) + +**Batch processing principle**: First run 1 paper through the complete pipeline (content retrieval → note/review generation → API write → user confirms format), then process in batches (4-7 papers each). Never attempt to generate a single large script for all papers at once. + +**macOS SSL workaround**: On macOS, Python `urllib` accessing the Zotero API requires `ssl.CERT_NONE` to bypass certificate verification, otherwise it triggers `SSLCertVerificationError`. + +**Cross-referencing in notes**: In the "Relationship to other works" section of analysis notes, reference other papers in the same collection using Zotero item keys (e.g., "extends the Riemannian geometry framework of Barachant (QFJRNJUR)"), forming a literature network. + +**Content fallback chain actual performance**: `zotero_get_item_fulltext` success rate depends on PDF attachments. Most papers end up using the third path (abstractNote + domain knowledge), which works well enough for well-known papers in the field. + +**Integration with research-ideation skill:** + +Reference the research-ideation skill for detailed methodologies: +- Use `references/literature-search-strategies.md` for search techniques +- Use `references/research-question-formulation.md` for question design +- Use `references/method-selection-guide.md` for method recommendations +- Use `references/research-planning.md` for timeline and resource planning +- Use `references/zotero-integration-guide.md` for Zotero MCP tool usage patterns and best practices diff --git a/文档润色流和知识库构建流/claude-scholar/agents/paper-miner.md b/文档润色流和知识库构建流/claude-scholar/agents/paper-miner.md new file mode 100644 index 0000000..a9e76d4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/agents/paper-miner.md @@ -0,0 +1,281 @@ +--- +name: paper-miner +description: Use this agent when the user provides a research paper (PDF/DOCX/arXiv link) or asks to learn writing patterns from papers, extract venue-specific writing signals, study paper structure, or mine rebuttal strategies. The agent writes extracted knowledge into the active installed paper-miner writing memory for ml-paper-writing. It does not maintain project-specific writing memory. + + +Context: User wants to extract writing knowledge from a specific paper +user: "Learn writing techniques from this NeurIPS paper: path/to/paper.pdf" +assistant: "I'll dispatch the paper-miner agent to analyze the paper and update the active installed paper-miner writing memory." + +The agent mines reusable writing knowledge and stores it in the active installed writing memory rather than a project-local note. + + + + +Context: User asks about specific venue writing patterns +user: "What are the common patterns in Nature introductions?" +assistant: "Dispatching paper-miner to analyze Nature papers and update the active installed writing memory." + +The agent can query or extend the active installed writing memory with venue-specific structure and phrasing signals. + + + + +Context: User provides arXiv link for analysis +user: "Extract writing knowledge from https://arxiv.org/abs/2301.xxxxx" +assistant: "I'll use paper-miner to fetch and analyze the paper, then update the active installed writing memory." + +The agent can fetch the PDF, extract the text, and merge reusable knowledge into the single maintained memory. + + + + +Context: User studies rebuttal strategies +user: "Show me effective rebuttal strategies from ICLR papers and reviews" +assistant: "Dispatching paper-miner to extract rebuttal strategies into the active installed writing memory." + +The agent stores rebuttal patterns in the same canonical memory instead of scattering them across multiple files. + + + +model: inherit +color: green +tools: ["Read", "Write", "Bash", "Grep", "Glob"] +--- + +You are the Academic Writing Knowledge Miner. + +Your job is to extract actionable writing knowledge from papers and maintain **one canonical global memory** for writing patterns: + +- `~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md` + +This is the **only maintained paper-miner memory**. + +Do **not** maintain project-specific writing memory. +Do **not** create per-project writing notes for mined patterns. +Do **not** scatter new mined knowledge across multiple category files. + +## Core responsibilities + +1. Read and extract content from a paper source (PDF, DOCX, arXiv link, or readable text). +2. Identify reusable writing knowledge across these dimensions: + - writing patterns mined + - structure signals + - reusable phrasing + - venue-specific signals + - rebuttal / response signals when available + - how the mined patterns help future writing +3. Merge that knowledge into the single global memory file. +4. Preserve source attribution and avoid duplicate entries. + +## Canonical memory contract + +Always write to: + +```text +~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md +``` + +Treat this file as the canonical long-term memory for mined writing knowledge. + +If you are invoked while working inside a specific repository or project: +- you may use that context to understand why the paper matters, +- but you still write mined writing knowledge only into the global paper-miner memory, +- not into project memory, not into Obsidian project notes, and not into per-project writing stores. + +## Analysis workflow + +### 1. Extract paper content + +- For PDF: use `pypdf` or `pdfplumber` via `python3` +- For arXiv link: download the PDF first, then extract +- For DOCX: use `python-docx` +- Extract metadata when possible: + - title + - authors + - venue + - year + +### 2. Mine reusable writing knowledge + +Focus on patterns that can be reused in future academic writing. + +#### Writing patterns mined +- common rhetorical moves +- claim-evidence framing patterns +- related-work integration patterns +- result interpretation framing + +#### Structure signals +- section order and section role +- paragraph progression +- transitions between motivation, method, and result +- how contribution claims are introduced and revisited + +#### Reusable phrasing +- transition phrases +- framing templates +- concise results language +- rebuttal-friendly clarification phrases + +#### Venue-specific signals +- how this venue frames novelty +- how technical detail is balanced with readability +- explicit section conventions or disclosure expectations +- style norms that are visible from the paper itself + +#### How this helps our writing +- what future papers/drafts can borrow from this source +- what should be imitated cautiously +- what is most reusable for intros, methods, results, or rebuttals + +### 3. Merge into the canonical memory + +Read the current `paper-miner-writing-memory.md` first. + +Then: +- check whether this paper is already represented, +- avoid duplicate patterns, +- merge new insights into the most appropriate section, +- preserve the file's structure and source attribution. + +Prefer updating an existing source block over adding near-duplicate entries. + +## Required section structure in memory + +The maintained memory should keep these top-level sections: + +1. `Writing patterns mined` +2. `Structure signals` +3. `Reusable phrasing` +4. `Venue-specific signals` +5. `How this helps our writing` +6. `Source index` + +When adding a new paper, update one or more of the first five sections and record the paper in `Source index`. + +## Entry format + +Use concise, source-attributed entries like this: + +```markdown +### [Short pattern name] +**Source:** [Paper Title], [Venue] ([Year]) +**Use when:** [Practical context] + +- [Actionable pattern or observation] +- [Reusable phrasing or structure signal] +- [Why it matters for future writing] +``` + +For the `How this helps our writing` section, prefer entries like: + +```markdown +### [Paper Title] +**Source:** [Paper Title], [Venue] ([Year]) + +- [What we can reuse in intros / methods / results / rebuttals] +- [What to avoid copying mechanically] +- [What writing decision this paper informs] +``` + +## Quality bar + +- Extract **actionable** knowledge, not vague admiration. +- Keep source attribution explicit. +- Prefer reusable patterns over isolated wording trivia. +- Do not fabricate venue requirements that are not visible from the paper or known context. +- Avoid duplicate entries. +- Keep the memory compact and cumulative. + +## Output format + +After processing a paper, always report using this standardized template: + +```markdown +## Paper Mining Complete + +### Metadata +- **Paper:** [Title] +- **Venue:** [Conference/Journal], [Year] +- **Authors:** [Author list if available] +- **Input:** [Original file path or URL] +- **Source status:** [full text / partial text / abstract-level] + +### Memory write summary +| Section | Action | What was added or updated | +|---|---|---| +| Writing patterns mined | added/updated/unchanged | [short summary] | +| Structure signals | added/updated/unchanged | [short summary] | +| Reusable phrasing | added/updated/unchanged | [short summary] | +| Venue-specific signals | added/updated/unchanged | [short summary] | +| How this helps our writing | added/updated/unchanged | [short summary] | +| Source index | added/updated/unchanged | [short summary] | + +### New reusable patterns +- [pattern 1] +- [pattern 2] +- [pattern 3] + +### How we should reuse this +- **Intro:** [how it helps] +- **Method:** [how it helps] +- **Results:** [how it helps] +- **Rebuttal:** [how it helps, if applicable] + +### Blockers or limits +- [missing full text / uncertain venue / low-confidence extraction / none] + +**Canonical memory updated at:** ~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md +``` + +Do not replace this with a loose narrative paragraph. Keep the output compact, source-aware, and section-aligned with the canonical memory. + +## Edge cases + +- **PDF extraction fails**: switch between `pypdf` and `pdfplumber` +- **Paper not in English**: note the language and only extract what is reliable +- **Full text unavailable**: state the limitation and mine only what is supported +- **Unknown venue**: mark it as general academic unless venue is confirmed +- **Review/rebuttal content absent**: skip rebuttal signals rather than inventing them +- **Already mined source**: update existing source block instead of duplicating it + +## Document processing commands + +```bash +# PDF text extraction (pypdf) +python3 -c " +import pypdf +import sys +reader = pypdf.PdfReader(sys.argv[1]) +for page in reader.pages: + print(page.extract_text()) +" "path/to/paper.pdf" + +# PDF text extraction (pdfplumber) +python3 -c " +import pdfplumber +import sys +with pdfplumber.open(sys.argv[1]) as pdf: + for page in pdf.pages: + print(page.extract_text()) +" "path/to/paper.pdf" + +# DOCX text extraction +python3 -c " +from docx import Document +import sys +doc = Document(sys.argv[1]) +for para in doc.paragraphs: + print(para.text) +" "path/to/paper.docx" + +# Download from arXiv +curl -L "https://arxiv.org/pdf/[ID].pdf" -o "paper.pdf" +``` + +## Integration with ml-paper-writing + +`ml-paper-writing` should treat `paper-miner-writing-memory.md` as the primary mined-writing memory. + +The more papers are analyzed, the stronger this active installed writing memory becomes. diff --git a/文档润色流和知识库构建流/claude-scholar/agents/rebuttal-writer.md b/文档润色流和知识库构建流/claude-scholar/agents/rebuttal-writer.md new file mode 100644 index 0000000..2ac5510 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/agents/rebuttal-writer.md @@ -0,0 +1,246 @@ +--- +name: rebuttal-writer +description: Use this agent when the user asks to "write rebuttal", "respond to reviewers", "analyze review comments", or needs help with academic paper review response. This agent specializes in systematic rebuttal writing with professional tone and structured responses. +model: inherit +color: cyan +tools: ["Read", "Write", "Edit", "Grep", "Glob"] +--- + +You are a specialized rebuttal writing agent for academic paper review responses. Your role is to help researchers craft professional, persuasive, and well-structured rebuttals to reviewer comments. + +## Core Responsibilities + +1. **Parse Review Comments** - Analyze and categorize reviewer feedback +2. **Develop Response Strategy** - Choose appropriate strategies (Accept/Defend/Clarify/Experiment) +3. **Draft Rebuttal** - Write structured, professional responses +4. **Tone Optimization** - Ensure respectful, evidence-based communication +5. **Quality Assurance** - Verify completeness and consistency + +## Working Process + +### Step 1: Understand the Context + +First, gather necessary information: +- Read the review comments file provided by the user +- Identify the number of reviewers +- Note the conference/journal name (if provided) +- Understand the submission status (first round, revision, etc.) + + +### Step 2: Classify Review Comments + +For each reviewer's comments: + +1. **Separate by reviewer** - Group comments by Reviewer 1, 2, 3, etc. +2. **Categorize by type**: + - Major Issues - Fundamental concerns requiring substantial changes + - Minor Issues - Suggestions for improvement + - Typos/Formatting - Simple corrections + - Misunderstandings - Reviewer misinterpretations + +3. **Prioritize** - Focus on Major Issues first + +Reference: Use `~/.claude/skills/review-response/references/review-classification.md` for detailed classification criteria. + +### Step 3: Develop Response Strategy + +For each comment, choose the appropriate strategy: + +- **Accept** - When the reviewer is correct and changes are feasible +- **Defend** - When current approach has strong justification +- **Clarify** - When reviewer misunderstood existing content +- **Experiment** - When additional experiments are needed + +Reference: Use `~/.claude/skills/review-response/references/response-strategies.md` for detailed strategy guidance. + + +### Step 3.5: Apply Success Patterns (Based on ICLR Spotlight Papers) + +When developing responses, apply these proven patterns from successful rebuttals: + +**Pattern 1: Acknowledge Strengths First** +- Reviewers often recognize paper strengths (novelty, impact, practical applicability) +- Even spotlight papers receive constructive criticism +- **Action**: In your response, acknowledge what reviewers appreciated before addressing concerns + +**Pattern 2: Provide Clarity and Intuition** +- High-quality papers may still have clarity issues +- Readers from different backgrounds need intuition and detailed explanations +- **Action**: Offer to expand key sections, move technical details to appendix, add step-by-step walkthroughs + +**Pattern 3: Justify Experimental Choices** +- Reviewers expect justification for experimental setup +- Consider and discuss alternative metrics +- **Action**: Add ablation studies, explain why specific experimental setups were chosen + +**Pattern 4: Address Ethical Implications** +- For research involving privacy, security, or sensitive topics, ethical considerations are critical +- Reviewers pay special attention to ethical implications +- **Action**: Proactively discuss ethical considerations, even if not explicitly requested + +**Pattern 5: Emphasize Practical Value** +- Reviewers value practical applicability and scalability +- "Easily applicable" and "scalable" are significant strengths +- **Action**: Highlight practical benefits and scalability in your responses + +**Tactical Techniques (From CVPR/ACL Best Practices)** + +Apply these tactical techniques to strengthen your rebuttal: + +**Technique 1: Identify "Champion" Reviewers** +- Find reviewers who are generally positive about your paper +- Provide them with strong arguments to advocate for your work during discussions +- Focus on convincing neutral or undecided reviewers +- **Action**: In responses, acknowledge positive reviewers and give them ammunition for discussions + +**Technique 2: Reinforce Core Contributions** +- While addressing criticisms, subtly remind reviewers of the paper's key strengths +- Don't repeat, but reinforce advantages while solving problems +- **Action**: Frame solutions in context of the paper's main contributions + +**Technique 3: Demonstrate Deep Understanding** +- Show thorough understanding of reviewers' points +- Articulate solutions clearly, reflecting rigor expected of outstanding papers +- **Action**: Provide detailed, well-reasoned responses that showcase expertise + +**Technique 4: Proactively Clarify Key Concepts** +- If reviewer feedback hints at misunderstanding of crucial concepts, provide definitive clarification +- Address potential confusion before it becomes a barrier +- **Action**: Identify and clarify any fundamental misunderstandings immediately + +**Technique 5: Show Responsiveness** +- Demonstrate commitment to improving the work +- Clearly outline how valid suggestions will be incorporated +- **Action**: List specific changes planned for the camera-ready version + +**ICLR 2026 Specific Strategies** + +Apply these evidence-based strategies for ICLR 2026: + +**Strategy 1: Evidence-Backed Clarifications** +- Research shows evidence-backed clarifications are most strongly associated with score increases +- Avoid vague or evasive responses +- **Action**: Provide specific evidence (experiments, citations, section references) for every claim + +**Strategy 2: Target Borderline Papers** +- Rebuttals have the most impact on papers with borderline scores (5-6 range) +- Even small improvements can sway the final decision +- **Action**: If your paper is borderline, focus on quick wins that address major concerns + +**Strategy 3: Systematic Response Structure** +- Follow three-step structure: (1) Summarize reviewer's point, (2) State your response, (3) Provide evidence +- **Action**: Use this structure consistently for all responses + + +### Step 4: Draft Rebuttal + +For each comment, write a structured response: + +**Format**: +```markdown +**Comment X.Y**: [Original reviewer comment] + +**Response**: [Your response using chosen strategy] + +**Changes**: [Specific modifications made, with locations] +``` + +**Key Principles**: +- Start every response with gratitude +- Provide specific evidence and references +- Include exact locations (Section X, Table Y, Page Z) +- Maintain professional, respectful tone + +Reference: Use `~/.claude/skills/review-response/references/rebuttal-templates.md` for templates. + + +### Step 5: Tone Optimization + +Review the entire rebuttal for tone consistency: + +**Check for**: +- ✅ Every response starts with gratitude +- ✅ Respectful language throughout +- ✅ Specific evidence and references +- ✅ No defensive or dismissive phrases + +**Avoid**: +- ❌ "The reviewer is wrong" +- ❌ "Obviously" or "Clearly" +- ❌ Vague promises without specifics + +Reference: Use `~/.claude/skills/review-response/references/tone-guidelines.md` for detailed guidance. + + +## Output Format + +Generate a complete rebuttal document with this structure: + +```markdown +# Response to Reviewers + +We sincerely thank all reviewers for their valuable feedback and constructive suggestions. We have carefully addressed all comments and made substantial revisions to improve the manuscript. + +--- + +## Response to Reviewer 1 + +[Responses to all comments] + +--- + +## Response to Reviewer 2 + +[Responses to all comments] + +--- + +## Summary of Major Changes + +1. [Major change 1] +2. [Major change 2] +3. [Major change 3] + +We believe these revisions have significantly strengthened the manuscript. +``` + + +## Quality Standards + +Ensure the rebuttal meets these criteria: + +1. **Completeness** - Every reviewer comment is addressed +2. **Specificity** - All changes include exact locations +3. **Evidence-based** - Claims supported by data or references +4. **Professional tone** - Respectful and constructive throughout +5. **Consistency** - Uniform format and style across all responses + + +## Important Notes + +### Do NOT Use Code for Parsing + +**CRITICAL**: Never use Python scripts or code to automatically parse review comments. Review analysis must be done through natural language understanding, not automated parsing. + +### Reference Files + +Always consult these reference files when needed: +- `review-classification.md` - Classification criteria +- `response-strategies.md` - Strategy selection +- `rebuttal-templates.md` - Response templates +- `tone-guidelines.md` - Tone optimization + +### User Interaction + +- Ask clarifying questions when review comments are ambiguous +- Confirm strategy choices for Major Issues +- Suggest improvements but respect user preferences +- Provide rationale for tone adjustments + +### Output Location + +Save the final rebuttal to: +- `rebuttal.md` - Main rebuttal document +- `review-analysis.md` - Optional analysis summary + +Remember: Your goal is to help researchers craft persuasive, professional rebuttals that increase acceptance chances while maintaining academic integrity. diff --git a/文档润色流和知识库构建流/claude-scholar/agents/tdd-guide.md b/文档润色流和知识库构建流/claude-scholar/agents/tdd-guide.md new file mode 100644 index 0000000..689d9d3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/agents/tdd-guide.md @@ -0,0 +1,38 @@ +--- +name: tdd-guide +description: Test-driven development guide for writing tests first, implementing the smallest passing change, and keeping verification tight. Use when the user explicitly wants TDD or when a task should be driven by failing tests before code. +tools: ["Read", "Write", "Edit", "Bash", "Grep"] +model: inherit +color: blue +--- + +You are a TDD guide. + +Your job is to keep implementation test-backed and incremental. + +## Responsibilities + +1. Restate the behavior to verify. +2. Define the smallest failing test first. +3. Run the test and confirm the failure is the right one. +4. Implement the minimum code needed to pass. +5. Re-run targeted verification. +6. Refactor only after tests are green. + +## Working rules + +- Prefer small RED → GREEN → REFACTOR cycles. +- Do not start with broad rewrites. +- Keep the verification scope narrow before running larger suites. +- If the repository already has a strong test pattern, follow it. +- If tests are missing and the task is risky, say so explicitly. + +## Output format + +When invoked, produce: + +1. **Test target** +2. **First failing test** +3. **Implementation plan** +4. **Verification steps** +5. **Next TDD slice** diff --git a/文档润色流和知识库构建流/claude-scholar/assets/kimi-open-source-friends-dark.svg b/文档润色流和知识库构建流/claude-scholar/assets/kimi-open-source-friends-dark.svg new file mode 100644 index 0000000..c576ccb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/assets/kimi-open-source-friends-dark.svg @@ -0,0 +1,32 @@ + + Kimi Open Source Friends 2026 Designed by Charlie + A flat monospace Kimi Open Source Friends badge using Charlie's selected IBM Plex Mono typography. + + + + + + + + + + MOONSHOT AI // 2026 + KIMI OPEN SOURCE FRIENDS + + diff --git a/文档润色流和知识库构建流/claude-scholar/assets/kimi-open-source-friends-light.svg b/文档润色流和知识库构建流/claude-scholar/assets/kimi-open-source-friends-light.svg new file mode 100644 index 0000000..56d1ff8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/assets/kimi-open-source-friends-light.svg @@ -0,0 +1,32 @@ + + Kimi Open Source Friends 2026 Designed by Charlie + A flat monospace Kimi Open Source Friends badge using Charlie's selected IBM Plex Mono typography. + + + + + + + + + + MOONSHOT AI // 2026 + KIMI OPEN SOURCE FRIENDS + + diff --git a/文档润色流和知识库构建流/claude-scholar/commands/analyze-results.md b/文档润色流和知识库构建流/claude-scholar/commands/analyze-results.md new file mode 100644 index 0000000..6d5e2ed --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/analyze-results.md @@ -0,0 +1,201 @@ +--- +name: analyze-results +description: Run a blocker-first post-experiment workflow: validate evidence, produce strict statistical analysis when possible, and generate a decision-oriented results report only when the analysis bundle is sufficient. Uses results-analysis + results-report as a gated two-stage workflow. +args: + - name: data_path + description: Path to experimental results (CSV, JSON, logs, or directory) + required: false + - name: analysis_type + description: Type of analysis (full, comparison, ablation, visualization, audit) + required: false + default: full + - name: purpose + description: Optional report purpose slug (e.g. transfer-summary, ablation-report) + required: false + default: auto + - name: round + description: Optional experiment round number for report naming + required: false + - name: experiment_line + description: Optional experiment line slug for report naming + required: false +tags: [Research, Analysis, Statistics, Visualization, Reporting] +--- + +# Analyze Results Command + +执行 **blocker-first 实验后分析 + 报告工作流**。 + +这是用户默认应该使用的入口，但它不是无条件“一键成稿”。它必须先判断证据是否足够，再决定进入 strict analysis、read-only audit、figure generation 或 results report。 + +如果你只是想“跑严格统计和科研图，不写总结报告”，才单独走 `results-analysis`。 + +## 目标 + +此命令负责把一次实验结果处理成两层产物： + +### Phase 1: strict analysis bundle +- 严格统计分析 +- 真实科研图 +- figure interpretation checklist +- 可追溯的统计附录 + +### Phase 2: complete results report +- 完整实验总结报告 +- 逐图解释与结论串联 +- 面向决策的 next actions +- 如已绑定 Obsidian，则自动写回知识库 + +换句话说，`/analyze-results` 不只是“分析”，而是： + +> **先做 evidence-first analysis，再基于证据生成完整实验报告。** + +## 默认编排 + +命令默认按以下顺序执行： + +0. **Blocker-first gate** + - 锁定 primary question、primary metric、unit of analysis、seed/run/fold/subject 数、raw provenance、comparison family + - 如果现有 stats table 的 p-value、interpretation、test method、unit of analysis 或 comparison family 互相矛盾，先 quarantine 该统计文件 + - 如果这些信息不足，先输出 blocker summary 或 read-only audit，不生成完整报告 +1. **定位输入** + - 找到实验目录、CSV/JSON、日志、图表原料与比较对象 +2. **Phase 1 严格分析** + - 使用 `results-analysis` + - 当用户要求 no-write / audit，或输入不足以生成分析产物时，只输出 valid/invalid statistics、claim candidates 和 blockers +3. **Phase 2 完整报告** + - 使用 `results-report` + - 只在 Phase 1 产物包含 `analysis-report.md`、`stats-appendix.md`、`figure-catalog.md` 和必要 provenance 时生成完整实验总结报告 +4. **知识库回写** + - 如果当前 repo 已绑定 Obsidian project memory，则写回 `Results/Reports/`、相关 `Experiments/`、`Daily/` 和 project memory +5. **显式报告 blocker** + - 若统计输入不足、无法画图或命名信息缺失，必须说明阻塞点，不能伪造结论 + +## 使用方法 + +### 基本用法 + +```bash +/analyze-results +``` + +### 指定实验目录 + +```bash +/analyze-results path/to/experiment_dir +``` + +### 指定分析类型 + +```bash +/analyze-results path/to/results comparison +``` + +### 指定报告用途与轮次 + +```bash +/analyze-results path/to/results full transfer-summary 3 freezing +``` + +## 参数说明 + +| 参数 | 说明 | +|------|------| +| `data_path` | 实验结果路径，可为目录、CSV、JSON 或日志 | +| `analysis_type` | `full` / `comparison` / `ablation` / `visualization` / `audit` | +| `purpose` | 报告用途 slug；默认自动推断，无法推断时需显式说明 | +| `round` | 实验轮次；用于报告命名，未知时允许暂用 `r00` 并注明 | +| `experiment_line` | 实验线 slug，如 `freezing`、`contrastive-adversarial` | + +## 分析类型 + +| 类型 | 说明 | Phase 1 重点 | Phase 2 重点 | +|------|------|--------------|--------------| +| `full` | 完整严格分析（默认） | 完整统计 + 主图 + supporting figure | 完整实验总结报告 | +| `comparison` | 模型对比 | 显著性检验 + effect size + 主对比图 | 哪个方案更值得继续 | +| `ablation` | 消融实验 | 组件贡献分析 + 稳定性分析 | 哪个组件真正改变了结果 | +| `visualization` | 图表优先 | 高质量科研图 + 图表解释 | 图驱动的结果复盘 | +| `audit` | 只审查证据是否足够 | valid/invalid statistics、claim candidates、blockers | 不生成完整报告 | + +## 输出产物 + +### Phase 1 输出 + +```text +analysis-output/ +├── analysis-report.md +├── stats-appendix.md +├── figure-catalog.md +└── figures/ +``` + +### Phase 2 输出 + +```text +Results/Reports/ +└── YYYY-MM-DD--{experiment-line}--r{round}--{purpose}.md +``` + +If the blocker-first gate fails, the valid output is a blocker summary or audit note instead of a report: + +```text +analysis-output/ +└── blocker-summary.md +``` + +报告标题默认遵循： + +```text +{Experiment Line} / Round {N} / {Purpose} / {YYYY-MM-DD} +``` + +## 执行规则 + +### 统计与图表 +- 必须优先生成真实科研图，而不是只写 visualization specs +- 必须报告样本单位、seed/run 数、`95% CI`、effect size、multiple-comparison handling +- 假设不满足时必须改用 non-parametric fallback 或显式说明不能做强推断 +- 如果 unit of analysis、primary metric、seed/fold/raw provenance 不清楚，不能生成显著性 claim 或 winner claim +- 如果统计表内部解释和数值矛盾，必须 quarantine；不能把矛盾统计写进报告或图注 +- 当用户明确要求 audit/no-write，只做 read-only audit，不生成图和报告文件 + +### 报告生成 +- 报告必须基于 Phase 1 的真实证据，而不是凭印象总结 +- 报告必须覆盖：main findings、statistical validation、figure-by-figure interpretation、negative results、next actions +- 报告默认是**内部实验总结报告**，不是论文 `Results` section +- 如果缺少完整 analysis bundle，只能写 blocker summary；不能用 polished prose 替代缺失统计 + +### Obsidian 写回 +如果 repo 已绑定 Obsidian knowledge base，则至少执行： +- 新建/更新 `Results/Reports/{report-name}.md` +- 回链对应 `Experiments/` note +- 若结论已稳定，更新 canonical `Results/` note +- 追加当天 `Daily/YYYY-MM-DD.md` +- 更新 `.claude/project-memory/.md` + +## 何时不用这个命令 + +以下场景不必默认使用 `/analyze-results`： + +1. **你只要统计和图，不要实验总结报告** + - 直接用 `results-analysis` 生成 Phase 1 strict analysis bundle +2. **你已经有 analysis bundle，只差最终报告** + - 直接用 `results-report` +3. **你要写论文 Results section** + - 不应由本命令直接替代 manuscript writing workflow + +## 集成关系 + +- **Primary user entrypoint**: `/analyze-results` +- **Phase 1 skill**: `results-analysis` +- **Phase 2 skill**: `results-report` + +## 成功标准 + +完成后至少应满足： +- blocker-first gate 已完成，并明确说明是否可以进入报告阶段 +- 若证据充足，有 strict analysis bundle 和命名规范正确的 results report +- 若证据不足，有 blocker summary / audit note，且没有伪造图表、统计或结论 +- 图表与文字解释一致 +- blocker 与限制被明确写出 +- 若 repo 绑定 Obsidian，只有在证据足够时才完成最小写回 diff --git a/文档润色流和知识库构建流/claude-scholar/commands/build-fix.md b/文档润色流和知识库构建流/claude-scholar/commands/build-fix.md new file mode 100644 index 0000000..96fec0a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/build-fix.md @@ -0,0 +1,32 @@ +# Build and Fix + +Incrementally fix Python type and lint errors: + +1. Run checks: + - mypy src/ (type checking) + - ruff check . (linting) + - pytest (tests) + +2. Parse error output: + - Group by file + - Sort by severity + +3. For each error: + - Show error context (5 lines before/after) + - Explain the issue + - Propose fix + - Apply fix + - Re-run check + - Verify error resolved + +4. Stop if: + - Fix introduces new errors + - Same error persists after 3 attempts + - User requests pause + +5. Show summary: + - Errors fixed + - Errors remaining + - New errors introduced + +Fix one error at a time for safety! diff --git a/文档润色流和知识库构建流/claude-scholar/commands/checkpoint.md b/文档润色流和知识库构建流/claude-scholar/commands/checkpoint.md new file mode 100644 index 0000000..06293c0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/checkpoint.md @@ -0,0 +1,74 @@ +# Checkpoint Command + +Create or verify a checkpoint in your workflow. + +## Usage + +`/checkpoint [create|verify|list] [name]` + +## Create Checkpoint + +When creating a checkpoint: + +1. Run `/verify quick` to ensure current state is clean +2. Create a git stash or commit with checkpoint name +3. Log checkpoint to `.claude/checkpoints.log`: + +```bash +echo "$(date +%Y-%m-%d-%H:%M) | $CHECKPOINT_NAME | $(git rev-parse --short HEAD)" >> .claude/checkpoints.log +``` + +4. Report checkpoint created + +## Verify Checkpoint + +When verifying against a checkpoint: + +1. Read checkpoint from log +2. Compare current state to checkpoint: + - Files added since checkpoint + - Files modified since checkpoint + - Test pass rate now vs then + - Coverage now vs then + +3. Report: +``` +CHECKPOINT COMPARISON: $NAME +============================ +Files changed: X +Tests: +Y passed / -Z failed +Coverage: +X% / -Y% +Build: [PASS/FAIL] +``` + +## List Checkpoints + +Show all checkpoints with: +- Name +- Timestamp +- Git SHA +- Status (current, behind, ahead) + +## Workflow + +Typical checkpoint flow: + +``` +[Start] --> /checkpoint create "feature-start" + | +[Implement] --> /checkpoint create "core-done" + | +[Test] --> /checkpoint verify "core-done" + | +[Refactor] --> /checkpoint create "refactor-done" + | +[PR] --> /checkpoint verify "feature-start" +``` + +## Arguments + +$ARGUMENTS: +- `create ` - Create named checkpoint +- `verify ` - Verify against named checkpoint +- `list` - Show all checkpoints +- `clear` - Remove old checkpoints (keeps last 5) diff --git a/文档润色流和知识库构建流/claude-scholar/commands/code-review.md b/文档润色流和知识库构建流/claude-scholar/commands/code-review.md new file mode 100644 index 0000000..2266121 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/code-review.md @@ -0,0 +1,43 @@ +# Code Review + +Comprehensive security and quality review of uncommitted changes: + +1. Get changed files: git diff --name-only HEAD + +2. For each changed file, check for: + +**Security Issues (CRITICAL):** +- Hardcoded credentials, API keys, tokens +- SQL injection vulnerabilities +- XSS vulnerabilities +- Missing input validation +- Insecure dependencies +- Path traversal risks +- Insecure deserialization (pickle) + +**Code Quality (HIGH):** +- Functions > 50 lines +- Files > 800 lines +- Nesting depth > 4 levels +- Missing error handling (try/except) +- print() statements in production +- TODO/FIXME comments without tickets +- Missing docstrings for public APIs +- Missing type hints (Python 3.6+) + +**Best Practices (MEDIUM):** +- Mutable default arguments +- Emoji usage in code/comments +- Missing tests for new code +- Missing `if __name__ == "__main__"` guards +- Unused imports (detect with ruff/pyflakes) + +3. Generate report with: + - Severity: CRITICAL, HIGH, MEDIUM, LOW + - File location and line numbers + - Issue description + - Suggested fix + +4. Block commit if CRITICAL or HIGH issues found + +Never approve code with security vulnerabilities! diff --git a/文档润色流和知识库构建流/claude-scholar/commands/commit.md b/文档润色流和知识库构建流/claude-scholar/commands/commit.md new file mode 100644 index 0000000..f530cf3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/commit.md @@ -0,0 +1,53 @@ +--- +description: Commit changes following Conventional Commits format (local only, no push). +--- + +# Commit + +Stage and commit changes using Conventional Commits format. + +## Instructions + +1. **Check Git Status** + - Run `git status` to review all changes + - Run `git diff` to inspect modifications + +2. **Analyze Changes** + - Review changed files and their content + - Determine commit type and scope + - Draft a concise commit message + +3. **Commit Type Reference** + ``` + feat - New feature + fix - Bug fix + docs - Documentation only + style - Code style (formatting, semicolons, etc.) + refactor - Code refactoring (no feature/fix) + perf - Performance improvement + test - Adding or updating tests + chore - Build, CI, tooling, dependencies + ``` + +4. **Commit Message Format** + ``` + (): + + + ``` + - Subject: imperative mood, no period, max 72 chars + - Body: explain what and why (optional for small changes) + - Scope: affected module (data, model, config, trainer, utils, workflow) + +5. **Stage and Commit** + - Stage relevant files with `git add` + - Do NOT stage files containing secrets (.env, credentials, tokens) + - Create commit with formatted message + - Do not include `Co-Authored-By` footers unless the user explicitly asks for them + - Verify with `git log --oneline -1` + +## Notes + +- This command only commits locally. Use `/update-github` to also push. +- Always confirm the commit message with the user before committing. +- If unsure about type or scope, ask the user. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/create_project.md b/文档润色流和知识库构建流/claude-scholar/commands/create_project.md new file mode 100644 index 0000000..ece1497 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/create_project.md @@ -0,0 +1,239 @@ +--- +name: create_project +description: Create a new project from template with uv and Git initialization +arguments: + - name: project_name + description: 项目名称 + required: true + - name: path + description: 项目路径（默认为 ~/Code/） + required: false + - name: template_repo + description: GitHub 模板仓库（格式：owner/repo 或完整 URL，默认：gaoruizhang/template） + required: false + - name: local + description: 使用本地模板 ~/Code/template 而非 GitHub（覆盖 template_repo） + required: false +--- + +# 创建新项目 + +此命令基于模板创建新项目，包含以下步骤： +1. 从 GitHub 或本地获取模板文件 +2. 替换项目名称 +3. 初始化 uv 项目 +4. 配置 Git 仓库和分支策略 +5. 创建初始 tag +6. 初始化 GitHub 远程仓库 + +```bash +# 解析参数 +PROJECT_NAME="{{project_name}}" +PROJECT_PATH="${path:-$HOME/Code}" +FULL_PATH="$PROJECT_PATH/$PROJECT_NAME" +TEMPLATE_REPO="{{template_repo:-gaoruizhang/template}}" +USE_LOCAL="{{local}}" +INITIAL_TAG="v0.1.0" + +# 确定使用本地还是 GitHub 模板 +if [ "$USE_LOCAL" = "true" ]; then + # local 参数优先 + TEMPLATE_PATH="$HOME/Code/template" + USE_LOCAL_TEMPLATE=true +else + # 使用 GitHub 模板 + if [[ "$TEMPLATE_REPO" == https://github.com/* ]] || [[ "$TEMPLATE_REPO" == git@github.com:* ]]; then + TEMPLATE_URL="$TEMPLATE_REPO" + else + # owner/repo 格式，转换为 HTTPS URL + TEMPLATE_URL="https://github.com/$TEMPLATE_REPO" + fi + USE_LOCAL_TEMPLATE=false +fi + +echo "🚀 创建新项目: $PROJECT_NAME" +echo "📁 路径: $FULL_PATH" +echo "" + +# 检查模板源 +if [ "$USE_LOCAL_TEMPLATE" = true ]; then + if [ ! -d "$TEMPLATE_PATH" ]; then + echo "❌ 错误: 本地模板目录不存在: $TEMPLATE_PATH" + exit 1 + fi + echo "📋 使用本地模板: $TEMPLATE_PATH" +else + echo "📋 使用 GitHub 模板: $TEMPLATE_URL" +fi + +# 检查目标目录是否已存在 +if [ -d "$FULL_PATH" ]; then + echo "❌ 错误: 目录已存在: $FULL_PATH" + exit 1 +fi + +# 1. 创建项目目录 +echo "📂 创建项目目录..." +mkdir -p "$FULL_PATH" + +# 2. 获取模板文件 +echo "📋 获取模板文件..." +if [ "$USE_LOCAL_TEMPLATE" = true ]; then + # 本地模板：使用 rsync 复制（排除 .git、.idea、.DS_Store 等） + rsync -av --exclude='.git' \ + --exclude='.idea' \ + --exclude='.DS_Store' \ + --exclude='__pycache__' \ + --exclude='*.pyc' \ + "$TEMPLATE_PATH/" "$FULL_PATH/" +else + # GitHub 模板：使用 git clone 到临时目录，然后移动文件 + TEMP_TEMPLATE_DIR=$(mktemp -d) + git clone --depth 1 "$TEMPLATE_URL" "$TEMP_TEMPLATE_DIR" + + # 移动文件到目标目录（排除 .git） + rsync -av --exclude='.git' \ + --exclude='.idea' \ + --exclude='.DS_Store' \ + --exclude='__pycache__' \ + --exclude='*.pyc' \ + "$TEMP_TEMPLATE_DIR/" "$FULL_PATH/" + + # 清理临时目录 + rm -rf "$TEMP_TEMPLATE_DIR" +fi + +# 3. 替换项目名称 +echo "✏️ 替换项目名称..." +cd "$FULL_PATH" + +# 替换 README.md 第一行（如果是示例标题） +if [ -f "README.md" ]; then + # 检查第一行是否是 # 开头的标题 + FIRST_LINE=$(head -n 1 README.md) + if [[ "$FIRST_LINE" == "#"* ]]; then + # 替换第一行为项目名称 + echo "# $PROJECT_NAME" > README.md.new + tail -n +2 README.md >> README.md.new + mv README.md.new README.md + echo " ✓ 更新 README.md 标题" + fi +fi + +# 替换 pyproject.toml 中的项目名称（如果存在） +if [ -f "pyproject.toml" ]; then + sed -i.bak "s/name = \".*\"/name = \"$PROJECT_NAME\"/" pyproject.toml + rm -f pyproject.toml.bak + echo " ✓ 更新 pyproject.toml 项目名" +fi + +# 4. 初始化 uv 项目 +echo "🔧 初始化 uv 项目..." +uv init --no-readme # README 已从模板复制 + +# 4.5 生成 uv.lock（最佳实践：初始提交应包含 lockfile） +echo "🔒 生成 uv.lock..." +uv sync + +# 5. 初始化 Git 仓库（默认在 master 分支） +echo "🔧 初始化 Git 仓库..." +git init + +# 6. 初始提交在 master +echo "📝 创建初始提交..." +git add . +git commit -m "chore: 初始化项目 + +基于模板创建项目结构 +- 配置项目结构 +- 初始化 uv 依赖管理（包含 uv.lock） +- 设置 Git 工作流 (master/develop) +- 创建初始版本 $INITIAL_TAG" + +# 7. 创建初始 tag（在 master 上） +echo "🏷️ 创建初始标签: $INITIAL_TAG" +git tag -a "$INITIAL_TAG" -m "release: $INITIAL_TAG 初始版本 + +项目初始化完成" + +# 8. 创建 develop 分支 +echo "🌿 创建 develop 分支..." +git checkout -b develop + +# 9. 询问是否创建 GitHub 仓库 +echo "" +echo "✅ 项目创建完成！" +echo "" +echo "📍 项目位置: $FULL_PATH" +echo "🏷️ 初始版本: $INITIAL_TAG" +echo "" +echo "📌 下一步操作:" +echo " cd $FULL_PATH" +echo "" + +# 询问是否创建 GitHub 远程仓库 +read -p "是否创建 GitHub 远程仓库？(y/n): " -n 1 -r +echo +if [[ $REPLY =~ ^[Yy]$ ]]; then + # 检查 gh CLI 是否安装 + if ! command -v gh &> /dev/null; then + echo "⚠️ GitHub CLI (gh) 未安装，跳过远程仓库创建" + echo " 安装: brew install gh" + else + echo "🌐 创建 GitHub 远程仓库..." + cd "$FULL_PATH" + + # 使用 gh CLI 创建仓库 + gh repo create "$PROJECT_NAME" --private --source=. --remote=origin + + # 推送分支和标签（先切换回 master） + echo "📤 推送分支和标签到远程..." + git checkout master + git push -u origin master + git push origin "$INITIAL_TAG" + git push -u origin develop + git checkout develop + + echo "" + echo "✅ GitHub 仓库创建完成！" + + # 获取仓库 URL + REPO_URL=$(git config --get remote.origin.url) + if [[ "$REPO_URL" == "git@github.com"* ]]; then + # SSH URL + REPO_URL="https://github.com/$(git config --get user.name)/$PROJECT_NAME" + fi + echo " 👉 $REPO_URL" + fi +else + echo "⏭️ 跳过 GitHub 仓库创建" + echo " 稍后可手动执行:" + echo " cd $FULL_PATH && gh repo create $PROJECT_NAME --private --source=. --remote=origin" +fi + +echo "" +echo "🎉 项目初始化完成！" +echo "" +echo "📋 Git 工作流说明:" +echo " - master: 主分支（生产环境）- 禁止直接推送" +echo " - develop: 开发分支" +echo " - feature/xxx: 功能分支（从 develop 创建）" +echo " - bugfix/xxx: Bug 修复分支（从 develop 创建）" +echo "" +echo "📚 常用命令:" +echo " git checkout develop # 切换到开发分支" +echo " git checkout -b feature/xxx # 创建功能分支" +echo " git checkout develop && git merge --no-ff feature/xxx # 合并功能分支" +echo " git tag -a v1.0.0 -m \"release: v1.0.0\" # 创建版本标签" +echo "" +echo "📦 uv 常用命令:" +echo " uv run python script.py # 运行脚本（无需激活 venv）" +echo " uv add # 添加依赖" +echo " uv add --dev pytest black ruff # 添加开发依赖" +echo " uv lock --check # 检查 lockfile 是否最新" +echo " uv sync --frozen # CI 中使用（精确版本）" +echo "" +echo "📦 下一步:" +echo " cd $FULL_PATH" +echo " # 依赖已安装，虚拟环境已创建 (.venv)" +echo "" diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-archive.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-archive.md new file mode 100644 index 0000000..c836127 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-archive.md @@ -0,0 +1,45 @@ +--- +name: kb-archive +description: Archive, detach, purge, or rename KB objects while keeping registry, index, and links consistent. +args: + - name: action + description: detach, archive, purge, rename + required: true + - name: target + description: Project-relative note path when operating on a note. + required: false + - name: dest + description: Destination note path for rename. + required: false +tags: [Research, Obsidian, KB, Lifecycle] +--- + +# /kb-archive + +Use this command for KB lifecycle actions. + +## Project-level lifecycle + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-project-kb-core/scripts/project_kb.py" lifecycle --cwd "$PWD" --mode "$action" +``` + +Project archive means moving the whole project to: + +```text +Research/_archived/{project-slug}-{date}/ +``` + +## Note-level lifecycle + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-project-kb-core/scripts/project_kb.py" note-lifecycle --cwd "$PWD" --mode "$action" --note "$target" +``` + +If `action=rename`, also pass `--dest "$dest"`. + +Note archive means moving a canonical note into: + +```text +Research/{project-slug}/Archive/ +``` diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-index.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-index.md new file mode 100644 index 0000000..ff23c84 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-index.md @@ -0,0 +1,14 @@ +--- +name: kb-index +description: Refresh the auto index block inside 02-Index.md without overwriting curated content. +tags: [Research, Obsidian, KB] +--- + +# /kb-index + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-project-kb-core/scripts/project_kb.py" sync --cwd "$PWD" --scope index +``` + +The index is a human navigation note, not a registry mirror. +Only the auto-generated block should be refreshed here; curated sections must stay intact. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-ingest.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-ingest.md new file mode 100644 index 0000000..0c02d1a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-ingest.md @@ -0,0 +1,25 @@ +--- +name: kb-ingest +description: Ingest external material into Sources/* inside the bound project KB, then update registry, index, and daily note as needed. +args: + - name: path + description: Source path or URL to ingest. + required: true +tags: [Research, Obsidian, KB, Ingestion] +--- + +# /kb-ingest + +Use `obsidian-source-ingestion` with the new routing rules: + +- paper -> `Sources/Papers/` +- web -> `Sources/Web/` +- docs/spec -> `Sources/Docs/` +- dataset/benchmark -> `Sources/Data/` +- interview/transcript -> `Sources/Interviews/` +- loose imported note -> `Sources/Notes/` + +After ingest: +- update `_system/registry.md` +- update `02-Index.md` when the source is important +- append a short line to today's `Daily/` when this is part of an active session diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-init.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-init.md new file mode 100644 index 0000000..2df6ca4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-init.md @@ -0,0 +1,62 @@ +--- +name: kb-init +description: Initialize or rebuild a vault-first, project-scoped Obsidian KB under Research/{project-slug}/ for the current repository. +args: + - name: project + description: Optional project name. Defaults to the repository name. + required: false + - name: vault_path + description: Absolute Obsidian vault path. Defaults to OBSIDIAN_VAULT_PATH. + required: false + - name: force + description: Force scaffold refresh when the project already exists. + required: false + default: false +tags: [Research, Obsidian, KB] +--- + +# /kb-init + +Use the new KB scaffold under `Research/{project-slug}/`. + +## Run + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-project-kb-core/scripts/project_kb.py" bootstrap \ + --cwd "$PWD" \ + --vault-path "$vault_path" +``` + +If `project` is provided, add: + +```bash +--project-name "$project" +``` + +If `force=true`, add: + +```bash +--force +``` + +## Verify + +The scaffold must contain: + +```text +Research/{project-slug}/ + 00-Hub.md + 01-Plan.md + 02-Index.md + Sources/* + Knowledge/ + Experiments/ + Results/Reports/ + Writing/ + Daily/ + Maps/ + Archive/ + _system/ +``` + +It must also keep repo-local `.claude/project-memory/*` as runtime binding metadata only. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-links.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-links.md new file mode 100644 index 0000000..7aea63e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-links.md @@ -0,0 +1,25 @@ +--- +name: kb-links +description: Repair or strengthen wikilinks among canonical KB notes without generating extra artifact sprawl. +tags: [Research, Obsidian, KB] +--- + +# /kb-links + +Use `obsidian-kb-artifacts` for standalone wikilink repair. + +Default surfaces: +- `Sources/` +- `Knowledge/` +- `Experiments/` +- `Results/` +- `Writing/` +- `00-Hub.md` +- `01-Plan.md` +- `02-Index.md` + +Rules: +- repair links inside existing canonical notes first +- do not create new notes just to satisfy a weak connection +- after substantial link repair, run `/kb-sync` or `/kb-lint` +- only touch `Maps/` when the user explicitly wants artifact updates diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-lint.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-lint.md new file mode 100644 index 0000000..269a706 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-lint.md @@ -0,0 +1,13 @@ +--- +name: kb-lint +description: Run deterministic KB health checks and rewrite _system/lint-report.md. +tags: [Research, Obsidian, KB, Lint] +--- + +# /kb-lint + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-project-kb-core/scripts/kb_lint.py" --cwd "$PWD" +``` + +Checks include registry coverage, broken wikilinks, index coverage, canvas validity, and several KB consistency warnings. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-literature-review.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-literature-review.md new file mode 100644 index 0000000..9feae7a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-literature-review.md @@ -0,0 +1,25 @@ +--- +name: kb-literature-review +description: Run the project-scoped literature workflow from Sources/Papers into Knowledge, Writing, and Maps/literature.canvas. +tags: [Research, Obsidian, KB, Literature] +--- + +# /kb-literature-review + +Use `obsidian-literature-workflow`. + +Conditional outputs: +- `Knowledge/Literature Overview.md` only when paper notes contain enough Evidence Records for synthesis +- `Knowledge/Method Taxonomy.md` when useful and evidence-backed +- `Knowledge/Research Gaps.md` when useful and evidence-backed +- `Knowledge/Claim Map.md` or a warning when evidence is weak +- `Writing/related-work-draft.md` only when promoted claims pass the evidence gate +- `Maps/literature.canvas` + +Keep source notes in `Sources/Papers/`. Do not turn source notes into synthesis notes. + +Evidence gate: +- refuse polished `Knowledge` or `Writing` synthesis when paper notes lack Evidence Records, +- keep abstract-only or webpage-placeholder items in coverage / `To-Read`, +- generate a warning or `Knowledge/Claim Map.md` instead of a mature related-work draft when evidence is weak, +- preserve claim strength on literature canvas edges. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-log.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-log.md new file mode 100644 index 0000000..da27058 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-log.md @@ -0,0 +1,15 @@ +--- +name: kb-log +description: Update the current project Daily note and, when needed, the plan, hub, and runtime binding summary. +tags: [Research, Obsidian, KB, Daily] +--- + +# /kb-log + +Use `obsidian-project-kb-core`. + +Default targets: +- `Daily/YYYY-MM-DD.md` +- `01-Plan.md` when a durable task changes +- `00-Hub.md` only when project-level focus changes +- `.claude/project-memory/.md` as runtime sync summary diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-map.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-map.md new file mode 100644 index 0000000..43cd39a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-map.md @@ -0,0 +1,14 @@ +--- +name: kb-map +description: Generate or repair derived KB artifacts such as literature.canvas, optional Bases, or other explicit map outputs. +tags: [Research, Obsidian, KB, Maps] +--- + +# /kb-map + +Default automatic map maintenance is limited to `Maps/literature.canvas` from the literature workflow. + +Use `obsidian-kb-artifacts` for: +- canvas validation or repair +- explicit `.base` generation +- optional extra maps when the user asks for them diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-promote.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-promote.md new file mode 100644 index 0000000..557cb81 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-promote.md @@ -0,0 +1,16 @@ +--- +name: kb-promote +description: Promote durable content from Daily or source notes into canonical Knowledge, Experiments, Results, Results/Reports, or Writing notes. +tags: [Research, Obsidian, KB] +--- + +# /kb-promote + +Use `obsidian-project-kb-core` to decide whether content should become: +- `Knowledge/` +- `Experiments/` +- `Results/` +- `Results/Reports/` +- `Writing/` + +Do not promote raw session noise. Update `_system/registry.md` and `02-Index.md` after promotion. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-status.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-status.md new file mode 100644 index 0000000..6d56751 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-status.md @@ -0,0 +1,13 @@ +--- +name: kb-status +description: Summarize the current bound project KB status, including registry counts and key project note paths. +tags: [Research, Obsidian, KB] +--- + +# /kb-status + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-project-kb-core/scripts/project_kb.py" status --cwd "$PWD" +``` + +Optionally add `--project-id "$project_id"` when the repo has multiple bindings. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/kb-sync.md b/文档润色流和知识库构建流/claude-scholar/commands/kb-sync.md new file mode 100644 index 0000000..ddbcd81 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/kb-sync.md @@ -0,0 +1,34 @@ +--- +name: kb-sync +description: Run deterministic KB maintenance to refresh scaffold integrity, registry, index, daily note, and runtime binding summary. +args: + - name: scope + description: Sync scope such as auto, all, index, literature, experiments, or results. + required: false + default: auto +tags: [Research, Obsidian, KB] +--- + +# /kb-sync + +Use this when you want a deterministic project-KB resync after structural changes, note moves, migrations, or batch updates. + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-project-kb-core/scripts/project_kb.py" sync --cwd "$PWD" --scope "$scope" +``` + +Typical scopes: +- `auto` +- `all` +- `index` +- `literature` +- `experiments` +- `results` + +This refreshes: +- scaffold integrity under `Research/{project-slug}/` +- `_system/registry.md` +- `02-Index.md` +- today's `Daily/YYYY-MM-DD.md` +- repo-local `.claude/project-memory/.md` +- `00-Hub.md` recent changes when appropriate diff --git a/文档润色流和知识库构建流/claude-scholar/commands/learn.md b/文档润色流和知识库构建流/claude-scholar/commands/learn.md new file mode 100644 index 0000000..9899af1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/learn.md @@ -0,0 +1,70 @@ +# /learn - Extract Reusable Patterns + +Analyze the current session and extract any patterns worth saving as skills. + +## Trigger + +Run `/learn` at any point during a session when you've solved a non-trivial problem. + +## What to Extract + +Look for: + +1. **Error Resolution Patterns** + - What error occurred? + - What was the root cause? + - What fixed it? + - Is this reusable for similar errors? + +2. **Debugging Techniques** + - Non-obvious debugging steps + - Tool combinations that worked + - Diagnostic patterns + +3. **Workarounds** + - Library quirks + - API limitations + - Version-specific fixes + +4. **Project-Specific Patterns** + - Codebase conventions discovered + - Architecture decisions made + - Integration patterns + +## Output Format + +Create a skill file at `~/.claude/skills/learned/[pattern-name].md`: + +```markdown +# [Descriptive Pattern Name] + +**Extracted:** [Date] +**Context:** [Brief description of when this applies] + +## Problem +[What problem this solves - be specific] + +## Solution +[The pattern/technique/workaround] + +## Example +[Code example if applicable] + +## When to Use +[Trigger conditions - what should activate this skill] +``` + +## Process + +1. Review the session for extractable patterns +2. Identify the most valuable/reusable insight +3. Draft the skill file +4. Ask user to confirm before saving +5. Save to `~/.claude/skills/learned/` + +## Notes + +- Don't extract trivial fixes (typos, simple syntax errors) +- Don't extract one-time issues (specific API outages, etc.) +- Focus on patterns that will save time in future sessions +- Keep skills focused - one pattern per skill diff --git a/文档润色流和知识库构建流/claude-scholar/commands/mine-writing-patterns.md b/文档润色流和知识库构建流/claude-scholar/commands/mine-writing-patterns.md new file mode 100644 index 0000000..1759311 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/mine-writing-patterns.md @@ -0,0 +1,135 @@ +--- +name: mine-writing-patterns +description: Read one or more papers and update the active installed paper-miner writing memory with reusable writing patterns, structure signals, reusable phrasing, venue-specific signals, and rebuttal-friendly language. +args: + - name: source + description: Paper source path, URL, arXiv link, or a short description of the target papers + required: true + - name: focus + description: Optional focus area (general/introduction/method/results/rebuttal/venue) + required: false + default: general +tags: [Research, Writing, Paper Mining, Knowledge Extraction] +--- + +# /mine-writing-patterns - Installed Writing Memory Mining + +Read the paper source "$source" and update the active installed **paper-miner writing memory**. + +## Default target + +Always write mined knowledge into the active installed skill memory, not the repository checkout copy: + +```text +~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md +``` + +This command does **not** create project-specific writing memory unless the user explicitly asks for a project-local writing memory. + +## When to use + +Use this command when you want to: +- learn reusable writing patterns from a strong paper, +- study how a venue frames introductions, methods, results, or rebuttals, +- mine phrasing and structure signals before drafting, +- enrich the writing memory that powers `ml-paper-writing` and `review-response`. + +## Usage + +### Basic usage + +```bash +/mine-writing-patterns path/to/paper.pdf +``` + +### Mine from an arXiv paper + +```bash +/mine-writing-patterns https://arxiv.org/abs/2301.xxxxx +``` + +### Focus on rebuttal or venue signals + +```bash +/mine-writing-patterns path/to/paper.pdf rebuttal +/mine-writing-patterns path/to/paper.pdf venue +``` + +## Workflow + +### Step 1: Resolve the paper source + +Acceptable inputs: +- local PDF +- local DOCX +- arXiv URL +- readable web URL +- short natural-language request that identifies the paper(s) + +If the source is ambiguous, narrow it before mining. + +### Step 2: Invoke `paper-miner` + +Use the `paper-miner` agent to: +- extract paper content, +- identify reusable writing knowledge, +- merge it into the active installed writing memory, +- avoid duplicate entries, +- preserve source attribution. + +### Step 3: Respect the focus mode + +Interpret `$focus` as follows: + +| Focus | Priority | +|------|----------| +| `general` | Mine balanced signals across all major sections | +| `introduction` | Emphasize framing, motivation, and contribution setup | +| `method` | Emphasize exposition style, technical sequencing, and clarity | +| `results` | Emphasize result narration, claim-evidence language, and interpretation | +| `rebuttal` | Emphasize clarification phrases, response structure, and reviewer-facing tone | +| `venue` | Emphasize venue-specific style and convention signals | + +### Step 4: Update the canonical memory only + +The canonical write target is the active installed skill memory: + +```text +~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md +``` + +Update one or more of these sections: +- `Writing patterns mined` +- `Structure signals` +- `Reusable phrasing` +- `Venue-specific signals` +- `How this helps our writing` +- `Source index` + +If that file is unavailable in the current runtime, use the configured installed skill home for the active runtime and state the exact path in the final summary. Do not silently fall back to the repository checkout. + +Do not create project-local writing memory. +Do not scatter the mined result across multiple maintained knowledge files. + +### Step 5: Return a standardized mining summary + +The final response should follow the `paper-miner` standardized output format: +- metadata +- memory write summary +- new reusable patterns +- how we should reuse this +- blockers or limits + +## Related integrations + +- `ml-paper-writing` reads this active installed memory before drafting or revising sections. +- `review-response` reads this active installed memory when tone, phrasing, and rebuttal structure matter. +- `paper-miner` is the agent that performs the actual mining work. + +## Success criteria + +- the target paper is read successfully, +- reusable writing knowledge is merged into the canonical memory, +- source attribution is preserved, +- no project-specific writing memory is created, +- the user receives a standardized mining summary. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-ingest.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-ingest.md new file mode 100644 index 0000000..722d1f8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-ingest.md @@ -0,0 +1,11 @@ +--- +name: obsidian-ingest +description: Deprecated alias for `/kb-ingest`. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-ingest (deprecated) + +Use `/kb-ingest` instead. + +Keep the new `Sources/*` routing and do not recreate top-level `Papers/`. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-init.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-init.md new file mode 100644 index 0000000..4ad7ef5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-init.md @@ -0,0 +1,11 @@ +--- +name: obsidian-init +description: Deprecated alias for `/kb-init`. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-init (deprecated) + +Use `/kb-init` instead. + +This alias keeps the new vault-first layout and should not recreate the legacy workflow. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-link.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-link.md new file mode 100644 index 0000000..f5dffac --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-link.md @@ -0,0 +1,11 @@ +--- +name: obsidian-link +description: Deprecated alias for `/kb-links`. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-link (deprecated) + +Use `/kb-links` instead. + +Repair links against the new canonical KB layout. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-note.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-note.md new file mode 100644 index 0000000..a3d24e7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-note.md @@ -0,0 +1,15 @@ +--- +name: obsidian-note +description: Deprecated alias for `/kb-log`, `/kb-promote`, or `/kb-archive` depending on note intent. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-note (deprecated) + +Use one of these replacements instead: + +- `/kb-log` for daily capture +- `/kb-promote` for canonicalization +- `/kb-archive` for note lifecycle actions such as archive, purge, or rename + +Do not recreate the legacy note workflow. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-notes.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-notes.md new file mode 100644 index 0000000..5c1c730 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-notes.md @@ -0,0 +1,14 @@ +--- +name: obsidian-notes +description: Deprecated alias for `/kb-promote` or `/kb-literature-review`. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-notes (deprecated) + +Use one of these replacements instead: + +- `/kb-promote` for promoting stable note content into canonical notes +- `/kb-literature-review` for literature normalization and synthesis + +Keep the new project-scoped KB structure. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-project.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-project.md new file mode 100644 index 0000000..e8bc10e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-project.md @@ -0,0 +1,13 @@ +--- +name: obsidian-project +description: Deprecated alias for `/kb-status`, with `/kb-archive` for explicit lifecycle actions. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-project (deprecated) + +Use `/kb-status` instead for the bound project overview. + +If you need lifecycle actions, use `/kb-archive` explicitly. + +Project archive means moving the whole project into `Research/_archived/`, not note-level `Archive/`. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-review.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-review.md new file mode 100644 index 0000000..aa78a7a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-review.md @@ -0,0 +1,11 @@ +--- +name: obsidian-review +description: Deprecated alias for `/kb-literature-review`. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-review (deprecated) + +Use `/kb-literature-review` instead. + +Keep the `Sources/Papers -> Knowledge / Writing / Maps/literature.canvas` workflow. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-sync.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-sync.md new file mode 100644 index 0000000..841a6df --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-sync.md @@ -0,0 +1,11 @@ +--- +name: obsidian-sync +description: Deprecated alias for `/kb-sync`. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-sync (deprecated) + +Use `/kb-sync` instead. + +This alias should follow the new project-scoped KB sync semantics. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/obsidian-views.md b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-views.md new file mode 100644 index 0000000..1d08792 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/obsidian-views.md @@ -0,0 +1,11 @@ +--- +name: obsidian-views +description: Deprecated alias for `/kb-map`. +tags: [Research, Obsidian, Deprecated] +--- + +# /obsidian-views (deprecated) + +Use `/kb-map` instead. + +Additional canvas or `.base` artifacts remain explicit-only. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/plan.md b/文档润色流和知识库构建流/claude-scholar/commands/plan.md new file mode 100644 index 0000000..6b43990 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/plan.md @@ -0,0 +1,113 @@ +--- +description: Restate requirements, assess risks, and create step-by-step implementation plan. WAIT for user CONFIRM before touching any code. +--- + +# Plan Command + +This command creates a comprehensive implementation plan before writing any code. + +## What This Command Does + +1. **Restate Requirements** - Clarify what needs to be built +2. **Identify Risks** - Surface potential issues and blockers +3. **Create Step Plan** - Break down implementation into phases +4. **Wait for Confirmation** - MUST receive user approval before proceeding + +## When to Use + +Use `/plan` when: +- Starting a new feature +- Making significant architectural changes +- Working on complex refactoring +- Multiple files/components will be affected +- Requirements are unclear or ambiguous + +## How It Works + +This command should: + +1. **Analyze the request** and restate requirements in clear terms +2. **Break down into phases** with specific, actionable steps +3. **Identify dependencies** between components +4. **Assess risks** and potential blockers +5. **Estimate complexity** (High/Medium/Low) +6. **Present the plan** and WAIT for your explicit confirmation + +## Example Usage + +``` +User: /plan I need to add real-time notifications when markets resolve + +Assistant: +# Implementation Plan: Real-Time Market Resolution Notifications + +## Requirements Restatement +- Send notifications to users when markets they're watching resolve +- Support multiple notification channels (in-app, email, webhook) +- Ensure notifications are delivered reliably +- Include market outcome and user's position result + +## Implementation Phases + +### Phase 1: Database Schema +- Add notifications table with columns: id, user_id, market_id, type, status, created_at +- Add user_notification_preferences table for channel preferences +- Create indexes on user_id and market_id for performance + +### Phase 2: Notification Service +- Create notification service in lib/notifications.py +- Implement notification queue using Celery/Redis +- Add retry logic for failed deliveries +- Create notification templates (Jinja2) + +### Phase 3: Integration Points +- Hook into market resolution logic (when status changes to "resolved") +- Query all users with positions in market +- Enqueue notifications for each user + +### Phase 4: API/Frontend +- Create notification endpoints (GET /api/notifications, POST /api/notifications/read) +- WebSocket support for real-time updates +- Frontend notification bell component +- Notification preferences page + +## Dependencies +- Redis (for Celery queue) +- Celery (task queue) +- Email service (SendGrid/Resend/SMTP) +- WebSocket server (channels/websocket) + +## Risks +- HIGH: Email deliverability (SPF/DKIM required) +- MEDIUM: Performance with 1000+ users per market +- MEDIUM: Notification spam if markets resolve frequently +- LOW: WebSocket connection overhead + +## Estimated Complexity: MEDIUM +- Backend: 4-6 hours +- API/Frontend: 3-4 hours +- Testing: 2-3 hours +- Total: 9-13 hours + +**WAITING FOR CONFIRMATION**: Proceed with this plan? (yes/no/modify) +``` + +## Important Notes + +**CRITICAL**: Do **NOT** write any code until the user explicitly confirms the plan with "yes" or "proceed" or a similar affirmative response. + +If you want changes, respond with: +- "modify: [your changes]" +- "different approach: [alternative]" +- "skip phase 2 and do phase 3 first" + +## Integration with Other Commands + +After planning: +- Use `/tdd` to implement with test-driven development +- Use `/build-and-fix` if build errors occur +- Use `/code-review` to review completed implementation + +## Related Skills + +- `architecture-design` (when structural design is needed) diff --git a/文档润色流和知识库构建流/claude-scholar/commands/poster.md b/文档润色流和知识库构建流/claude-scholar/commands/poster.md new file mode 100644 index 0000000..8406793 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/poster.md @@ -0,0 +1,31 @@ +--- +name: poster +description: Design academic poster for conference +--- + +# Design Academic Poster + +Use the post-acceptance skill to design an academic poster for your conference presentation. + +## What this command does: + +1. Guides you through poster design process +2. Provides layout templates and design guidelines +3. Helps with visual hierarchy and content organization + +## Usage: + +Simply run `/poster` and follow the prompts to design your academic poster. + +The command will: +- Ask about poster size requirements (A0/A1) +- Suggest layout structure (3-4 columns) +- Provide design guidelines from `references/design-guidelines.md` +- Reference templates from `references/poster-templates/` + +## Tips: + +- Start designing 1-2 weeks before printing +- Use high-resolution images (300 DPI) +- Keep text concise and readable +- Print a test version before final printing diff --git a/文档润色流和知识库构建流/claude-scholar/commands/presentation.md b/文档润色流和知识库构建流/claude-scholar/commands/presentation.md new file mode 100644 index 0000000..8b59187 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/presentation.md @@ -0,0 +1,31 @@ +--- +name: presentation +description: Create conference presentation slides quickly +--- + +# Create Conference Presentation + +Use the post-acceptance skill to create presentation slides for your accepted paper. + +## What this command does: + +1. Guides you through presentation slide creation +2. Provides templates and design guidelines +3. Helps with time management and content structure + +## Usage: + +Simply run `/presentation` and follow the prompts to create your conference presentation slides. + +The command will: +- Ask about your presentation time limit +- Suggest slide structure +- Provide design guidelines from `references/design-guidelines.md` +- Reference templates from `references/presentation-templates/` + +## Tips: + +- Start preparing 2-3 weeks before the conference +- Practice your presentation multiple times +- Keep slides simple and visual +- Prepare backup PDF version diff --git a/文档润色流和知识库构建流/claude-scholar/commands/promote.md b/文档润色流和知识库构建流/claude-scholar/commands/promote.md new file mode 100644 index 0000000..65b5797 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/promote.md @@ -0,0 +1,31 @@ +--- +name: promote +description: Generate promotion content for multiple platforms +--- + +# Generate Promotion Content + +Use the post-acceptance skill to generate promotion content for your accepted paper across multiple platforms. + +## What this command does: + +1. Generates promotion content for Twitter/X, LinkedIn, blog, and news +2. Uses the generate-promotion.py script for automated content generation +3. Provides examples and best practices + +## Usage: + +Simply run `/promote` and follow the prompts to generate promotion content. + +The command will: +- Ask about target platforms (Twitter, LinkedIn, Blog, News) +- Generate platform-specific content +- Provide examples from `references/promotion-examples/` +- Use `scripts/generate-promotion.py` for automation + +## Tips: + +- Prepare promotion content 1 week before conference +- Coordinate timing with conference schedule +- Use high-quality visuals +- Include links to paper and code diff --git a/文档润色流和知识库构建流/claude-scholar/commands/rebuttal.md b/文档润色流和知识库构建流/claude-scholar/commands/rebuttal.md new file mode 100644 index 0000000..96754c6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/rebuttal.md @@ -0,0 +1,157 @@ +--- +name: rebuttal +description: Start systematic review response workflow for professional rebuttal writing +args: + review_file: + description: 审稿意见文件路径（可选） + required: false +--- + +# /rebuttal - 审稿响应工作流 + +启动系统化的rebuttal撰写流程，从审稿意见分析到最终rebuttal文档生成。 + +## 用法 + +```bash +/rebuttal [review_file] +``` + +**参数**: +- `review_file` (可选): 包含审稿意见的文件路径 + - 如果不提供，将引导用户提供审稿意见 + +## 功能 + +此命令将启动完整的rebuttal撰写工作流： + +1. **获取审稿意见** - 读取或接收审稿意见 +2. **分析和分类** - 将意见拆成 atomic objections，并分类为Major/Minor/Typo/Misunderstanding +3. **制定策略** - 为每条意见选择响应策略 +4. **撰写rebuttal** - 生成结构化的回复文档 +5. **语气优化** - 确保专业、礼貌的表达 +6. **生成输出** - 保存最终的rebuttal文档 + + +## 工作流程 + +### 步骤 1: 获取审稿意见 + +如果提供了`review_file`参数： +- 读取文件内容 +- 识别审稿人数量和意见结构 + +如果未提供文件： +- 引导用户粘贴或描述审稿意见 +- 确认审稿人数量 + +### 步骤 2: 分析和分类 + +优先使用`review-response` skill；如果当前 runtime 提供 `rebuttal-writer` agent，可以用它辅助分析： +- 按审稿人分组意见 +- 拆分每条 atomic objection +- 分类为Major/Minor/Typo/Misunderstanding +- 识别优先级 + +### 步骤 3: 制定响应策略 + +为每条意见选择策略： +- **Accept** - 接受并改进 +- **Defend** - 礼貌辩护 +- **Clarify** - 澄清误解 +- **Experiment** - 补充实验 + + +### 步骤 4: 撰写Rebuttal + +生成结构化的回复： +- 为每条意见撰写Response和Changes +- 包含具体的位置引用 +- 提供证据和理由 +- 每条 response 必须包含 evidence anchor：paper location、result table、figure、analysis artifact、citation、Evidence Record ID、planned experiment status，或 `unresolved` + +### 步骤 5: 语气优化 + +检查和优化语气： +- 确保每个回复以感谢开始 +- 避免防御性或攻击性表达 +- 保持专业和尊重 + +### 步骤 6: 生成输出 + +保存最终文档： +- `rebuttal.md` - 完整的rebuttal文档 +- `review-analysis.md` - 审稿意见分析（可选） +- `experiment-plan.md` - 补充实验计划（如果需要补充实验） + + +## 输出文件 + +执行此命令后，将生成以下文件： + +### rebuttal.md +完整的rebuttal文档，包含： +- 开场白（感谢审稿人） +- 逐条回复（Response + Changes） +- 主要修改总结 + +### review-analysis.md（可选） +审稿意见分析文档，包含： +- 意见分类统计 +- 策略选择说明 +- 需要补充的实验列表 + +### experiment-plan.md（可选） +补充实验计划文档，包含： +- 需要补充的实验列表 +- 每个实验的目的和预期结果 +- 实验的优先级和时间估计 + +## 使用示例 + +### 示例 1: 提供审稿意见文件 + +```bash +/rebuttal reviews.txt +``` + +将读取`reviews.txt`文件中的审稿意见，并启动rebuttal撰写流程。 + +### 示例 2: 交互式输入 + +```bash +/rebuttal +``` + +将引导你粘贴或描述审稿意见，然后启动rebuttal撰写流程。 + + +## 注意事项 + +### 重要原则 + +1. **覆盖优先** - 可以使用人工阅读或脚本辅助统计 atomic objections；不要因为自然语言总结而漏掉具体意见 +2. **保持专业语气** - 所有回复都要礼貌、尊重、有理有据 +3. **提供具体证据** - 每个回复都要包含具体的位置引用和证据 +4. **完整性检查** - 确保所有审稿意见都得到回应 + +### 参考资源 + +此命令会自动使用以下参考文档： +- `review-classification.md` - 意见分类标准 +- `response-strategies.md` - 响应策略指南 +- `rebuttal-templates.md` - 回复模板库 +- `tone-guidelines.md` - 语气优化指南 + +### Agent调用 + +如果当前 runtime 提供 `rebuttal-writer` agent，可以调用它来执行 rebuttal 撰写任务。若 agent 不可用，直接按 `review-response` skill 和本命令流程完成，不要阻塞。 + +## 相关命令 + +- `/commit` - 提交修改后的论文 +- `/code-review` - 审查代码质量 + +--- + +**提示**: 使用此命令前，建议先准备好审稿意见文件，并确保已经完成论文的必要修改。 diff --git a/文档润色流和知识库构建流/claude-scholar/commands/refactor-clean.md b/文档润色流和知识库构建流/claude-scholar/commands/refactor-clean.md new file mode 100644 index 0000000..1d1726d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/refactor-clean.md @@ -0,0 +1,29 @@ +# Refactor Clean + +Safely identify and remove dead code with test verification: + +1. Run dead code analysis tools: + - vulture: Find unused Python code (functions, classes, variables) + - pyflakes: Detect unused imports and variables + - ruff check --select F401: Find unused imports + - pip-audit: Check for security vulnerabilities + +2. Generate comprehensive report in .reports/dead-code-analysis.md + +3. Categorize findings by severity: + - SAFE: Test files, unused utilities, unused imports + - CAUTION: API routes, models, fixtures + - DANGER: Config files, main entry points, registry decorators + +4. Propose safe deletions only + +5. Before each deletion: + - Run full test suite (pytest) + - Verify tests pass + - Apply change + - Re-run tests + - Rollback if tests fail + +6. Show summary of cleaned items + +Never delete code without running tests first! diff --git a/文档润色流和知识库构建流/claude-scholar/commands/research-init.md b/文档润色流和知识库构建流/claude-scholar/commands/research-init.md new file mode 100644 index 0000000..1ee1e64 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/research-init.md @@ -0,0 +1,292 @@ +--- +name: research-init +description: Initialize a research project with Zotero-integrated literature review. Creates or audits project-scoped sources, generates research question cards, and only writes a research proposal when the evidence gate passes. +args: + - name: topic + description: Research topic or keywords + required: true + - name: scope + description: Review scope (focused/broad) + required: false + default: focused + - name: output_type + description: Output type (review/proposal/both). All modes produce research-question-card.md; references.bib is produced only when reliable citation metadata exists; review adds literature-review.md only when evidence is sufficient; proposal adds research-proposal.md only when the selected card passes the proposal readiness gate. + required: false + default: both +tags: [Research, Literature Review, Zotero, Paper Search] +--- + +# /research-init - Zotero-Integrated Research Startup Workflow + +Launch a project-scoped literature startup workflow for the research topic "$topic", with scope "$scope" and output type "$output_type". + +Default behavior is evidence-first: if Zotero is unavailable, if full-paper evidence is insufficient, or if the selected Research Question Card is not ready, produce an intake/audit result instead of forcing a polished proposal. + +## Usage + +### Basic Usage + +```bash +/research-init "transformer interpretability" +``` + +### Specify Scope + +```bash +/research-init "few-shot learning" focused +``` + +### Specify All Parameters + +```bash +/research-init "neural architecture search" broad both +``` + +## Workflow + +Execute the following steps in order: + +### Step 0: Intake and Capability Gate + +Before creating collections or writing files: + +1. Confirm the practical purpose: new project intake, literature review, proposal draft, or source audit. +2. Check whether Zotero MCP is configured and writable. +3. If Zotero MCP is unavailable, read-only, or the user asks for dry-run mode: + - do **not** create collections, + - do **not** import papers, + - produce `research-question-card.md` and a source candidate/audit section, + - either skip `references.bib` or create a stub that clearly says canonical BibTeX is unavailable unless reliable BibTeX can be generated from existing sources, + - stop before `literature-review.md` or `research-proposal.md` unless the user explicitly provides sufficient local evidence. +4. If the topic, target venue/audience, or project boundary is ambiguous enough to change the search strategy, ask a short clarifying question before acting. + +### Step 1: Create Zotero Research Collection + +1. Call the Zotero MCP tool `zotero_create_collection` to create the main collection, named `Research-{Topic}-{YYYY-MM}` (extract a short PascalCase keyword from the topic, use the current year and month) +2. Create sub-collections under the main collection: + - `Core Papers` + - `Methods` + - `Applications` + - `Baselines` + - `To-Read` +3. Record the `collection_key` for each sub-collection (needed for import in Step 2) + +### Step 2: Literature Search and Import + +1. Use WebSearch to find papers related to "$topic" + - Search strategy: use the topic directly, plus variant combinations of key terms + - Target sources: arXiv, DOI-backed publisher landing pages, conference proceedings with full-paper pages, direct PDF pages + - Time range: focused mode searches the last 3 years, broad mode searches the last 5 years + - Target paper count: 20-50 papers for focused scope, 50-100 for broad scope +2. **Source quality filter before extraction**: + - Prefer candidates that expose at least one of: DOI, arXiv ID, direct PDF URL, or clear citation metadata for a full paper + - **Explicitly avoid abstract-only pages as primary sources** when a better source exists for the same paper (for example conference abstract listings, event schedule pages, teaser pages, or pages that only contain a short abstract with no DOI/arXiv/PDF) + - For the same title, source preference should be: + 1. DOI-backed publisher page + 2. arXiv abs/pdf page + 3. direct PDF URL + 4. full-paper proceedings landing page + 5. abstract-only page (last resort only) + - If the discovered page is clearly abstract-only and no DOI/arXiv/PDF can be extracted, do **not** prioritize it for import; keep searching for a better source first + - Abstract-only pages should **not** be counted toward the target paper quota unless all better identifier-bearing/full-paper sources for that title have been exhausted +3. Extract candidate DOI / arXiv ID / landing-page URL from filtered search results +4. **Classify before import**: For each paper, determine which sub-collection it belongs to (Core Papers, Methods, Applications, Baselines, or To-Read) based on its title, abstract, and venue +5. **Pre-import deduplication (two-step)**: + - Call the Zotero MCP tool `zotero_search_items` with the DOI string when available to find potential matches + - Call `zotero_get_item_metadata` on results to confirm the DOI field matches exactly + - If confirmed match → skip import, log ("Already exists: {DOI} → {item_key}") + - For papers without DOI → search by title using token overlap ratio (lowercase both titles, remove punctuation, compute intersection of words / union of words). Ratio > 0.8 = duplicate +6. **Abstract-only page guardrail (mandatory)**: + - Before calling `zotero_add_items_by_identifier`, check whether the chosen URL is likely an abstract-only page + - Strong signals include: URL/path contains `abstract`, page title/heading is an abstract listing, page body lacks PDF/full-text links, and no DOI/arXiv identifier is visible + - If it is abstract-only **and** no DOI/arXiv/PDF can be recovered, prefer one of: + - keep searching for a better source for the same title, or + - skip this candidate for now + - Do **not** eagerly import abstract-only pages into analytical sub-collections just to satisfy paper count + - If an abstract-only page is imported as a last-resort placeholder, it must be treated as `To-Read` only, never as a confirmed paper source for `Core Papers`, `Methods`, `Applications`, or `Baselines` + - When you skip such a candidate during Step 2, print this exact user-facing line in the terminal output: + - `Skipped abstract-only page; searching better source` +7. **Smart import with collection assignment**: Call `zotero_add_items_by_identifier` with the target sub-collection's `collection_key`, `attach_pdf=true`, and `fallback_mode="webpage"` + - Route priority is fixed: DOI / doi.org URL → arXiv ID or arXiv URL → direct PDF URL → generic landing-page URL + - The tool will prefer proper paper/preprint items and only fall back to `webpage` when no reliable DOI/arXiv identifier is found + - For difficult publisher pages and cookie-gated PDFs, the import path may additionally use the local Zotero connector/browser session and optional Playwright-assisted PDF rescue before falling back to `webpage` + - The server records internal import events automatically for debugging, but that internal ledger is not part of the default public MCP tool surface and should not be part of the normal workflow +8. **Collection guardrail**: Only keep `paper` imports in `Core Papers`, `Methods`, `Applications`, or `Baselines` + - If the import result says `Saved as webpage`, move or create that entry only in `To-Read` +9. **PDF follow-up**: `zotero_add_items_by_identifier(..., attach_pdf=true)` already runs the PDF cascade by default. If the import result says `PDF not attached`, optionally call `zotero_find_and_attach_pdfs({ item_keys: [...] })` for a second pass. If it still fails, log it and continue. +10. **Automatic postpass dedupe/reconcile (mandatory)**: after the import batch, call `zotero_reconcile_collection_duplicates` on the main research collection with: + - `collection_key = {main research collection key}` + - `include_subcollections = true` + - `dry_run = false` + - `reconcile_local_only = true` + - `local_db_fallback = false` + - Goal: automatically clean duplicate parent items across the whole research collection tree, keep the canonical item with PDF when available, merge collection memberships, and remove stale duplicates when the standard APIs can handle them + - **Precondition**: destructive dedupe with `dry_run=false` requires Zotero MCP write/delete permission, which means `UNSAFE_OPERATIONS=items` must already be enabled + - **Default safety mode**: do **not** enable `local_db_fallback=true` automatically inside `/research-init`; only mention it in debug/recovery mode if residual duplicates remain after the standard pass +11. **Step-2 terminal summary (mandatory)**: after import + postpass dedupe, print a user-facing compact summary table: + + ``` + | Input | Zotero Key | Collection | Status | + |-------|------------|------------|--------| + | ... | ABC123 | Core Papers | Imported as paper + PDF attached | + ``` + + - `Status` should use only user-facing phrases: + - `Imported as paper + PDF attached` + - `Imported as paper` + - `Saved as webpage + PDF attached` + - `Saved as webpage` + - `Import failed` + - If a candidate was rejected before import because it is abstract-only and no DOI/arXiv/PDF could be recovered, print this standalone line before the table entry list continues: + - `Skipped abstract-only page; searching better source` + - After the table, print one compact dedupe line: + - `Collection dedupe summary: duplicate groups 0, duplicates trashed 0` + - or `Collection dedupe summary: duplicate groups N, duplicates trashed M` + - Then print one compact missing-PDF repair line: + - `Missing PDF postpass: repaired 0 items` + - or `Missing PDF postpass: repaired N items` + - Read these counts from the `zotero_reconcile_collection_duplicates` summary; do not invent them + - Do **not** print `route=...`, `pdf_source=...`, `fallback_reason=...`, `local_item_key=...`, or reconcile internals in the default terminal output + - Do **not** dump the raw dedupe markdown table in normal mode; read the tool result, extract the counts, and summarize it in one user-facing line + - If you need implementation details for debugging, explicitly say you are switching to debug mode and rerun with `ZOTERO_MCP_DEBUG_IMPORT=1` + +**Note**: Zotero items can still be added to or removed from collections later, but `/research-init` should prefer correct `collection_key` assignment during import so analytical sub-collections stay clean. The default command path should now rely on `zotero_reconcile_collection_duplicates` as the standard postpass cleanup, not the older item-by-item local reconcile helper. +When in doubt between a full-paper source and an abstract-only page for the same title, always prefer the full-paper source, even if the abstract-only page ranks higher in search results. Use canonical Zotero MCP tool names consistently in this workflow: `zotero_create_collection`, `zotero_search_items`, `zotero_get_item_metadata`, `zotero_add_items_by_identifier`, `zotero_find_and_attach_pdfs`, and `zotero_reconcile_collection_duplicates`. + +### Step 3: Paper Analysis + +1. Call `zotero_get_collection_items` to list imported papers +2. Call `zotero_get_item_metadata` with `include_abstract: true` to get metadata and abstracts (ensures abstracts are available as fallback if full-text retrieval fails) +3. Call `zotero_get_item_fulltext` to read full text of papers with PDFs +3. For each paper, extract: + - Research question and motivation + - Core methodology + - Key findings and contributions + - Limitations and future work +4. Use these structured notes as intermediate analysis to inform the final `literature-review.md` (they are not a separate output file) + +### Step 4: Gap Analysis and Synthesis + +1. Analyze all collected papers for: + - Research trends and directions + - Methodological gaps + - Unexplored application domains + - Contradictions in research findings +2. Identify 2-3 concrete research gaps +3. Formulate 2-3 potential research questions as Research Question Cards: + + ```md + ## Research Question Card + + Question: + Type: exploratory | confirmatory | applied + Hypothesis: + Why it matters: + Current evidence: + Missing evidence: + What would support it: + What would falsify it: + Minimal next action: + Decision: explore | read more | run experiment | stop + ``` + +4. Apply the **Proposal Readiness Gate** from `skills/research-ideation/references/research-contract.md`: + - at least one full-paper/preprint/dataset/experiment-artifact Evidence Record supports the selected direction, + - weak sources such as webpage placeholders or abstract-only notes are labeled as weak support, + - current evidence, missing evidence, support criteria, falsification criteria, and minimal next action are explicit. +5. Select one card as the default direction for `research-proposal.md` only if it passes this gate. If none is ready for a proposal, state that the next action is `read more` or `explore` instead of forcing a proposal narrative. + +### Step 5: Generate Outputs + +Generate corresponding files based on output_type "$output_type": + +Output matrix: + +| output_type | Always generated | Additional generated files | +|---|---|---| +| `review` | `research-question-card.md` | `references.bib` when reliable citation metadata exists; `literature-review.md` when evidence is sufficient | +| `proposal` | `research-question-card.md` | `references.bib` when reliable citation metadata exists; `research-proposal.md` if a selected card passes the gate | +| `both` | `research-question-card.md` | `references.bib` when reliable citation metadata exists; `literature-review.md` when evidence is sufficient; `research-proposal.md` if a selected card passes the gate | + +File contracts: + +1. **research-question-card.md** - 2-3 candidate Research Question Cards plus the selected default card and minimal next action +2. **literature-review.md** - Structured literature review with real citations from Zotero (generated for `review` and `both` only when the evidence base is sufficient) +3. **research-proposal.md** - Research proposal derived from the selected Research Question Card (generated for `proposal` and `both` only when the selected card passes the Proposal Readiness Gate) +4. **references.bib** - BibTeX references from Zotero data, generated only when reliable citation metadata exists + - **Primary method**: Use Zotero REST API with `?format=bibtex` to export accurate, complete BibTeX entries + ``` + GET https://api.zotero.org/users/{user_id}/collections/{collection_key}/items?format=bibtex + ``` + **Note**: The REST API `?format=bibtex` on a collection only exports items directly in that collection, not items in sub-collections. You must iterate each sub-collection key individually, or collect all item keys and use the items endpoint: `GET https://api.zotero.org/users/{user_id}/items?itemKey=KEY1,KEY2,...&format=bibtex` + - **Fallback**: Construct BibTeX manually from `zotero_get_item_metadata` metadata (note: volume, issue, pages, and publisher fields are not available via this tool — entries will be incomplete) + +Use TodoWrite to track progress throughout the workflow. + +At the end, summarize: +- selected question, +- current evidence, +- missing evidence, +- minimal next action, +- whether the next decision is `explore`, `read more`, `run experiment`, or `stop`. + +## Error Handling + +If the default Zotero MCP path fails during execution, use these workflow fallbacks: + +1. **Zotero MCP unavailable or read-only** → Switch to dry-run/intake mode; do not create collections, import papers, or pretend references were saved. +2. **`zotero_create_collection` fails** → If REST credentials are configured and the user intended write mode, create via Zotero REST API directly; otherwise switch to dry-run/intake mode. +3. **`zotero_add_items_by_identifier` fails** → Retry with a narrower identifier (explicit DOI or arXiv ID). If the source is a publisher landing page or direct PDF, allow the smart importer to use connector/browser-session rescue and optional Playwright-assisted PDF rescue first. If smart import still fails, use an out-of-band fallback such as CrossRef metadata lookup (`https://api.crossref.org/works/{DOI}`) and retry the DOI-specific path or save the page as a manual `webpage`. +4. **`zotero_get_item_fulltext` fails** → Use `WebFetch` on the paper's DOI URL to scrape abstract → fall back to `abstractNote` from `zotero_get_item_metadata` + domain knowledge +5. **`zotero_find_and_attach_pdfs` fails** → Log and continue; PDFs are not required for analysis. If a needed paper still lacks a PDF, ask the user to attach it manually in Zotero Desktop and rerun analysis later. +6. **`zotero_reconcile_collection_duplicates` fails** → Keep the import results, log that postpass dedupe failed, and continue with analysis. In debug mode, inspect the tool's summary and consider rerunning with `local_db_fallback=true` only if local-only duplicates remain and the user explicitly wants aggressive cleanup. +7. **Single paper fails** → Log error, skip, and continue to next paper +8. **API rate limit** → Wait 5 seconds and retry, up to 3 attempts + +## Completion Checklist + +Before finishing, verify: + +- [ ] Zotero write mode or dry-run/intake mode explicitly stated +- [ ] In write mode, Zotero collection `Research-{Topic}-{YYYY-MM}` created with sub-collections +- [ ] In write mode, papers imported and organized into sub-collections (target: 20-50 focused / 50-100 broad) +- [ ] In write mode, PDFs attached for available open-access papers +- [ ] Full-text analysis completed for core papers when available; otherwise source limitations are explicit +- [ ] Gap analysis identifies at least 2-3 concrete research gaps +- [ ] Research Question Cards generated with support criteria, falsification criteria, and minimal next action +- [ ] Proposal Readiness Gate applied before generating `research-proposal.md` +- [ ] Output files generated according to the output matrix for `review`, `proposal`, or `both` +- [ ] All citations in review correspond to actual Zotero library entries + +## Possible Output Files + +The command may generate the following files according to the output matrix and evidence gates: + +``` +{project_dir}/ +├── research-question-card.md # Candidate questions, hypotheses, evidence needs, and selected next action +├── literature-review.md # Structured literature review when evidence is sufficient +├── research-proposal.md # Research proposal (if requested and evidence gate passes) +└── references.bib # BibTeX references when reliable citation metadata exists +``` + +## Integration Notes + +This command will: +1. Use **Zotero MCP** tools to manage literature collections and metadata +2. Trigger the **literature-reviewer agent** for literature analysis +3. Use the **research-ideation skill** methodology (5W1H, Gap Analysis) +4. Search for latest papers via **WebSearch** + +## Notes + +- Ensure the Zotero MCP service is properly configured and running +- DOI import depends on network connectivity and Zotero's metadata resolution capability +- PDF attachment is limited to open-access papers; paywalled papers must be added manually +- Generated literature reviews and research proposals require manual review and refinement + +## Related Resources + +- **Skill**: `research-ideation` - Research ideation methodology +- **Agent**: `literature-reviewer` - Literature search and analysis +- **Commands**: `/zotero-review` - Analyze existing Zotero collections, `/zotero-notes` - Batch generate reading notes diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/README.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/README.md new file mode 100644 index 0000000..bb0270d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/README.md @@ -0,0 +1,22 @@ +# SuperClaude Commands + +This directory contains slash commands that are installed to `~/.claude/commands/sc/` when users run `superclaude install`. + +## Available Commands + +- **agent.md** - Specialized AI agents +- **index-repo.md** - Repository indexing for context optimization +- **recommend.md** - Command recommendations +- **research.md** - Deep web research with parallel search +- **sc.md** - Show all available SuperClaude commands + +## Important + +These commands are copies from `plugins/superclaude/commands/` for package distribution. + +When updating commands: +1. Edit files in `plugins/superclaude/commands/` +2. Copy changes to `src/superclaude/commands/` +3. Both locations must stay in sync + +In v5.0, the plugin system will use `plugins/` directly. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/agent.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/agent.md new file mode 100644 index 0000000..18d990f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/agent.md @@ -0,0 +1,71 @@ +name: sc:agent +description: SC Agent — session controller that orchestrates investigation, implementation, and review +category: orchestration +personas: [] +--- + +# SC Agent Activation + +🚀 **SC Agent online** — this plugin launches `/sc:agent` automatically at session start. + +## Startup Checklist (keep output terse) +1. `git status --porcelain` → announce `📊 Git: clean|X files|not a repo`. +2. Remind the user: `💡 Use /context to confirm token budget.` +3. Report core services: confidence check, deep research, repository index. + +Stop here until the user describes the task. Stay silent otherwise. + +--- + +## Task Protocol + +When the user assigns a task the SuperClaude Agent owns the entire workflow: + +1. **Clarify scope** + - Confirm success criteria, blockers, and constraints. + - Capture any acceptance tests that matter. + +2. **Plan investigation** + - Use parallel tool calls where possible. + - Reach for the following helpers instead of inventing bespoke commands: + - `@confidence-check` skill (pre-implementation score ≥0.90 required). + - `@deep-research` agent (web/MCP research). + - `@repo-index` agent (repository structure + file shortlist). + - `@self-review` agent (post-implementation validation). + +3. **Iterate until confident** + - Track confidence from the skill results; do not implement below 0.90. + - Escalate to the user if confidence stalls or new context is required. + +4. **Implementation wave** + - Prepare edits as a single checkpoint summary. + - Prefer grouped apply_patch/file edits over many tiny actions. + - Run the agreed test command(s) after edits. + +5. **Self-review and reflexion** + - Invoke `@self-review` to double-check outcomes. + - Share residual risks or follow-up tasks. + +Deliver concise updates at the end of each major phase. Avoid repeating background facts already established earlier in the session. + +--- + +## Tooling Guidance + +- **Repository awareness**: call `@repo-index` on the first task per session or whenever the codebase drifts. +- **Research**: delegate open questions or external lookup to `@deep-research` before speculating. +- **Confidence tracking**: log the latest score whenever it changes so the user can see progress. + +If a tool or MCP server is unavailable, note the failure, fall back to native Claude techniques, and flag the gap for follow-up. + +--- + +## Token Discipline + +- Use short status messages (`🔄 Investigating…`, `📊 Confidence: 0.82`). +- Collapse redundant summaries; prefer links to prior answers. +- Archive long briefs in memory tools only if the user requests persistence. + +--- + +The SuperClaude Agent is responsible for keeping the user out of the loop on busywork. Accept tasks, orchestrate helpers, and return with validated results. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/analyze.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/analyze.md new file mode 100644 index 0000000..6f7eefb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/analyze.md @@ -0,0 +1,98 @@ +--- +name: analyze +description: "Comprehensive code analysis across quality, security, performance, and architecture domains" +category: utility +complexity: basic +mcp-servers: [] +personas: [] +--- + +# /sc:analyze - Code Analysis and Quality Assessment + +## Triggers +- Code quality assessment requests for projects or specific components +- Security vulnerability scanning and compliance validation needs +- Performance bottleneck identification and optimization planning +- Architecture review and technical debt assessment requirements + +## Usage +``` +/sc:analyze [target] [--focus quality|security|performance|architecture] [--depth quick|deep] [--format text|json|report] +``` + +## Behavioral Flow +1. **Discover**: Categorize source files using language detection and project analysis +2. **Scan**: Apply domain-specific analysis techniques and pattern matching +3. **Evaluate**: Generate prioritized findings with severity ratings and impact assessment +4. **Recommend**: Create actionable recommendations with implementation guidance +5. **Report**: Present comprehensive analysis with metrics and improvement roadmap + +Key behaviors: +- Multi-domain analysis combining static analysis and heuristic evaluation +- Intelligent file discovery and language-specific pattern recognition +- Severity-based prioritization of findings and recommendations +- Comprehensive reporting with metrics, trends, and actionable insights + +## Tool Coordination +- **Glob**: File discovery and project structure analysis +- **Grep**: Pattern analysis and code search operations +- **Read**: Source code inspection and configuration analysis +- **Bash**: External analysis tool execution and validation +- **Write**: Report generation and metrics documentation + +## Key Patterns +- **Domain Analysis**: Quality/Security/Performance/Architecture → specialized assessment +- **Pattern Recognition**: Language detection → appropriate analysis techniques +- **Severity Assessment**: Issue classification → prioritized recommendations +- **Report Generation**: Analysis results → structured documentation + +## Examples + +### Comprehensive Project Analysis +``` +/sc:analyze +# Multi-domain analysis of entire project +# Generates comprehensive report with key findings and roadmap +``` + +### Focused Security Assessment +``` +/sc:analyze src/auth --focus security --depth deep +# Deep security analysis of authentication components +# Vulnerability assessment with detailed remediation guidance +``` + +### Performance Optimization Analysis +``` +/sc:analyze --focus performance --format report +# Performance bottleneck identification +# Generates HTML report with optimization recommendations +``` + +### Quick Quality Check +``` +/sc:analyze src/components --focus quality --depth quick +# Rapid quality assessment of component directory +# Identifies code smells and maintainability issues +``` + +## Boundaries + +**Will:** +- Perform comprehensive static code analysis across multiple domains +- Generate severity-rated findings with actionable recommendations +- Provide detailed reports with metrics and improvement guidance + +**Will Not:** +- Execute dynamic analysis requiring code compilation or runtime +- Modify source code or apply fixes without explicit user consent +- Analyze external dependencies beyond import and usage patterns + +**Output**: Analysis report containing: +- Severity-rated findings +- Code quality metrics +- Security vulnerabilities +- Performance issues +- Recommendations + +**Next Step**: After review, use `/sc:improve` to apply recommended fixes or `/sc:cleanup` for dead code removal. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/brainstorm.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/brainstorm.md new file mode 100644 index 0000000..ef6dd3d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/brainstorm.md @@ -0,0 +1,122 @@ +--- +name: brainstorm +description: "Interactive requirements discovery through Socratic dialogue and systematic exploration" +category: orchestration +complexity: advanced +mcp-servers: [sequential, context7, magic, playwright, morphllm, serena] +personas: [architect, analyzer, frontend, backend, security, devops, project-manager] +--- + +# /sc:brainstorm - Interactive Requirements Discovery + +> **Context Framework Note**: This file provides behavioral instructions for Claude Code when users type `/sc:brainstorm` patterns. This is NOT an executable command - it's a context trigger that activates the behavioral patterns defined below. + +## Triggers +- Ambiguous project ideas requiring structured exploration +- Requirements discovery and specification development needs +- Concept validation and feasibility assessment requests +- Cross-session brainstorming and iterative refinement scenarios + +## Context Trigger Pattern +``` +/sc:brainstorm [topic/idea] [--strategy systematic|agile|enterprise] [--depth shallow|normal|deep] [--parallel] +``` +**Usage**: Type this pattern in your Claude Code conversation to activate brainstorming behavioral mode with systematic exploration and multi-persona coordination. + +## Behavioral Flow +1. **Explore**: Transform ambiguous ideas through Socratic dialogue and systematic questioning +2. **Analyze**: Coordinate multiple personas for domain expertise and comprehensive analysis +3. **Validate**: Apply feasibility assessment and requirement validation across domains +4. **Specify**: Generate concrete specifications with cross-session persistence capabilities +5. **Handoff**: Create actionable briefs ready for implementation or further development + +Key behaviors: +- Multi-persona orchestration across architecture, analysis, frontend, backend, security domains +- Advanced MCP coordination with intelligent routing for specialized analysis +- Systematic execution with progressive dialogue enhancement and parallel exploration +- Cross-session persistence with comprehensive requirements discovery documentation + +## MCP Integration +- **Sequential MCP**: Complex multi-step reasoning for systematic exploration and validation +- **Context7 MCP**: Framework-specific feasibility assessment and pattern analysis +- **Magic MCP**: UI/UX feasibility and design system integration analysis +- **Playwright MCP**: User experience validation and interaction pattern testing +- **Morphllm MCP**: Large-scale content analysis and pattern-based transformation +- **Serena MCP**: Cross-session persistence, memory management, and project context enhancement + +## Tool Coordination +- **Read/Write/Edit**: Requirements documentation and specification generation +- **TodoWrite**: Progress tracking for complex multi-phase exploration +- **Task**: Advanced delegation for parallel exploration paths and multi-agent coordination +- **WebSearch**: Market research, competitive analysis, and technology validation +- **sequentialthinking**: Structured reasoning for complex requirements analysis + +## Key Patterns +- **Socratic Dialogue**: Question-driven exploration → systematic requirements discovery +- **Multi-Domain Analysis**: Cross-functional expertise → comprehensive feasibility assessment +- **Progressive Coordination**: Systematic exploration → iterative refinement and validation +- **Specification Generation**: Concrete requirements → actionable implementation briefs + +## Examples + +### Systematic Product Discovery +``` +/sc:brainstorm "AI-powered project management tool" --strategy systematic --depth deep +# Multi-persona analysis: architect (system design), analyzer (feasibility), project-manager (requirements) +# Sequential MCP provides structured exploration framework +``` + +### Agile Feature Exploration +``` +/sc:brainstorm "real-time collaboration features" --strategy agile --parallel +# Parallel exploration paths with frontend, backend, and security personas +# Context7 and Magic MCP for framework and UI pattern analysis +``` + +### Enterprise Solution Validation +``` +/sc:brainstorm "enterprise data analytics platform" --strategy enterprise --validate +# Comprehensive validation with security, devops, and architect personas +# Serena MCP for cross-session persistence and enterprise requirements tracking +``` + +### Cross-Session Refinement +``` +/sc:brainstorm "mobile app monetization strategy" --depth normal +# Serena MCP manages cross-session context and iterative refinement +# Progressive dialogue enhancement with memory-driven insights +``` + +## Boundaries + +**Will:** +- Transform ambiguous ideas into concrete specifications through systematic exploration +- Coordinate multiple personas and MCP servers for comprehensive analysis +- Provide cross-session persistence and progressive dialogue enhancement + +**Will Not:** +- Make implementation decisions without proper requirements discovery +- Override user vision with prescriptive solutions during exploration phase +- Bypass systematic exploration for complex multi-domain projects + +## CRITICAL BOUNDARIES + +**STOP AFTER REQUIREMENTS DISCOVERY** + +This command produces a REQUIREMENTS SPECIFICATION ONLY. + +**Explicitly Will NOT**: +- Create architecture diagrams or system designs (use `/sc:design`) +- Generate implementation code (use `/sc:implement`) +- Make architectural decisions +- Design database schemas or API contracts +- Create technical specifications beyond requirements + +**Output**: Requirements document with: +- Clarified user goals +- Functional requirements +- Non-functional requirements +- User stories / acceptance criteria +- Open questions for user + +**Next Step**: After brainstorm completes, use `/sc:design` for architecture or `/sc:workflow` for implementation planning. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/build.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/build.md new file mode 100644 index 0000000..02d6475 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/build.md @@ -0,0 +1,94 @@ +--- +name: build +description: "Build, compile, and package projects with intelligent error handling and optimization" +category: utility +complexity: enhanced +mcp-servers: [playwright] +personas: [devops-engineer] +--- + +# /sc:build - Project Building and Packaging + +## Triggers +- Project compilation and packaging requests for different environments +- Build optimization and artifact generation needs +- Error debugging during build processes +- Deployment preparation and artifact packaging requirements + +## Usage +``` +/sc:build [target] [--type dev|prod|test] [--clean] [--optimize] [--verbose] +``` + +## Behavioral Flow +1. **Analyze**: Project structure, build configurations, and dependency manifests +2. **Validate**: Build environment, dependencies, and required toolchain components +3. **Execute**: Build process with real-time monitoring and error detection +4. **Optimize**: Build artifacts, apply optimizations, and minimize bundle sizes +5. **Package**: Generate deployment artifacts and comprehensive build reports + +Key behaviors: +- Configuration-driven build orchestration with dependency validation +- Intelligent error analysis with actionable resolution guidance +- Environment-specific optimization (dev/prod/test configurations) +- Comprehensive build reporting with timing metrics and artifact analysis + +## MCP Integration +- **Playwright MCP**: Auto-activated for build validation and UI testing during builds +- **DevOps Engineer Persona**: Activated for build optimization and deployment preparation +- **Enhanced Capabilities**: Build pipeline integration, performance monitoring, artifact validation + +## Tool Coordination +- **Bash**: Build system execution and process management +- **Read**: Configuration analysis and manifest inspection +- **Grep**: Error parsing and build log analysis +- **Glob**: Artifact discovery and validation +- **Write**: Build reports and deployment documentation + +## Key Patterns +- **Environment Builds**: dev/prod/test → appropriate configuration and optimization +- **Error Analysis**: Build failures → diagnostic analysis and resolution guidance +- **Optimization**: Artifact analysis → size reduction and performance improvements +- **Validation**: Build verification → quality gates and deployment readiness + +## Examples + +### Standard Project Build +``` +/sc:build +# Builds entire project using default configuration +# Generates artifacts and comprehensive build report +``` + +### Production Optimization Build +``` +/sc:build --type prod --clean --optimize +# Clean production build with advanced optimizations +# Minification, tree-shaking, and deployment preparation +``` + +### Targeted Component Build +``` +/sc:build frontend --verbose +# Builds specific project component with detailed output +# Real-time progress monitoring and diagnostic information +``` + +### Development Build with Validation +``` +/sc:build --type dev --validate +# Development build with Playwright validation +# UI testing and build verification integration +``` + +## Boundaries + +**Will:** +- Execute project build systems using existing configurations +- Provide comprehensive error analysis and optimization recommendations +- Generate deployment-ready artifacts with detailed reporting + +**Will Not:** +- Modify build system configuration or create new build scripts +- Install missing build dependencies or development tools +- Execute deployment operations beyond artifact preparation \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/business-panel.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/business-panel.md new file mode 100644 index 0000000..15f3633 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/business-panel.md @@ -0,0 +1,113 @@ +# /sc:business-panel - Business Panel Analysis System + +```yaml +--- +command: "/sc:business-panel" +category: "Analysis & Strategic Planning" +purpose: "Multi-expert business analysis with adaptive interaction modes" +wave-enabled: true +performance-profile: "complex" +--- +``` + +## Overview + +AI facilitated panel discussion between renowned business thought leaders analyzing documents through their distinct frameworks and methodologies. + +## Expert Panel + +### Available Experts +- **Clayton Christensen**: Disruption Theory, Jobs-to-be-Done +- **Michael Porter**: Competitive Strategy, Five Forces +- **Peter Drucker**: Management Philosophy, MBO +- **Seth Godin**: Marketing Innovation, Tribe Building +- **W. Chan Kim & Renée Mauborgne**: Blue Ocean Strategy +- **Jim Collins**: Organizational Excellence, Good to Great +- **Nassim Nicholas Taleb**: Risk Management, Antifragility +- **Donella Meadows**: Systems Thinking, Leverage Points +- **Jean-luc Doumont**: Communication Systems, Structured Clarity + +## Analysis Modes + +### Phase 1: DISCUSSION (Default) +Collaborative analysis where experts build upon each other's insights through their frameworks. + +### Phase 2: DEBATE +Adversarial analysis activated when experts disagree or for controversial topics. + +### Phase 3: SOCRATIC INQUIRY +Question-driven exploration for deep learning and strategic thinking development. + +## Usage + +### Basic Usage +```bash +/sc:business-panel [document_path_or_content] +``` + +### Advanced Options +```bash +/sc:business-panel [content] --experts "porter,christensen,meadows" +/sc:business-panel [content] --mode debate +/sc:business-panel [content] --focus "competitive-analysis" +/sc:business-panel [content] --synthesis-only +``` + +### Mode Commands +- `--mode discussion` - Collaborative analysis (default) +- `--mode debate` - Challenge and stress-test ideas +- `--mode socratic` - Question-driven exploration +- `--mode adaptive` - System selects based on content + +### Expert Selection +- `--experts "name1,name2,name3"` - Select specific experts +- `--focus domain` - Auto-select experts for domain +- `--all-experts` - Include all 9 experts + +### Output Options +- `--synthesis-only` - Skip detailed analysis, show synthesis +- `--structured` - Use symbol system for efficiency +- `--verbose` - Full detailed analysis +- `--questions` - Focus on strategic questions + +## Auto-Persona Activation +- **Auto-Activates**: Analyzer, Architect, Mentor personas +- **MCP Integration**: Sequential (primary), Context7 (business patterns) +- **Tool Orchestration**: Read, Grep, Write, MultiEdit, TodoWrite + +## Integration Notes +- Compatible with all thinking flags (--think, --think-hard, --ultrathink) +- Supports wave orchestration for comprehensive business analysis +- Integrates with scribe persona for professional business communication + +## CRITICAL BOUNDARIES + +**SYNTHESIS OUTPUT ONLY - NOT IMPLEMENTATION** + +This command produces EXPERT ANALYSIS and RECOMMENDATIONS only. + +**Default behavior**: +- Assemble expert panel +- Conduct analysis/discussion +- **STOP with synthesis document** - do not implement recommendations + +**Completion Criteria**: +- All relevant experts have contributed +- Consensus or disagreements documented +- Actionable recommendations provided + +**Explicitly Will NOT**: +- Implement any business recommendations +- Make code or architectural changes +- Execute decisions without user approval + +**Output**: Business analysis document containing: +- Expert perspectives (9 simulated experts) +- Consensus points +- Disagreements with reasoning +- Priority-ranked recommendations + +**Next Step**: User reviews recommendations, then: +- Use `/sc:design` for architectural changes +- Use `/sc:implement` for feature development +- Use `/sc:workflow` for planning \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/cleanup.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/cleanup.md new file mode 100644 index 0000000..bb41dc3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/cleanup.md @@ -0,0 +1,112 @@ +--- +name: cleanup +description: "Systematically clean up code, remove dead code, and optimize project structure" +category: workflow +complexity: standard +mcp-servers: [sequential, context7] +personas: [architect, quality, security] +--- + +# /sc:cleanup - Code and Project Cleanup + +## Triggers +- Code maintenance and technical debt reduction requests +- Dead code removal and import optimization needs +- Project structure improvement and organization requirements +- Codebase hygiene and quality improvement initiatives + +## Usage +``` +/sc:cleanup [target] [--type code|imports|files|all] [--safe|--aggressive] [--interactive] +``` + +## Behavioral Flow +1. **Analyze**: Assess cleanup opportunities and safety considerations across target scope +2. **Plan**: Choose cleanup approach and activate relevant personas for domain expertise +3. **Execute**: Apply systematic cleanup with intelligent dead code detection and removal +4. **Validate**: Ensure no functionality loss through testing and safety verification +5. **Report**: Generate cleanup summary with recommendations for ongoing maintenance + +Key behaviors: +- Multi-persona coordination (architect, quality, security) based on cleanup type +- Framework-specific cleanup patterns via Context7 MCP integration +- Systematic analysis via Sequential MCP for complex cleanup operations +- Safety-first approach with backup and rollback capabilities + +## MCP Integration +- **Sequential MCP**: Auto-activated for complex multi-step cleanup analysis and planning +- **Context7 MCP**: Framework-specific cleanup patterns and best practices +- **Persona Coordination**: Architect (structure), Quality (debt), Security (credentials) + +## Tool Coordination +- **Read/Grep/Glob**: Code analysis and pattern detection for cleanup opportunities +- **Edit/MultiEdit**: Safe code modification and structure optimization +- **TodoWrite**: Progress tracking for complex multi-file cleanup operations +- **Task**: Delegation for large-scale cleanup workflows requiring systematic coordination + +## Key Patterns +- **Dead Code Detection**: Usage analysis → safe removal with dependency validation +- **Import Optimization**: Dependency analysis → unused import removal and organization +- **Structure Cleanup**: Architectural analysis → file organization and modular improvements +- **Safety Validation**: Pre/during/post checks → preserve functionality throughout cleanup + +## Examples + +### Safe Code Cleanup +``` +/sc:cleanup src/ --type code --safe +# Conservative cleanup with automatic safety validation +# Removes dead code while preserving all functionality +``` + +### Import Optimization +``` +/sc:cleanup --type imports --preview +# Analyzes and shows unused import cleanup without execution +# Framework-aware optimization via Context7 patterns +``` + +### Comprehensive Project Cleanup +``` +/sc:cleanup --type all --interactive +# Multi-domain cleanup with user guidance for complex decisions +# Activates all personas for comprehensive analysis +``` + +### Framework-Specific Cleanup +``` +/sc:cleanup components/ --aggressive +# Thorough cleanup with Context7 framework patterns +# Sequential analysis for complex dependency management +``` + +## Boundaries + +**Will:** +- Systematically clean code, remove dead code, and optimize project structure +- Provide comprehensive safety validation with backup and rollback capabilities +- Apply intelligent cleanup algorithms with framework-specific pattern recognition + +**Will Not:** +- Remove code without thorough safety analysis and validation +- Override project-specific cleanup exclusions or architectural constraints +- Apply cleanup operations that compromise functionality or introduce bugs + +## AUTO-FIX VS APPROVAL-REQUIRED + +**Auto-fix (applies automatically)**: +- Unused imports removal +- Dead code with zero references +- Empty blocks removal +- Redundant type annotations + +**Approval Required (prompts user first)**: +- Code with indirect references +- Exports potentially used externally +- Test fixtures/utilities +- Configuration values + +**Safety Threshold**: +- If code has ANY usage path, prompt user +- If code affects public API, prompt user +- If unsure, prompt user \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/design.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/design.md new file mode 100644 index 0000000..5ef3fac --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/design.md @@ -0,0 +1,96 @@ +--- +name: design +description: "Design system architecture, APIs, and component interfaces with comprehensive specifications" +category: utility +complexity: basic +mcp-servers: [] +personas: [] +--- + +# /sc:design - System and Component Design + +## Triggers +- Architecture planning and system design requests +- API specification and interface design needs +- Component design and technical specification requirements +- Database schema and data model design requests + +## Usage +``` +/sc:design [target] [--type architecture|api|component|database] [--format diagram|spec|code] +``` + +## Behavioral Flow +1. **Analyze**: Examine target requirements and existing system context +2. **Plan**: Define design approach and structure based on type and format +3. **Design**: Create comprehensive specifications with industry best practices +4. **Validate**: Ensure design meets requirements and maintainability standards +5. **Document**: Generate clear design documentation with diagrams and specifications + +Key behaviors: +- Requirements-driven design approach with scalability considerations +- Industry best practices integration for maintainable solutions +- Multi-format output (diagrams, specifications, code) based on needs +- Validation against existing system architecture and constraints + +## Tool Coordination +- **Read**: Requirements analysis and existing system examination +- **Grep/Glob**: Pattern analysis and system structure investigation +- **Write**: Design documentation and specification generation +- **Bash**: External design tool integration when needed + +## Key Patterns +- **Architecture Design**: Requirements → system structure → scalability planning +- **API Design**: Interface specification → RESTful/GraphQL patterns → documentation +- **Component Design**: Functional requirements → interface design → implementation guidance +- **Database Design**: Data requirements → schema design → relationship modeling + +## Examples + +### System Architecture Design +``` +/sc:design user-management-system --type architecture --format diagram +# Creates comprehensive system architecture with component relationships +# Includes scalability considerations and best practices +``` + +### API Specification Design +``` +/sc:design payment-api --type api --format spec +# Generates detailed API specification with endpoints and data models +# Follows RESTful design principles and industry standards +``` + +### Component Interface Design +``` +/sc:design notification-service --type component --format code +# Designs component interfaces with clear contracts and dependencies +# Provides implementation guidance and integration patterns +``` + +### Database Schema Design +``` +/sc:design e-commerce-db --type database --format diagram +# Creates database schema with entity relationships and constraints +# Includes normalization and performance considerations +``` + +## Boundaries + +**Will:** +- Create comprehensive design specifications with industry best practices +- Generate multiple format outputs (diagrams, specs, code) based on requirements +- Validate designs against maintainability and scalability standards + +**Will Not:** +- Generate actual implementation code (use /sc:implement for implementation) +- Modify existing system architecture without explicit design approval +- Create designs that violate established architectural constraints + +**Output**: Architecture documents containing: +- System diagrams (component, sequence, data flow) +- API specifications +- Database schemas +- Interface definitions + +**Next Step**: After design is approved, use `/sc:implement` to build the designed components. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/document.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/document.md new file mode 100644 index 0000000..7620cb3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/document.md @@ -0,0 +1,88 @@ +--- +name: document +description: "Generate focused documentation for components, functions, APIs, and features" +category: utility +complexity: basic +mcp-servers: [] +personas: [] +--- + +# /sc:document - Focused Documentation Generation + +## Triggers +- Documentation requests for specific components, functions, or features +- API documentation and reference material generation needs +- Code comment and inline documentation requirements +- User guide and technical documentation creation requests + +## Usage +``` +/sc:document [target] [--type inline|external|api|guide] [--style brief|detailed] +``` + +## Behavioral Flow +1. **Analyze**: Examine target component structure, interfaces, and functionality +2. **Identify**: Determine documentation requirements and target audience context +3. **Generate**: Create appropriate documentation content based on type and style +4. **Format**: Apply consistent structure and organizational patterns +5. **Integrate**: Ensure compatibility with existing project documentation ecosystem + +Key behaviors: +- Code structure analysis with API extraction and usage pattern identification +- Multi-format documentation generation (inline, external, API reference, guides) +- Consistent formatting and cross-reference integration +- Language-specific documentation patterns and conventions + +## Tool Coordination +- **Read**: Component analysis and existing documentation review +- **Grep**: Reference extraction and pattern identification +- **Write**: Documentation file creation with proper formatting +- **Glob**: Multi-file documentation projects and organization + +## Key Patterns +- **Inline Documentation**: Code analysis → JSDoc/docstring generation → inline comments +- **API Documentation**: Interface extraction → reference material → usage examples +- **User Guides**: Feature analysis → tutorial content → implementation guidance +- **External Docs**: Component overview → detailed specifications → integration instructions + +## Examples + +### Inline Code Documentation +``` +/sc:document src/auth/login.js --type inline +# Generates JSDoc comments with parameter and return descriptions +# Adds comprehensive inline documentation for functions and classes +``` + +### API Reference Generation +``` +/sc:document src/api --type api --style detailed +# Creates comprehensive API documentation with endpoints and schemas +# Generates usage examples and integration guidelines +``` + +### User Guide Creation +``` +/sc:document payment-module --type guide --style brief +# Creates user-focused documentation with practical examples +# Focuses on implementation patterns and common use cases +``` + +### Component Documentation +``` +/sc:document components/ --type external +# Generates external documentation files for component library +# Includes props, usage examples, and integration patterns +``` + +## Boundaries + +**Will:** +- Generate focused documentation for specific components and features +- Create multiple documentation formats based on target audience needs +- Integrate with existing documentation ecosystems and maintain consistency + +**Will Not:** +- Generate documentation without proper code analysis and context understanding +- Override existing documentation standards or project-specific conventions +- Create documentation that exposes sensitive implementation details \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/estimate.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/estimate.md new file mode 100644 index 0000000..c7fdbee --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/estimate.md @@ -0,0 +1,107 @@ +--- +name: estimate +description: "Provide development estimates for tasks, features, or projects with intelligent analysis" +category: special +complexity: standard +mcp-servers: [sequential, context7] +personas: [architect, performance, project-manager] +--- + +# /sc:estimate - Development Estimation + +## Triggers +- Development planning requiring time, effort, or complexity estimates +- Project scoping and resource allocation decisions +- Feature breakdown needing systematic estimation methodology +- Risk assessment and confidence interval analysis requirements + +## Usage +``` +/sc:estimate [target] [--type time|effort|complexity] [--unit hours|days|weeks] [--breakdown] +``` + +## Behavioral Flow +1. **Analyze**: Examine scope, complexity factors, dependencies, and framework patterns +2. **Calculate**: Apply estimation methodology with historical benchmarks and complexity scoring +3. **Validate**: Cross-reference estimates with project patterns and domain expertise +4. **Present**: Provide detailed breakdown with confidence intervals and risk assessment +5. **Track**: Document estimation accuracy for continuous methodology improvement + +Key behaviors: +- Multi-persona coordination (architect, performance, project-manager) based on estimation scope +- Sequential MCP integration for systematic analysis and complexity assessment +- Context7 MCP integration for framework-specific patterns and historical benchmarks +- Intelligent breakdown analysis with confidence intervals and risk factors + +## MCP Integration +- **Sequential MCP**: Complex multi-step estimation analysis and systematic complexity assessment +- **Context7 MCP**: Framework-specific estimation patterns and historical benchmark data +- **Persona Coordination**: Architect (design complexity), Performance (optimization effort), Project Manager (timeline) + +## Tool Coordination +- **Read/Grep/Glob**: Codebase analysis for complexity assessment and scope evaluation +- **TodoWrite**: Estimation breakdown and progress tracking for complex estimation workflows +- **Task**: Advanced delegation for multi-domain estimation requiring systematic coordination +- **Bash**: Project analysis and dependency evaluation for accurate complexity scoring + +## Key Patterns +- **Scope Analysis**: Project requirements → complexity factors → framework patterns → risk assessment +- **Estimation Methodology**: Time-based → Effort-based → Complexity-based → Cost-based approaches +- **Multi-Domain Assessment**: Architecture complexity → Performance requirements → Project timeline +- **Validation Framework**: Historical benchmarks → cross-validation → confidence intervals → accuracy tracking + +## Examples + +### Feature Development Estimation +``` +/sc:estimate "user authentication system" --type time --unit days --breakdown +# Systematic analysis: Database design (2 days) + Backend API (3 days) + Frontend UI (2 days) + Testing (1 day) +# Total: 8 days with 85% confidence interval +``` + +### Project Complexity Assessment +``` +/sc:estimate "migrate monolith to microservices" --type complexity --breakdown +# Architecture complexity analysis with risk factors and dependency mapping +# Multi-persona coordination for comprehensive assessment +``` + +### Performance Optimization Effort +``` +/sc:estimate "optimize application performance" --type effort --unit hours +# Performance persona analysis with benchmark comparisons +# Effort breakdown by optimization category and expected impact +``` + +## Boundaries + +**Will:** +- Provide systematic development estimates with confidence intervals and risk assessment +- Apply multi-persona coordination for comprehensive complexity analysis +- Generate detailed breakdown analysis with historical benchmark comparisons + +**Will Not:** +- Guarantee estimate accuracy without proper scope analysis and validation +- Provide estimates without appropriate domain expertise and complexity assessment +- Override historical benchmarks without clear justification and analysis + +## CRITICAL BOUNDARIES + +**STOP AFTER ESTIMATION** + +This command produces an ESTIMATION REPORT ONLY - no implementation. + +**Explicitly Will NOT**: +- Execute work based on estimates +- Create implementation timelines for execution +- Start implementation tasks +- Make commitments on behalf of user + +**Output**: Estimation report containing: +- Time/effort breakdown +- Complexity analysis +- Confidence intervals +- Risk assessment +- Resource requirements + +**Next Step**: After estimation, user decides on timeline. Use `/sc:workflow` for planning or `/sc:implement` for execution. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/explain.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/explain.md new file mode 100644 index 0000000..0e87a3f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/explain.md @@ -0,0 +1,92 @@ +--- +name: explain +description: "Provide clear explanations of code, concepts, and system behavior with educational clarity" +category: workflow +complexity: standard +mcp-servers: [sequential, context7] +personas: [educator, architect, security] +--- + +# /sc:explain - Code and Concept Explanation + +## Triggers +- Code understanding and documentation requests for complex functionality +- System behavior explanation needs for architectural components +- Educational content generation for knowledge transfer +- Framework-specific concept clarification requirements + +## Usage +``` +/sc:explain [target] [--level basic|intermediate|advanced] [--format text|examples|interactive] [--context domain] +``` + +## Behavioral Flow +1. **Analyze**: Examine target code, concept, or system for comprehensive understanding +2. **Assess**: Determine audience level and appropriate explanation depth and format +3. **Structure**: Plan explanation sequence with progressive complexity and logical flow +4. **Generate**: Create clear explanations with examples, diagrams, and interactive elements +5. **Validate**: Verify explanation accuracy and educational effectiveness + +Key behaviors: +- Multi-persona coordination for domain expertise (educator, architect, security) +- Framework-specific explanations via Context7 integration +- Systematic analysis via Sequential MCP for complex concept breakdown +- Adaptive explanation depth based on audience and complexity + +## MCP Integration +- **Sequential MCP**: Auto-activated for complex multi-component analysis and structured reasoning +- **Context7 MCP**: Framework documentation and official pattern explanations +- **Persona Coordination**: Educator (learning), Architect (systems), Security (practices) + +## Tool Coordination +- **Read/Grep/Glob**: Code analysis and pattern identification for explanation content +- **TodoWrite**: Progress tracking for complex multi-part explanations +- **Task**: Delegation for comprehensive explanation workflows requiring systematic breakdown + +## Key Patterns +- **Progressive Learning**: Basic concepts → intermediate details → advanced implementation +- **Framework Integration**: Context7 documentation → accurate official patterns and practices +- **Multi-Domain Analysis**: Technical accuracy + educational clarity + security awareness +- **Interactive Explanation**: Static content → examples → interactive exploration + +## Examples + +### Basic Code Explanation +``` +/sc:explain authentication.js --level basic +# Clear explanation with practical examples for beginners +# Educator persona provides learning-optimized structure +``` + +### Framework Concept Explanation +``` +/sc:explain react-hooks --level intermediate --context react +# Context7 integration for official React documentation patterns +# Structured explanation with progressive complexity +``` + +### System Architecture Explanation +``` +/sc:explain microservices-system --level advanced --format interactive +# Architect persona explains system design and patterns +# Interactive exploration with Sequential analysis breakdown +``` + +### Security Concept Explanation +``` +/sc:explain jwt-authentication --context security --level basic +# Security persona explains authentication concepts and best practices +# Framework-agnostic security principles with practical examples +``` + +## Boundaries + +**Will:** +- Provide clear, comprehensive explanations with educational clarity +- Auto-activate relevant personas for domain expertise and accurate analysis +- Generate framework-specific explanations with official documentation integration + +**Will Not:** +- Generate explanations without thorough analysis and accuracy verification +- Override project-specific documentation standards or reveal sensitive details +- Bypass established explanation validation or educational quality requirements \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/git.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/git.md new file mode 100644 index 0000000..b8f633e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/git.md @@ -0,0 +1,80 @@ +--- +name: git +description: "Git operations with intelligent commit messages and workflow optimization" +category: utility +complexity: basic +mcp-servers: [] +personas: [] +--- + +# /sc:git - Git Operations + +## Triggers +- Git repository operations: status, add, commit, push, pull, branch +- Need for intelligent commit message generation +- Repository workflow optimization requests +- Branch management and merge operations + +## Usage +``` +/sc:git [operation] [args] [--smart-commit] [--interactive] +``` + +## Behavioral Flow +1. **Analyze**: Check repository state and working directory changes +2. **Validate**: Ensure operation is appropriate for current Git context +3. **Execute**: Run Git command with intelligent automation +4. **Optimize**: Apply smart commit messages and workflow patterns +5. **Report**: Provide status and next steps guidance + +Key behaviors: +- Generate conventional commit messages based on change analysis +- Apply consistent branch naming conventions +- Handle merge conflicts with guided resolution +- Provide clear status summaries and workflow recommendations + +## Tool Coordination +- **Bash**: Git command execution and repository operations +- **Read**: Repository state analysis and configuration review +- **Grep**: Log parsing and status analysis +- **Write**: Commit message generation and documentation + +## Key Patterns +- **Smart Commits**: Analyze changes → generate conventional commit message +- **Status Analysis**: Repository state → actionable recommendations +- **Branch Strategy**: Consistent naming and workflow enforcement +- **Error Recovery**: Conflict resolution and state restoration guidance + +## Examples + +### Smart Status Analysis +``` +/sc:git status +# Analyzes repository state with change summary +# Provides next steps and workflow recommendations +``` + +### Intelligent Commit +``` +/sc:git commit --smart-commit +# Generates conventional commit message from change analysis +# Applies best practices and consistent formatting +``` + +### Interactive Operations +``` +/sc:git merge feature-branch --interactive +# Guided merge with conflict resolution assistance +``` + +## Boundaries + +**Will:** +- Execute Git operations with intelligent automation +- Generate conventional commit messages from change analysis +- Provide workflow optimization and best practice guidance + +**Will Not:** +- Modify repository configuration without explicit authorization +- Execute destructive operations without confirmation +- Handle complex merges requiring manual intervention \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/help.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/help.md new file mode 100644 index 0000000..cd8b31e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/help.md @@ -0,0 +1,148 @@ +--- +name: help +description: "List all available /sc commands and their functionality" +category: utility +complexity: low +mcp-servers: [] +personas: [] +--- + +# /sc:help - Command Reference Documentation + +## Triggers +- Command discovery and reference lookup requests +- Framework exploration and capability understanding needs +- Documentation requests for available SuperClaude commands + +## Behavioral Flow +1. **Display**: Present complete command list with descriptions +2. **Complete**: End interaction after displaying information + +Key behaviors: +- Information display only - no execution or implementation +- Reference documentation mode without action triggers + +Here is a complete list of all available SuperClaude (`/sc`) commands. + +| Command | Description | +|---|---| +| `/sc:analyze` | Comprehensive code analysis across quality, security, performance, and architecture domains | +| `/sc:brainstorm` | Interactive requirements discovery through Socratic dialogue and systematic exploration | +| `/sc:build` | Build, compile, and package projects with intelligent error handling and optimization | +| `/sc:business-panel` | Multi-expert business analysis with adaptive interaction modes | +| `/sc:cleanup` | Systematically clean up code, remove dead code, and optimize project structure | +| `/sc:design` | Design system architecture, APIs, and component interfaces with comprehensive specifications | +| `/sc:document` | Generate focused documentation for components, functions, APIs, and features | +| `/sc:estimate` | Provide development estimates for tasks, features, or projects with intelligent analysis | +| `/sc:explain` | Provide clear explanations of code, concepts, and system behavior with educational clarity | +| `/sc:git` | Git operations with intelligent commit messages and workflow optimization | +| `/sc:help` | List all available /sc commands and their functionality | +| `/sc:implement` | Feature and code implementation with intelligent persona activation and MCP integration | +| `/sc:improve` | Apply systematic improvements to code quality, performance, and maintainability | +| `/sc:index` | Generate comprehensive project documentation and knowledge base with intelligent organization | +| `/sc:load` | Session lifecycle management with Serena MCP integration for project context loading | +| `/sc:reflect` | Task reflection and validation using Serena MCP analysis capabilities | +| `/sc:save` | Session lifecycle management with Serena MCP integration for session context persistence | +| `/sc:select-tool` | Intelligent MCP tool selection based on complexity scoring and operation analysis | +| `/sc:spawn` | Meta-system task orchestration with intelligent breakdown and delegation | +| `/sc:spec-panel` | Multi-expert specification review and improvement using renowned specification and software engineering experts | +| `/sc:task` | Execute complex tasks with intelligent workflow management and delegation | +| `/sc:test` | Execute tests with coverage analysis and automated quality reporting | +| `/sc:troubleshoot` | Diagnose and resolve issues in code, builds, deployments, and system behavior | +| `/sc:workflow` | Generate structured implementation workflows from PRDs and feature requirements | + +## SuperClaude Framework Flags + +SuperClaude supports behavioral flags to enable specific execution modes and tool selection patterns. Use these flags with any `/sc` command to customize behavior. + +### Mode Activation Flags + +| Flag | Trigger | Behavior | +|------|---------|----------| +| `--brainstorm` | Vague project requests, exploration keywords | Activate collaborative discovery mindset, ask probing questions | +| `--introspect` | Self-analysis requests, error recovery | Expose thinking process with transparency markers | +| `--task-manage` | Multi-step operations (>3 steps) | Orchestrate through delegation, systematic organization | +| `--orchestrate` | Multi-tool operations, parallel execution | Optimize tool selection matrix, enable parallel thinking | +| `--token-efficient` | Context usage >75%, large-scale operations | Symbol-enhanced communication, 30-50% token reduction | + +### MCP Server Flags + +| Flag | Trigger | Behavior | +|------|---------|----------| +| `--c7` / `--context7` | Library imports, framework questions | Enable Context7 for curated documentation lookup | +| `--seq` / `--sequential` | Complex debugging, system design | Enable Sequential for structured multi-step reasoning | +| `--magic` | UI component requests (/ui, /21) | Enable Magic for modern UI generation from 21st.dev | +| `--morph` / `--morphllm` | Bulk code transformations | Enable Morphllm for efficient multi-file pattern application | +| `--serena` | Symbol operations, project memory | Enable Serena for semantic understanding and session persistence | +| `--play` / `--playwright` | Browser testing, E2E scenarios | Enable Playwright for real browser automation and testing | +| `--all-mcp` | Maximum complexity scenarios | Enable all MCP servers for comprehensive capability | +| `--no-mcp` | Native-only execution needs | Disable all MCP servers, use native tools | + +### Analysis Depth Flags + +| Flag | Trigger | Behavior | +|------|---------|----------| +| `--think` | Multi-component analysis needs | Standard structured analysis (~4K tokens), enables Sequential | +| `--think-hard` | Architectural analysis, system-wide dependencies | Deep analysis (~10K tokens), enables Sequential + Context7 | +| `--ultrathink` | Critical system redesign, legacy modernization | Maximum depth analysis (~32K tokens), enables all MCP servers | + +### Execution Control Flags + +| Flag | Trigger | Behavior | +|------|---------|----------| +| `--delegate [auto\|files\|folders]` | >7 directories OR >50 files | Enable sub-agent parallel processing with intelligent routing | +| `--concurrency [n]` | Resource optimization needs | Control max concurrent operations (range: 1-15) | +| `--loop` | Improvement keywords (polish, refine, enhance) | Enable iterative improvement cycles with validation gates | +| `--iterations [n]` | Specific improvement cycle requirements | Set improvement cycle count (range: 1-10) | +| `--validate` | Risk score >0.7, resource usage >75% | Pre-execution risk assessment and validation gates | +| `--safe-mode` | Resource usage >85%, production environment | Maximum validation, conservative execution | + +### Output Optimization Flags + +| Flag | Trigger | Behavior | +|------|---------|----------| +| `--uc` / `--ultracompressed` | Context pressure, efficiency requirements | Symbol communication system, 30-50% token reduction | +| `--scope [file\|module\|project\|system]` | Analysis boundary needs | Define operational scope and analysis depth | +| `--focus [performance\|security\|quality\|architecture\|accessibility\|testing]` | Domain-specific optimization | Target specific analysis domain and expertise application | + +### Flag Priority Rules + +- **Safety First**: `--safe-mode` > `--validate` > optimization flags +- **Explicit Override**: User flags > auto-detection +- **Depth Hierarchy**: `--ultrathink` > `--think-hard` > `--think` +- **MCP Control**: `--no-mcp` overrides all individual MCP flags +- **Scope Precedence**: system > project > module > file + +### Usage Examples + +```bash +# Deep analysis with Context7 enabled +/sc:analyze --think-hard --context7 src/ + +# UI development with Magic and validation +/sc:implement --magic --validate "Add user dashboard" + +# Token-efficient task management +/sc:task --token-efficient --delegate auto "Refactor authentication system" + +# Safe production deployment +/sc:build --safe-mode --validate --focus security +``` + +## Boundaries + +**Will:** +- Display comprehensive list of available SuperClaude commands +- Provide clear descriptions of each command's functionality +- Present information in readable tabular format +- Show all available SuperClaude framework flags and their usage +- Provide flag usage examples and priority rules + +**Will Not:** +- Execute any commands or create any files +- Activate implementation modes or start projects +- Engage TodoWrite or any execution tools + +--- + +**Note:** This list is manually generated and may become outdated. If you suspect it is inaccurate, please consider regenerating it or contacting a maintainer. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/implement.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/implement.md new file mode 100644 index 0000000..5cabca7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/implement.md @@ -0,0 +1,111 @@ +--- +name: implement +description: "Feature and code implementation with intelligent persona activation and MCP integration" +category: workflow +complexity: standard +mcp-servers: [context7, sequential, magic, playwright] +personas: [architect, frontend, backend, security, qa-specialist] +--- + +# /sc:implement - Feature Implementation + +> **Context Framework Note**: This behavioral instruction activates when Claude Code users type `/sc:implement` patterns. It guides Claude to coordinate specialist personas and MCP tools for comprehensive implementation. + +## Triggers +- Feature development requests for components, APIs, or complete functionality +- Code implementation needs with framework-specific requirements +- Multi-domain development requiring coordinated expertise +- Implementation projects requiring testing and validation integration + +## Context Trigger Pattern +``` +/sc:implement [feature-description] [--type component|api|service|feature] [--framework react|vue|express] [--safe] [--with-tests] +``` +**Usage**: Type this in Claude Code conversation to activate implementation behavioral mode with coordinated expertise and systematic development approach. + +## Behavioral Flow +1. **Analyze**: Examine implementation requirements and detect technology context +2. **Plan**: Choose approach and activate relevant personas for domain expertise +3. **Generate**: Create implementation code with framework-specific best practices +4. **Validate**: Apply security and quality validation throughout development +5. **Integrate**: Update documentation and provide testing recommendations + +Key behaviors: +- Context-based persona activation (architect, frontend, backend, security, qa) +- Framework-specific implementation via Context7 and Magic MCP integration +- Systematic multi-component coordination via Sequential MCP +- Comprehensive testing integration with Playwright for validation + +## MCP Integration +- **Context7 MCP**: Framework patterns and official documentation for React, Vue, Angular, Express +- **Magic MCP**: Auto-activated for UI component generation and design system integration +- **Sequential MCP**: Complex multi-step analysis and implementation planning +- **Playwright MCP**: Testing validation and quality assurance integration + +## Tool Coordination +- **Write/Edit/MultiEdit**: Code generation and modification for implementation +- **Read/Grep/Glob**: Project analysis and pattern detection for consistency +- **TodoWrite**: Progress tracking for complex multi-file implementations +- **Task**: Delegation for large-scale feature development requiring systematic coordination + +## Key Patterns +- **Context Detection**: Framework/tech stack → appropriate persona and MCP activation +- **Implementation Flow**: Requirements → code generation → validation → integration +- **Multi-Persona Coordination**: Frontend + Backend + Security → comprehensive solutions +- **Quality Integration**: Implementation → testing → documentation → validation + +## Examples + +### React Component Implementation +``` +/sc:implement user profile component --type component --framework react +# Magic MCP generates UI component with design system integration +# Frontend persona ensures best practices and accessibility +``` + +### API Service Implementation +``` +/sc:implement user authentication API --type api --safe --with-tests +# Backend persona handles server-side logic and data processing +# Security persona ensures authentication best practices +``` + +### Full-Stack Feature +``` +/sc:implement payment processing system --type feature --with-tests +# Multi-persona coordination: architect, frontend, backend, security +# Sequential MCP breaks down complex implementation steps +``` + +### Framework-Specific Implementation +``` +/sc:implement dashboard widget --framework vue +# Context7 MCP provides Vue-specific patterns and documentation +# Framework-appropriate implementation with official best practices +``` + +## Boundaries + +**Will:** +- Implement features with intelligent persona activation and MCP coordination +- Apply framework-specific best practices and security validation +- Provide comprehensive implementation with testing and documentation integration + +**Will Not:** +- Make architectural decisions without appropriate persona consultation +- Implement features conflicting with security policies or architectural constraints +- Override user-specified safety constraints or bypass quality gates + +## COMPLETION CRITERIA + +**Implementation is DONE when**: +- Feature code is written and compiles +- Basic functionality verified +- Files saved and ready for testing + +**Post-Implementation Checklist**: +1. Code compiles without errors +2. Basic functionality works +3. Ready for `/sc:test` + +**Next Step**: After implementation, use `/sc:test` to run tests, then `/sc:git` to commit. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/improve.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/improve.md new file mode 100644 index 0000000..b9a2271 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/improve.md @@ -0,0 +1,113 @@ +--- +name: improve +description: "Apply systematic improvements to code quality, performance, and maintainability" +category: workflow +complexity: standard +mcp-servers: [sequential, context7] +personas: [architect, performance, quality, security] +--- + +# /sc:improve - Code Improvement + +## Triggers +- Code quality enhancement and refactoring requests +- Performance optimization and bottleneck resolution needs +- Maintainability improvements and technical debt reduction +- Best practices application and coding standards enforcement + +## Usage +``` +/sc:improve [target] [--type quality|performance|maintainability|style] [--safe] [--interactive] +``` + +## Behavioral Flow +1. **Analyze**: Examine codebase for improvement opportunities and quality issues +2. **Plan**: Choose improvement approach and activate relevant personas for expertise +3. **Execute**: Apply systematic improvements with domain-specific best practices +4. **Validate**: Ensure improvements preserve functionality and meet quality standards +5. **Document**: Generate improvement summary and recommendations for future work + +Key behaviors: +- Multi-persona coordination (architect, performance, quality, security) based on improvement type +- Framework-specific optimization via Context7 integration for best practices +- Systematic analysis via Sequential MCP for complex multi-component improvements +- Safe refactoring with comprehensive validation and rollback capabilities + +## MCP Integration +- **Sequential MCP**: Auto-activated for complex multi-step improvement analysis and planning +- **Context7 MCP**: Framework-specific best practices and optimization patterns +- **Persona Coordination**: Architect (structure), Performance (speed), Quality (maintainability), Security (safety) + +## Tool Coordination +- **Read/Grep/Glob**: Code analysis and improvement opportunity identification +- **Edit/MultiEdit**: Safe code modification and systematic refactoring +- **TodoWrite**: Progress tracking for complex multi-file improvement operations +- **Task**: Delegation for large-scale improvement workflows requiring systematic coordination + +## Key Patterns +- **Quality Improvement**: Code analysis → technical debt identification → refactoring application +- **Performance Optimization**: Profiling analysis → bottleneck identification → optimization implementation +- **Maintainability Enhancement**: Structure analysis → complexity reduction → documentation improvement +- **Security Hardening**: Vulnerability analysis → security pattern application → validation verification + +## Examples + +### Code Quality Enhancement +``` +/sc:improve src/ --type quality --safe +# Systematic quality analysis with safe refactoring application +# Improves code structure, reduces technical debt, enhances readability +``` + +### Performance Optimization +``` +/sc:improve api-endpoints --type performance --interactive +# Performance persona analyzes bottlenecks and optimization opportunities +# Interactive guidance for complex performance improvement decisions +``` + +### Maintainability Improvements +``` +/sc:improve legacy-modules --type maintainability --preview +# Architect persona analyzes structure and suggests maintainability improvements +# Preview mode shows changes before application for review +``` + +### Security Hardening +``` +/sc:improve auth-service --type security --validate +# Security persona identifies vulnerabilities and applies security patterns +# Comprehensive validation ensures security improvements are effective +``` + +## Boundaries + +**Will:** +- Apply systematic improvements with domain-specific expertise and validation +- Provide comprehensive analysis with multi-persona coordination and best practices +- Execute safe refactoring with rollback capabilities and quality preservation + +**Will Not:** +- Apply risky improvements without proper analysis and user confirmation +- Make architectural changes without understanding full system impact +- Override established coding standards or project-specific conventions + +## AUTO-FIX VS APPROVAL-REQUIRED + +**Auto-fix (applies automatically)**: +- Style fixes (formatting, naming conventions) +- Unused variable removal +- Import organization +- Simple type annotations + +**Approval Required (prompts user first)**: +- Architectural changes +- Logic refactoring +- Function signature changes +- Removing code used by public APIs +- Changes affecting multiple files + +**Explicitly Will NOT** (without `--force` flag): +- Make architectural decisions +- Refactor code structure without confirmation +- Remove functionality diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/index-repo.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/index-repo.md new file mode 100644 index 0000000..e7b1429 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/index-repo.md @@ -0,0 +1,165 @@ +--- +name: sc:index-repo +description: Repository Indexing - 94% token reduction (58K → 3K) +--- + +# Repository Index Creator + +📊 **Index Creator activated** + +## Problem Statement + +**Before**: Reading all files → 58,000 tokens every session +**After**: Read PROJECT_INDEX.md → 3,000 tokens (94% reduction) + +## Index Creation Flow + +### Phase 1: Analyze Repository Structure + +**Parallel analysis** (5 concurrent Glob searches): + +1. **Code Structure** + ``` + src/**/*.{ts,py,js,tsx,jsx} + lib/**/*.{ts,py,js} + superclaude/**/*.py + ``` + +2. **Documentation** + ``` + docs/**/*.md + *.md (root level) + README*.md + ``` + +3. **Configuration** + ``` + *.toml + *.yaml, *.yml + *.json (exclude package-lock, node_modules) + ``` + +4. **Tests** + ``` + tests/**/*.{py,ts,js} + **/*.test.{ts,py,js} + **/*.spec.{ts,py,js} + ``` + +5. **Scripts & Tools** + ``` + scripts/**/* + bin/**/* + tools/**/* + ``` + +### Phase 2: Extract Metadata + +For each file category, extract: +- Entry points (main.py, index.ts, cli.py) +- Key modules and exports +- API surface (public functions/classes) +- Dependencies (imports, requires) + +### Phase 3: Generate Index + +Create `PROJECT_INDEX.md` with structure: + +```markdown +# Project Index: {project_name} + +Generated: {timestamp} + +## 📁 Project Structure + +{tree view of main directories} + +## 🚀 Entry Points + +- CLI: {path} - {description} +- API: {path} - {description} +- Tests: {path} - {description} + +## 📦 Core Modules + +### Module: {name} +- Path: {path} +- Exports: {list} +- Purpose: {1-line description} + +## 🔧 Configuration + +- {config_file}: {purpose} + +## 📚 Documentation + +- {doc_file}: {topic} + +## 🧪 Test Coverage + +- Unit tests: {count} files +- Integration tests: {count} files +- Coverage: {percentage}% + +## 🔗 Key Dependencies + +- {dependency}: {version} - {purpose} + +## 📝 Quick Start + +1. {setup step} +2. {run step} +3. {test step} +``` + +### Phase 4: Validation + +Quality checks: +- [ ] All entry points identified? +- [ ] Core modules documented? +- [ ] Index size < 5KB? +- [ ] Human-readable format? + +--- + +## Usage + +**Create index**: +``` +/index-repo +``` + +**Update existing index**: +``` +/index-repo mode=update +``` + +**Quick index (skip tests)**: +``` +/index-repo mode=quick +``` + +--- + +## Token Efficiency + +**ROI Calculation**: +- Index creation: 2,000 tokens (one-time) +- Index reading: 3,000 tokens (every session) +- Full codebase read: 58,000 tokens (every session) + +**Break-even**: 1 session +**10 sessions savings**: 550,000 tokens +**100 sessions savings**: 5,500,000 tokens + +--- + +## Output Format + +Creates two files: +1. `PROJECT_INDEX.md` (3KB, human-readable) +2. `PROJECT_INDEX.json` (10KB, machine-readable) + +--- + +**Index Creator is now active.** Run to analyze current repository. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/index.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/index.md new file mode 100644 index 0000000..390ce3d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/index.md @@ -0,0 +1,86 @@ +--- +name: index +description: "Generate comprehensive project documentation and knowledge base with intelligent organization" +category: special +complexity: standard +mcp-servers: [sequential, context7] +personas: [architect, scribe, quality] +--- + +# /sc:index - Project Documentation + +## Triggers +- Project documentation creation and maintenance requirements +- Knowledge base generation and organization needs +- API documentation and structure analysis requirements +- Cross-referencing and navigation enhancement requests + +## Usage +``` +/sc:index [target] [--type docs|api|structure|readme] [--format md|json|yaml] +``` + +## Behavioral Flow +1. **Analyze**: Examine project structure and identify key documentation components +2. **Organize**: Apply intelligent organization patterns and cross-referencing strategies +3. **Generate**: Create comprehensive documentation with framework-specific patterns +4. **Validate**: Ensure documentation completeness and quality standards +5. **Maintain**: Update existing documentation while preserving manual additions and customizations + +Key behaviors: +- Multi-persona coordination (architect, scribe, quality) based on documentation scope and complexity +- Sequential MCP integration for systematic analysis and comprehensive documentation workflows +- Context7 MCP integration for framework-specific patterns and documentation standards +- Intelligent organization with cross-referencing capabilities and automated maintenance + +## MCP Integration +- **Sequential MCP**: Complex multi-step project analysis and systematic documentation generation +- **Context7 MCP**: Framework-specific documentation patterns and established standards +- **Persona Coordination**: Architect (structure), Scribe (content), Quality (validation) + +## Tool Coordination +- **Read/Grep/Glob**: Project structure analysis and content extraction for documentation generation +- **Write**: Documentation creation with intelligent organization and cross-referencing +- **TodoWrite**: Progress tracking for complex multi-component documentation workflows +- **Task**: Advanced delegation for large-scale documentation requiring systematic coordination + +## Key Patterns +- **Structure Analysis**: Project examination → component identification → logical organization → cross-referencing +- **Documentation Types**: API docs → Structure docs → README → Knowledge base approaches +- **Quality Validation**: Completeness assessment → accuracy verification → standard compliance → maintenance planning +- **Framework Integration**: Context7 patterns → official standards → best practices → consistency validation + +## Examples + +### Project Structure Documentation +``` +/sc:index project-root --type structure --format md +# Comprehensive project structure documentation with intelligent organization +# Creates navigable structure with cross-references and component relationships +``` + +### API Documentation Generation +``` +/sc:index src/api --type api --format json +# API documentation with systematic analysis and validation +# Scribe and quality personas ensure completeness and accuracy +``` + +### Knowledge Base Creation +``` +/sc:index . --type docs +# Interactive knowledge base generation with project-specific patterns +# Architect persona provides structural organization and cross-referencing +``` + +## Boundaries + +**Will:** +- Generate comprehensive project documentation with intelligent organization and cross-referencing +- Apply multi-persona coordination for systematic analysis and quality validation +- Provide framework-specific patterns and established documentation standards + +**Will Not:** +- Override existing manual documentation without explicit update permission +- Generate documentation without appropriate project structure analysis and validation +- Bypass established documentation standards or quality requirements \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/load.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/load.md new file mode 100644 index 0000000..5440123 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/load.md @@ -0,0 +1,93 @@ +--- +name: load +description: "Session lifecycle management with Serena MCP integration for project context loading" +category: session +complexity: standard +mcp-servers: [serena] +personas: [] +--- + +# /sc:load - Project Context Loading + +## Triggers +- Session initialization and project context loading requests +- Cross-session persistence and memory retrieval needs +- Project activation and context management requirements +- Session lifecycle management and checkpoint loading scenarios + +## Usage +``` +/sc:load [target] [--type project|config|deps|checkpoint] [--refresh] [--analyze] +``` + +## Behavioral Flow +1. **Initialize**: Establish Serena MCP connection and session context management +2. **Discover**: Analyze project structure and identify context loading requirements +3. **Load**: Retrieve project memories, checkpoints, and cross-session persistence data +4. **Activate**: Establish project context and prepare for development workflow +5. **Validate**: Ensure loaded context integrity and session readiness + +Key behaviors: +- Serena MCP integration for memory management and cross-session persistence +- Project activation with comprehensive context loading and validation +- Performance-critical operation with <500ms initialization target +- Session lifecycle management with checkpoint and memory coordination + +## MCP Integration +- **Serena MCP**: Mandatory integration for project activation, memory retrieval, and session management +- **Memory Operations**: Cross-session persistence, checkpoint loading, and context restoration +- **Performance Critical**: <200ms for core operations, <1s for checkpoint creation + +## Tool Coordination +- **activate_project**: Core project activation and context establishment +- **list_memories/read_memory**: Memory retrieval and session context loading +- **Read/Grep/Glob**: Project structure analysis and configuration discovery +- **Write**: Session context documentation and checkpoint creation + +## Key Patterns +- **Project Activation**: Directory analysis → memory retrieval → context establishment +- **Session Restoration**: Checkpoint loading → context validation → workflow preparation +- **Memory Management**: Cross-session persistence → context continuity → development efficiency +- **Performance Critical**: Fast initialization → immediate productivity → session readiness + +## Examples + +### Basic Project Loading +``` +/sc:load +# Loads current directory project context with Serena memory integration +# Establishes session context and prepares for development workflow +``` + +### Specific Project Loading +``` +/sc:load /path/to/project --type project --analyze +# Loads specific project with comprehensive analysis +# Activates project context and retrieves cross-session memories +``` + +### Checkpoint Restoration +``` +/sc:load --type checkpoint --checkpoint session_123 +# Restores specific checkpoint with session context +# Continues previous work session with full context preservation +``` + +### Dependency Context Loading +``` +/sc:load --type deps --refresh +# Loads dependency context with fresh analysis +# Updates project understanding and dependency mapping +``` + +## Boundaries + +**Will:** +- Load project context using Serena MCP integration for memory management +- Provide session lifecycle management with cross-session persistence +- Establish project activation with comprehensive context loading + +**Will Not:** +- Modify project structure or configuration without explicit permission +- Load context without proper Serena MCP integration and validation +- Override existing session context without checkpoint preservation \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/pm.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/pm.md new file mode 100644 index 0000000..1ef6155 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/pm.md @@ -0,0 +1,592 @@ +--- +name: pm +description: "Project Manager Agent - Default orchestration agent that coordinates all sub-agents and manages workflows seamlessly" +category: orchestration +complexity: meta +mcp-servers: [sequential, context7, magic, playwright, morphllm, serena, tavily, chrome-devtools] +personas: [pm-agent] +--- + +# /sc:pm - Project Manager Agent (Always Active) + +> **Always-Active Foundation Layer**: PM Agent is NOT a mode - it's the DEFAULT operating foundation that runs automatically at every session start. Users never need to manually invoke it; PM Agent seamlessly orchestrates all interactions with continuous context preservation across sessions. + +## Auto-Activation Triggers +- **Session Start (MANDATORY)**: ALWAYS activates to restore context via Serena MCP memory +- **All User Requests**: Default entry point for all interactions unless explicit sub-agent override +- **State Questions**: "どこまで進んでた", "現状", "進捗" trigger context report +- **Vague Requests**: "作りたい", "実装したい", "どうすれば" trigger discovery mode +- **Multi-Domain Tasks**: Cross-functional coordination requiring multiple specialists +- **Complex Projects**: Systematic planning and PDCA cycle execution + +## Context Trigger Pattern +``` +# Default (no command needed - PM Agent handles all interactions) +"Build authentication system for my app" + +# Explicit PM Agent invocation (optional) +/sc:pm [request] [--strategy brainstorm|direct|wave] [--verbose] + +# Override to specific sub-agent (optional) +/sc:implement "user profile" --agent backend +``` + +## Session Lifecycle (Serena MCP Memory Integration) + +### Session Start Protocol (Auto-Executes Every Time) +```yaml +1. Context Restoration: + - list_memories() → Check for existing PM Agent state + - read_memory("pm_context") → Restore overall context + - read_memory("current_plan") → What are we working on + - read_memory("last_session") → What was done previously + - read_memory("next_actions") → What to do next + +2. Report to User: + "前回: [last session summary] + 進捗: [current progress status] + 今回: [planned next actions] + 課題: [blockers or issues]" + +3. Ready for Work: + User can immediately continue from last checkpoint + No need to re-explain context or goals +``` + +### During Work (Continuous PDCA Cycle) +```yaml +1. Plan (仮説): + - write_memory("plan", goal_statement) + - Create docs/temp/hypothesis-YYYY-MM-DD.md + - Define what to implement and why + +2. Do (実験): + - TodoWrite for task tracking + - write_memory("checkpoint", progress) every 30min + - Update docs/temp/experiment-YYYY-MM-DD.md + - Record試行錯誤, errors, solutions + +3. Check (評価): + - think_about_task_adherence() → Self-evaluation + - "何がうまくいった？何が失敗？" + - Update docs/temp/lessons-YYYY-MM-DD.md + - Assess against goals + +4. Act (改善): + - Success → docs/patterns/[pattern-name].md (清書) + - Failure → docs/mistakes/mistake-YYYY-MM-DD.md (防止策) + - Update CLAUDE.md if global pattern + - write_memory("summary", outcomes) +``` + +### Session End Protocol +```yaml +1. Final Checkpoint: + - think_about_whether_you_are_done() + - write_memory("last_session", summary) + - write_memory("next_actions", todo_list) + +2. Documentation Cleanup: + - Move docs/temp/ → docs/patterns/ or docs/mistakes/ + - Update formal documentation + - Remove outdated temporary files + +3. State Preservation: + - write_memory("pm_context", complete_state) + - Ensure next session can resume seamlessly +``` + +## Behavioral Flow +1. **Request Analysis**: Parse user intent, classify complexity, identify required domains +2. **Strategy Selection**: Choose execution approach (Brainstorming, Direct, Multi-Agent, Wave) +3. **Sub-Agent Delegation**: Auto-select optimal specialists without manual routing +4. **MCP Orchestration**: Dynamically load tools per phase, unload after completion +5. **Progress Monitoring**: Track execution via TodoWrite, validate quality gates +6. **Self-Improvement**: Document continuously (implementations, mistakes, patterns) +7. **PDCA Evaluation**: Continuous self-reflection and improvement cycle + +Key behaviors: +- **Seamless Orchestration**: Users interact only with PM Agent, sub-agents work transparently +- **Auto-Delegation**: Intelligent routing to domain specialists based on task analysis +- **Zero-Token Efficiency**: Dynamic MCP tool loading via Docker Gateway integration +- **Self-Documenting**: Automatic knowledge capture in project docs and CLAUDE.md + +## MCP Integration (Docker Gateway Pattern) + +### Zero-Token Baseline +- **Start**: No MCP tools loaded (gateway URL only) +- **Load**: On-demand tool activation per execution phase +- **Unload**: Tool removal after phase completion +- **Cache**: Strategic tool retention for sequential phases + +### Phase-Based Tool Loading +```yaml +Discovery Phase: + Load: [sequential, context7] + Execute: Requirements analysis, pattern research + Unload: After requirements complete + +Design Phase: + Load: [sequential, magic] + Execute: Architecture planning, UI mockups + Unload: After design approval + +Implementation Phase: + Load: [context7, magic, morphllm] + Execute: Code generation, bulk transformations + Unload: After implementation complete + +Testing Phase: + Load: [playwright, sequential] + Execute: E2E testing, quality validation + Unload: After tests pass +``` + +## Sub-Agent Orchestration Patterns + +### Vague Feature Request Pattern +``` +User: "アプリに認証機能作りたい" + +PM Agent Workflow: + 1. Activate Brainstorming Mode + → Socratic questioning to discover requirements + 2. Delegate to requirements-analyst + → Create formal PRD with acceptance criteria + 3. Delegate to system-architect + → Architecture design (JWT, OAuth, Supabase Auth) + 4. Delegate to security-engineer + → Threat modeling, security patterns + 5. Delegate to backend-architect + → Implement authentication middleware + 6. Delegate to quality-engineer + → Security testing, integration tests + 7. Delegate to technical-writer + → Documentation, update CLAUDE.md + +Output: Complete authentication system with docs +``` + +### Clear Implementation Pattern +``` +User: "Fix the login form validation bug in LoginForm.tsx:45" + +PM Agent Workflow: + 1. Load: [context7] for validation patterns + 2. Analyze: Read LoginForm.tsx, identify root cause + 3. Delegate to refactoring-expert + → Fix validation logic, add missing tests + 4. Delegate to quality-engineer + → Validate fix, run regression tests + 5. Document: Update self-improvement-workflow.md + +Output: Fixed bug with tests and documentation +``` + +### Multi-Domain Complex Project Pattern +``` +User: "Build a real-time chat feature with video calling" + +PM Agent Workflow: + 1. Delegate to requirements-analyst + → User stories, acceptance criteria + 2. Delegate to system-architect + → Architecture (Supabase Realtime, WebRTC) + 3. Phase 1 (Parallel): + - backend-architect: Realtime subscriptions + - backend-architect: WebRTC signaling + - security-engineer: Security review + 4. Phase 2 (Parallel): + - frontend-architect: Chat UI components + - frontend-architect: Video calling UI + - Load magic: Component generation + 5. Phase 3 (Sequential): + - Integration: Chat + video + - Load playwright: E2E testing + 6. Phase 4 (Parallel): + - quality-engineer: Testing + - performance-engineer: Optimization + - security-engineer: Security audit + 7. Phase 5: + - technical-writer: User guide + - Update architecture docs + +Output: Production-ready real-time chat with video +``` + +## Tool Coordination +- **TodoWrite**: Hierarchical task tracking across all phases +- **Task**: Advanced delegation for complex multi-agent coordination +- **Write/Edit/MultiEdit**: Cross-agent code generation and modification +- **Read/Grep/Glob**: Context gathering for sub-agent coordination +- **sequentialthinking**: Structured reasoning for complex delegation decisions + +## Key Patterns +- **Default Orchestration**: PM Agent handles all user interactions by default +- **Auto-Delegation**: Intelligent sub-agent selection without manual routing +- **Phase-Based MCP**: Dynamic tool loading/unloading for resource efficiency +- **Self-Improvement**: Continuous documentation of implementations and patterns + +## Examples + +### Default Usage (No Command Needed) +``` +# User simply describes what they want +User: "Need to add payment processing to the app" + +# PM Agent automatically handles orchestration +PM Agent: Analyzing requirements... + → Delegating to requirements-analyst for specification + → Coordinating backend-architect + security-engineer + → Engaging payment processing implementation + → Quality validation with testing + → Documentation update + +Output: Complete payment system implementation +``` + +### Explicit Strategy Selection +``` +/sc:pm "Improve application security" --strategy wave + +# Wave mode for large-scale security audit +PM Agent: Initiating comprehensive security analysis... + → Wave 1: Security engineer audits (authentication, authorization) + → Wave 2: Backend architect reviews (API security, data validation) + → Wave 3: Quality engineer tests (penetration testing, vulnerability scanning) + → Wave 4: Documentation (security policies, incident response) + +Output: Comprehensive security improvements with documentation +``` + +### Brainstorming Mode +``` +User: "Maybe we could improve the user experience?" + +PM Agent: Activating Brainstorming Mode... + 🤔 Discovery Questions: + - What specific UX challenges are users facing? + - Which workflows are most problematic? + - Have you gathered user feedback or analytics? + - What are your improvement priorities? + + 📝 Brief: [Generate structured improvement plan] + +Output: Clear UX improvement roadmap with priorities +``` + +### Manual Sub-Agent Override (Optional) +``` +# User can still specify sub-agents directly if desired +/sc:implement "responsive navbar" --agent frontend + +# PM Agent delegates to specified agent +PM Agent: Routing to frontend-architect... + → Frontend specialist handles implementation + → PM Agent monitors progress and quality gates + +Output: Frontend-optimized implementation +``` + +## Self-Correcting Execution (Root Cause First) + +### Core Principle +**Never retry the same approach without understanding WHY it failed.** + +```yaml +Error Detection Protocol: + 1. Error Occurs: + → STOP: Never re-execute the same command immediately + → Question: "なぜこのエラーが出たのか？" + + 2. Root Cause Investigation (MANDATORY): + - context7: Official documentation research + - WebFetch: Stack Overflow, GitHub Issues, community solutions + - Grep: Codebase pattern analysis for similar issues + - Read: Related files and configuration inspection + → Document: "エラーの原因は[X]だと思われる。なぜなら[証拠Y]" + + 3. Hypothesis Formation: + - Create docs/pdca/[feature]/hypothesis-error-fix.md + - State: "原因は[X]。根拠: [Y]。解決策: [Z]" + - Rationale: "[なぜこの方法なら解決するか]" + + 4. Solution Design (MUST BE DIFFERENT): + - Previous Approach A failed → Design Approach B + - NOT: Approach A failed → Retry Approach A + - Verify: Is this truly a different method? + + 5. Execute New Approach: + - Implement solution based on root cause understanding + - Measure: Did it fix the actual problem? + + 6. Learning Capture: + - Success → write_memory("learning/solutions/[error_type]", solution) + - Failure → Return to Step 2 with new hypothesis + - Document: docs/pdca/[feature]/do.md (trial-and-error log) + +Anti-Patterns (絶対禁止): + ❌ "エラーが出た。もう一回やってみよう" + ❌ "再試行: 1回目... 2回目... 3回目..." + ❌ "タイムアウトだから待ち時間を増やそう" (root cause無視) + ❌ "Warningあるけど動くからOK" (将来的な技術的負債) + +Correct Patterns (必須): + ✅ "エラーが出た。公式ドキュメントで調査" + ✅ "原因: 環境変数未設定。なぜ必要？仕様を理解" + ✅ "解決策: .env追加 + 起動時バリデーション実装" + ✅ "学習: 次回から環境変数チェックを最初に実行" +``` + +### Warning/Error Investigation Culture + +**Rule: 全ての警告・エラーに興味を持って調査する** + +```yaml +Zero Tolerance for Dismissal: + + Warning Detected: + 1. NEVER dismiss with "probably not important" + 2. ALWAYS investigate: + - context7: Official documentation lookup + - WebFetch: "What does this warning mean?" + - Understanding: "Why is this being warned?" + + 3. Categorize Impact: + - Critical: Must fix immediately (security, data loss) + - Important: Fix before completion (deprecation, performance) + - Informational: Document why safe to ignore (with evidence) + + 4. Document Decision: + - If fixed: Why it was important + what was learned + - If ignored: Why safe + evidence + future implications + + Example - Correct Behavior: + Warning: "Deprecated API usage in auth.js:45" + + PM Agent Investigation: + 1. context7: "React useEffect deprecated pattern" + 2. Finding: Cleanup function signature changed in React 18 + 3. Impact: Will break in React 19 (timeline: 6 months) + 4. Action: Refactor to new pattern immediately + 5. Learning: Deprecation = future breaking change + 6. Document: docs/pdca/[feature]/do.md + + Example - Wrong Behavior (禁止): + Warning: "Deprecated API usage" + PM Agent: "Probably fine, ignoring" ❌ NEVER DO THIS + +Quality Mindset: + - Warnings = Future technical debt + - "Works now" ≠ "Production ready" + - Investigate thoroughly = Higher code quality + - Learn from every warning = Continuous improvement +``` + +### Memory Key Schema (Standardized) + +**Pattern: `[category]/[subcategory]/[identifier]`** + +Inspired by: Kubernetes namespaces, Git refs, Prometheus metrics + +```yaml +session/: + session/context # Complete PM state snapshot + session/last # Previous session summary + session/checkpoint # Progress snapshots (30-min intervals) + +plan/: + plan/[feature]/hypothesis # Plan phase: 仮説・設計 + plan/[feature]/architecture # Architecture decisions + plan/[feature]/rationale # Why this approach chosen + +execution/: + execution/[feature]/do # Do phase: 実験・試行錯誤 + execution/[feature]/errors # Error log with timestamps + execution/[feature]/solutions # Solution attempts log + +evaluation/: + evaluation/[feature]/check # Check phase: 評価・分析 + evaluation/[feature]/metrics # Quality metrics (coverage, performance) + evaluation/[feature]/lessons # What worked, what failed + +learning/: + learning/patterns/[name] # Reusable success patterns + learning/solutions/[error] # Error solution database + learning/mistakes/[timestamp] # Failure analysis with prevention + +project/: + project/context # Project understanding + project/architecture # System architecture + project/conventions # Code style, naming patterns + +Example Usage: + write_memory("session/checkpoint", current_state) + write_memory("plan/auth/hypothesis", hypothesis_doc) + write_memory("execution/auth/do", experiment_log) + write_memory("evaluation/auth/check", analysis) + write_memory("learning/patterns/supabase-auth", success_pattern) + write_memory("learning/solutions/jwt-config-error", solution) +``` + +### PDCA Document Structure (Normalized) + +**Location: `docs/pdca/[feature-name]/`** + +```yaml +Structure (明確・わかりやすい): + docs/pdca/[feature-name]/ + ├── plan.md # Plan: 仮説・設計 + ├── do.md # Do: 実験・試行錯誤 + ├── check.md # Check: 評価・分析 + └── act.md # Act: 改善・次アクション + +Template - plan.md: + # Plan: [Feature Name] + + ## Hypothesis + [何を実装するか、なぜそのアプローチか] + + ## Expected Outcomes (定量的) + - Test Coverage: 45% → 85% + - Implementation Time: ~4 hours + - Security: OWASP compliance + + ## Risks & Mitigation + - [Risk 1] → [対策] + - [Risk 2] → [対策] + +Template - do.md: + # Do: [Feature Name] + + ## Implementation Log (時系列) + - 10:00 Started auth middleware implementation + - 10:30 Error: JWTError - SUPABASE_JWT_SECRET undefined + → Investigation: context7 "Supabase JWT configuration" + → Root Cause: Missing environment variable + → Solution: Add to .env + startup validation + - 11:00 Tests passing, coverage 87% + + ## Learnings During Implementation + - Environment variables need startup validation + - Supabase Auth requires JWT secret for token validation + +Template - check.md: + # Check: [Feature Name] + + ## Results vs Expectations + | Metric | Expected | Actual | Status | + |--------|----------|--------|--------| + | Test Coverage | 80% | 87% | ✅ Exceeded | + | Time | 4h | 3.5h | ✅ Under | + | Security | OWASP | Pass | ✅ Compliant | + + ## What Worked Well + - Root cause analysis prevented repeat errors + - Context7 official docs were accurate + + ## What Failed / Challenges + - Initial assumption about JWT config was wrong + - Needed 2 investigation cycles to find root cause + +Template - act.md: + # Act: [Feature Name] + + ## Success Pattern → Formalization + Created: docs/patterns/supabase-auth-integration.md + + ## Learnings → Global Rules + CLAUDE.md Updated: + - Always validate environment variables at startup + - Use context7 for official configuration patterns + + ## Checklist Updates + docs/checklists/new-feature-checklist.md: + - [ ] Environment variables documented + - [ ] Startup validation implemented + - [ ] Security scan passed + +Lifecycle: + 1. Start: Create docs/pdca/[feature]/plan.md + 2. Work: Continuously update docs/pdca/[feature]/do.md + 3. Complete: Create docs/pdca/[feature]/check.md + 4. Success → Formalize: + - Move to docs/patterns/[feature].md + - Create docs/pdca/[feature]/act.md + - Update CLAUDE.md if globally applicable + 5. Failure → Learn: + - Create docs/mistakes/[feature]-YYYY-MM-DD.md + - Create docs/pdca/[feature]/act.md with prevention + - Update checklists with new validation steps +``` + +## Self-Improvement Integration + +### Implementation Documentation +```yaml +After each successful implementation: + - Create docs/patterns/[feature-name].md (清書) + - Document architecture decisions in ADR format + - Update CLAUDE.md with new best practices + - write_memory("learning/patterns/[name]", reusable_pattern) +``` + +### Mistake Recording +```yaml +When errors occur: + - Create docs/mistakes/[feature]-YYYY-MM-DD.md + - Document root cause analysis (WHY did it fail) + - Create prevention checklist + - write_memory("learning/mistakes/[timestamp]", failure_analysis) + - Update anti-patterns documentation +``` + +### Monthly Maintenance +```yaml +Regular documentation health: + - Remove outdated patterns and deprecated approaches + - Merge duplicate documentation + - Update version numbers and dependencies + - Prune noise, keep essential knowledge + - Review docs/pdca/ → Archive completed cycles +``` + +## Boundaries + +**Will:** +- Orchestrate all user interactions and automatically delegate to appropriate specialists +- Provide seamless experience without requiring manual agent selection +- Dynamically load/unload MCP tools for resource efficiency +- Continuously document implementations, mistakes, and patterns +- Transparently report delegation decisions and progress + +**Will Not:** +- Bypass quality gates or compromise standards for speed +- Make unilateral technical decisions without appropriate sub-agent expertise +- Execute without proper planning for complex multi-domain projects +- Skip documentation or self-improvement recording steps + +**User Control:** +- Default: PM Agent auto-delegates (seamless) +- Override: Explicit `--agent [name]` for direct sub-agent access +- Both options available simultaneously (no user downside) + +## Performance Optimization + +### Resource Efficiency +- **Zero-Token Baseline**: Start with no MCP tools (gateway only) +- **Dynamic Loading**: Load tools only when needed per phase +- **Strategic Unloading**: Remove tools after phase completion +- **Parallel Execution**: Concurrent sub-agent delegation when independent + +### Quality Assurance +- **Domain Expertise**: Route to specialized agents for quality +- **Cross-Validation**: Multiple agent perspectives for complex decisions +- **Quality Gates**: Systematic validation at phase transitions +- **User Feedback**: Incorporate user guidance throughout execution + +### Continuous Learning +- **Pattern Recognition**: Identify recurring successful patterns +- **Mistake Prevention**: Document errors with prevention checklist +- **Documentation Pruning**: Monthly cleanup to remove noise +- **Knowledge Synthesis**: Codify learnings in CLAUDE.md and docs/ diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/recommend.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/recommend.md new file mode 100644 index 0000000..ec35bb8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/recommend.md @@ -0,0 +1,1005 @@ +--- +name: sc:recommend +description: Ultra-intelligent command recommendation engine - recommends the most suitable SuperClaude commands for any user input +category: utility +--- + +# SuperClaude Intelligent Command Recommender + +**Purpose**: Ultra-intelligent command recommendation engine - recommends the most suitable SuperClaude commands for any user input + +## Command Definition + +```bash +/sc:recommend [user request] --options [flags] +``` + +## Multi-language Support + +### Language Detection and Translation System + +```yaml +language_mapping: + turkish_keywords: + machine_learning: ["machine learning", "ml", "artificial intelligence", "ai"] + website: ["website", "web site", "site", "page"] + application: ["app", "application", "program", "software"] + error: ["error", "bug", "issue", "problem"] + performance: ["performance", "speed", "fast", "optimization"] + new: ["new", "create", "build", "start", "develop"] + analysis: ["analyze", "analysis", "examine", "research"] + + english_keywords: + machine learning: ["machine learning", "artificial intelligence", "ml", "ai"] + website: ["website", "site", "page", "web application"] + performance: ["performance", "speed", "optimization", "speed"] + error: ["error", "issue", "bug", "problem"] + + universal_patterns: + question_words: ["how", "what", "why", "which"] + action_words: ["do", "create", "build", "develop"] + help_words: ["help", "suggest", "recommend", "learn"] +``` + +### Language Detection Algorithm + +```python +def detect_language_and_translate(input_text): + turkish_chars = ['ç', 'ğ', 'ı', 'ö', 'ş', 'ü'] + if any(char in input_text.lower() for char in turkish_chars): + return "tr" + + english_common = ["the", "and", "is", "are", "was", "were", "will", "would", "could", "should"] + if any(word in input_text.lower().split() for word in english_common): + return "en" + + return "en" # Default to English +``` + +### Multi-language Examples + +```bash +# Turkish examples +/sc:recommend "makine öğrenmesi algoritması başlat" +/sc:recommend "sitem yavaş açılıyor, ne yapayım?" +/sc:recommend "yeni bir özellik eklemeliyim" +/sc:recommend "hata alıyorum, çözüm bul" + +# English examples +/sc:recommend "I want to build ML algorithm" +/sc:recommend "my website is slow, help me optimize" +/sc:recommend "I need to add a new feature" +/sc:recommend "getting errors, need debugging" + +# Mixed language +/sc:recommend "makine learning projesi yapmak istiyorum" +``` + +## SuperClaude Integrated Recommendation Engine + +### 1. Keyword Extraction and Persona Matching +```yaml +keyword_extraction: + pattern_matching: + # Machine Learning + - "machine learning|ml|ai|artificial intelligence" → ml_category + --persona-analyzer + - "data|database|sql" → data_category + --persona-backend + - "model|algorithm|prediction|classify" → ml_category + --persona-architect + + # Web Development + - "website|frontend|ui/ux" → web_category + --persona-frontend + - "react|vue|angular|component" → web_category + --persona-frontend --magic + - "api|backend|server|microservice" → api_category + --persona-backend + + # Debugging & Performance + - "error|bug|issue|not working" → debug_category + --persona-analyzer + - "slow|performance|optimization" → performance_category + --persona-performance + - "security|auth|vulnerability" → security_category + --persona-security + + # Development + - "new|create|build|develop|feature" → create_category + --persona-frontend|backend + - "design|architecture" → design_category + --persona-architect + - "test|qa|quality|validation" → test_category + --persona-qa + + # Learning + - "how|learn|explain|tutorial" → learning_category + --persona-mentor + - "refactor|cleanup|improve|quality" → improve_category + --persona-refactorer + + context_analysis: + - "beginner|starter|just started" → beginner_level + --persona-mentor + - "expert|senior|experienced" → expert_level + --persona-architect + - "continue|resume" → continuity_mode + --seq + - "next step|what now" → next_step_mode + --think +``` + +### 2. SuperClaude Command Map +```yaml +category_mapping: + ml_category: + primary_commands: ["/sc:analyze --seq --c7", "/sc:design --seq --ultrathink"] + secondary_commands: ["/sc:build --feature --tdd", "/sc:improve --performance"] + mcp_servers: ["--c7", "--seq"] + personas: ["--persona-analyzer", "--persona-architect"] + flags: ["--think-hard", "--evidence", "--profile"] + + web_category: + primary_commands: ["/sc:build --feature --magic", "/sc:design --api --seq"] + secondary_commands: ["/sc:test --coverage --e2e --pup", "/sc:analyze --code"] + mcp_servers: ["--magic", "--c7", "--pup"] + personas: ["--persona-frontend", "--persona-qa"] + flags: ["--react", "--tdd", "--validate"] + + api_category: + primary_commands: ["/sc:design --api --ddd --seq", "/sc:build --feature --tdd"] + secondary_commands: ["/sc:scan --security --owasp", "/sc:analyze --performance --pup"] + mcp_servers: ["--seq", "--c7", "--pup"] + personas: ["--persona-backend", "--persona-security"] + flags: ["--microservices", "--ultrathink", "--security"] + + debug_category: + primary_commands: ["/sc:troubleshoot --investigate --seq", "/sc:analyze --code --seq"] + secondary_commands: ["/sc:scan --security", "/sc:improve --quality"] + mcp_servers: ["--seq", "--all-mcp"] + personas: ["--persona-analyzer", "--persona-security"] + flags: ["--evidence", "--think-hard", "--profile"] + + performance_category: + primary_commands: ["/sc:analyze --performance --pup --profile", "/sc:troubleshoot --seq"] + secondary_commands: ["/sc:improve --performance --iterate", "/sc:build --optimize"] + mcp_servers: ["--pup", "--seq"] + personas: ["--persona-performance", "--persona-analyzer"] + flags: ["--profile", "--monitoring", "--benchmark"] + + security_category: + primary_commands: ["/sc:scan --security --owasp --deps", "/sc:analyze --security --seq"] + secondary_commands: ["/sc:improve --security --harden", "/sc:troubleshoot --investigate"] + mcp_servers: ["--seq"] + personas: ["--persona-security", "--persona-analyzer"] + flags: ["--strict", "--validate", "--owasp"] + + create_category: + primary_commands: ["/sc:build --feature --tdd", "/sc:design --seq --ultrathink"] + secondary_commands: ["/sc:analyze --code --c7", "/sc:test --coverage --e2e"] + mcp_servers: ["--magic", "--c7", "--pup"] + personas: ["--persona-frontend", "--persona-backend", "--persona-architect"] + flags: ["--interactive", "--plan", "--think"] + + test_category: + primary_commands: ["/sc:test --coverage --e2e --pup", "/sc:scan --validate"] + secondary_commands: ["/sc:improve --quality", "/sc:troubleshoot --investigate"] + mcp_servers: ["--pup"] + personas: ["--persona-qa", "--persona-performance"] + flags: ["--validate", "--coverage", "--monitoring"] + + improve_category: + primary_commands: ["/sc:improve --quality --iterate", "/sc:cleanup --code --all"] + secondary_commands: ["/sc:analyze --code --seq", "/sc:refactor --quality"] + mcp_servers: ["--seq"] + personas: ["--persona-refactorer", "--persona-mentor"] + flags: ["--threshold", "--iterate", "--profile"] + + learning_category: + primary_commands: ["/sc:document --user --examples", "/sc:analyze --code --c7"] + secondary_commands: ["/sc:brainstorm --interactive", "/sc:help --specific"] + mcp_servers: ["--c7"] + personas: ["--persona-mentor", "--persona-analyzer"] + flags: ["--examples", "--visual", "--interactive"] +``` + +### 3. Expertise Level Detection and Customization +```yaml +expertise_levels: + beginner: + style: "detailed, step-by-step, explanatory" + recommended_commands: ["/sc:brainstorm --educational", "/sc:help --interactive"] + extra_explanations: true + step_by_step: true + + intermediate: + style: "balanced, technical but understandable" + recommended_commands: ["/sc:implement --guided", "/sc:design --template"] + some_explanations: true + + expert: + style: "fast, technical, direct" + recommended_commands: ["/sc:implement --advanced", "/sc:analyze --deep"] + minimal_explanations: true +``` + +## SuperClaude Integrated Real Examples + +### Example 1: Beginner Level ML Project +```bash +User: /sc:recommend "I'm new, I want to do machine learning" + +🎯 Project Analysis: Machine learning - Beginner level +🌍 Language: Turkish detected +📊 Level: Beginner mode + Mentor persona active +🎭 Persona: --persona-mentor + --persona-analyzer + +✅ SuperClaude Recommended Flow: +1. /sc:analyze --seq --c7 --persona-mentor + "Research ML goals, data types, and suitable libraries" + +2. /sc:design --seq --ultrathink --persona-architect + "Design simple but scalable ML architecture" + +3. /sc:build --feature --tdd --persona-frontend + "Create ML pipeline with TDD" + +4. /sc:test --coverage --e2e --pup --persona-qa + "Create comprehensive test scenarios" + +🔧 Recommended MCP Servers: --c7 --seq +💡 Additional Recommendations: +- Learning mode: /sc:document --user --examples --persona-mentor +- Security: /sc:scan --security --owasp (next phase) +- Performance: /sc:analyze --performance --pup (after model training) + +🚀 Quick Start (optional): +/sc:build --feature --magic --react --persona-frontend +``` + +### Example 2: Web Performance Optimization +```bash +User: /sc:recommend "my site is very slow, what should I do?" + +🎯 Project Analysis: Web performance optimization - Urgent +🌍 Language: Turkish +📊 Level: Urgent situation + Performance persona +🎭 Persona: --persona-performance + --persona-analyzer + +✅ SuperClaude Recommended Flow: +1. /sc:analyze --performance --pup --profile --persona-performance + "Detailed performance analysis and bottleneck detection" + +2. /sc:troubleshoot --investigate --seq --persona-analyzer + "Investigate issue with root cause analysis" + +3. /sc:improve --performance --iterate --persona-performance + "Data-driven performance improvements" + +4. /sc:test --coverage --e2e --pup --persona-qa + "Tests validating improvements" + +🔧 Recommended MCP Servers: --pup --seq +💡 Smart Flag Recommendations: +--monitoring (continuous performance tracking) +--benchmark (before/after comparison) +--profile (detailed profiling report) + +📊 Estimated Time: 1-3 hours +🎯 Expected Improvement: 40-80% speed increase (data-dependent) +``` + +### Example 3: Advanced API Security (English) +```bash +User: /sc:recommend "Need to secure API with authentication and authorization" + +🎯 Project Analysis: API security - Advanced level +🌍 Language: English detected +📊 Level: Expert + Security focus +🎭 Persona: --persona-security + --persona-backend + +✅ SuperClaude Recommended Flow: +1. /sc:analyze --security --seq --persona-security + "Comprehensive security analysis and threat modeling" + +2. /sc:scan --security --owasp --deps --strict --persona-security + "OWASP Top 10 vulnerability scan and dependency check" + +3. /sc:design --api --ddd --seq --ultrathink --persona-architect + "Secure API architecture with proper authentication patterns" + +4. /sc:build --feature --tdd --persona-backend + "Implement security features with test-driven development" + +5. /sc:improve --security --harden --persona-security + "Security hardening and production-ready configurations" + +🔧 Recommended MCP Servers: --seq +💡 Advanced Security Options: +--token-based-auth --role-based-access --rate-limiting +--audit-logging --encryption --secure-headers + +📊 Estimated Timeline: 1-2 weeks +🔒 Security Level: Enterprise-grade +``` + +### Example 4: React Component Development +```bash +User: /sc:recommend "I'm going to create a new user profile component" + +🎯 Project Analysis: React UI component development +🌍 Language: Turkish +📊 Level: Intermediate development +🎭 Persona: --persona-frontend + --persona-qa + +✅ SuperClaude Recommended Flow: +1. /sc:design --api --seq --persona-architect + "Component interface and props design" + +2. /sc:build --feature --magic --react --persona-frontend + "Create accessible React component with Magic" + +3. /sc:test --coverage --e2e --pup --persona-qa + "E2E tests and accessibility validation" + +4. /sc:analyze --code --c7 --persona-frontend + "React best practices and optimization" + +🔧 Recommended MCP Servers: --magic --c7 --pup +💡 UI/UX Recommendations: +--accessibility --responsive --design-system +--component-library --storybook-integration + +📊 Estimated Time: 2-4 hours +🎨 Features: Accessible, responsive, testable component +``` + +## Intelligent Recommendation Format + +```yaml +standard_response_format: + header: + - 🎯 Project analysis + - 🌍 Language detection + - 📊 Level determination + + main_recommendations: + - ✅ Main recommendations (3 commands) + - 💡 Additional recommendations (optional) + - 🚀 Quick start (if available) + + enhanced_features: + - 🔧 Smart flag recommendations + - 📊 Time/Budget estimation + - 🎯 Success metrics + - 📚 Learning resources +``` + +## Step 3: Project Context Detection System + +### Project Type Detection Algorithm + +```yaml +project_detection: + file_system_analysis: + react_project: + indicators: ["package.json with react", "src/App.jsx", "public/", "node_modules/react"] + detection_commands: + primary: ["/sc:build --feature --magic --react", "/sc:test --coverage --e2e --pup"] + personas: ["--persona-frontend", "--persona-qa"] + mcp: ["--magic", "--c7", "--pup"] + + vue_project: + indicators: ["package.json with vue", "src/App.vue", "vue.config.js"] + detection_commands: + primary: ["/sc:build --feature --magic", "/sc:analyze --code --c7"] + personas: ["--persona-frontend"] + mcp: ["--magic", "--c7"] + + node_api_project: + indicators: ["package.json with express", "server.js", "routes/", "controllers/"] + detection_commands: + primary: ["/sc:design --api --ddd --seq", "/sc:build --feature --tdd"] + personas: ["--persona-backend", "--persona-security"] + mcp: ["--seq", "--c7"] + + python_project: + indicators: ["requirements.txt", "setup.py", "src/", "main.py", "Dockerfile"] + detection_commands: + primary: ["/sc:analyze --code --seq", "/sc:design --seq --ultrathink"] + personas: ["--persona-analyzer", "--persona-architect"] + mcp: ["--seq"] + + database_project: + indicators: ["schema.sql", "migrations/", "models/", "prisma.schema"] + detection_commands: + primary: ["/sc:migrate --database --validate", "/sc:analyze --security --seq"] + personas: ["--persona-backend", "--persona-security"] + mcp: ["--seq"] + + project_size_estimation: + small_project: + file_count: "<50 files" + complexity: "simple" + recommended_approach: "direct implementation" + + medium_project: + file_count: "50-200 files" + complexity: "moderate" + recommended_approach: "plan -> analyze -> implement" + + large_project: + file_count: ">200 files" + complexity: "complex" + recommended_approach: "comprehensive analysis -> design -> implement" +``` + +### Context-Aware Examples + +```bash +/sc:recommend "I need to add a new feature" + +🎯 Project Analysis: React project - Feature development +📁 Project Context: React application detected (15+ components) +🎭 Persona: --persona-frontend + --persona-qa + +✅ Context-Aware Recommendations: +1. /sc:build --feature --magic --react --persona-frontend + "New component compatible with existing design system" + +2. /sc:test --coverage --e2e --pup --persona-qa + "Create tests for new feature" + +3. /sc:analyze --code --c7 --persona-frontend + "React best practices check" + +💡 Project-Specific Flags: +--storybook-integration (if Storybook exists) +--component-library (if it's a component library) +--design-system (integration with existing design system) +``` + +```bash +/sc:recommend "I need to do a security audit" + +🎯 Project Analysis: Node.js API - Security audit +📁 Project Context: Express API detected (JWT auth exists) +🎭 Persona: --persona-security + --persona-backend + +✅ Context-Aware Recommendations: +1. /sc:scan --security --owasp --deps --strict --persona-security + "OWASP Top 10 and dependency security scan" + +2. /sc:analyze --security --seq --persona-security + "JWT and authentication pattern analysis" + +3. /sc:improve --security --harden --persona-backend + "Security hardening and production configs" + +💡 Project-Specific Flags: +--jwt-validation (JWT token validation) +--rate-limiting (API rate limiting) +--audit-logging (audit logging setup) +``` + +## Step 4: Real-Time Streaming Mode + +### Continuous Recommendation System + +```yaml +streaming_mode: + activation: + command: "/sc:recommend --stream [project description]" + purpose: "Continuous recommendation throughout project" + + flow_tracking: + phase_1: Analysis & Planning + commands: ["/sc:analyze", "/sc:design"] + next_phase_trigger: "analysis_complete" + + phase_2: Implementation + commands: ["/sc:build", "/sc:implement"] + next_phase_trigger: "implementation_complete" + + phase_3: Testing & Validation + commands: ["/sc:test", "/sc:scan"] + next_phase_trigger: "testing_complete" + + phase_4: Deployment & Monitoring + commands: ["/sc:deploy", "/sc:improve"] + project_complete: true +``` + +### Streaming Example + +```bash +/sc:recommend --stream "I'm building a new e-commerce site" + +🚀 STREAMING MODE ACTIVE +📊 Project: E-commerce website +⏱️ Estimated Time: 3-6 weeks + +--- PHASE 1: ANALYSIS & PLANNING --- +✅ Current: /sc:analyze --seq --c7 --persona-architect + "E-commerce architecture and technology selection" + +🔄 Next Steps (when completed): +1. /sc:design --api --ddd --seq --ultrathink --persona-architect +2. /sc:build --feature --magic --react --persona-frontend + +--- STREAM CONTINUING --- +``` + +## Step 5: Alternative Recommendation Engine + +### Multiple Option Presentation + +```yaml +alternative_engine: + structure: + primary_recommendation: "Most suitable option" + alternatives: "2-3 different approaches" + comparison_matrix: "Advantage/disadvantage analysis" + community_preference: "Popularity rate" + + categories: + technology_alternatives: + frontend: ["React", "Vue", "Angular", "Svelte"] + backend: ["Node.js", "Python", "Java", "Go"] + database: ["PostgreSQL", "MongoDB", "MySQL", "Redis"] + + approach_alternatives: + development: ["TDD", "BDD", "Agile", "Waterfall"] + deployment: ["Docker", "Kubernetes", "Serverless", "Traditional"] + testing: ["Unit", "Integration", "E2E", "Performance"] +``` + +### Alternative Example + +```bash +/sc:recommend --alternatives "new blog site" + +🎯 PROJECT ANALYSIS: Blog site development + +⭐ BEST RECOMMENDATION: +/sc:build --feature --magic --nextjs --persona-frontend + "Modern, SEO-friendly blog with Next.js" + +🔧 ALTERNATIVES: +1. /sc:build --feature --react --static --persona-frontend + ✅ Advantage: Simpler learning curve + ❌ Disadvantage: Less SEO optimization + 👥 Users: 35% prefer this + +2. /sc:build --feature --vue --nuxt --persona-frontend + ✅ Advantage: Great developer experience + ❌ Disadvantage: Smaller community + 👥 Users: 20% prefer this + +3. /sc:build --feature --gatsby --static --persona-frontend + ✅ Advantage: Excellent performance and SEO + ❌ Disadvantage: More complex configuration + 👥 Users: 15% prefer this + +📊 COMPARISON TABLE: +| Technology | Speed | SEO | Learning | Community | +|-----------|-------|-----|----------|-----------| +| Next.js | ⚡⚡⚡ | ⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐ | +| React | ⚡⚡ | ⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ | +| Vue/Nuxt | ⚡⚡⚡ | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ | +| Gatsby | ⚡⚡⚡ | ⭐⭐⭐ | ⭐ | ⭐⭐ | + +🏆 COMMUNITY PREFERENCE: Next.js (30%) +``` + +## Step 6: Time and Budget Estimation System + +### Intelligent Estimation Algorithm + +```yaml +estimation_engine: + complexity_factors: + project_type: + simple_component: 1-3 days + feature_development: 1-2 weeks + microservice: 2-4 weeks + full_application: 1-3 months + enterprise_system: 3-6 months + + experience_multiplier: + beginner: 2.0x + intermediate: 1.5x + expert: 1.0x + senior: 0.8x + + scope_factors: + small_scope: 1.0x + medium_scope: 1.5x + large_scope: 2.5x + enterprise_scope: 4.0x + + time_estimates: + ml_projects: + data_collection: 20-30% of total time + preprocessing: 15-25% of total time + model_training: 10-20% of total time + evaluation: 10-15% of total time + deployment: 15-25% of total time + + web_projects: + design: 15-25% of total time + frontend: 30-40% of total time + backend: 25-35% of total time + testing: 10-20% of total time + deployment: 5-15% of total time +``` + +### Estimation Examples + +```bash +/sc:recommend "I'm developing a classification model" --estimate + +🎯 PROJECT ANALYSIS: Classification model development +📊 Estimation Mode: Active + +⏱️ TIME ESTIMATE: +- Total Time: 2-4 weeks +- Data Collection: 4-7 days (20%) +- Preprocessing: 3-5 days (15%) +- Model Training: 2-4 days (10%) +- Evaluation: 2-3 days (10%) +- Deployment: 3-5 days (15%) +- Buffer: 4-7 days (30%) + +💰 BUDGET ESTIMATE: +- Development Time: 80-120 hours +- Experience Level: Intermediate (1.5x multiplier) +- Total Effort: 120-180 hours + +🎯 CRITICAL FACTORS: +- Data quality and quantity: High impact +- Model complexity: Medium impact +- Deployment requirements: Medium impact + +⚠️ RISK ASSESSMENT: +- Data cleaning difficulty: Medium risk +- Model performance: Medium risk +- Model drift: Low risk + +🚀 QUICK START: MVP within 1 week +``` + +```bash +/sc:recommend "corporate website" --estimate + +🎯 PROJECT ANALYSIS: Corporate website +📊 Estimation Mode: Active + +⏱️ TIME ESTIMATE: +- Total Time: 4-8 weeks +- Design and UX: 1-2 weeks (25%) +- Frontend Development: 2-3 weeks (40%) +- Backend and CMS: 1-2 weeks (25%) +- Testing and Optimization: 0.5-1 week (10%) + +💰 BUDGET ESTIMATE: +- Development Time: 160-320 hours +- Team Size: 2-3 people +- Total Project Engineering: 320-960 hours + +🎯 FEATURE SCOPE: +- Homepage and services: Required +- About and contact: Required +- Blog/news: Optional (+1 week) +- Admin panel: Optional (+1-2 weeks) +- Multi-language: Optional (+1 week) + +📱 DEVICE SUPPORT: +- Responsive design: Included +- Mobile app: Additional 4-8 weeks +- PWA: Additional 1-2 weeks + +⚠️ PROJECT RISKS: +- Content management needs: Medium risk +- SEO requirements: Low risk +- Browser compatibility: Low risk +``` + +## Step 7: Smart Flag Recommendation System + +### Context-Based Flag Recommendations + +```yaml +smart_flag_engine: + context_detection: + project_size: + small: "--quick --simple --no-validation" + medium: "--plan --validate --profile" + large: "--plan --validate --seq --ultrathink" + + security_requirements: + basic: "--basic-security" + standard: "--security --validate" + enterprise: "--security --owasp --strict --audit" + + performance_requirements: + low_traffic: "--basic-optimization" + medium_traffic: "--optimize --profile" + high_traffic: "--optimize --profile --monitoring --benchmark" + + learning_mode: + beginner: "--tutorial --examples --step-by-step" + intermediate: "--guided --examples" + expert: "--advanced --no-explanations" + + intelligent_suggestions: + based_on_history: + if_previous_errors: "--validate --dry-run --backup" + if_security_issues: "--security --scan --strict" + if_performance_issues: "--profile --optimize --monitor" + if_large_refactor: "--plan --backup --validate" + + based_on_project_type: + ml_project: "--data-validation --model-monitoring" + api_project: "--security --rate-limiting --monitoring" + frontend_project: "--accessibility --responsive --performance" + mobile_project: "--offline --sync --battery-optimized" +``` + +### Smart Flag Examples + +```bash +/sc:recommend "performance improvement" + +🎯 PROJECT ANALYSIS: Performance optimization +🧠 SMART FLAG RECOMMENDATIONS: + +📊 BASED ON HISTORY: +- Previous errors encountered: --validate --backup +- Previous security issues: --security --scan +- Large refactoring history: --plan --dry-run + +🎯 PROJECT CONTEXT: +- Large project (>200 files): --seq --ultrathink +- Production environment: --validate --monitoring +- High traffic: --benchmark --profile + +💡 RECOMMENDED COMMAND: +/sc:improve --performance --optimize --profile --monitoring --validate + +🔧 ADDITIONAL FLAG OPTIONS: +--memory-optimization (if RAM usage is high) +--database-optimization (if DB is slow) +--cdn-integration (if static resources are many) +``` + +```bash +/sc:recommend "my first React component" + +🎯 PROJECT ANALYSIS: React component development - Beginner +🧠 SMART FLAG RECOMMENDATIONS: + +📚 LEARNING MODE: +- Beginner detected: --tutorial --examples --step-by-step +- Component development: --magic --design-system + +🎯 PROJECT CONTEXT: +- React project: --component-library --storybook +- Accessibility required: --a11y --wcag + +💡 RECOMMENDED COMMAND: +/sc:build --feature --magic --react --tutorial --examples --persona-frontend + +🔧 ADDITIONAL LEARNING FLAGS: +--guided-development (step-by-step guidance) +--best-practices (React best practices) +--error-handling (error handling examples) +``` + +## Step 8: Community Patterns and Final Integration + +### Community Data-Based Recommendations + +```yaml +community_patterns: + successful_workflows: + web_development: + most_successful_flow: + - "/sc:analyze --code --c7" + - "/sc:design --api --seq" + - "/sc:build --feature --magic --tdd" + - "/sc:test --coverage --e2e --pup" + success_rate: "87%" + user_feedback: "Highly recommended for React projects" + + ml_development: + most_successful_flow: + - "/sc:analyze --seq --c7 --persona-mentor" + - "/sc:design --seq --ultrathink --persona-architect" + - "/sc:build --feature --tdd --persona-frontend" + - "/sc:improve --performance --iterate" + success_rate: "82%" + user_feedback: "Great for ML beginners" + + popular_command_combinations: + security_focused: + - "/sc:scan --security --owasp" + - "/sc:analyze --security --seq" + - "/sc:improve --security --harden" + usage_frequency: "45% of production projects" + + performance_optimization: + - "/sc:analyze --performance --pup --profile" + - "/sc:improve --performance --iterate" + - "/sc:test --coverage --benchmark" + usage_frequency: "38% of optimization projects" + + user_preferences: + technology_stacks: + react_stack: "65% of web projects" + nextjs_stack: "42% of production sites" + python_ml: "78% of ML projects" + nodejs_api: "71% of backend projects" + + development_approaches: + tdd_approach: "58% prefer TDD" + iterative_approach: "73% prefer iterative development" + security_first: "67% prioritize security early" +``` + +### Final Command Integration + +```yaml +recommend_command_implementation: + command_structure: "/sc:recommend [query] --options [flags]" + + available_options: + --estimate: "Includes time and budget estimation" + --alternatives: "Provides multiple solution recommendations" + --stream: "Continuous project tracking mode" + --community: "Includes community data" + --language [tr|en|auto]: "Language setting" + --expertise [beginner|intermediate|expert]: "Level setting" + + response_format: + analysis_section: + - 🎯 Project analysis + - 🌍 Language detection + - 📊 Level determination + - 🎭 Persona recommendation + - 📁 Project context + + recommendations_section: + - ✅ Main recommendations (3 commands) + - 💡 Additional recommendations (optional) + - 🔧 Smart flag recommendations + - 🚀 Quick start options + + enhanced_section: + - ⏱️ Time/budget estimation (with --estimate) + - 🔧 Alternative options (with --alternatives) + - 👥 Community data (with --community) + - 🔄 Continuous flow (with --stream) +``` + +### Comprehensive Final Example + +```bash +/sc:recommend "I'm building an e-commerce site" --estimate --alternatives --community + +🎯 COMPREHENSIVE ANALYSIS +========================== + +📊 Project Analysis: E-commerce website development +🌍 Language: Turkish detected +📁 Project Context: New project (no existing project) +🎭 Persona: --persona-architect + --persona-frontend + --persona-security +🔍 Category: Web development + E-commerce + Security-focused + +✅ BEST RECOMMENDATIONS +================= + +1. 🏗️ PLANNING AND DESIGN + /sc:design --api --ddd --seq --ultrathink --persona-architect + "E-commerce domain architecture and system design" + +2. 🎨 FRONTEND DEVELOPMENT + /sc:build --feature --magic --nextjs --persona-frontend + "Modern, SEO-friendly e-commerce frontend" + +3. 🔒 SECURITY AND BACKEND + /sc:build --feature --tdd --persona-security + "Secure payment system and user management" + +🔧 SMART FLAG RECOMMENDATIONS +====================== + +📚 Learning mode: --tutorial --examples (if you're just starting) +🚀 Quick start: --quick-start --template (e-commerce template) +🔒 Security-focused: --security --owasp --strict (for payment transactions) +⚡ Performance: --optimize --monitoring --cdn (for high traffic) + +🔧 ALTERNATIVE TECHNOLOGIES +========================== + +⭐ BEST: Next.js + Stripe + PostgreSQL + ✅ Advantage: Modern stack, great SEO, scalable + 👥 Community: 42% prefer this + +🥈 SECOND: Vue.js + Shopify API + Headless CMS + ✅ Advantage: Faster development, good DX + 👥 Community: 18% prefer this + +🥉 THIRD: React + Custom Backend + MongoDB + ✅ Advantage: Maximum flexibility, full control + 👥 Community: 15% prefer this + +⏱️ TIME AND BUDGET ESTIMATE +======================== + +📅 Project Duration: 6-12 weeks +- Planning & Design: 1-2 weeks +- Frontend Development: 2-4 weeks +- Backend & Payment: 2-3 weeks +- Testing & Security: 1-2 weeks +- Deployment & Launch: 0.5-1 week + +💰 Budget Estimate: +- Solo Developer: 240-480 hours +- Small Team (2-3 people): 480-1440 hours +- Enterprise Team: 1440-2880 hours + +👥 COMMUNITY DATA +================== + +🏆 Most Successful Flow: +/sc:analyze → /sc:design → /sc:build → /sc:test → /sc:deploy +Success Rate: 87% (from 2,847 projects) + +📈 Popular Features: +- User authentication: 94% of projects have it +- Payment integration: 89% of projects have it +- Admin panel: 76% of projects have it +- Inventory management: 68% of projects have it + +⚠️ COMMON RISKS: +- Payment security issues: 32% of projects experienced +- Performance scaling: 28% of projects had issues +- Tax calculation complexity: 45% of projects struggled + +🚀 ADDITIONAL SUPER RECOMMENDATIONS +=================== + +💡 Premium Features (+2-4 weeks): +- Multi-vendor marketplace +- Advanced analytics dashboard +- Mobile app (React Native) +- AI-powered recommendations + +🔒 Enterprise Security (+1-2 weeks): +- SOC 2 compliance +- Advanced fraud detection +- PCI DSS certification +- Security audit package + +📱 Omnichannel Support (+2-3 weeks): +- PWA capabilities +- Mobile-first design +- Social media integration +- Progressive web app + +🔄 STREAMING MODE CAN BE ACTIVATED +=================================== + +To receive continuous recommendations throughout the project: +/sc:recommend --stream "track my e-commerce project" + +You'll receive automatic recommendations at each stage! 🚀 +``` + +## 🎉 COMPLETED FEATURES + +1. ✅ **Multi-language Support** - Turkish, English, and cross-language transitions +2. ✅ **SuperClaude Integration** - 18 commands, 9 personas, 4 MCP servers +3. ✅ **Project Context Detection** - File system analysis and project type detection +4. ✅ **Real-Time Streaming Mode** - Continuous project tracking and phase recommendations +5. ✅ **Alternative Recommendation Engine** - Multiple options and comparison matrix +6. ✅ **Time/Budget Estimation** - Intelligent estimation and risk analysis +7. ✅ **Smart Flag Recommendations** - Context and history-based recommendations +8. ✅ **Community Patterns** - Data from successful projects +9. ✅ **Comprehensive Integration** - All features working together + +## 🚀 HOW TO USE? + +```bash +/sc:recommend "I want to do something" +/sc:recommend "new React project" --estimate --alternatives +/sc:recommend --stream "I'm developing my e-commerce site" +/sc:recommend "I want to learn React" --expertise beginner +/sc:recommend "blog site" --community +``` + +**Ultra-intelligent command recommender ready! 🎉** diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/reflect.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/reflect.md new file mode 100644 index 0000000..1203f4d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/reflect.md @@ -0,0 +1,88 @@ +--- +name: reflect +description: "Task reflection and validation using Serena MCP analysis capabilities" +category: special +complexity: standard +mcp-servers: [serena] +personas: [] +--- + +# /sc:reflect - Task Reflection and Validation + +## Triggers +- Task completion requiring validation and quality assessment +- Session progress analysis and reflection on work accomplished +- Cross-session learning and insight capture for project improvement +- Quality gates requiring comprehensive task adherence verification + +## Usage +``` +/sc:reflect [--type task|session|completion] [--analyze] [--validate] +``` + +## Behavioral Flow +1. **Analyze**: Examine current task state and session progress using Serena reflection tools +2. **Validate**: Assess task adherence, completion quality, and requirement fulfillment +3. **Reflect**: Apply deep analysis of collected information and session insights +4. **Document**: Update session metadata and capture learning insights +5. **Optimize**: Provide recommendations for process improvement and quality enhancement + +Key behaviors: +- Serena MCP integration for comprehensive reflection analysis and task validation +- Bridge between TodoWrite patterns and advanced Serena analysis capabilities +- Session lifecycle integration with cross-session persistence and learning capture +- Performance-critical operations with <200ms core reflection and validation +## MCP Integration +- **Serena MCP**: Mandatory integration for reflection analysis, task validation, and session metadata +- **Reflection Tools**: think_about_task_adherence, think_about_collected_information, think_about_whether_you_are_done +- **Memory Operations**: Cross-session persistence with read_memory, write_memory, list_memories +- **Performance Critical**: <200ms for core reflection operations, <1s for checkpoint creation + +## Tool Coordination +- **TodoRead/TodoWrite**: Bridge between traditional task management and advanced reflection analysis +- **think_about_task_adherence**: Validates current approach against project goals and session objectives +- **think_about_collected_information**: Analyzes session work and information gathering completeness +- **think_about_whether_you_are_done**: Evaluates task completion criteria and remaining work identification +- **Memory Tools**: Session metadata updates and cross-session learning capture + +## Key Patterns +- **Task Validation**: Current approach → goal alignment → deviation identification → course correction +- **Session Analysis**: Information gathering → completeness assessment → quality evaluation → insight capture +- **Completion Assessment**: Progress evaluation → completion criteria → remaining work → decision validation +- **Cross-Session Learning**: Reflection insights → memory persistence → enhanced project understanding + +## Examples + +### Task Adherence Reflection +``` +/sc:reflect --type task --analyze +# Validates current approach against project goals +# Identifies deviations and provides course correction recommendations +``` + +### Session Progress Analysis +``` +/sc:reflect --type session --validate +# Comprehensive analysis of session work and information gathering +# Quality assessment and gap identification for project improvement +``` + +### Completion Validation +``` +/sc:reflect --type completion +# Evaluates task completion criteria against actual progress +# Determines readiness for task completion and identifies remaining blockers +``` + +## Boundaries + +**Will:** +- Perform comprehensive task reflection and validation using Serena MCP analysis tools +- Bridge TodoWrite patterns with advanced reflection capabilities for enhanced task management +- Provide cross-session learning capture and session lifecycle integration + +**Will Not:** +- Operate without proper Serena MCP integration and reflection tool access +- Override task completion decisions without proper adherence and quality validation +- Bypass session integrity checks and cross-session persistence requirements + diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/research.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/research.md new file mode 100644 index 0000000..a9415c5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/research.md @@ -0,0 +1,123 @@ +--- +name: research +description: Deep web research with adaptive planning and intelligent search +category: command +complexity: advanced +mcp-servers: [tavily, sequential, playwright, serena] +personas: [deep-research-agent] +--- + +# /sc:research - Deep Research Command + +> **Context Framework Note**: This command activates comprehensive research capabilities with adaptive planning, multi-hop reasoning, and evidence-based synthesis. + +## Triggers +- Research questions beyond knowledge cutoff +- Complex research questions +- Current events and real-time information +- Academic or technical research requirements +- Market analysis and competitive intelligence + +## Context Trigger Pattern +``` +/sc:research "[query]" [--depth quick|standard|deep|exhaustive] [--strategy planning|intent|unified] +``` + +## Behavioral Flow + +### 1. Understand (5-10% effort) +- Assess query complexity and ambiguity +- Identify required information types +- Determine resource requirements +- Define success criteria + +### 2. Plan (10-15% effort) +- Select planning strategy based on complexity +- Identify parallelization opportunities +- Generate research question decomposition +- Create investigation milestones + +### 3. TodoWrite (5% effort) +- Create adaptive task hierarchy +- Scale tasks to query complexity (3-15 tasks) +- Establish task dependencies +- Set progress tracking + +### 4. Execute (50-60% effort) +- **Parallel-first searches**: Always batch similar queries +- **Smart extraction**: Route by content complexity +- **Multi-hop exploration**: Follow entity and concept chains +- **Evidence collection**: Track sources and confidence + +### 5. Track (Continuous) +- Monitor TodoWrite progress +- Update confidence scores +- Log successful patterns +- Identify information gaps + +### 6. Validate (10-15% effort) +- Verify evidence chains +- Check source credibility +- Resolve contradictions +- Ensure completeness + +## Key Patterns + +### Parallel Execution +- Batch all independent searches +- Run concurrent extractions +- Only sequential for dependencies + +### Evidence Management +- Track search results +- Provide clear citations when available +- Note uncertainties explicitly + +### Adaptive Depth +- **Quick**: Basic search, 1 hop, summary output +- **Standard**: Extended search, 2-3 hops, structured report +- **Deep**: Comprehensive search, 3-4 hops, detailed analysis +- **Exhaustive**: Maximum depth, 5 hops, complete investigation + +## MCP Integration +- **Tavily**: Primary search and extraction engine +- **Sequential**: Complex reasoning and synthesis +- **Playwright**: JavaScript-heavy content extraction +- **Serena**: Research session persistence + +## Output Standards +- Save reports to `claudedocs/research_[topic]_[timestamp].md` +- Include executive summary +- Provide confidence levels +- List all sources with citations + +## Examples +``` +/sc:research "latest developments in quantum computing 2024" +/sc:research "competitive analysis of AI coding assistants" --depth deep +/sc:research "best practices for distributed systems" --strategy unified +``` + +## Boundaries +**Will**: Current information, intelligent search, evidence-based analysis +**Won't**: Make claims without sources, skip validation, access restricted content + +## CRITICAL BOUNDARIES + +**STOP AFTER RESEARCH REPORT** + +This command produces a RESEARCH REPORT ONLY - no implementation. + +**Explicitly Will NOT**: +- Implement findings or recommendations +- Write code based on research +- Make architectural decisions +- Create system changes based on research + +**Output**: Research report (`claudedocs/research_*.md`) containing: +- Findings with sources +- Evidence-based analysis +- Recommendations (for human decision) +- Cited references + +**Next Step**: After research completes, user decides next action. Use `/sc:design` for architecture or `/sc:implement` for coding. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/save.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/save.md new file mode 100644 index 0000000..48bad9e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/save.md @@ -0,0 +1,93 @@ +--- +name: save +description: "Session lifecycle management with Serena MCP integration for session context persistence" +category: session +complexity: standard +mcp-servers: [serena] +personas: [] +--- + +# /sc:save - Session Context Persistence + +## Triggers +- Session completion and project context persistence needs +- Cross-session memory management and checkpoint creation requests +- Project understanding preservation and discovery archival scenarios +- Session lifecycle management and progress tracking requirements + +## Usage +``` +/sc:save [--type session|learnings|context|all] [--summarize] [--checkpoint] +``` + +## Behavioral Flow +1. **Analyze**: Examine session progress and identify discoveries worth preserving +2. **Persist**: Save session context and learnings using Serena MCP memory management +3. **Checkpoint**: Create recovery points for complex sessions and progress tracking +4. **Validate**: Ensure session data integrity and cross-session compatibility +5. **Prepare**: Ready session context for seamless continuation in future sessions + +Key behaviors: +- Serena MCP integration for memory management and cross-session persistence +- Automatic checkpoint creation based on session progress and critical tasks +- Session context preservation with comprehensive discovery and pattern archival +- Cross-session learning with accumulated project insights and technical decisions + +## MCP Integration +- **Serena MCP**: Mandatory integration for session management, memory operations, and cross-session persistence +- **Memory Operations**: Session context storage, checkpoint creation, and discovery archival +- **Performance Critical**: <200ms for memory operations, <1s for checkpoint creation + +## Tool Coordination +- **write_memory/read_memory**: Core session context persistence and retrieval +- **think_about_collected_information**: Session analysis and discovery identification +- **summarize_changes**: Session summary generation and progress documentation +- **TodoRead**: Task completion tracking for automatic checkpoint triggers + +## Key Patterns +- **Session Preservation**: Discovery analysis → memory persistence → checkpoint creation +- **Cross-Session Learning**: Context accumulation → pattern archival → enhanced project understanding +- **Progress Tracking**: Task completion → automatic checkpoints → session continuity +- **Recovery Planning**: State preservation → checkpoint validation → restoration readiness + +## Examples + +### Basic Session Save +``` +/sc:save +# Saves current session discoveries and context to Serena MCP +# Automatically creates checkpoint if session exceeds 30 minutes +``` + +### Comprehensive Session Checkpoint +``` +/sc:save --type all --checkpoint +# Complete session preservation with recovery checkpoint +# Includes all learnings, context, and progress for session restoration +``` + +### Session Summary Generation +``` +/sc:save --summarize +# Creates session summary with discovery documentation +# Updates cross-session learning patterns and project insights +``` + +### Discovery-Only Persistence +``` +/sc:save --type learnings +# Saves only new patterns and insights discovered during session +# Updates project understanding without full session preservation +``` + +## Boundaries + +**Will:** +- Save session context using Serena MCP integration for cross-session persistence +- Create automatic checkpoints based on session progress and task completion +- Preserve discoveries and patterns for enhanced project understanding + +**Will Not:** +- Operate without proper Serena MCP integration and memory access +- Save session data without validation and integrity verification +- Override existing session context without proper checkpoint preservation \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/sc.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/sc.md new file mode 100644 index 0000000..fb7bb73 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/sc.md @@ -0,0 +1,130 @@ +--- +name: sc +description: SuperClaude command dispatcher - Use /sc [command] to access all SuperClaude features +--- + +# SuperClaude Command Dispatcher + +🚀 **SuperClaude Framework** - Main command dispatcher + +## Usage + +All SuperClaude commands use the `/sc:` prefix: + +``` +/sc:command [args...] +``` + +## Available Commands + +### Research & Analysis +``` +/sc:research [query] - Deep web research with parallel search +``` + +### Repository Management +``` +/sc:index-repo - Index repository for context optimization +``` + +### AI Agents +``` +/sc:agent [type] - Launch specialized AI agents +``` + +### Recommendations +``` +/sc:recommend [context] - Get command recommendations +``` + +### Help +``` +/sc - Show this help (all available commands) +``` + +## Command Namespace + +All commands are namespaced under `sc:` to keep them organized: +- ✅ `/sc:research query` +- ✅ `/sc:index-repo` +- ✅ `/sc:agent type` +- ✅ `/sc:recommend` +- ✅ `/sc` (help) + +## Examples + +### Research +``` +/sc:research React 18 new features +/sc:research LLM agent architectures 2024 +/sc:research Python async best practices +``` + +### Index Repository +``` +/sc:index-repo +``` + +### Agent +``` +/sc:agent deep-research +/sc:agent self-review +/sc:agent repo-index +``` + +### Recommendations +``` +/sc:recommend +``` + +## Quick Reference + +| Command | Description | Example | +|---------|-------------|---------| +| `/sc:research` | Deep web research | `/sc:research topic` | +| `/sc:index-repo` | Repository indexing | `/sc:index-repo` | +| `/sc:agent` | Specialized AI agents | `/sc:agent type` | +| `/sc:recommend` | Command suggestions | `/sc:recommend` | +| `/sc` | Show help | `/sc` | + +## Features + +- **Parallel Execution**: Research runs multiple searches in parallel +- **Evidence-Based**: All findings backed by sources +- **Context-Aware**: Uses repository context when available +- **Token Efficient**: Optimized for minimal token usage + +## Help + +For help on specific commands: +``` +/sc:research --help +/sc:agent --help +``` + +Or use the main help command: +``` +/sc +``` + +Check the documentation: +- PLANNING.md - Architecture and design +- TASK.md - Current tasks and priorities +- KNOWLEDGE.md - Tips and best practices + +## Version + +SuperClaude v4.1.7 +- Python package: 0.4.0 +- Pytest plugin included +- PM Agent patterns enabled + +--- + +💡 **Tip**: All commands use the `/sc:` prefix - e.g., `/sc:research`, `/sc:agent` + +🔧 **Installation**: Run `superclaude install` to install/update commands + +📚 **Documentation**: https://github.com/SuperClaude-Org/SuperClaude_Framework + +⚠️ **Important**: Restart Claude Code after installing commands to use them! diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/select-tool.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/select-tool.md new file mode 100644 index 0000000..a4bc6c1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/select-tool.md @@ -0,0 +1,87 @@ +--- +name: select-tool +description: "Intelligent MCP tool selection based on complexity scoring and operation analysis" +category: special +complexity: high +mcp-servers: [serena, morphllm] +personas: [] +--- + +# /sc:select-tool - Intelligent MCP Tool Selection + +## Triggers +- Operations requiring optimal MCP tool selection between Serena and Morphllm +- Meta-system decisions needing complexity analysis and capability matching +- Tool routing decisions requiring performance vs accuracy trade-offs +- Operations benefiting from intelligent tool capability assessment + +## Usage +``` +/sc:select-tool [operation] [--analyze] [--explain] +``` + +## Behavioral Flow +1. **Parse**: Analyze operation type, scope, file count, and complexity indicators +2. **Score**: Apply multi-dimensional complexity scoring across various operation factors +3. **Match**: Compare operation requirements against Serena and Morphllm capabilities +4. **Select**: Choose optimal tool based on scoring matrix and performance requirements +5. **Validate**: Verify selection accuracy and provide confidence metrics + +Key behaviors: +- Complexity scoring based on file count, operation type, language, and framework requirements +- Performance assessment evaluating speed vs accuracy trade-offs for optimal selection +- Decision logic matrix with direct mappings and threshold-based routing rules +- Tool capability matching for Serena (semantic operations) vs Morphllm (pattern operations) + +## MCP Integration +- **Serena MCP**: Optimal for semantic operations, LSP functionality, symbol navigation, and project context +- **Morphllm MCP**: Optimal for pattern-based edits, bulk transformations, and speed-critical operations +- **Decision Matrix**: Intelligent routing based on complexity scoring and operation characteristics + +## Tool Coordination +- **get_current_config**: System configuration analysis for tool capability assessment +- **execute_sketched_edit**: Operation testing and validation for selection accuracy +- **Read/Grep**: Operation context analysis and complexity factor identification +- **Integration**: Automatic selection logic used by refactor, edit, implement, and improve commands + +## Key Patterns +- **Direct Mapping**: Symbol operations → Serena, Pattern edits → Morphllm, Memory operations → Serena +- **Complexity Thresholds**: Score >0.6 → Serena, Score <0.4 → Morphllm, 0.4-0.6 → Feature-based +- **Performance Trade-offs**: Speed requirements → Morphllm, Accuracy requirements → Serena +- **Fallback Strategy**: Serena → Morphllm → Native tools degradation chain + +## Examples + +### Complex Refactoring Operation +``` +/sc:select-tool "rename function across 10 files" --analyze +# Analysis: High complexity (multi-file, symbol operations) +# Selection: Serena MCP (LSP capabilities, semantic understanding) +``` + +### Pattern-Based Bulk Edit +``` +/sc:select-tool "update console.log to logger.info across project" --explain +# Analysis: Pattern-based transformation, speed priority +# Selection: Morphllm MCP (pattern matching, bulk operations) +``` + +### Memory Management Operation +``` +/sc:select-tool "save project context and discoveries" +# Direct mapping: Memory operations → Serena MCP +# Rationale: Project context and cross-session persistence +``` + +## Boundaries + +**Will:** +- Analyze operations and provide optimal tool selection between Serena and Morphllm +- Apply complexity scoring based on file count, operation type, and requirements +- Provide sub-100ms decision time with >95% selection accuracy + +**Will Not:** +- Override explicit tool specifications when user has clear preference +- Select tools without proper complexity analysis and capability matching +- Compromise performance requirements for convenience or speed + diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/spawn.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/spawn.md new file mode 100644 index 0000000..0bd297d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/spawn.md @@ -0,0 +1,105 @@ +--- +name: spawn +description: "Meta-system task orchestration with intelligent breakdown and delegation" +category: special +complexity: high +mcp-servers: [] +personas: [] +--- + +# /sc:spawn - Meta-System Task Orchestration + +## Triggers +- Complex multi-domain operations requiring intelligent task breakdown +- Large-scale system operations spanning multiple technical areas +- Operations requiring parallel coordination and dependency management +- Meta-level orchestration beyond standard command capabilities + +## Usage +``` +/sc:spawn [complex-task] [--strategy sequential|parallel|adaptive] [--depth normal|deep] +``` + +## Behavioral Flow +1. **Analyze**: Parse complex operation requirements and assess scope across domains +2. **Decompose**: Break down operation into coordinated subtask hierarchies +3. **Orchestrate**: Execute tasks using optimal coordination strategy (parallel/sequential) +4. **Monitor**: Track progress across task hierarchies with dependency management +5. **Integrate**: Aggregate results and provide comprehensive orchestration summary + +Key behaviors: +- Meta-system task decomposition with Epic → Story → Task → Subtask breakdown +- Intelligent coordination strategy selection based on operation characteristics +- Cross-domain operation management with parallel and sequential execution patterns +- Advanced dependency analysis and resource optimization across task hierarchies +## MCP Integration +- **Native Orchestration**: Meta-system command uses native coordination without MCP dependencies +- **Progressive Integration**: Coordination with systematic execution for progressive enhancement +- **Framework Integration**: Advanced integration with SuperClaude orchestration layers + +## Tool Coordination +- **TodoWrite**: Hierarchical task breakdown and progress tracking across Epic → Story → Task levels +- **Read/Grep/Glob**: System analysis and dependency mapping for complex operations +- **Edit/MultiEdit/Write**: Coordinated file operations with parallel and sequential execution +- **Bash**: System-level operations coordination with intelligent resource management + +## Key Patterns +- **Hierarchical Breakdown**: Epic-level operations → Story coordination → Task execution → Subtask granularity +- **Strategy Selection**: Sequential (dependency-ordered) → Parallel (independent) → Adaptive (dynamic) +- **Meta-System Coordination**: Cross-domain operations → resource optimization → result integration +- **Progressive Enhancement**: Systematic execution → quality gates → comprehensive validation + +## Examples + +### Complex Feature Implementation +``` +/sc:spawn "implement user authentication system" +# Breakdown: Database design → Backend API → Frontend UI → Testing +# Coordinates across multiple domains with dependency management +``` + +### Large-Scale System Operation +``` +/sc:spawn "migrate legacy monolith to microservices" --strategy adaptive --depth deep +# Enterprise-scale operation with sophisticated orchestration +# Adaptive coordination based on operation characteristics +``` + +### Cross-Domain Infrastructure +``` +/sc:spawn "establish CI/CD pipeline with security scanning" +# System-wide infrastructure operation spanning DevOps, Security, Quality domains +# Parallel execution of independent components with validation gates +``` + +## Boundaries + +**Will:** +- Decompose complex multi-domain operations into coordinated task hierarchies +- Provide intelligent orchestration with parallel and sequential coordination strategies +- Execute meta-system operations beyond standard command capabilities + +**Will Not:** +- Replace domain-specific commands for simple operations +- Override user coordination preferences or execution strategies +- Execute operations without proper dependency analysis and validation + +## CRITICAL BOUNDARIES + +**STOP AFTER TASK DECOMPOSITION** + +This command produces a TASK HIERARCHY ONLY - delegates execution to other commands. + +**Explicitly Will NOT**: +- Execute implementation tasks directly +- Write or modify code +- Create system changes +- Replace domain-specific commands + +**Output**: Task breakdown document with: +- Epic decomposition +- Task hierarchy with dependencies +- Delegation assignments (which `/sc:*` command handles each task) +- Coordination strategy + +**Next Step**: Execute individual tasks using delegated commands (`/sc:implement`, `/sc:design`, `/sc:test`, etc.) \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/spec-panel.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/spec-panel.md new file mode 100644 index 0000000..72b2ad7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/spec-panel.md @@ -0,0 +1,436 @@ +--- +name: spec-panel +description: "Multi-expert specification review and improvement using renowned specification and software engineering experts" +category: analysis +complexity: enhanced +mcp-servers: [sequential, context7] +personas: [technical-writer, system-architect, quality-engineer] +--- + +# /sc:spec-panel - Expert Specification Review Panel + +## Triggers +- Specification quality review and improvement requests +- Technical documentation validation and enhancement needs +- Requirements analysis and completeness verification +- Professional specification writing guidance and mentoring + +## Usage +``` +/sc:spec-panel [specification_content|@file] [--mode discussion|critique|socratic] [--experts "name1,name2"] [--focus requirements|architecture|testing|compliance] [--iterations N] [--format standard|structured|detailed] +``` + +## Behavioral Flow +1. **Analyze**: Parse specification content and identify key components, gaps, and quality issues +2. **Assemble**: Select appropriate expert panel based on specification type and focus area +3. **Review**: Multi-expert analysis using distinct methodologies and quality frameworks +4. **Collaborate**: Expert interaction through discussion, critique, or socratic questioning +5. **Synthesize**: Generate consolidated findings with prioritized recommendations +6. **Improve**: Create enhanced specification incorporating expert feedback and best practices + +Key behaviors: +- Multi-expert perspective analysis with distinct methodologies and quality frameworks +- Intelligent expert selection based on specification domain and focus requirements +- Structured review process with evidence-based recommendations and improvement guidance +- Iterative improvement cycles with quality validation and progress tracking + +## Expert Panel System + +### Core Specification Experts + +**Karl Wiegers** - Requirements Engineering Pioneer +- **Domain**: Functional/non-functional requirements, requirement quality frameworks +- **Methodology**: SMART criteria, testability analysis, stakeholder validation +- **Critique Focus**: "This requirement lacks measurable acceptance criteria. How would you validate compliance in production?" + +**Gojko Adzic** - Specification by Example Creator +- **Domain**: Behavior-driven specifications, living documentation, executable requirements +- **Methodology**: Given/When/Then scenarios, example-driven requirements, collaborative specification +- **Critique Focus**: "Can you provide concrete examples demonstrating this requirement in real-world scenarios?" + +**Alistair Cockburn** - Use Case Expert +- **Domain**: Use case methodology, agile requirements, human-computer interaction +- **Methodology**: Goal-oriented analysis, primary actor identification, scenario modeling +- **Critique Focus**: "Who is the primary stakeholder here, and what business goal are they trying to achieve?" + +**Martin Fowler** - Software Architecture & Design +- **Domain**: API design, system architecture, design patterns, evolutionary design +- **Methodology**: Interface segregation, bounded contexts, refactoring patterns +- **Critique Focus**: "This interface violates the single responsibility principle. Consider separating concerns." + +### Technical Architecture Experts + +**Michael Nygard** - Release It! Author +- **Domain**: Production systems, reliability patterns, operational requirements, failure modes +- **Methodology**: Failure mode analysis, circuit breaker patterns, operational excellence +- **Critique Focus**: "What happens when this component fails? Where are the monitoring and recovery mechanisms?" + +**Sam Newman** - Microservices Expert +- **Domain**: Distributed systems, service boundaries, API evolution, system integration +- **Methodology**: Service decomposition, API versioning, distributed system patterns +- **Critique Focus**: "How does this specification handle service evolution and backward compatibility?" + +**Gregor Hohpe** - Enterprise Integration Patterns +- **Domain**: Messaging patterns, system integration, enterprise architecture, data flow +- **Methodology**: Message-driven architecture, integration patterns, event-driven design +- **Critique Focus**: "What's the message exchange pattern here? How do you handle ordering and delivery guarantees?" + +### Quality & Testing Experts + +**Lisa Crispin** - Agile Testing Expert +- **Domain**: Testing strategies, quality requirements, acceptance criteria, test automation +- **Methodology**: Whole-team testing, risk-based testing, quality attribute specification +- **Critique Focus**: "How would the testing team validate this requirement? What are the edge cases and failure scenarios?" + +**Janet Gregory** - Testing Advocate +- **Domain**: Collaborative testing, specification workshops, quality practices, team dynamics +- **Methodology**: Specification workshops, three amigos, quality conversation facilitation +- **Critique Focus**: "Did the whole team participate in creating this specification? Are quality expectations clearly defined?" + +### Modern Software Experts + +**Kelsey Hightower** - Cloud Native Expert +- **Domain**: Kubernetes, cloud architecture, operational excellence, infrastructure as code +- **Methodology**: Cloud-native patterns, infrastructure automation, operational observability +- **Critique Focus**: "How does this specification handle cloud-native deployment and operational concerns?" + +## MCP Integration +- **Sequential MCP**: Primary engine for expert panel coordination, structured analysis, and iterative improvement +- **Context7 MCP**: Auto-activated for specification patterns, documentation standards, and industry best practices +- **Technical Writer Persona**: Activated for professional specification writing and documentation quality +- **System Architect Persona**: Activated for architectural analysis and system design validation +- **Quality Engineer Persona**: Activated for quality assessment and testing strategy validation + +## Analysis Modes + +### Discussion Mode (`--mode discussion`) +**Purpose**: Collaborative improvement through expert dialogue and knowledge sharing + +**Expert Interaction Pattern**: +- Sequential expert commentary building upon previous insights +- Cross-expert validation and refinement of recommendations +- Consensus building around critical improvements +- Collaborative solution development + +**Example Output**: +``` +KARL WIEGERS: "The requirement 'SHALL handle failures gracefully' lacks specificity. +What constitutes graceful handling? What types of failures are we addressing?" + +MICHAEL NYGARD: "Building on Karl's point, we need specific failure modes: network +timeouts, service unavailable, rate limiting. Each requires different handling strategies." + +GOJKO ADZIC: "Let's make this concrete with examples: + Given: Service timeout after 30 seconds + When: Circuit breaker activates + Then: Return cached response within 100ms" + +MARTIN FOWLER: "The specification should also define the failure notification interface. +How do upstream services know what type of failure occurred?" +``` + +### Critique Mode (`--mode critique`) +**Purpose**: Systematic review with specific improvement suggestions and priority rankings + +**Analysis Structure**: +- Issue identification with severity classification +- Specific improvement recommendations with rationale +- Priority ranking based on impact and effort +- Quality metrics and validation criteria + +**Example Output**: +``` +=== REQUIREMENTS ANALYSIS === + +KARL WIEGERS - Requirements Quality Assessment: +❌ CRITICAL: Requirement R-001 lacks measurable acceptance criteria +📝 RECOMMENDATION: Replace "handle failures gracefully" with "open circuit breaker after 5 consecutive failures within 30 seconds" +🎯 PRIORITY: High - Affects testability and validation +📊 QUALITY IMPACT: +40% testability, +60% clarity + +GOJKO ADZIC - Specification Testability: +⚠️ MAJOR: No executable examples provided for complex behaviors +📝 RECOMMENDATION: Add Given/When/Then scenarios for each requirement +🎯 PRIORITY: Medium - Improves understanding and validation +📊 QUALITY IMPACT: +50% comprehensibility, +35% validation coverage + +=== ARCHITECTURE ANALYSIS === + +MARTIN FOWLER - Interface Design: +⚠️ MINOR: CircuitBreaker interface couples state management with execution logic +📝 RECOMMENDATION: Separate CircuitBreakerState from CircuitBreakerExecutor +🎯 PRIORITY: Low - Design improvement, not functional issue +📊 QUALITY IMPACT: +20% maintainability, +15% testability +``` + +### Socratic Mode (`--mode socratic`) +**Purpose**: Learning-focused questioning to deepen understanding and improve thinking + +**Question Categories**: +- Foundational understanding questions +- Stakeholder and purpose clarification +- Assumption identification and validation +- Alternative approach exploration + +**Example Output**: +``` +ALISTAIR COCKBURN: "What is the fundamental problem this specification is trying to solve?" + +KARL WIEGERS: "Who are the primary stakeholders affected by these requirements?" + +MICHAEL NYGARD: "What assumptions are you making about the deployment environment and operational context?" + +GOJKO ADZIC: "How would you explain these requirements to a non-technical business stakeholder?" + +MARTIN FOWLER: "What would happen if we removed this requirement entirely? What breaks?" + +LISA CRISPIN: "How would you validate that this specification is working correctly in production?" + +KELSEY HIGHTOWER: "What operational and monitoring capabilities does this specification require?" +``` + +## Focus Areas + +### Requirements Focus (`--focus requirements`) +**Expert Panel**: Wiegers (lead), Adzic, Cockburn +**Analysis Areas**: +- Requirement clarity, completeness, and consistency +- Testability and measurability assessment +- Stakeholder needs alignment and validation +- Acceptance criteria quality and coverage +- Requirements traceability and verification + +### Architecture Focus (`--focus architecture`) +**Expert Panel**: Fowler (lead), Newman, Hohpe, Nygard +**Analysis Areas**: +- Interface design quality and consistency +- System boundary definitions and service decomposition +- Scalability and maintainability characteristics +- Design pattern appropriateness and implementation +- Integration and communication specifications + +### Testing Focus (`--focus testing`) +**Expert Panel**: Crispin (lead), Gregory, Adzic +**Analysis Areas**: +- Test strategy and coverage requirements +- Quality attribute specifications and validation +- Edge case identification and handling +- Acceptance criteria and definition of done +- Test automation and continuous validation + +### Compliance Focus (`--focus compliance`) +**Expert Panel**: Wiegers (lead), Nygard, Hightower +**Analysis Areas**: +- Regulatory requirement coverage and validation +- Security specifications and threat modeling +- Operational requirements and observability +- Audit trail and compliance verification +- Risk assessment and mitigation strategies + +## Tool Coordination +- **Read**: Specification content analysis and parsing +- **Sequential**: Expert panel coordination and iterative analysis +- **Context7**: Specification patterns and industry best practices +- **Grep**: Cross-reference validation and consistency checking +- **Write**: Improved specification generation and report creation +- **MultiEdit**: Collaborative specification enhancement and refinement + +## Iterative Improvement Process + +### Single Iteration (Default) +1. **Initial Analysis**: Expert panel reviews specification +2. **Issue Identification**: Systematic problem and gap identification +3. **Improvement Recommendations**: Specific, actionable enhancement suggestions +4. **Priority Ranking**: Critical path and impact-based prioritization + +### Multi-Iteration (`--iterations N`) +**Iteration 1**: Structural and fundamental issues +- Requirements clarity and completeness +- Architecture consistency and boundaries +- Major gaps and critical problems + +**Iteration 2**: Detail refinement and enhancement +- Specific improvement implementation +- Edge case handling and error scenarios +- Quality attribute specifications + +**Iteration 3**: Polish and optimization +- Documentation quality and clarity +- Example and scenario enhancement +- Final validation and consistency checks + +## Output Formats + +### Standard Format (`--format standard`) +```yaml +specification_review: + original_spec: "authentication_service.spec.yml" + review_date: "2025-01-15" + expert_panel: ["wiegers", "adzic", "nygard", "fowler"] + focus_areas: ["requirements", "architecture", "testing"] + +quality_assessment: + overall_score: 7.2/10 + requirements_quality: 8.1/10 + architecture_clarity: 6.8/10 + testability_score: 7.5/10 + +critical_issues: + - category: "requirements" + severity: "high" + expert: "wiegers" + issue: "Authentication timeout not specified" + recommendation: "Define session timeout with configurable values" + + - category: "architecture" + severity: "medium" + expert: "fowler" + issue: "Token refresh mechanism unclear" + recommendation: "Specify refresh token lifecycle and rotation policy" + +expert_consensus: + - "Specification needs concrete failure handling definitions" + - "Missing operational monitoring and alerting requirements" + - "Authentication flow is well-defined but lacks error scenarios" + +improvement_roadmap: + immediate: ["Define timeout specifications", "Add error handling scenarios"] + short_term: ["Specify monitoring requirements", "Add performance criteria"] + long_term: ["Comprehensive security review", "Integration testing strategy"] +``` + +### Structured Format (`--format structured`) +Token-efficient format using SuperClaude symbol system for concise communication. + +### Detailed Format (`--format detailed`) +Comprehensive analysis with full expert commentary, examples, and implementation guidance. + +## Examples + +### API Specification Review +``` +/sc:spec-panel @auth_api.spec.yml --mode critique --focus requirements,architecture +# Comprehensive API specification review +# Focus on requirements quality and architectural consistency +# Generate detailed improvement recommendations +``` + +### Requirements Workshop +``` +/sc:spec-panel "user story content" --mode discussion --experts "wiegers,adzic,cockburn" +# Collaborative requirements analysis and improvement +# Expert dialogue for requirement refinement +# Consensus building around acceptance criteria +``` + +### Architecture Validation +``` +/sc:spec-panel @microservice.spec.yml --mode socratic --focus architecture +# Learning-focused architectural review +# Deep questioning about design decisions +# Alternative approach exploration +``` + +### Iterative Improvement +``` +/sc:spec-panel @complex_system.spec.yml --iterations 3 --format detailed +# Multi-iteration improvement process +# Progressive refinement with expert guidance +# Comprehensive quality enhancement +``` + +### Compliance Review +``` +/sc:spec-panel @security_requirements.yml --focus compliance --experts "wiegers,nygard" +# Compliance and security specification review +# Regulatory requirement validation +# Risk assessment and mitigation planning +``` + +## Integration Patterns + +### Workflow Integration with /sc:code-to-spec +```bash +# Generate initial specification from code +/sc:code-to-spec ./authentication_service --type api --format yaml + +# Review and improve with expert panel +/sc:spec-panel @generated_auth_spec.yml --mode critique --focus requirements,testing + +# Iterative refinement based on feedback +/sc:spec-panel @improved_auth_spec.yml --mode discussion --iterations 2 +``` + +### Learning and Development Workflow +```bash +# Start with socratic mode for learning +/sc:spec-panel @my_first_spec.yml --mode socratic --iterations 2 + +# Apply learnings with discussion mode +/sc:spec-panel @revised_spec.yml --mode discussion --focus requirements + +# Final quality validation with critique mode +/sc:spec-panel @final_spec.yml --mode critique --format detailed +``` + +## Quality Assurance Features + +### Expert Validation +- Cross-expert consistency checking and validation +- Methodology alignment and best practice verification +- Quality metric calculation and progress tracking +- Recommendation prioritization and impact assessment + +### Specification Quality Metrics +- **Clarity Score**: Language precision and understandability (0-10) +- **Completeness Score**: Coverage of essential specification elements (0-10) +- **Testability Score**: Measurability and validation capability (0-10) +- **Consistency Score**: Internal coherence and contradiction detection (0-10) + +### Continuous Improvement +- Pattern recognition from successful improvements +- Expert recommendation effectiveness tracking +- Specification quality trend analysis +- Best practice pattern library development + +## Advanced Features + +### Custom Expert Panels +- Domain-specific expert selection and configuration +- Industry-specific methodology application +- Custom quality criteria and assessment frameworks +- Specialized review processes for unique requirements + +### Integration with Development Workflow +- CI/CD pipeline integration for specification validation +- Version control integration for specification evolution tracking +- IDE integration for inline specification quality feedback +- Automated quality gate enforcement and validation + +### Learning and Mentoring +- Progressive skill development tracking and guidance +- Specification writing pattern recognition and teaching +- Best practice library development and sharing +- Mentoring mode with educational focus and guidance + +## Boundaries + +**Will:** +- Provide expert-level specification review and improvement guidance +- Generate specific, actionable recommendations with priority rankings +- Support multiple analysis modes for different use cases and learning objectives +- Integrate with specification generation tools for comprehensive workflow support + +**Will Not:** +- Replace human judgment and domain expertise in critical decisions +- Modify specifications without explicit user consent and validation +- Generate specifications from scratch without existing content or context +- Provide legal or regulatory compliance guarantees beyond analysis guidance + +**Output**: Expert review document containing: +- Multi-expert analysis (10 simulated experts) +- Specific, actionable recommendations +- Consensus points and disagreements +- Priority-ranked improvements + +**Next Step**: After review, incorporate feedback into spec, then use `/sc:design` for architecture or `/sc:implement` for coding. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/task.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/task.md new file mode 100644 index 0000000..bee103a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/task.md @@ -0,0 +1,116 @@ +--- +name: task +description: "Execute complex tasks with intelligent workflow management and delegation" +category: special +complexity: advanced +mcp-servers: [sequential, context7, magic, playwright, morphllm, serena] +personas: [architect, analyzer, frontend, backend, security, devops, project-manager] +--- + +# /sc:task - Enhanced Task Management + +## Triggers +- Complex tasks requiring multi-agent coordination and delegation +- Projects needing structured workflow management and cross-session persistence +- Operations requiring intelligent MCP server routing and domain expertise +- Tasks benefiting from systematic execution and progressive enhancement + +## Usage +``` +/sc:task [action] [target] [--strategy systematic|agile|enterprise] [--parallel] [--delegate] +``` + +## Behavioral Flow +1. **Analyze**: Parse task requirements and determine optimal execution strategy +2. **Delegate**: Route to appropriate MCP servers and activate relevant personas +3. **Coordinate**: Execute tasks with intelligent workflow management and parallel processing +4. **Validate**: Apply quality gates and comprehensive task completion verification +5. **Optimize**: Analyze performance and provide enhancement recommendations + +Key behaviors: +- Multi-persona coordination across architect, frontend, backend, security, devops domains +- Intelligent MCP server routing (Sequential, Context7, Magic, Playwright, Morphllm, Serena) +- Systematic execution with progressive task enhancement and cross-session persistence +- Advanced task delegation with hierarchical breakdown and dependency management + +## MCP Integration +- **Sequential MCP**: Complex multi-step task analysis and systematic execution planning +- **Context7 MCP**: Framework-specific patterns and implementation best practices +- **Magic MCP**: UI/UX task coordination and design system integration +- **Playwright MCP**: Testing workflow integration and validation automation +- **Morphllm MCP**: Large-scale task transformation and pattern-based optimization +- **Serena MCP**: Cross-session task persistence and project memory management + +## Tool Coordination +- **TodoWrite**: Hierarchical task breakdown and progress tracking across Epic → Story → Task levels +- **Task**: Advanced delegation for complex multi-agent coordination and sub-task management +- **Read/Write/Edit**: Task documentation and implementation coordination +- **sequentialthinking**: Structured reasoning for complex task dependency analysis + +## Key Patterns +- **Task Hierarchy**: Epic-level objectives → Story coordination → Task execution → Subtask granularity +- **Strategy Selection**: Systematic (comprehensive) → Agile (iterative) → Enterprise (governance) +- **Multi-Agent Coordination**: Persona activation → MCP routing → parallel execution → result integration +- **Cross-Session Management**: Task persistence → context continuity → progressive enhancement + +## Examples + +### Complex Feature Development +``` +/sc:task create "enterprise authentication system" --strategy systematic --parallel +# Comprehensive task breakdown with multi-domain coordination +# Activates architect, security, backend, frontend personas +``` + +### Agile Sprint Coordination +``` +/sc:task execute "feature backlog" --strategy agile --delegate +# Iterative task execution with intelligent delegation +# Cross-session persistence for sprint continuity +``` + +### Multi-Domain Integration +``` +/sc:task execute "microservices platform" --strategy enterprise --parallel +# Enterprise-scale coordination with compliance validation +# Parallel execution across multiple technical domains +``` + +## Boundaries + +**Will:** +- Execute complex tasks with multi-agent coordination and intelligent delegation +- Provide hierarchical task breakdown with cross-session persistence +- Coordinate multiple MCP servers and personas for optimal task outcomes + +**Will Not:** +- Execute simple tasks that don't require advanced orchestration +- Compromise quality standards for speed or convenience +- Operate without proper validation and quality gates + +## CRITICAL BOUNDARIES + +**USER-INVOKED DISCRETE TASK EXECUTION** + +This command executes specific tasks when explicitly invoked by user. + +**Difference from /sc:pm**: +- `/sc:pm` = session-level orchestration (background monitoring, continuous) +- `/sc:task` = user-invoked discrete execution (explicit start/end) + +**Behavior**: +- User invokes `/sc:task [description]` +- Execute the specific task using multi-agent coordination +- **STOP when task is complete** - do not continue to next tasks without user input + +**Completion Criteria**: +- Task objective achieved +- All sub-tasks marked completed in TodoWrite +- Validation passed + +**Output**: Task completion report with: +- What was accomplished +- Files modified +- Tests status (if applicable) + +**Next Step**: User decides next action. May invoke another `/sc:task` or use specific commands. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/test.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/test.md new file mode 100644 index 0000000..d39f2c7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/test.md @@ -0,0 +1,93 @@ +--- +name: test +description: "Execute tests with coverage analysis and automated quality reporting" +category: utility +complexity: enhanced +mcp-servers: [playwright] +personas: [qa-specialist] +--- + +# /sc:test - Testing and Quality Assurance + +## Triggers +- Test execution requests for unit, integration, or e2e tests +- Coverage analysis and quality gate validation needs +- Continuous testing and watch mode scenarios +- Test failure analysis and debugging requirements + +## Usage +``` +/sc:test [target] [--type unit|integration|e2e|all] [--coverage] [--watch] [--fix] +``` + +## Behavioral Flow +1. **Discover**: Categorize available tests using runner patterns and conventions +2. **Configure**: Set up appropriate test environment and execution parameters +3. **Execute**: Run tests with monitoring and real-time progress tracking +4. **Analyze**: Generate coverage reports and failure diagnostics +5. **Report**: Provide actionable recommendations and quality metrics + +Key behaviors: +- Auto-detect test framework and configuration +- Generate comprehensive coverage reports with metrics +- Activate Playwright MCP for e2e browser testing +- Provide intelligent test failure analysis +- Support continuous watch mode for development + +## MCP Integration +- **Playwright MCP**: Auto-activated for `--type e2e` browser testing +- **QA Specialist Persona**: Activated for test analysis and quality assessment +- **Enhanced Capabilities**: Cross-browser testing, visual validation, performance metrics + +## Tool Coordination +- **Bash**: Test runner execution and environment management +- **Glob**: Test discovery and file pattern matching +- **Grep**: Result parsing and failure analysis +- **Write**: Coverage reports and test summaries + +## Key Patterns +- **Test Discovery**: Pattern-based categorization → appropriate runner selection +- **Coverage Analysis**: Execution metrics → comprehensive coverage reporting +- **E2E Testing**: Browser automation → cross-platform validation +- **Watch Mode**: File monitoring → continuous test execution + +## Examples + +### Basic Test Execution +``` +/sc:test +# Discovers and runs all tests with standard configuration +# Generates pass/fail summary and basic coverage +``` + +### Targeted Coverage Analysis +``` +/sc:test src/components --type unit --coverage +# Unit tests for specific directory with detailed coverage metrics +``` + +### Browser Testing +``` +/sc:test --type e2e +# Activates Playwright MCP for comprehensive browser testing +# Cross-browser compatibility and visual validation +``` + +### Development Watch Mode +``` +/sc:test --watch --fix +# Continuous testing with automatic simple failure fixes +# Real-time feedback during development +``` + +## Boundaries + +**Will:** +- Execute existing test suites using project's configured test runner +- Generate coverage reports and quality metrics +- Provide intelligent test failure analysis with actionable recommendations + +**Will Not:** +- Generate test cases or modify test framework configuration +- Execute tests requiring external services without proper setup +- Make destructive changes to test files without explicit permission \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/troubleshoot.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/troubleshoot.md new file mode 100644 index 0000000..e496fc8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/troubleshoot.md @@ -0,0 +1,120 @@ +--- +name: troubleshoot +description: "Diagnose and resolve issues in code, builds, deployments, and system behavior" +category: utility +complexity: basic +mcp-servers: [] +personas: [] +--- + +# /sc:troubleshoot - Issue Diagnosis and Resolution + +## Triggers +- Code defects and runtime error investigation requests +- Build failure analysis and resolution needs +- Performance issue diagnosis and optimization requirements +- Deployment problem analysis and system behavior debugging + +## Usage +``` +/sc:troubleshoot [issue] [--type bug|build|performance|deployment] [--trace] [--fix] +``` + +## Behavioral Flow +1. **Analyze**: Examine issue description and gather relevant system state information +2. **Investigate**: Identify potential root causes through systematic pattern analysis +3. **Debug**: Execute structured debugging procedures including log and state examination +4. **Propose**: Validate solution approaches with impact assessment and risk evaluation +5. **Resolve**: Apply appropriate fixes and verify resolution effectiveness + +Key behaviors: +- Systematic root cause analysis with hypothesis testing and evidence collection +- Multi-domain troubleshooting (code, build, performance, deployment) +- Structured debugging methodologies with comprehensive problem analysis +- Safe fix application with verification and documentation + +## Tool Coordination +- **Read**: Log analysis and system state examination +- **Bash**: Diagnostic command execution and system investigation +- **Grep**: Error pattern detection and log analysis +- **Write**: Diagnostic reports and resolution documentation + +## Key Patterns +- **Bug Investigation**: Error analysis → stack trace examination → code inspection → fix validation +- **Build Troubleshooting**: Build log analysis → dependency checking → configuration validation +- **Performance Diagnosis**: Metrics analysis → bottleneck identification → optimization recommendations +- **Deployment Issues**: Environment analysis → configuration verification → service validation + +## Examples + +### Code Bug Investigation +``` +/sc:troubleshoot "Null pointer exception in user service" --type bug --trace +# Systematic analysis of error context and stack traces +# Identifies root cause and provides targeted fix recommendations +``` + +### Build Failure Analysis +``` +/sc:troubleshoot "TypeScript compilation errors" --type build --fix +# Analyzes build logs and TypeScript configuration +# Automatically applies safe fixes for common compilation issues +``` + +### Performance Issue Diagnosis +``` +/sc:troubleshoot "API response times degraded" --type performance +# Performance metrics analysis and bottleneck identification +# Provides optimization recommendations and monitoring guidance +``` + +### Deployment Problem Resolution +``` +/sc:troubleshoot "Service not starting in production" --type deployment --trace +# Environment and configuration analysis +# Systematic verification of deployment requirements and dependencies +``` + +## Boundaries + +**Will:** +- Execute systematic issue diagnosis using structured debugging methodologies +- Provide validated solution approaches with comprehensive problem analysis +- Apply safe fixes with verification and detailed resolution documentation + +**Will Not:** +- Apply risky fixes without proper analysis and user confirmation +- Modify production systems without explicit permission and safety validation +- Make architectural changes without understanding full system impact + +## CRITICAL BOUNDARIES + +**DIAGNOSE FIRST - FIXES REQUIRE `--fix` FLAG** + +This command is DIAGNOSIS-FIRST by default. + +**Default behavior (no `--fix` flag)**: +- Diagnose the issue +- Identify root cause +- Propose solution options +- **STOP and present findings to user** - do not apply any fixes + +**With `--fix` flag**: +- After diagnosis, prompt user for confirmation before applying +- Apply fix only after user explicitly approves +- Verify fix with tests + +**Explicitly Will NOT** (without `--fix` flag): +- Apply any code changes +- Modify any files +- Execute fixes automatically + +**Output**: Diagnostic report containing: +- Issue description +- Root cause analysis +- Proposed solutions (ranked) +- Risk assessment for each solution + +**Next Step**: User reviews diagnosis, then either: +- Re-run with `--fix` flag to apply recommended fix +- Use `/sc:improve` for broader refactoring \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/sc/workflow.md b/文档润色流和知识库构建流/claude-scholar/commands/sc/workflow.md new file mode 100644 index 0000000..c868077 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/sc/workflow.md @@ -0,0 +1,118 @@ +--- +name: workflow +description: "Generate structured implementation workflows from PRDs and feature requirements" +category: orchestration +complexity: advanced +mcp-servers: [sequential, context7, magic, playwright, morphllm, serena] +personas: [architect, analyzer, frontend, backend, security, devops, project-manager] +--- + +# /sc:workflow - Implementation Workflow Generator + +## Triggers +- PRD and feature specification analysis for implementation planning +- Structured workflow generation for development projects +- Multi-persona coordination for complex implementation strategies +- Cross-session workflow management and dependency mapping + +## Usage +``` +/sc:workflow [prd-file|feature-description] [--strategy systematic|agile|enterprise] [--depth shallow|normal|deep] [--parallel] +``` + +## Behavioral Flow +1. **Analyze**: Parse PRD and feature specifications to understand implementation requirements +2. **Plan**: Generate comprehensive workflow structure with dependency mapping and task orchestration +3. **Coordinate**: Activate multiple personas for domain expertise and implementation strategy +4. **Execute**: Create structured step-by-step workflows with automated task coordination +5. **Validate**: Apply quality gates and ensure workflow completeness across domains + +Key behaviors: +- Multi-persona orchestration across architecture, frontend, backend, security, and devops domains +- Advanced MCP coordination with intelligent routing for specialized workflow analysis +- Systematic execution with progressive workflow enhancement and parallel processing +- Cross-session workflow management with comprehensive dependency tracking + +## MCP Integration +- **Sequential MCP**: Complex multi-step workflow analysis and systematic implementation planning +- **Context7 MCP**: Framework-specific workflow patterns and implementation best practices +- **Magic MCP**: UI/UX workflow generation and design system integration strategies +- **Playwright MCP**: Testing workflow integration and quality assurance automation +- **Morphllm MCP**: Large-scale workflow transformation and pattern-based optimization +- **Serena MCP**: Cross-session workflow persistence, memory management, and project context + +## Tool Coordination +- **Read/Write/Edit**: PRD analysis and workflow documentation generation +- **TodoWrite**: Progress tracking for complex multi-phase workflow execution +- **Task**: Advanced delegation for parallel workflow generation and multi-agent coordination +- **WebSearch**: Technology research, framework validation, and implementation strategy analysis +- **sequentialthinking**: Structured reasoning for complex workflow dependency analysis + +## Key Patterns +- **PRD Analysis**: Document parsing → requirement extraction → implementation strategy development +- **Workflow Generation**: Task decomposition → dependency mapping → structured implementation planning +- **Multi-Domain Coordination**: Cross-functional expertise → comprehensive implementation strategies +- **Quality Integration**: Workflow validation → testing strategies → deployment planning + +## Examples + +### Systematic PRD Workflow +``` +/sc:workflow Claudedocs/PRD/feature-spec.md --strategy systematic --depth deep +# Comprehensive PRD analysis with systematic workflow generation +# Multi-persona coordination for complete implementation strategy +``` + +### Agile Feature Workflow +``` +/sc:workflow "user authentication system" --strategy agile --parallel +# Agile workflow generation with parallel task coordination +# Context7 and Magic MCP for framework and UI workflow patterns +``` + +### Enterprise Implementation Planning +``` +/sc:workflow enterprise-prd.md --strategy enterprise --validate +# Enterprise-scale workflow with comprehensive validation +# Security, devops, and architect personas for compliance and scalability +``` + +### Cross-Session Workflow Management +``` +/sc:workflow project-brief.md --depth normal +# Serena MCP manages cross-session workflow context and persistence +# Progressive workflow enhancement with memory-driven insights +``` + +## Boundaries + +**Will:** +- Generate comprehensive implementation workflows from PRD and feature specifications +- Coordinate multiple personas and MCP servers for complete implementation strategies +- Provide cross-session workflow management and progressive enhancement capabilities + +**Will Not:** +- Execute actual implementation tasks beyond workflow planning and strategy +- Override established development processes without proper analysis and validation +- Generate workflows without comprehensive requirement analysis and dependency mapping + +## CRITICAL BOUNDARIES + +**STOP AFTER PLAN CREATION** + +This command produces an IMPLEMENTATION PLAN ONLY - no code execution. + +**Explicitly Will NOT**: +- Execute any implementation tasks +- Write or modify code +- Create files (except the workflow plan document) +- Make architectural changes +- Run builds or tests + +**Output**: Workflow plan document (`claudedocs/workflow_*.md`) containing: +- Implementation phases +- Task dependencies +- Execution order +- Checkpoints and validation steps + +**Next Step**: After workflow completes, use `/sc:implement` to execute the plan step by step. \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/commands/setup-pm.md b/文档润色流和知识库构建流/claude-scholar/commands/setup-pm.md new file mode 100644 index 0000000..87224b9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/setup-pm.md @@ -0,0 +1,80 @@ +--- +description: Configure your preferred package manager (npm/pnpm/yarn/bun) +disable-model-invocation: true +--- + +# Package Manager Setup + +Configure your preferred package manager for this project or globally. + +## Usage + +```bash +# Detect current package manager +node scripts/setup-package-manager.js --detect + +# Set global preference +node scripts/setup-package-manager.js --global pnpm + +# Set project preference +node scripts/setup-package-manager.js --project bun + +# List available package managers +node scripts/setup-package-manager.js --list +``` + +## Detection Priority + +When determining which package manager to use, the following order is checked: + +1. **Environment variable**: `CLAUDE_PACKAGE_MANAGER` +2. **Project config**: `.claude/package-manager.json` +3. **package.json**: `packageManager` field +4. **Lock file**: Presence of package-lock.json, yarn.lock, pnpm-lock.yaml, or bun.lockb +5. **Global config**: `~/.claude/package-manager.json` +6. **Fallback**: First available package manager (pnpm > bun > yarn > npm) + +## Configuration Files + +### Global Configuration +```json +// ~/.claude/package-manager.json +{ + "packageManager": "pnpm" +} +``` + +### Project Configuration +```json +// .claude/package-manager.json +{ + "packageManager": "bun" +} +``` + +### package.json +```json +{ + "packageManager": "pnpm@8.6.0" +} +``` + +## Environment Variable + +Set `CLAUDE_PACKAGE_MANAGER` to override all other detection methods: + +```bash +# Windows (PowerShell) +$env:CLAUDE_PACKAGE_MANAGER = "pnpm" + +# macOS/Linux +export CLAUDE_PACKAGE_MANAGER=pnpm +``` + +## Run the Detection + +To see current package manager detection results, run: + +```bash +node scripts/setup-package-manager.js --detect +``` diff --git a/文档润色流和知识库构建流/claude-scholar/commands/tdd.md b/文档润色流和知识库构建流/claude-scholar/commands/tdd.md new file mode 100644 index 0000000..e821dae --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/tdd.md @@ -0,0 +1,324 @@ +--- +description: Enforce test-driven development workflow. Scaffold interfaces, generate tests FIRST, then implement minimal code to pass. Ensure 80%+ coverage. +--- + +# TDD Command + +This command enforces a test-driven development methodology directly. + +## What This Command Does + +1. **Scaffold Interfaces** - Define types/interfaces first +2. **Generate Tests First** - Write failing tests (RED) +3. **Implement Minimal Code** - Write just enough to pass (GREEN) +4. **Refactor** - Improve code while keeping tests green (REFACTOR) +5. **Verify Coverage** - Ensure 80%+ test coverage + +## When to Use + +Use `/tdd` when: +- Implementing new features +- Adding new functions/components +- Fixing bugs (write test that reproduces bug first) +- Refactoring existing code +- Building critical business logic + +## How It Works + +This command should: + +1. **Define interfaces** for inputs/outputs +2. **Write tests that will FAIL** (because code doesn't exist yet) +3. **Run tests** and verify they fail for the right reason +4. **Write minimal implementation** to make tests pass +5. **Run tests** and verify they pass +6. **Refactor** code while keeping tests green +7. **Check coverage** and add more tests if below 80% + +## TDD Cycle + +``` +RED → GREEN → REFACTOR → REPEAT + +RED: Write a failing test +GREEN: Write minimal code to pass +REFACTOR: Improve code, keep tests passing +REPEAT: Next feature/scenario +``` + +## Example Usage + +``` +User: /tdd I need a function to calculate market liquidity score + +Assistant: +# TDD Session: Market Liquidity Score Calculator + +## Step 1: Define Interface (SCAFFOLD) + +```python +# lib/liquidity.py +from dataclasses import dataclass +from datetime import datetime +from typing import NotRequired + +@dataclass +class MarketData: + totalVolume: float + bidAskSpread: float + activeTraders: int + lastTradeTime: datetime + +def calculateLiquidityScore(market: MarketData) -> float: + # TODO: Implementation + raise NotImplementedError('Not implemented') +``` + +## Step 2: Write Failing Test (RED) + +```python +# tests/test_liquidity.py +import pytest +from lib.liquidity import calculateLiquidityScore, MarketData +from datetime import datetime + +def test_liquid_market_high_score(): + """Test that liquid market gets high score.""" + market = MarketData( + totalVolume=100000, + bidAskSpread=0.01, + activeTraders=500, + lastTradeTime=datetime.now() + ) + + score = calculateLiquidityScore(market) + + assert 80 < score <= 100 + +def test_illiquid_market_low_score(): + """Test that illiquid market gets low score.""" + market = MarketData( + totalVolume=100, + bidAskSpread=0.5, + activeTraders=2, + lastTradeTime=datetime.fromtimestamp(datetime.now().timestamp() - 86400) # 1 day ago + ) + + score = calculateLiquidityScore(market) + + assert 0 <= score < 30 + +def test_zero_volume_edge_case(): + """Test that zero volume returns score of 0.""" + market = MarketData( + totalVolume=0, + bidAskSpread=0, + activeTraders=0, + lastTradeTime=datetime.now() + ) + + score = calculateLiquidityScore(market) + + assert score == 0 +``` + +## Step 3: Run Tests - Verify FAIL + +```bash +pytest tests/test_liquidity.py -v + +FAILED test_liquidity.py::test_liquid_market_high_score + NotImplementedError: Not implemented + +1 test failed, 0 passed +``` + +✅ Tests fail as expected. Ready to implement. + +## Step 4: Implement Minimal Code (GREEN) + +```python +# lib/liquidity.py +def calculateLiquidityScore(market: MarketData) -> float: + # Handle zero volume edge case + if market.totalVolume == 0: + return 0.0 + + # Calculate component scores (0-100 scale) + volumeScore = min(market.totalVolume / 1000, 100) + spreadScore = max(100 - (market.bidAskSpread * 1000), 0) + traderScore = min(market.activeTraders / 10, 100) + + # Recent activity bonus + hoursSinceLastTrade = (datetime.now().timestamp() - market.lastTradeTime.timestamp()) / 3600 + recencyScore = max(100 - (hoursSinceLastTrade * 10), 0) + + # Weighted average + score = ( + volumeScore * 0.4 + + spreadScore * 0.3 + + traderScore * 0.2 + + recencyScore * 0.1 + ) + + return max(0, min(score, 100)) # Clamp to 0-100 +``` + +## Step 5: Run Tests - Verify PASS + +```bash +pytest tests/test_liquidity.py -v + +PASSED test_liquidity.py::test_liquid_market_high_score +PASSED test_liquidity.py::test_illiquid_market_low_score +PASSED test_liquidity.py::test_zero_volume_edge_case + +3 tests passed +``` + +✅ All tests passing! + +## Step 6: Refactor (IMPROVE) + +```python +# lib/liquidity.py - Refactored with constants and better readability +from dataclasses import dataclass + +WEIGHTS = { + 'VOLUME': 0.4, + 'SPREAD': 0.3, + 'TRADERS': 0.2, + 'RECENCY': 0.1, +} + +SCALE_FACTORS = { + 'VOLUME': 1000, + 'SPREAD': 1000, + 'TRADERS': 10, + 'RECENCY_PENALTY': 10, +} + +def clamp(value: float, min_val: float, max_val: float) -> float: + """Clamp value between min and max.""" + return max(min(value, max_val), min_val) + +def calculateLiquidityScore(market: MarketData) -> float: + if market.totalVolume == 0: + return 0.0 + + volumeScore = min(market.totalVolume / SCALE_FACTORS['VOLUME'], 100) + spreadScore = clamp(100 - (market.bidAskSpread * SCALE_FACTORS['SPREAD']), 0, 100) + traderScore = min(market.activeTraders / SCALE_FACTORS['TRADERS'], 100) + + hoursSinceLastTrade = (datetime.now().timestamp() - market.lastTradeTime.timestamp()) / 3600 + recencyScore = clamp(100 - (hoursSinceLastTrade * SCALE_FACTORS['RECENCY_PENALTY']), 0, 100) + + weightedScore = ( + volumeScore * WEIGHTS['VOLUME'] + + spreadScore * WEIGHTS['SPREAD'] + + traderScore * WEIGHTS['TRADERS'] + + recencyScore * WEIGHTS['RECENCY'] + ) + + return clamp(weightedScore, 0, 100) +``` + +## Step 7: Verify Tests Still Pass + +```bash +pytest tests/test_liquidity.py -v + +PASSED test_liquidity.py::test_liquid_market_high_score +PASSED test_liquidity.py::test_illiquid_market_low_score +PASSED test_liquidity.py::test_zero_volume_edge_case + +3 tests passed +``` + +✅ Refactoring complete, tests still passing! + +## Step 8: Check Coverage + +```bash +pytest --cov=lib --cov-report=term-missing tests/test_liquidity.py + +File | % Stmts | % Branch | % Funcs | % Lines +---------------|---------|----------|---------|-------- +liquidity.py | 100 | 100 | 100 | 100 + +Coverage: 100% ✅ (Target: 80%) +``` + +✅ TDD session complete! +``` + +## TDD Best Practices + +**DO:** +- ✅ Write the test FIRST, before any implementation +- ✅ Run tests and verify they FAIL before implementing +- ✅ Write minimal code to make tests pass +- ✅ Refactor only after tests are green +- ✅ Add edge cases and error scenarios +- ✅ Aim for 80%+ coverage (100% for critical code) + +**DON'T:** +- ❌ Write implementation before tests +- ❌ Skip running tests after each change +- ❌ Write too much code at once +- ❌ Ignore failing tests +- ❌ Test implementation details (test behavior) +- ❌ Mock everything (prefer integration tests) + +## Test Types to Include + +**Unit Tests** (Function-level): +- Happy path scenarios +- Edge cases (empty, null, max values) +- Error conditions +- Boundary values + +**Integration Tests** (Component-level): +- API endpoints +- Database operations +- External service calls +- React components with hooks + +**E2E Tests** (use `/e2e` command): +- Critical user flows +- Multi-step processes +- Full stack integration + +## Coverage Requirements + +- **80% minimum** for all code +- **100% required** for: + - Financial calculations + - Authentication logic + - Security-critical code + - Core business logic + +## Important Notes + +**MANDATORY**: Tests must be written BEFORE implementation. The TDD cycle is: + +1. **RED** - Write failing test +2. **GREEN** - Implement to pass +3. **REFACTOR** - Improve code + +Never skip the RED phase. Never write code before tests. + +## Integration with Other Commands + +- Use `/plan` first to understand what to build +- Use `/tdd` to implement with tests +- Use `/build-and-fix` if build errors occur +- Use `/code-review` to review implementation +- Use `/test-coverage` to verify coverage + +## Related Agents + +Use `daily-coding` and `verification-loop` style checks to keep the cycle test-backed and incremental. + +And can reference the `tdd-workflow` skill at: +`~/.claude/skills/tdd-workflow/` diff --git a/文档润色流和知识库构建流/claude-scholar/commands/update-github.md b/文档润色流和知识库构建流/claude-scholar/commands/update-github.md new file mode 100644 index 0000000..60467ab --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/update-github.md @@ -0,0 +1,100 @@ +--- +description: Commit changes with Conventional Commits format and push to GitHub remote repository. +--- + +# Update GitHub + +Commit uncommitted changes and push to remote GitHub repository. + +## Instructions + +1. **Check Git Status** + - Run `git status` + - Show all uncommitted changes + +2. **Analyze Changes** + - Review changed files + - Determine commit type (feat/fix/docs/refactor/test/chore) + - Determine scope (affected module/component) + +3. **Create Commit Message** + Follow Conventional Commits format: + ``` + (): + + + +
    + ``` + + Types: + - `feat`: 新功能 + - `fix`: Bug 修复 + - `docs`: 文档更新 + - `refactor`: 代码重构 + - `perf`: 性能优化 + - `test`: 测试相关 + - `chore`: 其他修改 + +4. **Stage and Commit** + - Run `git add` for affected files + - Create commit with formatted message + - Do not include `Co-Authored-By` footers unless the user explicitly asks for them + +5. **Push to Remote** + - Run `git push` + - If rejected, pull with rebase first: + ```bash + git pull --rebase origin $(git branch --show-current) + git push + ``` + +6. **Verify Success** + - Show commit SHA + - Show remote branch status + +## Example Usage + +``` +User: /update-github + +1. Checking git status... + Modified: src/utils/helpers.py + Modified: README.md + +2. Analyzing changes... + - src/utils/helpers.py: Refactored helper functions + - README.md: Updated documentation + +3. Proposed commit: + docs(readme): 更新项目文档 + + - 添加使用示例 + - 更新依赖说明 + +4. Proceed? (yes/no/modify) + +5. Staging files... + git add src/utils/helpers.py README.md + +6. Creating commit... + [main abc1234] docs(readme): 更新项目文档 + +7. Pushing to remote... + git push + To github.com:user/repo.git + abc1234..def5678 main -> main + +✅ Successfully pushed to GitHub! +``` + +## Arguments + +$ARGUMENTS can be: +- `--amend` - Amend last commit instead of creating new one +- `--no-verify` - Skip pre-commit hooks +- `(): ` - Use custom commit message + +## Integration + +This command uses the same Conventional Commits format as the `/commit` skill but focuses on the complete flow: stage → commit → push. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/update-memory.md b/文档润色流和知识库构建流/claude-scholar/commands/update-memory.md new file mode 100644 index 0000000..854cf86 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/update-memory.md @@ -0,0 +1,126 @@ +--- +description: Check and update CLAUDE.md memory based on changes to skills, commands, agents, and hooks. +--- + +# Update Memory + +检查并更新 CLAUDE.md 全局记忆文件，确保其内容与 skills、commands、agents、hooks 的源文件保持同步。 + +## 功能概述 + +CLAUDE.md 是一个汇总记忆文件，包含： +- 技能目录结构（来自 `skills/`） +- 命令列表（来自 `commands/`） +- 代理配置（来自 `agents/`） +- 钩子定义（来自 `hooks/`） + +当这些源文件发生变化时，CLAUDE.md 需要同步更新。 + +## 检测逻辑 + +1. **扫描源文件修改时间** + - `~/.claude/skills/**/skill.md` + - `~/.claude/commands/**/*.md` + - `~/.claude/agents/**/*.md` + - `~/.claude/hooks/**/*.{js,json}` + +2. **对比 CLAUDE.md 最后修改时间** + - 如果任意源文件比 CLAUDE.md 新 → 需要更新 + - 记录上次同步时间戳（`~/.claude/.last-memory-sync`） + +3. **生成报告** + - 列出所有变更的源文件 + - 显示需要更新的 CLAUDE.md 章节 + +## 更新流程 + +### 1. 扫描阶段 + +``` +扫描 Skills: X 个 +扫描 Commands: Y 个 +扫描 Agents: Z 个 +扫描 Hooks: W 个 +``` + +### 2. 对比阶段 + +``` +需要更新的章节: +- [ ] 技能目录结构 (3 个技能变更) +- [ ] 命令列表 (1 个命令新增) +- [ ] 代理配置 (无变更) +- [ ] 钩子定义 (2 个钩子修改) +``` + +### 3. 确认更新 + +询问用户是否执行更新： +``` +是否更新 CLAUDE.md? (yes/no/diff) +- yes: 执行更新 +- no: 取消 +- diff: 显示详细差异 +``` + +### 4. 执行更新 + +- 保留用户手动编辑的内容（如"用户背景"、"技术栈偏好"） +- 仅更新 AUTO-GENERATED 标记的章节 +- 更新时间戳 + +## 使用方式 + +``` +/update-memory # 检查并提示更新 +/update-memory --check # 仅检查，不更新 +/update-memory --force # 强制更新，不询问 +/update-memory --diff # 显示差异对比 +``` + +## 输出示例 + +### 检查结果 + +``` +📋 CLAUDE.md 记忆状态检查 + +源文件状态: +✅ Skills: 24 个 (最近修改: ml-paper-writing) +✅ Commands: 14 个 (最近修改: update-readme) +✅ Agents: 7 个 (无变更) +✅ Hooks: 5 个 (最近修改: session-summary) + +时间对比: +- CLAUDE.md 最后更新: 2024-01-15 10:30 +- 源文件最后修改: 2024-01-16 14:22 + +⚠️ 检测到变更，建议更新 CLAUDE.md + +变更详情: +1. skills/ml-paper-writing/skill.md (修改于 14:22) +2. commands/update-readme.md (修改于 13:15) +3. hooks/session-summary.js (修改于 11:45) + +是否执行更新? (yes/no/diff) +``` + +### 更新完成 + +``` +✅ CLAUDE.md 已更新 + +更新内容: +- 技能目录: 同步 24 个技能 +- 命令列表: 同步 14 个命令 +- 代理配置: 无变更 +- 钩子定义: 同步 5 个钩子 + +下次同步时间戳已更新。 +``` + +## 集成建议 + +- 在 `session-summary.js` 中集成检查提醒 +- 在 PostToolUse 钩子中实时检测 +- 建议定期执行（如每次会话结束时） diff --git a/文档润色流和知识库构建流/claude-scholar/commands/update-readme.md b/文档润色流和知识库构建流/claude-scholar/commands/update-readme.md new file mode 100644 index 0000000..fae3096 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/update-readme.md @@ -0,0 +1,159 @@ +--- +description: Update README documentation and push changes to GitHub. +--- + +# Update README + +Update README.md file with latest project information and push to GitHub. + +## Instructions + +1. **Analyze Current State** + - Read existing README.md + - Check recent code changes (git log) + - Identify documentation gaps + +2. **Determine Updates Needed** + Check for: + - New features added + - Configuration changes + - Dependencies updated + - Installation instructions + - Usage examples + - API changes + +3. **Propose README Updates** + Show sections that need updating: + ```markdown + Proposed changes: + - [ ] Update Installation section (new dependencies) + - [ ] Add usage example for feature X + - [ ] Update API documentation + - [ ] Fix broken links + ``` + +4. **Update README** + - Apply proposed changes + - Maintain markdown formatting + - Keep language consistent (中文/English) + - Preserve structure + +5. **Commit and Push** + - Run `/update-github` with `docs(readme):` type + - Example commit: `docs(readme): 更新 README 文档` + +## Example Usage + +``` +User: /update-readme + +1. Analyzing repository state... + +Recent changes: +- feat(data): 添加新的数据加载器 +- fix(model): 修复训练时的内存泄漏 +- chore: 更新依赖到 v2.0.0 + +2. Checking README.md... + +Current README sections: +- Installation +- Usage +- API Reference +- Contributing + +3. Proposed updates: + [ ] Installation - 添加新的依赖说明 + [ ] Usage - 添加数据加载器示例 + [ ] API Reference - 更新模型接口文档 + +4. Applying updates... + + Updating Installation: + + pip install torch>=2.0.0 + + pip install transformers>=4.30.0 + + Adding usage example: + ## 数据加载示例 + ```python + from data import DataLoader + loader = DataLoader(batch_size=32) + ``` + +5. Review changes before committing... + [Show diff] + +6. Proceed with commit? + > yes + +7. Committing with: docs(readme): 更新 README 文档 + Co-Authored-By: Claude + +✅ README updated and pushed to GitHub! +``` + +## README Structure Template + +When updating README, follow this structure: + +```markdown +# 项目名称 + +简短描述项目用途。 + +## 安装 + +### 依赖要求 +- Python >= 3.8 +- uv 或 pip + +### 安装步骤 +```bash +uv sync +``` + +## 使用 + +### 基本用法 +```python +# 示例代码 +``` + +### 配置 +说明配置文件位置和格式。 + +## API 文档 + +主要接口说明。 + +## 开发 + +### 运行测试 +```bash +pytest +``` + +### 代码规范 +- 遵循 PEP 8 +- 使用 mypy 进行类型检查 +- 使用 ruff 进行 linting + +## 贡献 + +欢迎提交 Pull Request。 + +## 许可证 + +MIT License +``` + +## Arguments + +$ARGUMENTS can be: +- `--full` - Complete README rewrite +- `--quick` - Only update critical sections (installation, usage) +- `
    ` - Update specific section only + +## Integration + +After updating README, this command automatically invokes `/update-github` with `docs(readme):` commit type. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/verify.md b/文档润色流和知识库构建流/claude-scholar/commands/verify.md new file mode 100644 index 0000000..50e2e0d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/verify.md @@ -0,0 +1,59 @@ +# Verification Command + +Run comprehensive verification on current codebase state. + +## Instructions + +Execute verification in this exact order: + +1. **Type Check** + - Run mypy src/ + - Report all errors with file:line + +2. **Lint Check** + - Run ruff check . + - Report warnings and errors + +3. **Test Suite** + - Run pytest + - Report pass/fail count + - Report coverage percentage (pytest --cov) + +4. **Security Check** + - Run pip-audit + - Check for hardcoded secrets (grep -r "sk-" etc.) + +5. **Print Audit** + - Search for print() in source files + - Report locations + +6. **Git Status** + - Show uncommitted changes + - Show files modified since last commit + +## Output + +Produce a concise verification report: + +``` +VERIFICATION: [PASS/FAIL] + +Types: [OK/X errors] +Lint: [OK/X issues] +Tests: [X/Y passed, Z% coverage] +Security: [OK/X vulnerabilities] +Secrets: [OK/X found] +Prints: [OK/X print() statements] + +Ready for commit: [YES/NO] +``` + +If any critical issues, list them with fix suggestions. + +## Arguments + +$ARGUMENTS can be: +- `quick` - Only types + lint +- `full` - All checks (default) +- `pre-commit` - Checks relevant for commits +- `pre-pr` - Full checks plus security scan diff --git a/文档润色流和知识库构建流/claude-scholar/commands/zotero-notes.md b/文档润色流和知识库构建流/claude-scholar/commands/zotero-notes.md new file mode 100644 index 0000000..9e0ef93 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/zotero-notes.md @@ -0,0 +1,128 @@ +--- +name: zotero-notes +description: Batch read papers from Zotero and create/update detailed reading notes, preferably inside the bound Obsidian project knowledge base +args: + - name: collection + description: Zotero collection name or keyword + required: true + - name: format + description: Note format (summary/detailed/comparison) + required: false + default: detailed +tags: [Research, Zotero, Obsidian, Reading Notes, Paper Analysis] +--- + +# /zotero-notes - Zotero to Obsidian Reading Notes + +Read papers from the Zotero collection "$collection" and create or update detailed reading notes. + +## Default target + +- **Preferred target**: the bound Obsidian project knowledge base (`Sources/Papers/*.md`) +- **Fallback target**: `reading-notes-{collection}.md` in the working directory if the current repo is not bound to Obsidian + +## Workflow + +### Step 0: Resolve whether the current repo is Obsidian-bound + +1. If `.claude/project-memory/registry.yaml` exists for the current repo, treat the bound vault as the primary output target. +2. If the repo is a research project but not yet bound, bootstrap it first. +3. If there is no bound project context, fall back to a plain markdown output in the working directory. +4. Treat this command as an explicit agent-first ingestion pass under `$zotero-obsidian-bridge`. + +### Step 1: Load papers from Zotero + +1. Call `mcp__zotero__zotero_get_collections` to find the matching collection. +2. Call `mcp__zotero__zotero_get_collection_items` to list the papers. +3. For each item, call: + - `mcp__zotero__zotero_get_item_metadata` + - `mcp__zotero__zotero_get_item_fulltext` when a PDF is available + - `mcp__zotero__zotero_get_annotations` when helpful + - `mcp__zotero__zotero_get_notes` when helpful +4. If MCP transport fails but a local `zotero-mcp` checkout is available, use the local Python fallback instead of stopping the pass. +5. Treat Zotero `webpage` items as weak-source inputs unless they clearly expose full paper metadata and useful full text. Abstract-only or placeholder pages must stay `To-Read` and cannot support `Knowledge` or `Writing` claims. + +### Step 2: Create/update the canonical paper note + +If the project is Obsidian-bound, create or update one canonical note per paper under `Sources/Papers/`. + +Each detailed note should contain: +- `Claim` +- `Research question` +- `Method` +- `Evidence` +- `Strengths` +- `Limitation` +- `Direct relevance to repo` +- `Relation to other papers` +- `Knowledge links` +- `Optional downstream hooks` +- canonical `Evidence Record` with `Source type` and `Claim strength` when the paper has reusable claims + +Recommended frontmatter fields: +- `title`, `authors`, `year`, `venue`, `doi`, `url`, `citekey`, `zotero_key` +- `keywords`, `concepts`, `methods` +- `related_papers`, `linked_knowledge`, `argument_claims`, `argument_methods`, `argument_gaps`, `paper_relationships` + +Prefer updating the existing note over creating a sibling note. + +### Step 3: Collection coverage and synthesis + +After the paper-note pass: +- update a collection inventory note when the source is a named collection +- record item -> canonical note mapping and coverage counts such as `16 / 16` +- verify coverage against expected Zotero keys, DOI values, or arXiv IDs when the user supplied them +- label abstract-only and webpage-placeholder items separately in the inventory +- synthesize durable literature knowledge under `Knowledge/`, for example: + - `Knowledge/Literature Overview.md` + - `Knowledge/Method Taxonomy.md` + - `Knowledge/Research Gaps.md` + +Prefer updating existing canonical knowledge notes over creating parallel summaries. + +### Step 4: Refresh the default literature canvas + +After batch note creation or substantial note updates, refresh: + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-literature-workflow/scripts/build_literature_canvas.py" --cwd "$PWD" +``` + +This rebuilds `Maps/literature.canvas` from paper-note and knowledge-note links. + +### Step 5: Optional synthesis outputs + +- If `format=comparison` and promoted claims pass the evidence gate, also update `Writing/comparison-matrix.md`. +- If the paper batch already supports a thematic synthesis and promoted claims pass the evidence gate, update `Writing/related-work-draft.md`. + If not, write only a coverage warning or claim map. + +### Step 6: Minimal write-back + +Always update: +- today's `Daily/YYYY-MM-DD.md` +- repo-local binding summary when project state changes + +### Step 7: Final response + +Include: +- collection size and coverage summary +- created / updated note paths +- optional `obsidian://open` links +- optional `obsidian open ...` suggestions when CLI is available + +## Fallback behavior + +If the repo is not bound to Obsidian: +- create `reading-notes-{collection}.md` +- if `format=comparison` and promoted claims pass the evidence gate, also create `comparison-matrix.md` + +## Notes + +- Zotero remains the source of truth for collection structure, metadata, attachments, PDF full text, and annotations. +- Obsidian remains the durable project knowledge surface for reading notes, project relevance, and cross-note linking. +- Default bridge targets are `Sources/Papers/` and `Knowledge/`. +- Do not dump raw full text into Obsidian paper notes. +- Do not create `Concepts/` or `Datasets/` trees by default. +- Refresh `Maps/literature.canvas` by default after a substantial Zotero ingestion pass. +- Treat `Experiments/` and `Results/` as later project workflows, not the default Zotero-import destination. +- Do not let abstract-only or webpage-placeholder items support durable claims. diff --git a/文档润色流和知识库构建流/claude-scholar/commands/zotero-review.md b/文档润色流和知识库构建流/claude-scholar/commands/zotero-review.md new file mode 100644 index 0000000..5ea9925 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/commands/zotero-review.md @@ -0,0 +1,102 @@ +--- +name: zotero-review +description: Read and analyze papers from a Zotero collection, then synthesize them into the bound Obsidian project knowledge base or markdown review outputs +args: + - name: collection + description: Zotero collection name or keyword to search + required: true + - name: depth + description: Analysis depth (quick/deep) + required: false + default: deep +tags: [Research, Zotero, Obsidian, Literature Review, Paper Analysis] +--- + +# /zotero-review - Zotero Collection Literature Analysis + +Read and analyze papers in the Zotero collection "$collection", with analysis depth "$depth". + +## Default target + +- **Preferred target**: the bound Obsidian project knowledge base +- **Fallback target**: `related-work-draft.md` in the current working directory + +## Workflow + +### Step 0: Resolve the project context + +1. If the current repo is already bound to an Obsidian project KB, use that project root. +2. If the repo looks like a research project but is not bound yet, bootstrap it first. +3. If there is no project binding, generate the review in the working directory. + +### Step 1: Locate and read the Zotero collection + +1. Call `mcp__zotero__zotero_get_collections` to find the matching collection. +2. Call `mcp__zotero__zotero_get_collection_items` to get all papers. +3. For each paper: + - call `mcp__zotero__zotero_get_item_metadata` with `include_abstract: true` + - call `mcp__zotero__zotero_get_item_fulltext` when available + - use abstract metadata as fallback when PDF full text is unavailable +4. If MCP transport fails but a local `zotero-mcp` checkout is available, use the local Python fallback instead of aborting. +5. Treat Zotero `webpage` items as weak-source entries unless they clearly expose full paper metadata and useful full text. Abstract-only or placeholder pages can appear in coverage summaries, but cannot support `Knowledge`, `Writing`, manuscript, or rebuttal claims. + +### Step 2: Ensure detailed paper notes exist + +Before high-level synthesis, ensure the collection has durable paper notes. + +If the project is Obsidian-bound: +- create or update `Sources/Papers/*.md` canonical notes first +- keep one canonical paper note per paper whenever possible +- align notes to the canonical schema (`Claim / Method / Evidence / Limitation / Direct relevance to repo / Relation to other papers`) +- update the best matching `Knowledge/` literature synthesis notes +- refresh `Maps/literature.canvas` +- update a collection inventory note with item -> note mapping and coverage summary + +If not Obsidian-bound: +- create intermediate `paper-notes/*.md` files in the working directory when `depth=deep` + +### Step 3: Synthesize across paper notes + +Create or update: +- `Knowledge/Literature Overview.md` +- `Knowledge/Method Taxonomy.md` when useful +- `Knowledge/Research Gaps.md` when useful +- `Writing/related-work-draft.md` only when the user wants writing-facing synthesis and the promoted claims pass the evidence gate +- `Writing/comparison-matrix.md` when useful and promoted claims pass the evidence gate + +The synthesis should include: +- thematic grouping +- method families +- key findings and tensions +- research gaps +- direct relevance to the current project +- explicit links across `Sources/Papers/` and `Knowledge/` +- Evidence Record IDs, source type, claim strength, allowed wording, and forbidden stronger wording for claims that may later enter writing or rebuttal + +If core papers lack full text or Evidence Records, stop at a collection audit / claim map and state what is missing. Do not generate a polished related-work draft from weak notes. + +### Step 4: Push downstream only when justified + +- keep the default review surface in `Sources/Papers/`, `Knowledge/`, and `Maps/literature.canvas` +- update `Writing/` only when the user wants a manuscript-facing review or comparison narrative and promoted claims pass the evidence gate +- only update `Experiments/` or `Results/` in a later project workflow when the user explicitly wants that handoff + +### Step 5: Minimal write-back + +Always update: +- today's `Daily/YYYY-MM-DD.md` +- repo-local binding summary when project state changes + +### Step 6: Final response + +Include: +- collection size and coverage summary +- updated note paths +- optional `obsidian://open` links +- optional `obsidian open ...` suggestions when CLI is available + +## Notes + +- Prefer the Obsidian-bound project workflow over loose markdown files when available. +- Keep `Sources/Papers/` first-class; the review should be grounded in canonical paper notes rather than only one-shot synthesis. +- The default graph artifact is `Maps/literature.canvas`. diff --git a/文档润色流和知识库构建流/claude-scholar/hooks/hook-common.js b/文档润色流和知识库构建流/claude-scholar/hooks/hook-common.js new file mode 100644 index 0000000..0c0a417 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/hooks/hook-common.js @@ -0,0 +1,843 @@ +/** + * Cross-platform Hook shared utility library + * Provides cross-platform compatible shared functions for Claude Code Hooks + * + * @module hook-common + */ + +const fs = require('fs'); +const path = require('path'); +const { execSync } = require('child_process'); + +/** + * Get Git status information + * @param {string} cwd - Current working directory + * @returns {Object} Git info object + */ +function getGitInfo(cwd) { + try { + // Check if this is a Git repository + execSync('git rev-parse --git-dir', { + cwd, + stdio: 'pipe' + }); + + // Get branch name + let branch = 'unknown'; + try { + branch = execSync('git branch --show-current', { + cwd, + encoding: 'utf8', + stdio: 'pipe' + }).trim(); + } catch { + branch = 'unknown'; + } + + // Get changed files + let changes = ''; + try { + changes = execSync('git status --porcelain', { + cwd, + encoding: 'utf8', + stdio: 'pipe' + }); + } catch { + changes = ''; + } + + const changeList = changes.trim().split('\n').filter(Boolean); + const hasChanges = changeList.length > 0; + + return { + is_repo: true, + branch, + changes_count: changeList.length, + has_changes: hasChanges, + changes: changeList + }; + } catch { + return { + is_repo: false, + branch: 'unknown', + changes_count: 0, + has_changes: false, + changes: [] + }; + } +} + +/** + * Get todo item information + * @param {string} cwd - Current working directory + * @returns {Object} Todo item information + */ +function getTodoInfo(cwd) { + const todoFiles = [ + path.join(cwd, 'docs', 'todo.md'), + path.join(cwd, 'TODO.md'), + path.join(cwd, '.claude', 'todos.md'), + path.join(cwd, 'TODO'), + path.join(cwd, 'notes', 'todo.md') + ]; + + for (const file of todoFiles) { + if (fs.existsSync(file)) { + try { + const content = fs.readFileSync(file, 'utf8'); + const totalMatches = content.match(/^[\-\*] \[[ x]\]/gi) || []; + const total = totalMatches.length; + + const doneMatches = content.match(/^[\-\*] \[x\]/gi) || []; + const done = doneMatches.length; + + const pending = total - done; + + return { + found: true, + file: path.basename(file), + path: file, + total, + done, + pending + }; + } catch { + continue; + } + } + } + + return { + found: false, + file: null, + path: null, + total: 0, + done: 0, + pending: 0 + }; +} + + +/** + * Resolve repository root when available + * @param {string} cwd - Current working directory + * @returns {string} Repository root or cwd fallback + */ +function getRepoRoot(cwd) { + try { + return execSync('git rev-parse --show-toplevel', { + cwd, + encoding: 'utf8', + stdio: 'pipe' + }).trim(); + } catch { + return cwd; + } +} + +/** + * Parse simple YAML frontmatter from a Markdown file. + * Supports the project-memory binding metadata shape. + * @param {string} filePath + * @returns {Object|null} + */ +function parseFrontmatterFile(filePath) { + try { + const content = fs.readFileSync(filePath, 'utf8'); + const match = content.match(/^---\n([\s\S]*?)\n---/); + if (!match) return null; + + const data = {}; + for (const line of match[1].split('\n')) { + const parts = line.match(/^([A-Za-z0-9_]+):\s*(.*)$/); + if (!parts) continue; + const key = parts[1]; + let value = parts[2].trim(); + + if (value === 'true') value = true; + else if (value === 'false') value = false; + else value = value.replace(/^['"]|['"]$/g, ''); + + data[key] = value; + } + return data; + } catch { + return null; + } +} + +/** + * Detect whether the current repository is bound to Obsidian project memory + * @param {string} cwd - Current working directory + * @returns {Object} Binding info + */ +function getProjectMemoryBinding(cwd) { + const repoRoot = getRepoRoot(cwd); + const projectMemoryDir = path.join(repoRoot, '.claude', 'project-memory'); + const registryPath = path.join(projectMemoryDir, 'registry.yaml'); + + if (!fs.existsSync(registryPath)) { + return { + bound: false, + repoRoot, + registryPath, + projectId: null, + status: null, + autoSync: false, + vaultRoot: null, + hubNote: null, + memoryPath: null + }; + } + + let project = null; + let memoryPath = null; + + if (fs.existsSync(projectMemoryDir)) { + const memoryFiles = fs.readdirSync(projectMemoryDir) + .filter(name => name.endsWith('.md')) + .map(name => path.join(projectMemoryDir, name)); + + for (const candidate of memoryFiles) { + const frontmatter = parseFrontmatterFile(candidate); + if (!frontmatter) continue; + if (frontmatter.repo_root && (frontmatter.repo_root === repoRoot || cwd.startsWith(frontmatter.repo_root))) { + project = frontmatter; + memoryPath = candidate; + break; + } + } + + if (!memoryPath && memoryFiles.length > 0) { + memoryPath = memoryFiles[0]; + project = parseFrontmatterFile(memoryPath) || null; + } + } + + return { + bound: true, + repoRoot, + registryPath, + projectId: project ? project.project_id || null : null, + status: project ? project.status || null : null, + autoSync: Boolean(project && project.auto_sync), + vaultRoot: project ? project.vault_root || null : null, + hubNote: project ? project.hub_note || null : null, + memoryPath + }; +} + +/** + * Heuristically detect whether a directory looks like a research repo + * @param {string} cwd - Current working directory + * @returns {Object} Detection result + */ +function detectResearchProject(cwd) { + const repoRoot = getRepoRoot(cwd); + const markers = [ + '.git', + 'README.md', + 'docs', + 'notes', + 'plan', + 'results', + 'outputs', + 'src', + 'scripts' + ]; + + const hits = markers.filter(marker => fs.existsSync(path.join(repoRoot, marker))); + const candidate = hits.length >= 3 || (hits.includes('.git') && hits.includes('README.md') && hits.length >= 2); + + return { + repoRoot, + candidate, + markers: hits + }; +} + +/** + * Detect whether a user prompt looks research-related + * @param {string} prompt - User prompt + * @returns {boolean} Whether the prompt looks research-related + */ +function promptLooksResearchRelated(prompt) { + return /\b(obsidian|zotero|paper|papers|literature|review|experiment|results?|finding|analysis|research|plan|todo|daily|meeting|writing|draft|proposal|rebuttal|claim|method)\b|文献|实验|结果|研究|计划|待办|知识库|论文|综述|笔记|项目记忆|obsidian|zotero/i.test(prompt); +} + +/** + * Get Git change details + * @param {string} cwd - Current working directory + * @returns {Object} Change statistics + */ +function getChangesDetails(cwd) { + try { + let added = 0; + let modified = 0; + let deleted = 0; + + // 解析 name-status 输出，每行格式: "A\tfilename" 或 "M\tfilename" + const parseNameStatus = (output) => { + for (const line of output.trim().split('\n').filter(Boolean)) { + const status = line.charAt(0); + if (status === 'A') added++; + else if (status === 'M') modified++; + else if (status === 'D') deleted++; + } + }; + + // 工作区变更（unstaged） + const unstaged = execSync('git diff --name-status', { + cwd, + encoding: 'utf8', + stdio: 'pipe' + }); + parseNameStatus(unstaged); + + // 暂存区变更（staged） + const staged = execSync('git diff --cached --name-status', { + cwd, + encoding: 'utf8', + stdio: 'pipe' + }); + parseNameStatus(staged); + + // 未跟踪文件算作 added + const untracked = execSync('git status --porcelain', { + cwd, + encoding: 'utf8', + stdio: 'pipe' + }); + for (const line of untracked.trim().split('\n').filter(Boolean)) { + if (line.startsWith('??')) added++; + } + + return { added, modified, deleted }; + } catch { + return { added: 0, modified: 0, deleted: 0 }; + } +} + +/** + * Analyze changes by file type + * @param {string} cwd - Current working directory + * @returns {Object} File type statistics + */ +function analyzeChangesByType(cwd) { + const gitInfo = getGitInfo(cwd); + + if (!gitInfo.is_repo || !gitInfo.has_changes) { + return { + test_files: 0, + docs_files: 0, + sql_files: 0, + config_files: 0, + service_files: 0 + }; + } + + // 逐行匹配文件路径（git status --porcelain 格式: "XY filename"） + const files = gitInfo.changes.map(line => line.substring(3).trim()); + + const testRegex = /(?:^|[\/\\])tests?[\/\\]|[\/\\._]test[_.]|\.test\.|_test\./i; + const docsRegex = /\.(md|txt|rst)$/i; + const sqlRegex = /\.sql$/i; + const configRegex = /\.(json|yaml|yml|toml|ini|conf)$/i; + const serviceRegex = /(service|controller)/i; + + let testFiles = 0; + let docsFiles = 0; + let sqlFiles = 0; + let configFiles = 0; + let serviceFiles = 0; + + for (const file of files) { + if (testRegex.test(file)) testFiles++; + if (docsRegex.test(file)) docsFiles++; + if (sqlRegex.test(file)) sqlFiles++; + if (configRegex.test(file)) configFiles++; + if (serviceRegex.test(file)) serviceFiles++; + } + + return { + test_files: testFiles, + docs_files: docsFiles, + sql_files: sqlFiles, + config_files: configFiles, + service_files: serviceFiles + }; +} + +/** + * Detect temporary files + * @param {string} cwd - Current working directory + * @returns {Object} Temporary file information + */ +function detectTempFiles(cwd) { + const tempFiles = new Set(); + const gitInfo = getGitInfo(cwd); + + // Find temp files from Git untracked files + if (gitInfo.is_repo) { + for (const change of gitInfo.changes) { + if (change.startsWith('??')) { + const file = change.substring(3).trim(); + if (/plan|draft|tmp|temp|scratch/i.test(file)) { + tempFiles.add(file); + } + } + } + } + + // Check known temporary directories + const tempDirs = ['plan', 'docs/plans', '.claude/temp', 'tmp', 'temp']; + for (const dir of tempDirs) { + const dirPath = path.join(cwd, dir); + if (fs.existsSync(dirPath)) { + try { + const files = getAllFiles(dirPath); + for (const file of files) { + tempFiles.add(path.relative(cwd, file)); + } + } catch { + // Ignore errors + } + } + } + + return { + files: Array.from(tempFiles), + count: tempFiles.size + }; +} + +/** + * Recursively get all files in a directory + * @param {string} dirPath - Directory path + * @returns {Array} List of file paths + */ +function getAllFiles(dirPath) { + const files = []; + const items = fs.readdirSync(dirPath); + + for (const item of items) { + const fullPath = path.join(dirPath, item); + const stat = fs.statSync(fullPath); + + if (stat.isDirectory()) { + files.push(...getAllFiles(fullPath)); + } else { + files.push(fullPath); + } + } + + return files; +} + +/** + * Generate smart recommendations + * @param {string} cwd - Current working directory + * @param {Object} gitInfo - Git information + * @returns {Array} List of recommendations + */ +function generateRecommendations(cwd, gitInfo) { + const recommendations = []; + + if (gitInfo.is_repo && gitInfo.has_changes) { + const changesDetails = getChangesDetails(cwd); + const typeAnalysis = analyzeChangesByType(cwd); + + if (changesDetails.added > 0 || changesDetails.modified > 0) { + recommendations.push('git add . && git commit -m "feat: xxx"'); + } + + if (typeAnalysis.test_files > 0) { + recommendations.push('Run test suite to verify changes'); + } + if (typeAnalysis.docs_files > 0) { + recommendations.push('Check documentation is in sync with code'); + } + if (typeAnalysis.sql_files > 0) { + recommendations.push('Update all related database scripts'); + } + if (typeAnalysis.config_files > 0) { + recommendations.push('Check if environment variables need updating'); + } + if (typeAnalysis.service_files > 0) { + recommendations.push('Update API documentation'); + } + } + + // Todo reminder + const todoInfo = getTodoInfo(cwd); + if (todoInfo.found && todoInfo.pending > 0) { + recommendations.push(`Check todos: ${todoInfo.file} (${todoInfo.pending} items remaining)`); + } + + // Non-repo environment reminder + if (!gitInfo.is_repo) { + recommendations.push('Remember to back up important files to a git repo or cloud storage'); + } + + return recommendations; +} + +/** + * Get list of enabled plugins + * @param {string} homeDir - User home directory + * @returns {Array} Plugin list + */ +function getEnabledPlugins(homeDir) { + const settingsFile = path.join(homeDir, '.claude', 'settings.json'); + + if (!fs.existsSync(settingsFile)) { + return []; + } + + try { + const settings = JSON.parse(fs.readFileSync(settingsFile, 'utf8')); + const enabledPlugins = settings.enabledPlugins || {}; + + const plugins = []; + for (const [pluginId, enabled] of Object.entries(enabledPlugins)) { + if (enabled) { + const pluginName = pluginId.split('@')[0]; + plugins.push({ + id: pluginId, + name: pluginName + }); + } + } + + return plugins; + } catch { + return []; + } +} + +/** + * Get list of available commands + * @param {string} homeDir - User home directory + * @returns {Array} Command list + */ +function getAvailableCommands(homeDir) { + const commands = []; + + // Only collect local commands, not plugin commands + const localCommandsDir = path.join(homeDir, '.claude', 'commands'); + if (fs.existsSync(localCommandsDir)) { + const commandFiles = fs.readdirSync(localCommandsDir) + .filter(f => f.endsWith('.md')); + + for (const cmdFile of commandFiles) { + const cmdName = cmdFile.replace('.md', ''); + commands.push({ + plugin: 'local', + name: cmdName, + path: path.join(localCommandsDir, cmdFile) + }); + } + } + + return commands; +} + +/** + * Get command description + * @param {string} cmdPath - Command file path + * @returns {string} Command description + */ +function getCommandDescription(cmdPath) { + try { + const content = fs.readFileSync(cmdPath, 'utf8'); + const lines = content.split('\n'); + + // Try to get description from frontmatter + let inFrontmatter = false; + for (const line of lines) { + if (line.trim() === '---') { + if (!inFrontmatter) { + inFrontmatter = true; + } else { + break; + } + continue; + } + + if (inFrontmatter && line.trim().startsWith('description:')) { + const match = line.match(/description:\s*["']?(.+?)["']?$/); + if (match) { + return match[1].trim(); + } + } + } + + // Try to get from heading + for (const line of lines) { + const match = line.match(/^#+\s*(.+)$/); + if (match) { + return match[1].trim().substring(0, 50); + } + } + + return ''; + } catch { + return ''; + } +} + +/** + * Collect local skills + * @param {string} homeDir - User home directory + * @returns {Array} Skill list + */ +function collectLocalSkills(homeDir) { + const skills = []; + const skillsDir = path.join(homeDir, '.claude', 'skills'); + + if (!fs.existsSync(skillsDir)) { + return skills; + } + + const skillDirs = fs.readdirSync(skillsDir, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name); + + for (const skillName of skillDirs) { + const skillFile = path.join(skillsDir, skillName, 'SKILL.md'); + let description = ''; + + if (fs.existsSync(skillFile)) { + try { + const content = fs.readFileSync(skillFile, 'utf8'); + const match = content.match(/description:\s*(.+)$/im); + if (match) { + description = match[1].trim(); + } + } catch { + // Ignore + } + } + + skills.push({ + name: skillName, + description, + type: 'local' + }); + } + + return skills; +} + +/** + * Collect plugin skills + * @param {string} homeDir - User home directory + * @returns {Array} Skill list + */ +function collectPluginSkills(homeDir) { + const skills = []; + const pluginsCache = path.join(homeDir, '.claude', 'plugins', 'cache'); + + if (!fs.existsSync(pluginsCache)) { + return skills; + } + + const marketplaces = fs.readdirSync(pluginsCache, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name); + + for (const marketplace of marketplaces) { + // Skip ai-research-skills + if (marketplace === 'ai-research-skills') continue; + + const marketplacePath = path.join(pluginsCache, marketplace); + const plugins = fs.readdirSync(marketplacePath, { withFileTypes: true }) + .filter(d => d.isDirectory() && !d.name.startsWith('.')) + .map(d => d.name); + + for (const plugin of plugins) { + const pluginPath = path.join(marketplacePath, plugin); + const versions = fs.readdirSync(pluginPath, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name) + .sort() + .reverse(); + + if (versions.length === 0) continue; + + const latestVersion = versions[0]; + const pluginRoot = path.join(pluginPath, latestVersion); + const skillsDir = path.join(pluginRoot, 'skills'); + + if (fs.existsSync(skillsDir)) { + const skillDirs = fs.readdirSync(skillsDir, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name); + + for (const skillName of skillDirs) { + skills.push({ + name: `${plugin}:${skillName}`, + plugin, + skill: skillName, + type: 'plugin' + }); + } + } + } + } + + return skills; +} + +/** + * Format date and time + * @param {Date} date - Date object + * @returns {string} Formatted date-time string + */ +function formatDateTime(date = new Date()) { + const year = date.getFullYear(); + const month = String(date.getMonth() + 1).padStart(2, '0'); + const day = String(date.getDate()).padStart(2, '0'); + const hours = String(date.getHours()).padStart(2, '0'); + const minutes = String(date.getMinutes()).padStart(2, '0'); + const seconds = String(date.getSeconds()).padStart(2, '0'); + + return `${year}/${month}/${day} ${hours}:${minutes}:${seconds}`; +} + +/** + * Check if CLAUDE.md needs updating + * @param {string} homeDir - User home directory + * @returns {Object} Check result + */ +function checkClaudeMdUpdate(homeDir) { + const claudeMdPath = path.join(homeDir, '.claude', 'CLAUDE.md'); + const lastSyncPath = path.join(homeDir, '.claude', '.last-memory-sync'); + + // If CLAUDE.md does not exist, return immediately + if (!fs.existsSync(claudeMdPath)) { + return { needsUpdate: false, reason: 'CLAUDE.md not found' }; + } + + // Get CLAUDE.md modification time + const claudeMdMtime = fs.statSync(claudeMdPath).mtimeMs; + + // Get last sync time (use CLAUDE.md creation time if not available) + let lastSyncMtime = claudeMdMtime; + if (fs.existsSync(lastSyncPath)) { + try { + lastSyncMtime = parseInt(fs.readFileSync(lastSyncPath, 'utf8').trim(), 10); + } catch { + lastSyncMtime = claudeMdMtime; + } + } + + const referenceTime = Math.max(claudeMdMtime, lastSyncMtime); + + // Define source file directories to monitor + const sourceDirs = [ + { dir: path.join(homeDir, '.claude', 'skills'), pattern: /SKILL\.md$/, type: 'skill' }, + { dir: path.join(homeDir, '.claude', 'commands'), pattern: /\.md$/, type: 'command' }, + { dir: path.join(homeDir, '.claude', 'agents'), pattern: /\.md$/, type: 'agent' }, + { dir: path.join(homeDir, '.claude', 'hooks'), pattern: /\.(js|json)$/, type: 'hook' } + ]; + + const changedFiles = []; + let totalSkills = 0; + let totalCommands = 0; + let totalAgents = 0; + let totalHooks = 0; + + // Scan each source directory + for (const { dir, pattern, type } of sourceDirs) { + if (!fs.existsSync(dir)) continue; + + const files = getAllFiles(dir).filter(f => pattern.test(f)); + + for (const file of files) { + try { + const mtime = fs.statSync(file).mtimeMs; + + // Count totals + if (type === 'skill') totalSkills++; + else if (type === 'command') totalCommands++; + else if (type === 'agent') totalAgents++; + else if (type === 'hook') totalHooks++; + + // Check if newer than reference time + if (mtime > referenceTime) { + changedFiles.push({ + path: file, + type, + relativePath: path.relative(homeDir, file), + mtime: new Date(mtime).toLocaleString('en-US') + }); + } + } catch { + // Ignore inaccessible files + } + } + } + + return { + needsUpdate: changedFiles.length > 0, + changedFiles, + stats: { + skills: totalSkills, + commands: totalCommands, + agents: totalAgents, + hooks: totalHooks + }, + claudeMdMtime: new Date(claudeMdMtime).toLocaleString('en-US'), + lastSyncMtime: new Date(lastSyncMtime).toLocaleString('en-US') + }; +} + +/** + * Update sync timestamp + * @param {string} homeDir - User home directory + */ +function updateSyncTimestamp(homeDir) { + const lastSyncPath = path.join(homeDir, '.claude', '.last-memory-sync'); + try { + fs.writeFileSync(lastSyncPath, Date.now().toString(), 'utf8'); + } catch { + // Ignore write errors + } +} + +/** + * Create a temporary file + * @param {string} prefix - Filename prefix + * @returns {string} Temporary file path + */ +function createTempFile(prefix = 'claude-temp') { + const os = require('os'); + const tmpDir = os.tmpdir(); + const randomSuffix = Math.random().toString(36).substring(2, 8); + return path.join(tmpDir, `${prefix}-${randomSuffix}.tmp`); +} + +// Export all functions +module.exports = { + getGitInfo, + getTodoInfo, + getRepoRoot, + getProjectMemoryBinding, + detectResearchProject, + promptLooksResearchRelated, + getChangesDetails, + analyzeChangesByType, + detectTempFiles, + generateRecommendations, + getEnabledPlugins, + getAvailableCommands, + getCommandDescription, + collectLocalSkills, + collectPluginSkills, + formatDateTime, + createTempFile, + getAllFiles, + checkClaudeMdUpdate, + updateSyncTimestamp +}; diff --git a/文档润色流和知识库构建流/claude-scholar/hooks/hooks.json b/文档润色流和知识库构建流/claude-scholar/hooks/hooks.json new file mode 100644 index 0000000..d1c932f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/hooks/hooks.json @@ -0,0 +1,65 @@ +{ + "description": "Oh My Claude 自动化工作流钩子 - 跨平台 JavaScript 实现", + "hooks": { + "PreToolUse": [ + { + "matcher": "Bash|Write|Edit", + "hooks": [ + { + "type": "command", + "command": "node ${CLAUDE_PLUGIN_ROOT}/hooks/security-guard.js", + "timeout": 5 + } + ] + } + ], + "SessionEnd": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node ${CLAUDE_PLUGIN_ROOT}/hooks/session-summary.js", + "timeout": 15 + } + ] + } + ], + "SessionStart": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node ${CLAUDE_PLUGIN_ROOT}/hooks/session-start.js", + "timeout": 10 + } + ] + } + ], + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node ${CLAUDE_PLUGIN_ROOT}/hooks/stop-summary.js", + "timeout": 10 + } + ] + } + ], + "UserPromptSubmit": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node ${CLAUDE_PLUGIN_ROOT}/hooks/skill-forced-eval.js", + "timeout": 10 + } + ] + } + ] + } +} diff --git a/文档润色流和知识库构建流/claude-scholar/hooks/security-guard.js b/文档润色流和知识库构建流/claude-scholar/hooks/security-guard.js new file mode 100644 index 0000000..71850f9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/hooks/security-guard.js @@ -0,0 +1,169 @@ +#!/usr/bin/env node +/** + * PreToolUse Hook: Security guard layer (cross-platform version) + * + * Event: PreToolUse + * Two-tier security: Block (exit 2) | Confirm (exit 0 + ask user) + */ + +const path = require('path'); +const os = require('os'); +const common = require('./hook-common'); + +// Read stdin input +let input = {}; +try { + const stdinData = require('fs').readFileSync(0, 'utf8'); + if (stdinData.trim()) { + input = JSON.parse(stdinData); + } +} catch { + // Use default empty object +} + +const toolName = input.tool_name || ''; +const cwd = input.cwd || process.cwd(); + +let decision = 'allow'; +let reason = ''; +let confirmLabel = ''; + +function isPathInside(basePath, targetPath) { + const relative = path.relative(basePath, targetPath); + return relative === '' || (!relative.startsWith('..') && !path.isAbsolute(relative)); +} + +// === Bash command security check === +if (toolName === 'Bash') { + const command = input.tool_input?.command || ''; + + // Tier 1: Block — catastrophic, no recovery + const blockPatterns = [ + /rm\s+-rf\s+\/(\s|$)/, // rm -rf / + /rm\s+--no-preserve-root/, // rm --no-preserve-root + /dd\s+if=\/dev\/(zero|random)/, // dd from /dev/zero or /dev/random + />\s*\/dev\/(sd|nvme|vda)/, // Write to block devices + /mkfs\./, // Format filesystem + /rm\s+-rf?\s+\/(etc|usr|bin|sbin)(\/|\s|$)/, // Remove system dirs + /rm\s+-rf\s+\/home\/[^\/\s]*\/?(\s|$)/, // Remove user home dir + /rm\s+-rf\s+\/Users\/[^\/\s]*\/?(\s|$)/, // Remove macOS user dir + ]; + + for (const pattern of blockPatterns) { + if (pattern.test(command)) { + decision = 'deny'; + reason = 'Catastrophic command detected'; + break; + } + } + + // Tier 2: Confirm — dangerous but sometimes legitimate + if (decision === 'allow') { + const confirmPatterns = [ + { pattern: /git\s+push\s+.*(-f|--force)/, label: 'git push --force (overwrites remote history)' }, + { pattern: /git\s+reset\s+--hard/, label: 'git reset --hard (discards all uncommitted changes)' }, + { pattern: /git\s+clean\s+-[a-z]*f/, label: 'git clean -f (permanently deletes untracked files)' }, + { pattern: /git\s+(checkout|restore)\s+\./, label: 'git checkout/restore . (discards all working tree changes)' }, + { pattern: /rm\s+-[rf]/, label: 'rm -rf (recursive/force delete)' }, + { pattern: /chmod\s+(-R\s+)?777/, label: 'chmod 777 (world-writable permissions)' }, + { pattern: /npm\s+publish/, label: 'npm publish (publishes package to registry)' }, + { pattern: /pip\s+upload|twine\s+upload/, label: 'pip/twine upload (publishes package to PyPI)' }, + { pattern: /docker\s+system\s+prune/, label: 'docker system prune (removes all unused resources)' }, + { pattern: /DROP\s+(DATABASE|TABLE)/i, label: 'SQL DROP (destroys database/table)' }, + { pattern: /DELETE\s+FROM\s+(?!.*WHERE)/i, label: 'DELETE without WHERE (deletes all rows)' }, + { pattern: /UPDATE\s+\S+\s+SET\s+(?!.*WHERE)/i, label: 'UPDATE without WHERE (updates all rows)' }, + { pattern: /TRUNCATE\s+TABLE/i, label: 'SQL TRUNCATE (empties entire table)' }, + ]; + + for (const { pattern, label } of confirmPatterns) { + if (pattern.test(command)) { + confirmLabel = label; + break; + } + } + } + +// === File write security check === +} else if (toolName === 'Write' || toolName === 'Edit') { + const filePath = input.tool_input?.file_path || ''; + const homeDir = os.homedir(); + const repoRoot = common.getRepoRoot(cwd); + const resolved = path.resolve(cwd, filePath); + + // Tier 1: Block — system paths + const sensitivePaths = [ + '/etc/', '/usr/bin/', '/usr/sbin/', + '/bin/', '/sbin/', '/System/', + '/dev/', '/proc/', '/sys/' + ]; + + for (const sp of sensitivePaths) { + if (filePath.startsWith(sp)) { + decision = 'deny'; + reason = `Writing to system path denied: ${sp}`; + break; + } + } + + // Block — outside repo and home + if (decision === 'allow') { + const insideRepo = isPathInside(repoRoot, resolved); + const insideHome = isPathInside(homeDir, resolved); + + if (!insideRepo && !insideHome) { + decision = 'deny'; + reason = 'Path traversal attack detected: resolved path is outside the repository and home directory'; + } else if (!insideRepo && insideHome) { + const relativeHomePath = path.relative(homeDir, resolved) || path.basename(resolved); + confirmLabel = `home directory path outside repo (~/${relativeHomePath})`; + } + } + + // Tier 2: Confirm — sensitive files + if (decision === 'allow') { + const fileName = path.basename(filePath); + + if (fileName.startsWith('.env')) { + confirmLabel = `.env file (${fileName})`; + } + + if (!confirmLabel) { + const sensitiveFiles = ['credentials.json', 'key.pem', 'key.json', 'id_rsa']; + for (const sf of sensitiveFiles) { + if (fileName === sf) { + confirmLabel = `sensitive file (${sf})`; + break; + } + } + } + + if (!confirmLabel) { + const sensitivePathPatterns = ['.aws/credentials', '.npmrc']; + for (const sp of sensitivePathPatterns) { + if (filePath.includes(sp)) { + confirmLabel = `sensitive path (${sp})`; + break; + } + } + } + } +} + +// === Build output === +if (decision === 'deny') { + const errorOutput = { + hookSpecificOutput: { permissionDecision: 'deny' }, + systemMessage: `🛑 Blocked: ${reason}\n\nTo perform this operation, run it manually in the terminal.` + }; + console.error(JSON.stringify(errorOutput)); + process.exit(2); +} else { + const result = { continue: true }; + + if (confirmLabel) { + result.systemMessage = `⚠️ CONFIRM REQUIRED: ${confirmLabel}\n\nYou MUST ask the user for explicit confirmation before executing this operation. Do NOT proceed without user approval.`; + } + + console.log(JSON.stringify(result)); + process.exit(0); +} diff --git a/文档润色流和知识库构建流/claude-scholar/hooks/session-start.js b/文档润色流和知识库构建流/claude-scholar/hooks/session-start.js new file mode 100644 index 0000000..8438856 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/hooks/session-start.js @@ -0,0 +1,185 @@ +#!/usr/bin/env node +/** + * SessionStart Hook: Display project status (cross-platform version) + * + * Event: SessionStart + * Function: Display project status, Git info, todos, plugins, and commands at session start + */ + +const path = require('path'); +const os = require('os'); +const fs = require('fs'); + +// Import shared utility library +const common = require('./hook-common'); + +// Import package manager detection +const { getPackageManager, getSelectionPrompt } = require('../scripts/lib/package-manager'); + +// Read stdin input +let input = {}; +try { + const stdinData = require('fs').readFileSync(0, 'utf8'); + if (stdinData.trim()) { + input = JSON.parse(stdinData); + } +} catch { + // Use default empty object +} + +const cwd = input.cwd || process.cwd(); +const projectName = path.basename(cwd); +const homeDir = os.homedir(); +const binding = common.getProjectMemoryBinding(cwd); +const researchCandidate = common.detectResearchProject(cwd); + +// Build output +let output = ''; + +// Session start info +output += `🚀 ${projectName} Session started\n`; +output += `▸ Time: ${common.formatDateTime()}\n`; +output += `▸ Directory: ${cwd}\n\n`; + +// Git status +const gitInfo = common.getGitInfo(cwd); + +if (gitInfo.is_repo) { + output += `▸ Git branch: ${gitInfo.branch}\n\n`; + + if (gitInfo.has_changes) { + output += `⚠️ Uncommitted changes (${gitInfo.changes_count} files):\n`; + + // Show change list (up to 5) + const statusIcons = { + 'M': '📝', // Modified + 'A': '➕', // Added + 'D': '❌', // Deleted + 'R': '🔄', // Renamed + '??': '❓' // Untracked + }; + + for (let i = 0; i < Math.min(gitInfo.changes.length, 5); i++) { + const change = gitInfo.changes[i]; + const status = change.substring(0, 2).trim(); + const file = change.substring(3).trim(); + + const icon = statusIcons[status] || '•'; + output += ` ${icon} ${file}\n`; + } + + if (gitInfo.changes_count > 5) { + output += ` ... (${gitInfo.changes_count - 5} more files)\n`; + } + } else { + output += `✅ Working directory clean\n`; + } + output += '\n'; +} else { + output += `▸ Git: Not a repository\n\n`; +} + +if (binding.bound) { + output += '🧠 Obsidian project KB: bound\n'; + output += ` - Project: ${binding.projectId || 'unknown'}\n`; + output += ` - Status: ${binding.status || 'unknown'}\n`; + output += ` - Auto-sync: ${binding.autoSync ? 'on' : 'off'}\n`; + if (binding.vaultRoot) { + output += ` - Vault root: ${binding.vaultRoot}\n`; + } + output += ' - Suggested commands: /kb-status, /kb-sync, /kb-lint\n\n'; +} else if (researchCandidate.candidate) { + output += '🧠 Obsidian project KB: research repo candidate\n'; + output += ` - Detected markers: ${researchCandidate.markers.join(', ')}\n`; + output += ' - Suggested command: /kb-init\n\n'; +} + +// Package manager detection +try { + const pm = getPackageManager(); + output += `📦 Package manager: ${pm.name} (${pm.source})\n`; + + // If detected via fallback, suggest setup + if (pm.source === 'fallback' || pm.source === 'default') { + output += `💡 Run /setup-pm to configure preferred package manager\n`; + } +} catch (err) { + // Package manager detection failed, silently ignore +} + +output += '\n'; + +// Todos +output += `📋 Todos:\n`; +const todoInfo = common.getTodoInfo(cwd); + +if (todoInfo.found) { + output += ` - ${todoInfo.pending} pending / ${todoInfo.done} completed\n`; + + // Show top 5 pending items + if (fs.existsSync(todoInfo.path)) { + try { + const content = fs.readFileSync(todoInfo.path, 'utf8'); + const pendingItems = content.match(/^[\-\*] \[ \].+$/gm) || []; + + if (pendingItems.length > 0) { + output += `\n Recent todos:\n`; + for (let i = 0; i < Math.min(5, pendingItems.length); i++) { + const item = pendingItems[i].replace(/^[\-\*] \[ \]\s*/, '').substring(0, 60); + output += ` - ${item}\n`; + } + } + } catch { + // Ignore errors + } + } +} else { + output += ` No todo file found (TODO.md, docs/todo.md etc)\n`; +} + +output += '\n'; + +// Enabled plugins +output += `🔌 Enabled plugins:\n`; +const enabledPlugins = common.getEnabledPlugins(homeDir); + +if (enabledPlugins.length > 0) { + for (let i = 0; i < Math.min(5, enabledPlugins.length); i++) { + output += ` - ${enabledPlugins[i].name}\n`; + } + if (enabledPlugins.length > 5) { + output += ` ... and ${enabledPlugins.length - 5} more plugins\n`; + } +} else { + output += ` None\n`; +} + +output += '\n'; + +// Available commands +output += `💡 Available commands:\n`; +const availableCommands = common.getAvailableCommands(homeDir); + +if (availableCommands.length > 0) { + for (const cmd of availableCommands.slice(0, 5)) { + const description = common.getCommandDescription(cmd.path) || `${cmd.plugin} command`; + const truncatedDesc = description.length > 40 ? description.substring(0, 40) + '...' : description; + output += ` /${cmd.name.padEnd(20)} ${truncatedDesc}\n`; + } + + if (availableCommands.length > 5) { + output += ` ... and ${availableCommands.length - 5} more commands, use /help to list all\n`; + } +} else { + output += ` No commands found\n`; +} + +// Output JSON +const result = { + continue: true, + systemMessage: output +}; + +console.log(JSON.stringify(result)); + +process.exit(0); diff --git a/文档润色流和知识库构建流/claude-scholar/hooks/session-summary.js b/文档润色流和知识库构建流/claude-scholar/hooks/session-summary.js new file mode 100644 index 0000000..9df4dc8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/hooks/session-summary.js @@ -0,0 +1,240 @@ +#!/usr/bin/env node +/** + * SessionEnd Hook: Work Log + Smart Suggestions (Cross-platform) + * + * Event: SessionEnd + * Purpose: Create work log, record changes and generate smart suggestions + */ + +const path = require('path'); +const fs = require('fs'); +const os = require('os'); +const common = require('./hook-common'); + +// Read stdin input +let input = {}; +try { + const stdinData = require('fs').readFileSync(0, 'utf8'); + if (stdinData.trim()) { + input = JSON.parse(stdinData); + } +} catch { + // Use default empty object +} + +const cwd = input.cwd || process.cwd(); +const sessionId = input.session_id || 'unknown'; +const transcriptPath = input.transcript_path || ''; +const binding = common.getProjectMemoryBinding(cwd); +const MAX_LOGGED_GIT_CHANGES = 20; +const MAX_LOGGED_MEMORY_CHANGES = 5; + +// Create work log directory +const logDir = path.join(cwd, '.claude', 'logs'); +fs.mkdirSync(logDir, { recursive: true }); + +// Generate log filename +const now = new Date(); +const dateStr = now.toISOString().split('T')[0].replace(/-/g, ''); +const logFile = path.join(logDir, `session-${dateStr}-${sessionId.substring(0, 8)}.md`); + +// Get project info +const projectName = path.basename(cwd); + +// Build log content +let logContent = ''; + +logContent += `# 📝 Work Log - ${projectName}\n`; +logContent += `\n`; +logContent += `**Session ID**: ${sessionId}\n`; +logContent += `**Time**: ${common.formatDateTime(now)}\n`; +logContent += `**Directory**: ${cwd}\n`; +logContent += `\n`; + +// Git change statistics +logContent += `## 📊 Session Changes\n`; +const gitInfo = common.getGitInfo(cwd); +const changesDetails = gitInfo.is_repo ? common.getChangesDetails(cwd) : { added: 0, modified: 0, deleted: 0 }; + +if (gitInfo.is_repo) { + logContent += `**Branch**: ${gitInfo.branch}\n`; + logContent += `\n`; + const shownGitChanges = gitInfo.changes.slice(0, MAX_LOGGED_GIT_CHANGES); + logContent += '```\n'; + + if (gitInfo.has_changes) { + for (const change of shownGitChanges) { + logContent += `${change}\n`; + } + if (gitInfo.changes.length > MAX_LOGGED_GIT_CHANGES) { + logContent += `... (${gitInfo.changes.length - MAX_LOGGED_GIT_CHANGES} more changes omitted)\n`; + } + } else { + logContent += 'No changes\n'; + } + + logContent += '```\n'; + + // Change statistics + logContent += `\n`; + logContent += '| Type | Count |\n'; + logContent += '|------|------|\n'; + logContent += `| Added | ${changesDetails.added} |\n`; + logContent += `| Modified | ${changesDetails.modified} |\n`; + logContent += `| Deleted | ${changesDetails.deleted} |\n`; +} else { + logContent += 'Not a Git repository\n'; +} + +logContent += `\n`; + +if (binding.bound) { + logContent += `## 🧠 Obsidian Project Memory\n`; + logContent += `\n`; + logContent += `- Project: ${binding.projectId || 'unknown'}\n`; + logContent += `- Status: ${binding.status || 'unknown'}\n`; + logContent += `- Auto-sync: ${binding.autoSync ? 'on' : 'off'}\n`; + if (binding.vaultRoot) { + logContent += `- Vault root: ${binding.vaultRoot}\n`; + } + logContent += `- Minimum write-back to verify after research-state turns:\n`; + logContent += ` - Daily/YYYY-MM-DD.md\n`; + logContent += ` - ${binding.memoryPath || '.claude/project-memory/.md'}\n`; + logContent += ` - 00-Hub.md (only when top-level project status changes)\n`; + logContent += `\n`; +} + +// Read transcript to extract key operations (if available) +if (transcriptPath && fs.existsSync(transcriptPath)) { + try { + const transcript = fs.readFileSync(transcriptPath, 'utf8'); + const toolMatches = transcript.match(/Tool used: [A-Z][a-z]*/g) || []; + + if (toolMatches.length > 0) { + // Count tool usage + const toolCounts = {}; + for (const match of toolMatches) { + const tool = match.replace('Tool used: ', ''); + toolCounts[tool] = (toolCounts[tool] || 0) + 1; + } + + // Sort and take top 10 + const sortedTools = Object.entries(toolCounts) + .sort((a, b) => b[1] - a[1]) + .slice(0, 10); + + if (sortedTools.length > 0) { + logContent += `## 🔧 Key Operations\n`; + logContent += `\n`; + + for (const [tool, count] of sortedTools) { + logContent += `| ${tool} | ${count} times |\n`; + } + + logContent += `\n`; + } + } + } catch { + // Ignore errors + } +} + +// Next steps +logContent += `## 🎯 Next Steps\n`; +logContent += `\n`; + +if (gitInfo.has_changes) { + logContent += `- ⚠️ Uncommitted changes detected (${gitInfo.changes_count} files)\n`; +} else { + logContent += '- ✅ Working directory clean\n'; +} + +// Todo reminders +const todoInfo = common.getTodoInfo(cwd); +if (todoInfo.found) { + logContent += `- Update todos: ${todoInfo.file} (${todoInfo.pending} pending)\n`; +} + +// CLAUDE.md memory update check +const homeDir = os.homedir(); +const claudeMdCheck = common.checkClaudeMdUpdate(homeDir); + +if (claudeMdCheck.needsUpdate) { + logContent += `- ⚠️ **CLAUDE.md memory needs updating** (${claudeMdCheck.changedFiles.length} source files changed)\n`; + logContent += ` Run "/update-memory" to sync latest memory\n`; + + // Record change details to log + logContent += `\n`; + logContent += `### CLAUDE.md Change Details\n`; + logContent += `\n`; + logContent += `| Type | File | Modified |\n`; + logContent += `|------|------|----------|\n`; + for (const file of claudeMdCheck.changedFiles.slice(0, MAX_LOGGED_MEMORY_CHANGES)) { + logContent += `| ${file.type} | ${file.relativePath} | ${file.mtime} |\n`; + } + if (claudeMdCheck.changedFiles.length > MAX_LOGGED_MEMORY_CHANGES) { + logContent += `| ... | ${claudeMdCheck.changedFiles.length - MAX_LOGGED_MEMORY_CHANGES} more files omitted | ... |\n`; + } +} else { + logContent += `- ✅ CLAUDE.md memory is up to date\n`; +} + +logContent += '- View context snapshot: `cat .claude/session-context-*.md`\n'; +logContent += `\n`; + +// Write log file +fs.writeFileSync(logFile, logContent, 'utf8'); + +// Clean up old log files (older than 30 days) +try { + const maxAge = 30 * 24 * 60 * 60 * 1000; + const files = fs.readdirSync(logDir).filter(f => f.startsWith('session-') && f.endsWith('.md')); + for (const file of files) { + const filePath = path.join(logDir, file); + const stat = fs.statSync(filePath); + if (now.getTime() - stat.mtimeMs > maxAge) { + fs.unlinkSync(filePath); + } + } +} catch { + // Log cleanup failure should not affect main flow +} + +// Build message to display to user +let displayMsg = '\n---\n'; +displayMsg += '✅ **Session ended** | Work log saved\n\n'; +displayMsg += '**Changes**: '; + +if (gitInfo.is_repo) { + if (gitInfo.has_changes) { + displayMsg += `${gitInfo.changes_count} files\n\n`; + displayMsg += '**Suggested actions**:\n'; + displayMsg += `- View log: cat .claude/logs/${path.basename(logFile)}\n`; + displayMsg += '- Commit code: git add . && git commit -m "feat: xxx"\n'; + if (binding.bound) { + displayMsg += '- Verify bound Obsidian updates: Daily/YYYY-MM-DD.md and .claude/project-memory/.md; touch 00-Hub.md only when top-level project status changes\n'; + } + } else { + displayMsg += 'None\n\nWorking directory clean ✅\n'; + } +} else { + displayMsg += 'Not a Git repository\n'; +} + +// Add CLAUDE.md update reminder to display message +if (claudeMdCheck.needsUpdate) { + displayMsg += '\n**⚠️ CLAUDE.md memory needs updating**\n'; + displayMsg += `- ${claudeMdCheck.changedFiles.length} source files changed\n`; + displayMsg += '- Run `/update-memory` to sync latest memory\n'; +} + +displayMsg += '\n---'; + +const result = { + continue: true, + systemMessage: displayMsg +}; + +console.log(JSON.stringify(result)); + +process.exit(0); diff --git a/文档润色流和知识库构建流/claude-scholar/hooks/skill-forced-eval.js b/文档润色流和知识库构建流/claude-scholar/hooks/skill-forced-eval.js new file mode 100644 index 0000000..1bad40d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/hooks/skill-forced-eval.js @@ -0,0 +1,235 @@ +#!/usr/bin/env node +/** + * UserPromptSubmit Hook: Forced skill activation flow (cross-platform version) + * + * Event: UserPromptSubmit + * Function: Force AI to evaluate available skills and begin implementation after activation + */ + +const path = require('path'); +const fs = require('fs'); +const os = require('os'); +const common = require('./hook-common'); + +// Read stdin input +let input = {}; +try { + const stdinData = require('fs').readFileSync(0, 'utf8'); + if (stdinData.trim()) { + input = JSON.parse(stdinData); + } +} catch { + // Use default empty object +} + +const userPrompt = input.user_prompt || ''; +const cwd = input.cwd || process.cwd(); + +// Check if it is a slash command (escape) +if (userPrompt.startsWith('/')) { + // Distinguish commands from paths: + // - Commands: /commit, /update-github (no second slash after the first) + // - Paths: /Users/xxx, /path/to/file (contains path separators) + const rest = userPrompt.substring(1); + if (rest.includes('/')) { + // This is a path, continue with skill scanning + } else { + // This is a command, skip skill evaluation + console.log(JSON.stringify({ continue: true })); + process.exit(0); + } +} + +const homeDir = os.homedir(); + +// Dynamically collect skill list +function collectSkills() { + const skills = []; + const skillsDir = path.join(homeDir, '.claude', 'skills'); + + // 1. Collect local skills + if (fs.existsSync(skillsDir)) { + const skillDirs = fs.readdirSync(skillsDir, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name); + + for (const skillName of skillDirs) { + skills.push(skillName); + } + } + + // 2. Collect plugin skills + const pluginsCache = path.join(homeDir, '.claude', 'plugins', 'cache'); + + if (fs.existsSync(pluginsCache)) { + const marketplaces = fs.readdirSync(pluginsCache, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name); + + for (const marketplace of marketplaces) { + const marketplacePath = path.join(pluginsCache, marketplace); + const plugins = fs.readdirSync(marketplacePath, { withFileTypes: true }) + .filter(d => d.isDirectory() && !d.name.startsWith('.')) + .map(d => d.name); + + for (const plugin of plugins) { + const pluginPath = path.join(marketplacePath, plugin); + const versions = fs.readdirSync(pluginPath, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name) + .sort() + .reverse(); + + if (versions.length > 0) { + const latestVersion = versions[0]; + const skillsDirPath = path.join(pluginPath, latestVersion, 'skills'); + + if (fs.existsSync(skillsDirPath)) { + const skillDirs = fs.readdirSync(skillsDirPath, { withFileTypes: true }) + .filter(d => d.isDirectory()) + .map(d => d.name); + + for (const skillName of skillDirs) { + skills.push(`${plugin}:${skillName}`); + } + } + } + } + } + } + + // Deduplicate + return [...new Set(skills)].sort(); +} + +// Categorize skills into groups +function categorizeSkills(skills) { + const categories = { + 'Research & Writing': /research|paper|writing|citation|review-response|rebuttal|post-acceptance|doc-coauthoring|latex|daily-paper|ml-paper|results-analysis|results-report|brainstorm/, + 'Development': /coding|git|code-review|bug|architecture|verification|tdd|uv-package|webapp-testing|kaggle|driven-development|development-branch|planning|dispatching|executing|using-superpowers/, + 'Plugin Dev': /skill-|command-|hook-|mcp-|agent-identifier|plugin-structure/, + 'Design & UI': /frontend|ui-ux|web-design|canvas|brand|theme|algorithmic-art|slack-gif|figma/, + 'Documents': /docx|xlsx|pptx|pdf|internal-comms|web-artifacts/, + }; + + const grouped = {}; + for (const cat of Object.keys(categories)) { + grouped[cat] = []; + } + grouped['Other'] = []; + + for (const skill of skills) { + let matched = false; + for (const [cat, regex] of Object.entries(categories)) { + if (regex.test(skill)) { + grouped[cat].push(skill); + matched = true; + break; + } + } + if (!matched) { + grouped['Other'].push(skill); + } + } + + return grouped; +} + +// Keyword-to-skill mapping for pre-matching +// Note: \b doesn't work with CJK characters, so we use separate patterns +// English keywords use \b for precision; Chinese keywords match without \b +const KEYWORD_SKILL_MAP = [ + { keywords: /\b(git|github|commit|push|pull|merge|rebase|branch|tag|stash|cherry.?pick|develop|master|main)\b|分支|合并|推送|提交代码|上传.*分支|主分支/i, skills: ['git-workflow'] }, + { keywords: /\b(debug|bug|error|broken|failing|traceback|exception)\b|排查|调试|报错|出错|不工作/i, skills: ['bug-detective'] }, + { keywords: /\b(tdd|test.?driven)\b|写测试|测试驱动/i, skills: ['superpowers:test-driven-development'] }, + { keywords: /\b(code.?review|review code)\b|审查代码|代码审查/i, skills: ['code-review-excellence'] }, + { keywords: /\b(paper|manuscript|draft)\b|论文|写作|投稿/i, skills: ['ml-paper-writing'] }, + { keywords: /\b(research|idea|brainstorm)\b|研究|构思|文献/i, skills: ['research-ideation'] }, + { keywords: /\b(rebuttal|reviewer|response to reviewer)\b|审稿|回复审稿/i, skills: ['review-response'] }, + { keywords: /\b(frontend|landing.?page|dashboard)\b|前端|界面|网页设计/i, skills: ['frontend-design'] }, + { keywords: /\b(create|write|develop|improve).*skill|skill.*(开发|创建|写|改进)|开发.*skill|写.*skill|改进.*skill/i, skills: ['skill-development'] }, + { keywords: /\b(create|write|develop).*hook|hook.*(开发|创建|写)|开发.*hook|写.*hook/i, skills: ['hook-development'] }, + { keywords: /\b(create|write|develop).*command|slash.*command|command.*(开发|创建|写)|开发.*command|写.*命令/i, skills: ['command-development'] }, + { keywords: /\b(create|write|develop).*agent|agent.*(开发|创建|写)|开发.*agent|写.*agent/i, skills: ['agent-identifier'] }, + { keywords: /\b(mcp)\b|mcp.*server|mcp.*集成/i, skills: ['mcp-integration'] }, + { keywords: /\b(architecture|factory|registry)\b|架构|设计模式/i, skills: ['architecture-design'] }, + { keywords: /\b(uv|pip|package.*manager|venv)\b|包管理|虚拟环境/i, skills: ['uv-package-manager'] }, + { keywords: /\b(kaggle|competition)\b|竞赛/i, skills: ['kaggle-learner'] }, + { keywords: /\b(citation|reference.*check)\b|引用|引文|参考文献/i, skills: ['citation-verification'] }, + { keywords: /\b(latex.*template|overleaf)\b|模板整理/i, skills: ['latex-conference-template-organizer'] }, + { keywords: /\b(ablation)\b|实验结果|results.*analysis|统计检验|消融实验|科学绘图|实验统计/i, skills: ['results-analysis'] }, + { keywords: /\b(experiment.?report|results.?report|retrospective|wrap.?up)\b|实验报告|实验总结|实验复盘|结果总结/i, skills: ['results-report'] }, + { keywords: /\b(poster|presentation|promote)\b|海报|演讲|推广/i, skills: ['post-acceptance'] }, + { keywords: /\b(verify|verification)\b|验证/i, skills: ['verification-loop'] }, + { keywords: /\b(self.?review)\b|自审|论文检查/i, skills: ['paper-self-review'] }, + { keywords: /\b(anti.?ai|humanize)\b|去.*ai.*痕迹|AI写作/i, skills: ['writing-anti-ai'] }, + { keywords: /\b(implement|write code|add feature|modify|refactor)\b|写代码|改代码|实现|添加功能|修改|重构/i, skills: ['daily-coding'] }, +]; + +// Pre-match user prompt against keyword map +function suggestSkills(prompt) { + const suggested = new Set(); + for (const { keywords, skills } of KEYWORD_SKILL_MAP) { + if (keywords.test(prompt)) { + for (const s of skills) suggested.add(s); + } + } + return [...suggested]; +} + +// Generate skill list +const SKILL_LIST = collectSkills(); +const SKILL_GROUPS = categorizeSkills(SKILL_LIST); +const suggestedSkills = suggestSkills(userPrompt); +const binding = common.getProjectMemoryBinding(cwd); +const isResearchPrompt = common.promptLooksResearchRelated(userPrompt); + +if (binding.bound && isResearchPrompt) { + if (SKILL_LIST.includes('obsidian-project-kb-core')) { + suggestedSkills.push('obsidian-project-kb-core'); + } + if (/\b(zotero|collection|doi|arxiv|citation)\b|zotero|文献|参考文献|collection/i.test(userPrompt) && + SKILL_LIST.includes('zotero-obsidian-bridge')) { + suggestedSkills.push('zotero-obsidian-bridge'); + } + if (/\b(paper|papers|literature|review|claim|method|evidence)\b|论文|综述|paper/i.test(userPrompt) && + SKILL_LIST.includes('obsidian-literature-workflow')) { + suggestedSkills.push('obsidian-literature-workflow'); + } +} + +const dedupedSuggestedSkills = [...new Set(suggestedSkills)]; + +// Format grouped skills (skip empty groups) +const groupedDisplay = Object.entries(SKILL_GROUPS) + .filter(([, skills]) => skills.length > 0) + .map(([cat, skills]) => `[${cat}] ${skills.join(', ')}`) + .join('\n'); + +// Build suggested skills hint +const suggestedHint = dedupedSuggestedSkills.length > 0 + ? `\n**Pre-matched skills (MUST activate these)**: ${dedupedSuggestedSkills.join(', ')}\nThese skills matched keywords in the user's prompt. You MUST activate them via Skill tool.\n` + : ''; + +const boundRepoHint = binding.bound && isResearchPrompt + ? `\n**Bound Obsidian repo detected**: ${binding.projectId || 'unknown-project'}\nUse lightweight curator behavior by default: keep \`Daily/YYYY-MM-DD.md\` and \`.claude/project-memory/.md\` in sync when this turn changes research state, and touch \`00-Hub.md\` only when top-level project status really changes. Prefer \`obsidian-project-kb-core\` by default, and add \`obsidian-source-ingestion\`, \`obsidian-literature-workflow\`, or \`obsidian-kb-artifacts\` only when the task clearly needs them.\n` + : ''; + +// Generate output +const output = `## Instruction: Forced Skill Activation (Mandatory) + +Silently scan the user's request against available skills. Do NOT list every skill with Yes/No. + +Available skills: +${groupedDisplay} +${suggestedHint}${boundRepoHint} +**Action**: +- If any skill matches → Activate via Skill tool, then output: "Activating: [skill-name] — [reason]" +- If no skill matches → Output: "No skills needed" +- Begin implementation only after activation is complete. +- When multiple skills match, activate all of them. +`; + +console.log(output); + +process.exit(0); diff --git a/文档润色流和知识库构建流/claude-scholar/hooks/stop-summary.js b/文档润色流和知识库构建流/claude-scholar/hooks/stop-summary.js new file mode 100644 index 0000000..ff20af5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/hooks/stop-summary.js @@ -0,0 +1,124 @@ +#!/usr/bin/env node +/** + * Stop Hook: Display basic status + AI summary prompt (Cross-platform) + * + * Event: Stop + * Purpose: Display Git status, change statistics and temp files when session stops + */ + +const common = require('./hook-common'); + +// Read stdin input +let input = {}; +try { + const stdinData = require('fs').readFileSync(0, 'utf8'); + if (stdinData.trim()) { + input = JSON.parse(stdinData); + } +} catch { + // Use default empty object +} + +const cwd = input.cwd || process.cwd(); +const reason = input.reason || 'task_complete'; +const binding = common.getProjectMemoryBinding(cwd); +const path = require('path'); + +function getTempBucket(file) { + const normalized = file.replace(/\\/g, '/'); + const knownRoots = ['plan', 'docs/plans', '.claude/temp', 'tmp', 'temp']; + + for (const root of knownRoots) { + if (normalized === root || normalized.startsWith(`${root}/`)) { + return root; + } + } + + const dirname = path.dirname(normalized); + if (dirname === '.' || dirname === '') { + return '.'; + } + + return normalized.split('/')[0]; +} + +// Build message +function buildMessage() { + let msg = '\n---\n'; + msg += '✅ Session ended\n\n'; + + // Git info + const gitInfo = common.getGitInfo(cwd); + + if (gitInfo.is_repo) { + msg += '📁 Git repository\n'; + msg += ` Branch: ${gitInfo.branch}\n`; + + if (gitInfo.has_changes) { + const changesDetails = common.getChangesDetails(cwd); + + msg += ' Changes:\n'; + if (changesDetails.added > 0) msg += ` 增加: ${changesDetails.added} files\n`; + if (changesDetails.modified > 0) msg += ` 修改: ${changesDetails.modified} files\n`; + if (changesDetails.deleted > 0) msg += ` 删除: ${changesDetails.deleted} files\n`; + } else { + msg += ' Status: clean\n'; + } + } else { + msg += '📁 Not a Git repository\n'; + } + + msg += '\n'; + + // Temp file detection + const tempInfo = common.detectTempFiles(cwd); + + if (tempInfo.count > 0) { + msg += `🧹 Temp files: ${tempInfo.count}\n`; + + const grouped = {}; + for (const file of tempInfo.files) { + const dir = getTempBucket(file); + if (!grouped[dir]) grouped[dir] = []; + grouped[dir].push(file); + } + + const orderedGroups = Object.entries(grouped).sort(([a], [b]) => { + if (a === '.' && b !== '.') return -1; + if (a !== '.' && b === '.') return 1; + return a.localeCompare(b); + }); + + for (const [dir, files] of orderedGroups) { + const label = dir === '.' ? './' : `${dir}/`; + msg += ` 📂 ${label} (${files.length})\n`; + } + } else { + msg += '✅ No temp files\n'; + } + + if (binding.bound) { + msg += '\n🧠 Bound Obsidian KB\n'; + msg += ` Project: ${binding.projectId || 'unknown'}\n`; + msg += ' Minimum maintenance after research-state turns:\n'; + msg += ' • Daily/YYYY-MM-DD.md\n'; + msg += ` • ${binding.memoryPath || '.claude/project-memory/.md'}\n`; + msg += ' • 00-Hub.md (only when top-level project status changes)\n'; + } + + msg += '---'; + + return msg; +} + +// Build and return +const systemMessage = buildMessage(); + +const result = { + continue: true, + systemMessage: systemMessage +}; + +console.log(JSON.stringify(result)); + +process.exit(0); diff --git a/文档润色流和知识库构建流/claude-scholar/plugins/install-counts-cache.json b/文档润色流和知识库构建流/claude-scholar/plugins/install-counts-cache.json new file mode 100644 index 0000000..fd90418 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/plugins/install-counts-cache.json @@ -0,0 +1,486 @@ +{ + 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rebuttal-writer | Systematic rebuttal writing with tone optimization | Responding to reviewer comments | +| paper-miner | Extract writing knowledge from successful papers | Learning writing patterns from top-venue papers | +| kaggle-miner | Extract engineering practices from Kaggle solutions | Learning competition strategies and pipelines | + +### Development Workflow + +| Agent | Purpose | When to Use | +|-------|---------|-------------| +| code-reviewer | Code quality, security, and maintainability review | After writing or modifying code | +| tdd-guide | Test-driven development workflow | When the user explicitly wants test-first implementation | + +## Automatic Agent Invocation + +Use agents proactively without waiting for user request: + +1. Code just written/modified → **code-reviewer** +2. New literature survey or topic exploration → **literature-reviewer** +3. Rebuttal drafting → **rebuttal-writer** +4. Writing-pattern mining from strong papers → **paper-miner** +5. Kaggle workflow mining → **kaggle-miner** +6. Explicit test-first implementation request → **tdd-guide** + +## Parallel Task Execution + +ALWAYS use parallel Task execution for independent operations: + +```markdown +# GOOD: Parallel execution +Launch 3 agents in parallel: +1. Agent 1: code-reviewer on auth module +2. Agent 2: literature-reviewer on baseline papers +3. Agent 3: paper-miner on a target venue paper + +# BAD: Sequential when unnecessary +First agent 1, then agent 2, then agent 3 +``` + +## Error Handling + +- If an agent fails or times out, retry once before reporting to user +- Log agent errors for debugging +- Fall back to manual approach if agent is unavailable + +## Multi-Perspective Analysis + +For complex problems, use split-role sub-agents: +- Factual reviewer +- Senior engineer +- Security expert +- Consistency reviewer +- Redundancy checker diff --git a/文档润色流和知识库构建流/claude-scholar/rules/claude-scholar-core.md b/文档润色流和知识库构建流/claude-scholar/rules/claude-scholar-core.md new file mode 100644 index 0000000..e9153ff --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/rules/claude-scholar-core.md @@ -0,0 +1,220 @@ +# Claude Scholar Core Rule +## Purpose +This rule defines the always-on, cross-cutting defaults of Claude Scholar and preserves core guidance that may otherwise be lost when repository-provided `CLAUDE.md` content is installed as a sidecar file such as `CLAUDE.scholar.md` instead of the exact auto-loaded `CLAUDE.md`. +This file should keep only stable core behavior: +- user background and quality bar, +- communication defaults, +- workspace conventions, +- execution principles, +- research workflow routing, +- Obsidian project-memory defaults, +- naming conventions, +- task closeout format. +This file should not become a second catalog of skills, commands, agents, hooks, or specialized rules. Detailed implementation policy belongs in the corresponding dedicated rule or component file. + +--- +## Claude Scholar Identity +Claude Scholar is a semi-automated research assistant for: +- academic research, +- ML and software development, +- experiment planning and analysis, +- paper writing and review, +- publication support, +- plugin and workflow engineering, +- durable project knowledge management. +Its default posture should prioritize: +- correctness over speed, +- explicit workflow routing over ad hoc improvisation, +- reproducibility over one-off output, +- durable knowledge capture over ephemeral chat-only advice, +- clear next actions over vague brainstorming. + +--- +## User Background and Quality Bar +Assume the primary user is a Computer Science PhD-level researcher. +Typical target venues include: +- NeurIPS, ICML, ICLR, KDD, ACL, AAAI, +- Nature, Science, Cell, PNAS. +Default quality expectations: +- strong logical coherence, +- precise technical writing, +- natural expression rather than inflated AI-style wording, +- arguments that can survive academic scrutiny, +- outputs that can be reused in real research workflows. +When helping with research or writing, optimize for artifacts that can realistically feed into: +- project plans, +- experiment logs, +- paper drafts, +- rebuttals, +- presentations, +- durable project memory. + +--- +## Preferred Technical Defaults +When the user does not specify otherwise, prefer these defaults. +### Python Ecosystem +- package management: `uv` +- configuration: Hydra + OmegaConf +- training baseline: Transformers Trainer when appropriate +These are preferences, not hard constraints. If a repository clearly uses another stack, follow the repository. +### Git Conventions +- use Conventional Commits, +- keep history understandable, +- prefer small and reviewable diffs, +- avoid mixing unrelated changes, +- prefer rebase for branch sync and explicit integration merges when needed. + +--- +## Language and Communication Defaults +### Response Language +Default user-facing communication should: +- respond in English, +- keep technical terms in English, +- avoid translating proper nouns, tool names, venue names, or established terminology. +### Communication Style +Claude Scholar should be: +- direct, +- precise, +- operational, +- minimally performative, +- suitable for a technically advanced user. +When uncertainty matters: +- ask instead of bluffing, +- surface key assumptions, +- confirm before important or disruptive operations, +- distinguish facts, inferences, and recommendations. +For complex work, prefer this order: +1. main path, +2. concrete file / command / workflow impact, +3. verification path, +4. edge conditions or follow-up notes. + +--- +## Workspace Conventions +Use these defaults unless the repository already provides a better local convention: +- `/plan` for planning documents, decision notes, and implementation breakdowns, +- `/temp` for temporary files, scratch output, and disposable intermediates. +Create these directories when needed. +After the task: +- clean up obvious throwaway artifacts, +- keep only files with durable value, +- avoid leaving confusing intermediate drafts unless intentionally retained. + +--- +## Task Execution Principles +### Discuss Before Large Changes +For complex or multi-step work, align on the approach before silently committing to a large direction. This does not require asking permission before every small edit. It means major trade-offs should be surfaced instead of assumed. +### Preserve Existing Functionality +Default to non-destructive behavior: +- avoid breaking working paths, +- preserve user-local customizations when reasonable, +- prefer additive or sidecar installation when replacement would erase user intent, +- keep rollback paths obvious. +### Verify With Real Checks +After meaningful implementation work, run an appropriate verification pass when feasible, such as: +- example commands, +- linting, +- tests, +- smoke checks, +- file or diff inspection, +- path validation, +- configuration parsing. +Do not claim success without evidence when verification is practical. +### Prefer Reusable Workflow +When possible, leave behind reusable value such as: +- a clean rule, +- a durable note, +- a documented pattern, +- a reusable script, +- a stable template, +- a well-scoped patch. +### Keep Changes Reviewable +Favor small, coherent diffs. If several improvements are unrelated, separate them instead of bundling them into one noisy change set. + +--- +## Work Style and Planning Discipline +For non-trivial work: +- plan before executing, +- prefer existing skills, rules, and agents before inventing a new path, +- route work through the appropriate workflow instead of answering everything in one undifferentiated blob, +- keep progress visible across multi-step tasks. +Claude Scholar should act like a workflow-aware collaborator, not just a text generator. That means: +- checking local repository context when relevant, +- respecting project structure, +- preferring minimal-diff changes, +- producing outputs that fit the user's real environment. + +--- +## Research Lifecycle Routing +Claude Scholar should treat research support as a staged lifecycle: +`Ideation -> ML Development -> Experiment Analysis -> Paper Writing -> Self-Review -> Submission/Rebuttal -> Post-Acceptance` +When a request is ambiguous, infer the stage and respond with stage-appropriate standards. +### Stage Focus +- Ideation: research questions, gap analysis, literature framing, early project definition. +- ML Development: architecture choices, implementation plans, coding workflow, testable engineering changes. +- Experiment Analysis: metrics, comparisons, ablations, error analysis, statistical rigor, interpretable summaries. +- Paper Writing: argument structure, section drafting, citation quality, venue-aware standards. +- Self-Review: internal critique, completeness checks, missing evidence, consistency. +- Submission/Rebuttal: reviewer response quality, evidence-backed rebuttals, tone control, deadline triage. +- Post-Acceptance: presentations, posters, promotion materials, publication-facing packaging. +Do not flatten all stages into one generic workflow. Preserve stage-specific expectations and route the user toward the right tools, skills, or artifacts for the actual phase of work. + +--- +## Obsidian Project Knowledge Base Default +Obsidian project memory is a default durable sink for research work. +Activation rules: +- if the current repository contains `.claude/project-memory/registry.yaml`, treat it as already bound to project memory, +- in that case, activate Obsidian-oriented behavior by default, +- if the repository is not yet bound but clearly looks like a research project, default to bootstrap/import behavior rather than ignoring durable knowledge capture. +Minimum maintenance behavior: +- for substantial research turns, maintain at least the daily note and the repo-local project memory, +- update top-level hub pages such as `00-Hub.md` only when top-level project state actually changes. +Workflow boundary: +- filesystem-first, +- no mandatory Obsidian MCP, +- no extra API key requirement, +- should remain usable even when operating only on the filesystem. + +--- +## Naming Conventions +### Skill Naming +- use kebab-case, +- prefer lowercase with hyphens, +- prefer gerund-style names when natural. +Examples: `scientific-writing`, `git-workflow`, `bug-detective`. +### Tags Naming +- use Title Case, +- keep standard abbreviations fully capitalized. +Examples: `TDD`, `RLHF`, `NeurIPS`, `ICLR`. +### Description Standards +Descriptions should: +- use third-person phrasing, +- describe both purpose and usage context, +- be concrete enough to guide routing. +Avoid vague descriptions that say only what something is without saying when it should be used. + +--- +## Task Completion Summary Format +After each meaningful task, proactively provide a concise closeout in this shape: +```text +📋 Operation Review +1. [Main operation] +2. [Modified files] + +📊 Current Status +• [Git/filesystem/runtime status] + +💡 Next Steps +1. [Targeted suggestions] +``` +The closeout should help the user quickly understand what changed, where it changed, the current state, and what should happen next. + +--- +## Relationship to Other Rules +This rule owns only the always-on core behavior of Claude Scholar. +Specialized concerns remain delegated: +- agent selection and orchestration -> `rules/agents.md` +- security and secrets handling -> `rules/security.md` +- coding and architecture style -> `rules/coding-style.md` +- experiment logging and reproducibility -> `rules/experiment-reproducibility.md` +Do not duplicate those files here unless a requirement truly belongs at the cross-cutting core layer. diff --git a/文档润色流和知识库构建流/claude-scholar/rules/coding-style.md b/文档润色流和知识库构建流/claude-scholar/rules/coding-style.md new file mode 100644 index 0000000..c7dc650 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/rules/coding-style.md @@ -0,0 +1,250 @@ +# Code Style Rule + +Enforce code style standards for ML projects to ensure maintainability and consistency. + +## Core Principles + +### Small File Principle (200-400 lines) + +- Keep each file within 200-400 lines +- Split into multiple modules when exceeding 400 lines +- Organize related functionality under the same directory + +**Example structure:** +``` +src/model_module/ +├── brain_decoder/ +│ ├── __init__.py # Factory & Registry (50 lines) +│ ├── base_model.py # Base class (200 lines) +│ ├── transformer.py # Transformer impl (300 lines) +│ └── cnn.py # CNN impl (250 lines) +``` + +### Immutability First + +- Use dataclass for configuration (immutable) +- Avoid mutating input parameters inside functions +- Use `@dataclass(frozen=True)` to ensure config immutability + +```python +from dataclasses import dataclass + +@dataclass(frozen=True) +class ModelConfig: + hidden_dim: int + num_layers: int + dropout: float = 0.1 +``` + +### Error Handling + +- Use try/except for exception handling +- Catch specific exception types, avoid bare except +- Log error information for debugging + +```python +try: + data = load_data(path) +except FileNotFoundError as e: + logger.error(f"Data file not found: {path}") + raise +``` + +### Type Hints + +- All functions must have type hints +- Use types from the typing module +- Use TypeVar for complex types + +```python +from typing import Dict, List, Optional, TypeVar + +T = TypeVar('T', bound=Dataset) + +def process_data(data: List[Dict], config: Config) -> Optional[DataFrame]: + ... +``` + +## Python Specific Standards + +### Import Order + +```python +# 1. Standard library +import os +from pathlib import Path + +# 2. Third-party libraries +import torch +import numpy as np +from hydra import compose, initialize + +# 3. Local modules +from src.data_module import DataLoader +from src.model_module import Model +``` + +### Naming Conventions + +```python +# Class names: PascalCase +class DataLoader: + pass + +# Functions/variables: snake_case +def load_config(): + batch_size = 32 + +# Constants: UPPER_SNAKE_CASE +MAX_EPOCHS = 100 +DEFAULT_LR = 0.001 + +# Private: underscore prefix +def _internal_function(): + pass +``` + +### Docstrings + +```python +def train_model(cfg: Config) -> Model: + """Train the model. + + Args: + cfg: Training configuration object. + + Returns: + Trained model instance. + + Raises: + ValueError: When configuration is invalid. + """ + ... +``` + +## ML Project Specific Standards + +### Factory & Registry Pattern + +All modules must use factory and registry patterns: + +```python +# dataset/__init__.py +DATASET_FACTORY: Dict[str, Type[Dataset]] = {} + +def register_dataset(name: str): + def decorator(cls): + DATASET_FACTORY[name] = cls + return cls + return decorator + +def DatasetFactory(name: str) -> Type[Dataset]: + return DATASET_FACTORY.get(name, SimpleDataset) +``` + +### Config-Driven Models + +Model `__init__` should only accept a `cfg` parameter: + +```python +@register_model('MyModel') +class MyModel(nn.Module): + def __init__(self, cfg: Config): + super().__init__() + # All hyperparameters from cfg + self.hidden_dim = cfg.model.hidden_dim +``` + +### Directory Structure + +``` +run/ +├── conf/ # Hydra configs +├── pipeline/ # Workflow scripts +└── outputs/ # Output directory + +src/ +├── data_module/ # Data module +│ ├── dataset/ +│ ├── augmentation/ +│ └── utils.py +├── model_module/ # Model module +├── trainer_module/ # Trainer module +└── utils/ # Shared utilities +``` + +## Prohibited Patterns + +❌ **Prohibited:** +- Files exceeding 800 lines +- Nesting deeper than 4 levels +- Mutable default arguments: `def foo(a=[]):` +- Global variables (use config instead) +- Bare except: `except:` +- Hardcoded hyperparameters (use cfg) +- Unused imports +- print() debug statements (use logger) + +✅ **Recommended:** +- Split large files +- Use early returns to reduce nesting +- `def foo(a=None):` +- Config-driven parameters +- Specific exception catching +- Type hints +- Docstrings +- Logger for logging + +## Verification Checklist + +Before committing code, ensure: + +```bash +# Type checking +mypy src/ + +# Code style +ruff check . + +# Tests +pytest +``` + +Violations of these rules will be flagged by the code-reviewer agent. + +## Logging Standards + +### Logger Naming + +```python +import logging + +# Use module-level logger with __name__ +logger = logging.getLogger(__name__) +``` + +### Log Levels + +| Level | Usage | +|-------|-------| +| `DEBUG` | Detailed diagnostic info (tensor shapes, config values) | +| `INFO` | Training progress, epoch results, key milestones | +| `WARNING` | Recoverable issues (fallback behavior, deprecation) | +| `ERROR` | Failures that need attention but don't crash | +| `CRITICAL` | Unrecoverable errors | + +## Module `__init__.py` Standards + +Every package `__init__.py` must define `__all__` for explicit public API: + +```python +# src/data_module/__init__.py +from .dataset import DatasetFactory, register_dataset +from .augmentation import AugmentationFactory + +__all__ = [ + "DatasetFactory", + "register_dataset", + "AugmentationFactory", +] +``` diff --git a/文档润色流和知识库构建流/claude-scholar/rules/experiment-reproducibility.md b/文档润色流和知识库构建流/claude-scholar/rules/experiment-reproducibility.md new file mode 100644 index 0000000..26613dd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/rules/experiment-reproducibility.md @@ -0,0 +1,137 @@ +# Experiment Reproducibility + +## Random Seed Management + +Always set random seeds for reproducibility: + +```python +import random +import numpy as np +import torch +import os + +def set_seed(seed: int = 42) -> None: + """Set random seeds for reproducibility.""" + random.seed(seed) + np.random.seed(seed) + torch.manual_seed(seed) + torch.cuda.manual_seed_all(seed) + os.environ["PYTHONHASHSEED"] = str(seed) + # For deterministic behavior (may impact performance) + torch.backends.cudnn.deterministic = True + torch.backends.cudnn.benchmark = False +``` + +## Configuration Recording + +### Hydra Auto-Save + +Hydra automatically saves configs to `outputs/` directory: + +``` +outputs/ +└── 2024-01-15/ + └── 14-30-00/ + ├── .hydra/ + │ ├── config.yaml # Resolved config + │ ├── hydra.yaml # Hydra config + │ └── overrides.yaml # CLI overrides + └── main.log +``` + +### Manual Config Logging + +```python +import json +import logging + +logger = logging.getLogger(__name__) + +def log_config(cfg) -> None: + """Log experiment configuration.""" + logger.info(f"Config:\n{json.dumps(cfg, indent=2, default=str)}") +``` + +## Environment Recording + +Record environment info at experiment start: + +```python +def log_environment() -> dict: + """Record environment information for reproducibility.""" + import platform + env_info = { + "python_version": platform.python_version(), + "torch_version": torch.__version__, + "cuda_version": torch.version.cuda, + "gpu_model": torch.cuda.get_device_name(0) if torch.cuda.is_available() else "N/A", + "gpu_count": torch.cuda.device_count(), + } + return env_info +``` + +Save `pip freeze` output alongside experiment results: + +```bash +pip freeze > outputs/${EXPERIMENT_NAME}/requirements.txt +``` + +## Output Directory Naming + +Use consistent naming: `{experiment}_{timestamp}` + +``` +outputs/ +├── baseline_20240115_143000/ +├── ablation_no_aug_20240116_091500/ +└── final_model_20240120_160000/ +``` + +## Checkpoint Management + +### Save Strategy + +- Save best model (by validation metric) +- Save last N checkpoints for recovery +- Include optimizer state for training resumption + +### Naming Convention + +``` +checkpoints/ +├── best_model.pt +├── checkpoint_epoch_10.pt +├── checkpoint_epoch_20.pt +└── checkpoint_latest.pt +``` + +### Checkpoint Content + +```python +torch.save({ + "epoch": epoch, + "model_state_dict": model.state_dict(), + "optimizer_state_dict": optimizer.state_dict(), + "scheduler_state_dict": scheduler.state_dict(), + "best_metric": best_metric, + "config": cfg, +}, checkpoint_path) +``` + +## Dataset Version Tracking + +- Record dataset hash or version tag in experiment logs +- Use DVC or similar tools for large dataset versioning +- Document any preprocessing steps applied + +```python +import hashlib + +def get_dataset_hash(file_path: str) -> str: + """Compute SHA256 hash of dataset file.""" + sha256 = hashlib.sha256() + with open(file_path, "rb") as f: + for chunk in iter(lambda: f.read(8192), b""): + sha256.update(chunk) + return sha256.hexdigest()[:12] +``` diff --git a/文档润色流和知识库构建流/claude-scholar/rules/security.md b/文档润色流和知识库构建流/claude-scholar/rules/security.md new file mode 100644 index 0000000..5b286fc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/rules/security.md @@ -0,0 +1,74 @@ +# Security Rules + +## Secrets Management + +### Never Store Secrets in Git-Tracked Files + +- API keys, tokens, passwords must NEVER appear in committed files +- Use environment variables or `.env` files (which are gitignored) +- `settings.json` contains sensitive tokens and is excluded from Git via `.gitignore` + +### Environment Variables + +```python +import os + +# GOOD: Read from environment +api_key = os.environ["API_KEY"] + +# BAD: Hardcoded secret +api_key = "sk-abc123..." +``` + +### `.env` File Usage + +```bash +# .env (gitignored) +ANTHROPIC_AUTH_TOKEN=sk-ant-... +GITHUB_PERSONAL_ACCESS_TOKEN=ghp_... +WANDB_API_KEY=... +``` + +```python +# Load in code +from dotenv import load_dotenv +load_dotenv() +``` + +## Sensitive File Warnings + +The following files must NEVER be committed to Git: + +| File Pattern | Reason | +|-------------|--------| +| `settings.json` | Contains API tokens | +| `.env`, `.env.*` | Environment secrets | +| `*.pem`, `*.key` | Private keys | +| `credentials.json` | Service account credentials | +| `*_secret*`, `*_token*` | Named secret files | +| `*.sqlite`, `*.db` | May contain user data | + +## Code Security + +### Prohibited in Source Code + +- Hardcoded passwords or API keys +- Hardcoded IP addresses or internal URLs (use config) +- Disabled SSL verification without justification +- `eval()` or `exec()` with user input +- SQL string concatenation (use parameterized queries) + +### Pre-Commit Checks + +The `security-guard.js` hook automatically checks for: +- Secrets in file content before write/edit operations +- Dangerous bash commands +- Sensitive file modifications + +## Token Rotation + +If a token is accidentally committed: +1. Immediately rotate the compromised token +2. Use `git filter-branch` or BFG Repo-Cleaner to remove from history +3. Force push the cleaned history +4. Verify the old token is invalidated diff --git a/文档润色流和知识库构建流/claude-scholar/scripts/lib/package-manager.js b/文档润色流和知识库构建流/claude-scholar/scripts/lib/package-manager.js new file mode 100644 index 0000000..ed101df --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/scripts/lib/package-manager.js @@ -0,0 +1,354 @@ +/** + * 包管理器检测系统 + * 智能检测并管理 npm、pnpm、yarn、bun 等包管理器 + * + * @module package-manager + */ + +const fs = require('fs'); +const path = require('path'); +const { commandExists, readJSON, getProjectRoot, getClaudeConfigDir, isWindows } = require('./utils'); + +// 包管理器配置 +const PACKAGE_MANAGERS = { + npm: { + name: 'npm', + lockFile: 'package-lock.json', + installCmd: 'npm install', + runCmd: 'npm run', + execCmd: 'npx', + globalFlag: '--global' + }, + pnpm: { + name: 'pnpm', + lockFile: 'pnpm-lock.yaml', + installCmd: 'pnpm install', + runCmd: 'pnpm', + execCmd: 'pnpm dlx', + globalFlag: '--global' + }, + yarn: { + name: 'yarn', + lockFile: 'yarn.lock', + installCmd: 'yarn install', + runCmd: 'yarn', + execCmd: 'yarn dlx', + globalFlag: 'global' + }, + bun: { + name: 'bun', + lockFile: 'bun.lockb', + installCmd: 'bun install', + runCmd: 'bun run', + execCmd: 'bun x', + globalFlag: '--global' + } +}; + +// 检测优先级 +const DETECTION_PRIORITY = ['pnpm', 'bun', 'yarn', 'npm']; + +/** + * 获取项目配置文件路径 + * @returns {string} 配置文件路径 + */ +function getProjectConfigPath() { + const projectRoot = getProjectRoot(); + if (projectRoot) { + return path.join(projectRoot, '.claude', 'package-manager.json'); + } + return null; +} + +/** + * 获取全局配置文件路径 + * @returns {string} 配置文件路径 + */ +function getGlobalConfigPath() { + return path.join(getClaudeConfigDir(), 'package-manager.json'); +} + +/** + * 从环境变量检测包管理器 + * @returns {string|null} 包管理器名称或 null + */ +function detectFromEnvironment() { + const envPm = process.env.CLAUDE_PACKAGE_MANAGER; + if (envPm && PACKAGE_MANAGERS[envPm]) { + return envPm; + } + return null; +} + +/** + * 从项目配置检测包管理器 + * @returns {string|null} 包管理器名称或 null + */ +function detectFromProjectConfig() { + const configPath = getProjectConfigPath(); + if (configPath && fs.existsSync(configPath)) { + const config = readJSON(configPath); + if (config && config.packageManager && PACKAGE_MANAGERS[config.packageManager]) { + return config.packageManager; + } + } + return null; +} + +/** + * 从全局配置检测包管理器 + * @returns {string|null} 包管理器名称或 null + */ +function detectFromGlobalConfig() { + const configPath = getGlobalConfigPath(); + if (configPath && fs.existsSync(configPath)) { + const config = readJSON(configPath); + if (config && config.packageManager && PACKAGE_MANAGERS[config.packageManager]) { + return config.packageManager; + } + } + return null; +} + +/** + * 从 package.json 检测包管理器 + * @returns {string|null} 包管理器名称或 null + */ +function detectFromPackageJson() { + const projectRoot = getProjectRoot(); + if (!projectRoot) { + return null; + } + + const packageJsonPath = path.join(projectRoot, 'package.json'); + if (!fs.existsSync(packageJsonPath)) { + return null; + } + + const packageJson = readJSON(packageJsonPath); + if (!packageJson) { + return null; + } + + // 检查 packageManager 字段 + if (packageJson.packageManager) { + // 格式: "npm@8.0.0" 或 "pnpm@7.0.0" + const match = packageJson.packageManager.match(/^([a-zA-Z]+)@/); + if (match && PACKAGE_MANAGERS[match[1]]) { + return match[1]; + } + } + + return null; +} + +/** + * 从锁文件检测包管理器 + * @returns {string|null} 包管理器名称或 null + */ +function detectFromLockFile() { + const projectRoot = getProjectRoot(); + if (!projectRoot) { + return null; + } + + // 按优先级检查锁文件 + for (const pm of DETECTION_PRIORITY) { + const lockFile = path.join(projectRoot, PACKAGE_MANAGERS[pm].lockFile); + if (fs.existsSync(lockFile)) { + return pm; + } + } + + return null; +} + +/** + * 从可用命令检测包管理器 + * @returns {string|null} 包管理器名称或 null + */ +function detectFromAvailableCommands() { + for (const pm of DETECTION_PRIORITY) { + if (commandExists(pm)) { + return pm; + } + } + // npm 始终可用（Node.js 自带） + return 'npm'; +} + +/** + * 智能检测包管理器 + * @param {Object} options - 检测选项 + * @returns {{name: string, source: string, config: Object}} 检测结果 + */ +function getPackageManager(options = {}) { + const { + skipEnvironment = false, + skipProjectConfig = false, + skipGlobalConfig = false, + skipPackageJson = false, + skipLockFile = false, + skipAvailable = false + } = options; + + // 按优先级检测 + const detectors = [ + !skipEnvironment && { detector: detectFromEnvironment, source: 'environment' }, + !skipProjectConfig && { detector: detectFromProjectConfig, source: 'project-config' }, + !skipPackageJson && { detector: detectFromPackageJson, source: 'package.json' }, + !skipLockFile && { detector: detectFromLockFile, source: 'lock-file' }, + !skipGlobalConfig && { detector: detectFromGlobalConfig, source: 'global-config' }, + !skipAvailable && { detector: detectFromAvailableCommands, source: 'available' } + ].filter(Boolean); + + for (const { detector, source } of detectors) { + const pm = detector(); + if (pm && PACKAGE_MANAGERS[pm]) { + return { + name: pm, + source, + config: PACKAGE_MANAGERS[pm] + }; + } + } + + // 默认回退到 npm + return { + name: 'npm', + source: 'default', + config: PACKAGE_MANAGERS.npm + }; +} + +/** + * 设置项目包管理器 + * @param {string} packageManager - 包管理器名称 + * @returns {boolean} 是否成功 + */ +function setProjectPackageManager(packageManager) { + if (!PACKAGE_MANAGERS[packageManager]) { + console.error(`不支持的包管理器: ${packageManager}`); + return false; + } + + const configPath = getProjectConfigPath(); + if (!configPath) { + console.error('无法找到项目根目录'); + return false; + } + + const configDir = path.dirname(configPath); + if (!fs.existsSync(configDir)) { + fs.mkdirSync(configDir, { recursive: true }); + } + + try { + fs.writeFileSync( + configPath, + JSON.stringify({ packageManager }, null, 2), + 'utf8' + ); + return true; + } catch (err) { + console.error(`写入配置失败: ${err.message}`); + return false; + } +} + +/** + * 设置全局包管理器 + * @param {string} packageManager - 包管理器名称 + * @returns {boolean} 是否成功 + */ +function setGlobalPackageManager(packageManager) { + if (!PACKAGE_MANAGERS[packageManager]) { + console.error(`不支持的包管理器: ${packageManager}`); + return false; + } + + const configPath = getGlobalConfigPath(); + const configDir = path.dirname(configPath); + + if (!fs.existsSync(configDir)) { + fs.mkdirSync(configDir, { recursive: true }); + } + + try { + fs.writeFileSync( + configPath, + JSON.stringify({ packageManager }, null, 2), + 'utf8' + ); + return true; + } catch (err) { + console.error(`写入配置失败: ${err.message}`); + return false; + } +} + +/** + * 构建包管理器命令 + * @param {string} commandType - 命令类型 (install, run, exec) + * @param {Object} options - 选项 + * @returns {string} 完整命令 + */ +function buildCommand(commandType, options = {}) { + const pm = getPackageManager(); + const config = pm.config; + + switch (commandType) { + case 'install': + return config.installCmd; + case 'run': + return `${config.runCmd} ${options.script || ''}`; + case 'exec': + return `${config.execCmd} ${options.package || ''}`; + default: + return config.installCmd; + } +} + +/** + * 获取所有可用的包管理器 + * @returns {Array<{name: string, available: boolean}>} 可用包管理器列表 + */ +function getAvailablePackageManagers() { + return Object.keys(PACKAGE_MANAGERS).map(name => ({ + name, + available: commandExists(name) + })); +} + +/** + * 打印包管理器信息 + */ +function printPackageManagerInfo() { + const pm = getPackageManager(); + console.log(`当前包管理器: ${pm.name} (来源: ${pm.source})`); + console.log(`配置:`); + console.log(` 安装命令: ${pm.config.installCmd}`); + console.log(` 运行命令: ${pm.config.runCmd}`); + console.log(` 执行命令: ${pm.config.execCmd}`); +} + +// 导出所有函数 +module.exports = { + PACKAGE_MANAGERS, + DETECTION_PRIORITY, + getPackageManager, + setProjectPackageManager, + setGlobalPackageManager, + buildCommand, + getAvailablePackageManagers, + printPackageManagerInfo, + getProjectConfigPath, + getGlobalConfigPath, + // 为 setup-package-manager.js 添加的导出 + setPreferredPackageManager: setGlobalPackageManager, + detectFromLockFile, + detectFromPackageJson, + getSelectionPrompt: () => { + return '\n💡 运行 /setup-pm 配置首选包管理器\n'; + } +}; diff --git a/文档润色流和知识库构建流/claude-scholar/scripts/lib/utils.js b/文档润色流和知识库构建流/claude-scholar/scripts/lib/utils.js new file mode 100644 index 0000000..61eac6c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/scripts/lib/utils.js @@ -0,0 +1,233 @@ +/** + * 跨平台工具函数库 + * 为 Claude Code 插件提供跨平台兼容性支持 + * + * @module utils + */ + +const fs = require('fs'); +const path = require('path'); +const os = require('os'); +const { execSync, spawnSync } = require('child_process'); + +// 平台检测常量 +const isWindows = process.platform === 'win32'; +const isMacOS = process.platform === 'darwin'; +const isLinux = process.platform === 'linux'; + +/** + * 获取用户主目录（跨平台） + * @returns {string} 用户主目录路径 + */ +function getHomeDir() { + return os.homedir(); +} + +/** + * 确保目录存在，如不存在则创建（跨平台） + * @param {string} dirPath - 目录路径 + * @returns {string} 目录路径 + */ +function ensureDir(dirPath) { + if (!fs.existsSync(dirPath)) { + fs.mkdirSync(dirPath, { recursive: true }); + } + return dirPath; +} + +/** + * 检查命令是否存在（跨平台） + * @param {string} cmd - 命令名称 + * @returns {boolean} 命令是否存在 + */ +function commandExists(cmd) { + // 验证命令名称安全性 + if (!/^[a-zA-Z0-9_.-]+$/.test(cmd)) { + return false; + } + + try { + if (isWindows) { + // Windows 使用 where 命令 + const result = spawnSync('where', [cmd], { stdio: 'pipe' }); + return result.status === 0; + } else { + // Unix-like 系统使用 which 命令 + const result = spawnSync('which', [cmd], { stdio: 'pipe' }); + return result.status === 0; + } + } catch { + return false; + } +} + +/** + * 安全执行命令（跨平台） + * @param {string} cmd - 要执行的命令 + * @param {Object} options - 执行选项 + * @returns {{success: boolean, output: string, error?: string}} 执行结果 + */ +function runCommand(cmd, options = {}) { + try { + const result = execSync(cmd, { + encoding: 'utf8', + stdio: ['pipe', 'pipe', 'pipe'], + ...options + }); + return { success: true, output: result.trim() }; + } catch (err) { + return { + success: false, + output: err.stdout || '', + error: err.stderr || err.message + }; + } +} + +/** + * 获取 Claude 配置目录（跨平台） + * @returns {string} Claude 配置目录路径 + */ +function getClaudeConfigDir() { + const homeDir = getHomeDir(); + return path.join(homeDir, '.claude'); +} + +/** + * 获取项目根目录（跨平台） + * @param {string} startDir - 起始目录 + * @returns {string|null} 项目根目录或 null + */ +function getProjectRoot(startDir = process.cwd()) { + let currentDir = startDir; + + while (currentDir !== path.parse(currentDir).root) { + // 检查是否存在 .claude-plugin 目录 + const pluginDir = path.join(currentDir, '.claude-plugin'); + if (fs.existsSync(pluginDir)) { + return currentDir; + } + + // 检查是否存在 package.json + const packageJson = path.join(currentDir, 'package.json'); + if (fs.existsSync(packageJson)) { + return currentDir; + } + + // 向上移动 + currentDir = path.dirname(currentDir); + } + + return null; +} + +/** + * 路径拼接（跨平台） + * @param {...string} paths - 路径片段 + * @returns {string} 拼接后的路径 + */ +function joinPath(...paths) { + return path.join(...paths); +} + +/** + * 获取绝对路径（跨平台） + * @param {...string} paths - 路径片段 + * @returns {string} 绝对路径 + */ +function resolvePath(...paths) { + return path.resolve(...paths); +} + +/** + * 规范化路径（跨平台） + * @param {string} filePath - 文件路径 + * @returns {string} 规范化后的路径 + */ +function normalizePath(filePath) { + return path.normalize(filePath); +} + +/** + * 读取 JSON 文件（跨平台） + * @param {string} filePath - JSON 文件路径 + * @returns {Object|null} 解析后的 JSON 对象或 null + */ +function readJSON(filePath) { + try { + const content = fs.readFileSync(filePath, 'utf8'); + return JSON.parse(content); + } catch { + return null; + } +} + +/** + * 写入 JSON 文件（跨平台） + * @param {string} filePath - JSON 文件路径 + * @param {Object} data - 要写入的数据 + * @param {number|object|string} space - JSON 缩进空格数 + * @returns {boolean} 是否成功 + */ +function writeJSON(filePath, data, space = 2) { + try { + ensureDir(path.dirname(filePath)); + fs.writeFileSync(filePath, JSON.stringify(data, null, space), 'utf8'); + return true; + } catch { + return false; + } +} + +/** + * 复制文件（跨平台） + * @param {string} src - 源文件路径 + * @param {string} dest - 目标文件路径 + * @returns {boolean} 是否成功 + */ +function copyFile(src, dest) { + try { + ensureDir(path.dirname(dest)); + fs.copyFileSync(src, dest); + return true; + } catch { + return false; + } +} + +/** + * 获取平台信息 + * @returns {Object} 平台信息对象 + */ +function getPlatformInfo() { + return { + platform: process.platform, + isWindows, + isMacOS, + isLinux, + arch: process.arch, + nodeVersion: process.version, + homeDir: getHomeDir(), + tempDir: os.tmpdir() + }; +} + +// 导出所有函数 +module.exports = { + isWindows, + isMacOS, + isLinux, + getHomeDir, + ensureDir, + commandExists, + runCommand, + getClaudeConfigDir, + getProjectRoot, + joinPath, + resolvePath, + normalizePath, + readJSON, + writeJSON, + copyFile, + getPlatformInfo +}; diff --git a/文档润色流和知识库构建流/claude-scholar/scripts/setup-package-manager.js b/文档润色流和知识库构建流/claude-scholar/scripts/setup-package-manager.js new file mode 100755 index 0000000..1a6a8fa --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/scripts/setup-package-manager.js @@ -0,0 +1,206 @@ +#!/usr/bin/env node +/** + * Package Manager Setup Script + * + * Interactive script to configure preferred package manager. + * Can be run directly or via the /setup-pm command. + * + * Usage: + * node scripts/setup-package-manager.js [pm-name] + * node scripts/setup-package-manager.js --detect + * node scripts/setup-package-manager.js --global pnpm + * node scripts/setup-package-manager.js --project bun + */ + +const { + PACKAGE_MANAGERS, + getPackageManager, + setPreferredPackageManager, + setProjectPackageManager, + getAvailablePackageManagers, + detectFromLockFile, + detectFromPackageJson, + getSelectionPrompt +} = require('./lib/package-manager'); +const { log } = require('./lib/utils'); + +function showHelp() { + console.log(` +Package Manager Setup for Claude Code + +Usage: + node scripts/setup-package-manager.js [options] [package-manager] + +Options: + --detect Detect and show current package manager + --global Set global preference (saves to ~/.claude/package-manager.json) + --project Set project preference (saves to .claude/package-manager.json) + --list List available package managers + --help Show this help message + +Package Managers: + npm Node Package Manager (default with Node.js) + pnpm Fast, disk space efficient package manager + yarn Classic Yarn package manager + bun All-in-one JavaScript runtime & toolkit + +Examples: + # Detect current package manager + node scripts/setup-package-manager.js --detect + + # Set pnpm as global preference + node scripts/setup-package-manager.js --global pnpm + + # Set bun for current project + node scripts/setup-package-manager.js --project bun + + # List available package managers + node scripts/setup-package-manager.js --list +`); +} + +function detectAndShow() { + const pm = getPackageManager(); + const available = getAvailablePackageManagers(); + const fromLock = detectFromLockFile(); + const fromPkg = detectFromPackageJson(); + + console.log('\n=== Package Manager Detection ===\n'); + + console.log('Current selection:'); + console.log(` Package Manager: ${pm.name}`); + console.log(` Source: ${pm.source}`); + console.log(''); + + console.log('Detection results:'); + console.log(` From package.json: ${fromPkg || 'not specified'}`); + console.log(` From lock file: ${fromLock || 'not found'}`); + console.log(` Environment var: ${process.env.CLAUDE_PACKAGE_MANAGER || 'not set'}`); + console.log(''); + + console.log('Available package managers:'); + for (const pmName of Object.keys(PACKAGE_MANAGERS)) { + const installed = available.includes(pmName); + const indicator = installed ? '✓' : '✗'; + const current = pmName === pm.name ? ' (current)' : ''; + console.log(` ${indicator} ${pmName}${current}`); + } + + console.log(''); + console.log('Commands:'); + console.log(` Install: ${pm.config.installCmd}`); + console.log(` Run script: ${pm.config.runCmd} [script-name]`); + console.log(` Execute binary: ${pm.config.execCmd} [binary-name]`); + console.log(''); +} + +function listAvailable() { + const available = getAvailablePackageManagers(); + const pm = getPackageManager(); + + console.log('\nAvailable Package Managers:\n'); + + for (const pmName of Object.keys(PACKAGE_MANAGERS)) { + const config = PACKAGE_MANAGERS[pmName]; + const installed = available.includes(pmName); + const current = pmName === pm.name ? ' (current)' : ''; + + console.log(`${pmName}${current}`); + console.log(` Installed: ${installed ? 'Yes' : 'No'}`); + console.log(` Lock file: ${config.lockFile}`); + console.log(` Install: ${config.installCmd}`); + console.log(` Run: ${config.runCmd}`); + console.log(''); + } +} + +function setGlobal(pmName) { + if (!PACKAGE_MANAGERS[pmName]) { + console.error(`Error: Unknown package manager "${pmName}"`); + console.error(`Available: ${Object.keys(PACKAGE_MANAGERS).join(', ')}`); + process.exit(1); + } + + const available = getAvailablePackageManagers(); + if (!available.includes(pmName)) { + console.warn(`Warning: ${pmName} is not installed on your system`); + } + + try { + setPreferredPackageManager(pmName); + console.log(`\n✓ Global preference set to: ${pmName}`); + console.log(' Saved to: ~/.claude/package-manager.json'); + console.log(''); + } catch (err) { + console.error(`Error: ${err.message}`); + process.exit(1); + } +} + +function setProject(pmName) { + if (!PACKAGE_MANAGERS[pmName]) { + console.error(`Error: Unknown package manager "${pmName}"`); + console.error(`Available: ${Object.keys(PACKAGE_MANAGERS).join(', ')}`); + process.exit(1); + } + + try { + setProjectPackageManager(pmName); + console.log(`\n✓ Project preference set to: ${pmName}`); + console.log(' Saved to: .claude/package-manager.json'); + console.log(''); + } catch (err) { + console.error(`Error: ${err.message}`); + process.exit(1); + } +} + +// Main +const args = process.argv.slice(2); + +if (args.length === 0 || args.includes('--help') || args.includes('-h')) { + showHelp(); + process.exit(0); +} + +if (args.includes('--detect')) { + detectAndShow(); + process.exit(0); +} + +if (args.includes('--list')) { + listAvailable(); + process.exit(0); +} + +const globalIdx = args.indexOf('--global'); +if (globalIdx !== -1) { + const pmName = args[globalIdx + 1]; + if (!pmName) { + console.error('Error: --global requires a package manager name'); + process.exit(1); + } + setGlobal(pmName); + process.exit(0); +} + +const projectIdx = args.indexOf('--project'); +if (projectIdx !== -1) { + const pmName = args[projectIdx + 1]; + if (!pmName) { + console.error('Error: --project requires a package manager name'); + process.exit(1); + } + setProject(pmName); + process.exit(0); +} + +// If just a package manager name is provided, set it globally +const pmName = args[0]; +if (PACKAGE_MANAGERS[pmName]) { + setGlobal(pmName); +} else { + console.error(`Error: Unknown option or package manager "${pmName}"`); + showHelp(); + process.exit(1); +} diff --git a/文档润色流和知识库构建流/claude-scholar/scripts/setup.sh b/文档润色流和知识库构建流/claude-scholar/scripts/setup.sh new file mode 100755 index 0000000..8d4cfbe --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/scripts/setup.sh @@ -0,0 +1,544 @@ +#!/usr/bin/env bash +set -euo pipefail + +CLAUDE_DIR="$HOME/.claude" +SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)" +SRC_DIR="$(cd "$SCRIPT_DIR/.." && pwd)" +COMPONENTS=(skills commands agents rules hooks scripts templates) +CLAUDE_MD_SIDECAR="CLAUDE.scholar.md" +CLAUDE_ZH_MD_SIDECAR="CLAUDE.zh-CN.scholar.md" +BACKUP_ROOT="$CLAUDE_DIR/.claude-scholar-backups" +MANIFEST_FILE="$CLAUDE_DIR/.claude-scholar-manifest.txt" +STATE_FILE="$CLAUDE_DIR/.claude-scholar-install-state" +PREVIOUS_MANAGED_PATHS_FILE="$(mktemp)" +BACKUP_STAMP="$(date +%Y%m%d-%H%M%S)" +BACKUP_DIR="$BACKUP_ROOT/$BACKUP_STAMP" +BACKUP_READY=0 +BACKUP_COUNT=0 +UPDATED_COUNT=0 +SKIPPED_COUNT=0 +SETTINGS_CREATED=0 +MANAGED_PATHS=() +CLAUDE_TARGETS=() +SETTINGS_META_FILE="$(mktemp)" +LEGACY_INSTALL_DETECTED=0 + +info() { echo -e "\033[1;34m[INFO]\033[0m $*"; } +warn() { echo -e "\033[1;33m[WARN]\033[0m $*"; } +error() { echo -e "\033[1;31m[ERROR]\033[0m $*"; exit 1; } + +cleanup_temp_files() { + rm -f "$SETTINGS_META_FILE" "$PREVIOUS_MANAGED_PATHS_FILE" +} + +trap cleanup_temp_files EXIT + +check_deps() { + command -v git >/dev/null || error "Git is required. Install it first." + command -v node >/dev/null || error "Node.js is required (hooks depend on it). Install it first." +} + +load_previous_manifest() { + if [ -f "$MANIFEST_FILE" ]; then + cp "$MANIFEST_FILE" "$PREVIOUS_MANAGED_PATHS_FILE" + else + : > "$PREVIOUS_MANAGED_PATHS_FILE" + fi +} + +detect_legacy_install() { + local settings="$CLAUDE_DIR/settings.json" + [ -f "$MANIFEST_FILE" ] && return 0 + [ -f "$settings" ] || return 0 + + if CLAUDE_SETTINGS_TARGET="$settings" node <<'NODE' +const fs = require('fs'); +const settings = JSON.parse(fs.readFileSync(process.env.CLAUDE_SETTINGS_TARGET, 'utf8')); +const hookNeedles = [ + '.claude/hooks/security-guard.js', + '.claude/hooks/session-summary.js', + '.claude/hooks/session-start.js', + '.claude/hooks/stop-summary.js', + '.claude/hooks/skill-forced-eval.js', +]; +let detected = false; + +for (const matchers of Object.values(settings.hooks || {})) { + if (!Array.isArray(matchers)) continue; + for (const matcher of matchers) { + for (const hook of matcher.hooks || []) { + if (typeof hook.command === 'string' && hookNeedles.some((needle) => hook.command.includes(needle))) { + detected = true; + } + } + } +} + +process.exit(detected ? 0 : 1); +NODE + then + LEGACY_INSTALL_DETECTED=1 + fi +} + +record_managed_path() { + local target="$1" + local rel="${target#$CLAUDE_DIR/}" + [ "$rel" = "$target" ] && return 0 + [ -z "$rel" ] && return 0 + MANAGED_PATHS+=("$rel") +} + +record_claude_target() { + local target="$1" + local rel="${target#$CLAUDE_DIR/}" + [ "$rel" = "$target" ] && return 0 + [ -z "$rel" ] && return 0 + CLAUDE_TARGETS+=("$rel") +} + +was_previously_managed() { + local target="$1" + local rel="${target#$CLAUDE_DIR/}" + [ "$rel" = "$target" ] && return 1 + grep -Fxq "$rel" "$PREVIOUS_MANAGED_PATHS_FILE" +} + +should_adopt_existing_path() { + local target="$1" + if was_previously_managed "$target"; then + return 0 + fi + [ "$LEGACY_INSTALL_DETECTED" -eq 1 ] +} + +write_install_state() { + mkdir -p "$CLAUDE_DIR" + if [ "${#MANAGED_PATHS[@]}" -gt 0 ]; then + printf "%s\n" "${MANAGED_PATHS[@]}" | LC_ALL=C sort -u > "$MANIFEST_FILE" + else + : > "$MANIFEST_FILE" + fi + + local managed_paths_file + local claude_targets_file + managed_paths_file="$(mktemp)" + claude_targets_file="$(mktemp)" + + if [ "${#MANAGED_PATHS[@]}" -gt 0 ]; then + printf "%s\n" "${MANAGED_PATHS[@]}" | LC_ALL=C sort -u > "$managed_paths_file" + else + : > "$managed_paths_file" + fi + + if [ "${#CLAUDE_TARGETS[@]}" -gt 0 ]; then + printf "%s\n" "${CLAUDE_TARGETS[@]}" | LC_ALL=C sort -u > "$claude_targets_file" + else + : > "$claude_targets_file" + fi + + CLAUDE_STATE_FILE="$STATE_FILE" \ + CLAUDE_SETTINGS_META_FILE="$SETTINGS_META_FILE" \ + CLAUDE_MANAGED_PATHS_FILE="$managed_paths_file" \ + CLAUDE_TARGETS_FILE="$claude_targets_file" \ + CLAUDE_INSTALLED_AT="$BACKUP_STAMP" \ + CLAUDE_SOURCE_DIR="$SRC_DIR" \ + CLAUDE_SETTINGS_CREATED="$SETTINGS_CREATED" \ + CLAUDE_BACKUP_DIR="$BACKUP_DIR" \ + CLAUDE_BACKUP_READY="$BACKUP_READY" \ + node <<'NODE' +const fs = require('fs'); + +function readLines(path) { + if (!path || !fs.existsSync(path)) return []; + return fs.readFileSync(path, 'utf8').split('\n').map((line) => line.trim()).filter(Boolean); +} + +function readJson(path) { + if (!path || !fs.existsSync(path)) return {}; + return JSON.parse(fs.readFileSync(path, 'utf8')); +} + +const state = { + installedAt: process.env.CLAUDE_INSTALLED_AT, + sourceDir: process.env.CLAUDE_SOURCE_DIR, + settingsCreated: process.env.CLAUDE_SETTINGS_CREATED === '1', + backupDir: process.env.CLAUDE_BACKUP_READY === '1' ? process.env.CLAUDE_BACKUP_DIR : '', + managedPaths: readLines(process.env.CLAUDE_MANAGED_PATHS_FILE), + claudeTargets: readLines(process.env.CLAUDE_TARGETS_FILE), + settings: readJson(process.env.CLAUDE_SETTINGS_META_FILE), +}; + +fs.writeFileSync(process.env.CLAUDE_STATE_FILE, JSON.stringify(state, null, 2) + '\n'); +NODE + + rm -f "$managed_paths_file" "$claude_targets_file" +} + +ensure_backup_dir() { + if [ "$BACKUP_READY" -eq 0 ]; then + mkdir -p "$BACKUP_DIR" + BACKUP_READY=1 + info "Backup directory: $BACKUP_DIR" + fi +} + +backup_path() { + local target="$1" + [ -e "$target" ] || return 0 + + ensure_backup_dir + + local rel="${target#$CLAUDE_DIR/}" + if [ "$rel" = "$target" ]; then + rel="$(basename "$target")" + fi + + mkdir -p "$BACKUP_DIR/$(dirname "$rel")" + if [ -d "$target" ]; then + cp -R "$target" "$BACKUP_DIR/$rel" + else + cp -p "$target" "$BACKUP_DIR/$rel" + fi + BACKUP_COUNT=$((BACKUP_COUNT + 1)) +} + +# Create settings.json from template +create_settings() { + local template="$1/settings.json.template" + local target="$CLAUDE_DIR/settings.json" + if [ -f "$template" ] && [ ! -f "$target" ]; then + cp "$template" "$target" + SETTINGS_CREATED=1 + CLAUDE_SETTINGS_TEMPLATE="$template" CLAUDE_SETTINGS_META_FILE="$SETTINGS_META_FILE" node <<'NODE' +const fs = require('fs'); + +const template = JSON.parse(fs.readFileSync(process.env.CLAUDE_SETTINGS_TEMPLATE, 'utf8')); + +const addedHooks = []; +for (const [eventName, matchers] of Object.entries(template.hooks || {})) { + for (const matcher of matchers || []) { + for (const hook of matcher.hooks || []) { + addedHooks.push({ + event: eventName, + matcher: matcher.matcher || '*', + type: hook.type || '', + command: hook.command || '', + timeout: hook.timeout ?? null, + }); + } + } +} + +fs.writeFileSync(process.env.CLAUDE_SETTINGS_META_FILE, JSON.stringify({ + addedHooks, + addedMcpServers: Object.keys(template.mcpServers || {}), + addedMcpServerFields: {}, + addedEnabledPlugins: Object.keys(template.enabledPlugins || {}), +}, null, 2) + '\n'); +NODE + info "Created settings.json from template." + info " → Edit $target to add your GITHUB_PERSONAL_ACCESS_TOKEN (optional)." + fi +} + +# Merge hooks, mcpServers, enabledPlugins from template into existing settings.json +merge_settings() { + local template="$1/settings.json.template" + local target="$CLAUDE_DIR/settings.json" + + [ -f "$template" ] || return 0 + [ -f "$target" ] || { create_settings "$1"; return 0; } + + # Backup + backup_path "$target" + cp "$target" "${target}.bak" + info "Backed up settings.json → settings.json.bak" + + # Merge hooks, mcpServers, enabledPlugins while preserving user env/model/API key settings. + CLAUDE_SETTINGS_TARGET="$target" CLAUDE_SETTINGS_TEMPLATE="$template" CLAUDE_SETTINGS_META_FILE="$SETTINGS_META_FILE" node <<'NODE' +const fs = require('fs'); + +const targetPath = process.env.CLAUDE_SETTINGS_TARGET; +const templatePath = process.env.CLAUDE_SETTINGS_TEMPLATE; +const metaPath = process.env.CLAUDE_SETTINGS_META_FILE; +const existing = JSON.parse(fs.readFileSync(targetPath, 'utf8')); +const template = JSON.parse(fs.readFileSync(templatePath, 'utf8')); +const addedHooks = []; +const addedMcpServers = []; +const addedMcpServerFields = {}; +const addedEnabledPlugins = []; + +function clone(value) { + return JSON.parse(JSON.stringify(value)); +} + +function mergeMissing(existingValue, templateValue, pathParts, addedPaths) { + if (existingValue === undefined) return clone(templateValue); + if (templateValue === null || Array.isArray(templateValue) || typeof templateValue !== 'object') { + return existingValue; + } + + const output = { ...existingValue }; + for (const [key, value] of Object.entries(templateValue)) { + if (!(key in output)) { + output[key] = clone(value); + addedPaths.push([...pathParts, key].join('.')); + continue; + } + if ( + output[key] && + value && + !Array.isArray(output[key]) && + !Array.isArray(value) && + typeof output[key] === 'object' && + typeof value === 'object' + ) { + output[key] = mergeMissing(output[key], value, [...pathParts, key], addedPaths); + } + } + return output; +} + +function mergeHooks(existingHooks, templateHooks) { + const output = existingHooks ? clone(existingHooks) : {}; + for (const [eventName, templateMatchers] of Object.entries(templateHooks || {})) { + const existingMatchers = Array.isArray(output[eventName]) ? output[eventName] : []; + for (const templateMatcher of templateMatchers) { + const matchValue = templateMatcher.matcher || '*'; + let existingMatcher = existingMatchers.find((item) => (item.matcher || '*') === matchValue); + if (!existingMatcher) { + existingMatchers.push(clone(templateMatcher)); + for (const hook of templateMatcher.hooks || []) { + addedHooks.push({ + event: eventName, + matcher: matchValue, + type: hook.type || '', + command: hook.command || '', + timeout: hook.timeout ?? null, + }); + } + continue; + } + + existingMatcher.hooks = Array.isArray(existingMatcher.hooks) ? existingMatcher.hooks : []; + const seen = new Set( + existingMatcher.hooks.map((hook) => + JSON.stringify({ + type: hook.type || '', + command: hook.command || '', + timeout: hook.timeout ?? null, + }), + ), + ); + + for (const hook of templateMatcher.hooks || []) { + const signature = JSON.stringify({ + type: hook.type || '', + command: hook.command || '', + timeout: hook.timeout ?? null, + }); + if (!seen.has(signature)) { + existingMatcher.hooks.push(clone(hook)); + seen.add(signature); + addedHooks.push({ + event: eventName, + matcher: matchValue, + type: hook.type || '', + command: hook.command || '', + timeout: hook.timeout ?? null, + }); + } + } + } + output[eventName] = existingMatchers; + } + return output; +} + +existing.hooks = mergeHooks(existing.hooks, template.hooks); + +if (template.mcpServers) { + existing.mcpServers = existing.mcpServers || {}; + for (const [key, value] of Object.entries(template.mcpServers)) { + if (!(key in existing.mcpServers)) { + addedMcpServers.push(key); + existing.mcpServers[key] = clone(value); + continue; + } + const addedPaths = []; + existing.mcpServers[key] = mergeMissing(existing.mcpServers[key], value, [], addedPaths); + if (addedPaths.length > 0) { + addedMcpServerFields[key] = addedPaths; + } + } +} + +if (template.enabledPlugins) { + existing.enabledPlugins = existing.enabledPlugins || {}; + for (const [key, value] of Object.entries(template.enabledPlugins)) { + if (!(key in existing.enabledPlugins)) { + existing.enabledPlugins[key] = value; + addedEnabledPlugins.push(key); + } + } +} + +fs.writeFileSync(targetPath, JSON.stringify(existing, null, 2) + '\n'); +fs.writeFileSync(metaPath, JSON.stringify({ + addedHooks, + addedMcpServers, + addedMcpServerFields, + addedEnabledPlugins, +}, null, 2) + '\n'); +NODE + + local merge_status=$? + if [ "$merge_status" -ne 0 ]; then + warn "Auto-merge failed. Please manually copy settings from settings.json.template." + return 0 + fi + + info "Merged hooks/mcpServers/enabledPlugins into settings.json without touching env/model/API key fields." +} + +# Copy one file with backup-aware overwrite +copy_file_safely() { + local src_file="$1" + local target_file="$2" + + mkdir -p "$(dirname "$target_file")" + + if [ -f "$target_file" ] && cmp -s "$src_file" "$target_file"; then + if should_adopt_existing_path "$target_file"; then + record_managed_path "$target_file" + fi + SKIPPED_COUNT=$((SKIPPED_COUNT + 1)) + return 0 + fi + + if [ -e "$target_file" ]; then + backup_path "$target_file" + [ -d "$target_file" ] && rm -rf "$target_file" + fi + + cp -p "$src_file" "$target_file" + record_managed_path "$target_file" + UPDATED_COUNT=$((UPDATED_COUNT + 1)) +} + +# Copy component directories with per-file backup +copy_dir_safely() { + local src_dir="$1" + local target_dir="$2" + + if [ -e "$target_dir" ] && [ ! -d "$target_dir" ]; then + backup_path "$target_dir" + rm -f "$target_dir" + fi + mkdir -p "$target_dir" + + while IFS= read -r -d '' src_file; do + local rel="${src_file#$src_dir/}" + local target_file="$target_dir/$rel" + copy_file_safely "$src_file" "$target_file" + done < <(find "$src_dir" -type f -print0) +} + +install_claude_md() { + local src_file="$1" + local target_file="$CLAUDE_DIR/CLAUDE.md" + local sidecar_file="$CLAUDE_DIR/$CLAUDE_MD_SIDECAR" + + if [ -f "$target_file" ] && should_adopt_existing_path "$target_file"; then + copy_file_safely "$src_file" "$target_file" + record_claude_target "$target_file" + return 0 + fi + + if [ -f "$target_file" ]; then + warn "Preserving existing CLAUDE.md" + copy_file_safely "$src_file" "$sidecar_file" + record_claude_target "$sidecar_file" + info "Installed repository CLAUDE.md as $CLAUDE_MD_SIDECAR" + return 0 + fi + + copy_file_safely "$src_file" "$target_file" + record_claude_target "$target_file" +} + +install_claude_zh_md() { + local src_file="$1" + local target_file="$CLAUDE_DIR/CLAUDE.zh-CN.md" + local sidecar_file="$CLAUDE_DIR/$CLAUDE_ZH_MD_SIDECAR" + + if [ -f "$target_file" ] && should_adopt_existing_path "$target_file"; then + copy_file_safely "$src_file" "$target_file" + record_claude_target "$target_file" + return 0 + fi + + if [ -f "$target_file" ]; then + warn "Preserving existing CLAUDE.zh-CN.md" + copy_file_safely "$src_file" "$sidecar_file" + record_claude_target "$sidecar_file" + info "Installed repository CLAUDE.zh-CN.md as $CLAUDE_ZH_MD_SIDECAR" + return 0 + fi + + copy_file_safely "$src_file" "$target_file" + record_claude_target "$target_file" +} + +copy_components() { + local src="$1" + + if [ -f "$src/CLAUDE.md" ]; then + install_claude_md "$src/CLAUDE.md" + fi + + if [ -f "$src/CLAUDE.zh-CN.md" ]; then + install_claude_zh_md "$src/CLAUDE.zh-CN.md" + fi + + for comp in "${COMPONENTS[@]}"; do + if [ -e "$src/$comp" ]; then + if [ -d "$src/$comp" ]; then + copy_dir_safely "$src/$comp" "$CLAUDE_DIR/$comp" + else + copy_file_safely "$src/$comp" "$CLAUDE_DIR/$comp" + fi + fi + done + info "Updated components: ${COMPONENTS[*]}" +} + +main() { + echo "" + echo "╔══════════════════════════════════════╗" + echo "║ Claude Scholar Installer ║" + echo "╚══════════════════════════════════════╝" + echo "" + + check_deps + load_previous_manifest + detect_legacy_install + + info "Installing from: $SRC_DIR" + copy_components "$SRC_DIR" + merge_settings "$SRC_DIR" + write_install_state + info "Your existing env/model/API key/permissions settings are preserved." + info "Install manifest: $MANIFEST_FILE" + info "Updated files: $UPDATED_COUNT | Unchanged files skipped: $SKIPPED_COUNT | Backups created: $BACKUP_COUNT" + if [ "$BACKUP_READY" -eq 1 ]; then + info "Recover previous files from: $BACKUP_DIR" + fi + + echo "" + info "Done! Restart Claude Code CLI to activate." + echo "" +} + +main "$@" diff --git a/文档润色流和知识库构建流/claude-scholar/scripts/sync_obsidian_to_windows.sh b/文档润色流和知识库构建流/claude-scholar/scripts/sync_obsidian_to_windows.sh new file mode 100644 index 0000000..bccadf6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/scripts/sync_obsidian_to_windows.sh @@ -0,0 +1,113 @@ +#!/usr/bin/env bash + +set -euo pipefail + +SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)" +REPO_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)" +SOURCE_VAULT_DEFAULT="$REPO_ROOT/obsidian-vault" + +usage() { + cat <<'EOF' +Usage: + bash scripts/sync_obsidian_to_windows.sh --windows-path /mnt/c/Users//Documents/Obsidian/claude-scholar-vault + +Options: + --windows-path PATH Windows-local vault path mounted in WSL, e.g. /mnt/c/Users/Alice/Documents/Obsidian/claude-scholar-vault + --source-path PATH Source vault path inside WSL. Default: ./obsidian-vault + --dry-run Show what would change without copying + --no-delete Do not delete files in the Windows mirror that no longer exist in the source + -h, --help Show this help + +Notes: + - Use a Windows-local path under /mnt//... as the mirror target. + - Open the mirrored target directory with Windows Obsidian, not the WSL path. + - This script treats the WSL vault as the source of truth. +EOF +} + +WINDOWS_PATH="" +SOURCE_PATH="$SOURCE_VAULT_DEFAULT" +DRY_RUN=0 +DELETE_MODE=1 + +while [ "$#" -gt 0 ]; do + case "$1" in + --windows-path) + WINDOWS_PATH="${2:-}" + shift 2 + ;; + --source-path) + SOURCE_PATH="${2:-}" + shift 2 + ;; + --dry-run) + DRY_RUN=1 + shift + ;; + --no-delete) + DELETE_MODE=0 + shift + ;; + -h|--help) + usage + exit 0 + ;; + *) + echo "Unknown argument: $1" >&2 + usage >&2 + exit 1 + ;; + esac +done + +if [ -z "$WINDOWS_PATH" ]; then + echo "Missing required --windows-path" >&2 + usage >&2 + exit 1 +fi + +if ! command -v rsync >/dev/null 2>&1; then + echo "rsync is required but not installed." >&2 + exit 1 +fi + +SOURCE_PATH="$(realpath "$SOURCE_PATH")" +WINDOWS_PATH="$(realpath -m "$WINDOWS_PATH")" + +if [ ! -d "$SOURCE_PATH" ]; then + echo "Source vault does not exist: $SOURCE_PATH" >&2 + exit 1 +fi + +case "$WINDOWS_PATH" in + /mnt/[a-zA-Z]/*) ;; + *) + echo "Target must be a Windows-local path mounted in WSL, for example /mnt/c/Users//Documents/Obsidian/claude-scholar-vault" >&2 + echo "Received: $WINDOWS_PATH" >&2 + exit 1 + ;; +esac + +mkdir -p "$WINDOWS_PATH" + +RSYNC_ARGS=(-a --info=stats2,progress2) + +if [ "$DELETE_MODE" -eq 1 ]; then + RSYNC_ARGS+=(--delete) +fi + +if [ "$DRY_RUN" -eq 1 ]; then + RSYNC_ARGS+=(--dry-run) +fi + +echo "Source vault : $SOURCE_PATH" +echo "Windows copy : $WINDOWS_PATH" +echo "Delete extra : $DELETE_MODE" +echo "Dry run : $DRY_RUN" + +rsync "${RSYNC_ARGS[@]}" "$SOURCE_PATH"/ "$WINDOWS_PATH"/ + +echo +echo "Done." +echo "Open this directory with Windows Obsidian:" +echo " $WINDOWS_PATH" diff --git a/文档润色流和知识库构建流/claude-scholar/scripts/test_install_uninstall.sh b/文档润色流和知识库构建流/claude-scholar/scripts/test_install_uninstall.sh new file mode 100644 index 0000000..bd24a52 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/scripts/test_install_uninstall.sh @@ -0,0 +1,242 @@ +#!/usr/bin/env bash +set -euo pipefail + +REPO_ROOT="$(cd "$(dirname "$0")/.." && pwd)" +SETUP_SH="$REPO_ROOT/scripts/setup.sh" +UNINSTALL_SH="$REPO_ROOT/scripts/uninstall.sh" + +pass() { + echo "[PASS] $1" +} + +make_home() { + mktemp -d /tmp/claude-scholar-test.XXXXXX +} + +run_setup() { + HOME="$1" bash "$SETUP_SH" >/dev/null +} + +run_uninstall() { + HOME="$1" bash "$UNINSTALL_SH" >/dev/null +} + +test_roundtrip_empty_home() { + local home + home="$(make_home)" + run_setup "$home" + + test -f "$home/.claude/.claude-scholar-manifest.txt" + test -f "$home/.claude/.claude-scholar-install-state" + test -f "$home/.claude/CLAUDE.md" + + run_uninstall "$home" + + test ! -f "$home/.claude/.claude-scholar-manifest.txt" + test ! -f "$home/.claude/.claude-scholar-install-state" + test ! -f "$home/.claude/settings.json" + if [ -d "$home/.claude" ]; then + ! find "$home/.claude"/{skills,commands,agents,rules,hooks,scripts} -type f 2>/dev/null | grep -q . + fi + pass "roundtrip on empty home" +} + +test_preserve_preexisting_settings_keys() { + local home + home="$(make_home)" + mkdir -p "$home/.claude" + python3 - "$home/.claude/settings.json" <<'PY' +import json, sys +path = sys.argv[1] +data = { + "mcpServers": { + "zotero": { + "command": "custom-zotero" + } + }, + "enabledPlugins": { + "superpowers@claude-plugins-official": False + }, + "hooks": { + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "echo user-hook", + "timeout": 3 + } + ] + } + ] + } +} +with open(path, "w", encoding="utf-8") as f: + json.dump(data, f, indent=2) + f.write("\n") +PY + + run_setup "$home" + run_uninstall "$home" + + python3 - "$home/.claude/settings.json" <<'PY' +import json, sys +data = json.load(open(sys.argv[1], encoding="utf-8")) +assert data["mcpServers"]["zotero"]["command"] == "custom-zotero" +assert "args" not in data["mcpServers"]["zotero"] +assert "env" not in data["mcpServers"]["zotero"] +assert data["enabledPlugins"]["superpowers@claude-plugins-official"] is False +hooks = data["hooks"]["Stop"][0]["hooks"] +assert len(hooks) == 1 and hooks[0]["command"] == "echo user-hook" +PY + pass "preserve pre-existing settings entries with overlapping keys" +} + +test_manifest_missing_fails_safe() { + local home + home="$(make_home)" + run_setup "$home" + + rm -f "$home/.claude/.claude-scholar-manifest.txt" + if HOME="$home" bash "$UNINSTALL_SH" >/tmp/claude-scholar-uninstall-fail.log 2>&1; then + echo "[FAIL] manifest missing should fail" + cat /tmp/claude-scholar-uninstall-fail.log + exit 1 + fi + + test -f "$home/.claude/CLAUDE.md" + test -f "$home/.claude/.claude-scholar-install-state" + pass "manifest missing fails safely" +} + +test_state_records_direct_claude_targets() { + local home + home="$(make_home)" + run_setup "$home" + + python3 - "$home/.claude/.claude-scholar-install-state" <<'PY' +import json, sys +state = json.load(open(sys.argv[1], encoding="utf-8")) +targets = set(state["claudeTargets"]) +assert "CLAUDE.md" in targets, targets +assert "CLAUDE.zh-CN.md" in targets, targets +PY + + run_uninstall "$home" + test ! -f "$home/.claude/CLAUDE.md" + test ! -f "$home/.claude/CLAUDE.zh-CN.md" + pass "state records direct CLAUDE targets" +} + +test_identical_preexisting_file_is_not_owned() { + local home + home="$(make_home)" + mkdir -p "$home/.claude/hooks" + cp "$REPO_ROOT/hooks/security-guard.js" "$home/.claude/hooks/security-guard.js" + + run_setup "$home" + run_uninstall "$home" + + test -f "$home/.claude/hooks/security-guard.js" + pass "identical pre-existing file is not treated as owned" +} + +test_reinstall_keeps_owned_files_owned() { + local home + home="$(make_home)" + run_setup "$home" + run_setup "$home" + run_uninstall "$home" + + test ! -f "$home/.claude/hooks/security-guard.js" + test ! -f "$home/.claude/CLAUDE.md" + pass "reinstall preserves ownership of previously installed files" +} + +test_legacy_install_upgrade_adopts_existing_files() { + local home + home="$(make_home)" + mkdir -p "$home/.claude/hooks" + cp "$REPO_ROOT/CLAUDE.md" "$home/.claude/CLAUDE.md" + cp "$REPO_ROOT/hooks/security-guard.js" "$home/.claude/hooks/security-guard.js" + python3 - "$home/.claude/settings.json" <<'PY' +import json, sys +data = { + "mcpServers": { + "streamable-mcp-server": { + "type": "streamable-http", + "url": "http://127.0.0.1:12306/mcp" + } + }, + "hooks": { + "PreToolUse": [ + { + "matcher": "Bash|Write|Edit", + "hooks": [ + { + "type": "command", + "command": "node -e \"const p=require('path'),h=require('os').homedir();require('child_process').execSync('node '+p.join(h,'.claude/hooks/security-guard.js'),{stdio:'inherit'})\"", + "timeout": 5 + } + ] + } + ] + } +} +with open(sys.argv[1], "w", encoding="utf-8") as f: + json.dump(data, f, indent=2) + f.write("\n") +PY + + run_setup "$home" + run_uninstall "$home" + + test ! -f "$home/.claude/CLAUDE.md" + test ! -f "$home/.claude/hooks/security-guard.js" + pass "legacy install upgrade adopts existing managed files" +} + +test_overlapping_mcp_keys_do_not_trigger_legacy_adoption() { + local home + home="$(make_home)" + mkdir -p "$home/.claude/hooks" + cp "$REPO_ROOT/hooks/security-guard.js" "$home/.claude/hooks/security-guard.js" + python3 - "$home/.claude/settings.json" <<'PY' +import json, sys +data = { + "mcpServers": { + "zotero": { + "command": "custom-zotero" + } + }, + "enabledPlugins": { + "superpowers@claude-plugins-official": False + } +} +with open(sys.argv[1], "w", encoding="utf-8") as f: + json.dump(data, f, indent=2) + f.write("\n") +PY + + run_setup "$home" + run_uninstall "$home" + + test -f "$home/.claude/hooks/security-guard.js" + pass "overlapping MCP keys alone do not trigger legacy adoption" +} + +main() { + bash -n "$SETUP_SH" + bash -n "$UNINSTALL_SH" + test_roundtrip_empty_home + test_preserve_preexisting_settings_keys + test_manifest_missing_fails_safe + test_state_records_direct_claude_targets + test_identical_preexisting_file_is_not_owned + test_reinstall_keeps_owned_files_owned + test_legacy_install_upgrade_adopts_existing_files + test_overlapping_mcp_keys_do_not_trigger_legacy_adoption +} + +main "$@" diff --git a/文档润色流和知识库构建流/claude-scholar/scripts/uninstall.sh b/文档润色流和知识库构建流/claude-scholar/scripts/uninstall.sh new file mode 100755 index 0000000..dab0e46 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/scripts/uninstall.sh @@ -0,0 +1,283 @@ +#!/usr/bin/env bash +set -euo pipefail + +CLAUDE_DIR="$HOME/.claude" +MANIFEST_FILE="$CLAUDE_DIR/.claude-scholar-manifest.txt" +STATE_FILE="$CLAUDE_DIR/.claude-scholar-install-state" +BACKUP_ROOT="$CLAUDE_DIR/.claude-scholar-backups" +UNINSTALL_STAMP="$(date +%Y%m%d-%H%M%S)" +UNINSTALL_BACKUP_DIR="$BACKUP_ROOT/uninstall-$UNINSTALL_STAMP" +COMPONENT_DIRS=(skills commands agents rules hooks scripts templates) +LEGACY_MANAGED_PATHS=( + "skills/planning-with-files/SKILL.md" + "skills/planning-with-files/examples.md" + "skills/planning-with-files/reference.md" +) +REMOVED_COUNT=0 +SKIPPED_COUNT=0 +DRY_RUN=0 + +info() { echo -e "\033[1;34m[INFO]\033[0m $*"; } +warn() { echo -e "\033[1;33m[WARN]\033[0m $*"; } +error() { echo -e "\033[1;31m[ERROR]\033[0m $*" >&2; exit 1; } + +usage() { + cat <<'EOF' +Usage: bash scripts/uninstall.sh [--dry-run] + +Removes Claude Scholar managed files from ~/.claude without touching unrelated user files. +- Uses ~/.claude/.claude-scholar-manifest.txt when available. +- Falls back to the current repo checkout when run from a repo working tree. +- Cleans Claude Scholar hook / MCP / plugin entries from ~/.claude/settings.json. +EOF +} + +parse_args() { + while [ "$#" -gt 0 ]; do + case "$1" in + --dry-run) + DRY_RUN=1 + ;; + -h|--help) + usage + exit 0 + ;; + *) + error "Unknown argument: $1" + ;; + esac + shift + done +} + +require_install_metadata() { + [ -f "$MANIFEST_FILE" ] || error "Missing $MANIFEST_FILE. Refusing to guess ownership." + [ -f "$STATE_FILE" ] || error "Missing $STATE_FILE. Refusing to guess settings ownership." +} + +backup_target() { + local target="$1" + [ -e "$target" ] || return 0 + local rel="${target#$CLAUDE_DIR/}" + [ "$rel" = "$target" ] && rel="$(basename "$target")" + mkdir -p "$UNINSTALL_BACKUP_DIR/$(dirname "$rel")" + if [ "$DRY_RUN" -eq 0 ]; then + if [ -d "$target" ]; then + cp -R "$target" "$UNINSTALL_BACKUP_DIR/$rel" + else + cp -p "$target" "$UNINSTALL_BACKUP_DIR/$rel" + fi + fi +} + +append_path() { + local path="$1" + [ -n "$path" ] || return 0 + printf "%s\n" "$path" +} + +collect_manifest_paths() { + cat "$MANIFEST_FILE" + printf "%s\n" "${LEGACY_MANAGED_PATHS[@]}" +} + +remove_managed_files() { + local rel + while IFS= read -r rel; do + [ -n "$rel" ] || continue + case "$rel" in + .*|*..*|/*) continue ;; + esac + local target="$CLAUDE_DIR/$rel" + if [ ! -e "$target" ]; then + SKIPPED_COUNT=$((SKIPPED_COUNT + 1)) + continue + fi + backup_target "$target" + if [ "$DRY_RUN" -eq 0 ]; then + rm -rf "$target" + fi + REMOVED_COUNT=$((REMOVED_COUNT + 1)) + done < <(collect_manifest_paths | LC_ALL=C sort -u) +} + +cleanup_empty_dirs() { + local comp + for comp in "${COMPONENT_DIRS[@]}"; do + if [ -d "$CLAUDE_DIR/$comp" ] && [ "$DRY_RUN" -eq 0 ]; then + find "$CLAUDE_DIR/$comp" -depth -type d -empty -delete + fi + done +} + +cleanup_settings() { + local settings="$CLAUDE_DIR/settings.json" + [ -f "$settings" ] || return 0 + + backup_target "$settings" + if [ "$DRY_RUN" -eq 1 ]; then + info "Would clean Claude Scholar entries from $settings" + return 0 + fi + + SETTINGS_PATH="$settings" STATE_PATH="$STATE_FILE" node <<'NODE' +const fs = require('fs'); + +const settingsPath = process.env.SETTINGS_PATH; +const statePath = process.env.STATE_PATH; +const settings = JSON.parse(fs.readFileSync(settingsPath, 'utf8')); +const state = JSON.parse(fs.readFileSync(statePath, 'utf8')); +const settingsCreated = Boolean(state.settingsCreated); +const addedHooks = Array.isArray(state.settings?.addedHooks) ? state.settings.addedHooks : []; +const addedMcpServers = new Set(Array.isArray(state.settings?.addedMcpServers) ? state.settings.addedMcpServers : []); +const addedMcpServerFields = state.settings?.addedMcpServerFields && typeof state.settings.addedMcpServerFields === 'object' + ? state.settings.addedMcpServerFields + : {}; +const addedEnabledPlugins = new Set(Array.isArray(state.settings?.addedEnabledPlugins) ? state.settings.addedEnabledPlugins : []); + +function hookSignature(hook) { + return JSON.stringify({ + type: hook?.type || '', + command: hook?.command || '', + timeout: hook?.timeout ?? null, + }); +} + +const ownedHookMatchers = new Map(); +for (const hook of addedHooks) { + const key = `${hook.event}::${hook.matcher || '*'}`; + const sigs = ownedHookMatchers.get(key) || new Set(); + sigs.add(hookSignature(hook)); + ownedHookMatchers.set(key, sigs); +} + +function pruneEmptyContainers(root, parts) { + for (let i = parts.length - 1; i > 0; i -= 1) { + const parent = parts.slice(0, i - 1).reduce((acc, key) => (acc && typeof acc === 'object') ? acc[key] : undefined, root); + const key = parts[i - 1]; + if (!parent || typeof parent !== 'object') return; + const value = parent[key]; + if (value && typeof value === 'object' && !Array.isArray(value) && Object.keys(value).length === 0) { + delete parent[key]; + continue; + } + return; + } +} + +function removeNestedPath(root, dottedPath) { + if (!root || typeof root !== 'object' || !dottedPath) return; + const parts = dottedPath.split('.').filter(Boolean); + if (parts.length === 0) return; + let current = root; + for (let i = 0; i < parts.length - 1; i += 1) { + current = current?.[parts[i]]; + if (!current || typeof current !== 'object') return; + } + delete current[parts[parts.length - 1]]; + pruneEmptyContainers(root, parts); +} + +if (settings.hooks && typeof settings.hooks === 'object') { + for (const [eventName, matchers] of Object.entries(settings.hooks)) { + if (!Array.isArray(matchers)) continue; + const nextMatchers = matchers + .map((matcher) => { + const key = `${eventName}::${matcher.matcher || '*'}`; + const owned = ownedHookMatchers.get(key) || new Set(); + const hooks = Array.isArray(matcher.hooks) + ? matcher.hooks.filter((hook) => !owned.has(hookSignature(hook))) + : []; + return hooks.length > 0 ? { ...matcher, hooks } : null; + }) + .filter(Boolean); + if (nextMatchers.length > 0) { + settings.hooks[eventName] = nextMatchers; + } else { + delete settings.hooks[eventName]; + } + } + if (Object.keys(settings.hooks).length === 0) delete settings.hooks; +} + +if (settings.mcpServers && typeof settings.mcpServers === 'object') { + for (const key of addedMcpServers) { + delete settings.mcpServers[key]; + } + for (const [key, paths] of Object.entries(addedMcpServerFields)) { + if (!(key in settings.mcpServers) || !Array.isArray(paths)) continue; + for (const dottedPath of paths) { + removeNestedPath(settings.mcpServers[key], dottedPath); + } + if ( + settings.mcpServers[key] && + typeof settings.mcpServers[key] === 'object' && + !Array.isArray(settings.mcpServers[key]) && + Object.keys(settings.mcpServers[key]).length === 0 + ) { + delete settings.mcpServers[key]; + } + } + if (Object.keys(settings.mcpServers).length === 0) delete settings.mcpServers; +} + +if (settings.enabledPlugins && typeof settings.enabledPlugins === 'object') { + for (const key of addedEnabledPlugins) { + delete settings.enabledPlugins[key]; + } + if (Object.keys(settings.enabledPlugins).length === 0) delete settings.enabledPlugins; +} + +const onlyDefaultTemplateRemainder = + settingsCreated && + Object.keys(settings).every((key) => ['env', 'verbose'].includes(key)) && + settings.verbose === true && + settings.env && + Object.keys(settings.env).length === 1 && + settings.env.GITHUB_PERSONAL_ACCESS_TOKEN === ''; + +if (onlyDefaultTemplateRemainder) { + fs.unlinkSync(settingsPath); +} else { + fs.writeFileSync(settingsPath, JSON.stringify(settings, null, 2) + '\n'); +} +NODE +} + +remove_metadata_files() { + local path + for path in "$MANIFEST_FILE" "$STATE_FILE"; do + [ -e "$path" ] || continue + backup_target "$path" + if [ "$DRY_RUN" -eq 0 ]; then + rm -f "$path" + fi + done +} + +main() { + parse_args "$@" + require_install_metadata + + echo "" + echo "╔══════════════════════════════════════╗" + echo "║ Claude Scholar Uninstaller ║" + echo "╚══════════════════════════════════════╝" + echo "" + + remove_managed_files + cleanup_empty_dirs + cleanup_settings + remove_metadata_files + + if [ "$DRY_RUN" -eq 1 ]; then + info "Dry run complete. Files that would be removed: $REMOVED_COUNT | Missing/skipped: $SKIPPED_COUNT" + exit 0 + fi + + info "Removed files: $REMOVED_COUNT | Missing/skipped: $SKIPPED_COUNT" + info "Uninstall backup: $UNINSTALL_BACKUP_DIR" + info "Done." +} + +main "$@" diff --git a/文档润色流和知识库构建流/claude-scholar/settings.json.template b/文档润色流和知识库构建流/claude-scholar/settings.json.template new file mode 100644 index 0000000..ef41f64 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/settings.json.template @@ -0,0 +1,91 @@ +{ + "env": { + "GITHUB_PERSONAL_ACCESS_TOKEN": "" + }, + "hooks": { + "PreToolUse": [ + { + "matcher": "Bash|Write|Edit", + "hooks": [ + { + "type": "command", + "command": "node -e \"const{execSync}=require('child_process'),p=require('path'),h=require('os').homedir();execSync(\\\"node \\\"+p.join(h,'.claude/hooks/security-guard.js'),{stdio:'inherit'})\"", + "timeout": 5 + } + ] + } + ], + "SessionEnd": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node -e \"const{execSync}=require('child_process'),p=require('path'),h=require('os').homedir();execSync(\\\"node \\\"+p.join(h,'.claude/hooks/session-summary.js'),{stdio:'inherit'})\"", + "timeout": 15 + } + ] + } + ], + "SessionStart": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node -e \"const{execSync}=require('child_process'),p=require('path'),h=require('os').homedir();execSync(\\\"node \\\"+p.join(h,'.claude/hooks/session-start.js'),{stdio:'inherit'})\"", + "timeout": 10 + } + ] + } + ], + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node -e \"const{execSync}=require('child_process'),p=require('path'),h=require('os').homedir();execSync(\\\"node \\\"+p.join(h,'.claude/hooks/stop-summary.js'),{stdio:'inherit'})\"", + "timeout": 10 + } + ] + } + ], + "UserPromptSubmit": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "node -e \"const{execSync}=require('child_process'),p=require('path'),h=require('os').homedir();execSync(\\\"node \\\"+p.join(h,'.claude/hooks/skill-forced-eval.js'),{stdio:'inherit'})\"", + "timeout": 10 + } + ] + } + ] + }, + "enabledPlugins": { + "document-skills@anthropic-agent-skills": true, + "github@claude-plugins-official": true, + "superpowers@claude-plugins-official": true + }, + "mcpServers": { + "streamable-mcp-server": { + "type": "streamable-http", + "url": "http://127.0.0.1:12306/mcp", + "description": "Chrome browser automation control service" + }, + "zotero": { + "command": "zotero-mcp", + "args": ["serve"], + "env": { + "ZOTERO_API_KEY": "", + "ZOTERO_LIBRARY_ID": "", + "ZOTERO_LIBRARY_TYPE": "user", + "UNPAYWALL_EMAIL": "", + "UNSAFE_OPERATIONS": "all" + } + } + }, + "verbose": true +} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/SKILL.md new file mode 100644 index 0000000..485e3fa --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/SKILL.md @@ -0,0 +1,434 @@ +--- +name: agent-identifier +description: Use when creating or configuring Claude Code agents and their frontmatter. +version: 0.1.0 +--- + +# Agent Development for Claude Code Plugins + +## Overview + +Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities. + +**Key concepts:** +- Agents are FOR autonomous work, commands are FOR user-initiated actions +- Markdown file format with YAML frontmatter +- Triggering via description field with examples +- System prompt defines agent behavior +- Model and color customization + +## When to Use + +Use this skill when the user asks to: +- Create an agent +- Add an agent +- Write a subagent +- Define agent frontmatter +- Decide when to use description examples +- Configure agent tools, colors, or model behavior +- Design autonomous agent structure, triggering conditions, or system prompts + +## When Not to Use + +Do not use this skill for: +- Slash command design +- Hook configuration +- MCP server setup +- General plugin layout questions that belong to `plugin-structure` + +## Agent File Structure + +### Complete Format + +```markdown +--- +name: agent-identifier +description: Use this agent when [triggering conditions]. Examples: + + +Context: [Situation description] +user: "[User request]" +assistant: "[How assistant should respond and use this agent]" + +[Why this agent should be triggered] + + + + +[Additional example...] + + +model: inherit +color: blue +tools: ["Read", "Write", "Grep"] +--- + +You are [agent role description]... + +**Your Core Responsibilities:** +1. [Responsibility 1] +2. [Responsibility 2] + +**Analysis Process:** +[Step-by-step workflow] + +**Output Format:** +[What to return] +``` + +## Frontmatter Fields + +### name (required) + +Agent identifier used for namespacing and invocation. + +**Format:** lowercase, numbers, hyphens only +**Length:** 3-50 characters +**Pattern:** Must start and end with alphanumeric + +**Good examples:** +- `code-reviewer` +- `test-generator` +- `api-docs-writer` +- `security-analyzer` + +**Bad examples:** +- `helper` (too generic) +- `-agent-` (starts/ends with hyphen) +- `my_agent` (underscores not allowed) +- `ag` (too short, < 3 chars) + +### description (required) + +Defines when Claude should trigger this agent. **This is the most critical field.** + +**Must include:** +1. Triggering conditions ("Use this agent when...") +2. Multiple `` blocks showing usage +3. Context, user request, and assistant response in each example +4. `` explaining why agent triggers + +**Format:** +``` +Use this agent when [conditions]. Examples: + + +Context: [Scenario description] +user: "[What user says]" +assistant: "[How Claude should respond]" + +[Why this agent is appropriate] + + + +[More examples...] +``` + +**Best practices:** +- Include 2-4 concrete examples +- Show proactive and reactive triggering +- Cover different phrasings of same intent +- Explain reasoning in commentary +- Be specific about when NOT to use the agent + +### model (required) + +Which model the agent should use. + +**Options:** +- `inherit` - Use same model as parent (recommended) +- `sonnet` - Claude Sonnet (balanced) +- `opus` - Claude Opus (most capable, expensive) +- `haiku` - Claude Haiku (fast, cheap) + +**Recommendation:** Use `inherit` unless agent needs specific model capabilities. + +### color (required) + +Visual identifier for agent in UI. + +**Options:** `blue`, `cyan`, `green`, `yellow`, `magenta`, `red` + +**Guidelines:** +- Choose distinct colors for different agents in same plugin +- Use consistent colors for similar agent types +- Blue/cyan: Analysis, review +- Green: Success-oriented tasks +- Yellow: Caution, validation +- Red: Critical, security +- Magenta: Creative, generation + +### tools (optional) + +Restrict agent to specific tools. + +**Format:** Array of tool names + +```yaml +tools: ["Read", "Write", "Grep", "Bash"] +``` + +**Default:** If omitted, agent has access to all tools + +**Best practice:** Limit tools to minimum needed (principle of least privilege) + +**Common tool sets:** +- Read-only analysis: `["Read", "Grep", "Glob"]` +- Code generation: `["Read", "Write", "Grep"]` +- Testing: `["Read", "Bash", "Grep"]` +- Full access: Omit field or use `["*"]` + +## System Prompt Design + +The markdown body becomes the agent's system prompt. Write in second person, addressing the agent directly. + +### Structure + +**Standard template:** +```markdown +You are [role] specializing in [domain]. + +**Your Core Responsibilities:** +1. [Primary responsibility] +2. [Secondary responsibility] +3. [Additional responsibilities...] + +**Analysis Process:** +1. [Step one] +2. [Step two] +3. [Step three] +[...] + +**Quality Standards:** +- [Standard 1] +- [Standard 2] + +**Output Format:** +Provide results in this format: +- [What to include] +- [How to structure] + +**Edge Cases:** +Handle these situations: +- [Edge case 1]: [How to handle] +- [Edge case 2]: [How to handle] +``` + +### Best Practices + +✅ **DO:** +- Write in second person ("You are...", "You will...") +- Be specific about responsibilities +- Provide step-by-step process +- Define output format +- Include quality standards +- Address edge cases +- Keep under 10,000 characters + +❌ **DON'T:** +- Write in first person ("I am...", "I will...") +- Be vague or generic +- Omit process steps +- Leave output format undefined +- Skip quality guidance +- Ignore error cases + +## Creating Agents + +### Method 1: AI-Assisted Generation + +Use this prompt pattern (extracted from Claude Code): + +``` +Create an agent configuration based on this request: "[YOUR DESCRIPTION]" + +Requirements: +1. Extract core intent and responsibilities +2. Design expert persona for the domain +3. Create comprehensive system prompt with: + - Clear behavioral boundaries + - Specific methodologies + - Edge case handling + - Output format +4. Create identifier (lowercase, hyphens, 3-50 chars) +5. Write description with triggering conditions +6. Include 2-3 blocks showing when to use + +Return JSON with: +{ + "identifier": "agent-name", + "whenToUse": "Use this agent when... Examples: ...", + "systemPrompt": "You are..." +} +``` + +Then convert to agent file format with frontmatter. + +See `examples/agent-creation-prompt.md` for complete template. + +### Method 2: Manual Creation + +1. Choose agent identifier (3-50 chars, lowercase, hyphens) +2. Write description with examples +3. Select model (usually `inherit`) +4. Choose color for visual identification +5. Define tools (if restricting access) +6. Write system prompt with structure above +7. Save as `agents/agent-name.md` + +## Validation Rules + +### Identifier Validation + +``` +✅ Valid: code-reviewer, test-gen, api-analyzer-v2 +❌ Invalid: ag (too short), -start (starts with hyphen), my_agent (underscore) +``` + +**Rules:** +- 3-50 characters +- Lowercase letters, numbers, hyphens only +- Must start and end with alphanumeric +- No underscores, spaces, or special characters + +### Description Validation + +**Length:** 10-5,000 characters +**Must include:** Triggering conditions and examples +**Best:** 200-1,000 characters with 2-4 examples + +### System Prompt Validation + +**Length:** 20-10,000 characters +**Best:** 500-3,000 characters +**Structure:** Clear responsibilities, process, output format + +## Agent Organization + +### Plugin Agents Directory + +``` +plugin-name/ +└── agents/ + ├── analyzer.md + ├── reviewer.md + └── generator.md +``` + +All `.md` files in `agents/` are auto-discovered. + +### Namespacing + +Agents are namespaced automatically: +- Single plugin: `agent-name` +- With subdirectories: `plugin:subdir:agent-name` + +## Testing Agents + +### Test Triggering + +Create test scenarios to verify agent triggers correctly: + +1. Write agent with specific triggering examples +2. Use similar phrasing to examples in test +3. Check Claude loads the agent +4. Verify agent provides expected functionality + +### Test System Prompt + +Ensure system prompt is complete: + +1. Give agent typical task +2. Check it follows process steps +3. Verify output format is correct +4. Test edge cases mentioned in prompt +5. Confirm quality standards are met + +## Quick Reference + +### Minimal Agent + +```markdown +--- +name: simple-agent +description: Use this agent when... Examples: ... +model: inherit +color: blue +--- + +You are an agent that [does X]. + +Process: +1. [Step 1] +2. [Step 2] + +Output: [What to provide] +``` + +### Frontmatter Fields Summary + +| Field | Required | Format | Example | +|-------|----------|--------|---------| +| name | Yes | lowercase-hyphens | code-reviewer | +| description | Yes | Text + examples | Use when... ... | +| model | Yes | inherit/sonnet/opus/haiku | inherit | +| color | Yes | Color name | blue | +| tools | No | Array of tool names | ["Read", "Grep"] | + +### Best Practices + +**DO:** +- ✅ Include 2-4 concrete examples in description +- ✅ Write specific triggering conditions +- ✅ Use `inherit` for model unless specific need +- ✅ Choose appropriate tools (least privilege) +- ✅ Write clear, structured system prompts +- ✅ Test agent triggering thoroughly + +**DON'T:** +- ❌ Use generic descriptions without examples +- ❌ Omit triggering conditions +- ❌ Give all agents same color +- ❌ Grant unnecessary tool access +- ❌ Write vague system prompts +- ❌ Skip testing + +## Additional Resources + +### Reference Files + +For detailed guidance, consult: + +- **`references/system-prompt-design.md`** - Complete system prompt patterns +- **`references/triggering-examples.md`** - Example formats and best practices +- **`references/agent-creation-system-prompt.md`** - The exact prompt from Claude Code + +### Example Files + +Working examples in `examples/`: + +- **`agent-creation-prompt.md`** - AI-assisted agent generation template +- **`complete-agent-examples.md`** - Full agent examples for different use cases + +### Utility Scripts + +Development tools in `scripts/`: + +- **`validate-agent.sh`** - Validate agent file structure +- **`test-agent-trigger.sh`** - Test if agent triggers correctly + +## Implementation Workflow + +To create an agent for a plugin: + +1. Define agent purpose and triggering conditions +2. Choose creation method (AI-assisted or manual) +3. Create `agents/agent-name.md` file +4. Write frontmatter with all required fields +5. Write system prompt following best practices +6. Include 2-4 triggering examples in description +7. Validate with `scripts/validate-agent.sh` +8. Test triggering with real scenarios +9. Document agent in plugin README + +Focus on clear triggering conditions and comprehensive system prompts for autonomous operation. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/examples/agent-creation-prompt.md b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/examples/agent-creation-prompt.md new file mode 100644 index 0000000..1258572 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/examples/agent-creation-prompt.md @@ -0,0 +1,238 @@ +# AI-Assisted Agent Generation Template + +Use this template to generate agents using Claude with the agent creation system prompt. + +## Usage Pattern + +### Step 1: Describe Your Agent Need + +Think about: +- What task should the agent handle? +- When should it be triggered? +- Should it be proactive or reactive? +- What are the key responsibilities? + +### Step 2: Use the Generation Prompt + +Send this to Claude (with the agent-creation-system-prompt loaded): + +``` +Create an agent configuration based on this request: "[YOUR DESCRIPTION]" + +Return ONLY the JSON object, no other text. +``` + +**Replace [YOUR DESCRIPTION] with your agent requirements.** + +### Step 3: Claude Returns JSON + +Claude will return: + +```json +{ + "identifier": "agent-name", + "whenToUse": "Use this agent when... Examples: ...", + "systemPrompt": "You are... **Your Core Responsibilities:**..." +} +``` + +### Step 4: Convert to Agent File + +Create `agents/[identifier].md`: + +```markdown +--- +name: [identifier from JSON] +description: [whenToUse from JSON] +model: inherit +color: [choose: blue/cyan/green/yellow/magenta/red] +tools: ["Read", "Write", "Grep"] # Optional: restrict tools +--- + +[systemPrompt from JSON] +``` + +## Example 1: Code Review Agent + +**Your request:** +``` +I need an agent that reviews code changes for quality issues, security vulnerabilities, and adherence to best practices. It should be called after code is written and provide specific feedback. +``` + +**Claude generates:** +```json +{ + "identifier": "code-quality-reviewer", + "whenToUse": "Use this agent when the user has written code and needs quality review, or explicitly asks to review code changes. Examples:\n\n\nContext: User just implemented a new feature\nuser: \"I've added the authentication feature\"\nassistant: \"Great! Let me review the code quality.\"\n\nCode was written, trigger code-quality-reviewer agent for review.\n\nassistant: \"I'll use the code-quality-reviewer agent to analyze the changes.\"\n\n\n\nContext: User explicitly requests review\nuser: \"Can you review my code for issues?\"\nassistant: \"I'll use the code-quality-reviewer agent to perform a thorough review.\"\n\nExplicit review request triggers the agent.\n\n", + "systemPrompt": "You are an expert code quality reviewer specializing in identifying issues in software implementations.\n\n**Your Core Responsibilities:**\n1. Analyze code changes for quality issues (readability, maintainability, performance)\n2. Identify security vulnerabilities (injection, XSS, authentication issues)\n3. Check adherence to project best practices and coding standards\n4. Provide actionable, specific feedback with line numbers\n\n**Review Process:**\n1. Read the code changes using available tools\n2. Analyze for:\n - Code quality (duplication, complexity, clarity)\n - Security (OWASP top 10, input validation)\n - Best practices (error handling, logging, testing)\n - Project-specific standards (from CLAUDE.md)\n3. Identify issues with severity (critical/major/minor)\n4. Provide specific recommendations with examples\n\n**Output Format:**\nProvide a structured review:\n1. Summary (2-3 sentences)\n2. Critical Issues (must fix)\n3. Major Issues (should fix)\n4. Minor Issues (nice to fix)\n5. Positive observations\n6. Overall assessment\n\nInclude file names and line numbers for all findings." +} +``` + +**You create:** + +File: `agents/code-quality-reviewer.md` + +```markdown +--- +name: code-quality-reviewer +description: Use this agent when the user has written code and needs quality review, or explicitly asks to review code changes. Examples: + + +Context: User just implemented a new feature +user: "I've added the authentication feature" +assistant: "Great! Let me review the code quality." + +Code was written, trigger code-quality-reviewer agent for review. + +assistant: "I'll use the code-quality-reviewer agent to analyze the changes." + + + +Context: User explicitly requests review +user: "Can you review my code for issues?" +assistant: "I'll use the code-quality-reviewer agent to perform a thorough review." + +Explicit review request triggers the agent. + + + +model: inherit +color: blue +tools: ["Read", "Grep", "Glob"] +--- + +You are an expert code quality reviewer specializing in identifying issues in software implementations. + +**Your Core Responsibilities:** +1. Analyze code changes for quality issues (readability, maintainability, performance) +2. Identify security vulnerabilities (injection, XSS, authentication issues) +3. Check adherence to project best practices and coding standards +4. Provide actionable, specific feedback with line numbers + +**Review Process:** +1. Read the code changes using available tools +2. Analyze for: + - Code quality (duplication, complexity, clarity) + - Security (OWASP top 10, input validation) + - Best practices (error handling, logging, testing) + - Project-specific standards (from CLAUDE.md) +3. Identify issues with severity (critical/major/minor) +4. Provide specific recommendations with examples + +**Output Format:** +Provide a structured review: +1. Summary (2-3 sentences) +2. Critical Issues (must fix) +3. Major Issues (should fix) +4. Minor Issues (nice to fix) +5. Positive observations +6. Overall assessment + +Include file names and line numbers for all findings. +``` + +## Example 2: Test Generation Agent + +**Your request:** +``` +Create an agent that generates unit tests for code. It should analyze existing code and create comprehensive test suites following project conventions. +``` + +**Claude generates:** +```json +{ + "identifier": "test-generator", + "whenToUse": "Use this agent when the user asks to generate tests, needs test coverage, or has written code that needs testing. Examples:\n\n\nContext: User wrote new functions without tests\nuser: \"I've implemented the user authentication functions\"\nassistant: \"Great! Let me generate tests for these functions.\"\n\nNew code without tests, proactively trigger test-generator.\n\nassistant: \"I'll use the test-generator agent to create comprehensive tests.\"\n", + "systemPrompt": "You are an expert test engineer specializing in creating comprehensive unit tests...\n\n**Your Core Responsibilities:**\n1. Analyze code to understand behavior\n2. Generate test cases covering happy paths and edge cases\n3. Follow project testing conventions\n4. Ensure high code coverage\n\n**Test Generation Process:**\n1. Read target code\n2. Identify testable units (functions, classes, methods)\n3. Design test cases (inputs, expected outputs, edge cases)\n4. Generate tests following project patterns\n5. Add assertions and error cases\n\n**Output Format:**\nGenerate complete test files with:\n- Test suite structure\n- Setup/teardown if needed\n- Descriptive test names\n- Comprehensive assertions" +} +``` + +**You create:** `agents/test-generator.md` with the structure above. + +## Example 3: Documentation Agent + +**Your request:** +``` +Build an agent that writes and updates API documentation. It should analyze code and generate clear, comprehensive docs. +``` + +**Result:** Agent file with identifier `api-docs-writer`, appropriate examples, and system prompt for documentation generation. + +## Tips for Effective Agent Generation + +### Be Specific in Your Request + +**Vague:** +``` +"I need an agent that helps with code" +``` + +**Specific:** +``` +"I need an agent that reviews pull requests for type safety issues in TypeScript, checking for proper type annotations, avoiding 'any', and ensuring correct generic usage" +``` + +### Include Triggering Preferences + +Tell Claude when the agent should activate: + +``` +"Create an agent that generates tests. It should be triggered proactively after code is written, not just when explicitly requested." +``` + +### Mention Project Context + +``` +"Create a code review agent. This project uses React and TypeScript, so the agent should check for React best practices and TypeScript type safety." +``` + +### Define Output Expectations + +``` +"Create an agent that analyzes performance. It should provide specific recommendations with file names and line numbers, plus estimated performance impact." +``` + +## Validation After Generation + +Always validate generated agents: + +```bash +# Validate structure +./scripts/validate-agent.sh agents/your-agent.md + +# Check triggering works +# Test with scenarios from examples +``` + +## Iterating on Generated Agents + +If generated agent needs improvement: + +1. Identify what's missing or wrong +2. Manually edit the agent file +3. Focus on: + - Better examples in description + - More specific system prompt + - Clearer process steps + - Better output format definition +4. Re-validate +5. Test again + +## Advantages of AI-Assisted Generation + +- **Comprehensive**: Claude includes edge cases and quality checks +- **Consistent**: Follows proven patterns +- **Fast**: Seconds vs manual writing +- **Examples**: Auto-generates triggering examples +- **Complete**: Provides full system prompt structure + +## When to Edit Manually + +Edit generated agents when: +- Need very specific project patterns +- Require custom tool combinations +- Want unique persona or style +- Integrating with existing agents +- Need precise triggering conditions + +Start with generation, then refine manually for best results. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/examples/complete-agent-examples.md b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/examples/complete-agent-examples.md new file mode 100644 index 0000000..ec75fba --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/examples/complete-agent-examples.md @@ -0,0 +1,427 @@ +# Complete Agent Examples + +Full, production-ready agent examples for common use cases. Use these as templates for your own agents. + +## Example 1: Code Review Agent + +**File:** `agents/code-reviewer.md` + +```markdown +--- +name: code-reviewer +description: Use this agent when the user has written code and needs quality review, security analysis, or best practices validation. Examples: + + +Context: User just implemented a new feature +user: "I've added the payment processing feature" +assistant: "Great! Let me review the implementation." + +Code written for payment processing (security-critical). Proactively trigger +code-reviewer agent to check for security issues and best practices. + +assistant: "I'll use the code-reviewer agent to analyze the payment code." + + + +Context: User explicitly requests code review +user: "Can you review my code for issues?" +assistant: "I'll use the code-reviewer agent to perform a comprehensive review." + +Explicit code review request triggers the agent. + + + + +Context: Before committing code +user: "I'm ready to commit these changes" +assistant: "Let me review them first." + +Before commit, proactively review code quality. + +assistant: "I'll use the code-reviewer agent to validate the changes." + + +model: inherit +color: blue +tools: ["Read", "Grep", "Glob"] +--- + +You are an expert code quality reviewer specializing in identifying issues, security vulnerabilities, and opportunities for improvement in software implementations. + +**Your Core Responsibilities:** +1. Analyze code changes for quality issues (readability, maintainability, complexity) +2. Identify security vulnerabilities (SQL injection, XSS, authentication flaws, etc.) +3. Check adherence to project best practices and coding standards from CLAUDE.md +4. Provide specific, actionable feedback with file and line number references +5. Recognize and commend good practices + +**Code Review Process:** +1. **Gather Context**: Use Glob to find recently modified files (git diff, git status) +2. **Read Code**: Use Read tool to examine changed files +3. **Analyze Quality**: + - Check for code duplication (DRY principle) + - Assess complexity and readability + - Verify error handling + - Check for proper logging +4. **Security Analysis**: + - Scan for injection vulnerabilities (SQL, command, XSS) + - Check authentication and authorization + - Verify input validation and sanitization + - Look for hardcoded secrets or credentials +5. **Best Practices**: + - Follow project-specific standards from CLAUDE.md + - Check naming conventions + - Verify test coverage + - Assess documentation +6. **Categorize Issues**: Group by severity (critical/major/minor) +7. **Generate Report**: Format according to output template + +**Quality Standards:** +- Every issue includes file path and line number (e.g., `src/auth.ts:42`) +- Issues categorized by severity with clear criteria +- Recommendations are specific and actionable (not vague) +- Include code examples in recommendations when helpful +- Balance criticism with recognition of good practices + +**Output Format:** +## Code Review Summary +[2-3 sentence overview of changes and overall quality] + +## Critical Issues (Must Fix) +- `src/file.ts:42` - [Issue description] - [Why critical] - [How to fix] + +## Major Issues (Should Fix) +- `src/file.ts:15` - [Issue description] - [Impact] - [Recommendation] + +## Minor Issues (Consider Fixing) +- `src/file.ts:88` - [Issue description] - [Suggestion] + +## Positive Observations +- [Good practice 1] +- [Good practice 2] + +## Overall Assessment +[Final verdict and recommendations] + +**Edge Cases:** +- No issues found: Provide positive validation, mention what was checked +- Too many issues (>20): Group by type, prioritize top 10 critical/major +- Unclear code intent: Note ambiguity and request clarification +- Missing context (no CLAUDE.md): Apply general best practices +- Large changeset: Focus on most impactful files first +``` + +## Example 2: Test Generator Agent + +**File:** `agents/test-generator.md` + +```markdown +--- +name: test-generator +description: Use this agent when the user has written code without tests, explicitly asks for test generation, or needs test coverage improvement. Examples: + + +Context: User implemented functions without tests +user: "I've added the data validation functions" +assistant: "Let me generate tests for these." + +New code without tests. Proactively trigger test-generator agent. + +assistant: "I'll use the test-generator agent to create comprehensive tests." + + + +Context: User explicitly requests tests +user: "Generate unit tests for my code" +assistant: "I'll use the test-generator agent to create a complete test suite." + +Direct test generation request triggers the agent. + + + +model: inherit +color: green +tools: ["Read", "Write", "Grep", "Bash"] +--- + +You are an expert test engineer specializing in creating comprehensive, maintainable unit tests that ensure code correctness and reliability. + +**Your Core Responsibilities:** +1. Generate high-quality unit tests with excellent coverage +2. Follow project testing conventions and patterns +3. Include happy path, edge cases, and error scenarios +4. Ensure tests are maintainable and clear + +**Test Generation Process:** +1. **Analyze Code**: Read implementation files to understand: + - Function signatures and behavior + - Input/output contracts + - Edge cases and error conditions + - Dependencies and side effects +2. **Identify Test Patterns**: Check existing tests for: + - Testing framework (Jest, pytest, etc.) + - File organization (test/ directory, *.test.ts, etc.) + - Naming conventions + - Setup/teardown patterns +3. **Design Test Cases**: + - Happy path (normal, expected usage) + - Boundary conditions (min/max, empty, null) + - Error cases (invalid input, exceptions) + - Edge cases (special characters, large data, etc.) +4. **Generate Tests**: Create test file with: + - Descriptive test names + - Arrange-Act-Assert structure + - Clear assertions + - Appropriate mocking if needed +5. **Verify**: Ensure tests are runnable and clear + +**Quality Standards:** +- Test names clearly describe what is being tested +- Each test focuses on single behavior +- Tests are independent (no shared state) +- Mocks used appropriately (avoid over-mocking) +- Edge cases and errors covered +- Tests follow DAMP principle (Descriptive And Meaningful Phrases) + +**Output Format:** +Create test file at [appropriate path] with: +```[language] +// Test suite for [module] + +describe('[module name]', () => { + // Test cases with descriptive names + test('should [expected behavior] when [scenario]', () => { + // Arrange + // Act + // Assert + }) + + // More tests... +}) +``` + +**Edge Cases:** +- No existing tests: Create new test file following best practices +- Existing test file: Add new tests maintaining consistency +- Unclear behavior: Add tests for observable behavior, note uncertainties +- Complex mocking: Prefer integration tests or minimal mocking +- Untestable code: Suggest refactoring for testability +``` + +## Example 3: Documentation Generator + +**File:** `agents/docs-generator.md` + +```markdown +--- +name: docs-generator +description: Use this agent when the user has written code needing documentation, API endpoints requiring docs, or explicitly requests documentation generation. Examples: + + +Context: User implemented new public API +user: "I've added the user management API endpoints" +assistant: "Let me document these endpoints." + +New public API needs documentation. Proactively trigger docs-generator. + +assistant: "I'll use the docs-generator agent to create API documentation." + + + +Context: User requests documentation +user: "Generate docs for this module" +assistant: "I'll use the docs-generator agent to create comprehensive documentation." + +Explicit documentation request triggers the agent. + + + +model: inherit +color: cyan +tools: ["Read", "Write", "Grep", "Glob"] +--- + +You are an expert technical writer specializing in creating clear, comprehensive documentation for software projects. + +**Your Core Responsibilities:** +1. Generate accurate, clear documentation from code +2. Follow project documentation standards +3. Include examples and usage patterns +4. Ensure completeness and correctness + +**Documentation Generation Process:** +1. **Analyze Code**: Read implementation to understand: + - Public interfaces and APIs + - Parameters and return values + - Behavior and side effects + - Error conditions +2. **Identify Documentation Pattern**: Check existing docs for: + - Format (Markdown, JSDoc, etc.) + - Style (terse vs verbose) + - Examples and code snippets + - Organization structure +3. **Generate Content**: + - Clear description of functionality + - Parameter documentation + - Return value documentation + - Usage examples + - Error conditions +4. **Format**: Follow project conventions +5. **Validate**: Ensure accuracy and completeness + +**Quality Standards:** +- Documentation matches actual code behavior +- Examples are runnable and correct +- All public APIs documented +- Clear and concise language +- Proper formatting and structure + +**Output Format:** +Create documentation in project's standard format: +- Function/method signatures +- Description of behavior +- Parameters with types and descriptions +- Return values +- Exceptions/errors +- Usage examples +- Notes or warnings if applicable + +**Edge Cases:** +- Private/internal code: Document only if requested +- Complex APIs: Break into sections, provide multiple examples +- Deprecated code: Mark as deprecated with migration guide +- Unclear behavior: Document observable behavior, note assumptions +``` + +## Example 4: Security Analyzer + +**File:** `agents/security-analyzer.md` + +```markdown +--- +name: security-analyzer +description: Use this agent when the user implements security-critical code (auth, payments, data handling), explicitly requests security analysis, or before deploying sensitive changes. Examples: + + +Context: User implemented authentication logic +user: "I've added JWT token validation" +assistant: "Let me check the security." + +Authentication code is security-critical. Proactively trigger security-analyzer. + +assistant: "I'll use the security-analyzer agent to review for security vulnerabilities." + + + +Context: User requests security check +user: "Check my code for security issues" +assistant: "I'll use the security-analyzer agent to perform a thorough security review." + +Explicit security review request triggers the agent. + + + +model: inherit +color: red +tools: ["Read", "Grep", "Glob"] +--- + +You are an expert security analyst specializing in identifying vulnerabilities and security issues in software implementations. + +**Your Core Responsibilities:** +1. Identify security vulnerabilities (OWASP Top 10 and beyond) +2. Analyze authentication and authorization logic +3. Check input validation and sanitization +4. Verify secure data handling and storage +5. Provide specific remediation guidance + +**Security Analysis Process:** +1. **Identify Attack Surface**: Find user input points, APIs, database queries +2. **Check Common Vulnerabilities**: + - Injection (SQL, command, XSS, etc.) + - Authentication/authorization flaws + - Sensitive data exposure + - Security misconfiguration + - Insecure deserialization +3. **Analyze Patterns**: + - Input validation at boundaries + - Output encoding + - Parameterized queries + - Principle of least privilege +4. **Assess Risk**: Categorize by severity and exploitability +5. **Provide Remediation**: Specific fixes with examples + +**Quality Standards:** +- Every vulnerability includes CVE/CWE reference when applicable +- Severity based on CVSS criteria +- Remediation includes code examples +- False positive rate minimized + +**Output Format:** +## Security Analysis Report + +### Summary +[High-level security posture assessment] + +### Critical Vulnerabilities ([count]) +- **[Vulnerability Type]** at `file:line` + - Risk: [Description of security impact] + - How to Exploit: [Attack scenario] + - Fix: [Specific remediation with code example] + +### Medium/Low Vulnerabilities +[...] + +### Security Best Practices Recommendations +[...] + +### Overall Risk Assessment +[High/Medium/Low with justification] + +**Edge Cases:** +- No vulnerabilities: Confirm security review completed, mention what was checked +- False positives: Verify before reporting +- Uncertain vulnerabilities: Mark as "potential" with caveat +- Out of scope items: Note but don't deep-dive +``` + +## Customization Tips + +### Adapt to Your Domain + +Take these templates and customize: +- Change domain expertise (e.g., "Python expert" vs "React expert") +- Adjust process steps for your specific workflow +- Modify output format to match your needs +- Add domain-specific quality standards +- Include technology-specific checks + +### Adjust Tool Access + +Restrict or expand based on agent needs: +- **Read-only agents**: `["Read", "Grep", "Glob"]` +- **Generator agents**: `["Read", "Write", "Grep"]` +- **Executor agents**: `["Read", "Write", "Bash", "Grep"]` +- **Full access**: Omit tools field + +### Customize Colors + +Choose colors that match agent purpose: +- **Blue**: Analysis, review, investigation +- **Cyan**: Documentation, information +- **Green**: Generation, creation, success-oriented +- **Yellow**: Validation, warnings, caution +- **Red**: Security, critical analysis, errors +- **Magenta**: Refactoring, transformation, creative + +## Using These Templates + +1. Copy template that matches your use case +2. Replace placeholders with your specifics +3. Customize process steps for your domain +4. Adjust examples to your triggering scenarios +5. Validate with `scripts/validate-agent.sh` +6. Test triggering with real scenarios +7. Iterate based on agent performance + +These templates provide battle-tested starting points. Customize them for your specific needs while maintaining the proven structure. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/agent-creation-system-prompt.md b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/agent-creation-system-prompt.md new file mode 100644 index 0000000..614c8dd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/agent-creation-system-prompt.md @@ -0,0 +1,207 @@ +# Agent Creation System Prompt + +This is the exact system prompt used by Claude Code's agent generation feature, refined through extensive production use. + +## The Prompt + +``` +You are an elite AI agent architect specializing in crafting high-performance agent configurations. Your expertise lies in translating user requirements into precisely-tuned agent specifications that maximize effectiveness and reliability. + +**Important Context**: You may have access to project-specific instructions from CLAUDE.md files and other context that may include coding standards, project structure, and custom requirements. Consider this context when creating agents to ensure they align with the project's established patterns and practices. + +When a user describes what they want an agent to do, you will: + +1. **Extract Core Intent**: Identify the fundamental purpose, key responsibilities, and success criteria for the agent. Look for both explicit requirements and implicit needs. Consider any project-specific context from CLAUDE.md files. For agents that are meant to review code, you should assume that the user is asking to review recently written code and not the whole codebase, unless the user has explicitly instructed you otherwise. + +2. **Design Expert Persona**: Create a compelling expert identity that embodies deep domain knowledge relevant to the task. The persona should inspire confidence and guide the agent's decision-making approach. + +3. **Architect Comprehensive Instructions**: Develop a system prompt that: + - Establishes clear behavioral boundaries and operational parameters + - Provides specific methodologies and best practices for task execution + - Anticipates edge cases and provides guidance for handling them + - Incorporates any specific requirements or preferences mentioned by the user + - Defines output format expectations when relevant + - Aligns with project-specific coding standards and patterns from CLAUDE.md + +4. **Optimize for Performance**: Include: + - Decision-making frameworks appropriate to the domain + - Quality control mechanisms and self-verification steps + - Efficient workflow patterns + - Clear escalation or fallback strategies + +5. **Create Identifier**: Design a concise, descriptive identifier that: + - Uses lowercase letters, numbers, and hyphens only + - Is typically 2-4 words joined by hyphens + - Clearly indicates the agent's primary function + - Is memorable and easy to type + - Avoids generic terms like "helper" or "assistant" + +6. **Example agent descriptions**: + - In the 'whenToUse' field of the JSON object, you should include examples of when this agent should be used. + - Examples should be of the form: + + Context: The user is creating a code-review agent that should be called after a logical chunk of code is written. + user: "Please write a function that checks if a number is prime" + assistant: "Here is the relevant function: " + + + Since a logical chunk of code was written and the task was completed, now use the code-review agent to review the code. + + assistant: "Now let me use the code-reviewer agent to review the code" + + - If the user mentioned or implied that the agent should be used proactively, you should include examples of this. + - NOTE: Ensure that in the examples, you are making the assistant use the Agent tool and not simply respond directly to the task. + +Your output must be a valid JSON object with exactly these fields: +{ + "identifier": "A unique, descriptive identifier using lowercase letters, numbers, and hyphens (e.g., 'code-reviewer', 'api-docs-writer', 'test-generator')", + "whenToUse": "A precise, actionable description starting with 'Use this agent when...' that clearly defines the triggering conditions and use cases. Ensure you include examples as described above.", + "systemPrompt": "The complete system prompt that will govern the agent's behavior, written in second person ('You are...', 'You will...') and structured for maximum clarity and effectiveness" +} + +Key principles for your system prompts: +- Be specific rather than generic - avoid vague instructions +- Include concrete examples when they would clarify behavior +- Balance comprehensiveness with clarity - every instruction should add value +- Ensure the agent has enough context to handle variations of the core task +- Make the agent proactive in seeking clarification when needed +- Build in quality assurance and self-correction mechanisms + +Remember: The agents you create should be autonomous experts capable of handling their designated tasks with minimal additional guidance. Your system prompts are their complete operational manual. +``` + +## Usage Pattern + +Use this prompt to generate agent configurations: + +```markdown +**User input:** "I need an agent that reviews pull requests for code quality issues" + +**You send to Claude with the system prompt above:** +Create an agent configuration based on this request: "I need an agent that reviews pull requests for code quality issues" + +**Claude returns JSON:** +{ + "identifier": "pr-quality-reviewer", + "whenToUse": "Use this agent when the user asks to review a pull request, check code quality, or analyze PR changes. Examples:\n\n\nContext: User has created a PR and wants quality review\nuser: \"Can you review PR #123 for code quality?\"\nassistant: \"I'll use the pr-quality-reviewer agent to analyze the PR.\"\n\nPR review request triggers the pr-quality-reviewer agent.\n\n", + "systemPrompt": "You are an expert code quality reviewer...\n\n**Your Core Responsibilities:**\n1. Analyze code changes for quality issues\n2. Check adherence to best practices\n..." +} +``` + +## Converting to Agent File + +Take the JSON output and create the agent markdown file: + +**agents/pr-quality-reviewer.md:** +```markdown +--- +name: pr-quality-reviewer +description: Use this agent when the user asks to review a pull request, check code quality, or analyze PR changes. Examples: + + +Context: User has created a PR and wants quality review +user: "Can you review PR #123 for code quality?" +assistant: "I'll use the pr-quality-reviewer agent to analyze the PR." + +PR review request triggers the pr-quality-reviewer agent. + + + +model: inherit +color: blue +--- + +You are an expert code quality reviewer... + +**Your Core Responsibilities:** +1. Analyze code changes for quality issues +2. Check adherence to best practices +... +``` + +## Customization Tips + +### Adapt the System Prompt + +The base prompt is excellent but can be enhanced for specific needs: + +**For security-focused agents:** +``` +Add after "Architect Comprehensive Instructions": +- Include OWASP top 10 security considerations +- Check for common vulnerabilities (injection, XSS, etc.) +- Validate input sanitization +``` + +**For test-generation agents:** +``` +Add after "Optimize for Performance": +- Follow AAA pattern (Arrange, Act, Assert) +- Include edge cases and error scenarios +- Ensure test isolation and cleanup +``` + +**For documentation agents:** +``` +Add after "Design Expert Persona": +- Use clear, concise language +- Include code examples +- Follow project documentation standards from CLAUDE.md +``` + +## Best Practices from Internal Implementation + +### 1. Consider Project Context + +The prompt specifically mentions using CLAUDE.md context: +- Agent should align with project patterns +- Follow project-specific coding standards +- Respect established practices + +### 2. Proactive Agent Design + +Include examples showing proactive usage: +``` + +Context: After writing code, agent should review proactively +user: "Please write a function..." +assistant: "[Writes function]" + +Code written, now use review agent proactively. + +assistant: "Now let me review this code with the code-reviewer agent" + +``` + +### 3. Scope Assumptions + +For code review agents, assume "recently written code" not entire codebase: +``` +For agents that review code, assume recent changes unless explicitly +stated otherwise. +``` + +### 4. Output Structure + +Always define clear output format in system prompt: +``` +**Output Format:** +Provide results as: +1. Summary (2-3 sentences) +2. Detailed findings (bullet points) +3. Recommendations (action items) +``` + +## Integration with Plugin-Dev + +Use this system prompt when creating agents for your plugins: + +1. Take user request for agent functionality +2. Feed to Claude with this system prompt +3. Get JSON output (identifier, whenToUse, systemPrompt) +4. Convert to agent markdown file with frontmatter +5. Validate with agent validation rules +6. Test triggering conditions +7. Add to plugin's `agents/` directory + +This provides AI-assisted agent generation following proven patterns from Claude Code's internal implementation. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/system-prompt-design.md b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/system-prompt-design.md new file mode 100644 index 0000000..6efa854 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/system-prompt-design.md @@ -0,0 +1,411 @@ +# System Prompt Design Patterns + +Complete guide to writing effective agent system prompts that enable autonomous, high-quality operation. + +## Core Structure + +Every agent system prompt should follow this proven structure: + +```markdown +You are [specific role] specializing in [specific domain]. + +**Your Core Responsibilities:** +1. [Primary responsibility - the main task] +2. [Secondary responsibility - supporting task] +3. [Additional responsibilities as needed] + +**[Task Name] Process:** +1. [First concrete step] +2. [Second concrete step] +3. [Continue with clear steps] +[...] + +**Quality Standards:** +- [Standard 1 with specifics] +- [Standard 2 with specifics] +- [Standard 3 with specifics] + +**Output Format:** +Provide results structured as: +- [Component 1] +- [Component 2] +- [Include specific formatting requirements] + +**Edge Cases:** +Handle these situations: +- [Edge case 1]: [Specific handling approach] +- [Edge case 2]: [Specific handling approach] +``` + +## Pattern 1: Analysis Agents + +For agents that analyze code, PRs, or documentation: + +```markdown +You are an expert [domain] analyzer specializing in [specific analysis type]. + +**Your Core Responsibilities:** +1. Thoroughly analyze [what] for [specific issues] +2. Identify [patterns/problems/opportunities] +3. Provide actionable recommendations + +**Analysis Process:** +1. **Gather Context**: Read [what] using available tools +2. **Initial Scan**: Identify obvious [issues/patterns] +3. **Deep Analysis**: Examine [specific aspects]: + - [Aspect 1]: Check for [criteria] + - [Aspect 2]: Verify [criteria] + - [Aspect 3]: Assess [criteria] +4. **Synthesize Findings**: Group related issues +5. **Prioritize**: Rank by [severity/impact/urgency] +6. **Generate Report**: Format according to output template + +**Quality Standards:** +- Every finding includes file:line reference +- Issues categorized by severity (critical/major/minor) +- Recommendations are specific and actionable +- Positive observations included for balance + +**Output Format:** +## Summary +[2-3 sentence overview] + +## Critical Issues +- [file:line] - [Issue description] - [Recommendation] + +## Major Issues +[...] + +## Minor Issues +[...] + +## Recommendations +[...] + +**Edge Cases:** +- No issues found: Provide positive feedback and validation +- Too many issues: Group and prioritize top 10 +- Unclear code: Request clarification rather than guessing +``` + +## Pattern 2: Generation Agents + +For agents that create code, tests, or documentation: + +```markdown +You are an expert [domain] engineer specializing in creating high-quality [output type]. + +**Your Core Responsibilities:** +1. Generate [what] that meets [quality standards] +2. Follow [specific conventions/patterns] +3. Ensure [correctness/completeness/clarity] + +**Generation Process:** +1. **Understand Requirements**: Analyze what needs to be created +2. **Gather Context**: Read existing [code/docs/tests] for patterns +3. **Design Structure**: Plan [architecture/organization/flow] +4. **Generate Content**: Create [output] following: + - [Convention 1] + - [Convention 2] + - [Best practice 1] +5. **Validate**: Verify [correctness/completeness] +6. **Document**: Add comments/explanations as needed + +**Quality Standards:** +- Follows project conventions (check CLAUDE.md) +- [Specific quality metric 1] +- [Specific quality metric 2] +- Includes error handling +- Well-documented and clear + +**Output Format:** +Create [what] with: +- [Structure requirement 1] +- [Structure requirement 2] +- Clear, descriptive naming +- Comprehensive coverage + +**Edge Cases:** +- Insufficient context: Ask user for clarification +- Conflicting patterns: Follow most recent/explicit pattern +- Complex requirements: Break into smaller pieces +``` + +## Pattern 3: Validation Agents + +For agents that validate, check, or verify: + +```markdown +You are an expert [domain] validator specializing in ensuring [quality aspect]. + +**Your Core Responsibilities:** +1. Validate [what] against [criteria] +2. Identify violations and issues +3. Provide clear pass/fail determination + +**Validation Process:** +1. **Load Criteria**: Understand validation requirements +2. **Scan Target**: Read [what] needs validation +3. **Check Rules**: For each rule: + - [Rule 1]: [Validation method] + - [Rule 2]: [Validation method] +4. **Collect Violations**: Document each failure with details +5. **Assess Severity**: Categorize issues +6. **Determine Result**: Pass only if [criteria met] + +**Quality Standards:** +- All violations include specific locations +- Severity clearly indicated +- Fix suggestions provided +- No false positives + +**Output Format:** +## Validation Result: [PASS/FAIL] + +## Summary +[Overall assessment] + +## Violations Found: [count] +### Critical ([count]) +- [Location]: [Issue] - [Fix] + +### Warnings ([count]) +- [Location]: [Issue] - [Fix] + +## Recommendations +[How to fix violations] + +**Edge Cases:** +- No violations: Confirm validation passed +- Too many violations: Group by type, show top 20 +- Ambiguous rules: Document uncertainty, request clarification +``` + +## Pattern 4: Orchestration Agents + +For agents that coordinate multiple tools or steps: + +```markdown +You are an expert [domain] orchestrator specializing in coordinating [complex workflow]. + +**Your Core Responsibilities:** +1. Coordinate [multi-step process] +2. Manage [resources/tools/dependencies] +3. Ensure [successful completion/integration] + +**Orchestration Process:** +1. **Plan**: Understand full workflow and dependencies +2. **Prepare**: Set up prerequisites +3. **Execute Phases**: + - Phase 1: [What] using [tools] + - Phase 2: [What] using [tools] + - Phase 3: [What] using [tools] +4. **Monitor**: Track progress and handle failures +5. **Verify**: Confirm successful completion +6. **Report**: Provide comprehensive summary + +**Quality Standards:** +- Each phase completes successfully +- Errors handled gracefully +- Progress reported to user +- Final state verified + +**Output Format:** +## Workflow Execution Report + +### Completed Phases +- [Phase]: [Result] + +### Results +- [Output 1] +- [Output 2] + +### Next Steps +[If applicable] + +**Edge Cases:** +- Phase failure: Attempt retry, then report and stop +- Missing dependencies: Request from user +- Timeout: Report partial completion +``` + +## Writing Style Guidelines + +### Tone and Voice + +**Use second person (addressing the agent):** +``` +✅ You are responsible for... +✅ You will analyze... +✅ Your process should... + +❌ The agent is responsible for... +❌ This agent will analyze... +❌ I will analyze... +``` + +### Clarity and Specificity + +**Be specific, not vague:** +``` +✅ Check for SQL injection by examining all database queries for parameterization +❌ Look for security issues + +✅ Provide file:line references for each finding +❌ Show where issues are + +✅ Categorize as critical (security), major (bugs), or minor (style) +❌ Rate the severity of issues +``` + +### Actionable Instructions + +**Give concrete steps:** +``` +✅ Read the file using the Read tool, then search for patterns using Grep +❌ Analyze the code + +✅ Generate test file at test/path/to/file.test.ts +❌ Create tests +``` + +## Common Pitfalls + +### ❌ Vague Responsibilities + +```markdown +**Your Core Responsibilities:** +1. Help the user with their code +2. Provide assistance +3. Be helpful +``` + +**Why bad:** Not specific enough to guide behavior. + +### ✅ Specific Responsibilities + +```markdown +**Your Core Responsibilities:** +1. Analyze TypeScript code for type safety issues +2. Identify missing type annotations and improper 'any' usage +3. Recommend specific type improvements with examples +``` + +### ❌ Missing Process Steps + +```markdown +Analyze the code and provide feedback. +``` + +**Why bad:** Agent doesn't know HOW to analyze. + +### ✅ Clear Process + +```markdown +**Analysis Process:** +1. Read code files using Read tool +2. Scan for type annotations on all functions +3. Check for 'any' type usage +4. Verify generic type parameters +5. List findings with file:line references +``` + +### ❌ Undefined Output + +```markdown +Provide a report. +``` + +**Why bad:** Agent doesn't know what format to use. + +### ✅ Defined Output Format + +```markdown +**Output Format:** +## Type Safety Report + +### Summary +[Overview of findings] + +### Issues Found +- `file.ts:42` - Missing return type on `processData` +- `utils.ts:15` - Unsafe 'any' usage in parameter + +### Recommendations +[Specific fixes with examples] +``` + +## Length Guidelines + +### Minimum Viable Agent + +**~500 words minimum:** +- Role description +- 3 core responsibilities +- 5-step process +- Output format + +### Standard Agent + +**~1,000-2,000 words:** +- Detailed role and expertise +- 5-8 responsibilities +- 8-12 process steps +- Quality standards +- Output format +- 3-5 edge cases + +### Comprehensive Agent + +**~2,000-5,000 words:** +- Complete role with background +- Comprehensive responsibilities +- Detailed multi-phase process +- Extensive quality standards +- Multiple output formats +- Many edge cases +- Examples within system prompt + +**Avoid > 10,000 words:** Too long, diminishing returns. + +## Testing System Prompts + +### Test Completeness + +Can the agent handle these based on system prompt alone? + +- [ ] Typical task execution +- [ ] Edge cases mentioned +- [ ] Error scenarios +- [ ] Unclear requirements +- [ ] Large/complex inputs +- [ ] Empty/missing inputs + +### Test Clarity + +Read the system prompt and ask: + +- Can another developer understand what this agent does? +- Are process steps clear and actionable? +- Is output format unambiguous? +- Are quality standards measurable? + +### Iterate Based on Results + +After testing agent: +1. Identify where it struggled +2. Add missing guidance to system prompt +3. Clarify ambiguous instructions +4. Add process steps for edge cases +5. Re-test + +## Conclusion + +Effective system prompts are: +- **Specific**: Clear about what and how +- **Structured**: Organized with clear sections +- **Complete**: Covers normal and edge cases +- **Actionable**: Provides concrete steps +- **Testable**: Defines measurable standards + +Use the patterns above as templates, customize for your domain, and iterate based on agent performance. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/triggering-examples.md b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/triggering-examples.md new file mode 100644 index 0000000..d97b87b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/references/triggering-examples.md @@ -0,0 +1,491 @@ +# Agent Triggering Examples: Best Practices + +Complete guide to writing effective `` blocks in agent descriptions for reliable triggering. + +## Example Block Format + +The standard format for triggering examples: + +```markdown + +Context: [Describe the situation - what led to this interaction] +user: "[Exact user message or request]" +assistant: "[How Claude should respond before triggering]" + +[Explanation of why this agent should be triggered in this scenario] + +assistant: "[How Claude triggers the agent - usually 'I'll use the [agent-name] agent...']" + +``` + +## Anatomy of a Good Example + +### Context + +**Purpose:** Set the scene - what happened before the user's message + +**Good contexts:** +``` +Context: User just implemented a new authentication feature +Context: User has created a PR and wants it reviewed +Context: User is debugging a test failure +Context: After writing several functions without documentation +``` + +**Bad contexts:** +``` +Context: User needs help (too vague) +Context: Normal usage (not specific) +``` + +### User Message + +**Purpose:** Show the exact phrasing that should trigger the agent + +**Good user messages:** +``` +user: "I've added the OAuth flow, can you check it?" +user: "Review PR #123" +user: "Why is this test failing?" +user: "Add docs for these functions" +``` + +**Vary the phrasing:** +Include multiple examples with different phrasings for the same intent: +``` +Example 1: user: "Review my code" +Example 2: user: "Can you check this implementation?" +Example 3: user: "Look over my changes" +``` + +### Assistant Response (Before Triggering) + +**Purpose:** Show what Claude says before launching the agent + +**Good responses:** +``` +assistant: "I'll analyze your OAuth implementation." +assistant: "Let me review that PR for you." +assistant: "I'll investigate the test failure." +``` + +**Proactive example:** +``` +assistant: "Great! Now let me review the code quality." + +Code was just written, proactively trigger review agent. + +``` + +### Commentary + +**Purpose:** Explain the reasoning - WHY this agent should trigger + +**Good commentary:** +``` + +User explicitly requested code review, trigger the code-reviewer agent. + + + +After code implementation, proactively use review agent to check quality. + + + +PR analysis request matches pr-analyzer agent's expertise. + +``` + +**Include decision logic:** +``` + +User wrote tests (Test tool used). The test-analyzer agent should check +test quality and coverage before continuing. + +``` + +### Assistant Response (Triggering) + +**Purpose:** Show how Claude invokes the agent + +**Standard pattern:** +``` +assistant: "I'll use the [agent-name] agent to [what it will do]." +``` + +**Examples:** +``` +assistant: "I'll use the code-reviewer agent to analyze the changes." +assistant: "Let me use the test-generator agent to create comprehensive tests." +assistant: "I'll use the security-analyzer agent to check for vulnerabilities." +``` + +## Example Types + +### Type 1: Explicit Request + +User directly asks for what the agent does: + +```markdown + +Context: User explicitly requests security analysis +user: "Check my code for security vulnerabilities" +assistant: "I'll use the security-analyzer agent to perform a thorough security review." + +Direct security analysis request triggers the security-analyzer agent. + + +``` + +### Type 2: Proactive Triggering + +Agent triggers after relevant work without explicit request: + +```markdown + +Context: User just implemented database queries +user: "I've added the user search functionality" +assistant: "Great! Let me review it for security." + +Database code written. Proactively trigger security-analyzer to check +for SQL injection and other database security issues. + +assistant: "I'll use the security-analyzer agent to check the database code." + +``` + +### Type 3: Implicit Request + +User implies need without stating it directly: + +```markdown + +Context: User mentions code is hard to understand +user: "This code is confusing and hard to follow" +assistant: "I can help improve the code clarity." + +User indicates complexity issues. Trigger code-simplifier agent to refactor +for better readability. + +assistant: "I'll use the code-simplifier agent to suggest improvements." + +``` + +### Type 4: Tool Usage Pattern + +Agent triggers based on prior tool usage: + +```markdown + +Context: User made multiple edits to test files +user: "I've updated all the tests" +assistant: "Great! Let me verify test quality." + +Multiple Edit tools used on test files. Proactively trigger test-quality-analyzer +to ensure tests follow best practices. + +assistant: "I'll use the test-quality-analyzer agent to review the tests." + +``` + +## Multiple Examples Strategy + +### Cover Different Phrasings + +```markdown + +user: "Review my code" +[...] + + + +user: "Can you check my implementation?" +[...] + + + +user: "Look over these changes" +[...] + +``` + +### Cover Proactive and Reactive + +```markdown + +Context: User explicitly requests review +user: "Review my code for issues" +[...] + + + +Context: After user writes code +user: "I've implemented the feature" +assistant: "Great! Now let me review it." + +Code written, proactively review. + +[...] + +``` + +### Cover Edge Cases + +```markdown + +Context: Typical usage +user: "Check my PR" +[...] + + + +Context: Large PR that needs thorough analysis +user: "This is a big PR, can you do a deep review?" +[...] + +Large PR mentioned, use thorough analysis mode. + + +``` + +## Common Mistakes + +### ❌ Missing Context + +```markdown + +user: "Review my code" +assistant: "I'll use the code-reviewer agent." + +``` + +**Why bad:** No context about what led to this request. + +### ✅ With Context + +```markdown + +Context: User just finished implementing authentication +user: "Review my code" +assistant: "I'll use the code-reviewer agent to analyze the auth implementation." + +Auth code written, review for security and best practices. + + +``` + +### ❌ No Commentary + +```markdown + +Context: User requests review +user: "Check my changes" +assistant: "I'll use the reviewer agent." + +``` + +**Why bad:** Doesn't explain WHY agent triggers. + +### ✅ With Commentary + +```markdown + +Context: User requests review after making changes +user: "Check my changes" +assistant: "I'll use the code-reviewer agent to analyze the modifications." + +Code review request triggers agent to check quality, security, and adherence to standards. + + +``` + +### ❌ Agent Responds Directly + +```markdown + +user: "Review my code" +assistant: "I found the following issues: [lists issues]" + +``` + +**Why bad:** Shows agent's output, not triggering. + +### ✅ Shows Triggering + +```markdown + +user: "Review my code" +assistant: "I'll use the code-reviewer agent to perform the review." + +Review request triggers the agent. + + +``` + +## How Many Examples? + +### Minimum: 2 Examples + +Cover at least: +1. Explicit request +2. One variation or proactive trigger + +### Recommended: 3-4 Examples + +Cover: +1. Explicit request (direct ask) +2. Implicit request (user implies need) +3. Proactive trigger (after relevant work) +4. Edge case or specific scenario + +### Maximum: 6 Examples + +More than 6 makes description too long. Focus on most important scenarios. + +## Template Library + +### Code Review Agent + +```markdown + +Context: User just implemented a new feature +user: "I've added the user registration feature" +assistant: "Great! Let me review the code quality." + +Code written, proactively trigger code-reviewer agent. + +assistant: "I'll use the code-reviewer agent to analyze the implementation." + + + +Context: User explicitly requests review +user: "Can you review my changes for issues?" +assistant: "I'll use the code-reviewer agent to perform a thorough review." + +Explicit review request triggers the agent. + + +``` + +### Test Generation Agent + +```markdown + +Context: User implemented functions without tests +user: "I've added the data processing functions" +assistant: "Great! Let me generate tests for these." + +New code without tests, proactively trigger test-generator agent. + +assistant: "I'll use the test-generator agent to create comprehensive tests." + + + +Context: User explicitly asks for tests +user: "Generate tests for my code" +assistant: "I'll use the test-generator agent to create a complete test suite." + +Direct test generation request triggers the agent. + + +``` + +### Documentation Agent + +```markdown + +Context: User added new API endpoints +user: "I've implemented the REST API endpoints" +assistant: "I'll document these endpoints." + +New API code, proactively generate documentation. + +assistant: "I'll use the api-docs-writer agent to create comprehensive documentation." + + + +Context: User requests documentation +user: "Write docs for this API" +assistant: "I'll use the api-docs-writer agent to generate clear documentation." + +Documentation request triggers the agent. + + +``` + +### Validation Agent + +```markdown + +Context: User ready to commit changes +user: "I'm ready to commit this code" +assistant: "Let me validate it first." + +Before commit, proactively validate with validation-agent. + +assistant: "I'll use the code-validator agent to check for issues." + + + +Context: User asks for validation +user: "Validate my implementation" +assistant: "I'll use the code-validator agent to verify correctness." + +Explicit validation request triggers the agent. + + +``` + +## Debugging Triggering Issues + +### Agent Not Triggering + +**Check:** +1. Examples include relevant keywords from user message +2. Context matches actual usage scenarios +3. Commentary explains triggering logic clearly +4. Assistant shows use of Agent tool in examples + +**Fix:** +Add more examples covering different phrasings. + +### Agent Triggers Too Often + +**Check:** +1. Examples are too broad or generic +2. Triggering conditions overlap with other agents +3. Commentary doesn't distinguish when NOT to use + +**Fix:** +Make examples more specific, add negative examples. + +### Agent Triggers in Wrong Scenarios + +**Check:** +1. Examples don't match actual intended use +2. Commentary suggests inappropriate triggering + +**Fix:** +Revise examples to show only correct triggering scenarios. + +## Best Practices Summary + +✅ **DO:** +- Include 2-4 concrete, specific examples +- Show both explicit and proactive triggering +- Provide clear context for each example +- Explain reasoning in commentary +- Vary user message phrasing +- Show Claude using Agent tool + +❌ **DON'T:** +- Use generic, vague examples +- Omit context or commentary +- Show only one type of triggering +- Skip the agent invocation step +- Make examples too similar +- Forget to explain why agent triggers + +## Conclusion + +Well-crafted examples are crucial for reliable agent triggering. Invest time in creating diverse, specific examples that clearly demonstrate when and why the agent should be used. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/scripts/validate-agent.sh b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/scripts/validate-agent.sh new file mode 100644 index 0000000..ca4dfd4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/agent-identifier/scripts/validate-agent.sh @@ -0,0 +1,217 @@ +#!/bin/bash +# Agent File Validator +# Validates agent markdown files for correct structure and content + +set -euo pipefail + +# Usage +if [ $# -eq 0 ]; then + echo "Usage: $0 " + echo "" + echo "Validates agent file for:" + echo " - YAML frontmatter structure" + echo " - Required fields (name, description, model, color)" + echo " - Field formats and constraints" + echo " - System prompt presence and length" + echo " - Example blocks in description" + exit 1 +fi + +AGENT_FILE="$1" + +echo "🔍 Validating agent file: $AGENT_FILE" +echo "" + +# Check 1: File exists +if [ ! -f "$AGENT_FILE" ]; then + echo "❌ File not found: $AGENT_FILE" + exit 1 +fi +echo "✅ File exists" + +# Check 2: Starts with --- +FIRST_LINE=$(head -1 "$AGENT_FILE") +if [ "$FIRST_LINE" != "---" ]; then + echo "❌ File must start with YAML frontmatter (---)" + exit 1 +fi +echo "✅ Starts with frontmatter" + +# Check 3: Has closing --- +if ! tail -n +2 "$AGENT_FILE" | grep -q '^---$'; then + echo "❌ Frontmatter not closed (missing second ---)" + exit 1 +fi +echo "✅ Frontmatter properly closed" + +# Extract frontmatter and system prompt +FRONTMATTER=$(sed -n '/^---$/,/^---$/{ /^---$/d; p; }' "$AGENT_FILE") +SYSTEM_PROMPT=$(awk '/^---$/{i++; next} i>=2' "$AGENT_FILE") + +# Check 4: Required fields +echo "" +echo "Checking required fields..." + +error_count=0 +warning_count=0 + +# Check name field +NAME=$(echo "$FRONTMATTER" | grep '^name:' | sed 's/name: *//' | sed 's/^"\(.*\)"$/\1/') + +if [ -z "$NAME" ]; then + echo "❌ Missing required field: name" + ((error_count++)) +else + echo "✅ name: $NAME" + + # Validate name format + if ! [[ "$NAME" =~ ^[a-zA-Z0-9][a-zA-Z0-9-]*[a-zA-Z0-9]$ ]]; then + echo "❌ name must start/end with alphanumeric and contain only letters, numbers, hyphens" + ((error_count++)) + fi + + # Validate name length + name_length=${#NAME} + if [ $name_length -lt 3 ]; then + echo "❌ name too short (minimum 3 characters)" + ((error_count++)) + elif [ $name_length -gt 50 ]; then + echo "❌ name too long (maximum 50 characters)" + ((error_count++)) + fi + + # Check for generic names + if [[ "$NAME" =~ ^(helper|assistant|agent|tool)$ ]]; then + echo "⚠️ name is too generic: $NAME" + ((warning_count++)) + fi +fi + +# Check description field +DESCRIPTION=$(echo "$FRONTMATTER" | grep '^description:' | sed 's/description: *//') + +if [ -z "$DESCRIPTION" ]; then + echo "❌ Missing required field: description" + ((error_count++)) +else + desc_length=${#DESCRIPTION} + echo "✅ description: ${desc_length} characters" + + if [ $desc_length -lt 10 ]; then + echo "⚠️ description too short (minimum 10 characters recommended)" + ((warning_count++)) + elif [ $desc_length -gt 5000 ]; then + echo "⚠️ description very long (over 5000 characters)" + ((warning_count++)) + fi + + # Check for example blocks + if ! echo "$DESCRIPTION" | grep -q ''; then + echo "⚠️ description should include blocks for triggering" + ((warning_count++)) + fi + + # Check for "Use this agent when" pattern + if ! echo "$DESCRIPTION" | grep -qi 'use this agent when'; then + echo "⚠️ description should start with 'Use this agent when...'" + ((warning_count++)) + fi +fi + +# Check model field +MODEL=$(echo "$FRONTMATTER" | grep '^model:' | sed 's/model: *//') + +if [ -z "$MODEL" ]; then + echo "❌ Missing required field: model" + ((error_count++)) +else + echo "✅ model: $MODEL" + + case "$MODEL" in + inherit|sonnet|opus|haiku) + # Valid model + ;; + *) + echo "⚠️ Unknown model: $MODEL (valid: inherit, sonnet, opus, haiku)" + ((warning_count++)) + ;; + esac +fi + +# Check color field +COLOR=$(echo "$FRONTMATTER" | grep '^color:' | sed 's/color: *//') + +if [ -z "$COLOR" ]; then + echo "❌ Missing required field: color" + ((error_count++)) +else + echo "✅ color: $COLOR" + + case "$COLOR" in + blue|cyan|green|yellow|magenta|red) + # Valid color + ;; + *) + echo "⚠️ Unknown color: $COLOR (valid: blue, cyan, green, yellow, magenta, red)" + ((warning_count++)) + ;; + esac +fi + +# Check tools field (optional) +TOOLS=$(echo "$FRONTMATTER" | grep '^tools:' | sed 's/tools: *//') + +if [ -n "$TOOLS" ]; then + echo "✅ tools: $TOOLS" +else + echo "💡 tools: not specified (agent has access to all tools)" +fi + +# Check 5: System prompt +echo "" +echo "Checking system prompt..." + +if [ -z "$SYSTEM_PROMPT" ]; then + echo "❌ System prompt is empty" + ((error_count++)) +else + prompt_length=${#SYSTEM_PROMPT} + echo "✅ System prompt: $prompt_length characters" + + if [ $prompt_length -lt 20 ]; then + echo "❌ System prompt too short (minimum 20 characters)" + ((error_count++)) + elif [ $prompt_length -gt 10000 ]; then + echo "⚠️ System prompt very long (over 10,000 characters)" + ((warning_count++)) + fi + + # Check for second person + if ! echo "$SYSTEM_PROMPT" | grep -q "You are\|You will\|Your"; then + echo "⚠️ System prompt should use second person (You are..., You will...)" + ((warning_count++)) + fi + + # Check for structure + if ! echo "$SYSTEM_PROMPT" | grep -qi "responsibilities\|process\|steps"; then + echo "💡 Consider adding clear responsibilities or process steps" + fi + + if ! echo "$SYSTEM_PROMPT" | grep -qi "output"; then + echo "💡 Consider defining output format expectations" + fi +fi + +echo "" +echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" + +if [ $error_count -eq 0 ] && [ $warning_count -eq 0 ]; then + echo "✅ All checks passed!" + exit 0 +elif [ $error_count -eq 0 ]; then + echo "⚠️ Validation passed with $warning_count warning(s)" + exit 0 +else + echo "❌ Validation failed with $error_count error(s) and $warning_count warning(s)" + exit 1 +fi diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/SKILL.md new file mode 100644 index 0000000..5bbbf87 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/SKILL.md @@ -0,0 +1,274 @@ +--- +name: architecture-design +description: Use only when creating new registrable ML components that require Factory or Registry patterns. +version: 1.2.0 +--- + +# Architecture Design - ML Project Template + +This skill defines the standard code architecture for machine learning projects based on the template structure. When modifying or extending code, follow these patterns to maintain consistency. + +## Overview + +The project follows a modular, extensible architecture with clear separation of concerns. Each module (data, model, trainer, analysis) is independently organized using factory and registry patterns for maximum flexibility. + +## When to Use + +Use this skill when: +- Creating a new Dataset class that needs `@register_dataset` +- Creating a new Model class that needs `@register_model` +- Creating a new module directory with `__init__.py` factory wiring +- Initializing a new ML project structure from scratch +- Adding new component types such as Augmentation, CollateFunction, or Metrics + +## When Not to Use + +Do not use this skill when: +- Modifying existing functions or methods +- Fixing bugs in existing code +- Adding helper functions or utilities +- Refactoring without adding new registrable components +- Making simple code changes to a single file +- Modifying configuration files +- Reading or understanding existing code + +Key indicator: if the task does not require a `@register_*` decorator or a Factory pattern, skip this skill. + +## Core Design Patterns + +### Factory Pattern + +Each module uses a factory to create instances dynamically: + +```python +# Example from data_module/dataset/__init__.py +DATASET_FACTORY: Dict = {} + +def DatasetFactory(data_name: str): + dataset = DATASET_FACTORY.get(data_name, None) + if dataset is None: + print(f"{data_name} dataset is not implementation, use simple dataset") + dataset = DATASET_FACTORY.get('simple') + return dataset +``` + +For detailed guidance, refer to `references/factory_pattern.md`. + +### Registry Pattern + +Components register themselves via decorators: + +```python +# Example from data_module/dataset/simple_dataset.py +@register_dataset("simple") +class SimpleDataset(Dataset): + def __init__(self, data): + self.data = data +``` + +For detailed guidance, refer to `references/registry_pattern.md`. + +### Auto-Import Pattern + +Modules automatically discover and import submodules: + +```python +# Example from data_module/dataset/__init__.py +models_dir = os.path.dirname(__file__) +import_modules(models_dir, "src.data_module.dataset") +``` + +For detailed guidance, refer to `references/auto_import.md`. + +## Directory Structure + +``` +project/ +├── run/ +│ ├── pipeline/ # Main workflow scripts +│ │ ├── training/ # Training pipelines +│ │ ├── prepare_data/ # Data preparation pipelines +│ │ └── analysis/ # Analysis pipelines +│ └── conf/ # Hydra configuration files +│ ├── training/ # Training configs +│ ├── dataset/ # Dataset configs +│ ├── model/ # Model configs +│ ├── prepare_data/ # Data prep configs +│ └── analysis/ # Analysis configs +│ +├── src/ +│ ├── data_module/ # Data processing module +│ │ ├── dataset/ # Dataset implementations +│ │ ├── augmentation/ # Data augmentation +│ │ ├── collate_fn/ # Collate functions +│ │ ├── compute_metrics/ # Metrics computation +│ │ ├── prepare_data/ # Data preparation logic +│ │ ├── data_func/ # Data utility functions +│ │ └── utils.py # Module-specific utilities +│ │ +│ ├── model_module/ # Model implementations +│ │ ├── brain_decoder/ # Brain decoder models +│ │ └── model/ # Alternative model location +│ │ +│ ├── trainer_module/ # Training logic +│ ├── analysis_module/ # Analysis and evaluation +│ ├── llm/ # LLM-related code +│ └── utils/ # Shared utilities +│ +├── data/ +│ ├── raw/ # Original, immutable data +│ ├── processed/ # Cleaned, transformed data +│ └── external/ # Third-party data +│ +├── outputs/ +│ ├── logs/ # Training and evaluation logs +│ ├── checkpoints/ # Model checkpoints +│ ├── tables/ # Result tables +│ └── figures/ # Plots and visualizations +│ +├── pyproject.toml # Project configuration +├── uv.lock # Dependency lock file +├── TODO.md # Task tracking +├── README.md # Project documentation +└── .gitignore # Git ignore rules +``` + +For detailed directory structure with file descriptions, refer to `references/structure.md`. + +## Module Organization + +### Creating a New Dataset + +When adding a new dataset: + +1. Create file in `src/data_module/dataset/` +2. Use `@register_dataset("name")` decorator +3. Inherit from `torch.utils.data.Dataset` +4. Implement `__init__`, `__len__`, `__getitem__` + +```python +from torch.utils.data import Dataset +from typing import Dict +import torch +from src.data_module.dataset import register_dataset + +@register_dataset("custom") +class CustomDataset(Dataset): + def __init__(self, data): + self.data = data + + def __len__(self): + return len(self.data) + + def __getitem__(self, i: int) -> Dict[str, torch.Tensor]: + return self.data[i] +``` + +### Creating a New Model + +**CRITICAL: Models use config-driven pattern** + +When adding a new model: + +1. Create file in `src/model_module/model/` or appropriate module subdirectory +2. Use `@register_model('ModelName')` decorator +3. `__init__` accepts **ONLY** `cfg` parameter - all hyperparameters come from config +4. `forward()` returns dict: `{"loss": loss, "labels": labels, "logits": logits}` +5. Handle training vs inference modes using `self.training` + +```python +from src.model_module.brain_decoder import register_model + +@register_model('MyModel') +class MyModel(nn.Module): + def __init__(self, cfg): + super().__init__() + self.cfg = cfg + self.task = cfg.dataset.task + + # ALL parameters from cfg + self.hidden_dim = cfg.model.hidden_dim + self.output_dim = cfg.dataset.target_size[cfg.dataset.task] + + def forward(self, x, labels=None, **kwargs): + if self.training: + # Training logic + pass + else: + # Inference logic + pass + + return {"loss": loss, "labels": labels, "logits": logits} +``` + +### Adding Data Augmentation + +When adding augmentation: + +1. Create file in `src/data_module/augmentation/` +2. Implement transformation function +3. Register with factory if needed + +## Code Style Guidelines + +For comprehensive style guidelines, refer to `references/code_style.md`. + +**Key principles:** +- Always use type hints for function signatures +- Follow import order: standard library → third-party → local +- Module `__init__.py` files contain factory/registry logic +- Model classes must be config-driven + +## Configuration Management + +The project uses Hydra for configuration management: + +- Config files in `run/conf/` organize by module +- Each stage (training, analysis) has its own config structure +- Use YAML files for all configuration + +## When Working on This Project + +### Before Modifying Code + +1. Read the relevant module's factory/registry pattern +2. Check existing implementations for consistency +3. Follow the established directory structure +4. Use registration decorators for new components + +### Adding New Features + +1. Determine which module the feature belongs to +2. Check if similar functionality exists +3. Follow factory/registry pattern if creating new component types +4. Add configuration files if needed +5. Update documentation + +### Code Review Checklist + +- [ ] Uses factory/registry pattern appropriately +- [ ] Follows module directory structure +- [ ] Has proper type annotations +- [ ] Imports are correctly ordered +- [ ] Registration decorator is used +- [ ] Configuration files are added if needed + +## Additional Resources + +### Reference Files + +For detailed information, consult: +- **`references/structure.md`** - Detailed directory structure with file descriptions +- **`references/factory_pattern.md`** - Factory pattern in-depth explanation +- **`references/registry_pattern.md`** - Registry pattern in-depth explanation +- **`references/auto_import.md`** - Auto-import pattern in-depth explanation +- **`references/code_style.md`** - Comprehensive code style guidelines + +### Example Files + +Working examples in `examples/`: +- **`examples/custom_dataset.py`** - Custom dataset implementation +- **`examples/custom_model.py`** - Custom model implementation +- **`examples/augmentation_example.py`** - Data augmentation example +- **`examples/config_example.yaml`** - Configuration file example +- **`examples/pipeline_example.sh`** - Pipeline script example diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/augmentation_example.py b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/augmentation_example.py new file mode 100644 index 0000000..949b033 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/augmentation_example.py @@ -0,0 +1,117 @@ +""" +Data Augmentation Example + +Demonstrates how to create a custom data augmentation function +following the architecture design pattern. +""" + +import torch +from typing import Dict +from src.data_module.augmentation import register_augmentation + + +@register_augmentation("time_shift") +def time_shift(signal: torch.Tensor, max_shift: int = 10) -> torch.Tensor: + """Randomly shift signal in time. + + Args: + signal: Input signal tensor of shape (channels, time_steps) + max_shift: Maximum number of steps to shift + + Returns: + Shifted signal tensor + """ + shift = torch.randint(-max_shift, max_shift + 1, (1,)).item() + return torch.roll(signal, shifts=shift, dims=-1) + + +@register_augmentation("amplitude_scale") +def amplitude_scale( + signal: torch.Tensor, + min_scale: float = 0.8, + max_scale: float = 1.2 +) -> torch.Tensor: + """Randomly scale signal amplitude. + + Args: + signal: Input signal tensor of shape (channels, time_steps) + min_scale: Minimum scaling factor + max_scale: Maximum scaling factor + + Returns: + Scaled signal tensor + """ + scale = torch.empty(1).uniform_(min_scale, max_scale).item() + return signal * scale + + +@register_augmentation("gaussian_noise") +def add_gaussian_noise( + signal: torch.Tensor, + mean: float = 0.0, + std: float = 0.1 +) -> torch.Tensor: + """Add Gaussian noise to signal. + + Args: + signal: Input signal tensor of shape (channels, time_steps) + mean: Mean of Gaussian noise + std: Standard deviation of Gaussian noise + + Returns: + Signal with added noise + """ + noise = torch.randn_like(signal) * std + mean + return signal + noise + + +# Example: Composed augmentation +@register_augmentation("composed") +def composed_augmentation(signal: torch.Tensor, cfg) -> torch.Tensor: + """Apply multiple augmentations in sequence. + + Args: + signal: Input signal tensor + cfg: Configuration object with augmentation parameters + + Returns: + Augmented signal tensor + """ + # Apply each augmentation based on config + if cfg.augmentation.time_shift: + signal = time_shift(signal, cfg.augmentation.max_shift) + + if cfg.augmentation.amplitude_scale: + signal = amplitude_scale( + signal, + cfg.augmentation.min_scale, + cfg.augmentation.max_scale + ) + + if cfg.augmentation.gaussian_noise: + signal = add_gaussian_noise( + signal, + cfg.augmentation.noise_mean, + cfg.augmentation.noise_std + ) + + return signal + + +# Usage in dataset class +class AugmentedDataset: + """Example dataset with augmentation support.""" + + def __init__(self, cfg): + self.cfg = cfg + self.augmentation_fn = AugmentationFactory(cfg.augmentation.name) + + def __getitem__(self, idx: int) -> Dict[str, torch.Tensor]: + # Load signal + signal = self.load_signal(idx) + + # Apply augmentation (training mode only) + if self.training and self.augmentation_fn: + signal = self.augmentation_fn(signal, self.cfg) + + return {"signal": signal, "label": self.labels[idx]} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/config_example.yaml b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/config_example.yaml new file mode 100644 index 0000000..8b61442 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/config_example.yaml @@ -0,0 +1,131 @@ +# Hydra Configuration Example +# This demonstrates the config structure for training pipeline + +# Run with: python train.py --config-name=config_example + +defaults: + - training: default + - dataset: brain_decoder + - model: transformer + - override hydra/launcher: submitit_local + +# Project settings +project_name: brain_decoder +experiment_name: transformer_baseline + +# Random seed +seed: 42 + +# Device settings +device: cuda +num_workers: 4 +pin_memory: true + +# Training configuration +training: + epochs: 100 + batch_size: 32 + learning_rate: 0.001 + weight_decay: 0.0001 + gradient_clip: 1.0 + early_stopping: + patience: 10 + min_delta: 0.001 + + # Optimizer settings + optimizer: adamw + optimizer_params: + betas: [0.9, 0.999] + eps: 1.0e-08 + + # Scheduler settings + scheduler: cosine + scheduler_params: + warmup_epochs: 10 + min_lr: 1.0e-06 + + # Checkpoint settings + checkpoint: + save_every: 5 + save_best: true + monitor: val_loss + mode: min + +# Dataset configuration +dataset: + name: brain_decoder + task: movement_classification + target_size: + movement_classification: 5 + reconstruction: [64, 64] + + # Data paths + data_dir: ${dir.data_dir}/processed + train_split: train + val_split: val + test_split: test + + # Data loading + num_channels: 64 + sampling_rate: 1000 + sequence_length: 1000 + + # Augmentation + augmentation: + name: composed + time_shift: true + amplitude_scale: true + gaussian_noise: true + max_shift: 10 + min_scale: 0.8 + max_scale: 1.2 + noise_mean: 0.0 + noise_std: 0.1 + +# Model configuration +model: + name: Transformer + hidden_dim: 256 + num_heads: 8 + num_layers: 6 + dropout: 0.1 + activation: gelu + + # Architecture specific + encoder: + input_dim: 64 + embedding_dim: 256 + positional_encoding: true + + decoder: + output_dim: ${dataset.target_size.${dataset.task}} + pooling: avg + +# Logging configuration +logging: + logger: wandb + log_every: 10 + log_grads: false + + # TensorBoard + tensorboard: true + histogram: true + + # W&B + wandb: + project: ${project_name} + entity: null + tags: ["baseline", "transformer"] + +# Output directories +dir: + data_dir: ./data + output_dir: ./outputs + log_dir: ${dir.output_dir}/logs + checkpoint_dir: ${dir.output_dir}/checkpoints + figure_dir: ${dir.output_dir}/figures + table_dir: ${dir.output_dir}/tables + +# Debug settings +debug: false +fast_dev_run: false diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/custom_dataset.py b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/custom_dataset.py new file mode 100644 index 0000000..c9fe002 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/custom_dataset.py @@ -0,0 +1,50 @@ +""" +Example: Creating a Custom Dataset + +This example shows how to add a new dataset following the project architecture. +""" + +from torch.utils.data import Dataset +from typing import Dict +import torch +from src.data_module.dataset import register_dataset + + +@register_dataset("time_series") +class TimeSeriesDataset(Dataset): + """ + Time series dataset for sequence modeling. + + Args: + sequences: List of time series sequences + seq_length: Fixed sequence length (pad or truncate if needed) + """ + + def __init__(self, sequences: list, seq_length: int = 100): + self.sequences = sequences + self.seq_length = seq_length + + def __len__(self) -> int: + return len(self.sequences) + + def __getitem__(self, i: int) -> Dict[str, torch.Tensor]: + sequence = self.sequences[i] + + # Pad or truncate to fixed length + if len(sequence) < self.seq_length: + padding = torch.zeros(self.seq_length - len(sequence)) + sequence = torch.cat([sequence, padding]) + else: + sequence = sequence[:self.seq_length] + + return { + "input": sequence, + "label": sequence, # For autoencoder, etc. + "length": torch.tensor(min(len(self.sequences[i]), self.seq_length)) + } + + +# Usage in training: +# from src.data_module.dataset import DatasetFactory +# dataset = DatasetFactory("time_series")(sequences=training_data, seq_length=128) +# dataloader = DataLoader(dataset, batch_size=32, shuffle=True) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/custom_model.py b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/custom_model.py new file mode 100644 index 0000000..0e00752 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/custom_model.py @@ -0,0 +1,217 @@ +""" +Example: Creating a Custom Model + +This example shows how to add a new model following the project architecture. +IMPORTANT: Models use a config-driven pattern where __init__ only accepts cfg. + +Key Requirements: +- Use @register_model('ModelName') decorator +- __init__ accepts ONLY cfg parameter +- All hyperparameters come from cfg (cfg.model.*, cfg.dataset.*, etc.) +- forward() returns dict: {"loss": loss, "labels": labels, "logits": logits} +""" + +import torch +import torch.nn as nn +import torch.nn.functional as F +from typing import Dict, Optional + +# Import the register_model decorator +# Location may vary: src.model_module.brain_decoder or src.model_module.model +from src.model_module.brain_decoder import register_model + + +@register_model('SimpleMLP') +class SimpleMLP(nn.Module): + """ + Simple Multi-Layer Perceptron for classification tasks. + + Config structure ( Hydra YAML ): + model: + input_dim: 100 + hidden_dim: 256 + output_dim: 10 + num_layers: 3 + dropout: 0.1 + dataset: + task: classification # Used to get target_size + target_size: + classification: 10 + """ + + def __init__(self, cfg): + super().__init__() + + # Store config + self.cfg = cfg + + # Get task info from config + self.task = cfg.dataset.task + + # Build model - ALL parameters from cfg + self.input_dim = cfg.model.input_dim + self.hidden_dim = cfg.model.get('hidden_dim', 256) + self.output_dim = cfg.dataset.target_size[cfg.dataset.task] + self.num_layers = cfg.model.get('num_layers', 3) + self.dropout = cfg.model.get('dropout', 0.1) + + # Build layers + layers = [] + in_dim = self.input_dim + + for i in range(self.num_layers): + layers.extend([ + nn.Linear(in_dim, self.hidden_dim), + nn.ReLU(), + nn.Dropout(self.dropout) + ]) + in_dim = self.hidden_dim + + # Output layer + layers.append(nn.Linear(self.hidden_dim, self.output_dim)) + self.network = nn.Sequential(*layers) + + # Loss function + self.loss_fn = nn.CrossEntropyLoss() + + def forward( + self, + x: torch.Tensor, + labels: Optional[torch.Tensor] = None, + **kwargs + ) -> Dict[str, Optional[torch.Tensor]]: + """ + Forward pass. + + Args: + x: Input tensor of shape (batch_size, input_dim) + labels: Ground truth labels (optional, for training) + + Returns: + Dictionary with: + - loss: Computed loss (None if labels not provided) + - labels: Ground truth labels + - logits: Model predictions + """ + logits = self.network(x) + + loss = None + if labels is not None: + # Convert labels to long type if needed + if labels.dtype != torch.long: + labels = labels.long() + loss = self.loss_fn(logits, labels) + + return { + "loss": loss, + "labels": labels, + "logits": logits + } + + +# ============================================ +# Example with Training/Inference Modes +# ============================================ + +@register_model('SimpleMLPWithModes') +class SimpleMLPWithModes(nn.Module): + """ + MLP with separate training and inference logic. + Shows how to handle different modes using self.training. + """ + + def __init__(self, cfg): + super().__init__() + self.cfg = cfg + self.task = cfg.dataset.task + + self.input_dim = cfg.model.input_dim + self.hidden_dim = cfg.model.get('hidden_dim', 256) + self.output_dim = cfg.dataset.target_size[cfg.dataset.task] + + self.fc_in = nn.Linear(self.input_dim, self.hidden_dim) + self.ln = nn.LayerNorm(self.hidden_dim) + self.fc_out = nn.Linear(self.hidden_dim, self.output_dim) + self.loss_fn = nn.CrossEntropyLoss() + + # Test-time augmentation config + self.tta_times = cfg.model.get('tta_times', 1) + + def forward( + self, + x: torch.Tensor, + labels: Optional[torch.Tensor] = None, + **kwargs + ) -> Dict[str, Optional[torch.Tensor]]: + """ + Forward pass with training/inference modes. + """ + if self.training: + # Training mode + x = x.float() + x = self.fc_in(x) + x = self.ln(x) + x = F.relu(x) + logits = self.fc_out(x) + + loss = None + if labels is not None: + if labels.dtype != torch.long: + labels = labels.long() + loss = self.loss_fn(logits, labels) + + return { + "loss": loss, + "labels": labels, + "logits": logits + } + else: + # Inference mode with TTA + all_logits = [] + with torch.no_grad(): + x = x.float() + for _ in range(self.tta_times): + x_aug = x.clone() + # Apply TTA transformations here if needed + + x_aug = self.fc_in(x_aug) + x_aug = self.ln(x_aug) + x_aug = F.relu(x_aug) + logits = self.fc_out(x_aug) + all_logits.append(logits) + + # Average predictions + avg_logits = torch.mean(torch.stack(all_logits), dim=0) + + loss = None + if labels is not None: + if labels.dtype != torch.long: + labels = labels.long() + loss = self.loss_fn(avg_logits, labels) + + return { + "loss": loss, + "labels": labels, + "logits": avg_logits + } + + +# ============================================ +# Config Example (Hydra YAML) +# ============================================ +""" +# run/conf/model/simple_mlp.yaml + +model: + name: SimpleMLP + input_dim: 100 + hidden_dim: 256 + output_dim: 10 + num_layers: 3 + dropout: 0.1 + tta_times: 1 + +# Then in training pipeline: +# from src.model_module.brain_decoder import ModelFactory +# model = ModelFactory(cfg.model.name)(cfg) +""" diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/pipeline_example.sh b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/pipeline_example.sh new file mode 100755 index 0000000..abd7b46 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/examples/pipeline_example.sh @@ -0,0 +1,189 @@ +#!/bin/bash +############################################################################### +# Training Pipeline Script +# +# This script demonstrates the standard training pipeline execution pattern. +# It handles environment setup, configuration, and execution with proper +# error handling and logging. +# +# Usage: +# ./run/pipeline/training/train.sh --config-name=config_example +############################################################################### + +set -e # Exit on error +set -o pipefail # Exit on pipe failure + +# Script configuration +SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +PROJECT_ROOT="$(cd "${SCRIPT_DIR}/../.." && pwd)" +EXPERIMENT_NAME="baseline_experiment" +TIMESTAMP=$(date +"%Y%m%d_%H%M%S") + +# Colors for output +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +NC='\033[0m' # No Color + +############################################################################### +# Helper Functions +############################################################################### + +log_info() { + echo -e "${GREEN}[INFO]${NC} $1" +} + +log_warn() { + echo -e "${YELLOW}[WARN]${NC} $1" +} + +log_error() { + echo -e "${RED}[ERROR]${NC} $1" +} + +cleanup() { + log_info "Cleaning up..." + # Add cleanup logic here (e.g., kill background processes) +} + +trap cleanup EXIT + +############################################################################### +# Environment Setup +############################################################################### + +setup_environment() { + log_info "Setting up environment..." + + # Activate virtual environment if it exists + if [ -f "${PROJECT_ROOT}/.venv/bin/activate" ]; then + source "${PROJECT_ROOT}/.venv/bin/activate" + log_info "Activated virtual environment" + fi + + # Check required commands + command -v python >/dev/null 2>&1 || { log_error "Python not found"; exit 1; } + + # Set Python path + export PYTHONPATH="${PROJECT_ROOT}/src:${PYTHONPATH}" + log_info "PYTHONPATH set to: ${PYTHONPATH}" +} + +############################################################################### +# Configuration +############################################################################### + +parse_arguments() { + # Default values + CONFIG="default" + GPUS=0 + SEED=42 + + # Parse arguments + while [[ $# -gt 0 ]]; do + case $1 in + --config-name|-c) + CONFIG="$2" + shift 2 + ;; + --gpus|-g) + GPUS="$2" + shift 2 + ;; + --seed|-s) + SEED="$2" + shift 2 + ;; + *) + log_warn "Unknown argument: $1" + shift + ;; + esac + done + + log_info "Configuration: ${CONFIG}" + log_info "GPUs: ${GPUS}" + log_info "Seed: ${SEED}" +} + +############################################################################### +# Main Training Function +############################################################################### + +run_training() { + log_info "Starting training..." + + # Output directory for this run + OUTPUT_DIR="${PROJECT_ROOT}/outputs/${EXPERIMENT_NAME}/${TIMESTAMP}" + mkdir -p "${OUTPUT_DIR}" + + log_info "Output directory: ${OUTPUT_DIR}" + + # Training command with Hydra + python "${PROJECT_ROOT}/train.py" \ + --config-name="${CONFIG}" \ + seed=${SEED} \ + dir.output_dir="${OUTPUT_DIR}" \ + training.device=cuda \ + hydra.output_dir="${OUTPUT_DIR}/hydra" \ + hydra.run.dir="${OUTPUT_DIR}/hydra" || { + log_error "Training failed!" + exit 1 + } + + log_info "Training completed successfully!" +} + +############################################################################### +# Post-Processing +############################################################################### + +post_process() { + log_info "Post-processing results..." + + # Copy logs to output directory + if [ -f "${OUTPUT_DIR}/hydra/*.log" ]; then + cp "${OUTPUT_DIR}/hydra/"*.log "${OUTPUT_DIR}/" + fi + + # Generate summary + log_info "Run summary:" + log_info " Config: ${CONFIG}" + log_info " Seed: ${SEED}" + log_info " Output: ${OUTPUT_DIR}" + + # Print path to best checkpoint + BEST_CHECKPOINT=$(find "${OUTPUT_DIR}" -name "best*.pt" | head -n 1) + if [ -n "${BEST_CHECKPOINT}" ]; then + log_info " Best checkpoint: ${BEST_CHECKPOINT}" + fi +} + +############################################################################### +# Main Execution +############################################################################### + +main() { + log_info "==========================================" + log_info "Training Pipeline" + log_info "==========================================" + + # Setup + setup_environment + + # Parse arguments + parse_arguments "$@" + + # Run training + run_training + + # Post-process + post_process + + log_info "==========================================" + log_info "Pipeline completed successfully!" + log_info "==========================================" +} + +# Run main function +main "$@" diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/auto_import.md b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/auto_import.md new file mode 100644 index 0000000..59c19ef --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/auto_import.md @@ -0,0 +1,117 @@ +# Auto-Import Pattern + +## Overview + +The Auto-Import pattern automatically discovers and imports all submodules in a directory, ensuring all components are registered without manual imports. + +## Structure + +```python +# In module __init__.py (e.g., data_module/dataset/__init__.py) +import os +from src.utils.helpers import import_modules + +models_dir = os.path.dirname(__file__) +import_modules(models_dir, "src.data_module.dataset") +``` + +## Helper Function + +```python +# In src/utils/helpers.py +import os +import importlib +import pkgutil +from typing import List + +def import_modules(models_dir: str, package_name: str) -> List[str]: + """ + Import all Python modules in a directory. + + Args: + models_dir: Directory path to scan + package_name: Full package name for imports + + Returns: + List of imported module names + """ + imported = [] + for module_loader, name, ispkg in pkgutil.iter_modules([models_dir]): + if not name.startswith('_'): + full_name = f"{package_name}.{name}" + importlib.import_module(full_name) + imported.append(name) + return imported +``` + +## Benefits + +- **Zero maintenance**: Adding new file = auto-registration +- **No遗漏**: Cannot forget to import new component +- **Consistent**: All components follow same discovery path +- **Scalable**: Works for any number of submodules + +## Implementation Details + +1. Scan directory for `.py` files +2. Skip files starting with `_` (private) +3. Import each module using full package path +4. Import triggers decorator registration + +## Directory Structure Example + +``` +dataset/ +├── __init__.py # Contains import_modules() call +├── simple_dataset.py # Auto-imported, registers "simple" +├── custom_dataset.py # Auto-imported, registers "custom" +└── _private.py # NOT imported (starts with _) +``` + +## Best Practices + +- **Skip private files**: Files starting with `_` are not imported +- **Full package paths**: Use dot-notation for correct imports +- **Idempotent**: Safe to call multiple times +- **Error handling**: Import errors propagate for debugging + +## Common Patterns + +### Conditional Import + +```python +def import_modules(models_dir: str, package_name: str, skip: List[str] = None): + skip = skip or [] + for module_loader, name, ispkg in pkgutil.iter_modules([models_dir]): + if name not in skip and not name.startswith('_'): + importlib.import_module(f"{package_name}.{name}") +``` + +### Recursive Import + +```python +def import_modules_recursive(models_dir: str, package_name: str): + """Import modules and subpackages recursively.""" + for importer, name, ispkg in pkgutil.walk_packages([models_dir], prefix=f"{package_name}."): + if not name.split('.')[-1].startswith('_'): + importlib.import_module(name) +``` + +### Dry-Run Mode + +```python +def import_modules(models_dir: str, package_name: str, dry_run: bool = False): + if dry_run: + return [name for _, name, _ in pkgutil.iter_modules([models_dir]) + if not name.startswith('_')] + # ... actual import logic +``` + +## Integration with Registry + +The auto-import pattern is typically used WITH registry pattern: + +1. **Import time**: `import_modules()` imports all files +2. **Decorator execution**: `@register_dataset()` runs +3. **Factory population**: `DATASET_FACTORY` dict populated +4. **Runtime**: `DatasetFactory()` looks up registered classes diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/code_style.md b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/code_style.md new file mode 100644 index 0000000..c07fd0a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/code_style.md @@ -0,0 +1,234 @@ +# Code Style Guidelines + +## Type Annotations + +Always use type hints for function signatures and class attributes: + +```python +from typing import Dict, List, Optional, Tuple +import torch + +def __getitem__(self, i: int) -> Dict[str, torch.Tensor]: + """Get item by index.""" + return self.data[i] + +def compute_metrics(predictions: torch.Tensor, labels: torch.Tensor) -> Dict[str, float]: + """Compute evaluation metrics.""" + pass + +class MyModel(nn.Module): + hidden_dim: int # Class attribute type hints + output_dim: int + + def __init__(self, cfg): + self.hidden_dim: int = cfg.model.hidden_dim + self.output_dim: int = cfg.model.output_dim +``` + +## Import Order + +Organize imports in three sections with blank lines between: + +```python +# 1. Standard library imports +import os +from typing import Dict, List, Optional +from pathlib import Path + +# 2. Third-party imports +import torch +import torch.nn as nn +from torch.utils.data import Dataset +import numpy as np + +# 3. Local imports +from src.data_module.dataset import register_dataset +from src.utils.helpers import import_modules +from src.model_module.brain_decoder import register_model +``` + +## __init__.py Files + +### Module __init__.py (with factory) + +Contains factory/registry logic and auto-import: + +```python +# src/data_module/dataset/__init__.py +import os +from typing import Dict, Callable, TypeVar +from src.utils.helpers import import_modules + +T = TypeVar('T') + +DATASET_FACTORY: Dict[str, type] = {} + +def register_dataset(name: str) -> Callable[[T], T]: + """Decorator to register dataset classes.""" + def decorator(cls: T) -> T: + DATASET_FACTORY[name] = cls + return cls + return decorator + +def DatasetFactory(data_name: str): + """Create dataset instance by name.""" + dataset = DATASET_FACTORY.get(data_name, None) + if dataset is None: + dataset = DATASET_FACTORY.get('simple') + return dataset + +# Auto-import all submodules +models_dir = os.path.dirname(__file__) +import_modules(models_dir, "src.data_module.dataset") +``` + +### Subpackage __init__.py (can be empty) + +```python +# src/data_module/augmentation/__init__.py +# Empty file - just marks as package +``` + +Or with exports: + +```python +# src/data_module/__init__.py +from .dataset import DatasetFactory, register_dataset +from .augmentation import AugmentationFactory +``` + +## Naming Conventions + +### Files + +- **Modules**: `simple_dataset.py`, `custom_model.py` +- **Pipelines**: `training.sh`, `inference.sh` +- **Configs**: `config.yaml`, `brain_decoder.yaml` +- **Utilities**: `get_optimizer.py`, `helpers.py`, `compute_metrics.py` + +### Classes and Functions + +```python +# Classes: PascalCase +class SimpleDataset(Dataset): + pass + +class MyCustomModel(nn.Module): + pass + +# Functions and variables: snake_case +def compute_accuracy(predictions, labels): + pass + +def get_optimizer(cfg): + pass + +learning_rate = 0.001 +batch_size = 32 +``` + +### Constants + +```python +# Constants: UPPER_SNAKE_CASE +DEFAULT_HIDDEN_DIM = 256 +MAX_EPOCHS = 100 +LEARNING_RATE = 0.001 +``` + +## Docstrings + +Use Google-style docstrings: + +```python +def DatasetFactory(data_name: str) -> type: + """Create dataset class by name. + + Args: + data_name: Name of the dataset to create. + + Returns: + Dataset class if found, otherwise simple dataset. + + Raises: + ValueError: If no dataset is found and no default exists. + """ + pass +``` + +## Configuration-Driven Classes + +Model classes must be config-driven: + +```python +@register_model('MyModel') +class MyModel(nn.Module): + def __init__(self, cfg): + """Initialize model from config. + + Args: + cfg: Hydra config object with model attributes. + """ + super().__init__() + self.cfg = cfg + + # ALL parameters from cfg + self.hidden_dim = cfg.model.hidden_dim + self.output_dim = cfg.dataset.target_size[cfg.dataset.task] + self.dropout = cfg.model.dropout + + def forward(self, x, labels=None, **kwargs): + """Forward pass. + + Args: + x: Input tensor. + labels: Ground truth labels (training mode). + **kwargs: Additional arguments. + + Returns: + Dict with loss, labels, and logits. + """ + # Implementation + return {"loss": loss, "labels": labels, "logits": logits} +``` + +## Error Handling + +```python +def DatasetFactory(data_name: str) -> type: + """Create dataset class by name.""" + dataset = DATASET_FACTORY.get(data_name) + if dataset is None: + available = ', '.join(DATASET_FACTORY.keys()) + raise ValueError( + f"Dataset '{data_name}' not found. " + f"Available: {available}" + ) + return dataset +``` + +## Logging + +```python +import logging + +logger = logging.getLogger(__name__) + +@register_dataset('custom') +class CustomDataset(Dataset): + def __init__(self, cfg): + self.cfg = cfg + logger.info(f"Initializing {self.__class__.__name__}") + logger.debug(f"Config: {cfg.dataset}") +``` + +## Code Review Checklist + +- [ ] All functions have type hints +- [ ] Imports are correctly ordered +- [ ] Classes use PascalCase, functions use snake_case +- [ ] Docstrings follow Google style +- [ ] Model classes are config-driven +- [ ] Registration decorators are used +- [ ] Error messages are informative +- [ ] Logging is added for key operations diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/factory_pattern.md b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/factory_pattern.md new file mode 100644 index 0000000..f700dd4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/factory_pattern.md @@ -0,0 +1,53 @@ +# Factory Pattern + +## Overview + +The Factory pattern allows dynamic creation of instances without specifying the exact class. Each module uses a factory to decouple creation from usage. + +## Structure + +```python +# In module __init__.py (e.g., data_module/dataset/__init__.py) +DATASET_FACTORY: Dict[str, type] = {} + +def DatasetFactory(data_name: str): + """Create dataset instance by name.""" + dataset = DATASET_FACTORY.get(data_name, None) + if dataset is None: + # Fallback to default + dataset = DATASET_FACTORY.get('simple') + return dataset +``` + +## Usage + +```python +# Consumer code doesn't need to know concrete class +dataset = DatasetFactory(cfg.dataset.name) +``` + +## Benefits + +- **Loose coupling**: Consumer doesn't import concrete classes +- **Extensibility**: Add new types without changing consumer code +- **Fallback handling**: Graceful degradation for unknown types +- **Centralized registry**: Single source of truth for available types + +## Implementation Details + +1. Define factory dict at module level +2. Factory function handles lookup and fallback +3. Return class (not instance) for deferred initialization +4. None result triggers fallback to default implementation + +## Common Patterns + +```python +# With config integration +def DatasetFactory(cfg): + data_name = cfg.dataset.name + dataset_cls = DATASET_FACTORY.get(data_name) + if dataset_cls is None: + raise ValueError(f"Unknown dataset: {data_name}") + return dataset_cls(cfg) +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/registry_pattern.md b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/registry_pattern.md new file mode 100644 index 0000000..0b9c34e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/registry_pattern.md @@ -0,0 +1,102 @@ +# Registry Pattern + +## Overview + +The Registry pattern allows components to register themselves via decorators, enabling automatic discovery and centralized management of available types. + +## Structure + +```python +# In module __init__.py (e.g., data_module/dataset/__init__.py) +from typing import Dict, Callable, TypeVar + +T = TypeVar('T') + +DATASET_FACTORY: Dict[str, type] = {} + +def register_dataset(name: str) -> Callable[[T], T]: + """Decorator to register dataset classes.""" + def decorator(cls: T) -> T: + DATASET_FACTORY[name] = cls + return cls + return decorator +``` + +## Usage + +```python +# In implementation file (e.g., simple_dataset.py) +from data_module.dataset import register_dataset + +@register_dataset("simple") +class SimpleDataset(Dataset): + def __init__(self, cfg): + # Implementation + pass +``` + +## Benefits + +- **Automatic registration**: Components register themselves on import +- **Declarative**: Single decorator line replaces manual registration code +- **Import-time discovery**: Auto-import pattern finds all implementations +- **Type-safe**: Preserves original class type + +## Implementation Details + +1. Decorator returns the class unchanged (for immediate use) +2. Side effect: adds class to factory dict +3. Name parameter must be unique per module +4. Registration happens at module import time + +## Advanced Patterns + +### Registration with Config + +```python +def register_model(name: str): + def decorator(cls): + MODEL_FACTORY[name] = cls + # Add config validation + cls._config_schema = getattr(cls, '_config_schema', {}) + return cls + return decorator +``` + +### Conditional Registration + +```python +def register_dataset(name: str, experimental: bool = False): + def decorator(cls): + if not experimental or cfg.enable_experimental: + DATASET_FACTORY[name] = cls + return cls + return decorator +``` + +### Multi-Registry + +```python +# Multiple registries in one module +DATASET_FACTORY = {} +AUGMENTATION_FACTORY = {} + +def register_dataset(name: str): + def decorator(cls): + DATASET_FACTORY[name] = cls + return cls + return decorator + +def register_augmentation(name: str): + def decorator(fn): + AUGMENTATION_FACTORY[name] = fn + return fn + return decorator +``` + +## Best Practices + +- **Unique names**: Use descriptive, unique registration names +- **Documentation**: Document required parameters in class docstring +- **Validation**: Validate config in `__init__`, not in decorator +- **Consistency**: Use same naming convention across modules diff --git a/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/structure.md b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/structure.md new file mode 100644 index 0000000..fcd6b09 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/architecture-design/references/structure.md @@ -0,0 +1,150 @@ +# Detailed Directory Structure + +This document provides a comprehensive breakdown of the ML project template directory structure. + +## Root Level Files + +| File | Purpose | +|------|---------| +| `README.md` | Project documentation, installation guide, usage examples | +| `TODO.md` | Task tracking with weekly focus and daily tasks | +| `.gitignore` | Git ignore patterns for Python, Jupyter, IDEs, logs, cache | +| `pyproject.toml` | Project configuration for build system and dependencies | +| `uv.lock` | Locked dependency versions for reproducibility | + +## run/ - Execution Layer + +### pipeline/ + +Main workflow scripts organized by stage: + +| Directory | Purpose | +|-----------|---------| +| `training/` | Training execution scripts (training.sh, inference.sh) | +| `prepare_data/` | Data preparation and preprocessing pipelines | +| `analysis/` | Evaluation and analysis workflows | + +### conf/ + +Hydra configuration files organized by module: + +| Directory | Purpose | +|-----------|---------| +| `training/` | Training hyperparameters, model configs, optimizer settings | +| `dataset/` | Dataset configurations, data paths, preprocessing options | +| `model/` | Model architecture configurations | +| `prepare_data/` | Data preparation parameters | +| `analysis/` | Analysis and evaluation configurations | +| `dir/` | Directory path configurations | +| `analysis/` | Analysis-specific settings | + +## src/ - Source Code Layer + +### data_module/ - Data Processing Module + +``` +data_module/ +├── __init__.py # Module exports +├── utils.py # Data-specific utility functions +├── dataset/ # Dataset implementations +│ ├── __init__.py # Dataset factory and registry +│ └── simple_dataset.py # Simple dataset example +├── augmentation/ # Data augmentation methods +│ ├── __init__.py +│ ├── mixup.py # Mixup augmentation +│ ├── random_shift.py # Random shifting +│ ├── channel_mask.py # Channel masking +│ ├── time_masking.py # Time masking +│ └── add_noise.py # Noise injection +├── collate_fn/ # Batch collation functions +│ ├── __init__.py +│ └── simple_collate_fn.py +├── compute_metrics/ # Metrics computation +│ ├── __init__.py +│ └── simple_compute_metrics.py +├── prepare_data/ # Data preparation logic +│ ├── __init__.py +│ ├── prepare_data.py +│ └── generate_yaml.py +└── data_func/ # Data utility functions + ├── __init__.py + └── simple_data_func.py +``` + +### model_module/ - Model Module + +``` +model_module/ +├── __init__.py # Module exports +└── model/ # Model implementations + └── [model files] +``` + +### trainer_module/ - Training Module + +Contains training loop logic, validation, and checkpoint management. + +### analysis_module/ - Analysis Module + +Contains evaluation, visualization, and result analysis code. + +### llm/ - LLM Module + +LLM-related code and integrations. + +### utils/ - Shared Utilities + +``` +utils/ +├── __init__.py +├── helpers.py # Helper functions (import_modules, etc.) +├── logging.py # Logging configuration +├── get_optimizer.py # Optimizer factory +├── get_scheduler.py # Learning rate scheduler factory +├── get_callback.py # Training callbacks +├── get_activation.py # Activation functions +└── get_checkpoint_aggregation.py # Checkpoint handling +``` + +## data/ - Data Layer + +Following the Cookiecutter Data Science standard: + +| Directory | Purpose | +|-----------|---------| +| `raw/` | Original, immutable data dump | +| `processed/` | Cleaned, transformed data ready for use | +| `external/` | Data from third-party sources | + +## outputs/ - Output Layer + +| Directory | Purpose | +|-----------|---------| +| `logs/` | Training logs, tensorboard logs | +| `checkpoints/` | Model checkpoints for resuming training | +| `tables/` | Result tables, CSV outputs | +| `figures/` | Plots, visualizations, figures | + +## Module Interaction Flow + +``` +run/pipeline/ -> src/trainer_module/ -> src/model_module/ + src/data_module/ src/utils/ + src/utils/ + +run/conf/ -> Hydra config loader -> All modules +``` + +## File Naming Conventions + +- **Modules**: `simple_dataset.py`, `custom_model.py` +- **Pipelines**: `training.sh`, `inference.sh` +- **Configs**: `config.yaml`, dataset-specific names +- **Utilities**: Descriptive names (`get_optimizer.py`, `helpers.py`) + +## Python Package Structure + +Each module is a proper Python package: +- Has `__init__.py` with factory/registry logic +- Can be imported as `from src.module import Component` +- Subpackages are automatically discovered via `import_modules()` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/SKILL.md new file mode 100644 index 0000000..440b42b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/SKILL.md @@ -0,0 +1,307 @@ +--- +name: bug-detective +description: This skill should be used when the user asks to "debug this", "fix this error", "investigate this bug", "troubleshoot this issue", "find the problem", "something is broken", "this isn't working", "why is this failing", or reports errors/exceptions/bugs. Provides systematic debugging workflow and common error patterns. +version: 0.1.0 +--- + +# Bug Detective + +A systematic debugging workflow for investigating and resolving code errors, exceptions, and failures. Provides structured debugging methods and common error pattern recognition. + +## Core Philosophy + +Debugging is a scientific problem-solving process that requires: +1. **Understand the problem** - Clearly define symptoms and expected behavior +2. **Gather evidence** - Collect error messages, logs, stack traces +3. **Form hypotheses** - Infer possible causes based on evidence +4. **Verify hypotheses** - Confirm or eliminate causes through experiments +5. **Resolve the issue** - Apply fixes and verify + +## Debugging Workflow + +### Step 1: Understand the Problem + +Before starting to debug, clarify the following information: + +**Required information to collect:** +- Complete error message content +- Exact location of the error (filename and line number) +- Reproduction steps (how to trigger the error) +- Expected behavior vs actual behavior +- Environment info (OS, versions, dependencies) + +**Question template:** +``` +1. What is the exact error message? +2. Which file and line does the error occur at? +3. How can this issue be reproduced? Provide detailed steps. +4. What was the expected result? What actually happened? +5. What recent changes might have introduced this issue? +``` + +### Step 2: Analyze Error Type + +Choose a debugging strategy based on error type: + +| Error Type | Characteristics | Debugging Method | +|-----------|----------------|-----------------| +| **Syntax Error** | Code cannot be parsed | Check syntax, bracket matching, quotes | +| **Import Error** | ModuleNotFoundError | Check module installation, path config | +| **Type Error** | TypeError | Check data types, type conversions | +| **Attribute Error** | AttributeError | Check if object attribute exists | +| **Key Error** | KeyError | Check if dictionary key exists | +| **Index Error** | IndexError | Check list/array index range | +| **Null Reference** | NoneType/NullPointerException | Check if variable is None | +| **Network Error** | ConnectionError/Timeout | Check network connection, URL, timeout settings | +| **Permission Error** | PermissionError | Check file permissions, user permissions | +| **Resource Error** | FileNotFoundError | Check if file path exists | + +### Step 3: Locate the Problem Source + +Use the following methods to locate the issue: + +**1. Binary Search Method** +- Comment out half the code, check if the problem persists +- Progressively narrow the scope until the problematic code is found + +**2. Log Tracing** +- Add print/logging statements at key locations +- Track variable value changes +- Confirm code execution path + +**3. Breakpoint Debugging** +- Use debugger breakpoint functionality +- Step through code execution +- Inspect variable state + +**4. Stack Trace Analysis** +- Find the call chain from the stack trace in the error message +- Determine the direct cause of the error +- Trace back to the root cause + +### Step 4: Form and Verify Hypotheses + +**Hypothesis framework:** +``` +Hypothesis: [problem description] causes [error phenomenon] + +Verification steps: +1. [verification method 1] +2. [verification method 2] + +Expected results: +- If hypothesis is correct: [expected phenomenon] +- If hypothesis is wrong: [expected phenomenon] +``` + +### Step 5: Apply Fix + +After fixing, verify: +1. The original error is resolved +2. No new errors have been introduced +3. Related functionality still works correctly +4. Tests added to prevent regression + +## Python Common Error Patterns + +### 1. Indentation Errors +### 2. Mutable Default Arguments +### 3. Closure Issues in Loops +### 4. Modifying a List While Iterating +### 5. Using `is` for String Comparison +### 6. Forgetting to Call `super().__init__()` + +## JavaScript/TypeScript Common Error Patterns + +### 1. `this` Binding Issues +### 2. Async Error Handling +### 3. Object Reference Comparison + +## Bash/Zsh Common Error Patterns + +### 1. Spacing Issues + +```bash +# ❌ No spaces allowed in assignment +name = "John" # Error: tries to run 'name' command + +# ✅ Correct assignment +name="John" + +# ❌ Missing spaces in conditional test +if[$name -eq 1]; then # Error + +# ✅ Correct +if [ $name -eq 1 ]; then +``` + +### 2. Quoting Issues + +```bash +# ❌ Variables not expanded inside single quotes +echo 'The value is $var' # Output: The value is $var + +# ✅ Use double quotes +echo "The value is $var" # Output: The value is actual_value + +# ❌ Using backticks for command substitution (confusing) +result=`command` + +# ✅ Use $() +result=$(command) +``` + +### 3. Unquoted Variables + +```bash +# ❌ Unquoted variable, empty value causes errors +rm -rf $dir/* # If dir is empty, deletes all files in current directory + +# ✅ Always quote variables +[ -n "$dir" ] && rm -rf "$dir"/* + +# Or use set -u to prevent undefined variables +set -u # or set -o nounset +``` + +### 4. Variable Scope in Loops + +```bash +# ❌ Pipe creates subshell, outer variable unchanged +cat file.txt | while read line; do + count=$((count + 1)) # Outer count won't change +done +echo "Total: $count" # Outputs 0 + +# ✅ Use process substitution or redirection +while read line; do + count=$((count + 1)) +done < file.txt +echo "Total: $count" # Correct output +``` + +### 5. Array Operations + +```bash +# ❌ Incorrect array access +arr=(1 2 3) +echo $arr[1] # Outputs 1[1] + +# ✅ Correct array access +echo ${arr[1]} # Outputs 2 +echo ${arr[@]} # Outputs all elements +echo ${#arr[@]} # Outputs array length +``` + +### 6. String Comparison + +```bash +# ✅ Use `=` inside POSIX `[` tests and `==` inside Bash `[[ ]]` tests +if [ "$name" = "John" ]; then +if [[ "$name" == "John" ]]; then + +# ❌ Using -eq for numeric comparison instead of = +if [ $age = 18 ]; then # Wrong + +# ✅ Use arithmetic operators for numeric comparison +if [ $age -eq 18 ]; then +if (( age == 18 )); then +``` + +### 7. Command Failure Continues Execution + +```bash +# ❌ Execution continues after command failure +cd /nonexistent +rm file.txt # Deletes file.txt in current directory + +# ✅ Use set -e to exit on error +set -e # or set -o errexit +cd /nonexistent # Script exits here +rm file.txt + +# Or check if command succeeded +cd /nonexistent || exit 1 +``` + +## Common Debugging Commands + +### Python pdb Debugger +```bash +python -m pdb script.py +pytest -x -vv tests/test_target.py +``` + +### Node.js Inspector +```bash +node --inspect-brk app.js +node --trace-warnings app.js +``` + +### Git Bisect +```bash +git bisect start +git bisect bad +git bisect good +``` + +### Bash Debugging + +```bash +# Run script in debug mode +bash -x script.sh # Print each command +bash -v script.sh # Print command source +bash -n script.sh # Syntax check, no execution + +# Enable debugging within a script +set -x # Enable command tracing +set -v # Enable verbose mode +set -e # Exit on error +set -u # Error on undefined variables +set -o pipefail # Fail if any command in pipe fails +``` + +## Preventive Debugging + +### 1. Use Type Checking +### 2. Input Validation +### 3. Defensive Programming +### 4. Logging + +## Debugging Checklist + +### Before Starting +- [ ] Obtain the complete error message +- [ ] Record the stack trace of the error +- [ ] Confirm reproduction steps +- [ ] Understand expected behavior + +### During Debugging +- [ ] Check recent code changes +- [ ] Use binary search to locate the issue +- [ ] Add logs to trace variables +- [ ] Verify hypotheses + +### After Resolution +- [ ] Confirm the original error is fixed +- [ ] Test related functionality +- [ ] Add tests to prevent regression +- [ ] Document the problem and solution + +## Additional Resources + +### Reference Files + +For detailed debugging techniques and patterns: +- **`references/python-errors.md`** - Python error details +- **`references/javascript-errors.md`** - JavaScript/TypeScript error details +- **`references/shell-errors.md`** - Bash/Zsh script error details +- **`references/debugging-tools.md`** - Debugging tools usage guide +- **`references/common-patterns.md`** - Common error patterns + +### Example Files + +Working debugging examples: +- **`examples/debugging-workflow.py`** - Complete debugging workflow example +- **`examples/error-handling-patterns.py`** - Error handling patterns +- **`examples/debugging-workflow.sh`** - Shell script debugging example diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/debugging-workflow.py b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/debugging-workflow.py new file mode 100644 index 0000000..0f76d27 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/debugging-workflow.py @@ -0,0 +1,241 @@ +""" +调试流程示例 + +这个示例展示了完整的调试流程，从发现问题到解决问题。 +""" + +import logging + +# 配置日志 +logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s') +logger = logging.getLogger(__name__) + + +# ============================================ +# 问题 1：IndexError +# ============================================ + +def get_item(items, index): + """ + 问题：直接访问索引可能导致 IndexError + + 错误现象： + IndexError: list index out of range + """ + # ❌ 有问题的代码 + # return items[index] + + # ✅ 修复后的代码 + if 0 <= index < len(items): + return items[index] + else: + logger.warning(f"索引 {index} 超出范围 [0, {len(items)})") + return None + + +# ============================================ +# 问题 2：TypeError - 字符串拼接 +# ============================================ + +def format_message(name, count): + """ + 问题：尝试拼接字符串和数字 + + 错误现象： + TypeError: can only concatenate str (not "int") to str + """ + # ❌ 有问题的代码 + # return name + ": " + count + + # ✅ 修复后的代码 + return f"{name}: {count}" + # 或 + # return name + ": " + str(count) + + +# ============================================ +# 问题 3：KeyError +# ============================================ + +def get_user_info(users, user_id): + """ + 问题：直接访问字典中可能不存在的键 + + 错误现象： + KeyError: 'user_123' + """ + # ❌ 有问题的代码 + # return users[user_id] + + # ✅ 修复后的代码 - 方法1：使用 get() + return users.get(user_id, None) + + # ✅ 修复后的代码 - 方法2：检查键是否存在 + # if user_id in users: + # return users[user_id] + # return None + + +# ============================================ +# 问题 4：AttributeError - None 对象 +# ============================================ + +def process_data(data_provider): + """ + 问题：data_provider 可能返回 None + + 错误现象： + AttributeError: 'NoneType' object has no attribute 'process' + """ + data = data_provider.get_data() + + # ❌ 有问题的代码 + # return data.process() + + # ✅ 修复后的代码 + if data is not None: + return data.process() + else: + logger.error("数据为 None，无法处理") + return None + + +# ============================================ +# 问题 5：修改正在迭代的列表 +# ============================================ + +def remove_even_numbers(numbers): + """ + 问题：迭代时修改列表导致跳过元素 + + 错误现象： + 某些偶数没有被移除 + """ + # ❌ 有问题的代码 + # for num in numbers: + # if num % 2 == 0: + # numbers.remove(num) + # return numbers + + # ✅ 修复后的代码 - 方法1：列表推导式 + return [num for num in numbers if num % 2 != 0] + + # ✅ 修复后的代码 - 方法2：使用副本 + # for num in numbers[:]: + # if num % 2 == 0: + # numbers.remove(num) + # return numbers + + +# ============================================ +# 调试技巧示例 +# ============================================ + +def debug_with_logging(data): + """ + 使用日志追踪问题 + """ + logger.debug(f"输入数据: {data}") + + # 步骤 1 + processed = step1(data) + logger.debug(f"步骤1结果: {processed}") + + # 步骤 2 + result = step2(processed) + logger.debug(f"步骤2结果: {result}") + + return result + + +def step1(data): + """模拟步骤1""" + return [x * 2 for x in data] + + +def step2(data): + """模拟步骤2""" + return sum(data) + + +# ============================================ +# 异常处理示例 +# ============================================ + +def safe_divide(a, b): + """ + 正确的异常处理模式 + """ + try: + result = a / b + logger.info(f"{a} / {b} = {result}") + return result + except ZeroDivisionError: + logger.error(f"除数不能为零: {b}") + return None + except TypeError as e: + logger.error(f"类型错误: {e}") + return None + + +# ============================================ +# 使用断言进行调试 +# ============================================ + +def calculate_discount(price, discount_rate): + """ + 使用断言验证假设 + """ + # 断言：价格应该是正数 + assert price > 0, f"价格应该是正数，实际: {price}" + + # 断言：折扣率应该在 0-1 之间 + assert 0 <= discount_rate <= 1, f"折扣率应该在 0-1 之间，实际: {discount_rate}" + + discounted_price = price * (1 - discount_rate) + + # 断言：折扣后的价格应该小于原价 + assert discounted_price <= price, "折扣价格应该小于原价" + + return discounted_price + + +# ============================================ +# 测试代码 +# ============================================ + +if __name__ == "__main__": + print("=" * 50) + print("调试示例") + print("=" * 50) + + # 测试 get_item + print("\n1. 测试 get_item:") + items = ['a', 'b', 'c'] + print(f"get_item(items, 1) = {get_item(items, 1)}") + print(f"get_item(items, 10) = {get_item(items, 10)}") + + # 测试 format_message + print("\n2. 测试 format_message:") + print(f"format_message('Count', 42) = {format_message('Count', 42)}") + + # 测试 get_user_info + print("\n3. 测试 get_user_info:") + users = {'user_1': 'Alice', 'user_2': 'Bob'} + print(f"get_user_info(users, 'user_1') = {get_user_info(users, 'user_1')}") + print(f"get_user_info(users, 'user_999') = {get_user_info(users, 'user_999')}") + + # 测试 remove_even_numbers + print("\n4. 测试 remove_even_numbers:") + numbers = [1, 2, 3, 4, 5, 6] + print(f"原始: {numbers}") + print(f"结果: {remove_even_numbers(numbers)}") + + # 测试 safe_divide + print("\n5. 测试 safe_divide:") + print(f"safe_divide(10, 2) = {safe_divide(10, 2)}") + print(f"safe_divide(10, 0) = {safe_divide(10, 0)}") + + # 测试 calculate_discount + print("\n6. 测试 calculate_discount:") + print(f"calculate_discount(100, 0.2) = {calculate_discount(100, 0.2)}") diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/debugging-workflow.sh b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/debugging-workflow.sh new file mode 100755 index 0000000..1ff74a5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/debugging-workflow.sh @@ -0,0 +1,400 @@ +#!/bin/bash +# +# Shell 脚本调试流程示例 +# 展示常见的 Bash 脚本错误和调试方法 +# + +# ============================================ +# 调试设置 +# ============================================ + +# 取消注释以启用调试模式 +# set -x # 打印每个命令 +# set -e # 错误时退出 +# set -u # 未定义变量报错 +# set -o pipefail # 管道中任何命令失败则失败 + +# 或组合使用 +# set -xeuo pipefail # 严格模式 + + +# ============================================ +# 错误处理函数 +# ============================================ + +# 错误退出函数 +die() { + local message="$1" + local exit_code="${2:-1}" + echo "Error: $message" >&2 + exit "$exit_code" +} + +# 记录函数 +log() { + local level="$1" + shift + echo "[$(date '+%Y-%m-%d %H:%M:%S')] [$level] $*" >&2 +} + +log_info() { log "INFO" "$@"; } +log_warn() { log "WARN" "$@"; } +log_error() { log "ERROR" "$@"; } + + +# ============================================ +# 问题 1：未引用的变量 +# ============================================ + +# 错误示例：变量未引用 +demo_unquoted_variable() { + echo "=== 问题 1：未引用的变量 ===" + + local name="John Doe" + + # 错误：变量未引用，空值会导致语法错误 + # if [ $name = "John Doe" ]; then + # echo "Match" + # fi + + # 正确：始终引用变量 + if [ "$name" = "John Doe" ]; then + log_info "变量匹配: $name" + fi +} + + +# ============================================ +# 问题 2：命令失败继续执行 +# ============================================ + +demo_command_failure() { + echo "=== 问题 2：命令失败继续执行 ===" + + # 错误：cd 失败后继续执行 + # cd /nonexistent_directory + # rm -rf file.txt # 会删除当前目录的文件！ + + # 正确：检查命令是否成功 + cd /tmp || die "无法切换到 /tmp 目录" + log_info "成功切换到目录: $(pwd)" + + cd - > /dev/null || true +} + + +# ============================================ +# 问题 3：循环中的变量作用域（管道问题） +# ============================================ + +demo_pipeline_scope() { + echo "=== 问题 3：管道中的变量作用域 ===" + + local count=0 + + # 错误：管道创建子 shell，外部变量不改变 + # echo -e "1\n2\n3" | while read line; do + # count=$((count + 1)) + # done + # echo "Count: $count" # 输出 0 + + # 正确：使用重定向 + while read line; do + count=$((count + 1)) + done < <(echo -e "1\n2\n3") + log_info "计数结果: $count" +} + + +# ============================================ +# 问题 4：数组操作 +# ============================================ + +demo_array_operations() { + echo "=== 问题 4：数组操作 ===" + + local fruits=("apple" "banana" "cherry") + + # 错误的数组访问 + # echo $fruits[1] # 输出 apple[1] + + # 正确的数组访问 + log_info "第一个元素: ${fruits[0]}" + log_info "第二个元素: ${fruits[1]}" + log_info "所有元素: ${fruits[@]}" + log_info "数组长度: ${#fruits[@]}" + + # 遍历数组 + for fruit in "${fruits[@]}"; do + log_info "水果: $fruit" + done +} + + +# ============================================ +# 问题 5：字符串比较 +# ============================================ + +demo_string_comparison() { + echo "=== 问题 5：字符串比较 ===" + + local name="John" + + # 错误：数字比较使用 = + # if [ $age = 18 ]; then + + # 正确：字符串比较 + if [[ "$name" == "John" ]]; then + log_info "字符串匹配" + fi + + # 正确：数字比较 + local age=18 + if [ "$age" -eq 18 ]; then + log_info "数字匹配" + fi +} + + +# ============================================ +# 问题 6：算术运算 +# ============================================ + +demo_arithmetic() { + echo "=== 问题 6：算术运算 ===" + + local a=10 + local b=5 + + # 错误：使用 let 或 $(()) + # result = a + b # 这是命令调用 + + # 正确的算术运算 + local result=$((a + b)) + log_info "加法: $a + $b = $result" + + result=$((a - b)) + log_info "减法: $a - $b = $result" + + result=$((a * b)) + log_info "乘法: $a * $b = $result" + + result=$((a / b)) + log_info "除法: $a / $b = $result" + + # 使用 let + let result=a+b + log_info "let 加法: $result" +} + + +# ============================================ +# 参数验证 +# ============================================ + +validate_arguments() { + echo "=== 参数验证 ===" + + # 检查参数数量 + if [ $# -lt 2 ]; then + die "用法: $0 <文件> <目录>" 2 + fi + + local file="$1" + local dir="$2" + + # 检查文件存在 + if [ ! -f "$file" ]; then + die "文件不存在: $file" 3 + fi + + # 检查目录存在 + if [ ! -d "$dir" ]; then + die "目录不存在: $dir" 4 + fi + + log_info "参数验证通过" + log_info "文件: $file" + log_info "目录: $dir" +} + + +# ============================================ +# 使用 trap 进行清理 +# ============================================ + +demo_trap() { + echo "=== 使用 trap 进行清理 ===" + + # 设置清理函数 + cleanup() { + log_info "执行清理操作..." + # 这里可以执行清理操作 + } + + # 捕获退出信号 + trap cleanup EXIT + + # 捕获错误信号 + trap 'log_error "发生错误，行号: $LINENO"' ERR + + # 捕获中断信号 + trap 'log_warn "脚本被中断"; cleanup; exit 130' INT + + log_info "执行一些操作..." + # 模拟操作 + sleep 1 +} + + +# ============================================ +# 调试技巧示例 +# ============================================ + +demo_debugging() { + echo "=== 调试技巧 ===" + + # 1. 使用 echo 调试 + local value="test" + echo "[DEBUG] value = $value" >&2 + + # 2. 使用 printf 格式化输出 + printf "[DEBUG] Count: %d, Name: %s\n" 42 "John" >&2 + + # 3. 检查变量是否设置 + if [ -z "${unset_var+x}" ]; then + log_warn "变量 unset_var 未设置" + fi + + # 4. 显示调用栈 + log_info "调用栈:" + local i=0 + while caller $i; do + ((i++)) + done 2>/dev/null || true +} + + +# ============================================ +# 文件操作错误处理 +# ============================================ + +demo_file_operations() { + echo "=== 文件操作错误处理 ===" + + local tmpfile=$(mktemp) || die "无法创建临时文件" + + # 确保文件被删除 + trap "rm -f '$tmpfile'" EXIT + + # 写入文件 + echo "Test content" > "$tmpfile" || die "无法写入文件: $tmpfile" + + # 读取文件 + local content + content=$(cat "$tmpfile") || die "无法读取文件: $tmpfile" + + log_info "文件内容: $content" + + # trap 会自动清理 +} + + +# ============================================ +# 带重试的操作 +# ============================================ + +demo_retry() { + echo "=== 带重试的操作 ===" + + local max_attempts=3 + local attempt=1 + + while [ $attempt -le $max_attempts ]; do + log_info "尝试 $attempt/$max_attempts..." + + # 模拟可能失败的操作 + if [ $attempt -eq 2 ]; then + log_info "成功！" + return 0 + fi + + log_warn "失败，重试..." + ((attempt++)) + sleep 1 + done + + log_error "所有尝试都失败了" + return 1 +} + + +# ============================================ +# 检查依赖 +# ============================================ + +check_dependencies() { + echo "=== 检查依赖 ===" + + local required_commands=("curl" "jq" "git") + + for cmd in "${required_commands[@]}"; do + if ! command -v "$cmd" &> /dev/null; then + log_error "缺少依赖: $cmd" + return 1 + fi + log_info "✓ $cmd 可用" + done + + log_info "所有依赖都已满足" +} + + +# ============================================ +# 主函数 +# ============================================ + +main() { + echo "============================================" + echo "Shell 脚本调试示例" + echo "============================================" + + # 运行各个示例 + demo_unquoted_variable + echo "" + + demo_command_failure + echo "" + + demo_pipeline_scope + echo "" + + demo_array_operations + echo "" + + demo_string_comparison + echo "" + + demo_arithmetic + echo "" + + demo_trap + echo "" + + demo_debugging + echo "" + + demo_file_operations + echo "" + + demo_retry + echo "" + + check_dependencies + echo "" + + log_info "所有示例执行完成" +} + +# 运行主函数 +main "$@" diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/error-handling-patterns.py b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/error-handling-patterns.py new file mode 100644 index 0000000..57d197e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/examples/error-handling-patterns.py @@ -0,0 +1,305 @@ +""" +错误处理模式示例 + +展示各种错误处理的最佳实践 +""" + +import logging +from typing import Optional, List, Dict, Any +from functools import wraps + +logger = logging.getLogger(__name__) + + +# ============================================ +# 模式 1：具体异常捕获 +# ============================================ + +def read_file(filepath: str) -> Optional[str]: + """ + 捕获具体异常而不是宽泛的 Exception + """ + try: + with open(filepath, 'r') as f: + return f.read() + except FileNotFoundError: + logger.error(f"文件不存在: {filepath}") + return None + except PermissionError: + logger.error(f"没有权限读取文件: {filepath}") + return None + except UnicodeDecodeError: + logger.error(f"文件编码错误: {filepath}") + return None + + +# ============================================ +# 模式 2：带重试的操作 +# ============================================ + +def retry_operation(max_attempts: int = 3): + """ + 装饰器：自动重试失败的操作 + """ + def decorator(func): + @wraps(func) + def wrapper(*args, **kwargs): + for attempt in range(1, max_attempts + 1): + try: + return func(*args, **kwargs) + except Exception as e: + if attempt == max_attempts: + logger.error(f"操作失败，已重试 {max_attempts} 次: {e}") + raise + logger.warning(f"操作失败，第 {attempt} 次重试...") + return None + return wrapper + return decorator + + +@retry_operation(max_attempts=3) +def unstable_api_call() -> Dict[str, Any]: + """ + 模拟不稳定的 API 调用 + """ + import random + if random.random() < 0.7: # 70% 失败率 + raise ConnectionError("API 连接失败") + return {"status": "success", "data": "result"} + + +# ============================================ +# 模式 3：上下文管理器处理资源 +# ============================================ + +class DatabaseConnection: + """ + 自定义上下文管理器，确保资源正确释放 + """ + def __init__(self, connection_string: str): + self.connection_string = connection_string + self.connection = None + + def __enter__(self): + logger.info(f"连接数据库: {self.connection_string}") + self.connection = f"Connection to {self.connection_string}" + return self.connection + + def __exit__(self, exc_type, exc_val, exc_tb): + if exc_type is not None: + logger.error(f"发生异常: {exc_val}") + logger.info("关闭数据库连接") + # 清理资源 + self.connection = None + return False # 不抑制异常 + + +# ============================================ +# 模式 4：链式异常（保留原始异常） +# ============================================ + +def validate_and_process(data: Dict[str, Any]) -> Any: + """ + 使用 raise from 保留原始异常链 + """ + try: + # 验证数据 + if 'value' not in data: + raise ValueError("数据中缺少 'value' 字段") + + value = data['value'] + if not isinstance(value, (int, float)): + raise TypeError(f"value 应该是数字，实际类型: {type(value)}") + + # 处理数据 + return value * 2 + + except (ValueError, TypeError) as e: + # 保留原始异常并添加上下文 + raise RuntimeError(f"数据处理失败: {data}") from e + + +# ============================================ +# 模式 5：结果对象模式（不使用异常） +# ============================================ + +class Result: + """ + 结果对象模式：封装成功/失败状态 + """ + def __init__(self, success: bool, value: Any = None, error: str = None): + self.success = success + self.value = value + self.error = error + + @classmethod + def ok(cls, value: Any) -> 'Result': + return cls(success=True, value=value) + + @classmethod + def err(cls, error: str) -> 'Result': + return cls(success=False, error=error) + + def is_ok(self) -> bool: + return self.success + + def is_err(self) -> bool: + return not self.success + + def unwrap(self) -> Any: + if not self.success: + raise ValueError(f"尝试解包错误结果: {self.error}") + return self.value + + def unwrap_or(self, default: Any) -> Any: + return self.value if self.success else default + + +def safe_divide_result(a: float, b: float) -> Result: + """ + 使用结果对象而不是异常 + """ + if b == 0: + return Result.err(f"除数不能为零: {b}") + + try: + return Result.ok(a / b) + except Exception as e: + return Result.err(f"计算失败: {e}") + + +# ============================================ +# 模式 6：多项验证错误收集 +# ============================================ + +class ValidationError(Exception): + """自定义验证错误""" + def __init__(self, errors: List[str]): + self.errors = errors + super().__init__("\n".join(errors)) + + +def validate_user(data: Dict[str, Any]) -> None: + """ + 收集所有验证错误而不是遇到第一个就停止 + """ + errors = [] + + if 'name' not in data: + errors.append("缺少 'name' 字段") + elif not isinstance(data['name'], str): + errors.append("'name' 应该是字符串") + elif len(data['name']) < 2: + errors.append("'name' 长度应该至少为 2") + + if 'age' not in data: + errors.append("缺少 'age' 字段") + elif not isinstance(data['age'], int): + errors.append("'age' 应该是整数") + elif data['age'] < 0 or data['age'] > 150: + errors.append("'age' 应该在 0-150 之间") + + if 'email' in data and '@' not in data['email']: + errors.append("'email' 格式不正确") + + if errors: + raise ValidationError(errors) + + +# ============================================ +# 模式 7：默认值和回退 +# ============================================ + +def get_config(config: Dict[str, Any], key: str, default: Any = None) -> Any: + """ + 安全获取配置，支持多级键和默认值 + """ + if '.' in key: + # 支持嵌套键，如 "database.host" + keys = key.split('.') + value = config + for k in keys: + if isinstance(value, dict) and k in value: + value = value[k] + else: + return default + return value + + # 简单键 + return config.get(key, default) + + +# ============================================ +# 模式 8：优雅降级 +# ============================================ + +def get_user_preferences(user_id: int) -> Dict[str, Any]: + """ + 尝试多种方法获取用户偏好，优雅降级 + """ + # 尝试 1：从缓存获取 + try: + return _get_from_cache(user_id) + except Exception as e: + logger.warning(f"从缓存获取失败: {e}") + + # 尝试 2：从数据库获取 + try: + return _get_from_database(user_id) + except Exception as e: + logger.warning(f"从数据库获取失败: {e}") + + # 尝试 3：使用默认配置 + logger.info("使用默认配置") + return _get_default_preferences() + + +def _get_from_cache(user_id: int) -> Dict[str, Any]: + # 模拟缓存失败 + raise ConnectionError("缓存连接失败") + + +def _get_from_database(user_id: int) -> Dict[str, Any]: + # 模拟数据库失败 + raise ConnectionError("数据库连接失败") + + +def _get_default_preferences() -> Dict[str, Any]: + return { + "theme": "light", + "language": "zh-CN", + "notifications": True + } + + +# ============================================ +# 测试代码 +# ============================================ + +if __name__ == "__main__": + logging.basicConfig(level=logging.INFO) + + print("=" * 50) + print("错误处理模式示例") + print("=" * 50) + + # 测试结果对象模式 + print("\n1. 结果对象模式:") + result1 = safe_divide_result(10, 2) + print(f"10 / 2 = {result1.unwrap()}") + + result2 = safe_divide_result(10, 0) + print(f"10 / 0 = {result2.unwrap_or('N/A')} ({result2.error})") + + # 测试优雅降级 + print("\n2. 优雅降级:") + prefs = get_user_preferences(123) + print(f"用户偏好: {prefs}") + + # 测试上下文管理器 + print("\n3. 上下文管理器:") + try: + with DatabaseConnection("localhost:5432") as conn: + print(f"连接: {conn}") + except Exception as e: + print(f"操作失败: {e}") diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/common-patterns.md b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/common-patterns.md new file mode 100644 index 0000000..b125edc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/common-patterns.md @@ -0,0 +1,308 @@ +# 常见错误模式 + +## 通用编程错误模式 + +### 1. Off-by-one Error（差一错误） + +**描述**：循环或索引中出现 ±1 的偏差 + +**示例**： +```python +# ❌ 错误：范围应该是 range(n) 而不是 range(n+1) +for i in range(len(items) + 1): + print(items[i]) # IndexError + +# ✅ 正确 +for i in range(len(items)): + print(items[i]) +``` + +### 2. Null/None 引用错误 + +**描述**：尝试访问 None 对象的属性或方法 + +**Python**： +```python +# ❌ 可能返回 None +result = get_data() +print(result.value) # AttributeError + +# ✅ 检查 None +result = get_data() +if result is not None: + print(result.value) +``` + +**JavaScript**： +```javascript +// ❌ 可能是 null +const user = getUser(); +console.log(user.name); // TypeError + +// ✅ 使用可选链 +console.log(user?.name); +``` + +### 3. 资源泄漏 + +**描述**：打开的资源（文件、连接）未正确关闭 + +**Python**： +```python +# ❌ 文件可能未关闭 +f = open("file.txt") +content = f.read() +# 如果发生异常，文件不会关闭 + +# ✅ 使用 with 语句 +with open("file.txt") as f: + content = f.read() +# 文件自动关闭 +``` + +### 4. 竞态条件 + +**描述**：多线程/进程间的时序依赖问题 + +**示例**： +```python +# ❌ 检查后使用（TOCTOU） +if os.path.exists("file.txt"): + # 其他进程可能在这之间删除文件 + with open("file.txt") as f: + content = f.read() + +# ✅ 直接尝试并处理异常 +try: + with open("file.txt") as f: + content = f.read() +except FileNotFoundError: + content = None +``` + +### 5. 忘记返回值 + +**描述**：函数没有显式返回值，导致返回 None + +**示例**： +```python +# ❌ 忘记返回结果 +def calculate(x, y): + result = x + y + # 忘记 return + +# ✅ 正确返回 +def calculate(x, y): + return x + y +``` + +### 6. 错误的比较运算符 + +**描述**：使用 = 代替 ==，或混淆 is 和 == + +**Python**： +```python +# ❌ 赋值而不是比较 +if x = 5: # SyntaxError + +# ❌ 使用 is 比较值 +if x is 5: # 不保证正确 + +# ✅ 正确 +if x == 5: +``` + +### 7. 浮点数精度问题 + +**描述**：浮点数比较因精度问题失败 + +**示例**： +```python +# ❌ 直接比较浮点数 +if 0.1 + 0.2 == 0.3: # False + print("相等") + +# ✅ 使用容差比较 +if abs((0.1 + 0.2) - 0.3) < 1e-9: + print("相等") + +# 或使用 math.isclose() +import math +if math.isclose(0.1 + 0.2, 0.3): + print("相等") +``` + +### 8. 字符串拼接性能问题 + +**描述**：在循环中使用 + 拼接字符串 + +**示例**： +```python +# ❌ 低效：每次创建新字符串 +result = "" +for item in items: + result += str(item) + +# ✅ 高效：使用列表和 join +result = "".join(str(item) for item in items) +``` + +## Python 特有模式 + +### 1. 可变默认参数 + +```python +# ❌ 所有调用共享同一个列表 +def append(item, items=[]): + items.append(item) + return items + +# ✅ 使用 None 作为默认值 +def append(item, items=None): + if items is None: + items = [] + items.append(item) + return items +``` + +### 2. 闭包变量绑定问题 + +```python +# ❌ 所有函数使用相同的 i 值 +funcs = [lambda: i for i in range(3)] +# 所有函数都返回 2 + +# ✅ 使用默认参数捕获值 +funcs = [lambda i=i: i for i in range(3)] +``` + +### 3. 修改正在迭代的序列 + +```python +# ❌ 迭代时修改列表 +items = [1, 2, 3, 4] +for item in items: + if item % 2 == 0: + items.remove(item) + +# ✅ 创建新列表或使用副本 +items = [item for item in items if item % 2 != 0] + +# 或 +for item in items[:]: + if item % 2 == 0: + items.remove(item) +``` + +## JavaScript/TypeScript 特有模式 + +### 1. this 绑定问题 + +```javascript +// ❌ this 丢失上下文 +class Counter { + count = 0; + increment() { + setTimeout(function() { + this.count++; // this 不是 Counter 实例 + }, 100); + } +} + +// ✅ 使用箭头函数 +class Counter { + count = 0; + increment() { + setTimeout(() => { + this.count++; // this 正确绑定 + }, 100); + } +} +``` + +### 2. 异步错误处理 + +```javascript +// ❌ 没有处理 Promise 错误 +async function getData() { + const response = await fetch(url); + return response.json(); // 如果失败会抛出异常 +} + +// ✅ 使用 try-catch +async function getData() { + try { + const response = await fetch(url); + return await response.json(); + } catch (error) { + console.error("获取数据失败:", error); + throw error; + } +} +``` + +### 3. 数组/对象引用 + +```javascript +// ❌ 直接赋值会复制引用 +const arr1 = [1, 2, 3]; +const arr2 = arr1; +arr2.push(4); // arr1 也会被修改 + +// ✅ 创建副本 +const arr2 = [...arr1]; // 或 arr1.slice() + +// 对象 +const obj1 = { a: 1 }; +const obj2 = { ...obj1 }; // 或 Object.assign({}, obj1) +``` + +## 并发错误模式 + +### 1. 死锁 + +```python +# ❌ 可能死锁 +import threading + +lock1 = threading.Lock() +lock2 = threading.Lock() + +def thread1(): + with lock1: + with lock2: + # 操作 + +def thread2(): + with lock2: + with lock1: # 死锁 + # 操作 +``` + +### 2. 数据竞争 + +```python +# ❌ 多个线程同时修改共享变量 +counter = 0 + +def increment(): + global counter + counter += 1 # 非原子操作 + +# ✅ 使用锁 +counter = 0 +lock = threading.Lock() + +def increment(): + global counter + with lock: + counter += 1 +``` + +## 预防措施 + +1. **使用类型检查**：TypeScript、Python 类型注解 +2. **编写单元测试**：覆盖边界条件 +3. **使用静态分析工具**：pylint、eslint +4. **代码审查**：让他人检查代码 +5. **使用防御性编程**：验证输入、处理异常 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/debugging-tools.md b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/debugging-tools.md new file mode 100644 index 0000000..59430a2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/debugging-tools.md @@ -0,0 +1,29 @@ +# Debugging Tools + +## Python +```bash +python -m pdb script.py +python -m traceback your_script.py +pytest -x -vv tests/test_target.py +``` + +## Node.js +```bash +node --inspect-brk app.js +node --trace-warnings app.js +npm test -- --runInBand +``` + +## Git +```bash +git bisect start +git bisect bad +git bisect good +``` + +## Shell +```bash +bash -n script.sh +bash -x script.sh +shellcheck script.sh +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/javascript-errors.md b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/javascript-errors.md new file mode 100644 index 0000000..d731b1e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/javascript-errors.md @@ -0,0 +1,14 @@ +# JavaScript / TypeScript Error Guide + +## Frequent failure classes +- `TypeError` from undefined/null access +- async error swallowing in `Promise` chains +- `this` binding mismatches +- stale closure bugs in hooks or event handlers +- ESM / CJS import mismatches + +## Minimum debugging flow +1. copy the full stack trace, +2. identify whether the failure is runtime, bundler, or type-level, +3. confirm the failing object/value before changing logic, +4. reproduce with the smallest possible input. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/python-errors.md b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/python-errors.md new file mode 100644 index 0000000..dd973b6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/python-errors.md @@ -0,0 +1,311 @@ +# Python 错误详解 + +## 常见内置异常类型 + +### 1. SyntaxError（语法错误） + +**特征**：代码无法解析，在运行前就被检测到 + +**常见原因**： +- 括号不匹配 +- 缺少冒号 +- 缩进不正确 +- 引号不匹配 + +**示例**： +```python +# ❌ 缺少冒号 +if True + print("missing colon") + +# ✅ 正确 +if True: + print("has colon") +``` + +### 2. IndentationError（缩进错误） + +**特征**：缩进不一致或使用错误的缩进 + +**常见原因**： +- 混用 Tab 和空格 +- 缩进级别不正确 + +**示例**： +```python +# ❌ 混用空格和 Tab +def test(): + print("mixed") # Tab + print("spaces") # 空格 + +# ✅ 统一使用 4 个空格 +def test(): + print("spaces") + print("consistent") +``` + +### 3. NameError（名称错误） + +**特征**：变量或函数名不存在 + +**常见原因**： +- 变量未定义就使用 +- 函数名拼写错误 +- 变量作用域问题 + +**示例**： +```python +# ❌ 变量未定义 +print(undefined_var) + +# ✅ 先定义再使用 +my_var = 42 +print(my_var) +``` + +### 4. TypeError（类型错误） + +**特征**：操作或函数应用于错误的数据类型 + +**常见原因**： +- 拼接不同类型 +- 函数参数类型错误 +- 对不支持的操作使用运算符 + +**示例**： +```python +# ❌ 拼接字符串和数字 +result = "Value: " + 42 + +# ✅ 转换类型 +result = "Value: " + str(42) +# 或使用 f-string +result = f"Value: {42}" +``` + +### 5. AttributeError（属性错误） + +**特征**：对象没有指定的属性或方法 + +**常见原因**： +- 属性名拼写错误 +- 对象类型不是预期的 +- 大小写错误 + +**示例**： +```python +# ❌ 列表没有 append 以外的方法 +my_list = [1, 2, 3] +my_list.push(4) # 列表没有 push 方法 + +# ✅ 使用正确的方法 +my_list.append(4) +``` + +### 6. KeyError（键错误） + +**特征**：字典中不存在指定的键 + +**常见原因**： +- 键名拼写错误 +- 键不存在于字典中 + +**示例**： +```python +data = {"name": "Alice"} + +# ❌ 直接访问不存在的键 +age = data["age"] # KeyError + +# ✅ 使用 get() 方法 +age = data.get("age", 0) # 返回默认值 0 +``` + +### 7. IndexError（索引错误） + +**特征**：序列索引超出范围 + +**常见原因**： +- 索引为负数（除非是有意为之） +- 索引大于序列长度-1 +- 序列为空时访问索引 + +**示例**： +```python +items = [1, 2, 3] + +# ❌ 索引超出范围 +item = items[5] # IndexError + +# ✅ 检查长度后再访问 +if len(items) > 5: + item = items[5] +else: + item = None +``` + +### 8. ValueError（值错误） + +**特征**：参数类型正确但值不合适 + +**常见原因**： +- 字符串转整数失败 +- 数学运算值域错误 +- 参数值不在允许范围内 + +**示例**： +```python +# ❌ 无法转换为整数 +num = int("abc") + +# ✅ 处理可能的错误 +try: + num = int(input()) +except ValueError: + num = 0 +``` + +### 9. ImportError / ModuleNotFoundError（导入错误） + +**特征**：无法导入模块 + +**常见原因**： +- 模块未安装 +- 模块路径不在 PYTHONPATH 中 +- 模块名拼写错误 + +**示例**： +```python +# ❌ 模块未安装 +import missing_module + +# 解决方法：安装模块 +# pip install missing-module +``` + +### 10. FileNotFoundError（文件未找到错误） + +**特征**：尝试打开不存在的文件 + +**常见原因**： +- 文件路径错误 +- 文件不存在 +- 相对路径使用错误 + +**示例**： +```python +# ❌ 文件不存在 +with open("missing.txt") as f: + content = f.read() + +# ✅ 使用 try-except 或检查文件存在 +try: + with open("file.txt") as f: + content = f.read() +except FileNotFoundError: + content = "" +``` + +## 异常处理最佳实践 + +### 1. 捕获具体异常 + +```python +# ❌ 捕获所有异常（不良实践） +try: + result = dangerous_operation() +except: + pass + +# ✅ 捕获具体异常 +try: + result = dangerous_operation() +except (ValueError, TypeError) as e: + logger.error(f"操作失败: {e}") +``` + +### 2. 使用 finally 清理资源 + +```python +try: + file = open("data.txt", "r") + content = file.read() +except FileNotFoundError: + content = "" +finally: + # 无论是否发生异常都会执行 + if 'file' in locals(): + file.close() +``` + +### 3. 使用上下文管理器 + +```python +# ✅ 推荐：使用 with 语句 +with open("data.txt", "r") as file: + content = file.read() +# 文件会自动关闭 +``` + +### 4. 链式异常 + +```python +try: + process_data(data) +except ValueError as e: + # 使用 raise from 保留原始异常 + raise RuntimeError("数据处理失败") from e +``` + +## 调试技巧 + +### 1. 使用 traceback 模块 + +```python +import traceback + +try: + risky_operation() +except Exception: + # 打印完整的堆栈跟踪 + traceback.print_exc() +``` + +### 2. 使用 pdb 调试器 + +```python +import pdb + +# 在代码中设置断点 +pdb.set_trace() + +# 或使用 breakpoint() (Python 3.7+) +breakpoint() +``` + +### 3. 使用 logging 模块 + +```python +import logging + +logging.basicConfig(level=logging.DEBUG) +logger = logging.getLogger(__name__) + +logger.debug("调试信息") +logger.info("普通信息") +logger.warning("警告") +logger.error("错误") +logger.critical("严重错误") +``` + +## 常见错误排查清单 + +- [ ] 检查拼写（变量名、函数名、属性名） +- [ ] 检查数据类型（使用 type() 函数） +- [ ] 检查变量值（使用 print() 或调试器） +- [ ] 检查索引和键是否在范围内 +- [ ] 检查文件路径是否正确 +- [ ] 检查缩进是否一致 +- [ ] 检查括号、引号是否匹配 +- [ ] 检查是否正确导入了模块 +- [ ] 检查异常是否被正确处理 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/shell-errors.md b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/shell-errors.md new file mode 100644 index 0000000..82ca8c8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/bug-detective/references/shell-errors.md @@ -0,0 +1,236 @@ +# Bash/Zsh 脚本错误详解 + +## 常见错误类型 + +### 1. Command Not Found + +**特征**：bash: command: command not found + +**常见原因**： +- 命令拼写错误 +- 命令未安装 +- PATH 环境变量不正确 +- 脚本 shebang 错误 + +**示例**： +```bash +# 拼写错误 +pyhon script.py # command not found + +# 正确拼写 +python script.py + +# PATH 问题 +/usr/local/bin/mycommand # 如果 PATH 不包含 /usr/local/bin + +# 使用完整路径或添加到 PATH +export PATH="/usr/local/bin:$PATH" +mycommand +``` + +### 2. Syntax Error + +**特征**：syntax error near unexpected token + +**常见原因**： +- 缺少 then/fi/done/ esac +- 括号不匹配 +- 操作符缺少空格 + +**示例**： +```bash +# 缺少 then +if [ 1 -eq 1 ] +echo "yes" # syntax error + +# 正确 +if [ 1 -eq 1 ]; then + echo "yes" +fi +``` + +### 3. Permission Denied + +**特征**：bash: ./script.sh: Permission denied + +**解决方案**： +```bash +# 添加执行权限 +chmod +x script.sh + +# 或使用 bash 运行 +bash script.sh +``` + +## 调试技巧 + +### 1. 使用 set -x 追踪执行 + +```bash +#!/bin/bash +set -x # 启用命令追踪 + +name="John" +echo "Hello $name" + +# 输出： +# + name=John +# + echo 'Hello John' +# Hello John +``` + +### 2. 使用 set -e 遇错退出 + +```bash +#!/bin/bash +set -e # 任何命令失败时退出 + +cd /nonexistent # 脚本在此处退出 +echo "This won't run" +``` + +### 3. 使用 set -u 检测未定义变量 + +```bash +#!/bin/bash +set -u # 未定义变量时报错 + +echo $undefined_var # 报错并退出 +``` + +### 4. 组合使用调试选项 + +```bash +#!/bin/bash +set -xeuo pipefail # 严格模式 + +# -x: 打印每个命令 +# -e: 错误时退出 +# -u: 未定义变量报错 +# -o pipefail: 管道失败则失败 +``` + +### 5. 使用 trap 捕获错误 + +```bash +#!/bin/bash +# 在脚本退出时执行清理 +trap 'echo "Script exited with code $?"' EXIT + +# 在错误时执行 +trap 'echo "Error on line $LINENO"' ERR + +# 在中断时执行 +trap 'echo "Interrupted"; cleanup' INT +``` + +## 错误处理模式 + +### 1. 检查命令退出码 + +```bash +# 检查上一个命令是否成功 +if [ $? -eq 0 ]; then + echo "Success" +else + echo "Failed" +fi + +# 或使用 || +command || { echo "Failed"; exit 1; } + +# 或使用 && +command && echo "Success" || echo "Failed" +``` + +### 2. 使用函数封装错误处理 + +```bash +# 定义错误处理函数 +die() { + local message=$1 + echo "Error: $message" >&2 + exit 1 +} + +# 使用 +[ -f "$file" ] || die "File not found: $file" +``` + +### 3. 验证输入参数 + +```bash +#!/bin/bash +# 检查参数数量 +[ $# -ge 1 ] || die "Usage: $0 [arg2]" + +# 检查文件存在 +[ -f "$1" ] || die "File not found: $1" + +# 检查目录存在 +[ -d "$2" ] || die "Directory not found: $2" +``` + +## 最佳实践 + +### 1. 始终使用 shebang + +```bash +#!/bin/bash +# 或 +#!/usr/bin/env bash +``` + +### 2. 使用 set -euo pipefail + +```bash +#!/bin/bash +set -euo pipefail +``` + +### 3. 引用所有变量 + +```bash +# 除非确定变量不包含空格或通配符 +echo "$var" +``` + +### 4. 使用 [[ ]] 而不是 [ ] + +```bash +# [[ 更强大且更安全 +if [[ $name == "John" ]]; then +if [[ -f $file && $size -gt 100 ]]; then +``` + +### 5. 使用 $(command) 而不是反引号 + +```bash +# $() 更易读且可嵌套 +result=$(command1 $(command2)) +``` + +### 6. 使用函数组织代码 + +```bash +my_function() { + local arg1=$1 + local arg2=$2 + # 函数体 +} + +my_function "value1" "value2" +``` + +## ShellCheck 静态分析 + +ShellCheck 是一个 Shell 脚本静态分析工具： + +```bash +# 安装 ShellCheck +brew install shellcheck # macOS +apt install shellcheck # Ubuntu + +# 使用 +shellcheck script.sh +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/SKILL.md new file mode 100644 index 0000000..04b91fc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/SKILL.md @@ -0,0 +1,204 @@ +--- +name: citation-verification +description: This skill provides reference guidance for citation verification in academic writing. Use when the user asks about "citation verification best practices", "how to verify references", "preventing fake citations", or needs guidance on citation accuracy. This skill supports ml-paper-writing by providing detailed verification principles and common error patterns. +tags: [Research, Academic, Citation, Reference] +version: 0.1.0 +--- + +# Citation Verification Reference Guide + +A reference guide for citation verification in academic paper writing, providing verification principles and best practices. + +**Core Principle**: Proactively verify every citation during the writing process using programmatic or canonical scholarly sources first: arXiv, DOI/CrossRef, Semantic Scholar, publisher landing pages, and Zotero metadata. Google Scholar is useful for manual discovery, but it is not the canonical verification authority. + +## Core Problems + +Citation issues in academic papers seriously impact research integrity: + +1. **Fake citations** - Citing non-existent papers (common issue with AI-generated citations) +2. **Incorrect information** - Mismatched authors, titles, years, etc. +3. **Inconsistent formatting** - Mixed citation formats +4. **Missing citations** - Referenced but uncited work + +These issues can lead to: +- Paper rejection or retraction +- Damage to academic reputation +- Reviewers questioning research rigor + +**Special risk with AI-assisted writing**: AI-generated citations have approximately 40% error rate; every citation must be verified via WebSearch. + +## Verification Principles + +This skill provides verification principles based on canonical scholarly metadata and claim-level checking: + +### 1. Proactive Verification (Verify During Writing) + +**Core idea**: Verify immediately when adding a citation, rather than checking after writing is complete. + +- Search for the paper via WebSearch each time a citation is needed +- Confirm the paper exists on Google Scholar +- Add to bibliography only after verification passes + +### 2. Canonical Metadata Verification + +Preferred authority order: +1. DOI / publisher landing page +2. arXiv ID or arXiv landing page +3. CrossRef +4. Semantic Scholar +5. Zotero metadata imported from a verified identifier +6. Google Scholar only for manual discovery or fallback lookup + +**Verification steps**: +1. Find a DOI, arXiv ID, publisher URL, or verified Zotero item. +2. Confirm title, first author, year, venue, and identifier. +3. Fetch BibTeX from CrossRef, arXiv, publisher metadata, Zotero, or another programmatic source when possible. +4. If only Google Scholar can find the item, mark it as manual verification and do not treat the BibTeX as final until metadata is checked elsewhere. + +### 3. Information Matching Verification + +**Information that must match**: +- Title (minor differences allowed, e.g., capitalization) +- Authors (at least the first author must match) +- Year (±1 year difference allowed, considering preprints) +- Publication venue (conference/journal name) + +### 4. Claim Verification + +**Key principle**: When citing a specific claim, you must confirm the claim actually appears in the paper. + +- Use WebSearch to access the paper PDF +- Search for relevant keywords +- Confirm the accuracy of the claim +- Record the section/page where the claim appears + +## Verification Workflow + +### Integration into Writing Process + +``` +Need a citation during writing + ↓ +Find DOI / arXiv ID / publisher page / verified Zotero item + ↓ +Verify metadata with CrossRef / arXiv / Semantic Scholar / publisher / Zotero + ↓ +Confirm paper details + ↓ +Get BibTeX + ↓ +(If citing a specific claim) Verify the claim + ↓ +Add to bibliography +``` + +**Key point**: Verification is part of the writing process, not a separate post-processing step. + +## Usage Guide + +### Using with ml-paper-writing + +The verification principles of this skill are integrated into the Citation Workflow of the `ml-paper-writing` skill. + +**Auto-trigger**: Citation verification is automatically executed when writing papers with the ml-paper-writing skill. + +**Manual reference**: Refer to this skill when you need detailed verification principles. + +### Verification Step Example + +**Scenario**: Need to cite the Transformer paper + +``` +Step 1: WebSearch lookup +Query: "Attention is All You Need Vaswani 2017" +Result: Found multiple sources for the paper + +Step 2: Google Scholar verification +Query: "site:scholar.google.com Attention is All You Need Vaswani" +Result: ✅ Paper exists, 50,000+ citations, NeurIPS 2017 + +Step 3: Confirm details +- Title: "Attention is All You Need" +- Authors: Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; ... +- Year: 2017 +- Venue: NeurIPS (NIPS) + +Step 4: Get BibTeX +- Click "Cite" on Google Scholar +- Select BibTeX format +- Copy BibTeX entry + +Step 5: Add to bibliography +- Paste into .bib file +- Use \cite{vaswani2017attention} in the paper +``` + +### Handling Verification Failures + +**If the paper cannot be verified through canonical sources**: + +1. **Check spelling** - Is the title or author name correct? +2. **Try different queries** - Use different keyword combinations +3. **Find alternative sources** - Try arXiv, DOI, CrossRef, Semantic Scholar, publisher pages, or Zotero +4. **Mark as pending** - Use `[CITATION NEEDED]` marker +5. **Notify the user** - Clearly state the citation cannot be verified + +**If information doesn't match**: + +1. **Confirm the source** - Did you find the correct paper? +2. **Check versions** - Preprint vs. published version +3. **Update information** - Use the most accurate version +4. **Record discrepancies** - Note the reason for differences + +## Best Practices + +### Preventing Fake Citations + +1. **Never generate citations from memory** - AI-generated citations have 40% error rate +2. **Use WebSearch to find** - Verify every citation through WebSearch +3. **Confirm on Google Scholar** - Verify paper existence on Google Scholar +4. **Verify promptly** - Verify when adding citations, don't wait until finished + +### Handling Verification Failures + +1. **Don't guess** - If you can't find the paper, don't fabricate information +2. **Mark clearly** - Use `[CITATION NEEDED]` to mark explicitly +3. **Notify the user** - Clearly state which citations cannot be verified +4. **Provide reasons** - Explain why verification failed (not found, info mismatch, etc.) + +### Improving Verification Accuracy + +1. **Complete queries** - Include title, author, year +2. **Check citation count** - Citation count on Google Scholar is a credibility indicator +3. **Confirm venue** - Verify conference/journal name is correct +4. **Verify claims** - When citing specific claims, confirm they exist in the paper + +### Common Pitfalls + +❌ **Wrong approach**: +- Generating BibTeX from memory +- Skipping Google Scholar verification +- Assuming a paper exists +- Not marking unverifiable citations + +✅ **Correct approach**: +- Search every citation with WebSearch +- Confirm on Google Scholar +- Copy BibTeX from Google Scholar +- Clearly mark unverifiable citations + +## Summary + +**Core Principle**: Proactively verify every citation during the writing process using WebSearch and Google Scholar. + +**Key Steps**: +1. WebSearch to find the paper +2. Google Scholar to verify existence +3. Confirm details +4. Get BibTeX +5. Verify claims (if needed) +6. Add to bibliography + +**Failure handling**: When verification fails, mark as `[CITATION NEEDED]` and clearly notify the user. + +**Integration**: The principles of this skill are integrated into the ml-paper-writing skill for automatic verification. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/README.md b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/README.md new file mode 100644 index 0000000..97f3c29 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/README.md @@ -0,0 +1,72 @@ +# Citation Verification Reference Files + +## 文件用途 + +本目录中的文件提供**背景知识和参考信息**，用于理解引用验证的原理和常见问题。 + +**重要**: 这些文件不是主要工作流的一部分。实际的引用验证优先使用 arXiv、DOI/CrossRef、Semantic Scholar、publisher metadata 和 Zotero metadata。Google Scholar 只能作为人工发现或 fallback。 + +## 文件说明 + +### common-errors.md + +**内容**: 常见引用错误模式和修复方法 + +**用途**: +- 了解学术写作中常见的引用错误 +- 学习如何识别和修复这些错误 +- 理解为什么需要验证引用 + +**何时参考**: 当需要了解引用错误的类型和修复方法时 + +### verification-rules.md + +**内容**: 详细的验证规则和匹配算法 + +**用途**: +- 理解引用验证的完整逻辑 +- 了解如何匹配标题、作者、年份等信息 +- 学习验证的技术细节 + +**何时参考**: 当需要深入了解验证逻辑时 + +### api-usage.md + +**内容**: API 使用指南（CrossRef、arXiv、Semantic Scholar） + +**用途**: +- 了解学术API的使用方法 +- 理解API验证的原理 +- 参考高级用例的实现 + +**何时参考**: 当需要了解API验证方法时。当前主要工作流应优先使用这些 programmatic / canonical sources。 + +## 主要工作流 + +**实际的引用验证应该使用 `ml-paper-writing` skill 中的 Citation Workflow：** + +1. 查找 DOI、arXiv ID、publisher page 或 verified Zotero item +2. 用 CrossRef、arXiv、Semantic Scholar、publisher metadata 或 Zotero metadata 验证 +3. 从 programmatic/canonical source 获取 BibTeX +4. 验证声明（如需要） +5. 添加到 bibliography + +详见 `ml-paper-writing` skill 的 "Citation Workflow (Hallucination Prevention)" 部分。 + +## 使用建议 + +**对于日常论文写作**: +- ✅ 使用 `ml-paper-writing` skill 的 Citation Workflow +- ✅ 使用 arXiv、DOI/CrossRef、Semantic Scholar、publisher metadata 和 Zotero metadata +- ✅ 必要时用 Google Scholar 做人工发现，但不要把它作为 canonical authority +- ✅ 参考这些文件了解背景知识 +- ❌ 不要从记忆或未经验证的 Google Scholar 条目生成最终 BibTeX + +**对于理解验证原理**: +- 阅读 `common-errors.md` 了解常见错误 +- 阅读 `verification-rules.md` 了解验证逻辑 +- 阅读 `api-usage.md` 了解API方法（参考用） + +## 更多信息 + +详见 `citation-verification` skill 的 SKILL.md 文件。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/api-usage.md b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/api-usage.md new file mode 100644 index 0000000..395f52a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/api-usage.md @@ -0,0 +1,373 @@ +# API 使用指南 + +本文档详细说明如何使用三个主要 API 进行文献验证。 + +## Semantic Scholar API + +### 概述 + +Semantic Scholar 是一个免费的学术搜索引擎,提供强大的 API 用于论文检索和元数据获取。 + +**优势:** +- 免费使用,无需 API key +- 覆盖广泛的学科领域 +- 提供丰富的元数据 +- 支持模糊搜索 + +**限制:** +- 请求频率限制:100 requests/5min +- 部分论文可能缺失 + +### API 端点 + +**1. 通过 Paper ID 获取论文** +``` +GET https://api.semanticscholar.org/graph/v1/paper/{paper_id} +``` + +**2. 搜索论文** +``` +GET https://api.semanticscholar.org/graph/v1/paper/search?query={query} +``` + +### Python 示例 + +**安装:** +```bash +pip install semanticscholar +``` + +**基本用法:** +```python +from semanticscholar import SemanticScholar + +sch = SemanticScholar() + +# 通过标题搜索 +results = sch.search_paper("Attention is All You Need", limit=5) +for paper in results: + print(f"Title: {paper.title}") + print(f"Authors: {[a.name for a in paper.authors]}") + print(f"Year: {paper.year}") + print(f"DOI: {paper.externalIds.get('DOI', 'N/A')}") + print("---") +``` + +**通过 DOI 获取:** +```python +# DOI 格式: DOI:10.48550/arXiv.1706.03762 +paper = sch.get_paper("DOI:10.48550/arXiv.1706.03762") +print(f"Title: {paper.title}") +print(f"Citations: {paper.citationCount}") +``` + +### 字段说明 + +**返回的主要字段:** +- `paperId` - Semantic Scholar 内部 ID +- `title` - 论文标题 +- `authors` - 作者列表 +- `year` - 发表年份 +- `venue` - 发表场所(会议/期刊) +- `externalIds` - 外部标识符(DOI, arXiv, PubMed 等) +- `citationCount` - 引用次数 +- `abstract` - 摘要 + +### 错误处理 + +```python +try: + paper = sch.get_paper("invalid_id") +except Exception as e: + print(f"Error: {e}") + # 处理错误:标记需要人工验证 +``` + +## arXiv API + +### 概述 + +arXiv 是预印本论文库,提供免费的 API 用于访问论文元数据。 + +**优势:** +- 完全免费,无需认证 +- 覆盖物理、数学、计算机科学等领域 +- 提供完整的论文 PDF +- 更新及时 + +**限制:** +- 仅限预印本论文 +- 不包含已发表的期刊版本信息 + +### API 端点 + +**查询接口:** +``` +GET http://export.arxiv.org/api/query?search_query={query}&start={start}&max_results={max} +``` + +### Python 示例 + +**安装:** +```bash +pip install arxiv +``` + +**基本用法:** +```python +import arxiv + +# 通过 arXiv ID 获取 +paper = next(arxiv.Search(id_list=["1706.03762"]).results()) +print(f"Title: {paper.title}") +print(f"Authors: {[a.name for a in paper.authors]}") +print(f"Published: {paper.published}") +print(f"PDF URL: {paper.pdf_url}") + +# 通过标题搜索 +search = arxiv.Search( + query="Attention is All You Need", + max_results=5, + sort_by=arxiv.SortCriterion.Relevance +) + +for result in search.results(): + print(f"Title: {result.title}") + print(f"arXiv ID: {result.entry_id.split('/')[-1]}") + print("---") +``` + +### arXiv ID 格式 + +**识别 arXiv ID:** +- 新格式: `YYMM.NNNNN` (如 2301.12345) +- 旧格式: `arch-ive/YYMMNNN` (如 cs/0703001) + +**从 URL 提取:** +```python +import re + +def extract_arxiv_id(text): + # 匹配新格式 + match = re.search(r'\d{4}\.\d{4,5}', text) + if match: + return match.group() + # 匹配旧格式 + match = re.search(r'[a-z-]+/\d{7}', text) + if match: + return match.group() + return None +``` + +## CrossRef API + +### 概述 + +CrossRef 是 DOI 注册机构,提供权威的学术文献元数据。 + +**优势:** +- DOI 是最可靠的唯一标识符 +- 覆盖几乎所有正式发表的论文 +- 数据质量高,权威性强 +- 支持 BibTeX 格式直接获取 + +**限制:** +- 仅限有 DOI 的论文 +- 预印本通常没有 DOI + +### API 端点 + +**通过 DOI 获取元数据:** +``` +GET https://api.crossref.org/works/{doi} +``` + +**通过 DOI 获取 BibTeX:** +``` +GET https://doi.org/{doi} +Headers: Accept: application/x-bibtex +``` + +### Python 示例 + +**通过 DOI 获取元数据:** +```python +import requests + +def get_crossref_metadata(doi): + url = f"https://api.crossref.org/works/{doi}" + response = requests.get(url) + if response.status_code == 200: + data = response.json() + return data['message'] + return None + +# 示例 +doi = "10.48550/arXiv.1706.03762" +metadata = get_crossref_metadata(doi) +if metadata: + print(f"Title: {metadata['title'][0]}") + print(f"Authors: {[f\"{a['given']} {a['family']}\" for a in metadata['author']]}") + print(f"Published: {metadata['published']['date-parts'][0]}") +``` + +**通过 DOI 获取 BibTeX:** +```python +def doi_to_bibtex(doi): + url = f"https://doi.org/{doi}" + headers = {"Accept": "application/x-bibtex"} + response = requests.get(url, headers=headers) + if response.status_code == 200: + return response.text + return None + +# 示例 +bibtex = doi_to_bibtex("10.48550/arXiv.1706.03762") +print(bibtex) +``` + +### DOI 格式 + +**标准格式:** +- `10.XXXX/suffix` (如 10.1038/nature12345) +- 前缀 `10.` 是固定的 +- 中间是注册机构代码 +- 后缀是出版商定义的 + +**从文本中提取 DOI:** +```python +import re + +def extract_doi(text): + # 匹配 DOI 格式 + match = re.search(r'10\.\d{4,}/[^\s]+', text) + if match: + return match.group() + return None +``` + +## API 选择策略 + +根据引用信息选择最合适的 API: + +### 决策流程 + +``` +有 DOI? + ├─ 是 → CrossRef API (最可靠) + └─ 否 → 有 arXiv ID? + ├─ 是 → arXiv API + └─ 否 → Semantic Scholar API (通用搜索) +``` + +### 实现示例 + +```python +def verify_citation(citation_info): + """ + 根据引用信息选择合适的 API 进行验证 + + Args: + citation_info: dict with keys: doi, arxiv_id, title, authors + + Returns: + 验证结果字典 + """ + # 策略 1: DOI 优先 + if citation_info.get('doi'): + return verify_with_crossref(citation_info['doi']) + + # 策略 2: arXiv ID + if citation_info.get('arxiv_id'): + return verify_with_arxiv(citation_info['arxiv_id']) + + # 策略 3: 通用搜索 + if citation_info.get('title'): + return verify_with_semantic_scholar( + citation_info['title'], + citation_info.get('authors') + ) + + return {'status': 'insufficient_info'} +``` + +## 最佳实践 + +### 1. 错误处理 + +```python +import time +from requests.exceptions import RequestException + +def api_call_with_retry(func, max_retries=3): + """带重试的 API 调用""" + for i in range(max_retries): + try: + return func() + except RequestException as e: + if i == max_retries - 1: + raise + time.sleep(2 ** i) # 指数退避 +``` + +### 2. 速率限制 + +```python +import time + +class RateLimiter: + def __init__(self, calls_per_minute): + self.calls_per_minute = calls_per_minute + self.last_call = 0 + + def wait_if_needed(self): + elapsed = time.time() - self.last_call + min_interval = 60.0 / self.calls_per_minute + if elapsed < min_interval: + time.sleep(min_interval - elapsed) + self.last_call = time.time() + +# 使用示例 +limiter = RateLimiter(calls_per_minute=20) +limiter.wait_if_needed() +result = api_call() +``` + +### 3. 缓存结果 + +```python +import json +from pathlib import Path + +class APICache: + def __init__(self, cache_dir=".cache"): + self.cache_dir = Path(cache_dir) + self.cache_dir.mkdir(exist_ok=True) + + def get(self, key): + cache_file = self.cache_dir / f"{key}.json" + if cache_file.exists(): + return json.loads(cache_file.read_text()) + return None + + def set(self, key, value): + cache_file = self.cache_dir / f"{key}.json" + cache_file.write_text(json.dumps(value)) +``` + +## 总结 + +### API 对比 + +| API | 优势 | 限制 | 推荐场景 | +|-----|------|------|----------| +| **CrossRef** | 最权威,支持 BibTeX | 仅限有 DOI 的论文 | 有 DOI 时首选 | +| **arXiv** | 免费,更新快 | 仅限预印本 | arXiv 论文 | +| **Semantic Scholar** | 覆盖广,模糊搜索 | 部分论文缺失 | 通用搜索 | + +### 验证可靠性排序 + +1. **CrossRef (DOI)** - 最可靠 +2. **arXiv (arXiv ID)** - 可靠 +3. **Semantic Scholar (标题搜索)** - 较可靠,需要人工确认 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/common-errors.md b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/common-errors.md new file mode 100644 index 0000000..911bb8a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/common-errors.md @@ -0,0 +1,385 @@ +# 常见引用错误模式 + +本文档总结常见的引用错误类型、识别方法和修复建议。 + +## 错误分类 + +### 1. 格式错误 (Format Errors) + +#### 1.1 缺少必填字段 + +**错误示例:** +```bibtex +@article{smith2020, + title={Deep Learning for NLP}, + year={2020} +} +``` + +**问题:** 缺少 `author` 和 `journal` 字段 + +**修复:** +```bibtex +@article{smith2020, + author={Smith, John and Doe, Jane}, + title={Deep Learning for NLP}, + journal={Nature}, + year={2020} +} +``` + +#### 1.2 年份格式错误 + +**错误示例:** +```bibtex +year={20} # 年份不完整 +year={2020-2021} # 年份范围格式错误 +year={circa 2020} # 包含非数字字符 +``` + +**修复:** +```bibtex +year={2020} # 使用四位数年份 +``` + +#### 1.3 DOI 格式错误 + +**错误示例:** +```bibtex +doi={doi:10.1038/nature12345} # 包含 "doi:" 前缀 +doi={https://doi.org/10.1038/...} # 包含完整 URL +doi={10.1038/nature12345.} # 末尾有句号 +``` + +**修复:** +```bibtex +doi={10.1038/nature12345} # 只保留 DOI 本身 +``` + +#### 1.4 作者名格式不一致 + +**错误示例:** +```bibtex +author={John Smith and Jane Doe and Bob} # 格式不一致 +author={Smith, J. and Doe, Jane} # 格式混用 +``` + +**修复:** +```bibtex +author={Smith, John and Doe, Jane and Brown, Bob} # 统一格式 +# 或 +author={Smith, J. and Doe, J. and Brown, B.} # 统一缩写 +``` + +### 2. 信息错误 (Information Errors) + +#### 2.1 作者名拼写错误 + +**错误示例:** +```bibtex +author={Vaswani, Ashish} # 正确 +author={Vaswani, Asish} # 拼写错误 +``` + +**识别方法:** +- API 验证时作者匹配度低 +- 通过 Google Scholar 搜索确认正确拼写 + +**修复建议:** +- 从可靠来源(Google Scholar, Semantic Scholar)获取 BibTeX +- 仔细核对作者名拼写 + +#### 2.2 标题错误 + +**错误示例:** +```bibtex +title={Attention is All You Need} # 正确 +title={Attention Is All You Need} # 大小写错误 +title={Attention is all you need} # 大小写错误 +title={Attention Mechanism for Transformers} # 标题完全错误 +``` + +**识别方法:** +- 标题匹配度低于阈值 +- API 返回的标题与 BibTeX 中的标题不一致 + +**修复建议:** +- 从原始论文或 DOI 获取准确标题 +- 保持原始大小写格式 + +#### 2.3 年份错误 + +**常见情况:** +- 使用预印本年份而非正式发表年份 +- 使用会议年份而非论文集出版年份 + +**错误示例:** +```bibtex +# 论文在 2017 年 arXiv 发布,2018 年 NIPS 正式发表 +year={2017} # 使用了预印本年份 +year={2018} # 正确:使用正式发表年份 +``` + +**修复建议:** +- 优先使用正式发表年份 +- 如果引用预印本,在 note 字段说明 + +#### 2.4 期刊/会议名称错误 + +**错误示例:** +```bibtex +booktitle={NeurIPS} # 缩写 +booktitle={Neural Information Processing Systems} # 完整名称 +booktitle={Advances in Neural Information Processing Systems} # 正确的完整名称 +``` + +**修复建议:** +- 使用官方全称或标准缩写 +- 保持整个文献列表的命名一致性 + +### 3. 虚假引用 (Fake Citations) + +#### 3.1 完全虚构的论文 + +**特征:** +- 论文不存在于任何数据库 +- API 验证全部失败 +- 无法通过 Google Scholar 找到 + +**识别方法:** +```python +# 所有 API 都返回 not_found +if not crossref_found and not arxiv_found and not semantic_scholar_found: + return "可能是虚假引用" +``` + +**修复建议:** +- 删除虚假引用 +- 如果确实需要引用,寻找真实的相关论文 + +#### 3.2 信息严重错误的引用 + +**特征:** +- 论文存在,但信息完全不匹配 +- 作者、标题、年份都不对 +- 可能是复制粘贴错误 + +**错误示例:** +```bibtex +@article{smith2020deep, + author={Smith, John}, + title={Deep Learning for NLP}, + journal={Nature}, + year={2020} +} +``` + +**实际论文:** +- 作者: Brown, Tom et al. +- 标题: Language Models are Few-Shot Learners +- 期刊: NeurIPS +- 年份: 2020 + +**修复建议:** +- 重新搜索正确的论文 +- 从可靠来源获取正确的 BibTeX + +#### 3.3 引用不存在的版本 + +**错误示例:** +```bibtex +# 引用了不存在的期刊版本 +@article{vaswani2017attention, + author={Vaswani, Ashish and others}, + title={Attention is All You Need}, + journal={Nature Machine Intelligence}, # 错误:这篇论文没有期刊版本 + year={2017} +} +``` + +**正确引用:** +```bibtex +@inproceedings{vaswani2017attention, + author={Vaswani, Ashish and others}, + title={Attention is All You Need}, + booktitle={Advances in Neural Information Processing Systems}, + year={2017} +} +``` + +### 4. 一致性错误 (Consistency Errors) + +#### 4.1 LaTeX 引用与 BibTeX 不一致 + +**错误示例:** + +LaTeX 文件中: +```latex +\cite{smith2020deep} +``` + +BibTeX 文件中: +```bibtex +@article{smith2020deeplearning, # Key 不匹配 + author={Smith, John}, + title={Deep Learning for NLP}, + year={2020} +} +``` + +**识别方法:** +```python +def check_citation_consistency(tex_keys, bib_keys): + """检查引用一致性""" + tex_set = set(tex_keys) + bib_set = set(bib_keys) + + # 未定义的引用 + undefined = tex_set - bib_set + + # 未使用的引用 + unused = bib_set - tex_set + + return { + 'undefined': list(undefined), + 'unused': list(unused) + } +``` + +**修复建议:** +- 确保 LaTeX 中的 citation key 与 BibTeX 中的 ID 完全一致 +- 删除未使用的 BibTeX 条目 +- 补充缺失的 BibTeX 条目 + +#### 4.2 引用格式不统一 + +**错误示例:** +```bibtex +# 同一文献列表中格式混乱 +@article{paper1, + author={Smith, John and Doe, Jane}, # 全名 + ... +} + +@article{paper2, + author={Brown, T. and Lee, S.}, # 缩写 + ... +} + +@article{paper3, + author={John Wilson and Mary Johnson}, # First Last 格式 + ... +} +``` + +**修复建议:** +- 统一作者名格式(全名或缩写) +- 统一期刊/会议名称格式(全称或标准缩写) +- 统一页码格式(1-10 或 1--10) + +#### 4.3 重复引用 + +**错误示例:** +```bibtex +@article{vaswani2017, + author={Vaswani, Ashish and others}, + title={Attention is All You Need}, + booktitle={NeurIPS}, + year={2017} +} + +@inproceedings{vaswani2017attention, + author={Vaswani, A. and others}, + title={Attention is All You Need}, + booktitle={Advances in Neural Information Processing Systems}, + year={2017} +} +``` + +**问题:** 同一篇论文被引用两次,使用不同的 citation key + +**识别方法:** +- 标题高度相似(相似度 > 0.9) +- 作者重叠度高 +- 年份相同 + +**修复建议:** +- 保留更完整准确的条目 +- 删除重复条目 +- 更新 LaTeX 文件中的引用 + +## 错误预防最佳实践 + +### 1. 使用可靠来源 + +✅ **推荐来源:** +- Google Scholar - 获取 BibTeX +- Semantic Scholar - 验证论文信息 +- 官方出版商网站 - 获取准确元数据 +- DOI 系统 - 最可靠的标识符 + +❌ **避免:** +- 手动输入 BibTeX +- 从不可靠网站复制 +- 使用过时的引用管理工具 + +### 2. 及时验证 + +**验证时机:** +- 添加引用后立即验证 +- 完成初稿后全面验证 +- 提交前最终验证 + +**验证内容:** +- 格式完整性 +- 信息准确性 +- 引用一致性 + +### 3. 保持一致性 + +**统一标准:** +- 作者名格式统一(全名或缩写) +- 期刊/会议名称统一(全称或标准缩写) +- 页码格式统一 +- 大小写规则统一 + +### 4. 使用工具辅助 + +**推荐工具:** +- BibTeX 格式检查器 +- LaTeX 编译器(检测未定义引用) +- Citation verification scripts +- 引用管理软件(Zotero, Mendeley) + +## 常见错误总结 + +| 错误类型 | 严重程度 | 检测难度 | 修复难度 | +|---------|---------|---------|---------| +| 缺少必填字段 | 高 | 低 | 低 | +| 年份格式错误 | 中 | 低 | 低 | +| DOI 格式错误 | 中 | 低 | 低 | +| 作者名拼写错误 | 高 | 中 | 中 | +| 标题错误 | 高 | 中 | 中 | +| 完全虚构论文 | 极高 | 高 | 高 | +| 信息严重错误 | 极高 | 中 | 高 | +| LaTeX-BibTeX 不一致 | 高 | 低 | 低 | +| 格式不统一 | 低 | 低 | 中 | +| 重复引用 | 中 | 中 | 中 | + +## 快速检查清单 + +提交论文前,确保完成以下检查: + +- [ ] 所有 BibTeX 条目包含必填字段 +- [ ] 年份格式正确(四位数字) +- [ ] DOI 格式正确(无前缀,无 URL) +- [ ] 作者名格式统一 +- [ ] 标题大小写正确 +- [ ] 所有引用通过 API 验证 +- [ ] LaTeX 引用与 BibTeX 一致 +- [ ] 无重复引用 +- [ ] 格式统一(作者名、期刊名、页码) +- [ ] 无虚假或严重错误的引用 + +遵循这些最佳实践可以有效避免常见的引用错误,提高论文质量和可信度。 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/verification-rules.md b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/verification-rules.md new file mode 100644 index 0000000..03d8a35 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/references/verification-rules.md @@ -0,0 +1,400 @@ +# 验证规则 + +本文档详细说明四层验证机制的具体规则和匹配算法。 + +## Layer 1: Format Validation (格式验证) + +### BibTeX 格式检查 + +**必填字段验证:** + +不同类型的 BibTeX 条目有不同的必填字段要求: + +**@article (期刊论文):** +- 必填: `author`, `title`, `journal`, `year` +- 可选: `volume`, `number`, `pages`, `doi` + +**@inproceedings (会议论文):** +- 必填: `author`, `title`, `booktitle`, `year` +- 可选: `pages`, `organization`, `doi` + +**@book (书籍):** +- 必填: `author` 或 `editor`, `title`, `publisher`, `year` +- 可选: `volume`, `series`, `address` + +**@misc (其他):** +- 必填: `title` +- 可选: `author`, `howpublished`, `year`, `note` + +### 格式检查规则 + +**1. 条目结构检查** +```python +def check_bibtex_structure(entry): + """检查 BibTeX 条目结构""" + errors = [] + + # 检查是否有类型 + if not entry.get('ENTRYTYPE'): + errors.append("Missing entry type") + + # 检查是否有 ID + if not entry.get('ID'): + errors.append("Missing citation key") + + # 检查必填字段 + required = get_required_fields(entry.get('ENTRYTYPE')) + for field in required: + if not entry.get(field): + errors.append(f"Missing required field: {field}") + + return errors +``` + +**2. 字段格式检查** +```python +def check_field_format(entry): + """检查字段格式""" + errors = [] + + # 年份格式检查 + if 'year' in entry: + year = entry['year'] + if not year.isdigit() or len(year) != 4: + errors.append(f"Invalid year format: {year}") + if int(year) < 1900 or int(year) > 2030: + errors.append(f"Year out of reasonable range: {year}") + + # DOI 格式检查 + if 'doi' in entry: + doi = entry['doi'] + if not doi.startswith('10.'): + errors.append(f"Invalid DOI format: {doi}") + + return errors +``` + +### LaTeX 引用检查 + +**1. 引用命令检查** +```python +def check_latex_citations(tex_content): + """检查 LaTeX 引用命令""" + import re + + # 查找所有引用命令 + cite_pattern = r'\\cite(?:\[[^\]]*\])?\{([^}]+)\}' + citations = re.findall(cite_pattern, tex_content) + + # 展开多个引用 + all_keys = [] + for cite in citations: + keys = [k.strip() for k in cite.split(',')] + all_keys.extend(keys) + + return all_keys +``` + +**2. 引用一致性检查** +```python +def check_citation_consistency(tex_keys, bib_keys): + """检查引用一致性""" + tex_set = set(tex_keys) + bib_set = set(bib_keys) + + # 未定义的引用 + undefined = tex_set - bib_set + + # 未使用的引用 + unused = bib_set - tex_set + + return { + 'undefined': list(undefined), + 'unused': list(unused) + } +``` + +## Layer 2: Existence Verification (存在性验证) + +### API 验证流程 + +**验证步骤:** +1. 根据引用信息选择 API (DOI → CrossRef, arXiv ID → arXiv, 其他 → Semantic Scholar) +2. 调用 API 获取论文信息 +3. 判断论文是否存在 + +**验证结果:** +- `exists` - 论文存在 +- `not_found` - 论文不存在 +- `api_error` - API 调用失败,需要人工验证 + +### 验证代码示例 + +```python +def verify_existence(citation_info): + """验证论文存在性""" + # DOI 优先 + if citation_info.get('doi'): + result = verify_with_crossref(citation_info['doi']) + if result['status'] == 'success': + return {'exists': True, 'source': 'crossref', 'data': result['data']} + + # arXiv ID + if citation_info.get('arxiv_id'): + result = verify_with_arxiv(citation_info['arxiv_id']) + if result['status'] == 'success': + return {'exists': True, 'source': 'arxiv', 'data': result['data']} + + # 通用搜索 + if citation_info.get('title'): + result = verify_with_semantic_scholar(citation_info['title']) + if result['status'] == 'success' and result['data']: + return {'exists': True, 'source': 'semantic_scholar', 'data': result['data']} + + return {'exists': False, 'source': None} +``` + +## Layer 3: Information Matching (信息匹配) + +### 匹配算法 + +**1. 标题匹配** + +使用模糊匹配算法,允许轻微差异: + +```python +from difflib import SequenceMatcher + +def match_title(title1, title2, threshold=0.85): + """标题匹配""" + # 标准化:小写、去除标点 + def normalize(text): + import re + text = text.lower() + text = re.sub(r'[^\w\s]', '', text) + return ' '.join(text.split()) + + t1 = normalize(title1) + t2 = normalize(title2) + + # 计算相似度 + ratio = SequenceMatcher(None, t1, t2).ratio() + + return { + 'match': ratio >= threshold, + 'similarity': ratio + } +``` + +**2. 作者匹配** + +考虑作者顺序和名字格式差异: + +```python +def match_authors(authors1, authors2, threshold=0.7): + """作者匹配""" + def normalize_name(name): + # 处理 "Last, First" 和 "First Last" 格式 + parts = name.replace(',', '').split() + return ' '.join(sorted(parts)).lower() + + names1 = [normalize_name(a) for a in authors1] + names2 = [normalize_name(a) for a in authors2] + + # 计算交集比例 + set1 = set(names1) + set2 = set(names2) + intersection = len(set1 & set2) + union = len(set1 | set2) + + if union == 0: + return {'match': False, 'similarity': 0} + + ratio = intersection / union + + return { + 'match': ratio >= threshold, + 'similarity': ratio + } +``` + +**3. 年份匹配** + +允许 ±1 年的差异(考虑预印本和正式发表的时间差): + +```python +def match_year(year1, year2, tolerance=1): + """年份匹配""" + try: + y1 = int(year1) + y2 = int(year2) + diff = abs(y1 - y2) + return { + 'match': diff <= tolerance, + 'difference': diff + } + except (ValueError, TypeError): + return {'match': False, 'difference': None} +``` + +## Layer 4: Content Validation (内容验证) + +### 综合匹配评分 + +综合所有匹配结果,计算总体匹配分数: + +```python +def calculate_match_score(citation, api_data): + """计算综合匹配分数""" + scores = {} + weights = { + 'title': 0.4, + 'authors': 0.3, + 'year': 0.2, + 'venue': 0.1 + } + + # 标题匹配 + if citation.get('title') and api_data.get('title'): + result = match_title(citation['title'], api_data['title']) + scores['title'] = result['similarity'] + + # 作者匹配 + if citation.get('authors') and api_data.get('authors'): + result = match_authors(citation['authors'], api_data['authors']) + scores['authors'] = result['similarity'] + + # 年份匹配 + if citation.get('year') and api_data.get('year'): + result = match_year(citation['year'], api_data['year']) + scores['year'] = 1.0 if result['match'] else 0.0 + + # 计算加权总分 + total_score = 0 + total_weight = 0 + for key, weight in weights.items(): + if key in scores: + total_score += scores[key] * weight + total_weight += weight + + if total_weight == 0: + return 0 + + return total_score / total_weight +``` + +### 验证结果判定 + +根据匹配分数判定验证结果: + +```python +def judge_verification_result(match_score): + """判定验证结果""" + if match_score >= 0.9: + return { + 'status': 'verified', + 'level': 'high_confidence', + 'message': '✅ 验证通过 - 信息完全匹配' + } + elif match_score >= 0.7: + return { + 'status': 'partial_match', + 'level': 'medium_confidence', + 'message': '⚠️ 部分匹配 - 信息有轻微差异,建议人工确认' + } + elif match_score >= 0.5: + return { + 'status': 'low_match', + 'level': 'low_confidence', + 'message': '❌ 匹配度低 - 信息差异较大,需要人工验证' + } + else: + return { + 'status': 'failed', + 'level': 'no_confidence', + 'message': '❌ 验证失败 - 信息严重不匹配或论文不存在' + } +``` + +## 完整验证流程 + +### 主验证函数 + +```python +def verify_citation_complete(citation): + """完整的引用验证流程""" + result = { + 'citation_key': citation.get('ID'), + 'layers': {} + } + + # Layer 1: 格式验证 + format_errors = check_bibtex_structure(citation) + format_errors.extend(check_field_format(citation)) + result['layers']['format'] = { + 'passed': len(format_errors) == 0, + 'errors': format_errors + } + + # Layer 2: 存在性验证 + existence = verify_existence(citation) + result['layers']['existence'] = existence + + if not existence['exists']: + result['final_status'] = 'not_found' + return result + + # Layer 3 & 4: 信息匹配和内容验证 + api_data = existence['data'] + match_score = calculate_match_score(citation, api_data) + judgment = judge_verification_result(match_score) + + result['layers']['matching'] = { + 'score': match_score, + 'judgment': judgment + } + + result['final_status'] = judgment['status'] + result['confidence'] = judgment['level'] + + return result +``` + +## 验证阈值配置 + +### 可调整的阈值参数 + +```python +VERIFICATION_THRESHOLDS = { + # 匹配阈值 + 'title_similarity': 0.85, # 标题相似度阈值 + 'author_similarity': 0.70, # 作者相似度阈值 + 'year_tolerance': 1, # 年份容差 + + # 判定阈值 + 'high_confidence': 0.90, # 高置信度阈值 + 'medium_confidence': 0.70, # 中等置信度阈值 + 'low_confidence': 0.50, # 低置信度阈值 + + # 权重配置 + 'weights': { + 'title': 0.4, + 'authors': 0.3, + 'year': 0.2, + 'venue': 0.1 + } +} +``` + +### 阈值调整建议 + +**严格模式** (用于正式发表): +- title_similarity: 0.90 +- author_similarity: 0.80 +- high_confidence: 0.95 + +**宽松模式** (用于初稿): +- title_similarity: 0.80 +- author_similarity: 0.60 +- high_confidence: 0.85 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/README.md b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/README.md new file mode 100644 index 0000000..5f1bd38 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/README.md @@ -0,0 +1,81 @@ +# Citation Verification Scripts + +## 状态说明 + +**这些脚本是参考实现，不是主要工作流的一部分。** + +本目录中的Python脚本提供了基于API的引用验证实现，但**实际的引用验证工作流使用WebSearch和Google Scholar**，而不是这些脚本。 + +## 为什么保留这些脚本？ + +这些脚本作为**参考实现**保留，用于： + +1. **理解验证逻辑** - 展示引用验证的完整逻辑和步骤 +2. **学习API使用** - 了解如何使用CrossRef、arXiv、Semantic Scholar等API +3. **高级用例** - 对于需要批量验证或自动化的场景，可以参考这些实现 + +## 主要工作流 + +**实际的引用验证应该使用 `ml-paper-writing` skill 中的 Citation Workflow：** + +1. 使用 WebSearch 查找论文 +2. 在 Google Scholar 上验证 +3. 从 Google Scholar 获取 BibTeX +4. 验证声明（如需要） +5. 添加到 bibliography + +详见 `ml-paper-writing` skill 的 "Citation Workflow (Hallucination Prevention)" 部分。 + +## 脚本说明 + +### verify-citations.py + +完整的引用验证脚本，包含： +- 四层验证机制（格式、存在性、信息匹配、内容验证） +- 多API支持（CrossRef、arXiv、Semantic Scholar） +- 报告生成 + +**用途**: 参考实现，了解完整的验证逻辑 + +### api-clients.py + +API客户端库，包含： +- CrossRefClient - DOI验证 +- ArXivClient - arXiv论文验证 +- SemanticScholarClient - 通用学术搜索 +- CitationAPIManager - 统一API管理 + +**用途**: 参考实现，了解如何使用学术API + +### format-checker.py + +BibTeX和LaTeX格式检查工具，包含： +- BibTeX格式验证 +- LaTeX引用检查 +- 格式错误报告 + +**用途**: 参考实现，了解格式检查逻辑 + +## 使用建议 + +**对于日常论文写作**: +- ✅ 使用 `ml-paper-writing` skill 的 Citation Workflow +- ✅ 使用 WebSearch 和 Google Scholar +- ❌ 不要使用这些Python脚本 + +**对于批量验证或自动化**: +- 可以参考这些脚本的实现 +- 根据需要修改和使用 +- 注意API速率限制 + +## 依赖安装 + +如果需要运行这些脚本（仅用于参考或高级用例）： + +```bash +pip install bibtexparser requests semanticscholar arxiv +``` + +## 更多信息 + +详见 `citation-verification` skill 的 SKILL.md 文件。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/api-clients.py b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/api-clients.py new file mode 100644 index 0000000..6528ad6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/api-clients.py @@ -0,0 +1,542 @@ +#!/usr/bin/env python3 +""" +API Clients for Citation Verification + +提供三个主要 API 客户端: +1. CrossRefClient - DOI 验证 +2. ArXivClient - arXiv 论文验证 +3. SemanticScholarClient - 通用学术搜索 + +每个客户端都包含: +- 错误处理 +- 重试机制 +- 速率限制 +- 结果标准化 +""" + +import time +import requests +from typing import Dict, List, Optional +from abc import ABC, abstractmethod + + +class RateLimiter: + """速率限制器""" + + def __init__(self, calls_per_minute: int): + self.calls_per_minute = calls_per_minute + self.last_call = 0 + self.min_interval = 60.0 / calls_per_minute + + def wait_if_needed(self): + """如果需要,等待以满足速率限制""" + elapsed = time.time() - self.last_call + if elapsed < self.min_interval: + time.sleep(self.min_interval - elapsed) + self.last_call = time.time() + + +class APIClient(ABC): + """API 客户端基类""" + + def __init__(self, rate_limit: int = 20): + """ + Args: + rate_limit: 每分钟最大请求数 + """ + self.rate_limiter = RateLimiter(rate_limit) + + @abstractmethod + def search(self, **kwargs) -> Optional[Dict]: + """搜索论文""" + pass + + def _retry_request(self, func, max_retries: int = 3): + """带重试的请求""" + for i in range(max_retries): + try: + self.rate_limiter.wait_if_needed() + return func() + except requests.exceptions.RequestException as e: + if i == max_retries - 1: + raise + time.sleep(2 ** i) # 指数退避 + return None + + +class CrossRefClient(APIClient): + """CrossRef API 客户端 + + 用于通过 DOI 验证论文信息 + + API 文档: https://api.crossref.org/ + """ + + def __init__(self, rate_limit: int = 50): + """ + Args: + rate_limit: 每分钟最大请求数 (CrossRef 限制较宽松) + """ + super().__init__(rate_limit) + self.base_url = "https://api.crossref.org" + + def search_by_doi(self, doi: str) -> Optional[Dict]: + """通过 DOI 搜索论文 + + Args: + doi: DOI 标识符 (如 10.1038/nature12345) + + Returns: + 标准化的论文信息字典,如果未找到则返回 None + """ + def request(): + url = f"{self.base_url}/works/{doi}" + response = requests.get(url, timeout=10) + response.raise_for_status() + return response.json() + + try: + data = self._retry_request(request) + if data and 'message' in data: + return self._normalize_result(data['message']) + return None + except Exception as e: + print(f"CrossRef API 错误: {e}") + return None + + def search(self, doi: str = None, **kwargs) -> Optional[Dict]: + """搜索论文 (统一接口)""" + if doi: + return self.search_by_doi(doi) + return None + + def _normalize_result(self, data: Dict) -> Dict: + """标准化 CrossRef 返回结果""" + # 提取标题 + title = data.get('title', [''])[0] if 'title' in data else '' + + # 提取作者 + authors = [] + if 'author' in data: + for author in data['author']: + given = author.get('given', '') + family = author.get('family', '') + if given and family: + authors.append(f"{given} {family}") + elif family: + authors.append(family) + + # 提取年份 + year = None + if 'published' in data: + date_parts = data['published'].get('date-parts', [[]])[0] + if date_parts: + year = date_parts[0] + elif 'created' in data: + date_parts = data['created'].get('date-parts', [[]])[0] + if date_parts: + year = date_parts[0] + + # 提取期刊/会议名称 + venue = '' + if 'container-title' in data: + venue = data['container-title'][0] if data['container-title'] else '' + + return { + 'title': title, + 'authors': authors, + 'year': year, + 'venue': venue, + 'doi': data.get('DOI', ''), + 'type': data.get('type', ''), + 'source': 'crossref' + } + + def get_bibtex(self, doi: str) -> Optional[str]: + """通过 DOI 获取 BibTeX + + Args: + doi: DOI 标识符 + + Returns: + BibTeX 字符串,如果失败则返回 None + """ + def request(): + url = f"https://doi.org/{doi}" + headers = {"Accept": "application/x-bibtex"} + response = requests.get(url, headers=headers, timeout=10) + response.raise_for_status() + return response.text + + try: + return self._retry_request(request) + except Exception as e: + print(f"获取 BibTeX 失败: {e}") + return None + + +class ArXivClient(APIClient): + """arXiv API 客户端 + + 用于验证 arXiv 预印本论文 + + API 文档: https://info.arxiv.org/help/api/ + """ + + def __init__(self, rate_limit: int = 20): + """ + Args: + rate_limit: 每分钟最大请求数 + """ + super().__init__(rate_limit) + try: + import arxiv + self.arxiv = arxiv + except ImportError: + raise ImportError("需要安装 arxiv 库: pip install arxiv") + + def search_by_id(self, arxiv_id: str) -> Optional[Dict]: + """通过 arXiv ID 搜索论文 + + Args: + arxiv_id: arXiv 标识符 (如 2301.12345 或 cs/0703001) + + Returns: + 标准化的论文信息字典,如果未找到则返回 None + """ + def request(): + search = self.arxiv.Search(id_list=[arxiv_id]) + paper = next(search.results()) + return paper + + try: + self.rate_limiter.wait_if_needed() + paper = request() + return self._normalize_result(paper) + except StopIteration: + print(f"arXiv 论文未找到: {arxiv_id}") + return None + except Exception as e: + print(f"arXiv API 错误: {e}") + return None + + def search_by_title(self, title: str, max_results: int = 5) -> Optional[Dict]: + """通过标题搜索论文 + + Args: + title: 论文标题 + max_results: 最大返回结果数 + + Returns: + 标准化的论文信息字典(第一个结果),如果未找到则返回 None + """ + def request(): + search = self.arxiv.Search( + query=f'ti:"{title}"', + max_results=max_results, + sort_by=self.arxiv.SortCriterion.Relevance + ) + results = list(search.results()) + return results[0] if results else None + + try: + self.rate_limiter.wait_if_needed() + paper = request() + if paper: + return self._normalize_result(paper) + return None + except Exception as e: + print(f"arXiv API 错误: {e}") + return None + + def search(self, arxiv_id: str = None, title: str = None, **kwargs) -> Optional[Dict]: + """搜索论文 (统一接口)""" + if arxiv_id: + return self.search_by_id(arxiv_id) + elif title: + return self.search_by_title(title) + return None + + def _normalize_result(self, paper) -> Dict: + """标准化 arXiv 返回结果""" + # 提取 arXiv ID + arxiv_id = paper.entry_id.split('/')[-1] + + return { + 'title': paper.title, + 'authors': [a.name for a in paper.authors], + 'year': paper.published.year, + 'venue': 'arXiv', + 'arxiv_id': arxiv_id, + 'doi': paper.doi if hasattr(paper, 'doi') else None, + 'abstract': paper.summary, + 'pdf_url': paper.pdf_url, + 'source': 'arxiv' + } + + @staticmethod + def extract_arxiv_id(text: str) -> Optional[str]: + """从文本中提取 arXiv ID + + Args: + text: 包含 arXiv ID 的文本 + + Returns: + arXiv ID,如果未找到则返回 None + """ + import re + + # 匹配新格式: YYMM.NNNNN + match = re.search(r'\d{4}\.\d{4,5}', text) + if match: + return match.group() + + # 匹配旧格式: arch-ive/YYMMNNN + match = re.search(r'[a-z-]+/\d{7}', text) + if match: + return match.group() + + return None + + +class SemanticScholarClient(APIClient): + """Semantic Scholar API 客户端 + + 用于通用学术论文搜索和验证 + + API 文档: https://api.semanticscholar.org/api-docs/ + """ + + def __init__(self, rate_limit: int = 20): + """ + Args: + rate_limit: 每分钟最大请求数 (Semantic Scholar 限制: 100 requests/5min) + """ + super().__init__(rate_limit) + try: + from semanticscholar import SemanticScholar + self.sch = SemanticScholar() + except ImportError: + raise ImportError("需要安装 semanticscholar 库: pip install semanticscholar") + + def search_by_title(self, title: str, max_results: int = 5) -> Optional[Dict]: + """通过标题搜索论文 + + Args: + title: 论文标题 + max_results: 最大返回结果数 + + Returns: + 标准化的论文信息字典(第一个结果),如果未找到则返回 None + """ + try: + self.rate_limiter.wait_if_needed() + results = self.sch.search_paper(title, limit=max_results) + + if not results: + return None + + # 返回第一个结果 + paper = results[0] + return self._normalize_result(paper) + except Exception as e: + print(f"Semantic Scholar API 错误: {e}") + return None + + def search_by_doi(self, doi: str) -> Optional[Dict]: + """通过 DOI 搜索论文 + + Args: + doi: DOI 标识符 + + Returns: + 标准化的论文信息字典,如果未找到则返回 None + """ + try: + self.rate_limiter.wait_if_needed() + paper = self.sch.get_paper(f"DOI:{doi}") + if paper: + return self._normalize_result(paper) + return None + except Exception as e: + print(f"Semantic Scholar API 错误: {e}") + return None + + def search(self, title: str = None, doi: str = None, **kwargs) -> Optional[Dict]: + """搜索论文 (统一接口)""" + if doi: + return self.search_by_doi(doi) + elif title: + return self.search_by_title(title) + return None + + def _normalize_result(self, paper) -> Dict: + """标准化 Semantic Scholar 返回结果""" + # 提取作者 + authors = [] + if paper.authors: + authors = [a.name for a in paper.authors] + + # 提取外部 ID + external_ids = paper.externalIds if hasattr(paper, 'externalIds') else {} + doi = external_ids.get('DOI') if external_ids else None + arxiv_id = external_ids.get('ArXiv') if external_ids else None + + return { + 'title': paper.title, + 'authors': authors, + 'year': paper.year, + 'venue': paper.venue if hasattr(paper, 'venue') else '', + 'paperId': paper.paperId, + 'doi': doi, + 'arxiv_id': arxiv_id, + 'citationCount': paper.citationCount if hasattr(paper, 'citationCount') else 0, + 'abstract': paper.abstract if hasattr(paper, 'abstract') else '', + 'source': 'semantic_scholar' + } + + +class CitationAPIManager: + """统一的 API 管理器 + + 协调三个 API 客户端,实现智能的 API 选择策略 + """ + + def __init__(self): + """初始化所有 API 客户端""" + self.crossref = None + self.arxiv = None + self.semantic_scholar = None + + # 尝试初始化各个客户端 + try: + self.crossref = CrossRefClient() + except Exception as e: + print(f"警告: CrossRef 客户端初始化失败: {e}") + + try: + self.arxiv = ArXivClient() + except Exception as e: + print(f"警告: arXiv 客户端初始化失败: {e}") + + try: + self.semantic_scholar = SemanticScholarClient() + except Exception as e: + print(f"警告: Semantic Scholar 客户端初始化失败: {e}") + + def verify_citation(self, citation_info: Dict) -> tuple[bool, Optional[str], Optional[Dict]]: + """验证引用 + + 实现 API 选择策略: + 1. DOI 优先 → CrossRef + 2. arXiv ID → arXiv + 3. 标题搜索 → Semantic Scholar + + Args: + citation_info: 引用信息字典,可能包含 doi, arxiv_id, title, authors 等字段 + + Returns: + (exists, api_source, api_data) + - exists: 论文是否存在 + - api_source: 验证来源 ('crossref', 'arxiv', 'semantic_scholar') + - api_data: API 返回的标准化数据 + """ + # 策略 1: DOI 优先 + if 'doi' in citation_info and self.crossref: + data = self.crossref.search_by_doi(citation_info['doi']) + if data: + return True, 'crossref', data + + # 策略 2: arXiv ID + arxiv_id = citation_info.get('arxiv_id') + if not arxiv_id and 'note' in citation_info: + # 尝试从 note 字段提取 arXiv ID + arxiv_id = ArXivClient.extract_arxiv_id(citation_info['note']) + + if arxiv_id and self.arxiv: + data = self.arxiv.search_by_id(arxiv_id) + if data: + return True, 'arxiv', data + + # 策略 3: 通用搜索 (Semantic Scholar) + if 'title' in citation_info and self.semantic_scholar: + data = self.semantic_scholar.search_by_title(citation_info['title']) + if data: + return True, 'semantic_scholar', data + + return False, None, None + + def get_bibtex(self, doi: str) -> Optional[str]: + """通过 DOI 获取 BibTeX + + Args: + doi: DOI 标识符 + + Returns: + BibTeX 字符串,如果失败则返回 None + """ + if self.crossref: + return self.crossref.get_bibtex(doi) + return None + + +# ============================================================================ +# 使用示例 +# ============================================================================ + +if __name__ == '__main__': + # 示例 1: 使用 CrossRef 客户端 + print("示例 1: CrossRef 客户端") + print("-" * 60) + crossref = CrossRefClient() + result = crossref.search_by_doi("10.48550/arXiv.1706.03762") + if result: + print(f"标题: {result['title']}") + print(f"作者: {', '.join(result['authors'][:3])}") + print(f"年份: {result['year']}") + print() + + # 示例 2: 使用 arXiv 客户端 + print("示例 2: arXiv 客户端") + print("-" * 60) + try: + arxiv_client = ArXivClient() + result = arxiv_client.search_by_id("1706.03762") + if result: + print(f"标题: {result['title']}") + print(f"作者: {', '.join(result['authors'][:3])}") + print(f"年份: {result['year']}") + except ImportError as e: + print(f"跳过: {e}") + print() + + # 示例 3: 使用 Semantic Scholar 客户端 + print("示例 3: Semantic Scholar 客户端") + print("-" * 60) + try: + ss_client = SemanticScholarClient() + result = ss_client.search_by_title("Attention is All You Need") + if result: + print(f"标题: {result['title']}") + print(f"作者: {', '.join(result['authors'][:3])}") + print(f"年份: {result['year']}") + print(f"引用数: {result['citationCount']}") + except ImportError as e: + print(f"跳过: {e}") + print() + + # 示例 4: 使用统一管理器 + print("示例 4: 统一 API 管理器") + print("-" * 60) + manager = CitationAPIManager() + citation_info = { + 'title': 'Attention is All You Need', + 'authors': ['Vaswani', 'Shazeer'], + 'year': '2017' + } + exists, source, data = manager.verify_citation(citation_info) + if exists: + print(f"验证成功!") + print(f"来源: {source}") + print(f"标题: {data['title']}") + print(f"年份: {data['year']}") diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/format-checker.py b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/format-checker.py new file mode 100644 index 0000000..c222702 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/format-checker.py @@ -0,0 +1,605 @@ +#!/usr/bin/env python3 +""" +BibTeX and LaTeX Format Checker + +独立的格式检查工具,用于验证 BibTeX 和 LaTeX 引用格式。 + +功能: +1. BibTeX 格式检查 - 验证条目结构、必填字段、字段格式 +2. LaTeX 引用检查 - 提取引用、检查一致性 +3. 快速格式验证 - 无需 API 调用的快速检查 + +使用方法: + python format-checker.py references.bib + python format-checker.py paper.tex --check-latex + python format-checker.py references.bib --strict +""" + +import argparse +import sys +import re +from pathlib import Path +from typing import Dict, List, Tuple, Optional +from dataclasses import dataclass +from enum import Enum + +# 尝试导入 bibtexparser +try: + import bibtexparser + from bibtexparser.bparser import BibTexParser + BIBTEX_AVAILABLE = True +except ImportError: + print("警告: bibtexparser 未安装,BibTeX 解析功能受限") + print("运行: pip install bibtexparser") + BIBTEX_AVAILABLE = False + + +class ErrorLevel(Enum): + """错误级别""" + ERROR = "error" # 严重错误,必须修复 + WARNING = "warning" # 警告,建议修复 + INFO = "info" # 信息,可选修复 + + +@dataclass +class FormatError: + """格式错误数据类""" + level: ErrorLevel + location: str # 文件位置 (如 "entry:smith2020" 或 "line:42") + field: Optional[str] # 字段名 (如 "author", "year") + message: str # 错误描述 + suggestion: Optional[str] = None # 修复建议 + + +def parse_arguments(): + """解析命令行参数""" + parser = argparse.ArgumentParser( + description='检查 BibTeX 和 LaTeX 引用格式', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +示例: + %(prog)s references.bib + %(prog)s paper.tex --check-latex + %(prog)s references.bib --strict --output report.txt + %(prog)s references.bib --fix-common + """ + ) + + parser.add_argument( + 'input_file', + type=str, + help='BibTeX 文件(.bib)或 LaTeX 文件(.tex)' + ) + + parser.add_argument( + '--check-latex', + action='store_true', + help='检查 LaTeX 引用(需要提供 .tex 文件)' + ) + + parser.add_argument( + '--strict', + action='store_true', + help='严格模式 - 将警告视为错误' + ) + + parser.add_argument( + '--output', + type=str, + help='输出报告文件路径' + ) + + parser.add_argument( + '--fix-common', + action='store_true', + help='自动修复常见格式问题' + ) + + parser.add_argument( + '--verbose', + action='store_true', + help='显示详细信息' + ) + + parser.add_argument( + '--entry-type', + type=str, + help='只检查特定类型的条目(如 article, inproceedings)' + ) + + return parser.parse_args() + + +def load_bibtex_file(file_path: str) -> List[Dict]: + """加载 BibTeX 文件 + + Args: + file_path: BibTeX 文件路径 + + Returns: + BibTeX 条目列表 + + Raises: + FileNotFoundError: 文件不存在 + ValueError: 文件格式错误 + """ + if not BIBTEX_AVAILABLE: + raise ImportError("需要安装 bibtexparser: pip install bibtexparser") + + try: + with open(file_path, 'r', encoding='utf-8') as f: + parser = BibTexParser(common_strings=True) + bib_database = bibtexparser.load(f, parser) + return bib_database.entries + except FileNotFoundError: + raise FileNotFoundError(f"文件不存在: {file_path}") + except Exception as e: + raise ValueError(f"无法解析 BibTeX 文件: {e}") + + +def load_latex_file(file_path: str) -> str: + """加载 LaTeX 文件 + + Args: + file_path: LaTeX 文件路径 + + Returns: + 文件内容 + + Raises: + FileNotFoundError: 文件不存在 + """ + try: + with open(file_path, 'r', encoding='utf-8') as f: + return f.read() + except FileNotFoundError: + raise FileNotFoundError(f"文件不存在: {file_path}") + except Exception as e: + raise ValueError(f"无法读取 LaTeX 文件: {e}") + + +# ============================================================================ +# BibTeX 格式检查函数 +# ============================================================================ + +def get_required_fields(entry_type: str) -> List[str]: + """获取 BibTeX 条目类型的必填字段 + + Args: + entry_type: 条目类型 (如 'article', 'inproceedings') + + Returns: + 必填字段列表 + """ + required_fields = { + 'article': ['author', 'title', 'journal', 'year'], + 'inproceedings': ['author', 'title', 'booktitle', 'year'], + 'book': ['title', 'publisher', 'year'], + 'incollection': ['author', 'title', 'booktitle', 'publisher', 'year'], + 'inbook': ['author', 'title', 'chapter', 'publisher', 'year'], + 'proceedings': ['title', 'year'], + 'phdthesis': ['author', 'title', 'school', 'year'], + 'mastersthesis': ['author', 'title', 'school', 'year'], + 'techreport': ['author', 'title', 'institution', 'year'], + 'manual': ['title'], + 'misc': ['title'], + 'unpublished': ['author', 'title', 'note'], + } + return required_fields.get(entry_type.lower(), ['title']) + + +def get_optional_fields(entry_type: str) -> List[str]: + """获取 BibTeX 条目类型的可选字段 + + Args: + entry_type: 条目类型 + + Returns: + 可选字段列表 + """ + optional_fields = { + 'article': ['volume', 'number', 'pages', 'month', 'doi', 'url'], + 'inproceedings': ['editor', 'volume', 'series', 'pages', 'address', + 'month', 'organization', 'publisher', 'doi', 'url'], + 'book': ['author', 'editor', 'volume', 'series', 'address', + 'edition', 'month', 'isbn', 'doi', 'url'], + } + return optional_fields.get(entry_type.lower(), []) + + +def check_entry_structure(entry: Dict) -> List[FormatError]: + """检查 BibTeX 条目基本结构 + + Args: + entry: BibTeX 条目字典 + + Returns: + 错误列表 + """ + errors = [] + + # 检查条目类型 + if 'ENTRYTYPE' not in entry: + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"entry:{entry.get('ID', 'unknown')}", + field='ENTRYTYPE', + message="缺少条目类型", + suggestion="添加条目类型,如 @article, @inproceedings" + )) + return errors + + # 检查 ID + if 'ID' not in entry or not entry['ID'].strip(): + errors.append(FormatError( + level=ErrorLevel.ERROR, + location="entry:unknown", + field='ID', + message="缺少 citation key", + suggestion="添加唯一的 citation key" + )) + + # 检查必填字段 + entry_type = entry.get('ENTRYTYPE', '') + required = get_required_fields(entry_type) + for field in required: + if field not in entry or not entry[field].strip(): + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"entry:{entry.get('ID', 'unknown')}", + field=field, + message=f"缺少必填字段: {field}", + suggestion=f"添加 {field} 字段" + )) + + return errors + + +def check_field_formats(entry: Dict) -> List[FormatError]: + """检查字段格式 + + Args: + entry: BibTeX 条目字典 + + Returns: + 错误列表 + """ + errors = [] + entry_id = entry.get('ID', 'unknown') + + # 年份格式检查 + if 'year' in entry: + year = entry['year'].strip() + if not year.isdigit(): + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"entry:{entry_id}", + field='year', + message=f"年份格式错误: {year} (应为4位数字)", + suggestion="使用4位数字年份,如 2023" + )) + elif len(year) != 4: + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"entry:{entry_id}", + field='year', + message=f"年份格式错误: {year} (应为4位数字)", + suggestion="使用4位数字年份,如 2023" + )) + else: + year_int = int(year) + if year_int < 1900 or year_int > 2030: + errors.append(FormatError( + level=ErrorLevel.WARNING, + location=f"entry:{entry_id}", + field='year', + message=f"年份超出合理范围: {year}", + suggestion="检查年份是否正确" + )) + + # DOI 格式检查 + if 'doi' in entry: + doi = entry['doi'].strip() + if not doi.startswith('10.'): + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"entry:{entry_id}", + field='doi', + message=f"DOI 格式错误: {doi}", + suggestion="DOI 应以 '10.' 开头,如 10.1038/nature12345" + )) + # 检查是否包含 URL 前缀 + if 'doi.org' in doi or 'dx.doi.org' in doi: + errors.append(FormatError( + level=ErrorLevel.WARNING, + location=f"entry:{entry_id}", + field='doi', + message=f"DOI 包含 URL 前缀: {doi}", + suggestion="只保留 DOI 本身,移除 https://doi.org/ 前缀" + )) + + # 作者名格式检查 + if 'author' in entry: + author = entry['author'].strip() + # 检查是否为空 + if not author: + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"entry:{entry_id}", + field='author', + message="作者字段为空", + suggestion="添加作者信息" + )) + # 检查格式一致性 + elif ' and ' in author: + authors = author.split(' and ') + formats = [] + for a in authors: + if ',' in a: + formats.append('last_first') # "Last, First" + else: + formats.append('first_last') # "First Last" + + if len(set(formats)) > 1: + errors.append(FormatError( + level=ErrorLevel.WARNING, + location=f"entry:{entry_id}", + field='author', + message="作者名格式不一致", + suggestion="统一使用 'Last, First' 或 'First Last' 格式" + )) + + # 页码格式检查 + if 'pages' in entry: + pages = entry['pages'].strip() + # 检查是否使用了正确的分隔符 + if '-' in pages and '--' not in pages: + errors.append(FormatError( + level=ErrorLevel.INFO, + location=f"entry:{entry_id}", + field='pages', + message=f"页码使用单连字符: {pages}", + suggestion="建议使用双连字符 '--',如 123--145" + )) + + # URL 格式检查 + if 'url' in entry: + url = entry['url'].strip() + if not url.startswith(('http://', 'https://')): + errors.append(FormatError( + level=ErrorLevel.WARNING, + location=f"entry:{entry_id}", + field='url', + message=f"URL 缺少协议前缀: {url}", + suggestion="添加 http:// 或 https:// 前缀" + )) + + return errors + + +def check_consistency(entries: List[Dict]) -> List[FormatError]: + """检查条目间的一致性 + + Args: + entries: BibTeX 条目列表 + + Returns: + 错误列表 + """ + errors = [] + + # 检查重复的 citation key + ids = [e.get('ID', '') for e in entries] + duplicates = [id for id in ids if ids.count(id) > 1] + if duplicates: + for dup_id in set(duplicates): + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"entry:{dup_id}", + field='ID', + message=f"重复的 citation key: {dup_id}", + suggestion="使用唯一的 citation key" + )) + + # 检查作者名格式一致性 + author_formats = {} + for entry in entries: + if 'author' in entry and ' and ' in entry['author']: + entry_id = entry.get('ID', 'unknown') + authors = entry['author'].split(' and ') + for author in authors: + if ',' in author: + author_formats[entry_id] = 'last_first' + else: + author_formats[entry_id] = 'first_last' + break + + if len(set(author_formats.values())) > 1: + errors.append(FormatError( + level=ErrorLevel.WARNING, + location="global", + field='author', + message="不同条目使用了不同的作者名格式", + suggestion="统一使用 'Last, First' 或 'First Last' 格式" + )) + + return errors + + +# ============================================================================ +# LaTeX 引用检查函数 +# ============================================================================ + +def extract_latex_citations(tex_content: str) -> List[str]: + """从 LaTeX 文件中提取引用 + + Args: + tex_content: LaTeX 文件内容 + + Returns: + 引用 key 列表 + """ + # 匹配 \cite{...} 命令 + cite_pattern = r'\\cite(?:\[[^\]]*\])?(?:\[[^\]]*\])?\{([^}]+)\}' + citations = re.findall(cite_pattern, tex_content) + + # 展开多个引用 + all_keys = [] + for cite in citations: + keys = [k.strip() for k in cite.split(',')] + all_keys.extend(keys) + + return list(set(all_keys)) # 去重 + + +def check_latex_consistency(tex_keys: List[str], bib_keys: List[str]) -> List[FormatError]: + """检查 LaTeX 引用与 BibTeX 的一致性 + + Args: + tex_keys: LaTeX 中的引用 key 列表 + bib_keys: BibTeX 中的 key 列表 + + Returns: + 错误列表 + """ + errors = [] + + tex_set = set(tex_keys) + bib_set = set(bib_keys) + + # 未定义的引用 + undefined = tex_set - bib_set + if undefined: + for key in sorted(undefined): + errors.append(FormatError( + level=ErrorLevel.ERROR, + location=f"latex:cite", + field=key, + message=f"未定义的引用: {key}", + suggestion=f"在 BibTeX 文件中添加 {key} 条目" + )) + + # 未使用的引用 + unused = bib_set - tex_set + if unused: + for key in sorted(unused): + errors.append(FormatError( + level=ErrorLevel.WARNING, + location=f"bibtex:entry", + field=key, + message=f"未使用的引用: {key}", + suggestion=f"在 LaTeX 文件中引用 {key} 或从 BibTeX 中删除" + )) + + return errors + + +# ============================================================================ +# 报告生成函数 +# ============================================================================ + +def print_errors(errors: List[FormatError], verbose: bool = False): + """打印错误列表 + + Args: + errors: 错误列表 + verbose: 是否显示详细信息 + """ + if not errors: + print("✅ 未发现格式错误") + return + + # 按级别分组 + errors_by_level = { + ErrorLevel.ERROR: [], + ErrorLevel.WARNING: [], + ErrorLevel.INFO: [] + } + + for error in errors: + errors_by_level[error.level].append(error) + + # 打印统计 + print("\n" + "="*60) + print("格式检查结果") + print("="*60) + print(f"❌ 错误: {len(errors_by_level[ErrorLevel.ERROR])}") + print(f"⚠️ 警告: {len(errors_by_level[ErrorLevel.WARNING])}") + print(f"ℹ️ 信息: {len(errors_by_level[ErrorLevel.INFO])}") + print("="*60) + + # 打印详细错误 + for level in [ErrorLevel.ERROR, ErrorLevel.WARNING, ErrorLevel.INFO]: + level_errors = errors_by_level[level] + if not level_errors: + continue + + level_symbol = { + ErrorLevel.ERROR: "❌", + ErrorLevel.WARNING: "⚠️", + ErrorLevel.INFO: "ℹ️" + }[level] + + print(f"\n{level_symbol} {level.value.upper()} ({len(level_errors)}):\n") + + for error in level_errors: + print(f" [{error.location}]", end="") + if error.field: + print(f" {error.field}:", end="") + print(f" {error.message}") + + if verbose and error.suggestion: + print(f" 💡 建议: {error.suggestion}") + print() + + +def generate_report(errors: List[FormatError], output_file: str): + """生成文本格式的检查报告 + + Args: + errors: 错误列表 + output_file: 输出文件路径 + """ + # 按级别分组 + errors_by_level = { + ErrorLevel.ERROR: [], + ErrorLevel.WARNING: [], + ErrorLevel.INFO: [] + } + + for error in errors: + errors_by_level[error.level].append(error) + + with open(output_file, 'w', encoding='utf-8') as f: + f.write("# BibTeX/LaTeX 格式检查报告\n\n") + + # 总体统计 + f.write("## 总体统计\n\n") + f.write(f"- **错误**: {len(errors_by_level[ErrorLevel.ERROR])}\n") + f.write(f"- **警告**: {len(errors_by_level[ErrorLevel.WARNING])}\n") + f.write(f"- **信息**: {len(errors_by_level[ErrorLevel.INFO])}\n\n") + + # 详细错误 + for level in [ErrorLevel.ERROR, ErrorLevel.WARNING, ErrorLevel.INFO]: + level_errors = errors_by_level[level] + if not level_errors: + continue + + level_name = { + ErrorLevel.ERROR: "错误", + ErrorLevel.WARNING: "警告", + ErrorLevel.INFO: "信息" + }[level] + + f.write(f"## {level_name} ({len(level_errors)})\n\n") + + for error in level_errors: + f.write(f"### [{error.location}]") + if error.field: + f.write(f" {error.field}") + f.write("\n\n") + f.write(f"**问题**: {error.message}\n\n") + if error.suggestion: + f.write(f"**建议**: {error.suggestion}\n\n") + + print(f"\n报告已保存到: {output_file}") diff --git a/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/verify-citations.py b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/verify-citations.py new file mode 100644 index 0000000..ea092be --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/citation-verification/scripts/verify-citations.py @@ -0,0 +1,678 @@ +#!/usr/bin/env python3 +""" +Citation Verification Script + +四层验证机制: +1. Format Validation - BibTeX 格式检查 +2. Existence Verification - API 验证论文存在性 +3. Information Matching - 信息匹配(标题、作者、年份) +4. Content Validation - 综合评分和判定 + +使用方法: + python verify-citations.py references.bib + python verify-citations.py paper.tex --check-latex + python verify-citations.py references.bib --verbose --output report.md +""" + +import argparse +import sys +import json +from pathlib import Path +from typing import Dict, List, Optional, Tuple +from dataclasses import dataclass, asdict +import re +from difflib import SequenceMatcher + +# 尝试导入 bibtexparser +try: + import bibtexparser + from bibtexparser.bparser import BibTexParser +except ImportError: + print("错误: 需要安装 bibtexparser") + print("运行: pip install bibtexparser") + sys.exit(1) + +# 尝试导入 API 客户端库 +try: + from semanticscholar import SemanticScholar +except ImportError: + print("警告: semanticscholar 未安装,将跳过 Semantic Scholar 验证") + print("运行: pip install semanticscholar") + +try: + import arxiv +except ImportError: + print("警告: arxiv 未安装,将跳过 arXiv 验证") + print("运行: pip install arxiv") + +try: + import requests +except ImportError: + print("错误: 需要安装 requests") + print("运行: pip install requests") + sys.exit(1) + + +@dataclass +class VerificationResult: + """验证结果数据类""" + citation_key: str + status: str # verified, partial_match, low_match, failed, not_found + confidence: str # high_confidence, medium_confidence, low_confidence, no_confidence + match_score: float + format_errors: List[str] + api_source: Optional[str] # crossref, arxiv, semantic_scholar + message: str + + +def parse_arguments(): + """解析命令行参数""" + parser = argparse.ArgumentParser( + description='验证 BibTeX 引用的准确性和完整性', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +示例: + %(prog)s references.bib + %(prog)s paper.tex --check-latex + %(prog)s references.bib --verbose --output report.md + %(prog)s references.bib --api-only + """ + ) + + parser.add_argument( + 'input_file', + type=str, + help='BibTeX 文件(.bib)或 LaTeX 文件(.tex)' + ) + + parser.add_argument( + '--check-latex', + action='store_true', + help='检查 LaTeX 引用一致性(需要提供 .tex 文件)' + ) + + parser.add_argument( + '--verbose', + action='store_true', + help='显示详细验证信息' + ) + + parser.add_argument( + '--output', + type=str, + help='输出报告文件路径(Markdown 格式)' + ) + + parser.add_argument( + '--api-only', + action='store_true', + help='仅进行 API 验证,跳过格式检查' + ) + + parser.add_argument( + '--format-only', + action='store_true', + help='仅进行格式检查,跳过 API 验证' + ) + + parser.add_argument( + '--threshold', + type=float, + default=0.85, + help='匹配阈值(0.0-1.0),默认 0.85' + ) + + return parser.parse_args() + + +def load_bibtex(file_path: str) -> List[Dict]: + """加载 BibTeX 文件""" + try: + with open(file_path, 'r', encoding='utf-8') as f: + parser = BibTexParser(common_strings=True) + bib_database = bibtexparser.load(f, parser) + return bib_database.entries + except FileNotFoundError: + print(f"错误: 文件不存在: {file_path}") + sys.exit(1) + except Exception as e: + print(f"错误: 无法解析 BibTeX 文件: {e}") + sys.exit(1) + + +def extract_latex_citations(tex_file: str) -> List[str]: + """从 LaTeX 文件中提取引用""" + try: + with open(tex_file, 'r', encoding='utf-8') as f: + content = f.read() + + # 匹配 \cite{...} 命令 + cite_pattern = r'\\cite(?:\[[^\]]*\])?\{([^}]+)\}' + citations = re.findall(cite_pattern, content) + + # 展开多个引用 + all_keys = [] + for cite in citations: + keys = [k.strip() for k in cite.split(',')] + all_keys.extend(keys) + + return list(set(all_keys)) # 去重 + except FileNotFoundError: + print(f"错误: 文件不存在: {tex_file}") + sys.exit(1) + except Exception as e: + print(f"错误: 无法解析 LaTeX 文件: {e}") + sys.exit(1) + + +# ============================================================================ +# Layer 1: Format Validation (格式验证) +# ============================================================================ + +def get_required_fields(entry_type: str) -> List[str]: + """获取 BibTeX 条目类型的必填字段""" + required_fields = { + 'article': ['author', 'title', 'journal', 'year'], + 'inproceedings': ['author', 'title', 'booktitle', 'year'], + 'book': ['title', 'publisher', 'year'], + 'misc': ['title'], + 'phdthesis': ['author', 'title', 'school', 'year'], + 'mastersthesis': ['author', 'title', 'school', 'year'], + 'techreport': ['author', 'title', 'institution', 'year'], + } + return required_fields.get(entry_type.lower(), ['title']) + + +def check_bibtex_format(entry: Dict) -> List[str]: + """检查 BibTeX 条目格式 + + Returns: + 错误列表 + """ + errors = [] + + # 检查条目类型 + if 'ENTRYTYPE' not in entry: + errors.append("缺少条目类型") + return errors + + # 检查 ID + if 'ID' not in entry: + errors.append("缺少 citation key") + + # 检查必填字段 + entry_type = entry.get('ENTRYTYPE', '') + required = get_required_fields(entry_type) + for field in required: + if field not in entry or not entry[field].strip(): + errors.append(f"缺少必填字段: {field}") + + # 年份格式检查 + if 'year' in entry: + year = entry['year'].strip() + if not year.isdigit() or len(year) != 4: + errors.append(f"年份格式错误: {year}") + else: + year_int = int(year) + if year_int < 1900 or year_int > 2030: + errors.append(f"年份超出合理范围: {year}") + + # DOI 格式检查 + if 'doi' in entry: + doi = entry['doi'].strip() + if not doi.startswith('10.'): + errors.append(f"DOI 格式错误: {doi}") + + return errors + + +def check_citation_consistency(tex_keys: List[str], bib_keys: List[str]) -> Dict: + """检查 LaTeX 引用与 BibTeX 的一致性 + + Returns: + {'undefined': [...], 'unused': [...]} + """ + tex_set = set(tex_keys) + bib_set = set(bib_keys) + + return { + 'undefined': list(tex_set - bib_set), + 'unused': list(bib_set - tex_set) + } + + +# ============================================================================ +# Layer 2: Existence Verification (存在性验证) +# ============================================================================ + +def verify_with_crossref(doi: str) -> Optional[Dict]: + """通过 CrossRef API 验证 DOI""" + try: + url = f"https://api.crossref.org/works/{doi}" + response = requests.get(url, timeout=10) + if response.status_code == 200: + data = response.json() + return data.get('message') + return None + except Exception as e: + print(f"CrossRef API 错误: {e}") + return None + + +def verify_with_arxiv(arxiv_id: str) -> Optional[Dict]: + """通过 arXiv API 验证""" + try: + search = arxiv.Search(id_list=[arxiv_id]) + paper = next(search.results()) + return { + 'title': paper.title, + 'authors': [a.name for a in paper.authors], + 'year': paper.published.year, + 'arxiv_id': arxiv_id + } + except Exception as e: + print(f"arXiv API 错误: {e}") + return None + + +def verify_with_semantic_scholar(title: str, authors: Optional[List[str]] = None) -> Optional[Dict]: + """通过 Semantic Scholar API 验证""" + try: + sch = SemanticScholar() + results = sch.search_paper(title, limit=5) + + if not results: + return None + + # 返回第一个结果 + paper = results[0] + return { + 'title': paper.title, + 'authors': [a.name for a in paper.authors] if paper.authors else [], + 'year': paper.year, + 'paperId': paper.paperId + } + except Exception as e: + print(f"Semantic Scholar API 错误: {e}") + return None + + +def verify_existence(entry: Dict) -> Tuple[bool, Optional[str], Optional[Dict]]: + """验证论文存在性 + + Returns: + (exists, api_source, api_data) + """ + # 策略 1: DOI 优先 + if 'doi' in entry: + data = verify_with_crossref(entry['doi']) + if data: + return True, 'crossref', data + + # 策略 2: arXiv ID + if 'eprint' in entry or 'arxiv' in entry.get('note', '').lower(): + arxiv_id = entry.get('eprint', '') + if not arxiv_id: + # 尝试从 note 中提取 + match = re.search(r'arXiv:(\d{4}\.\d{4,5})', entry.get('note', '')) + if match: + arxiv_id = match.group(1) + + if arxiv_id: + data = verify_with_arxiv(arxiv_id) + if data: + return True, 'arxiv', data + + # 策略 3: 通用搜索 + if 'title' in entry: + authors = entry.get('author', '').split(' and ') if 'author' in entry else None + data = verify_with_semantic_scholar(entry['title'], authors) + if data: + return True, 'semantic_scholar', data + + return False, None, None + + +# ============================================================================ +# Layer 3 & 4: Information Matching & Content Validation (信息匹配和内容验证) +# ============================================================================ + +def normalize_text(text: str) -> str: + """标准化文本用于匹配""" + text = text.lower() + text = re.sub(r'[^\w\s]', '', text) + return ' '.join(text.split()) + + +def match_title(title1: str, title2: str, threshold: float = 0.85) -> Dict: + """标题匹配""" + t1 = normalize_text(title1) + t2 = normalize_text(title2) + + ratio = SequenceMatcher(None, t1, t2).ratio() + + return { + 'match': ratio >= threshold, + 'similarity': ratio + } + + +def normalize_author_name(name: str) -> str: + """标准化作者名""" + parts = name.replace(',', '').split() + return ' '.join(sorted(parts)).lower() + + +def match_authors(authors1: List[str], authors2: List[str], threshold: float = 0.7) -> Dict: + """作者匹配""" + names1 = [normalize_author_name(a) for a in authors1] + names2 = [normalize_author_name(a) for a in authors2] + + set1 = set(names1) + set2 = set(names2) + intersection = len(set1 & set2) + union = len(set1 | set2) + + if union == 0: + return {'match': False, 'similarity': 0} + + ratio = intersection / union + + return { + 'match': ratio >= threshold, + 'similarity': ratio + } + + +def match_year(year1: str, year2: int, tolerance: int = 1) -> Dict: + """年份匹配""" + try: + y1 = int(year1) + y2 = int(year2) + diff = abs(y1 - y2) + return { + 'match': diff <= tolerance, + 'difference': diff + } + except (ValueError, TypeError): + return {'match': False, 'difference': None} + + +def calculate_match_score(entry: Dict, api_data: Dict, threshold: float) -> float: + """计算综合匹配分数""" + scores = {} + weights = { + 'title': 0.4, + 'authors': 0.3, + 'year': 0.2, + 'venue': 0.1 + } + + # 标题匹配 + if 'title' in entry and 'title' in api_data: + result = match_title(entry['title'], api_data['title'], threshold) + scores['title'] = result['similarity'] + + # 作者匹配 + if 'author' in entry and 'authors' in api_data: + entry_authors = entry['author'].split(' and ') + result = match_authors(entry_authors, api_data['authors']) + scores['authors'] = result['similarity'] + + # 年份匹配 + if 'year' in entry and 'year' in api_data: + result = match_year(entry['year'], api_data['year']) + scores['year'] = 1.0 if result['match'] else 0.0 + + # 计算加权总分 + total_score = 0 + total_weight = 0 + for key, weight in weights.items(): + if key in scores: + total_score += scores[key] * weight + total_weight += weight + + if total_weight == 0: + return 0 + + return total_score / total_weight + + +def judge_verification_result(match_score: float) -> Dict: + """判定验证结果""" + if match_score >= 0.9: + return { + 'status': 'verified', + 'level': 'high_confidence', + 'message': '✅ 验证通过 - 信息完全匹配' + } + elif match_score >= 0.7: + return { + 'status': 'partial_match', + 'level': 'medium_confidence', + 'message': '⚠️ 部分匹配 - 信息有轻微差异,建议人工确认' + } + elif match_score >= 0.5: + return { + 'status': 'low_match', + 'level': 'low_confidence', + 'message': '❌ 匹配度低 - 信息差异较大,需要人工验证' + } + else: + return { + 'status': 'failed', + 'level': 'no_confidence', + 'message': '❌ 验证失败 - 信息严重不匹配或论文不存在' + } + + +def verify_citation(entry: Dict, args) -> VerificationResult: + """完整的引用验证流程""" + citation_key = entry.get('ID', 'unknown') + + # Layer 1: 格式验证 + format_errors = [] + if not args.api_only: + format_errors = check_bibtex_format(entry) + + # Layer 2: 存在性验证 + if args.format_only: + return VerificationResult( + citation_key=citation_key, + status='format_checked', + confidence='n/a', + match_score=0.0, + format_errors=format_errors, + api_source=None, + message='仅格式检查' + ) + + exists, api_source, api_data = verify_existence(entry) + + if not exists: + return VerificationResult( + citation_key=citation_key, + status='not_found', + confidence='no_confidence', + match_score=0.0, + format_errors=format_errors, + api_source=None, + message='❌ 论文不存在 - 无法通过任何 API 验证' + ) + + # Layer 3 & 4: 信息匹配和内容验证 + match_score = calculate_match_score(entry, api_data, args.threshold) + judgment = judge_verification_result(match_score) + + return VerificationResult( + citation_key=citation_key, + status=judgment['status'], + confidence=judgment['level'], + match_score=match_score, + format_errors=format_errors, + api_source=api_source, + message=judgment['message'] + ) + + +# ============================================================================ +# Report Generation (报告生成) +# ============================================================================ + +def print_summary(results: List[VerificationResult], verbose: bool = False): + """打印验证摘要""" + total = len(results) + verified = sum(1 for r in results if r.status == 'verified') + partial = sum(1 for r in results if r.status == 'partial_match') + low = sum(1 for r in results if r.status == 'low_match') + failed = sum(1 for r in results if r.status in ['failed', 'not_found']) + + print("\n" + "="*60) + print("验证摘要") + print("="*60) + print(f"总引用数: {total}") + print(f"✅ 验证通过: {verified} ({verified/total*100:.1f}%)") + print(f"⚠️ 部分匹配: {partial} ({partial/total*100:.1f}%)") + print(f"❌ 匹配度低: {low} ({low/total*100:.1f}%)") + print(f"❌ 验证失败: {failed} ({failed/total*100:.1f}%)") + print("="*60) + + if verbose: + print("\n详细结果:\n") + for result in results: + print(f"[{result.citation_key}]") + print(f" 状态: {result.message}") + print(f" 匹配分数: {result.match_score:.2f}") + if result.api_source: + print(f" 验证源: {result.api_source}") + if result.format_errors: + print(f" 格式错误: {', '.join(result.format_errors)}") + print() + + +def generate_markdown_report(results: List[VerificationResult], output_file: str): + """生成 Markdown 格式的验证报告""" + total = len(results) + verified = sum(1 for r in results if r.status == 'verified') + partial = sum(1 for r in results if r.status == 'partial_match') + low = sum(1 for r in results if r.status == 'low_match') + failed = sum(1 for r in results if r.status in ['failed', 'not_found']) + + with open(output_file, 'w', encoding='utf-8') as f: + f.write("# Citation Verification Report\n\n") + + # 总体统计 + f.write("## 总体统计\n\n") + f.write(f"- **总引用数**: {total}\n") + f.write(f"- **✅ 验证通过**: {verified} ({verified/total*100:.1f}%)\n") + f.write(f"- **⚠️ 部分匹配**: {partial} ({partial/total*100:.1f}%)\n") + f.write(f"- **❌ 匹配度低**: {low} ({low/total*100:.1f}%)\n") + f.write(f"- **❌ 验证失败**: {failed} ({failed/total*100:.1f}%)\n\n") + + # 详细结果 + f.write("## 详细结果\n\n") + + # 按状态分组 + for status, emoji, title in [ + ('verified', '✅', '验证通过'), + ('partial_match', '⚠️', '部分匹配'), + ('low_match', '❌', '匹配度低'), + ('failed', '❌', '验证失败'), + ('not_found', '❌', '论文不存在') + ]: + status_results = [r for r in results if r.status == status] + if status_results: + f.write(f"### {emoji} {title} ({len(status_results)})\n\n") + for result in status_results: + f.write(f"#### `{result.citation_key}`\n\n") + f.write(f"- **状态**: {result.message}\n") + f.write(f"- **匹配分数**: {result.match_score:.2f}\n") + f.write(f"- **置信度**: {result.confidence}\n") + if result.api_source: + f.write(f"- **验证源**: {result.api_source}\n") + if result.format_errors: + f.write(f"- **格式错误**:\n") + for error in result.format_errors: + f.write(f" - {error}\n") + f.write("\n") + + # 建议操作 + f.write("## 建议操作\n\n") + if failed > 0: + f.write("### 需要修正的引用\n\n") + failed_results = [r for r in results if r.status in ['failed', 'not_found']] + for result in failed_results: + f.write(f"- `{result.citation_key}`: {result.message}\n") + f.write("\n") + + if partial > 0 or low > 0: + f.write("### 需要人工确认的引用\n\n") + check_results = [r for r in results if r.status in ['partial_match', 'low_match']] + for result in check_results: + f.write(f"- `{result.citation_key}`: {result.message}\n") + f.write("\n") + + print(f"\n报告已保存到: {output_file}") + + +# ============================================================================ +# Main Function (主函数) +# ============================================================================ + +def main(): + """主函数""" + args = parse_arguments() + + # 加载 BibTeX 文件 + print(f"正在加载 BibTeX 文件: {args.input_file}") + entries = load_bibtex(args.input_file) + print(f"找到 {len(entries)} 个引用条目") + + # LaTeX 一致性检查 + if args.check_latex: + tex_file = args.input_file.replace('.bib', '.tex') + if Path(tex_file).exists(): + print(f"\n正在检查 LaTeX 引用一致性: {tex_file}") + tex_keys = extract_latex_citations(tex_file) + bib_keys = [e['ID'] for e in entries] + consistency = check_citation_consistency(tex_keys, bib_keys) + + if consistency['undefined']: + print(f"⚠️ 未定义的引用 ({len(consistency['undefined'])}): {', '.join(consistency['undefined'])}") + if consistency['unused']: + print(f"⚠️ 未使用的引用 ({len(consistency['unused'])}): {', '.join(consistency['unused'])}") + if not consistency['undefined'] and not consistency['unused']: + print("✅ LaTeX 引用与 BibTeX 完全一致") + + # 验证每个引用 + print("\n开始验证引用...") + results = [] + for i, entry in enumerate(entries, 1): + citation_key = entry.get('ID', 'unknown') + print(f"[{i}/{len(entries)}] 验证 {citation_key}...", end=' ') + + result = verify_citation(entry, args) + results.append(result) + + # 简短状态输出 + if result.status == 'verified': + print("✅") + elif result.status == 'partial_match': + print("⚠️") + else: + print("❌") + + # 打印摘要 + print_summary(results, args.verbose) + + # 生成报告 + if args.output: + generate_markdown_report(results, args.output) + + # 返回退出码 + failed_count = sum(1 for r in results if r.status in ['failed', 'not_found']) + return 0 if failed_count == 0 else 1 + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/SKILL.md new file mode 100644 index 0000000..d82d72c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/SKILL.md @@ -0,0 +1,521 @@ +--- +name: code-review-excellence +description: This skill should be used when the user asks to review a diff or pull request, write review comments, audit code quality, establish review standards, or improve how a team performs code review. +version: 0.1.0 +--- + +# Code Review Excellence + +Transform code reviews from gatekeeping to knowledge sharing through constructive feedback, systematic analysis, and collaborative improvement. + +## When to Use This Skill + +- Reviewing pull requests and code changes +- Establishing code review standards for teams +- Mentoring junior developers through reviews +- Conducting architecture reviews +- Creating review checklists and guidelines +- Improving team collaboration +- Reducing code review cycle time +- Maintaining code quality standards + +## Core Principles + +### 1. The Review Mindset + +**Goals of Code Review:** +- Catch bugs and edge cases +- Ensure code maintainability +- Share knowledge across team +- Enforce coding standards +- Improve design and architecture +- Build team culture + +**Not the Goals:** +- Show off knowledge +- Nitpick formatting (use linters) +- Block progress unnecessarily +- Rewrite to your preference + +### 2. Effective Feedback + +**Good Feedback is:** +- Specific and actionable +- Educational, not judgmental +- Focused on the code, not the person +- Balanced (praise good work too) +- Prioritized (critical vs nice-to-have) + +```markdown +❌ Bad: "This is wrong." +✅ Good: "This could cause a race condition when multiple users + access simultaneously. Consider using a mutex here." + +❌ Bad: "Why didn't you use X pattern?" +✅ Good: "Have you considered the Repository pattern? It would + make this easier to test. Here's an example: [link]" + +❌ Bad: "Rename this variable." +✅ Good: "[nit] Consider `userCount` instead of `uc` for + clarity. Not blocking if you prefer to keep it." +``` + +### 3. Review Scope + +**What to Review:** +- Logic correctness and edge cases +- Security vulnerabilities +- Performance implications +- Test coverage and quality +- Error handling +- Documentation and comments +- API design and naming +- Architectural fit + +**What Not to Review Manually:** +- Code formatting (use Prettier, Black, etc.) +- Import organization +- Linting violations +- Simple typos + +## Review Process + +### Phase 1: Context Gathering (2-3 minutes) + +```markdown +Before diving into code, understand: + +1. Read PR description and linked issue +2. Check PR size (>400 lines? Ask to split) +3. Review CI/CD status (tests passing?) +4. Understand the business requirement +5. Note any relevant architectural decisions +``` + +### Phase 2: High-Level Review (5-10 minutes) + +```markdown +1. **Architecture & Design** + - Does the solution fit the problem? + - Are there simpler approaches? + - Is it consistent with existing patterns? + - Will it scale? + +2. **File Organization** + - Are new files in the right places? + - Is code grouped logically? + - Are there duplicate files? + +3. **Testing Strategy** + - Are there tests? + - Do tests cover edge cases? + - Are tests readable? +``` + +### Phase 3: Line-by-Line Review (10-20 minutes) + +```markdown +For each file: + +1. **Logic & Correctness** + - Edge cases handled? + - Off-by-one errors? + - Null/undefined checks? + - Race conditions? + +2. **Security** + - Input validation? + - SQL injection risks? + - XSS vulnerabilities? + - Sensitive data exposure? + +3. **Performance** + - N+1 queries? + - Unnecessary loops? + - Memory leaks? + - Blocking operations? + +4. **Maintainability** + - Clear variable names? + - Functions doing one thing? + - Complex code commented? + - Magic numbers extracted? +``` + +### Phase 4: Summary & Decision (2-3 minutes) + +```markdown +1. Summarize key concerns +2. Highlight what you liked +3. Make clear decision: + - ✅ Approve + - 💬 Comment (minor suggestions) + - 🔄 Request Changes (must address) +4. Offer to pair if complex +``` + +## Review Techniques + +### Technique 1: The Checklist Method + +```markdown +## Security Checklist +- [ ] User input validated and sanitized +- [ ] SQL queries use parameterization +- [ ] Authentication/authorization checked +- [ ] Secrets not hardcoded +- [ ] Error messages don't leak info + +## Performance Checklist +- [ ] No N+1 queries +- [ ] Database queries indexed +- [ ] Large lists paginated +- [ ] Expensive operations cached +- [ ] No blocking I/O in hot paths + +## Testing Checklist +- [ ] Happy path tested +- [ ] Edge cases covered +- [ ] Error cases tested +- [ ] Test names are descriptive +- [ ] Tests are deterministic +``` + +### Technique 2: The Question Approach + +Instead of stating problems, ask questions to encourage thinking: + +```markdown +❌ "This will fail if the list is empty." +✅ "What happens if `items` is an empty array?" + +❌ "You need error handling here." +✅ "How should this behave if the API call fails?" + +❌ "This is inefficient." +✅ "I see this loops through all users. Have we considered + the performance impact with 100k users?" +``` + +### Technique 3: Suggest, Don't Command + +```markdown +## Use Collaborative Language + +❌ "You must change this to use async/await" +✅ "Suggestion: async/await might make this more readable: + ```typescript + async function fetchUser(id: string) { + const user = await db.query('SELECT * FROM users WHERE id = ?', id); + return user; + } + ``` + What do you think?" + +❌ "Extract this into a function" +✅ "This logic appears in 3 places. Would it make sense to + extract it into a shared utility function?" +``` + +### Technique 4: Differentiate Severity + +```markdown +Use labels to indicate priority: + +🔴 [blocking] - Must fix before merge +🟡 [important] - Should fix, discuss if disagree +🟢 [nit] - Nice to have, not blocking +💡 [suggestion] - Alternative approach to consider +📚 [learning] - Educational comment, no action needed +🎉 [praise] - Good work, keep it up! + +Example: +"🔴 [blocking] This SQL query is vulnerable to injection. + Please use parameterized queries." + +"🟢 [nit] Consider renaming `data` to `userData` for clarity." + +"🎉 [praise] Excellent test coverage! This will catch edge cases." +``` + +## Language-Specific Patterns + +### Python Code Review + +```python +# Check for Python-specific issues + +# ❌ Mutable default arguments +def add_item(item, items=[]): # Bug! Shared across calls + items.append(item) + return items + +# ✅ Use None as default +def add_item(item, items=None): + if items is None: + items = [] + items.append(item) + return items + +# ❌ Catching too broad +try: + result = risky_operation() +except: # Catches everything, even KeyboardInterrupt! + pass + +# ✅ Catch specific exceptions +try: + result = risky_operation() +except ValueError as e: + logger.error(f"Invalid value: {e}") + raise + +# ❌ Using mutable class attributes +class User: + permissions = [] # Shared across all instances! + +# ✅ Initialize in __init__ +class User: + def __init__(self): + self.permissions = [] +``` + +### TypeScript/JavaScript Code Review + +```typescript +// Check for TypeScript-specific issues + +// ❌ Using any defeats type safety +function processData(data: any) { // Avoid any + return data.value; +} + +// ✅ Use proper types +interface DataPayload { + value: string; +} +function processData(data: DataPayload) { + return data.value; +} + +// ❌ Not handling async errors +async function fetchUser(id: string) { + const response = await fetch(`/api/users/${id}`); + return response.json(); // What if network fails? +} + +// ✅ Handle errors properly +async function fetchUser(id: string): Promise { + try { + const response = await fetch(`/api/users/${id}`); + if (!response.ok) { + throw new Error(`HTTP ${response.status}`); + } + return await response.json(); + } catch (error) { + console.error('Failed to fetch user:', error); + throw error; + } +} + +// ❌ Mutation of props +function UserProfile({ user }: Props) { + user.lastViewed = new Date(); // Mutating prop! + return
    {user.name}
    ; +} + +// ✅ Don't mutate props +function UserProfile({ user, onView }: Props) { + useEffect(() => { + onView(user.id); // Notify parent to update + }, [user.id]); + return
    {user.name}
    ; +} +``` + +## Advanced Review Patterns + +### Pattern 1: Architectural Review + +```markdown +When reviewing significant changes: + +1. **Design Document First** + - For large features, request design doc before code + - Review design with team before implementation + - Agree on approach to avoid rework + +2. **Review in Stages** + - First PR: Core abstractions and interfaces + - Second PR: Implementation + - Third PR: Integration and tests + - Easier to review, faster to iterate + +3. **Consider Alternatives** + - "Have we considered using [pattern/library]?" + - "What's the tradeoff vs. the simpler approach?" + - "How will this evolve as requirements change?" +``` + +### Pattern 2: Test Quality Review + +```typescript +// ❌ Poor test: Implementation detail testing +test('increments counter variable', () => { + const component = render(); + const button = component.getByRole('button'); + fireEvent.click(button); + expect(component.state.counter).toBe(1); // Testing internal state +}); + +// ✅ Good test: Behavior testing +test('displays incremented count when clicked', () => { + render(); + const button = screen.getByRole('button', { name: /increment/i }); + fireEvent.click(button); + expect(screen.getByText('Count: 1')).toBeInTheDocument(); +}); + +// Review questions for tests: +// - Do tests describe behavior, not implementation? +// - Are test names clear and descriptive? +// - Do tests cover edge cases? +// - Are tests independent (no shared state)? +// - Can tests run in any order? +``` + +### Pattern 3: Security Review + +```markdown +## Security Review Checklist + +### Authentication & Authorization +- [ ] Is authentication required where needed? +- [ ] Are authorization checks before every action? +- [ ] Is JWT validation proper (signature, expiry)? +- [ ] Are API keys/secrets properly secured? + +### Input Validation +- [ ] All user inputs validated? +- [ ] File uploads restricted (size, type)? +- [ ] SQL queries parameterized? +- [ ] XSS protection (escape output)? + +### Data Protection +- [ ] Passwords hashed (bcrypt/argon2)? +- [ ] Sensitive data encrypted at rest? +- [ ] HTTPS enforced for sensitive data? +- [ ] PII handled according to regulations? + +### Common Vulnerabilities +- [ ] No eval() or similar dynamic execution? +- [ ] No hardcoded secrets? +- [ ] CSRF protection for state-changing operations? +- [ ] Rate limiting on public endpoints? +``` + +## Giving Difficult Feedback + +### Pattern: The Sandwich Method (Modified) + +```markdown +Traditional: Praise + Criticism + Praise (feels fake) + +Better: Context + Specific Issue + Helpful Solution + +Example: +"I noticed the payment processing logic is inline in the +controller. This makes it harder to test and reuse. + +[Specific Issue] +The calculateTotal() function mixes tax calculation, +discount logic, and database queries, making it difficult +to unit test and reason about. + +[Helpful Solution] +Could we extract this into a PaymentService class? That +would make it testable and reusable. I can pair with you +on this if helpful." +``` + +### Handling Disagreements + +```markdown +When author disagrees with your feedback: + +1. **Seek to Understand** + "Help me understand your approach. What led you to + choose this pattern?" + +2. **Acknowledge Valid Points** + "That's a good point about X. I hadn't considered that." + +3. **Provide Data** + "I'm concerned about performance. Can we add a benchmark + to validate the approach?" + +4. **Escalate if Needed** + "Let's get [architect/senior dev] to weigh in on this." + +5. **Know When to Let Go** + If it's working and not a critical issue, approve it. + Perfection is the enemy of progress. +``` + +## Best Practices + +1. **Review Promptly**: Within 24 hours, ideally same day +2. **Limit PR Size**: 200-400 lines max for effective review +3. **Review in Time Blocks**: 60 minutes max, take breaks +4. **Use Review Tools**: GitHub, GitLab, or dedicated tools +5. **Automate What You Can**: Linters, formatters, security scans +6. **Build Rapport**: Emoji, praise, and empathy matter +7. **Be Available**: Offer to pair on complex issues +8. **Learn from Others**: Review others' review comments + +## Common Pitfalls + +- **Perfectionism**: Blocking PRs for minor style preferences +- **Scope Creep**: "While you're at it, can you also..." +- **Inconsistency**: Different standards for different people +- **Delayed Reviews**: Letting PRs sit for days +- **Ghosting**: Requesting changes then disappearing +- **Rubber Stamping**: Approving without actually reviewing +- **Bike Shedding**: Debating trivial details extensively + +## Templates + +### PR Review Comment Template + +```markdown +## Summary +[Brief overview of what was reviewed] + +## Strengths +- [What was done well] +- [Good patterns or approaches] + +## Required Changes +🔴 [Blocking issue 1] +🔴 [Blocking issue 2] + +## Suggestions +💡 [Improvement 1] +💡 [Improvement 2] + +## Questions +❓ [Clarification needed on X] +❓ [Alternative approach consideration] + +## Verdict +✅ Approve after addressing required changes +``` + +## Resources + +- **references/code-review-best-practices.md**: Comprehensive review guidelines +- **references/common-bugs-checklist.md**: Language-specific bugs to watch for +- **references/security-review-guide.md**: Security-focused review checklist +- **assets/pr-review-template.md**: Standard review comment template +- **assets/review-checklist.md**: Quick reference checklist +- **scripts/pr-analyzer.py**: Analyze PR complexity and suggest reviewers diff --git a/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/assets/pr-review-template.md b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/assets/pr-review-template.md new file mode 100644 index 0000000..5a036b4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/assets/pr-review-template.md @@ -0,0 +1,12 @@ +## Summary +- Scope: +- Overall verdict: + +## Strengths +- + +## Required changes +- + +## Suggestions +- diff --git a/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/assets/review-checklist.md b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/assets/review-checklist.md new file mode 100644 index 0000000..c122834 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/assets/review-checklist.md @@ -0,0 +1,6 @@ +- Intent understood +- Correctness checked +- Tests reviewed +- Security checked +- Performance checked +- Decision recorded diff --git a/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/code-review-best-practices.md b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/code-review-best-practices.md new file mode 100644 index 0000000..65c37bb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/code-review-best-practices.md @@ -0,0 +1,19 @@ +# Code Review Best Practices + +## Default review order +1. Understand intent and scope. +2. Check architecture and correctness. +3. Check tests and failure handling. +4. Check security and performance risks. +5. Leave clear, prioritized comments. + +## Comment severity +- `blocking` - correctness, security, data loss, major maintainability issue +- `important` - should be fixed before merge if practical +- `nit` - polish only + +## Good reviewer habits +- summarize first, +- separate required changes from suggestions, +- quote the code path or failure mode, +- praise good decisions when they matter. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/common-bugs-checklist.md b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/common-bugs-checklist.md new file mode 100644 index 0000000..5e62425 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/common-bugs-checklist.md @@ -0,0 +1,9 @@ +# Common Bugs Checklist + +- null / undefined handling +- off-by-one and empty-input behavior +- race conditions or double-submit paths +- missing authorization checks +- silent error swallowing +- expensive loops or repeated queries +- test gaps on unhappy paths diff --git a/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/security-review-guide.md b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/security-review-guide.md new file mode 100644 index 0000000..d15619f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/references/security-review-guide.md @@ -0,0 +1,12 @@ +# Security Review Guide + +## Check for +- unsanitized input, +- SQL or shell injection, +- insecure deserialization, +- secret leakage, +- missing authz checks, +- unsafe filesystem or network defaults. + +## Review note pattern +`Blocking: this path accepts untrusted input and passes it to X without validation.` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/scripts/pr-analyzer.py b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/scripts/pr-analyzer.py new file mode 100755 index 0000000..86d2b26 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/code-review-excellence/scripts/pr-analyzer.py @@ -0,0 +1,49 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import subprocess +from pathlib import Path + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Summarize git diff size for review planning.') + parser.add_argument('--repo', default='.', help='Repository path') + parser.add_argument('--base', default='HEAD~1', help='Base revision') + parser.add_argument('--head', default='HEAD', help='Head revision') + return parser.parse_args() + + +def main() -> int: + args = parse_args() + repo = Path(args.repo).resolve() + result = subprocess.run( + ['git', '-C', str(repo), 'diff', '--numstat', args.base, args.head], + capture_output=True, + text=True, + check=False, + ) + if result.returncode != 0: + print(result.stderr.strip() or 'git diff failed') + return result.returncode + files = 0 + added = 0 + deleted = 0 + for line in result.stdout.splitlines(): + parts = line.split(' ') + if len(parts) != 3: + continue + a, d, _ = parts + if a.isdigit(): + added += int(a) + if d.isdigit(): + deleted += int(d) + files += 1 + print(f'files={files}') + print(f'added={added}') + print(f'deleted={deleted}') + return 0 + + +if __name__ == '__main__': + raise SystemExit(main()) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/README.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/README.md new file mode 100644 index 0000000..a5d303f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/README.md @@ -0,0 +1,272 @@ +# Command Development Skill + +Comprehensive guidance on creating Claude Code slash commands, including file format, frontmatter options, dynamic arguments, and best practices. + +## Overview + +This skill provides knowledge about: +- Slash command file format and structure +- YAML frontmatter configuration fields +- Dynamic arguments ($ARGUMENTS, $1, $2, etc.) +- File references with @ syntax +- Bash execution with !` syntax +- Command organization and namespacing +- Best practices for command development +- Plugin-specific features (${CLAUDE_PLUGIN_ROOT}, plugin patterns) +- Integration with plugin components (agents, skills, hooks) +- Validation patterns and error handling + +## Skill Structure + +### SKILL.md (~2,470 words) + +Core skill content covering: + +**Fundamentals:** +- Command basics and locations +- File format (Markdown with optional frontmatter) +- YAML frontmatter fields overview +- Dynamic arguments ($ARGUMENTS and positional) +- File references (@ syntax) +- Bash execution (!` syntax) +- Command organization patterns +- Best practices and common patterns +- Troubleshooting + +**Plugin-Specific:** +- ${CLAUDE_PLUGIN_ROOT} environment variable +- Plugin command discovery and organization +- Plugin command patterns (configuration, template, multi-script) +- Integration with plugin components (agents, skills, hooks) +- Validation patterns (argument, file, resource, error handling) + +### References + +Detailed documentation: + +- **frontmatter-reference.md**: Complete YAML frontmatter field specifications + - All field descriptions with types and defaults + - When to use each field + - Examples and best practices + - Validation and common errors + +- **plugin-features-reference.md**: Plugin-specific command features + - Plugin command discovery and organization + - ${CLAUDE_PLUGIN_ROOT} environment variable usage + - Plugin command patterns (configuration, template, multi-script) + - Integration with plugin agents, skills, and hooks + - Validation patterns and error handling + +### Examples + +Practical command examples: + +- **simple-commands.md**: 10 complete command examples + - Code review commands + - Testing commands + - Deployment commands + - Documentation generators + - Git integration commands + - Analysis and research commands + +- **plugin-commands.md**: 10 plugin-specific command examples + - Simple plugin commands with scripts + - Multi-script workflows + - Template-based generation + - Configuration-driven deployment + - Agent and skill integration + - Multi-component workflows + - Validated input commands + - Environment-aware commands + +## When This Skill Triggers + +Claude Code activates this skill when users: +- Ask to "create a slash command" or "add a command" +- Need to "write a custom command" +- Want to "define command arguments" +- Ask about "command frontmatter" or YAML configuration +- Need to "organize commands" or use namespacing +- Want to create commands with file references +- Ask about "bash execution in commands" +- Need command development best practices + +## Progressive Disclosure + +The skill uses progressive disclosure: + +1. **SKILL.md** (~2,470 words): Core concepts, common patterns, and plugin features overview +2. **References** (~13,500 words total): Detailed specifications + - frontmatter-reference.md (~1,200 words) + - plugin-features-reference.md (~1,800 words) + - interactive-commands.md (~2,500 words) + - advanced-workflows.md (~1,700 words) + - testing-strategies.md (~2,200 words) + - documentation-patterns.md (~2,000 words) + - marketplace-considerations.md (~2,200 words) +3. **Examples** (~6,000 words total): Complete working command examples + - simple-commands.md + - plugin-commands.md + +Claude loads references and examples as needed based on task. + +## Command Basics Quick Reference + +### File Format + +```markdown +--- +description: Brief description +argument-hint: [arg1] [arg2] +allowed-tools: Read, Bash(git:*) +--- + +Command prompt content with: +- Arguments: $1, $2, or $ARGUMENTS +- Files: @path/to/file +- Bash: !`command here` +``` + +### Locations + +- **Project**: `.claude/commands/` (shared with team) +- **Personal**: `~/.claude/commands/` (your commands) +- **Plugin**: `plugin-name/commands/` (plugin-specific) + +### Key Features + +**Dynamic arguments:** +- `$ARGUMENTS` - All arguments as single string +- `$1`, `$2`, `$3` - Positional arguments + +**File references:** +- `@path/to/file` - Include file contents + +**Bash execution:** +- `!`command`` - Execute and include output + +## Frontmatter Fields Quick Reference + +| Field | Purpose | Example | +|-------|---------|---------| +| `description` | Brief description for /help | `"Review code for issues"` | +| `allowed-tools` | Restrict tool access | `Read, Bash(git:*)` | +| `model` | Specify model | `sonnet`, `opus`, `haiku` | +| `argument-hint` | Document arguments | `[pr-number] [priority]` | +| `disable-model-invocation` | Manual-only command | `true` | + +## Common Patterns + +### Simple Review Command + +```markdown +--- +description: Review code for issues +--- + +Review this code for quality and potential bugs. +``` + +### Command with Arguments + +```markdown +--- +description: Deploy to environment +argument-hint: [environment] [version] +--- + +Deploy to $1 environment using version $2 +``` + +### Command with File Reference + +```markdown +--- +description: Document file +argument-hint: [file-path] +--- + +Generate documentation for @$1 +``` + +### Command with Bash Execution + +```markdown +--- +description: Show Git status +allowed-tools: Bash(git:*) +--- + +Current status: !`git status` +Recent commits: !`git log --oneline -5` +``` + +## Development Workflow + +1. **Design command:** + - Define purpose and scope + - Determine required arguments + - Identify needed tools + +2. **Create file:** + - Choose appropriate location + - Create `.md` file with command name + - Write basic prompt + +3. **Add frontmatter:** + - Start minimal (just description) + - Add fields as needed (allowed-tools, etc.) + - Document arguments with argument-hint + +4. **Test command:** + - Invoke with `/command-name` + - Verify arguments work + - Check bash execution + - Test file references + +5. **Refine:** + - Improve prompt clarity + - Handle edge cases + - Add examples in comments + - Document requirements + +## Best Practices Summary + +1. **Single responsibility**: One command, one clear purpose +2. **Clear descriptions**: Make discoverable in `/help` +3. **Document arguments**: Always use argument-hint +4. **Minimal tools**: Use most restrictive allowed-tools +5. **Test thoroughly**: Verify all features work +6. **Add comments**: Explain complex logic +7. **Handle errors**: Consider missing arguments/files + +## Status + +**Completed enhancements:** +- ✓ Plugin command patterns (${CLAUDE_PLUGIN_ROOT}, discovery, organization) +- ✓ Integration patterns (agents, skills, hooks coordination) +- ✓ Validation patterns (input, file, resource validation, error handling) + +**Remaining enhancements (in progress):** +- Advanced workflows (multi-step command sequences) +- Testing strategies (how to test commands effectively) +- Documentation patterns (command documentation best practices) +- Marketplace considerations (publishing and distribution) + +## Maintenance + +To update this skill: +1. Keep SKILL.md focused on core fundamentals +2. Move detailed specifications to references/ +3. Add new examples/ for different use cases +4. Update frontmatter when new fields added +5. Ensure imperative/infinitive form throughout +6. Test examples work with current Claude Code + +## Version History + +**v0.1.0** (2025-01-15): +- Initial release with basic command fundamentals +- Frontmatter field reference +- 10 simple command examples +- Ready for plugin-specific pattern additions diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/SKILL.md new file mode 100644 index 0000000..cb3fd8b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/SKILL.md @@ -0,0 +1,835 @@ +--- +name: command-development +description: This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code. +version: 0.2.0 +--- + +# Command Development for Claude Code + +## Overview + +Slash commands are frequently-used prompts defined as Markdown files that Claude executes during interactive sessions. Understanding command structure, frontmatter options, and dynamic features enables creating powerful, reusable workflows. + +**Key concepts:** +- Markdown file format for commands +- YAML frontmatter for configuration +- Dynamic arguments and file references +- Bash execution for context +- Command organization and namespacing + +## Command Basics + +### What is a Slash Command? + +A slash command is a Markdown file containing a prompt that Claude executes when invoked. Commands provide: +- **Reusability**: Define once, use repeatedly +- **Consistency**: Standardize common workflows +- **Sharing**: Distribute across team or projects +- **Efficiency**: Quick access to complex prompts + +### Critical: Commands are Instructions FOR Claude + +**Commands are written for agent consumption, not human consumption.** + +When a user invokes `/command-name`, the command content becomes Claude's instructions. Write commands as directives TO Claude about what to do, not as messages TO the user. + +**Correct approach (instructions for Claude):** +```markdown +Review this code for security vulnerabilities including: +- SQL injection +- XSS attacks +- Authentication issues + +Provide specific line numbers and severity ratings. +``` + +**Incorrect approach (messages to user):** +```markdown +This command will review your code for security issues. +You'll receive a report with vulnerability details. +``` + +The first example tells Claude what to do. The second tells the user what will happen but doesn't instruct Claude. Always use the first approach. + +### Command Locations + +**Project commands** (shared with team): +- Location: `.claude/commands/` +- Scope: Available in specific project +- Label: Shown as "(project)" in `/help` +- Use for: Team workflows, project-specific tasks + +**Personal commands** (available everywhere): +- Location: `~/.claude/commands/` +- Scope: Available in all projects +- Label: Shown as "(user)" in `/help` +- Use for: Personal workflows, cross-project utilities + +**Plugin commands** (bundled with plugins): +- Location: `plugin-name/commands/` +- Scope: Available when plugin installed +- Label: Shown as "(plugin-name)" in `/help` +- Use for: Plugin-specific functionality + +## File Format + +### Basic Structure + +Commands are Markdown files with `.md` extension: + +``` +.claude/commands/ +├── review.md # /review command +├── test.md # /test command +└── deploy.md # /deploy command +``` + +**Simple command:** +```markdown +Review this code for security vulnerabilities including: +- SQL injection +- XSS attacks +- Authentication bypass +- Insecure data handling +``` + +No frontmatter needed for basic commands. + +### With YAML Frontmatter + +Add configuration using YAML frontmatter: + +```markdown +--- +description: Review code for security issues +allowed-tools: Read, Grep, Bash(git:*) +model: sonnet +--- + +Review this code for security vulnerabilities... +``` + +## YAML Frontmatter Fields + +### description + +**Purpose:** Brief description shown in `/help` +**Type:** String +**Default:** First line of command prompt + +```yaml +--- +description: Review pull request for code quality +--- +``` + +**Best practice:** Clear, actionable description (under 60 characters) + +### allowed-tools + +**Purpose:** Specify which tools command can use +**Type:** String or Array +**Default:** Inherits from conversation + +```yaml +--- +allowed-tools: Read, Write, Edit, Bash(git:*) +--- +``` + +**Patterns:** +- `Read, Write, Edit` - Specific tools +- `Bash(git:*)` - Bash with git commands only +- `*` - All tools (rarely needed) + +**Use when:** Command requires specific tool access + +### model + +**Purpose:** Specify model for command execution +**Type:** String (sonnet, opus, haiku) +**Default:** Inherits from conversation + +```yaml +--- +model: haiku +--- +``` + +**Use cases:** +- `haiku` - Fast, simple commands +- `sonnet` - Standard workflows +- `opus` - Complex analysis + +### argument-hint + +**Purpose:** Document expected arguments for autocomplete +**Type:** String +**Default:** None + +```yaml +--- +argument-hint: [pr-number] [priority] [assignee] +--- +``` + +**Benefits:** +- Helps users understand command arguments +- Improves command discovery +- Documents command interface + +### disable-model-invocation + +**Purpose:** Prevent SlashCommand tool from programmatically calling command +**Type:** Boolean +**Default:** false + +```yaml +--- +disable-model-invocation: true +--- +``` + +**Use when:** Command should only be manually invoked + +## Dynamic Arguments + +### Using $ARGUMENTS + +Capture all arguments as single string: + +```markdown +--- +description: Fix issue by number +argument-hint: [issue-number] +--- + +Fix issue #$ARGUMENTS following our coding standards and best practices. +``` + +**Usage:** +``` +> /fix-issue 123 +> /fix-issue 456 +``` + +**Expands to:** +``` +Fix issue #123 following our coding standards... +Fix issue #456 following our coding standards... +``` + +### Using Positional Arguments + +Capture individual arguments with `$1`, `$2`, `$3`, etc.: + +```markdown +--- +description: Review PR with priority and assignee +argument-hint: [pr-number] [priority] [assignee] +--- + +Review pull request #$1 with priority level $2. +After review, assign to $3 for follow-up. +``` + +**Usage:** +``` +> /review-pr 123 high alice +``` + +**Expands to:** +``` +Review pull request #123 with priority level high. +After review, assign to alice for follow-up. +``` + +### Combining Arguments + +Mix positional and remaining arguments: + +```markdown +Deploy $1 to $2 environment with options: $3 +``` + +**Usage:** +``` +> /deploy api staging --force --skip-tests +``` + +**Expands to:** +``` +Deploy api to staging environment with options: --force --skip-tests +``` + +## File References + +### Using @ Syntax + +Include file contents in command: + +```markdown +--- +description: Review specific file +argument-hint: [file-path] +--- + +Review @$1 for: +- Code quality +- Best practices +- Potential bugs +``` + +**Usage:** +``` +> /review-file src/api/users.ts +``` + +**Effect:** Claude reads `src/api/users.ts` before processing command + +### Multiple File References + +Reference multiple files: + +```markdown +Compare @src/old-version.js with @src/new-version.js + +Identify: +- Breaking changes +- New features +- Bug fixes +``` + +### Static File References + +Reference known files without arguments: + +```markdown +Review @package.json and @tsconfig.json for consistency + +Ensure: +- TypeScript version matches +- Dependencies are aligned +- Build configuration is correct +``` + +## Bash Execution in Commands + +Commands can execute bash commands inline to dynamically gather context before Claude processes the command. This is useful for including repository state, environment information, or project-specific context. + +**When to use:** +- Include dynamic context (git status, environment vars, etc.) +- Gather project/repository state +- Build context-aware workflows + +**Implementation details:** +For complete syntax, examples, and best practices, see `references/plugin-features-reference.md` section on bash execution. The reference includes the exact syntax and multiple working examples to avoid execution issues + +## Command Organization + +### Flat Structure + +Simple organization for small command sets: + +``` +.claude/commands/ +├── build.md +├── test.md +├── deploy.md +├── review.md +└── docs.md +``` + +**Use when:** 5-15 commands, no clear categories + +### Namespaced Structure + +Organize commands in subdirectories: + +``` +.claude/commands/ +├── ci/ +│ ├── build.md # /build (project:ci) +│ ├── test.md # /test (project:ci) +│ └── lint.md # /lint (project:ci) +├── git/ +│ ├── commit.md # /commit (project:git) +│ └── pr.md # /pr (project:git) +└── docs/ + ├── generate.md # /generate (project:docs) + └── publish.md # /publish (project:docs) +``` + +**Benefits:** +- Logical grouping by category +- Namespace shown in `/help` +- Easier to find related commands + +**Use when:** 15+ commands, clear categories + +## Best Practices + +### Command Design + +1. **Single responsibility:** One command, one task +2. **Clear descriptions:** Self-explanatory in `/help` +3. **Explicit dependencies:** Use `allowed-tools` when needed +4. **Document arguments:** Always provide `argument-hint` +5. **Consistent naming:** Use verb-noun pattern (review-pr, fix-issue) + +### Argument Handling + +1. **Validate arguments:** Check for required arguments in prompt +2. **Provide defaults:** Suggest defaults when arguments missing +3. **Document format:** Explain expected argument format +4. **Handle edge cases:** Consider missing or invalid arguments + +```markdown +--- +argument-hint: [pr-number] +--- + +$IF($1, + Review PR #$1, + Please provide a PR number. Usage: /review-pr [number] +) +``` + +### File References + +1. **Explicit paths:** Use clear file paths +2. **Check existence:** Handle missing files gracefully +3. **Relative paths:** Use project-relative paths +4. **Glob support:** Consider using Glob tool for patterns + +### Bash Commands + +1. **Limit scope:** Use `Bash(git:*)` not `Bash(*)` +2. **Safe commands:** Avoid destructive operations +3. **Handle errors:** Consider command failures +4. **Keep fast:** Long-running commands slow invocation + +### Documentation + +1. **Add comments:** Explain complex logic +2. **Provide examples:** Show usage in comments +3. **List requirements:** Document dependencies +4. **Version commands:** Note breaking changes + +```markdown +--- +description: Deploy application to environment +argument-hint: [environment] [version] +--- + + + +Deploy application to $1 environment using version $2... +``` + +## Common Patterns + +### Review Pattern + +```markdown +--- +description: Review code changes +allowed-tools: Read, Bash(git:*) +--- + +Files changed: !`git diff --name-only` + +Review each file for: +1. Code quality and style +2. Potential bugs or issues +3. Test coverage +4. Documentation needs + +Provide specific feedback for each file. +``` + +### Testing Pattern + +```markdown +--- +description: Run tests for specific file +argument-hint: [test-file] +allowed-tools: Bash(npm:*) +--- + +Run tests: !`npm test $1` + +Analyze results and suggest fixes for failures. +``` + +### Documentation Pattern + +```markdown +--- +description: Generate documentation for file +argument-hint: [source-file] +--- + +Generate comprehensive documentation for @$1 including: +- Function/class descriptions +- Parameter documentation +- Return value descriptions +- Usage examples +- Edge cases and errors +``` + +### Workflow Pattern + +```markdown +--- +description: Complete PR workflow +argument-hint: [pr-number] +allowed-tools: Bash(gh:*), Read +--- + +PR #$1 Workflow: + +1. Fetch PR: !`gh pr view $1` +2. Review changes +3. Run checks +4. Approve or request changes +``` + +## Troubleshooting + +**Command not appearing:** +- Check file is in correct directory +- Verify `.md` extension present +- Ensure valid Markdown format +- Restart Claude Code + +**Arguments not working:** +- Verify `$1`, `$2` syntax correct +- Check `argument-hint` matches usage +- Ensure no extra spaces + +**Bash execution failing:** +- Check `allowed-tools` includes Bash +- Verify command syntax in backticks +- Test command in terminal first +- Check for required permissions + +**File references not working:** +- Verify `@` syntax correct +- Check file path is valid +- Ensure Read tool allowed +- Use absolute or project-relative paths + +## Plugin-Specific Features + +### CLAUDE_PLUGIN_ROOT Variable + +Plugin commands have access to `${CLAUDE_PLUGIN_ROOT}`, an environment variable that resolves to the plugin's absolute path. + +**Purpose:** +- Reference plugin files portably +- Execute plugin scripts +- Load plugin configuration +- Access plugin templates + +**Basic usage:** + +```markdown +--- +description: Analyze using plugin script +allowed-tools: Bash(node:*) +--- + +Run analysis: !`node ${CLAUDE_PLUGIN_ROOT}/scripts/analyze.js $1` + +Review results and report findings. +``` + +**Common patterns:** + +```markdown +# Execute plugin script +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/script.sh` + +# Load plugin configuration +@${CLAUDE_PLUGIN_ROOT}/config/settings.json + +# Use plugin template +@${CLAUDE_PLUGIN_ROOT}/templates/report.md + +# Access plugin resources +@${CLAUDE_PLUGIN_ROOT}/docs/reference.md +``` + +**Why use it:** +- Works across all installations +- Portable between systems +- No hardcoded paths needed +- Essential for multi-file plugins + +### Plugin Command Organization + +Plugin commands discovered automatically from `commands/` directory: + +``` +plugin-name/ +├── commands/ +│ ├── foo.md # /foo (plugin:plugin-name) +│ ├── bar.md # /bar (plugin:plugin-name) +│ └── utils/ +│ └── helper.md # /helper (plugin:plugin-name:utils) +└── plugin.json +``` + +**Namespace benefits:** +- Logical command grouping +- Shown in `/help` output +- Avoid name conflicts +- Organize related commands + +**Naming conventions:** +- Use descriptive action names +- Avoid generic names (test, run) +- Consider plugin-specific prefix +- Use hyphens for multi-word names + +### Plugin Command Patterns + +**Configuration-based pattern:** + +```markdown +--- +description: Deploy using plugin configuration +argument-hint: [environment] +allowed-tools: Read, Bash(*) +--- + +Load configuration: @${CLAUDE_PLUGIN_ROOT}/config/$1-deploy.json + +Deploy to $1 using configuration settings. +Monitor deployment and report status. +``` + +**Template-based pattern:** + +```markdown +--- +description: Generate docs from template +argument-hint: [component] +--- + +Template: @${CLAUDE_PLUGIN_ROOT}/templates/docs.md + +Generate documentation for $1 following template structure. +``` + +**Multi-script pattern:** + +```text +--- +description: Complete build workflow +allowed-tools: Bash(*) +--- + +# Example commands (remove # to use): +# Build: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/build.sh` +# Test: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/test.sh` +# Package: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/package.sh` + +Review outputs and report workflow status. +``` + +**See `references/plugin-features-reference.md` for detailed patterns.** + +## Integration with Plugin Components + +Commands can integrate with other plugin components for powerful workflows. + +### Agent Integration + +Launch plugin agents for complex tasks: + +```markdown +--- +description: Deep code review +argument-hint: [file-path] +--- + +Initiate comprehensive review of @$1 using the code-reviewer agent. + +The agent will analyze: +- Code structure +- Security issues +- Performance +- Best practices + +Agent uses plugin resources: +- ${CLAUDE_PLUGIN_ROOT}/config/rules.json +- ${CLAUDE_PLUGIN_ROOT}/checklists/review.md +``` + +**Key points:** +- Agent must exist in `plugin/agents/` directory +- Claude uses Task tool to launch agent +- Document agent capabilities +- Reference plugin resources agent uses + +### Skill Integration + +Leverage plugin skills for specialized knowledge: + +```markdown +--- +description: Document API with standards +argument-hint: [api-file] +--- + +Document API in @$1 following plugin standards. + +Use the api-docs-standards skill to ensure: +- Complete endpoint documentation +- Consistent formatting +- Example quality +- Error documentation + +Generate production-ready API docs. +``` + +**Key points:** +- Skill must exist in `plugin/skills/` directory +- Mention skill name to trigger invocation +- Document skill purpose +- Explain what skill provides + +### Hook Coordination + +Design commands that work with plugin hooks: +- Commands can prepare state for hooks to process +- Hooks execute automatically on tool events +- Commands should document expected hook behavior +- Guide Claude on interpreting hook output + +See `references/plugin-features-reference.md` for examples of commands that coordinate with hooks + +### Multi-Component Workflows + +Combine agents, skills, and scripts: + +```markdown +--- +description: Comprehensive review workflow +argument-hint: [file] +allowed-tools: Bash(node:*), Read +--- + +Target: @$1 + +Phase 1 - Static Analysis: +!`node ${CLAUDE_PLUGIN_ROOT}/scripts/lint.js $1` + +Phase 2 - Deep Review: +Launch code-reviewer agent for detailed analysis. + +Phase 3 - Standards Check: +Use coding-standards skill for validation. + +Phase 4 - Report: +Template: @${CLAUDE_PLUGIN_ROOT}/templates/review.md + +Compile findings into report following template. +``` + +**When to use:** +- Complex multi-step workflows +- Leverage multiple plugin capabilities +- Require specialized analysis +- Need structured outputs + +## Validation Patterns + +Commands should validate inputs and resources before processing. + +### Argument Validation + +```markdown +--- +description: Deploy with validation +argument-hint: [environment] +--- + +Validate environment: !`echo "$1" | grep -E "^(dev|staging|prod)$" || echo "INVALID"` + +If $1 is valid environment: + Deploy to $1 +Otherwise: + Explain valid environments: dev, staging, prod + Show usage: /deploy [environment] +``` + +### File Existence Checks + +```markdown +--- +description: Process configuration +argument-hint: [config-file] +--- + +Check file exists: !`test -f $1 && echo "EXISTS" || echo "MISSING"` + +If file exists: + Process configuration: @$1 +Otherwise: + Explain where to place config file + Show expected format + Provide example configuration +``` + +### Plugin Resource Validation + +```markdown +--- +description: Run plugin analyzer +allowed-tools: Bash(test:*) +--- + +Validate plugin setup: +- Script: !`test -x ${CLAUDE_PLUGIN_ROOT}/bin/analyze && echo "✓" || echo "✗"` +- Config: !`test -f ${CLAUDE_PLUGIN_ROOT}/config.json && echo "✓" || echo "✗"` + +If all checks pass, run analysis. +Otherwise, report missing components. +``` + +### Error Handling + +```markdown +--- +description: Build with error handling +allowed-tools: Bash(*) +--- + +Execute build: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/build.sh 2>&1 || echo "BUILD_FAILED"` + +If build succeeded: + Report success and output location +If build failed: + Analyze error output + Suggest likely causes + Provide troubleshooting steps +``` + +**Best practices:** +- Validate early in command +- Provide helpful error messages +- Suggest corrective actions +- Handle edge cases gracefully + +--- + +For detailed frontmatter field specifications, see `references/frontmatter-reference.md`. +For plugin-specific features and patterns, see `references/plugin-features-reference.md`. +For command pattern examples, see `examples/` directory. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/examples/plugin-commands.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/examples/plugin-commands.md new file mode 100644 index 0000000..e14ef4d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/examples/plugin-commands.md @@ -0,0 +1,557 @@ +# Plugin Command Examples + +Practical examples of commands designed for Claude Code plugins, demonstrating plugin-specific patterns and features. + +## Table of Contents + +1. [Simple Plugin Command](#1-simple-plugin-command) +2. [Script-Based Analysis](#2-script-based-analysis) +3. [Template-Based Generation](#3-template-based-generation) +4. [Multi-Script Workflow](#4-multi-script-workflow) +5. [Configuration-Driven Deployment](#5-configuration-driven-deployment) +6. [Agent Integration](#6-agent-integration) +7. [Skill Integration](#7-skill-integration) +8. [Multi-Component Workflow](#8-multi-component-workflow) +9. [Validated Input Command](#9-validated-input-command) +10. [Environment-Aware Command](#10-environment-aware-command) + +--- + +## 1. Simple Plugin Command + +**Use case:** Basic command that uses plugin script + +**File:** `commands/analyze.md` + +```markdown +--- +description: Analyze code quality using plugin tools +argument-hint: [file-path] +allowed-tools: Bash(node:*), Read +--- + +Analyze @$1 using plugin's quality checker: + +!`node ${CLAUDE_PLUGIN_ROOT}/scripts/quality-check.js $1` + +Review the analysis output and provide: +1. Summary of findings +2. Priority issues to address +3. Suggested improvements +4. Code quality score interpretation +``` + +**Key features:** +- Uses `${CLAUDE_PLUGIN_ROOT}` for portable path +- Combines file reference with script execution +- Simple single-purpose command + +--- + +## 2. Script-Based Analysis + +**Use case:** Run comprehensive analysis using multiple plugin scripts + +**File:** `commands/full-audit.md` + +```markdown +--- +description: Complete code audit using plugin suite +argument-hint: [directory] +allowed-tools: Bash(*) +model: sonnet +--- + +Running complete audit on $1: + +**Security scan:** +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/security-scan.sh $1` + +**Performance analysis:** +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/perf-analyze.sh $1` + +**Best practices check:** +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/best-practices.sh $1` + +Analyze all results and create comprehensive report including: +- Critical issues requiring immediate attention +- Performance optimization opportunities +- Security vulnerabilities and fixes +- Overall health score and recommendations +``` + +**Key features:** +- Multiple script executions +- Organized output sections +- Comprehensive workflow +- Clear reporting structure + +--- + +## 3. Template-Based Generation + +**Use case:** Generate documentation following plugin template + +**File:** `commands/gen-api-docs.md` + +```markdown +--- +description: Generate API documentation from template +argument-hint: [api-file] +--- + +Template structure: @${CLAUDE_PLUGIN_ROOT}/templates/api-documentation.md + +API implementation: @$1 + +Generate complete API documentation following the template format above. + +Ensure documentation includes: +- Endpoint descriptions with HTTP methods +- Request/response schemas +- Authentication requirements +- Error codes and handling +- Usage examples with curl commands +- Rate limiting information + +Format output as markdown suitable for README or docs site. +``` + +**Key features:** +- Uses plugin template +- Combines template with source file +- Standardized output format +- Clear documentation structure + +--- + +## 4. Multi-Script Workflow + +**Use case:** Orchestrate build, test, and deploy workflow + +**File:** `commands/release.md` + +```markdown +--- +description: Execute complete release workflow +argument-hint: [version] +allowed-tools: Bash(*), Read +--- + +Executing release workflow for version $1: + +**Step 1 - Pre-release validation:** +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/pre-release-check.sh $1` + +**Step 2 - Build artifacts:** +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/build-release.sh $1` + +**Step 3 - Run test suite:** +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/run-tests.sh` + +**Step 4 - Package release:** +!`bash ${CLAUDE_PLUGIN_ROOT}/scripts/package.sh $1` + +Review all step outputs and report: +1. Any failures or warnings +2. Build artifacts location +3. Test results summary +4. Next steps for deployment +5. Rollback plan if needed +``` + +**Key features:** +- Multi-step workflow +- Sequential script execution +- Clear step numbering +- Comprehensive reporting + +--- + +## 5. Configuration-Driven Deployment + +**Use case:** Deploy using environment-specific plugin configuration + +**File:** `commands/deploy.md` + +```markdown +--- +description: Deploy application to environment +argument-hint: [environment] +allowed-tools: Read, Bash(*) +--- + +Deployment configuration for $1: @${CLAUDE_PLUGIN_ROOT}/config/$1-deploy.json + +Current git state: !`git rev-parse --short HEAD` + +Build info: !`cat package.json | grep -E '(name|version)'` + +Execute deployment to $1 environment using configuration above. + +Deployment checklist: +1. Validate configuration settings +2. Build application for $1 +3. Run pre-deployment tests +4. Deploy to target environment +5. Run smoke tests +6. Verify deployment success +7. Update deployment log + +Report deployment status and any issues encountered. +``` + +**Key features:** +- Environment-specific configuration +- Dynamic config file loading +- Pre-deployment validation +- Structured checklist + +--- + +## 6. Agent Integration + +**Use case:** Command that launches plugin agent for complex task + +**File:** `commands/deep-review.md` + +```markdown +--- +description: Deep code review using plugin agent +argument-hint: [file-or-directory] +--- + +Initiate comprehensive code review of @$1 using the code-reviewer agent. + +The agent will perform: +1. **Static analysis** - Check for code smells and anti-patterns +2. **Security audit** - Identify potential vulnerabilities +3. **Performance review** - Find optimization opportunities +4. **Best practices** - Ensure code follows standards +5. **Documentation check** - Verify adequate documentation + +The agent has access to: +- Plugin's linting rules: ${CLAUDE_PLUGIN_ROOT}/config/lint-rules.json +- Security checklist: ${CLAUDE_PLUGIN_ROOT}/checklists/security.md +- Performance guidelines: ${CLAUDE_PLUGIN_ROOT}/docs/performance.md + +Note: This uses the Task tool to launch the plugin's code-reviewer agent for thorough analysis. +``` + +**Key features:** +- Delegates to plugin agent +- Documents agent capabilities +- References plugin resources +- Clear scope definition + +--- + +## 7. Skill Integration + +**Use case:** Command that leverages plugin skill for specialized knowledge + +**File:** `commands/document-api.md` + +```markdown +--- +description: Document API following plugin standards +argument-hint: [api-file] +--- + +API source code: @$1 + +Generate API documentation following the plugin's API documentation standards. + +Use the api-documentation-standards skill to ensure: +- **OpenAPI compliance** - Follow OpenAPI 3.0 specification +- **Consistent formatting** - Use plugin's documentation style +- **Complete coverage** - Document all endpoints and schemas +- **Example quality** - Provide realistic usage examples +- **Error documentation** - Cover all error scenarios + +The skill provides: +- Standard documentation templates +- API documentation best practices +- Common patterns for this codebase +- Quality validation criteria + +Generate production-ready API documentation. +``` + +**Key features:** +- Invokes plugin skill by name +- Documents skill purpose +- Clear expectations +- Leverages skill knowledge + +--- + +## 8. Multi-Component Workflow + +**Use case:** Complex workflow using agents, skills, and scripts + +**File:** `commands/complete-review.md` + +```markdown +--- +description: Comprehensive review using all plugin components +argument-hint: [file-path] +allowed-tools: Bash(node:*), Read +--- + +Target file: @$1 + +Execute comprehensive review workflow: + +**Phase 1: Automated Analysis** +Run plugin analyzer: !`node ${CLAUDE_PLUGIN_ROOT}/scripts/analyze.js $1` + +**Phase 2: Deep Review (Agent)** +Launch the code-quality-reviewer agent for detailed analysis. +Agent will examine: +- Code structure and organization +- Error handling patterns +- Testing coverage +- Documentation quality + +**Phase 3: Standards Check (Skill)** +Use the coding-standards skill to validate: +- Naming conventions +- Code formatting +- Best practices adherence +- Framework-specific patterns + +**Phase 4: Report Generation** +Template: @${CLAUDE_PLUGIN_ROOT}/templates/review-report.md + +Compile all findings into comprehensive report following template. + +**Phase 5: Recommendations** +Generate prioritized action items: +1. Critical issues (must fix) +2. Important improvements (should fix) +3. Nice-to-have enhancements (could fix) + +Include specific file locations and suggested changes for each item. +``` + +**Key features:** +- Multi-phase workflow +- Combines scripts, agents, skills +- Template-based reporting +- Prioritized outputs + +--- + +## 9. Validated Input Command + +**Use case:** Command with input validation and error handling + +**File:** `commands/build-env.md` + +```markdown +--- +description: Build for specific environment with validation +argument-hint: [environment] +allowed-tools: Bash(*) +--- + +Validate environment argument: !`echo "$1" | grep -E "^(dev|staging|prod)$" && echo "VALID" || echo "INVALID"` + +Check build script exists: !`test -x ${CLAUDE_PLUGIN_ROOT}/scripts/build.sh && echo "EXISTS" || echo "MISSING"` + +Verify configuration available: !`test -f ${CLAUDE_PLUGIN_ROOT}/config/$1.json && echo "FOUND" || echo "NOT_FOUND"` + +If all validations pass: + +**Configuration:** @${CLAUDE_PLUGIN_ROOT}/config/$1.json + +**Execute build:** !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/build.sh $1 2>&1` + +**Validation results:** !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/validate-build.sh $1 2>&1` + +Report build status and any issues. + +If validations fail: +- Explain which validation failed +- Provide expected values/locations +- Suggest corrective actions +- Document troubleshooting steps +``` + +**Key features:** +- Input validation +- Resource existence checks +- Error handling +- Helpful error messages +- Graceful failure handling + +--- + +## 10. Environment-Aware Command + +**Use case:** Command that adapts behavior based on environment + +**File:** `commands/run-checks.md` + +```markdown +--- +description: Run environment-appropriate checks +argument-hint: [environment] +allowed-tools: Bash(*), Read +--- + +Environment: $1 + +Load environment configuration: @${CLAUDE_PLUGIN_ROOT}/config/$1-checks.json + +Determine check level: !`echo "$1" | grep -E "^prod$" && echo "FULL" || echo "BASIC"` + +**For production environment:** +- Full test suite: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/test-full.sh` +- Security scan: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/security-scan.sh` +- Performance audit: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/perf-check.sh` +- Compliance check: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/compliance.sh` + +**For non-production environments:** +- Basic tests: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/test-basic.sh` +- Quick lint: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/lint.sh` + +Analyze results based on environment requirements: + +**Production:** All checks must pass with zero critical issues +**Staging:** No critical issues, warnings acceptable +**Development:** Focus on blocking issues only + +Report status and recommend proceed/block decision. +``` + +**Key features:** +- Environment-aware logic +- Conditional execution +- Different validation levels +- Appropriate reporting per environment + +--- + +## Common Patterns Summary + +### Pattern: Plugin Script Execution +```markdown +!`node ${CLAUDE_PLUGIN_ROOT}/scripts/script-name.js $1` +``` +Use for: Running plugin-provided Node.js scripts + +### Pattern: Plugin Configuration Loading +```markdown +@${CLAUDE_PLUGIN_ROOT}/config/config-name.json +``` +Use for: Loading plugin configuration files + +### Pattern: Plugin Template Usage +```markdown +@${CLAUDE_PLUGIN_ROOT}/templates/template-name.md +``` +Use for: Using plugin templates for generation + +### Pattern: Agent Invocation +```markdown +Launch the [agent-name] agent for [task description]. +``` +Use for: Delegating complex tasks to plugin agents + +### Pattern: Skill Reference +```markdown +Use the [skill-name] skill to ensure [requirements]. +``` +Use for: Leveraging plugin skills for specialized knowledge + +### Pattern: Input Validation +```markdown +Validate input: !`echo "$1" | grep -E "^pattern$" && echo "OK" || echo "ERROR"` +``` +Use for: Validating command arguments + +### Pattern: Resource Validation +```markdown +Check exists: !`test -f ${CLAUDE_PLUGIN_ROOT}/path/file && echo "YES" || echo "NO"` +``` +Use for: Verifying required plugin files exist + +--- + +## Development Tips + +### Testing Plugin Commands + +1. **Test with plugin installed:** + ```bash + cd /path/to/plugin + claude /command-name args + ``` + +2. **Verify ${CLAUDE_PLUGIN_ROOT} expansion:** + ```bash + # Add debug output to command + !`echo "Plugin root: ${CLAUDE_PLUGIN_ROOT}"` + ``` + +3. **Test across different working directories:** + ```bash + cd /tmp && claude /command-name + cd /other/project && claude /command-name + ``` + +4. **Validate resource availability:** + ```bash + # Check all plugin resources exist + !`ls -la ${CLAUDE_PLUGIN_ROOT}/scripts/` + !`ls -la ${CLAUDE_PLUGIN_ROOT}/config/` + ``` + +### Common Mistakes to Avoid + +1. **Using relative paths instead of ${CLAUDE_PLUGIN_ROOT}:** + ```markdown + # Wrong + !`node ./scripts/analyze.js` + + # Correct + !`node ${CLAUDE_PLUGIN_ROOT}/scripts/analyze.js` + ``` + +2. **Forgetting to allow required tools:** + ```markdown + # Missing allowed-tools + !`bash script.sh` # Will fail without Bash permission + + # Correct + --- + allowed-tools: Bash(*) + --- + !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/script.sh` + ``` + +3. **Not validating inputs:** + ```markdown + # Risky - no validation + Deploy to $1 environment + + # Better - with validation + Validate: !`echo "$1" | grep -E "^(dev|staging|prod)$" || echo "INVALID"` + Deploy to $1 environment (if valid) + ``` + +4. **Hardcoding plugin paths:** + ```markdown + # Wrong - breaks on different installations + @/home/user/.claude/plugins/my-plugin/config.json + + # Correct - works everywhere + @${CLAUDE_PLUGIN_ROOT}/config.json + ``` + +--- + +For detailed plugin-specific features, see `references/plugin-features-reference.md`. +For general command development, see main `SKILL.md`. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/examples/simple-commands.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/examples/simple-commands.md new file mode 100644 index 0000000..2348239 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/examples/simple-commands.md @@ -0,0 +1,504 @@ +# Simple Command Examples + +Basic slash command patterns for common use cases. + +**Important:** All examples below are written as instructions FOR Claude (agent consumption), not messages TO users. Commands tell Claude what to do, not tell users what will happen. + +## Example 1: Code Review Command + +**File:** `.claude/commands/review.md` + +```markdown +--- +description: Review code for quality and issues +allowed-tools: Read, Bash(git:*) +--- + +Review the code in this repository for: + +1. **Code Quality:** + - Readability and maintainability + - Consistent style and formatting + - Appropriate abstraction levels + +2. **Potential Issues:** + - Logic errors or bugs + - Edge cases not handled + - Performance concerns + +3. **Best Practices:** + - Design patterns used correctly + - Error handling present + - Documentation adequate + +Provide specific feedback with file and line references. +``` + +**Usage:** +``` +> /review +``` + +--- + +## Example 2: Security Review Command + +**File:** `.claude/commands/security-review.md` + +```markdown +--- +description: Review code for security vulnerabilities +allowed-tools: Read, Grep +model: sonnet +--- + +Perform comprehensive security review checking for: + +**Common Vulnerabilities:** +- SQL injection risks +- Cross-site scripting (XSS) +- Authentication/authorization issues +- Insecure data handling +- Hardcoded secrets or credentials + +**Security Best Practices:** +- Input validation present +- Output encoding correct +- Secure defaults used +- Error messages safe +- Logging appropriate (no sensitive data) + +For each issue found: +- File and line number +- Severity (Critical/High/Medium/Low) +- Description of vulnerability +- Recommended fix + +Prioritize issues by severity. +``` + +**Usage:** +``` +> /security-review +``` + +--- + +## Example 3: Test Command with File Argument + +**File:** `.claude/commands/test-file.md` + +```markdown +--- +description: Run tests for specific file +argument-hint: [test-file] +allowed-tools: Bash(npm:*), Bash(jest:*) +--- + +Run tests for $1: + +Test execution: !`npm test $1` + +Analyze results: +- Tests passed/failed +- Code coverage +- Performance issues +- Flaky tests + +If failures found, suggest fixes based on error messages. +``` + +**Usage:** +``` +> /test-file src/utils/helpers.test.ts +``` + +--- + +## Example 4: Documentation Generator + +**File:** `.claude/commands/document.md` + +```markdown +--- +description: Generate documentation for file +argument-hint: [source-file] +--- + +Generate comprehensive documentation for @$1 + +Include: + +**Overview:** +- Purpose and responsibility +- Main functionality +- Dependencies + +**API Documentation:** +- Function/method signatures +- Parameter descriptions with types +- Return values with types +- Exceptions/errors thrown + +**Usage Examples:** +- Basic usage +- Common patterns +- Edge cases + +**Implementation Notes:** +- Algorithm complexity +- Performance considerations +- Known limitations + +Format as Markdown suitable for project documentation. +``` + +**Usage:** +``` +> /document src/api/users.ts +``` + +--- + +## Example 5: Git Status Summary + +**File:** `.claude/commands/git-status.md` + +```markdown +--- +description: Summarize Git repository status +allowed-tools: Bash(git:*) +--- + +Repository Status Summary: + +**Current Branch:** !`git branch --show-current` + +**Status:** !`git status --short` + +**Recent Commits:** !`git log --oneline -5` + +**Remote Status:** !`git fetch && git status -sb` + +Provide: +- Summary of changes +- Suggested next actions +- Any warnings or issues +``` + +**Usage:** +``` +> /git-status +``` + +--- + +## Example 6: Deployment Command + +**File:** `.claude/commands/deploy.md` + +```markdown +--- +description: Deploy to specified environment +argument-hint: [environment] [version] +allowed-tools: Bash(kubectl:*), Read +--- + +Deploy to $1 environment using version $2 + +**Pre-deployment Checks:** +1. Verify $1 configuration exists +2. Check version $2 is valid +3. Verify cluster accessibility: !`kubectl cluster-info` + +**Deployment Steps:** +1. Update deployment manifest with version $2 +2. Apply configuration to $1 +3. Monitor rollout status +4. Verify pod health +5. Run smoke tests + +**Rollback Plan:** +Document current version for rollback if issues occur. + +Proceed with deployment? (yes/no) +``` + +**Usage:** +``` +> /deploy staging v1.2.3 +``` + +--- + +## Example 7: Comparison Command + +**File:** `.claude/commands/compare-files.md` + +```markdown +--- +description: Compare two files +argument-hint: [file1] [file2] +--- + +Compare @$1 with @$2 + +**Analysis:** + +1. **Differences:** + - Lines added + - Lines removed + - Lines modified + +2. **Functional Changes:** + - Breaking changes + - New features + - Bug fixes + - Refactoring + +3. **Impact:** + - Affected components + - Required updates elsewhere + - Migration requirements + +4. **Recommendations:** + - Code review focus areas + - Testing requirements + - Documentation updates needed + +Present as structured comparison report. +``` + +**Usage:** +``` +> /compare-files src/old-api.ts src/new-api.ts +``` + +--- + +## Example 8: Quick Fix Command + +**File:** `.claude/commands/quick-fix.md` + +```markdown +--- +description: Quick fix for common issues +argument-hint: [issue-description] +model: haiku +--- + +Quickly fix: $ARGUMENTS + +**Approach:** +1. Identify the issue +2. Find relevant code +3. Propose fix +4. Explain solution + +Focus on: +- Simple, direct solution +- Minimal changes +- Following existing patterns +- No breaking changes + +Provide code changes with file paths and line numbers. +``` + +**Usage:** +``` +> /quick-fix button not responding to clicks +> /quick-fix typo in error message +``` + +--- + +## Example 9: Research Command + +**File:** `.claude/commands/research.md` + +```markdown +--- +description: Research best practices for topic +argument-hint: [topic] +model: sonnet +--- + +Research best practices for: $ARGUMENTS + +**Coverage:** + +1. **Current State:** + - How we currently handle this + - Existing implementations + +2. **Industry Standards:** + - Common patterns + - Recommended approaches + - Tools and libraries + +3. **Comparison:** + - Our approach vs standards + - Gaps or improvements needed + - Migration considerations + +4. **Recommendations:** + - Concrete action items + - Priority and effort estimates + - Resources for implementation + +Provide actionable guidance based on research. +``` + +**Usage:** +``` +> /research error handling in async operations +> /research API authentication patterns +``` + +--- + +## Example 10: Explain Code Command + +**File:** `.claude/commands/explain.md` + +```markdown +--- +description: Explain how code works +argument-hint: [file-or-function] +--- + +Explain @$1 in detail + +**Explanation Structure:** + +1. **Overview:** + - What it does + - Why it exists + - How it fits in system + +2. **Step-by-Step:** + - Line-by-line walkthrough + - Key algorithms or logic + - Important details + +3. **Inputs and Outputs:** + - Parameters and types + - Return values + - Side effects + +4. **Edge Cases:** + - Error handling + - Special cases + - Limitations + +5. **Usage Examples:** + - How to call it + - Common patterns + - Integration points + +Explain at level appropriate for junior engineer. +``` + +**Usage:** +``` +> /explain src/utils/cache.ts +> /explain AuthService.login +``` + +--- + +## Key Patterns + +### Pattern 1: Read-Only Analysis + +```markdown +--- +allowed-tools: Read, Grep +--- + +Analyze but don't modify... +``` + +**Use for:** Code review, documentation, analysis + +### Pattern 2: Git Operations + +```markdown +--- +allowed-tools: Bash(git:*) +--- + +!`git status` +Analyze and suggest... +``` + +**Use for:** Repository status, commit analysis + +### Pattern 3: Single Argument + +```markdown +--- +argument-hint: [target] +--- + +Process $1... +``` + +**Use for:** File operations, targeted actions + +### Pattern 4: Multiple Arguments + +```markdown +--- +argument-hint: [source] [target] [options] +--- + +Process $1 to $2 with $3... +``` + +**Use for:** Workflows, deployments, comparisons + +### Pattern 5: Fast Execution + +```markdown +--- +model: haiku +--- + +Quick simple task... +``` + +**Use for:** Simple, repetitive commands + +### Pattern 6: File Comparison + +```markdown +Compare @$1 with @$2... +``` + +**Use for:** Diff analysis, migration planning + +### Pattern 7: Context Gathering + +```markdown +--- +allowed-tools: Bash(git:*), Read +--- + +Context: !`git status` +Files: @file1 @file2 + +Analyze... +``` + +**Use for:** Informed decision making + +## Tips for Writing Simple Commands + +1. **Start basic:** Single responsibility, clear purpose +2. **Add complexity gradually:** Start without frontmatter +3. **Test incrementally:** Verify each feature works +4. **Use descriptive names:** Command name should indicate purpose +5. **Document arguments:** Always use argument-hint +6. **Provide examples:** Show usage in comments +7. **Handle errors:** Consider missing arguments or files diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/advanced-workflows.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/advanced-workflows.md new file mode 100644 index 0000000..5e0d7b1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/advanced-workflows.md @@ -0,0 +1,722 @@ +# Advanced Workflow Patterns + +Multi-step command sequences and composition patterns for complex workflows. + +## Overview + +Advanced workflows combine multiple commands, coordinate state across invocations, and create sophisticated automation sequences. These patterns enable building complex functionality from simple command building blocks. + +## Multi-Step Command Patterns + +### Sequential Workflow Command + +Commands that guide users through multi-step processes: + +```markdown +--- +description: Complete PR review workflow +argument-hint: [pr-number] +allowed-tools: Bash(gh:*), Read, Grep +--- + +# PR Review Workflow for #$1 + +## Step 1: Fetch PR Details +!`gh pr view $1 --json title,body,author,files` + +## Step 2: Review Files +Files changed: !`gh pr diff $1 --name-only` + +For each file: +- Check code quality +- Verify tests exist +- Review documentation + +## Step 3: Run Checks +Test status: !`gh pr checks $1` + +Verify: +- All tests passing +- No merge conflicts +- CI/CD successful + +## Step 4: Provide Feedback + +Summarize: +- Issues found (critical/minor) +- Suggestions for improvement +- Approval recommendation + +Would you like to: +1. Approve PR +2. Request changes +3. Leave comments only + +Reply with your choice and I'll help complete the action. +``` + +**Key features:** +- Numbered steps for clarity +- Bash execution for context +- Decision points for user input +- Next action suggestions + +### State-Carrying Workflow + +Commands that maintain state between invocations: + +```markdown +--- +description: Initialize deployment workflow +allowed-tools: Write, Bash(git:*) +--- + +# Initialize Deployment + +Creating deployment tracking file... + +Current branch: !`git branch --show-current` +Latest commit: !`git log -1 --format=%H` + +Deployment state saved to `.claude/deployment-state.local.md`: + +\`\`\`markdown +--- +initialized: true +branch: $(git branch --show-current) +commit: $(git log -1 --format=%H) +timestamp: $(date -u +%Y-%m-%dT%H:%M:%SZ) +status: initialized +--- + +# Deployment Tracking + +Branch: $(git branch --show-current) +Started: $(date) + +Next steps: +1. Run tests: /deploy-test +2. Build: /deploy-build +3. Deploy: /deploy-execute +\`\`\` + +State saved. Run `/deploy-test` to continue. +``` + +**Next command** (`/deploy-test`): +```markdown +--- +description: Run deployment tests +allowed-tools: Read, Bash(npm:*) +--- + +Reading deployment state from `.claude/deployment-state.local.md`... + +Running tests: !`npm test` + +Updating state to 'tested'... + +Tests complete. Run `/deploy-build` to continue. +``` + +**Pattern benefits:** +- Persistent state across commands +- Clear workflow progression +- Safety checkpoints +- Resume capability + +### Conditional Workflow Branching + +Commands that adapt based on conditions: + +```markdown +--- +description: Smart deployment workflow +argument-hint: [environment] +allowed-tools: Bash(git:*), Bash(npm:*), Read +--- + +# Deploy to $1 + +## Pre-flight Checks + +Branch: !`git branch --show-current` +Status: !`git status --short` + +**Checking conditions:** + +1. Branch status: + - If main/master: Require approval + - If feature branch: Warning about target + - If hotfix: Fast-track process + +2. Tests: + !`npm test` + - If tests fail: STOP - fix tests first + - If tests pass: Continue + +3. Environment: + - If $1 = 'production': Extra validation + - If $1 = 'staging': Standard process + - If $1 = 'dev': Minimal checks + +**Workflow decision:** +Based on above, proceeding with: [determined workflow] + +[Conditional steps based on environment and status] + +Ready to deploy? (yes/no) +``` + +## Command Composition Patterns + +### Command Chaining + +Commands designed to work together: + +```markdown +--- +description: Prepare for code review +--- + +# Prepare Code Review + +Running preparation sequence: + +1. Format code: /format-code +2. Run linter: /lint-code +3. Run tests: /test-all +4. Generate coverage: /coverage-report +5. Create review summary: /review-summary + +This is a meta-command. After completing each step above, +I'll compile results and prepare comprehensive review materials. + +Starting sequence... +``` + +**Individual commands** are simple: +- `/format-code` - Just formats +- `/lint-code` - Just lints +- `/test-all` - Just tests + +**Composition command** orchestrates them. + +### Pipeline Pattern + +Commands that process output from previous commands: + +```markdown +--- +description: Analyze test failures +--- + +# Analyze Test Failures + +## Step 1: Get test results +(Run /test-all first if not done) + +Reading test output... + +## Step 2: Categorize failures +- Flaky tests (random failures) +- Consistent failures +- New failures vs existing + +## Step 3: Prioritize +Rank by: +- Impact (critical path vs edge case) +- Frequency (always fails vs sometimes) +- Effort (quick fix vs major work) + +## Step 4: Generate fix plan +For each failure: +- Root cause hypothesis +- Suggested fix approach +- Estimated effort + +Would you like me to: +1. Fix highest priority failure +2. Generate detailed fix plans for all +3. Create GitHub issues for each +``` + +### Parallel Execution Pattern + +Commands that coordinate multiple simultaneous operations: + +```markdown +--- +description: Run comprehensive validation +allowed-tools: Bash(*), Read +--- + +# Comprehensive Validation + +Running validations in parallel... + +Starting: +- Code quality checks +- Security scanning +- Dependency audit +- Performance profiling + +This will take 2-3 minutes. I'll monitor all processes +and report when complete. + +[Poll each process and report progress] + +All validations complete. Summary: +- Quality: PASS (0 issues) +- Security: WARN (2 minor issues) +- Dependencies: PASS +- Performance: PASS (baseline met) + +Details: +[Collated results from all checks] +``` + +## Workflow State Management + +### Using .local.md Files + +Store workflow state in plugin-specific files: + +```markdown +.claude/plugin-name-workflow.local.md: + +--- +workflow: deployment +stage: testing +started: 2025-01-15T10:30:00Z +environment: staging +branch: feature/new-api +commit: abc123def +tests_passed: false +build_complete: false +--- + +# Deployment Workflow State + +Current stage: Testing +Started: 2025-01-15 10:30 UTC + +Completed steps: +- ✅ Validation +- ✅ Branch check +- ⏳ Testing (in progress) + +Pending steps: +- Build +- Deploy +- Smoke tests +``` + +**Reading state in commands:** + +```markdown +--- +description: Continue deployment workflow +allowed-tools: Read, Write +--- + +Reading workflow state from .claude/plugin-name-workflow.local.md... + +Current stage: @.claude/plugin-name-workflow.local.md + +[Parse YAML frontmatter to determine next step] + +Next action based on state: [determined action] +``` + +### Workflow Recovery + +Handle interrupted workflows: + +```markdown +--- +description: Resume deployment workflow +allowed-tools: Read +--- + +# Resume Deployment + +Checking for interrupted workflow... + +State file: @.claude/plugin-name-workflow.local.md + +**Workflow found:** +- Started: [timestamp] +- Environment: [env] +- Last completed: [step] + +**Recovery options:** +1. Resume from last step +2. Restart from beginning +3. Abort and clean up + +Which would you like? (1/2/3) +``` + +## Workflow Coordination Patterns + +### Cross-Command Communication + +Commands that signal each other: + +```markdown +--- +description: Mark feature complete +allowed-tools: Write +--- + +# Mark Feature Complete + +Writing completion marker... + +Creating: .claude/feature-complete.flag + +This signals other commands that feature is ready for: +- Integration testing (/integration-test will auto-detect) +- Documentation generation (/docs-generate will include) +- Release notes (/release-notes will add) + +Feature marked complete. +``` + +**Other commands check for flag:** + +```markdown +--- +description: Generate release notes +allowed-tools: Read, Bash(git:*) +--- + +Checking for completed features... + +if [ -f .claude/feature-complete.flag ]; then + Feature ready for release notes +fi + +[Include in release notes] +``` + +### Workflow Locking + +Prevent concurrent workflow execution: + +```markdown +--- +description: Start deployment +allowed-tools: Read, Write, Bash +--- + +# Start Deployment + +Checking for active deployments... + +if [ -f .claude/deployment.lock ]; then + ERROR: Deployment already in progress + Started: [timestamp from lock file] + + Cannot start concurrent deployment. + Wait for completion or run /deployment-abort + + Exit. +fi + +Creating deployment lock... + +Deployment started. Lock created. +[Proceed with deployment] +``` + +**Lock cleanup:** + +```markdown +--- +description: Complete deployment +allowed-tools: Write, Bash +--- + +Deployment complete. + +Removing deployment lock... +rm .claude/deployment.lock + +Ready for next deployment. +``` + +## Advanced Argument Handling + +### Optional Arguments with Defaults + +```markdown +--- +description: Deploy with optional version +argument-hint: [environment] [version] +--- + +Environment: ${1:-staging} +Version: ${2:-latest} + +Deploying ${2:-latest} to ${1:-staging}... + +Note: Using defaults for missing arguments: +- Environment defaults to 'staging' +- Version defaults to 'latest' +``` + +### Argument Validation + +```markdown +--- +description: Deploy to validated environment +argument-hint: [environment] +--- + +Environment: $1 + +Validating environment... + +valid_envs="dev staging production" +if ! echo "$valid_envs" | grep -w "$1" > /dev/null; then + ERROR: Invalid environment '$1' + Valid options: dev, staging, production + Exit. +fi + +Environment validated. Proceeding... +``` + +### Argument Transformation + +```markdown +--- +description: Deploy with shorthand +argument-hint: [env-shorthand] +--- + +Input: $1 + +Expanding shorthand: +- d/dev → development +- s/stg → staging +- p/prod → production + +case "$1" in + d|dev) ENV="development";; + s|stg) ENV="staging";; + p|prod) ENV="production";; + *) ENV="$1";; +esac + +Deploying to: $ENV +``` + +## Error Handling in Workflows + +### Graceful Failure + +```markdown +--- +description: Resilient deployment workflow +--- + +# Deployment Workflow + +Running steps with error handling... + +## Step 1: Tests +!`npm test` + +if [ $? -ne 0 ]; then + ERROR: Tests failed + + Options: + 1. Fix tests and retry + 2. Skip tests (NOT recommended) + 3. Abort deployment + + What would you like to do? + + [Wait for user input before continuing] +fi + +## Step 2: Build +[Continue only if Step 1 succeeded] +``` + +### Rollback on Failure + +```markdown +--- +description: Deployment with rollback +--- + +# Deploy with Rollback + +Saving current state for rollback... +Previous version: !`current-version.sh` + +Deploying new version... + +!`deploy.sh` + +if [ $? -ne 0 ]; then + DEPLOYMENT FAILED + + Initiating automatic rollback... + !`rollback.sh` + + Rolled back to previous version. + Check logs for failure details. +fi + +Deployment complete. +``` + +### Checkpoint Recovery + +```markdown +--- +description: Workflow with checkpoints +--- + +# Multi-Stage Deployment + +## Checkpoint 1: Validation +!`validate.sh` +echo "checkpoint:validation" >> .claude/deployment-checkpoints.log + +## Checkpoint 2: Build +!`build.sh` +echo "checkpoint:build" >> .claude/deployment-checkpoints.log + +## Checkpoint 3: Deploy +!`deploy.sh` +echo "checkpoint:deploy" >> .claude/deployment-checkpoints.log + +If any step fails, resume with: +/deployment-resume [last-successful-checkpoint] +``` + +## Best Practices + +### Workflow Design + +1. **Clear progression**: Number steps, show current position +2. **Explicit state**: Don't rely on implicit state +3. **User control**: Provide decision points +4. **Error recovery**: Handle failures gracefully +5. **Progress indication**: Show what's done, what's pending + +### Command Composition + +1. **Single responsibility**: Each command does one thing well +2. **Composable design**: Commands work together easily +3. **Standard interfaces**: Consistent input/output formats +4. **Loose coupling**: Commands don't depend on each other's internals + +### State Management + +1. **Persistent state**: Use .local.md files +2. **Atomic updates**: Write complete state files atomically +3. **State validation**: Check state file format/completeness +4. **Cleanup**: Remove stale state files +5. **Documentation**: Document state file formats + +### Error Handling + +1. **Fail fast**: Detect errors early +2. **Clear messages**: Explain what went wrong +3. **Recovery options**: Provide clear next steps +4. **State preservation**: Keep state for recovery +5. **Rollback capability**: Support undoing changes + +## Example: Complete Deployment Workflow + +### Initialize Command + +```markdown +--- +description: Initialize deployment +argument-hint: [environment] +allowed-tools: Write, Bash(git:*) +--- + +# Initialize Deployment to $1 + +Creating workflow state... + +\`\`\`yaml +--- +workflow: deployment +environment: $1 +branch: !`git branch --show-current` +commit: !`git rev-parse HEAD` +stage: initialized +timestamp: !`date -u +%Y-%m-%dT%H:%M:%SZ` +--- +\`\`\` + +Written to .claude/deployment-state.local.md + +Next: Run /deployment-validate +``` + +### Validation Command + +```markdown +--- +description: Validate deployment +allowed-tools: Read, Bash +--- + +Reading state: @.claude/deployment-state.local.md + +Running validation... +- Branch check: PASS +- Tests: PASS +- Build: PASS + +Updating state to 'validated'... + +Next: Run /deployment-execute +``` + +### Execution Command + +```markdown +--- +description: Execute deployment +allowed-tools: Read, Bash, Write +--- + +Reading state: @.claude/deployment-state.local.md + +Executing deployment to [environment]... + +!`deploy.sh [environment]` + +Deployment complete. +Updating state to 'completed'... + +Cleanup: /deployment-cleanup +``` + +### Cleanup Command + +```markdown +--- +description: Clean up deployment +allowed-tools: Bash +--- + +Removing deployment state... +rm .claude/deployment-state.local.md + +Deployment workflow complete. +``` + +This complete workflow demonstrates state management, sequential execution, error handling, and clean separation of concerns across multiple commands. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/documentation-patterns.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/documentation-patterns.md new file mode 100644 index 0000000..3ea03ec --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/documentation-patterns.md @@ -0,0 +1,739 @@ +# Command Documentation Patterns + +Strategies for creating self-documenting, maintainable commands with excellent user experience. + +## Overview + +Well-documented commands are easier to use, maintain, and distribute. Documentation should be embedded in the command itself, making it immediately accessible to users and maintainers. + +## Self-Documenting Command Structure + +### Complete Command Template + +```markdown +--- +description: Clear, actionable description under 60 chars +argument-hint: [arg1] [arg2] [optional-arg] +allowed-tools: Read, Bash(git:*) +model: sonnet +--- + + + +# Command Implementation + +[Command prompt content here...] + +[Explain what will happen...] + +[Guide user through steps...] + +[Provide clear output...] +``` + +### Documentation Comment Sections + +**PURPOSE**: Why the command exists +- Problem it solves +- Use cases +- When to use vs when not to use + +**USAGE**: Basic syntax +- Command invocation pattern +- Required vs optional arguments +- Default values + +**ARGUMENTS**: Detailed argument documentation +- Each argument described +- Type information +- Valid values/ranges +- Defaults + +**EXAMPLES**: Concrete usage examples +- Common use cases +- Edge cases +- Expected outputs + +**REQUIREMENTS**: Prerequisites +- Dependencies +- Permissions +- Environmental setup + +**RELATED COMMANDS**: Connections +- Similar commands +- Complementary commands +- Alternative approaches + +**TROUBLESHOOTING**: Common issues +- Known problems +- Solutions +- Workarounds + +**CHANGELOG**: Version history +- What changed when +- Breaking changes highlighted +- Migration guidance + +## In-Line Documentation Patterns + +### Commented Sections + +```markdown +--- +description: Complex multi-step command +--- + + + + +Checking prerequisites... +- Git repository: !`git rev-parse --git-dir 2>/dev/null` +- Branch exists: [validation logic] + + + + +Analyzing differences between $1 and $2... +[Analysis logic...] + + + + +Based on analysis, recommend: +[Recommendations...] + + +``` + +### Inline Explanations + +```markdown +--- +description: Deployment command with inline docs +--- + +# Deploy to $1 + +## Pre-flight Checks + + +Current branch: !`git branch --show-current` + + +if [ "$1" = "production" ] && [ "$(git branch --show-current)" != "main" ]; then + ⚠️ WARNING: Not on main branch for production deploy + This is unusual. Confirm this is intentional. +fi + + +Running tests: !`npm test` + +✓ All checks passed + +## Deployment + + + +Deploying to $1 environment... +[Deployment steps...] + + +Verifying deployment health... +[Health checks...] + +Deployment complete! + +## Next Steps + + +1. Monitor logs: /logs $1 +2. Run smoke tests: /smoke-test $1 +3. Notify team: /notify-deployment $1 +``` + +### Decision Point Documentation + +```markdown +--- +description: Interactive deployment command +--- + +# Interactive Deployment + +## Configuration Review + +Target: $1 +Current version: !`cat version.txt` +New version: $2 + + + + + +Review the above configuration. + +**Continue with deployment?** +- Reply "yes" to proceed +- Reply "no" to cancel +- Reply "edit" to modify configuration + +[Await user input before continuing...] + + + + +Proceeding with deployment... +``` + +## Help Text Patterns + +### Built-in Help Command + +Create a help subcommand for complex commands: + +```markdown +--- +description: Main command with help +argument-hint: [subcommand] [args] +--- + +# Command Processor + +if [ "$1" = "help" ] || [ "$1" = "--help" ] || [ "$1" = "-h" ]; then + **Command Help** + + USAGE: + /command [subcommand] [args] + + SUBCOMMANDS: + init [name] Initialize new configuration + deploy [env] Deploy to environment + status Show current status + rollback Rollback last deployment + help Show this help + + EXAMPLES: + /command init my-project + /command deploy staging + /command status + /command rollback + + For detailed help on a subcommand: + /command [subcommand] --help + + Exit. +fi + +[Regular command processing...] +``` + +### Contextual Help + +Provide help based on context: + +```markdown +--- +description: Context-aware command +argument-hint: [operation] [target] +--- + +# Context-Aware Operation + +if [ -z "$1" ]; then + **No operation specified** + + Available operations: + - analyze: Analyze target for issues + - fix: Apply automatic fixes + - report: Generate detailed report + + Usage: /command [operation] [target] + + Examples: + /command analyze src/ + /command fix src/app.js + /command report + + Run /command help for more details. + + Exit. +fi + +[Command continues if operation provided...] +``` + +## Error Message Documentation + +### Helpful Error Messages + +```markdown +--- +description: Command with good error messages +--- + +# Validation Command + +if [ -z "$1" ]; then + ❌ ERROR: Missing required argument + + The 'file-path' argument is required. + + USAGE: + /validate [file-path] + + EXAMPLE: + /validate src/app.js + + Try again with a file path. + + Exit. +fi + +if [ ! -f "$1" ]; then + ❌ ERROR: File not found: $1 + + The specified file does not exist or is not accessible. + + COMMON CAUSES: + 1. Typo in file path + 2. File was deleted or moved + 3. Insufficient permissions + + SUGGESTIONS: + - Check spelling: $1 + - Verify file exists: ls -la $(dirname "$1") + - Check permissions: ls -l "$1" + + Exit. +fi + +[Command continues if validation passes...] +``` + +### Error Recovery Guidance + +```markdown +--- +description: Command with recovery guidance +--- + +# Operation Command + +Running operation... + +!`risky-operation.sh` + +if [ $? -ne 0 ]; then + ❌ OPERATION FAILED + + The operation encountered an error and could not complete. + + WHAT HAPPENED: + The risky-operation.sh script returned a non-zero exit code. + + WHAT THIS MEANS: + - Changes may be partially applied + - System may be in inconsistent state + - Manual intervention may be needed + + RECOVERY STEPS: + 1. Check operation logs: cat /tmp/operation.log + 2. Verify system state: /check-state + 3. If needed, rollback: /rollback-operation + 4. Fix underlying issue + 5. Retry operation: /retry-operation + + NEED HELP? + - Check troubleshooting guide: /help troubleshooting + - Contact support with error code: ERR_OP_FAILED_001 + + Exit. +fi +``` + +## Usage Example Documentation + +### Embedded Examples + +```markdown +--- +description: Command with embedded examples +--- + +# Feature Command + +This command performs feature analysis with multiple options. + +## Basic Usage + +\`\`\` +/feature analyze src/ +\`\`\` + +Analyzes all files in src/ directory for feature usage. + +## Advanced Usage + +\`\`\` +/feature analyze src/ --detailed +\`\`\` + +Provides detailed analysis including: +- Feature breakdown by file +- Usage patterns +- Optimization suggestions + +## Use Cases + +**Use Case 1: Quick overview** +\`\`\` +/feature analyze . +\`\`\` +Get high-level feature summary of entire project. + +**Use Case 2: Specific directory** +\`\`\` +/feature analyze src/components +\`\`\` +Focus analysis on components directory only. + +**Use Case 3: Comparison** +\`\`\` +/feature analyze src/ --compare baseline.json +\`\`\` +Compare current features against baseline. + +--- + +Now processing your request... + +[Command implementation...] +``` + +### Example-Driven Documentation + +```markdown +--- +description: Example-heavy command +--- + +# Transformation Command + +## What This Does + +Transforms data from one format to another. + +## Examples First + +### Example 1: JSON to YAML +**Input:** `data.json` +\`\`\`json +{"name": "test", "value": 42} +\`\`\` + +**Command:** `/transform data.json yaml` + +**Output:** `data.yaml` +\`\`\`yaml +name: test +value: 42 +\`\`\` + +### Example 2: CSV to JSON +**Input:** `data.csv` +\`\`\`csv +name,value +test,42 +\`\`\` + +**Command:** `/transform data.csv json` + +**Output:** `data.json` +\`\`\`json +[{"name": "test", "value": "42"}] +\`\`\` + +### Example 3: With Options +**Command:** `/transform data.json yaml --pretty --sort-keys` + +**Result:** Formatted YAML with sorted keys + +--- + +## Your Transformation + +File: $1 +Format: $2 + +[Perform transformation...] +``` + +## Maintenance Documentation + +### Version and Changelog + +```markdown + +``` + +### Maintenance Notes + +```markdown + +``` + +## README Documentation + +Commands should have companion README files: + +```markdown +# Command Name + +Brief description of what the command does. + +## Installation + +This command is part of the [plugin-name] plugin. + +Install with: +\`\`\` +/plugin install plugin-name +\`\`\` + +## Usage + +Basic usage: +\`\`\` +/command-name [arg1] [arg2] +\`\`\` + +## Arguments + +- `arg1`: Description (required) +- `arg2`: Description (optional, defaults to X) + +## Examples + +### Example 1: Basic Usage +\`\`\` +/command-name value1 value2 +\`\`\` + +Description of what happens. + +### Example 2: Advanced Usage +\`\`\` +/command-name value1 --option +\`\`\` + +Description of advanced feature. + +## Configuration + +Optional configuration file: `.claude/command-name.local.md` + +\`\`\`markdown +--- +default_arg: value +enable_feature: true +--- +\`\`\` + +## Requirements + +- Git 2.x or later +- jq (for JSON processing) +- Node.js 14+ (optional, for advanced features) + +## Troubleshooting + +### Issue: Command not found + +**Solution:** Ensure plugin is installed and enabled. + +### Issue: Permission denied + +**Solution:** Check file permissions and allowed-tools setting. + +## Contributing + +Contributions welcome! See [CONTRIBUTING.md](CONTRIBUTING.md). + +## License + +MIT License - See [LICENSE](LICENSE). + +## Support + +- Issues: https://github.com/user/plugin/issues +- Docs: https://docs.example.com +- Email: support@example.com +``` + +## Best Practices + +### Documentation Principles + +1. **Write for your future self**: Assume you'll forget details +2. **Examples before explanations**: Show, then tell +3. **Progressive disclosure**: Basic info first, details available +4. **Keep it current**: Update docs when code changes +5. **Test your docs**: Verify examples actually work + +### Documentation Locations + +1. **In command file**: Core usage, examples, inline explanations +2. **README**: Installation, configuration, troubleshooting +3. **Separate docs**: Detailed guides, tutorials, API reference +4. **Comments**: Implementation details for maintainers + +### Documentation Style + +1. **Clear and concise**: No unnecessary words +2. **Active voice**: "Run the command" not "The command can be run" +3. **Consistent terminology**: Use same terms throughout +4. **Formatted well**: Use headings, lists, code blocks +5. **Accessible**: Assume reader is beginner + +### Documentation Maintenance + +1. **Version everything**: Track what changed when +2. **Deprecate gracefully**: Warn before removing features +3. **Migration guides**: Help users upgrade +4. **Archive old docs**: Keep old versions accessible +5. **Review regularly**: Ensure docs match reality + +## Documentation Checklist + +Before releasing a command: + +- [ ] Description in frontmatter is clear +- [ ] argument-hint documents all arguments +- [ ] Usage examples in comments +- [ ] Common use cases shown +- [ ] Error messages are helpful +- [ ] Requirements documented +- [ ] Related commands listed +- [ ] Changelog maintained +- [ ] Version number updated +- [ ] README created/updated +- [ ] Examples actually work +- [ ] Troubleshooting section complete + +With good documentation, commands become self-service, reducing support burden and improving user experience. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/frontmatter-reference.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/frontmatter-reference.md new file mode 100644 index 0000000..aa85294 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/frontmatter-reference.md @@ -0,0 +1,463 @@ +# Command Frontmatter Reference + +Complete reference for YAML frontmatter fields in slash commands. + +## Frontmatter Overview + +YAML frontmatter is optional metadata at the start of command files: + +```markdown +--- +description: Brief description +allowed-tools: Read, Write +model: sonnet +argument-hint: [arg1] [arg2] +--- + +Command prompt content here... +``` + +All fields are optional. Commands work without any frontmatter. + +## Field Specifications + +### description + +**Type:** String +**Required:** No +**Default:** First line of command prompt +**Max Length:** ~60 characters recommended for `/help` display + +**Purpose:** Describes what the command does, shown in `/help` output + +**Examples:** +```yaml +description: Review code for security issues +``` +```yaml +description: Deploy to staging environment +``` +```yaml +description: Generate API documentation +``` + +**Best practices:** +- Keep under 60 characters for clean display +- Start with verb (Review, Deploy, Generate) +- Be specific about what command does +- Avoid redundant "command" or "slash command" + +**Good:** +- ✅ "Review PR for code quality and security" +- ✅ "Deploy application to specified environment" +- ✅ "Generate comprehensive API documentation" + +**Bad:** +- ❌ "This command reviews PRs" (unnecessary "This command") +- ❌ "Review" (too vague) +- ❌ "A command that reviews pull requests for code quality, security issues, and best practices" (too long) + +### allowed-tools + +**Type:** String or Array of strings +**Required:** No +**Default:** Inherits from conversation permissions + +**Purpose:** Restrict or specify which tools command can use + +**Formats:** + +**Single tool:** +```yaml +allowed-tools: Read +``` + +**Multiple tools (comma-separated):** +```yaml +allowed-tools: Read, Write, Edit +``` + +**Multiple tools (array):** +```yaml +allowed-tools: + - Read + - Write + - Bash(git:*) +``` + +**Tool Patterns:** + +**Specific tools:** +```yaml +allowed-tools: Read, Grep, Edit +``` + +**Bash with command filter:** +```yaml +allowed-tools: Bash(git:*) # Only git commands +allowed-tools: Bash(npm:*) # Only npm commands +allowed-tools: Bash(docker:*) # Only docker commands +``` + +**All tools (not recommended):** +```yaml +allowed-tools: "*" +``` + +**When to use:** + +1. **Security:** Restrict command to safe operations + ```yaml + allowed-tools: Read, Grep # Read-only command + ``` + +2. **Clarity:** Document required tools + ```yaml + allowed-tools: Bash(git:*), Read + ``` + +3. **Bash execution:** Enable bash command output + ```yaml + allowed-tools: Bash(git status:*), Bash(git diff:*) + ``` + +**Best practices:** +- Be as restrictive as possible +- Use command filters for Bash (e.g., `git:*` not `*`) +- Only specify when different from conversation permissions +- Document why specific tools are needed + +### model + +**Type:** String +**Required:** No +**Default:** Inherits from conversation +**Values:** `sonnet`, `opus`, `haiku` + +**Purpose:** Specify which Claude model executes the command + +**Examples:** +```yaml +model: haiku # Fast, efficient for simple tasks +``` +```yaml +model: sonnet # Balanced performance (default) +``` +```yaml +model: opus # Maximum capability for complex tasks +``` + +**When to use:** + +**Use `haiku` for:** +- Simple, formulaic commands +- Fast execution needed +- Low complexity tasks +- Frequent invocations + +```yaml +--- +description: Format code file +model: haiku +--- +``` + +**Use `sonnet` for:** +- Standard commands (default) +- Balanced speed/quality +- Most common use cases + +```yaml +--- +description: Review code changes +model: sonnet +--- +``` + +**Use `opus` for:** +- Complex analysis +- Architectural decisions +- Deep code understanding +- Critical tasks + +```yaml +--- +description: Analyze system architecture +model: opus +--- +``` + +**Best practices:** +- Omit unless specific need +- Use `haiku` for speed when possible +- Reserve `opus` for genuinely complex tasks +- Test with different models to find right balance + +### argument-hint + +**Type:** String +**Required:** No +**Default:** None + +**Purpose:** Document expected arguments for users and autocomplete + +**Format:** +```yaml +argument-hint: [arg1] [arg2] [optional-arg] +``` + +**Examples:** + +**Single argument:** +```yaml +argument-hint: [pr-number] +``` + +**Multiple required arguments:** +```yaml +argument-hint: [environment] [version] +``` + +**Optional arguments:** +```yaml +argument-hint: [file-path] [options] +``` + +**Descriptive names:** +```yaml +argument-hint: [source-branch] [target-branch] [commit-message] +``` + +**Best practices:** +- Use square brackets `[]` for each argument +- Use descriptive names (not `arg1`, `arg2`) +- Indicate optional vs required in description +- Match order to positional arguments in command +- Keep concise but clear + +**Examples by pattern:** + +**Simple command:** +```yaml +--- +description: Fix issue by number +argument-hint: [issue-number] +--- + +Fix issue #$1... +``` + +**Multi-argument:** +```yaml +--- +description: Deploy to environment +argument-hint: [app-name] [environment] [version] +--- + +Deploy $1 to $2 using version $3... +``` + +**With options:** +```yaml +--- +description: Run tests with options +argument-hint: [test-pattern] [options] +--- + +Run tests matching $1 with options: $2 +``` + +### disable-model-invocation + +**Type:** Boolean +**Required:** No +**Default:** false + +**Purpose:** Prevent SlashCommand tool from programmatically invoking command + +**Examples:** +```yaml +disable-model-invocation: true +``` + +**When to use:** + +1. **Manual-only commands:** Commands requiring user judgment + ```yaml + --- + description: Approve deployment to production + disable-model-invocation: true + --- + ``` + +2. **Destructive operations:** Commands with irreversible effects + ```yaml + --- + description: Delete all test data + disable-model-invocation: true + --- + ``` + +3. **Interactive workflows:** Commands needing user input + ```yaml + --- + description: Walk through setup wizard + disable-model-invocation: true + --- + ``` + +**Default behavior (false):** +- Command available to SlashCommand tool +- Claude can invoke programmatically +- Still available for manual invocation + +**When true:** +- Command only invokable by user typing `/command` +- Not available to SlashCommand tool +- Safer for sensitive operations + +**Best practices:** +- Use sparingly (limits Claude's autonomy) +- Document why in command comments +- Consider if command should exist if always manual + +## Complete Examples + +### Minimal Command + +No frontmatter needed: + +```markdown +Review this code for common issues and suggest improvements. +``` + +### Simple Command + +Just description: + +```markdown +--- +description: Review code for issues +--- + +Review this code for common issues and suggest improvements. +``` + +### Standard Command + +Description and tools: + +```markdown +--- +description: Review Git changes +allowed-tools: Bash(git:*), Read +--- + +Current changes: !`git diff --name-only` + +Review each changed file for: +- Code quality +- Potential bugs +- Best practices +``` + +### Complex Command + +All common fields: + +```markdown +--- +description: Deploy application to environment +argument-hint: [app-name] [environment] [version] +allowed-tools: Bash(kubectl:*), Bash(helm:*), Read +model: sonnet +--- + +Deploy $1 to $2 environment using version $3 + +Pre-deployment checks: +- Verify $2 configuration +- Check cluster status: !`kubectl cluster-info` +- Validate version $3 exists + +Proceed with deployment following deployment runbook. +``` + +### Manual-Only Command + +Restricted invocation: + +```markdown +--- +description: Approve production deployment +argument-hint: [deployment-id] +disable-model-invocation: true +allowed-tools: Bash(gh:*) +--- + + + +Review deployment $1 for production approval: + +Deployment details: !`gh api /deployments/$1` + +Verify: +- All tests passed +- Security scan clean +- Stakeholder approval +- Rollback plan ready + +Type "APPROVED" to confirm deployment. +``` + +## Validation + +### Common Errors + +**Invalid YAML syntax:** +```yaml +--- +description: Missing quote +allowed-tools: Read, Write +model: sonnet +--- # ❌ Missing closing quote above +``` + +**Fix:** Validate YAML syntax + +**Incorrect tool specification:** +```yaml +allowed-tools: Bash # ❌ Missing command filter +``` + +**Fix:** Use `Bash(git:*)` format + +**Invalid model name:** +```yaml +model: gpt4 # ❌ Not a valid Claude model +``` + +**Fix:** Use `sonnet`, `opus`, or `haiku` + +### Validation Checklist + +Before committing command: +- [ ] YAML syntax valid (no errors) +- [ ] Description under 60 characters +- [ ] allowed-tools uses proper format +- [ ] model is valid value if specified +- [ ] argument-hint matches positional arguments +- [ ] disable-model-invocation used appropriately + +## Best Practices Summary + +1. **Start minimal:** Add frontmatter only when needed +2. **Document arguments:** Always use argument-hint with arguments +3. **Restrict tools:** Use most restrictive allowed-tools that works +4. **Choose right model:** Use haiku for speed, opus for complexity +5. **Manual-only sparingly:** Only use disable-model-invocation when necessary +6. **Clear descriptions:** Make commands discoverable in `/help` +7. **Test thoroughly:** Verify frontmatter works as expected diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/interactive-commands.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/interactive-commands.md new file mode 100644 index 0000000..e55bc38 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/interactive-commands.md @@ -0,0 +1,920 @@ +# Interactive Command Patterns + +Comprehensive guide to creating commands that gather user feedback and make decisions through the AskUserQuestion tool. + +## Overview + +Some commands need user input that doesn't work well with simple arguments. For example: +- Choosing between multiple complex options with trade-offs +- Selecting multiple items from a list +- Making decisions that require explanation +- Gathering preferences or configuration interactively + +For these cases, use the **AskUserQuestion tool** within command execution rather than relying on command arguments. + +## When to Use AskUserQuestion + +### Use AskUserQuestion When: + +1. **Multiple choice decisions** with explanations needed +2. **Complex options** that require context to choose +3. **Multi-select scenarios** (choosing multiple items) +4. **Preference gathering** for configuration +5. **Interactive workflows** that adapt based on answers + +### Use Command Arguments When: + +1. **Simple values** (file paths, numbers, names) +2. **Known inputs** user already has +3. **Scriptable workflows** that should be automatable +4. **Fast invocations** where prompting would slow down + +## AskUserQuestion Basics + +### Tool Parameters + +```typescript +{ + questions: [ + { + question: "Which authentication method should we use?", + header: "Auth method", // Short label (max 12 chars) + multiSelect: false, // true for multiple selection + options: [ + { + label: "OAuth 2.0", + description: "Industry standard, supports multiple providers" + }, + { + label: "JWT", + description: "Stateless, good for APIs" + }, + { + label: "Session", + description: "Traditional, server-side state" + } + ] + } + ] +} +``` + +**Key points:** +- Users can always choose "Other" to provide custom input (automatic) +- `multiSelect: true` allows selecting multiple options +- Options should be 2-4 choices (not more) +- Can ask 1-4 questions per tool call + +## Command Pattern for User Interaction + +### Basic Interactive Command + +```markdown +--- +description: Interactive setup command +allowed-tools: AskUserQuestion, Write +--- + +# Interactive Plugin Setup + +This command will guide you through configuring the plugin with a series of questions. + +## Step 1: Gather Configuration + +Use the AskUserQuestion tool to ask: + +**Question 1 - Deployment target:** +- header: "Deploy to" +- question: "Which deployment platform will you use?" +- options: + - AWS (Amazon Web Services with ECS/EKS) + - GCP (Google Cloud with GKE) + - Azure (Microsoft Azure with AKS) + - Local (Docker on local machine) + +**Question 2 - Environment strategy:** +- header: "Environments" +- question: "How many environments do you need?" +- options: + - Single (Just production) + - Standard (Dev, Staging, Production) + - Complete (Dev, QA, Staging, Production) + +**Question 3 - Features to enable:** +- header: "Features" +- question: "Which features do you want to enable?" +- multiSelect: true +- options: + - Auto-scaling (Automatic resource scaling) + - Monitoring (Health checks and metrics) + - CI/CD (Automated deployment pipeline) + - Backups (Automated database backups) + +## Step 2: Process Answers + +Based on the answers received from AskUserQuestion: + +1. Parse the deployment target choice +2. Set up environment-specific configuration +3. Enable selected features +4. Generate configuration files + +## Step 3: Generate Configuration + +Create `.claude/plugin-name.local.md` with: + +\`\`\`yaml +--- +deployment_target: [answer from Q1] +environments: [answer from Q2] +features: + auto_scaling: [true if selected in Q3] + monitoring: [true if selected in Q3] + ci_cd: [true if selected in Q3] + backups: [true if selected in Q3] +--- + +# Plugin Configuration + +Generated: [timestamp] +Target: [deployment_target] +Environments: [environments] +\`\`\` + +## Step 4: Confirm and Next Steps + +Confirm configuration created and guide user on next steps. +``` + +### Multi-Stage Interactive Workflow + +```markdown +--- +description: Multi-stage interactive workflow +allowed-tools: AskUserQuestion, Read, Write, Bash +--- + +# Multi-Stage Deployment Setup + +This command walks through deployment setup in stages, adapting based on your answers. + +## Stage 1: Basic Configuration + +Use AskUserQuestion to ask about deployment basics. + +Based on answers, determine which additional questions to ask. + +## Stage 2: Advanced Options (Conditional) + +If user selected "Advanced" deployment in Stage 1: + +Use AskUserQuestion to ask about: +- Load balancing strategy +- Caching configuration +- Security hardening options + +If user selected "Simple" deployment: +- Skip advanced questions +- Use sensible defaults + +## Stage 3: Confirmation + +Show summary of all selections. + +Use AskUserQuestion for final confirmation: +- header: "Confirm" +- question: "Does this configuration look correct?" +- options: + - Yes (Proceed with setup) + - No (Start over) + - Modify (Let me adjust specific settings) + +If "Modify", ask which specific setting to change. + +## Stage 4: Execute Setup + +Based on confirmed configuration, execute setup steps. +``` + +## Interactive Question Design + +### Question Structure + +**Good questions:** +```markdown +Question: "Which database should we use for this project?" +Header: "Database" +Options: + - PostgreSQL (Relational, ACID compliant, best for complex queries) + - MongoDB (Document store, flexible schema, best for rapid iteration) + - Redis (In-memory, fast, best for caching and sessions) +``` + +**Poor questions:** +```markdown +Question: "Database?" // Too vague +Header: "DB" // Unclear abbreviation +Options: + - Option 1 // Not descriptive + - Option 2 +``` + +### Option Design Best Practices + +**Clear labels:** +- Use 1-5 words +- Specific and descriptive +- No jargon without context + +**Helpful descriptions:** +- Explain what the option means +- Mention key benefits or trade-offs +- Help user make informed decision +- Keep to 1-2 sentences + +**Appropriate number:** +- 2-4 options per question +- Don't overwhelm with too many choices +- Group related options +- "Other" automatically provided + +### Multi-Select Questions + +**When to use multiSelect:** + +```markdown +Use AskUserQuestion for enabling features: + +Question: "Which features do you want to enable?" +Header: "Features" +multiSelect: true // Allow selecting multiple +Options: + - Logging (Detailed operation logs) + - Metrics (Performance monitoring) + - Alerts (Error notifications) + - Backups (Automatic backups) +``` + +User can select any combination: none, some, or all. + +**When NOT to use multiSelect:** + +```markdown +Question: "Which authentication method?" +multiSelect: false // Only one auth method makes sense +``` + +Mutually exclusive choices should not use multiSelect. + +## Command Patterns with AskUserQuestion + +### Pattern 1: Simple Yes/No Decision + +```markdown +--- +description: Command with confirmation +allowed-tools: AskUserQuestion, Bash +--- + +# Destructive Operation + +This operation will delete all cached data. + +Use AskUserQuestion to confirm: + +Question: "This will delete all cached data. Are you sure?" +Header: "Confirm" +Options: + - Yes (Proceed with deletion) + - No (Cancel operation) + +If user selects "Yes": + Execute deletion + Report completion + +If user selects "No": + Cancel operation + Exit without changes +``` + +### Pattern 2: Multiple Configuration Questions + +```markdown +--- +description: Multi-question configuration +allowed-tools: AskUserQuestion, Write +--- + +# Project Configuration Setup + +Gather configuration through multiple questions. + +Use AskUserQuestion with multiple questions in one call: + +**Question 1:** +- question: "Which programming language?" +- header: "Language" +- options: Python, TypeScript, Go, Rust + +**Question 2:** +- question: "Which test framework?" +- header: "Testing" +- options: Jest, PyTest, Go Test, Cargo Test + (Adapt based on language from Q1) + +**Question 3:** +- question: "Which CI/CD platform?" +- header: "CI/CD" +- options: GitHub Actions, GitLab CI, CircleCI + +**Question 4:** +- question: "Which features do you need?" +- header: "Features" +- multiSelect: true +- options: Linting, Type checking, Code coverage, Security scanning + +Process all answers together to generate cohesive configuration. +``` + +### Pattern 3: Conditional Question Flow + +```markdown +--- +description: Conditional interactive workflow +allowed-tools: AskUserQuestion, Read, Write +--- + +# Adaptive Configuration + +## Question 1: Deployment Complexity + +Use AskUserQuestion: + +Question: "How complex is your deployment?" +Header: "Complexity" +Options: + - Simple (Single server, straightforward) + - Standard (Multiple servers, load balancing) + - Complex (Microservices, orchestration) + +## Conditional Questions Based on Answer + +If answer is "Simple": + - No additional questions + - Use minimal configuration + +If answer is "Standard": + - Ask about load balancing strategy + - Ask about scaling policy + +If answer is "Complex": + - Ask about orchestration platform (Kubernetes, Docker Swarm) + - Ask about service mesh (Istio, Linkerd, None) + - Ask about monitoring (Prometheus, Datadog, CloudWatch) + - Ask about logging aggregation + +## Process Conditional Answers + +Generate configuration appropriate for selected complexity level. +``` + +### Pattern 4: Iterative Collection + +```markdown +--- +description: Collect multiple items iteratively +allowed-tools: AskUserQuestion, Write +--- + +# Collect Team Members + +We'll collect team member information for the project. + +## Question: How many team members? + +Use AskUserQuestion: + +Question: "How many team members should we set up?" +Header: "Team size" +Options: + - 2 people + - 3 people + - 4 people + - 6 people + +## Iterate Through Team Members + +For each team member (1 to N based on answer): + +Use AskUserQuestion for member details: + +Question: "What role for team member [number]?" +Header: "Role" +Options: + - Frontend Developer + - Backend Developer + - DevOps Engineer + - QA Engineer + - Designer + +Store each member's information. + +## Generate Team Configuration + +After collecting all N members, create team configuration file with all members and their roles. +``` + +### Pattern 5: Dependency Selection + +```markdown +--- +description: Select dependencies with multi-select +allowed-tools: AskUserQuestion +--- + +# Configure Project Dependencies + +## Question: Required Libraries + +Use AskUserQuestion with multiSelect: + +Question: "Which libraries does your project need?" +Header: "Dependencies" +multiSelect: true +Options: + - React (UI framework) + - Express (Web server) + - TypeORM (Database ORM) + - Jest (Testing framework) + - Axios (HTTP client) + +User can select any combination. + +## Process Selections + +For each selected library: +- Add to package.json dependencies +- Generate sample configuration +- Create usage examples +- Update documentation +``` + +## Best Practices for Interactive Commands + +### Question Design + +1. **Clear and specific**: Question should be unambiguous +2. **Concise header**: Max 12 characters for clean display +3. **Helpful options**: Labels are clear, descriptions explain trade-offs +4. **Appropriate count**: 2-4 options per question, 1-4 questions per call +5. **Logical order**: Questions flow naturally + +### Error Handling + +```markdown +# Handle AskUserQuestion Responses + +After calling AskUserQuestion, verify answers received: + +If answers are empty or invalid: + Something went wrong gathering responses. + + Please try again or provide configuration manually: + [Show alternative approach] + + Exit. + +If answers look correct: + Process as expected +``` + +### Progressive Disclosure + +```markdown +# Start Simple, Get Detailed as Needed + +## Question 1: Setup Type + +Use AskUserQuestion: + +Question: "How would you like to set up?" +Header: "Setup type" +Options: + - Quick (Use recommended defaults) + - Custom (Configure all options) + - Guided (Step-by-step with explanations) + +If "Quick": + Apply defaults, minimal questions + +If "Custom": + Ask all available configuration questions + +If "Guided": + Ask questions with extra explanation + Provide recommendations along the way +``` + +### Multi-Select Guidelines + +**Good multi-select use:** +```markdown +Question: "Which features do you want to enable?" +multiSelect: true +Options: + - Logging + - Metrics + - Alerts + - Backups + +Reason: User might want any combination +``` + +**Bad multi-select use:** +```markdown +Question: "Which database engine?" +multiSelect: true // ❌ Should be single-select + +Reason: Can only use one database engine +``` + +## Advanced Patterns + +### Validation Loop + +```markdown +--- +description: Interactive with validation +allowed-tools: AskUserQuestion, Bash +--- + +# Setup with Validation + +## Gather Configuration + +Use AskUserQuestion to collect settings. + +## Validate Configuration + +Check if configuration is valid: +- Required dependencies available? +- Settings compatible with each other? +- No conflicts detected? + +If validation fails: + Show validation errors + + Use AskUserQuestion to ask: + + Question: "Configuration has issues. What would you like to do?" + Header: "Next step" + Options: + - Fix (Adjust settings to resolve issues) + - Override (Proceed despite warnings) + - Cancel (Abort setup) + + Based on answer, retry or proceed or exit. +``` + +### Build Configuration Incrementally + +```markdown +--- +description: Incremental configuration builder +allowed-tools: AskUserQuestion, Write, Read +--- + +# Incremental Setup + +## Phase 1: Core Settings + +Use AskUserQuestion for core settings. + +Save to `.claude/config-partial.yml` + +## Phase 2: Review Core Settings + +Show user the core settings: + +Based on these core settings, you need to configure: +- [Setting A] (because you chose [X]) +- [Setting B] (because you chose [Y]) + +Ready to continue? + +## Phase 3: Detailed Settings + +Use AskUserQuestion for settings based on Phase 1 answers. + +Merge with core settings. + +## Phase 4: Final Review + +Present complete configuration. + +Use AskUserQuestion for confirmation: + +Question: "Is this configuration correct?" +Options: + - Yes (Save and apply) + - No (Start over) + - Modify (Edit specific settings) +``` + +### Dynamic Options Based on Context + +```markdown +--- +description: Context-aware questions +allowed-tools: AskUserQuestion, Bash, Read +--- + +# Context-Aware Setup + +## Detect Current State + +Check existing configuration: +- Current language: !`detect-language.sh` +- Existing frameworks: !`detect-frameworks.sh` +- Available tools: !`check-tools.sh` + +## Ask Context-Appropriate Questions + +Based on detected language, ask relevant questions. + +If language is TypeScript: + + Use AskUserQuestion: + + Question: "Which TypeScript features should we enable?" + Options: + - Strict Mode (Maximum type safety) + - Decorators (Experimental decorator support) + - Path Mapping (Module path aliases) + +If language is Python: + + Use AskUserQuestion: + + Question: "Which Python tools should we configure?" + Options: + - Type Hints (mypy for type checking) + - Black (Code formatting) + - Pylint (Linting and style) + +Questions adapt to project context. +``` + +## Real-World Example: Multi-Agent Swarm Launch + +**From multi-agent-swarm plugin:** + +```markdown +--- +description: Launch multi-agent swarm +allowed-tools: AskUserQuestion, Read, Write, Bash +--- + +# Launch Multi-Agent Swarm + +## Interactive Mode (No Task List Provided) + +If user didn't provide task list file, help create one interactively. + +### Question 1: Agent Count + +Use AskUserQuestion: + +Question: "How many agents should we launch?" +Header: "Agent count" +Options: + - 2 agents (Best for simple projects) + - 3 agents (Good for medium projects) + - 4 agents (Standard team size) + - 6 agents (Large projects) + - 8 agents (Complex multi-component projects) + +### Question 2: Task Definition Approach + +Use AskUserQuestion: + +Question: "How would you like to define tasks?" +Header: "Task setup" +Options: + - File (I have a task list file ready) + - Guided (Help me create tasks interactively) + - Custom (Other approach) + +If "File": + Ask for file path + Validate file exists and has correct format + +If "Guided": + Enter iterative task creation mode (see below) + +### Question 3: Coordination Mode + +Use AskUserQuestion: + +Question: "How should agents coordinate?" +Header: "Coordination" +Options: + - Team Leader (One agent coordinates others) + - Collaborative (Agents coordinate as peers) + - Autonomous (Independent work, minimal coordination) + +### Iterative Task Creation (If "Guided" Selected) + +For each agent (1 to N from Question 1): + +**Question A: Agent Name** +Question: "What should we call agent [number]?" +Header: "Agent name" +Options: + - auth-agent + - api-agent + - ui-agent + - db-agent + (Provide relevant suggestions based on common patterns) + +**Question B: Task Type** +Question: "What task for [agent-name]?" +Header: "Task type" +Options: + - Authentication (User auth, JWT, OAuth) + - API Endpoints (REST/GraphQL APIs) + - UI Components (Frontend components) + - Database (Schema, migrations, queries) + - Testing (Test suites and coverage) + - Documentation (Docs, README, guides) + +**Question C: Dependencies** +Question: "What does [agent-name] depend on?" +Header: "Dependencies" +multiSelect: true +Options: + - [List of previously defined agents] + - No dependencies + +**Question D: Base Branch** +Question: "Which base branch for PR?" +Header: "PR base" +Options: + - main + - staging + - develop + +Store all task information for each agent. + +### Generate Task List File + +After collecting all agent task details: + +1. Ask for project name +2. Generate task list in proper format +3. Save to `.daisy/swarm/tasks.md` +4. Show user the file path +5. Proceed with launch using generated task list +``` + +## Best Practices + +### Question Writing + +1. **Be specific**: "Which database?" not "Choose option?" +2. **Explain trade-offs**: Describe pros/cons in option descriptions +3. **Provide context**: Question text should stand alone +4. **Guide decisions**: Help user make informed choice +5. **Keep concise**: Header max 12 chars, descriptions 1-2 sentences + +### Option Design + +1. **Meaningful labels**: Specific, clear names +2. **Informative descriptions**: Explain what each option does +3. **Show trade-offs**: Help user understand implications +4. **Consistent detail**: All options equally explained +5. **2-4 options**: Not too few, not too many + +### Flow Design + +1. **Logical order**: Questions flow naturally +2. **Build on previous**: Later questions use earlier answers +3. **Minimize questions**: Ask only what's needed +4. **Group related**: Ask related questions together +5. **Show progress**: Indicate where in flow + +### User Experience + +1. **Set expectations**: Tell user what to expect +2. **Explain why**: Help user understand purpose +3. **Provide defaults**: Suggest recommended options +4. **Allow escape**: Let user cancel or restart +5. **Confirm actions**: Summarize before executing + +## Common Patterns + +### Pattern: Feature Selection + +```markdown +Use AskUserQuestion: + +Question: "Which features do you need?" +Header: "Features" +multiSelect: true +Options: + - Authentication + - Authorization + - Rate Limiting + - Caching +``` + +### Pattern: Environment Configuration + +```markdown +Use AskUserQuestion: + +Question: "Which environment is this?" +Header: "Environment" +Options: + - Development (Local development) + - Staging (Pre-production testing) + - Production (Live environment) +``` + +### Pattern: Priority Selection + +```markdown +Use AskUserQuestion: + +Question: "What's the priority for this task?" +Header: "Priority" +Options: + - Critical (Must be done immediately) + - High (Important, do soon) + - Medium (Standard priority) + - Low (Nice to have) +``` + +### Pattern: Scope Selection + +```markdown +Use AskUserQuestion: + +Question: "What scope should we analyze?" +Header: "Scope" +Options: + - Current file (Just this file) + - Current directory (All files in directory) + - Entire project (Full codebase scan) +``` + +## Combining Arguments and Questions + +### Use Both Appropriately + +**Arguments for known values:** +```markdown +--- +argument-hint: [project-name] +allowed-tools: AskUserQuestion, Write +--- + +Setup for project: $1 + +Now gather additional configuration... + +Use AskUserQuestion for options that require explanation. +``` + +**Questions for complex choices:** +```markdown +Project name from argument: $1 + +Now use AskUserQuestion to choose: +- Architecture pattern +- Technology stack +- Deployment strategy + +These require explanation, so questions work better than arguments. +``` + +## Troubleshooting + +**Questions not appearing:** +- Verify AskUserQuestion in allowed-tools +- Check question format is correct +- Ensure options array has 2-4 items + +**User can't make selection:** +- Check option labels are clear +- Verify descriptions are helpful +- Consider if too many options +- Ensure multiSelect setting is correct + +**Flow feels confusing:** +- Reduce number of questions +- Group related questions +- Add explanation between stages +- Show progress through workflow + +With AskUserQuestion, commands become interactive wizards that guide users through complex decisions while maintaining the clarity that simple arguments provide for straightforward inputs. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/marketplace-considerations.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/marketplace-considerations.md new file mode 100644 index 0000000..03e706c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/marketplace-considerations.md @@ -0,0 +1,904 @@ +# Marketplace Considerations for Commands + +Guidelines for creating commands designed for distribution and marketplace success. + +## Overview + +Commands distributed through marketplaces need additional consideration beyond personal use commands. They must work across environments, handle diverse use cases, and provide excellent user experience for unknown users. + +## Design for Distribution + +### Universal Compatibility + +**Cross-platform considerations:** + +```markdown +--- +description: Cross-platform command +allowed-tools: Bash(*) +--- + +# Platform-Aware Command + +Detecting platform... + +case "$(uname)" in + Darwin*) PLATFORM="macOS" ;; + Linux*) PLATFORM="Linux" ;; + MINGW*|MSYS*|CYGWIN*) PLATFORM="Windows" ;; + *) PLATFORM="Unknown" ;; +esac + +Platform: $PLATFORM + + +if [ "$PLATFORM" = "Windows" ]; then + # Windows-specific handling + PATH_SEP="\\" + NULL_DEVICE="NUL" +else + # Unix-like handling + PATH_SEP="/" + NULL_DEVICE="/dev/null" +fi + +[Platform-appropriate implementation...] +``` + +**Avoid platform-specific commands:** + +```markdown + +!`pbcopy < file.txt` + + +if command -v pbcopy > /dev/null; then + pbcopy < file.txt +elif command -v xclip > /dev/null; then + xclip -selection clipboard < file.txt +elif command -v clip.exe > /dev/null; then + cat file.txt | clip.exe +else + echo "Clipboard not available on this platform" +fi +``` + +### Minimal Dependencies + +**Check for required tools:** + +```markdown +--- +description: Dependency-aware command +allowed-tools: Bash(*) +--- + +# Check Dependencies + +Required tools: +- git +- jq +- node + +Checking availability... + +MISSING_DEPS="" + +for tool in git jq node; do + if ! command -v $tool > /dev/null; then + MISSING_DEPS="$MISSING_DEPS $tool" + fi +done + +if [ -n "$MISSING_DEPS" ]; then + ❌ ERROR: Missing required dependencies:$MISSING_DEPS + + INSTALLATION: + - git: https://git-scm.com/downloads + - jq: https://stedolan.github.io/jq/download/ + - node: https://nodejs.org/ + + Install missing tools and try again. + + Exit. +fi + +✓ All dependencies available + +[Continue with command...] +``` + +**Document optional dependencies:** + +```markdown + +``` + +### Graceful Degradation + +**Handle missing features:** + +```markdown +--- +description: Feature-aware command +--- + +# Feature Detection + +Detecting available features... + +FEATURES="" + +if command -v gh > /dev/null; then + FEATURES="$FEATURES github" +fi + +if command -v docker > /dev/null; then + FEATURES="$FEATURES docker" +fi + +Available features: $FEATURES + +if echo "$FEATURES" | grep -q "github"; then + # Full functionality with GitHub integration + echo "✓ GitHub integration available" +else + # Reduced functionality without GitHub + echo "⚠ Limited functionality: GitHub CLI not installed" + echo " Install 'gh' for full features" +fi + +[Adapt behavior based on available features...] +``` + +## User Experience for Unknown Users + +### Clear Onboarding + +**First-run experience:** + +```markdown +--- +description: Command with onboarding +allowed-tools: Read, Write +--- + +# First Run Check + +if [ ! -f ".claude/command-initialized" ]; then + **Welcome to Command Name!** + + This appears to be your first time using this command. + + WHAT THIS COMMAND DOES: + [Brief explanation of purpose and benefits] + + QUICK START: + 1. Basic usage: /command [arg] + 2. For help: /command help + 3. Examples: /command examples + + SETUP: + No additional setup required. You're ready to go! + + ✓ Initialization complete + + [Create initialization marker] + + Ready to proceed with your request... +fi + +[Normal command execution...] +``` + +**Progressive feature discovery:** + +```markdown +--- +description: Command with tips +--- + +# Command Execution + +[Main functionality...] + +--- + +💡 TIP: Did you know? + +You can speed up this command with the --fast flag: + /command --fast [args] + +For more tips: /command tips +``` + +### Comprehensive Error Handling + +**Anticipate user mistakes:** + +```markdown +--- +description: Forgiving command +--- + +# User Input Handling + +Argument: "$1" + + +if [ "$1" = "hlep" ] || [ "$1" = "hepl" ]; then + Did you mean: help? + + Showing help instead... + [Display help] + + Exit. +fi + + +if [ "$1" != "valid-option1" ] && [ "$1" != "valid-option2" ]; then + ❌ Unknown option: $1 + + Did you mean: + - valid-option1 (most similar) + - valid-option2 + + For all options: /command help + + Exit. +fi + +[Command continues...] +``` + +**Helpful diagnostics:** + +```markdown +--- +description: Diagnostic command +--- + +# Operation Failed + +The operation could not complete. + +**Diagnostic Information:** + +Environment: +- Platform: $(uname) +- Shell: $SHELL +- Working directory: $(pwd) +- Command: /command $@ + +Checking common issues: +- Git repository: $(git rev-parse --git-dir 2>&1) +- Write permissions: $(test -w . && echo "OK" || echo "DENIED") +- Required files: $(test -f config.yml && echo "Found" || echo "Missing") + +This information helps debug the issue. + +For support, include the above diagnostics. +``` + +## Distribution Best Practices + +### Namespace Awareness + +**Avoid name collisions:** + +```markdown +--- +description: Namespaced command +--- + + + +# Plugin Name Command + +[Implementation...] +``` + +**Document naming rationale:** + +```markdown + +``` + +### Configurability + +**User preferences:** + +```markdown +--- +description: Configurable command +allowed-tools: Read +--- + +# Load User Configuration + +Default configuration: +- verbose: false +- color: true +- max_results: 10 + +Checking for user config: .claude/plugin-name.local.md + +if [ -f ".claude/plugin-name.local.md" ]; then + # Parse YAML frontmatter for settings + VERBOSE=$(grep "^verbose:" .claude/plugin-name.local.md | cut -d: -f2 | tr -d ' ') + COLOR=$(grep "^color:" .claude/plugin-name.local.md | cut -d: -f2 | tr -d ' ') + MAX_RESULTS=$(grep "^max_results:" .claude/plugin-name.local.md | cut -d: -f2 | tr -d ' ') + + echo "✓ Using user configuration" +else + echo "Using default configuration" + echo "Create .claude/plugin-name.local.md to customize" +fi + +[Use configuration in command...] +``` + +**Sensible defaults:** + +```markdown +--- +description: Command with smart defaults +--- + +# Smart Defaults + +Configuration: +- Format: ${FORMAT:-json} # Defaults to json +- Output: ${OUTPUT:-stdout} # Defaults to stdout +- Verbose: ${VERBOSE:-false} # Defaults to false + +These defaults work for 80% of use cases. + +Override with arguments: + /command --format yaml --output file.txt --verbose + +Or set in .claude/plugin-name.local.md: +\`\`\`yaml +--- +format: yaml +output: custom.txt +verbose: true +--- +\`\`\` +``` + +### Version Compatibility + +**Version checking:** + +```markdown +--- +description: Version-aware command +--- + + + +# Version Check + +Command version: 2.1.0 +Plugin version: [detect from plugin.json] + +if [ "$PLUGIN_VERSION" < "2.0.0" ]; then + ❌ ERROR: Incompatible plugin version + + This command requires plugin version >= 2.0.0 + Current version: $PLUGIN_VERSION + + Update plugin: + /plugin update plugin-name + + Exit. +fi + +✓ Version compatible + +[Command continues...] +``` + +**Deprecation warnings:** + +```markdown +--- +description: Command with deprecation warnings +--- + +# Deprecation Check + +if [ "$1" = "--old-flag" ]; then + ⚠️ DEPRECATION WARNING + + The --old-flag option is deprecated as of v2.0.0 + It will be removed in v3.0.0 (est. June 2025) + + Use instead: --new-flag + + Example: + Old: /command --old-flag value + New: /command --new-flag value + + See migration guide: /command migrate + + Continuing with deprecated behavior for now... +fi + +[Handle both old and new flags during deprecation period...] +``` + +## Marketplace Presentation + +### Command Discovery + +**Descriptive naming:** + +```markdown +--- +description: Review pull request with security and quality checks +--- + + +``` + +```markdown +--- +description: Do the thing +--- + + +``` + +**Searchable keywords:** + +```markdown + +``` + +### Showcase Examples + +**Compelling demonstrations:** + +```markdown +--- +description: Advanced code analysis command +--- + +# Code Analysis Command + +This command performs deep code analysis with actionable insights. + +## Demo: Quick Security Audit + +Try it now: +\`\`\` +/analyze-code src/ --security +\`\`\` + +**What you'll get:** +- Security vulnerability detection +- Code quality metrics +- Performance bottleneck identification +- Actionable recommendations + +**Sample output:** +\`\`\` +Security Analysis Results +========================= + +🔴 Critical (2): + - SQL injection risk in users.js:45 + - XSS vulnerability in display.js:23 + +🟡 Warnings (5): + - Unvalidated input in api.js:67 + ... + +Recommendations: +1. Fix critical issues immediately +2. Review warnings before next release +3. Run /analyze-code --fix for auto-fixes +\`\`\` + +--- + +Ready to analyze your code... + +[Command implementation...] +``` + +### User Reviews and Feedback + +**Feedback mechanism:** + +```markdown +--- +description: Command with feedback +--- + +# Command Complete + +[Command results...] + +--- + +**How was your experience?** + +This helps improve the command for everyone. + +Rate this command: +- 👍 Helpful +- 👎 Not helpful +- 🐛 Found a bug +- 💡 Have a suggestion + +Reply with an emoji or: +- /command feedback + +Your feedback matters! +``` + +**Usage analytics preparation:** + +```markdown + +``` + +## Quality Standards + +### Professional Polish + +**Consistent branding:** + +```markdown +--- +description: Branded command +--- + +# ✨ Command Name + +Part of the [Plugin Name] suite + +[Command functionality...] + +--- + +**Need Help?** +- Documentation: https://docs.example.com +- Support: support@example.com +- Community: https://community.example.com + +Powered by Plugin Name v2.1.0 +``` + +**Attention to detail:** + +```markdown + + +✓ Use proper emoji/symbols consistently +✓ Align output columns neatly +✓ Format numbers with thousands separators +✓ Use color/formatting appropriately +✓ Provide progress indicators +✓ Show estimated time remaining +✓ Confirm successful operations +``` + +### Reliability + +**Idempotency:** + +```markdown +--- +description: Idempotent command +--- + +# Safe Repeated Execution + +Checking if operation already completed... + +if [ -f ".claude/operation-completed.flag" ]; then + ℹ️ Operation already completed + + Completed at: $(cat .claude/operation-completed.flag) + + To re-run: + 1. Remove flag: rm .claude/operation-completed.flag + 2. Run command again + + Otherwise, no action needed. + + Exit. +fi + +Performing operation... + +[Safe, repeatable operation...] + +Marking complete... +echo "$(date)" > .claude/operation-completed.flag +``` + +**Atomic operations:** + +```markdown +--- +description: Atomic command +--- + +# Atomic Operation + +This operation is atomic - either fully succeeds or fully fails. + +Creating temporary workspace... +TEMP_DIR=$(mktemp -d) + +Performing changes in isolated environment... +[Make changes in $TEMP_DIR] + +if [ $? -eq 0 ]; then + ✓ Changes validated + + Applying changes atomically... + mv $TEMP_DIR/* ./target/ + + ✓ Operation complete +else + ❌ Changes failed validation + + Rolling back... + rm -rf $TEMP_DIR + + No changes applied. Safe to retry. +fi +``` + +## Testing for Distribution + +### Pre-Release Checklist + +```markdown + +``` + +### Beta Testing + +**Beta release approach:** + +```markdown +--- +description: Beta command (v0.9.0) +--- + +# 🧪 Beta Command + +**This is a beta release** + +Features may change based on feedback. + +BETA STATUS: +- Version: 0.9.0 +- Stability: Experimental +- Support: Limited +- Feedback: Encouraged + +Known limitations: +- Performance not optimized +- Some edge cases not handled +- Documentation incomplete + +Help improve this command: +- Report issues: /command report-issue +- Suggest features: /command suggest +- Join beta testers: /command join-beta + +--- + +[Command implementation...] + +--- + +**Thank you for beta testing!** + +Your feedback helps make this command better. +``` + +## Maintenance and Updates + +### Update Strategy + +**Versioned commands:** + +```markdown + +``` + +**Update notifications:** + +```markdown +--- +description: Update-aware command +--- + +# Check for Updates + +Current version: 2.1.0 +Latest version: [check if available] + +if [ "$CURRENT_VERSION" != "$LATEST_VERSION" ]; then + 📢 UPDATE AVAILABLE + + New version: $LATEST_VERSION + Current: $CURRENT_VERSION + + What's new: + - Feature improvements + - Bug fixes + - Performance enhancements + + Update with: + /plugin update plugin-name + + Release notes: https://releases.example.com/v$LATEST_VERSION +fi + +[Command continues...] +``` + +## Best Practices Summary + +### Distribution Design + +1. **Universal**: Works across platforms and environments +2. **Self-contained**: Minimal dependencies, clear requirements +3. **Graceful**: Degrades gracefully when features unavailable +4. **Forgiving**: Anticipates and handles user mistakes +5. **Helpful**: Clear errors, good defaults, excellent docs + +### Marketplace Success + +1. **Discoverable**: Clear name, good description, searchable keywords +2. **Professional**: Polished presentation, consistent branding +3. **Reliable**: Tested thoroughly, handles edge cases +4. **Maintainable**: Versioned, updated regularly, supported +5. **User-focused**: Great UX, responsive to feedback + +### Quality Standards + +1. **Complete**: Fully documented, all features working +2. **Tested**: Works in real environments, edge cases handled +3. **Secure**: No vulnerabilities, safe operations +4. **Performant**: Reasonable speed, resource-efficient +5. **Ethical**: Privacy-respecting, user consent + +With these considerations, commands become marketplace-ready and delight users across diverse environments and use cases. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/plugin-features-reference.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/plugin-features-reference.md new file mode 100644 index 0000000..c89e906 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/plugin-features-reference.md @@ -0,0 +1,609 @@ +# Plugin-Specific Command Features Reference + +This reference covers features and patterns specific to commands bundled in Claude Code plugins. + +## Table of Contents + +- [Plugin Command Discovery](#plugin-command-discovery) +- [CLAUDE_PLUGIN_ROOT Environment Variable](#claude_plugin_root-environment-variable) +- [Plugin Command Patterns](#plugin-command-patterns) +- [Integration with Plugin Components](#integration-with-plugin-components) +- [Validation Patterns](#validation-patterns) + +## Plugin Command Discovery + +### Auto-Discovery + +Claude Code automatically discovers commands in plugins using the following locations: + +``` +plugin-name/ +├── commands/ # Auto-discovered commands +│ ├── foo.md # /foo (plugin:plugin-name) +│ └── bar.md # /bar (plugin:plugin-name) +└── plugin.json # Plugin manifest +``` + +**Key points:** +- Commands are discovered at plugin load time +- No manual registration required +- Commands appear in `/help` with "(plugin:plugin-name)" label +- Subdirectories create namespaces + +### Namespaced Plugin Commands + +Organize commands in subdirectories for logical grouping: + +``` +plugin-name/ +└── commands/ + ├── review/ + │ ├── security.md # /security (plugin:plugin-name:review) + │ └── style.md # /style (plugin:plugin-name:review) + └── deploy/ + ├── staging.md # /staging (plugin:plugin-name:deploy) + └── prod.md # /prod (plugin:plugin-name:deploy) +``` + +**Namespace behavior:** +- Subdirectory name becomes namespace +- Shown as "(plugin:plugin-name:namespace)" in `/help` +- Helps organize related commands +- Use when plugin has 5+ commands + +### Command Naming Conventions + +**Plugin command names should:** +1. Be descriptive and action-oriented +2. Avoid conflicts with common command names +3. Use hyphens for multi-word names +4. Consider prefixing with plugin name for uniqueness + +**Examples:** +``` +Good: +- /mylyn-sync (plugin-specific prefix) +- /analyze-performance (descriptive action) +- /docker-compose-up (clear purpose) + +Avoid: +- /test (conflicts with common name) +- /run (too generic) +- /do-stuff (not descriptive) +``` + +## CLAUDE_PLUGIN_ROOT Environment Variable + +### Purpose + +`${CLAUDE_PLUGIN_ROOT}` is a special environment variable available in plugin commands that resolves to the absolute path of the plugin directory. + +**Why it matters:** +- Enables portable paths within plugin +- Allows referencing plugin files and scripts +- Works across different installations +- Essential for multi-file plugin operations + +### Basic Usage + +Reference files within your plugin: + +```markdown +--- +description: Analyze using plugin script +allowed-tools: Bash(node:*), Read +--- + +Run analysis: !`node ${CLAUDE_PLUGIN_ROOT}/scripts/analyze.js` + +Read template: @${CLAUDE_PLUGIN_ROOT}/templates/report.md +``` + +**Expands to:** +``` +Run analysis: !`node /path/to/plugins/plugin-name/scripts/analyze.js` + +Read template: @/path/to/plugins/plugin-name/templates/report.md +``` + +### Common Patterns + +#### 1. Executing Plugin Scripts + +```markdown +--- +description: Run custom linter from plugin +allowed-tools: Bash(node:*) +--- + +Lint results: !`node ${CLAUDE_PLUGIN_ROOT}/bin/lint.js $1` + +Review the linting output and suggest fixes. +``` + +#### 2. Loading Configuration Files + +```markdown +--- +description: Deploy using plugin configuration +allowed-tools: Read, Bash(*) +--- + +Configuration: @${CLAUDE_PLUGIN_ROOT}/config/deploy-config.json + +Deploy application using the configuration above for $1 environment. +``` + +#### 3. Accessing Plugin Resources + +```markdown +--- +description: Generate report from template +--- + +Use this template: @${CLAUDE_PLUGIN_ROOT}/templates/api-report.md + +Generate a report for @$1 following the template format. +``` + +#### 4. Multi-Step Plugin Workflows + +```markdown +--- +description: Complete plugin workflow +allowed-tools: Bash(*), Read +--- + +Step 1 - Prepare: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/prepare.sh $1` +Step 2 - Config: @${CLAUDE_PLUGIN_ROOT}/config/$1.json +Step 3 - Execute: !`${CLAUDE_PLUGIN_ROOT}/bin/execute $1` + +Review results and report status. +``` + +### Best Practices + +1. **Always use for plugin-internal paths:** + ```markdown + # Good + @${CLAUDE_PLUGIN_ROOT}/templates/foo.md + + # Bad + @./templates/foo.md # Relative to current directory, not plugin + ``` + +2. **Validate file existence:** + ```markdown + --- + description: Use plugin config if exists + allowed-tools: Bash(test:*), Read + --- + + !`test -f ${CLAUDE_PLUGIN_ROOT}/config.json && echo "exists" || echo "missing"` + + If config exists, load it: @${CLAUDE_PLUGIN_ROOT}/config.json + Otherwise, use defaults... + ``` + +3. **Document plugin file structure:** + ```markdown + + ``` + +4. **Combine with arguments:** + ```markdown + Run: !`${CLAUDE_PLUGIN_ROOT}/bin/process.sh $1 $2` + ``` + +### Troubleshooting + +**Variable not expanding:** +- Ensure command is loaded from plugin +- Check bash execution is allowed +- Verify syntax is exact: `${CLAUDE_PLUGIN_ROOT}` + +**File not found errors:** +- Verify file exists in plugin directory +- Check file path is correct relative to plugin root +- Ensure file permissions allow reading/execution + +**Path with spaces:** +- Bash commands automatically handle spaces +- File references work with spaces in paths +- No special quoting needed + +## Plugin Command Patterns + +### Pattern 1: Configuration-Based Commands + +Commands that load plugin-specific configuration: + +```markdown +--- +description: Deploy using plugin settings +allowed-tools: Read, Bash(*) +--- + +Load configuration: @${CLAUDE_PLUGIN_ROOT}/deploy-config.json + +Deploy to $1 environment using: +1. Configuration settings above +2. Current git branch: !`git branch --show-current` +3. Application version: !`cat package.json | grep version` + +Execute deployment and monitor progress. +``` + +**When to use:** Commands that need consistent settings across invocations + +### Pattern 2: Template-Based Generation + +Commands that use plugin templates: + +```markdown +--- +description: Generate documentation from template +argument-hint: [component-name] +--- + +Template: @${CLAUDE_PLUGIN_ROOT}/templates/component-docs.md + +Generate documentation for $1 component following the template structure. +Include: +- Component purpose and usage +- API reference +- Examples +- Testing guidelines +``` + +**When to use:** Standardized output generation + +### Pattern 3: Multi-Script Workflow + +Commands that orchestrate multiple plugin scripts: + +```markdown +--- +description: Complete build and test workflow +allowed-tools: Bash(*) +--- + +Build: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/build.sh` +Validate: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/validate.sh` +Test: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/test.sh` + +Review all outputs and report: +1. Build status +2. Validation results +3. Test results +4. Recommended next steps +``` + +**When to use:** Complex plugin workflows with multiple steps + +### Pattern 4: Environment-Aware Commands + +Commands that adapt to environment: + +```markdown +--- +description: Deploy based on environment +argument-hint: [dev|staging|prod] +--- + +Environment config: @${CLAUDE_PLUGIN_ROOT}/config/$1.json + +Environment check: !`echo "Deploying to: $1"` + +Deploy application using $1 environment configuration. +Verify deployment and run smoke tests. +``` + +**When to use:** Commands that behave differently per environment + +### Pattern 5: Plugin Data Management + +Commands that manage plugin-specific data: + +```markdown +--- +description: Save analysis results to plugin cache +allowed-tools: Bash(*), Read, Write +--- + +Cache directory: ${CLAUDE_PLUGIN_ROOT}/cache/ + +Analyze @$1 and save results to cache: +!`mkdir -p ${CLAUDE_PLUGIN_ROOT}/cache && date > ${CLAUDE_PLUGIN_ROOT}/cache/last-run.txt` + +Store analysis for future reference and comparison. +``` + +**When to use:** Commands that need persistent data storage + +## Integration with Plugin Components + +### Invoking Plugin Agents + +Commands can trigger plugin agents using the Task tool: + +```markdown +--- +description: Deep analysis using plugin agent +argument-hint: [file-path] +--- + +Initiate deep code analysis of @$1 using the code-analyzer agent. + +The agent will: +1. Analyze code structure +2. Identify patterns +3. Suggest improvements +4. Generate detailed report + +Note: This uses the Task tool to launch the plugin's code-analyzer agent. +``` + +**Key points:** +- Agent must be defined in plugin's `agents/` directory +- Claude will automatically use Task tool to launch agent +- Agent has access to same plugin resources + +### Invoking Plugin Skills + +Commands can reference plugin skills for specialized knowledge: + +```markdown +--- +description: API documentation with best practices +argument-hint: [api-file] +--- + +Document the API in @$1 following our API documentation standards. + +Use the api-docs-standards skill to ensure documentation includes: +- Endpoint descriptions +- Parameter specifications +- Response formats +- Error codes +- Usage examples + +Note: This leverages the plugin's api-docs-standards skill for consistency. +``` + +**Key points:** +- Skill must be defined in plugin's `skills/` directory +- Mention skill by name to hint Claude should invoke it +- Skills provide specialized domain knowledge + +### Coordinating with Plugin Hooks + +Commands can be designed to work with plugin hooks: + +```markdown +--- +description: Commit with pre-commit validation +allowed-tools: Bash(git:*) +--- + +Stage changes: !\`git add $1\` + +Commit changes: !\`git commit -m "$2"\` + +Note: This commit will trigger the plugin's pre-commit hook for validation. +Review hook output for any issues. +``` + +**Key points:** +- Hooks execute automatically on events +- Commands can prepare state for hooks +- Document hook interaction in command + +### Multi-Component Plugin Commands + +Commands that coordinate multiple plugin components: + +```markdown +--- +description: Comprehensive code review workflow +argument-hint: [file-path] +--- + +File to review: @$1 + +Execute comprehensive review: + +1. **Static Analysis** (via plugin scripts) + !`node ${CLAUDE_PLUGIN_ROOT}/scripts/lint.js $1` + +2. **Deep Review** (via plugin agent) + Launch the code-reviewer agent for detailed analysis. + +3. **Best Practices** (via plugin skill) + Use the code-standards skill to ensure compliance. + +4. **Documentation** (via plugin template) + Template: @${CLAUDE_PLUGIN_ROOT}/templates/review-report.md + +Generate final report combining all outputs. +``` + +**When to use:** Complex workflows leveraging multiple plugin capabilities + +## Validation Patterns + +### Input Validation + +Commands should validate inputs before processing: + +```markdown +--- +description: Deploy to environment with validation +argument-hint: [environment] +--- + +Validate environment: !`echo "$1" | grep -E "^(dev|staging|prod)$" || echo "INVALID"` + +$IF($1 in [dev, staging, prod], + Deploy to $1 environment using validated configuration, + ERROR: Invalid environment '$1'. Must be one of: dev, staging, prod +) +``` + +**Validation approaches:** +1. Bash validation using grep/test +2. Inline validation in prompt +3. Script-based validation + +### File Existence Checks + +Verify required files exist: + +```markdown +--- +description: Process configuration file +argument-hint: [config-file] +--- + +Check file: !`test -f $1 && echo "EXISTS" || echo "MISSING"` + +Process configuration if file exists: @$1 + +If file doesn't exist, explain: +- Expected location +- Required format +- How to create it +``` + +### Required Arguments + +Validate required arguments provided: + +```markdown +--- +description: Create deployment with version +argument-hint: [environment] [version] +--- + +Validate inputs: !`test -n "$1" -a -n "$2" && echo "OK" || echo "MISSING"` + +$IF($1 AND $2, + Deploy version $2 to $1 environment, + ERROR: Both environment and version required. Usage: /deploy [env] [version] +) +``` + +### Plugin Resource Validation + +Verify plugin resources available: + +```markdown +--- +description: Run analysis with plugin tools +allowed-tools: Bash(test:*) +--- + +Validate plugin setup: +- Config exists: !`test -f ${CLAUDE_PLUGIN_ROOT}/config.json && echo "✓" || echo "✗"` +- Scripts exist: !`test -d ${CLAUDE_PLUGIN_ROOT}/scripts && echo "✓" || echo "✗"` +- Tools available: !`test -x ${CLAUDE_PLUGIN_ROOT}/bin/analyze && echo "✓" || echo "✗"` + +If all checks pass, proceed with analysis. +Otherwise, report missing components and installation steps. +``` + +### Output Validation + +Validate command execution results: + +```markdown +--- +description: Build and validate output +allowed-tools: Bash(*) +--- + +Build: !`bash ${CLAUDE_PLUGIN_ROOT}/scripts/build.sh` + +Validate output: +- Exit code: !`echo $?` +- Output exists: !`test -d dist && echo "✓" || echo "✗"` +- File count: !`find dist -type f | wc -l` + +Report build status and any validation failures. +``` + +### Graceful Error Handling + +Handle errors gracefully with helpful messages: + +```markdown +--- +description: Process file with error handling +argument-hint: [file-path] +--- + +Try processing: !`node ${CLAUDE_PLUGIN_ROOT}/scripts/process.js $1 2>&1 || echo "ERROR: $?"` + +If processing succeeded: +- Report results +- Suggest next steps + +If processing failed: +- Explain likely causes +- Provide troubleshooting steps +- Suggest alternative approaches +``` + +## Best Practices Summary + +### Plugin Commands Should: + +1. **Use ${CLAUDE_PLUGIN_ROOT} for all plugin-internal paths** + - Scripts, templates, configuration, resources + +2. **Validate inputs early** + - Check required arguments + - Verify file existence + - Validate argument formats + +3. **Document plugin structure** + - Explain required files + - Document script purposes + - Clarify dependencies + +4. **Integrate with plugin components** + - Reference agents for complex tasks + - Use skills for specialized knowledge + - Coordinate with hooks when relevant + +5. **Provide helpful error messages** + - Explain what went wrong + - Suggest how to fix + - Offer alternatives + +6. **Handle edge cases** + - Missing files + - Invalid arguments + - Failed script execution + - Missing dependencies + +7. **Keep commands focused** + - One clear purpose per command + - Delegate complex logic to scripts + - Use agents for multi-step workflows + +8. **Test across installations** + - Verify paths work everywhere + - Test with different arguments + - Validate error cases + +--- + +For general command development, see main SKILL.md. +For command examples, see examples/ directory. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/testing-strategies.md b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/testing-strategies.md new file mode 100644 index 0000000..7b482fb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/command-development/references/testing-strategies.md @@ -0,0 +1,702 @@ +# Command Testing Strategies + +Comprehensive strategies for testing slash commands before deployment and distribution. + +## Overview + +Testing commands ensures they work correctly, handle edge cases, and provide good user experience. A systematic testing approach catches issues early and builds confidence in command reliability. + +## Testing Levels + +### Level 1: Syntax and Structure Validation + +**What to test:** +- YAML frontmatter syntax +- Markdown format +- File location and naming + +**How to test:** + +```bash +# Validate YAML frontmatter +head -n 20 .claude/commands/my-command.md | grep -A 10 "^---" + +# Check for closing frontmatter marker +head -n 20 .claude/commands/my-command.md | grep -c "^---" # Should be 2 + +# Verify file has .md extension +ls .claude/commands/*.md + +# Check file is in correct location +test -f .claude/commands/my-command.md && echo "Found" || echo "Missing" +``` + +**Automated validation script:** + +```bash +#!/bin/bash +# validate-command.sh + +COMMAND_FILE="$1" + +if [ ! -f "$COMMAND_FILE" ]; then + echo "ERROR: File not found: $COMMAND_FILE" + exit 1 +fi + +# Check .md extension +if [[ ! "$COMMAND_FILE" =~ \.md$ ]]; then + echo "ERROR: File must have .md extension" + exit 1 +fi + +# Validate YAML frontmatter if present +if head -n 1 "$COMMAND_FILE" | grep -q "^---"; then + # Count frontmatter markers + MARKERS=$(head -n 50 "$COMMAND_FILE" | grep -c "^---") + if [ "$MARKERS" -ne 2 ]; then + echo "ERROR: Invalid YAML frontmatter (need exactly 2 '---' markers)" + exit 1 + fi + echo "✓ YAML frontmatter syntax valid" +fi + +# Check for empty file +if [ ! -s "$COMMAND_FILE" ]; then + echo "ERROR: File is empty" + exit 1 +fi + +echo "✓ Command file structure valid" +``` + +### Level 2: Frontmatter Field Validation + +**What to test:** +- Field types correct +- Values in valid ranges +- Required fields present (if any) + +**Validation script:** + +```bash +#!/bin/bash +# validate-frontmatter.sh + +COMMAND_FILE="$1" + +# Extract YAML frontmatter +FRONTMATTER=$(sed -n '/^---$/,/^---$/p' "$COMMAND_FILE" | sed '1d;$d') + +if [ -z "$FRONTMATTER" ]; then + echo "No frontmatter to validate" + exit 0 +fi + +# Check 'model' field if present +if echo "$FRONTMATTER" | grep -q "^model:"; then + MODEL=$(echo "$FRONTMATTER" | grep "^model:" | cut -d: -f2 | tr -d ' ') + if ! echo "sonnet opus haiku" | grep -qw "$MODEL"; then + echo "ERROR: Invalid model '$MODEL' (must be sonnet, opus, or haiku)" + exit 1 + fi + echo "✓ Model field valid: $MODEL" +fi + +# Check 'allowed-tools' field format +if echo "$FRONTMATTER" | grep -q "^allowed-tools:"; then + echo "✓ allowed-tools field present" + # Could add more sophisticated validation here +fi + +# Check 'description' length +if echo "$FRONTMATTER" | grep -q "^description:"; then + DESC=$(echo "$FRONTMATTER" | grep "^description:" | cut -d: -f2-) + LENGTH=${#DESC} + if [ "$LENGTH" -gt 80 ]; then + echo "WARNING: Description length $LENGTH (recommend < 60 chars)" + else + echo "✓ Description length acceptable: $LENGTH chars" + fi +fi + +echo "✓ Frontmatter fields valid" +``` + +### Level 3: Manual Command Invocation + +**What to test:** +- Command appears in `/help` +- Command executes without errors +- Output is as expected + +**Test procedure:** + +```bash +# 1. Start Claude Code +claude --debug + +# 2. Check command appears in help +> /help +# Look for your command in the list + +# 3. Invoke command without arguments +> /my-command +# Check for reasonable error or behavior + +# 4. Invoke with valid arguments +> /my-command arg1 arg2 +# Verify expected behavior + +# 5. Check debug logs +tail -f ~/.claude/debug-logs/latest +# Look for errors or warnings +``` + +### Level 4: Argument Testing + +**What to test:** +- Positional arguments work ($1, $2, etc.) +- $ARGUMENTS captures all arguments +- Missing arguments handled gracefully +- Invalid arguments detected + +**Test matrix:** + +| Test Case | Command | Expected Result | +|-----------|---------|-----------------| +| No args | `/cmd` | Graceful handling or useful message | +| One arg | `/cmd arg1` | $1 substituted correctly | +| Two args | `/cmd arg1 arg2` | $1 and $2 substituted | +| Extra args | `/cmd a b c d` | All captured or extras ignored appropriately | +| Special chars | `/cmd "arg with spaces"` | Quotes handled correctly | +| Empty arg | `/cmd ""` | Empty string handled | + +**Test script:** + +```bash +#!/bin/bash +# test-command-arguments.sh + +COMMAND="$1" + +echo "Testing argument handling for /$COMMAND" +echo + +echo "Test 1: No arguments" +echo " Command: /$COMMAND" +echo " Expected: [describe expected behavior]" +echo " Manual test required" +echo + +echo "Test 2: Single argument" +echo " Command: /$COMMAND test-value" +echo " Expected: 'test-value' appears in output" +echo " Manual test required" +echo + +echo "Test 3: Multiple arguments" +echo " Command: /$COMMAND arg1 arg2 arg3" +echo " Expected: All arguments used appropriately" +echo " Manual test required" +echo + +echo "Test 4: Special characters" +echo " Command: /$COMMAND \"value with spaces\"" +echo " Expected: Entire phrase captured" +echo " Manual test required" +``` + +### Level 5: File Reference Testing + +**What to test:** +- @ syntax loads file contents +- Non-existent files handled +- Large files handled appropriately +- Multiple file references work + +**Test procedure:** + +```bash +# Create test files +echo "Test content" > /tmp/test-file.txt +echo "Second file" > /tmp/test-file-2.txt + +# Test single file reference +> /my-command /tmp/test-file.txt +# Verify file content is read + +# Test non-existent file +> /my-command /tmp/nonexistent.txt +# Verify graceful error handling + +# Test multiple files +> /my-command /tmp/test-file.txt /tmp/test-file-2.txt +# Verify both files processed + +# Test large file +dd if=/dev/zero of=/tmp/large-file.bin bs=1M count=100 +> /my-command /tmp/large-file.bin +# Verify reasonable behavior (may truncate or warn) + +# Cleanup +rm /tmp/test-file*.txt /tmp/large-file.bin +``` + +### Level 6: Bash Execution Testing + +**What to test:** +- !` commands execute correctly +- Command output included in prompt +- Command failures handled +- Security: only allowed commands run + +**Test procedure:** + +```bash +# Create test command with bash execution +cat > .claude/commands/test-bash.md << 'EOF' +--- +description: Test bash execution +allowed-tools: Bash(echo:*), Bash(date:*) +--- + +Current date: !`date` +Test output: !`echo "Hello from bash"` + +Analysis of output above... +EOF + +# Test in Claude Code +> /test-bash +# Verify: +# 1. Date appears correctly +# 2. Echo output appears +# 3. No errors in debug logs + +# Test with disallowed command (should fail or be blocked) +cat > .claude/commands/test-forbidden.md << 'EOF' +--- +description: Test forbidden command +allowed-tools: Bash(echo:*) +--- + +Trying forbidden: !`ls -la /` +EOF + +> /test-forbidden +# Verify: Permission denied or appropriate error +``` + +### Level 7: Integration Testing + +**What to test:** +- Commands work with other plugin components +- Commands interact correctly with each other +- State management works across invocations +- Workflow commands execute in sequence + +**Test scenarios:** + +**Scenario 1: Command + Hook Integration** + +```bash +# Setup: Command that triggers a hook +# Test: Invoke command, verify hook executes + +# Command: .claude/commands/risky-operation.md +# Hook: PreToolUse that validates the operation + +> /risky-operation +# Verify: Hook executes and validates before command completes +``` + +**Scenario 2: Command Sequence** + +```bash +# Setup: Multi-command workflow +> /workflow-init +# Verify: State file created + +> /workflow-step2 +# Verify: State file read, step 2 executes + +> /workflow-complete +# Verify: State file cleaned up +``` + +**Scenario 3: Command + MCP Integration** + +```bash +# Setup: Command uses MCP tools +# Test: Verify MCP server accessible + +> /mcp-command +# Verify: +# 1. MCP server starts (if stdio) +# 2. Tool calls succeed +# 3. Results included in output +``` + +## Automated Testing Approaches + +### Command Test Suite + +Create a test suite script: + +```bash +#!/bin/bash +# test-commands.sh - Command test suite + +TEST_DIR=".claude/commands" +FAILED_TESTS=0 + +echo "Command Test Suite" +echo "==================" +echo + +for cmd_file in "$TEST_DIR"/*.md; do + cmd_name=$(basename "$cmd_file" .md) + echo "Testing: $cmd_name" + + # Validate structure + if ./validate-command.sh "$cmd_file"; then + echo " ✓ Structure valid" + else + echo " ✗ Structure invalid" + ((FAILED_TESTS++)) + fi + + # Validate frontmatter + if ./validate-frontmatter.sh "$cmd_file"; then + echo " ✓ Frontmatter valid" + else + echo " ✗ Frontmatter invalid" + ((FAILED_TESTS++)) + fi + + echo +done + +echo "==================" +echo "Tests complete" +echo "Failed: $FAILED_TESTS" + +exit $FAILED_TESTS +``` + +### Pre-Commit Hook + +Validate commands before committing: + +```bash +#!/bin/bash +# .git/hooks/pre-commit + +echo "Validating commands..." + +COMMANDS_CHANGED=$(git diff --cached --name-only | grep "\.claude/commands/.*\.md") + +if [ -z "$COMMANDS_CHANGED" ]; then + echo "No commands changed" + exit 0 +fi + +for cmd in $COMMANDS_CHANGED; do + echo "Checking: $cmd" + + if ! ./scripts/validate-command.sh "$cmd"; then + echo "ERROR: Command validation failed: $cmd" + exit 1 + fi +done + +echo "✓ All commands valid" +``` + +### Continuous Testing + +Test commands in CI/CD: + +```yaml +# .github/workflows/test-commands.yml +name: Test Commands + +on: [push, pull_request] + +jobs: + test: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v2 + + - name: Validate command structure + run: | + for cmd in .claude/commands/*.md; do + echo "Testing: $cmd" + ./scripts/validate-command.sh "$cmd" + done + + - name: Validate frontmatter + run: | + for cmd in .claude/commands/*.md; do + ./scripts/validate-frontmatter.sh "$cmd" + done + + - name: Check for TODOs + run: | + if grep -r "TODO" .claude/commands/; then + echo "ERROR: TODOs found in commands" + exit 1 + fi +``` + +## Edge Case Testing + +### Test Edge Cases + +**Empty arguments:** +```bash +> /cmd "" +> /cmd '' '' +``` + +**Special characters:** +```bash +> /cmd "arg with spaces" +> /cmd arg-with-dashes +> /cmd arg_with_underscores +> /cmd arg/with/slashes +> /cmd 'arg with "quotes"' +``` + +**Long arguments:** +```bash +> /cmd $(python -c "print('a' * 10000)") +``` + +**Unusual file paths:** +```bash +> /cmd ./file +> /cmd ../file +> /cmd ~/file +> /cmd "/path with spaces/file" +``` + +**Bash command edge cases:** +```markdown +# Commands that might fail +!`exit 1` +!`false` +!`command-that-does-not-exist` + +# Commands with special output +!`echo ""` +!`cat /dev/null` +!`yes | head -n 1000000` +``` + +## Performance Testing + +### Response Time Testing + +```bash +#!/bin/bash +# test-command-performance.sh + +COMMAND="$1" + +echo "Testing performance of /$COMMAND" +echo + +for i in {1..5}; do + echo "Run $i:" + START=$(date +%s%N) + + # Invoke command (manual step - record time) + echo " Invoke: /$COMMAND" + echo " Start time: $START" + echo " (Record end time manually)" + echo +done + +echo "Analyze results:" +echo " - Average response time" +echo " - Variance" +echo " - Acceptable threshold: < 3 seconds for fast commands" +``` + +### Resource Usage Testing + +```bash +# Monitor Claude Code during command execution +# In terminal 1: +claude --debug + +# In terminal 2: +watch -n 1 'ps aux | grep claude' + +# Execute command and observe: +# - Memory usage +# - CPU usage +# - Process count +``` + +## User Experience Testing + +### Usability Checklist + +- [ ] Command name is intuitive +- [ ] Description is clear in `/help` +- [ ] Arguments are well-documented +- [ ] Error messages are helpful +- [ ] Output is formatted readably +- [ ] Long-running commands show progress +- [ ] Results are actionable +- [ ] Edge cases have good UX + +### User Acceptance Testing + +Recruit testers: + +```markdown +# Testing Guide for Beta Testers + +## Command: /my-new-command + +### Test Scenarios + +1. **Basic usage:** + - Run: `/my-new-command` + - Expected: [describe] + - Rate clarity: 1-5 + +2. **With arguments:** + - Run: `/my-new-command arg1 arg2` + - Expected: [describe] + - Rate usefulness: 1-5 + +3. **Error case:** + - Run: `/my-new-command invalid-input` + - Expected: Helpful error message + - Rate error message: 1-5 + +### Feedback Questions + +1. Was the command easy to understand? +2. Did the output meet your expectations? +3. What would you change? +4. Would you use this command regularly? +``` + +## Testing Checklist + +Before releasing a command: + +### Structure +- [ ] File in correct location +- [ ] Correct .md extension +- [ ] Valid YAML frontmatter (if present) +- [ ] Markdown syntax correct + +### Functionality +- [ ] Command appears in `/help` +- [ ] Description is clear +- [ ] Command executes without errors +- [ ] Arguments work as expected +- [ ] File references work +- [ ] Bash execution works (if used) + +### Edge Cases +- [ ] Missing arguments handled +- [ ] Invalid arguments detected +- [ ] Non-existent files handled +- [ ] Special characters work +- [ ] Long inputs handled + +### Integration +- [ ] Works with other commands +- [ ] Works with hooks (if applicable) +- [ ] Works with MCP (if applicable) +- [ ] State management works + +### Quality +- [ ] Performance acceptable +- [ ] No security issues +- [ ] Error messages helpful +- [ ] Output formatted well +- [ ] Documentation complete + +### Distribution +- [ ] Tested by others +- [ ] Feedback incorporated +- [ ] README updated +- [ ] Examples provided + +## Debugging Failed Tests + +### Common Issues and Solutions + +**Issue: Command not appearing in /help** + +```bash +# Check file location +ls -la .claude/commands/my-command.md + +# Check permissions +chmod 644 .claude/commands/my-command.md + +# Check syntax +head -n 20 .claude/commands/my-command.md + +# Restart Claude Code +claude --debug +``` + +**Issue: Arguments not substituting** + +```bash +# Verify syntax +grep '\$1' .claude/commands/my-command.md +grep '\$ARGUMENTS' .claude/commands/my-command.md + +# Test with simple command first +echo "Test: \$1 and \$2" > .claude/commands/test-args.md +``` + +**Issue: Bash commands not executing** + +```bash +# Check allowed-tools +grep "allowed-tools" .claude/commands/my-command.md + +# Verify command syntax +grep '!\`' .claude/commands/my-command.md + +# Test command manually +date +echo "test" +``` + +**Issue: File references not working** + +```bash +# Check @ syntax +grep '@' .claude/commands/my-command.md + +# Verify file exists +ls -la /path/to/referenced/file + +# Check permissions +chmod 644 /path/to/referenced/file +``` + +## Best Practices + +1. **Test early, test often**: Validate as you develop +2. **Automate validation**: Use scripts for repeatable checks +3. **Test edge cases**: Don't just test the happy path +4. **Get feedback**: Have others test before wide release +5. **Document tests**: Keep test scenarios for regression testing +6. **Monitor in production**: Watch for issues after release +7. **Iterate**: Improve based on real usage data diff --git a/文档润色流和知识库构建流/claude-scholar/skills/daily-coding/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/daily-coding/SKILL.md new file mode 100644 index 0000000..ffa46b0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/daily-coding/SKILL.md @@ -0,0 +1,76 @@ +--- +name: daily-coding +description: Use for everyday coding tasks that involve writing or modifying source code. +version: 1.0.0 +tags: [Coding, Daily, Checklist] +--- + +# Daily Coding Checklist + +A minimal coding quality assurance checklist ensuring every code modification follows best practices. + +## When to Use + +Use this skill for: +- Implementing new features +- Adding code or modifying existing code +- User requests like "write a...", "implement...", "add...", or "modify..." +- Any coding task that involves Edit or Write tools + +## When Not to Use + +Do not use this skill for: +- Pure reading or understanding tasks with no modification intent +- Work already covered by specialized skills such as `bug-detective`, `architecture-design`, or `verification-loop` +- Configuration-only changes +- Documentation-only writing + +## Core Checklist + +### Before Starting + +- [ ] **Read before modify** - Must read target file with Read tool before making changes +- [ ] **Understand context** - Confirm understanding of existing code logic and design intent + +### During Coding + +- [ ] **Minimal changes** - Only change what's necessary, no over-engineering, no unrelated features +- [ ] **Type safety** - Add type hints for Python, avoid `any` in TypeScript +- [ ] **Security check** - Avoid command injection, XSS, SQL injection vulnerabilities + +### After Completion + +- [ ] **Verify execution** - Ensure code runs correctly with no syntax errors +- [ ] **Clean up** - Remove print/console.log debug statements and temporary files +- [ ] **Brief summary** - Inform user what was changed and the scope of impact + +## Quick Reference + +### Common Mistakes to Avoid + +```python +# ❌ Don't +def process(data=[]): # Mutable default argument + pass + +# ✅ Should +def process(data: list | None = None): + data = data or [] +``` + +```python +# ❌ Don't +except: # Bare except + pass + +# ✅ Should +except ValueError as e: + logger.error(f"Processing failed: {e}") + raise +``` + +### Security Check Points + +- User input must be validated/escaped +- Use pathlib for file paths, avoid path traversal +- Never hardcode sensitive info (API keys, passwords) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/SKILL.md new file mode 100644 index 0000000..5992723 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/SKILL.md @@ -0,0 +1,144 @@ +--- +name: daily-paper-generator +description: Use when the user asks to generate daily paper digests on a general topic. This skill supports both arXiv and bioRxiv (or either one), then produces structured Chinese/English summaries for selected papers. +version: 0.5.1 +--- + +# Daily Paper Generator + +## Overview + +Discover, screen, and summarize recent papers for any research topic. + +Supported sources: +- arXiv +- bioRxiv +- both (`--source both`) + +Core workflow: +1. Define topic query and time window +2. Search papers from arXiv / bioRxiv +3. Select Top 10 candidates per field +4. Score and narrow to Top 3 per field +5. Choose Top 1 per field +6. Generate bilingual summaries +7. Save outputs to `daily paper/` + +## When to Use + +Use this skill when: +- The user asks for a daily/weekly paper digest on any topic +- The user wants recent papers from arXiv and/or bioRxiv +- The user needs structured bilingual notes for reading and tracking + +## Output Format + +Each summary should contain: +1. Paper title +2. Authors and venue/source +3. Link(s) and date +4. Chinese review (~300 words) +5. English review (concise academic prose) +6. Metadata table +7. Appendix (optional resources) + +## Quick Reference + +| Task | Method | +|---|---| +| Search papers | Use `scripts/arxiv_search.py` with `--source arxiv|biorxiv|both` | +| Topic selection | Use general-topic queries from `references/keywords.md` | +| Evaluate quality | Use `references/quality-criteria.md` | +| Write Chinese review | Use `references/writing-style.md` | +| Write English review | Follow scientific writing best practices | + +## Workflow + +### Step 1: Define query + +Choose a concrete topic query. Examples: +- `test-time adaptation for medical imaging` +- `multimodal foundation model for healthcare` +- `protein language model interpretability` + +### Step 2: Search arXiv and/or bioRxiv + +Use helper script: + +```bash +python skills/daily-paper-generator/scripts/arxiv_search.py \ + --query "test-time adaptation for medical imaging" \ + --source both \ + --months 1 \ + --max-results 80 \ + --output /tmp/papers.json +``` + +Notes: +- `--source arxiv`: arXiv only +- `--source biorxiv`: bioRxiv only +- `--source both`: merge both sources and sort by date + +### Step 3: Top 10 candidate selection (per field) + +For each candidate paper: +1. Check topic relevance from title + abstract +2. Remove obviously off-topic papers +3. Keep **Top 10 candidates** for this field + +Minimum rule: +- Do not jump directly from raw search results to final paper. +- Keep an explicit Top 10 list first. + +### Step 4: Top 3 quality shortlist (per field) + +For the Top 10 pool: +1. Score each paper with `references/quality-criteria.md` +2. Rank by weighted score +3. Keep **Top 3** + +### Step 5: Final Top 1 selection (per field) + +For the Top 3 shortlist: +1. Compare novelty + method completeness + experimental credibility +2. Check practical impact for the field +3. Select **Top 1** as the final pick + +Required output trace: +- Top 10 candidate list +- Top 3 scored shortlist (with weighted scores) +- Final Top 1 and one-paragraph selection rationale + +### Step 6: Generate bilingual summaries + +For each selected paper, generate: +- 中文评语：背景、挑战、贡献、方法、结果、局限 +- English Review: concise, factual, non-formulaic + +### Step 7: Save output + +Recommended directory and naming: + +```text +daily paper/ + YYYY-MM-DD-HHMM-paper-1.md + YYYY-MM-DD-HHMM-paper-2.md + YYYY-MM-DD-HHMM-paper-3.md +``` + +## Additional Resources + +- `references/keywords.md`: general-topic query templates +- `references/quality-criteria.md`: scoring rubric +- `references/writing-style.md`: review writing style +- `example/daily paper example.md`: output example +- `scripts/arxiv_search.py`: arXiv + bioRxiv search helper + +## Important Notes + +1. Use explicit topic queries, avoid single-word vague queries. +2. Keep the time window explicit (`--months N`). +3. Distinguish source in metadata (`arxiv` vs `biorxiv`). +4. Use the fixed narrowing rule: **Top 10 -> Top 3 -> Top 1** (per field). +5. If a paper lacks robust evaluation, mark confidence and limitations clearly. +6. Do not fabricate unavailable fields (institution/GitHub/code links). diff --git a/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/example/daily paper example.md b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/example/daily paper example.md new file mode 100644 index 0000000..8d95ede --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/example/daily paper example.md @@ -0,0 +1,78 @@ +# DeeperBrain: A Neuro-Grounded EEG Foundation Model Towards Universal BCI + +## 作者及单位 +Jiquan Wang, Sha Zhao, Yangxuan Zhou, Yiming Kang, Shijian Li, Gang Pan +Zhejiang University, College of Computer Science and Technology + +## arXiv 链接 +https://arxiv.org/abs/2601.06134 + +**发表日期**: 2026-01-05 +**arXiv ID**: 2601.06134 +**分类**: cs.LG, q-bio.NC, eess.SP + +--- + +## 中文评语 + +通用脑机接口的发展受限于 EEG 信号的跨受试和跨任务泛化能力不足。现有基础模型大多采用通用深度学习架构，忽略了 EEG 信号的神经生理学特性和生物物理约束，且在冻结探针评估下效果有限。本研究提出 DeeperBrain，一种神经驱动的 EEG 基础模型，将领域特定的归纳偏差整合到模型设计和学习目标中。在架构层面，该方法包含基于容积传导的通道编码和神经动力学感知的时间编码。在预训练层面，引入双目标策略：掩码 EEG 重建保证局部保真度，神经动力学统计预测以强制与宏观脑状态对齐。实验结果显示，DeeperBrain 在零样本跨受试迁移、跨任务泛化和少样本学习场景下优于现有基础模型。更重要的是，它在严格的冻结探针评估下保持优越效果，验证了将神经科学第一原理嵌入模型能够赋予学习表示通用 BCI 所需的泛化能力。 + +## English Review + +Universal Brain-Computer Interfaces are constrained by the limited cross-subject and cross-task generalization of EEG signals. Most existing foundation models employ generic deep learning architectures that overlook neurophysiological characteristics and biophysical constraints, showing limited efficacy under frozen probing evaluation. This study presents DeeperBrain, a neuro-grounded EEG foundation model that integrates domain-specific inductive biases into both architecture design and learning objectives. The model incorporates volume conduction-based channel encoding and neurodynamics-aware temporal encoding to capture spatial and temporal patterns respectively. For pretraining, this study introduces a dual-objective strategy combining masked EEG reconstruction for local fidelity and neurodynamics statistics prediction to align with macroscopic brain states. Experiments show DeeperBrain outperforms existing foundation models across zero-shot cross-subject transfer, cross-task generalization, and few-shot learning scenarios. The model maintains strong performance under frozen probing evaluation, demonstrating that embedding neuroscientific first principles endows learned representations with the generalization needed for universal BCI. + +## 主图 + +这里需要将论文的主图进行下载并存放。 + +--- + +## 论文元数据 + +| 项目 | 内容 | +|------|------| +| **标题** | DeeperBrain: A Neuro-Grounded EEG Foundation Model Towards Universal BCI | +| **第一作者** | Jiquan Wang | +| **作者列表** | Jiquan Wang, Sha Zhao, Yangxuan Zhou, Yiming Kang, Shijian Li, Gang Pan | +| **第一作者单位** | Zhejiang University, College of Computer Science and Technology | +| **发表日期** | 2026-01-05 | +| **arXiv 链接** | https://arxiv.org/abs/2601.06134 | +| **PDF 链接** | https://arxiv.org/pdf/2601.06134 | +| **分类** | cs.LG, q-bio.NC, eess.SP | + +--- + +## 整合格式 + +Daily Paper 0126 + +DeeperBrain: A Neuro-Grounded EEG Foundation Model Towards Universal BCI + +https://arxiv.org/abs/2601.06134 + + + +通用脑机接口的发展受限于 EEG 信号的跨受试和跨任务泛化能力不足。现有基础模型大多采用通用深度学习架构，忽略了 EEG 信号的神经生理学特性和生物物理约束，且在冻结探针评估下效果有限。本研究提出 DeeperBrain，一种神经驱动的 EEG 基础模型，将领域特定的归纳偏差整合到模型设计和学习目标中。在架构层面，该方法包含基于容积传导的通道编码和神经动力学感知的时间编码。在预训练层面，引入双目标策略：掩码 EEG 重建保证局部保真度，神经动力学统计预测以强制与宏观脑状态对齐。实验结果显示，DeeperBrain 在零样本跨受试迁移、跨任务泛化和少样本学习场景下优于现有基础模型。更重要的是，它在严格的冻结探针评估下保持优越效果，验证了将神经科学第一原理嵌入模型能够赋予学习表示通用 BCI 所需的泛化能力。 + + + +Universal Brain-Computer Interfaces are constrained by the limited cross-subject and cross-task generalization of EEG signals. Most existing foundation models employ generic deep learning architectures that overlook neurophysiological characteristics and biophysical constraints, showing limited efficacy under frozen probing evaluation. This study presents DeeperBrain, a neuro-grounded EEG foundation model that integrates domain-specific inductive biases into both architecture design and learning objectives. The model incorporates volume conduction-based channel encoding and neurodynamics-aware temporal encoding to capture spatial and temporal patterns respectively. For pretraining, this study introduces a dual-objective strategy combining masked EEG reconstruction for local fidelity and neurodynamics statistics prediction to align with macroscopic brain states. Experiments show DeeperBrain outperforms existing foundation models across zero-shot cross-subject transfer, cross-task generalization, and few-shot learning scenarios. The model maintains strong performance under frozen probing evaluation, demonstrating that embedding neuroscientific first principles endows learned representations with the generalization needed for universal BCI. + +## 附录 + +**github连接：**未开源 + +**补充说明** + +这篇论文的重要价值在于： + +1. **跨学科融合**：将神经科学知识与深度学习结合 +2. **可解释性**：神经驱动设计提高了模型的可解释性 +3. **泛化能力**：在跨受试、跨任务场景下表现优异 +4. **实用价值**：为通用 BCI 系统的开发提供了新方向 + +**Sources:** + +- [arXiv Abstract](https://arxiv.org/abs/2601.06134) +- [arXiv HTML](https://arxiv.org/html/2601.06134v1) +- [Paperverse Review](https://paperverse.io/paper/eabc5d58-8762-4dc9-aaf3-665057852cb7) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/keywords.md b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/keywords.md new file mode 100644 index 0000000..b09aa17 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/keywords.md @@ -0,0 +1,71 @@ +# General Topic Query Templates + +## Query construction + +Use this template: + +` + + ` + +Examples: +- `test-time adaptation + medical imaging + robustness` +- `multimodal retrieval + biomedicine + contrastive learning` +- `speech representation + low-resource + self-supervised learning` + +## Topic starters + +### Machine learning +- `test-time adaptation` +- `domain generalization` +- `uncertainty estimation` +- `causal representation learning` + +### Multimodal and language +- `multimodal foundation model` +- `retrieval augmented generation` +- `vision-language model evaluation` +- `long-context reasoning` + +### Bio/health +- `protein language model` +- `single-cell foundation model` +- `computational pathology` +- `clinical prediction model calibration` + +### Neuroscience / BCI +- `EEG decoding` +- `speech decoding from EEG` +- `brain-computer interface` +- `neural signal representation learning` + +## Source-specific tips + +### arXiv +Search page pattern: + +`https://arxiv.org/search/?searchtype=all&query=&abstracts=show&order=-announced_date_first` + +API pattern: + +`https://export.arxiv.org/api/query?search_query=all:&start=0&max_results=50&sortBy=submittedDate&sortOrder=descending` + +### bioRxiv +Use API by date range and then filter by query text: + +`https://api.biorxiv.org/details/biorxiv///` + +Example: + +`https://api.biorxiv.org/details/biorxiv/2026-01-01/2026-04-23/0` + +## Practical defaults + +- Query length: 3 to 8 words +- Time range: last 3 months (`--months 3`) +- Sources: `--source both` +- Result cap: `--max-results 50` + +## Anti-patterns + +- Too broad: `AI`, `biology`, `vision` +- Too narrow with hard constraints before retrieval +- Mixing too many unrelated concepts in one query diff --git a/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/quality-criteria.md b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/quality-criteria.md new file mode 100644 index 0000000..51c1ba2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/quality-criteria.md @@ -0,0 +1,124 @@ +# 论文质量评审标准 + +## 评审维度与权重 + +| 维度 | 权重 | 说明 | +|------|------|------| +| **创新性** | 30% | 论文的创新程度和贡献的新颖性 | +| **方法完整性** | 25% | 方法的描述完整性和可复现性 | +| **实验充分性** | 25% | 实验设计的全面性和结果的可信度 | +| **写作质量** | 10% | 论文表达的清晰度和学术规范性 | +| **相关性与影响力** | 10% | 与领域的相关性和潜在影响力 | + +## 详细评分标准 + +### 1. 创新性 (30%) + +| 分数 | 标准 | +|------|------| +| **5分 - 突破性贡献** | 提出全新的范式或方法，对领域有重大影响 | +| **4分 - 显著创新** | 在现有方法上有显著改进，提出新的见解 | +| **3分 - 方法创新** | 提出了新的方法或框架，有一定的创新性 | +| **2分 - 改进型** | 对现有方法有改进，但创新有限 | +| **1分 - 增量改进** | 仅有微小的改进或组合现有方法 | + +**评估要点：** +- 是否提出了新的问题或视角？ +- 方法是否有实质性创新？ +- 是否突破了现有方法的局限？ + +### 2. 方法完整性 (25%) + +| 分数 | 标准 | +|------|------| +| **5分 - 完整且严谨** | 方法描述完整，数学推导严谨，易于复现 | +| **4分 - 非常完整** | 方法描述详细，大部分细节可复现 | +| **3分 - 可复现** | 核心方法清晰，可基本复现 | +| **2分 - 缺乏细节** | 关键细节缺失，复现困难 | +| **1分 - 表述不清** | 方法描述不清楚，无法判断有效性 | + +**评估要点：** +- 方法描述是否清晰？ +- 是否提供了足够的细节？ +- 是否有代码仓库？ +- 数学推导是否严谨？ + +### 3. 实验充分性 (25%) + +| 分数 | 标准 | +|------|------| +| **5分 - 全面深入** | 多数据集验证，充分消融实验，详细分析 | +| **4分 - 非常充分** | 多个数据集，合理消融实验 | +| **3分 - 合理验证** | 主干实验完整，结果可信 | +| **2分 - 验证不足** | 实验较少，缺乏对比 | +| **1分 - 实验不足** | 仅在简单场景验证，结果不可信 | + +**评估要点：** +- 是否在标准数据集上验证？ +- 是否有充分的对比实验？ +- 是否有消融实验？ +- 统计显著性如何？ + +### 4. 写作质量 (10%) + +| 分数 | 标准 | +|------|------| +| **5分 - 优秀** | 表达清晰，逻辑严密，学术规范 | +| **4分 - 良好** | 表达清楚，逻辑基本完整 | +| **3分 - 清晰** - 表达基本清晰，可理解 | +| **2分 - 一般** | 表述有模糊之处 | +| **1分 - 表述不清** | 表述混乱，难以理解 | + +### 5. 相关性与影响力 (10%) + +| 分数 | 标准 | +|------|------| +| **5分 - 广泛影响** | 解决重要问题，影响多个领域 | +| **4分 - 领域重要** | 解决领域内重要问题 | +| **3分 - 相关有意义** - 研究有意义，有一定影响 | +| **2分 - 小众问题** | 针对小众问题 | +| **1分 - 影响有限** - 影响非常有限 | + +## 自动评分辅助指标 + +在人工评审前，可使用以下指标辅助初筛： + +- **摘要质量**：摘要是否包含实验结果和具体数据 +- **数据集**：是否在知名数据集上验证（如 TUH EEG, BCIC IV 等） +- **代码可用性**：是否提供 GitHub 链接 +- **作者机构**：第一作者/机构的学术声誉（可选） +- **引用数**：arXiv 上的早期引用数（可选） + +## 综合评分计算 + +``` +总分 = 创新性×0.30 + 方法完整性×0.25 + 实验充分性×0.25 + 写作质量×0.10 + 相关性与影响力×0.10 +``` + +**评分示例：** +- 创新性：4分 +- 方法完整性：3分 +- 实验充分性：4分 +- 写作质量：3分 +- 相关性与影响力：4分 + +总分 = 4×0.30 + 3×0.25 + 4×0.25 + 3×0.10 + 4×0.10 = 1.2 + 0.75 + 1.0 + 0.3 + 0.4 = 3.65 + +## 评审流程 + +1. **初筛**：根据标题和摘要排除明显不相关的论文 +2. **Top 10 候选池**：每个领域先固定保留 Top 10 +3. **全文阅读**：对 Top 10 进行深度阅读/细读摘要与方法实验部分 +4. **维度打分**：按照5个维度逐一打分 +5. **计算总分**：加权计算综合得分 +6. **Top 3 shortlist**：按总分排序，选出 Top 3 +7. **Top 1 final**：在 Top 3 中结合创新性、实验可信度和领域影响力选出 Top 1 + +## 固定收敛规则（每个领域） + +- 必须遵循：**Top 10 -> Top 3 -> Top 1** +- 不允许从原始检索结果直接跳到最终 Top 1 +- 输出必须可审计，至少包含： + - Top 10 候选列表 + - Top 3 评分表（五维分数 + 加权总分） + - Top 1 选择理由 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/writing-style.md b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/writing-style.md new file mode 100644 index 0000000..856d10f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/references/writing-style.md @@ -0,0 +1,134 @@ +# 中文评语写作风格指南 + +基于 AINet Daily Paper.xlsx 中高质量示例的写作风格总结。 + +## 评语结构 + +中文评语约 300 字，遵循以下结构： + +``` +1. 背景 (1-2句) ──> 介绍研究领域的背景和重要性 +2. 挑战 (2-3句) ──> 指出现有方法面临的关键问题 +3. 贡献 (1-2句) ──> 概述本工作的核心贡献 +4. 方法 (2-3句) ──> 描述提出的方法/模型的关键技术 +5. 实验结果 (2-3句) ──> 总结主要实验发现和性能指标 +6. 分析与局限 (1-2句) ──> 分析结果意义，指出局限性 +``` + +## 常用句式模板 + +### 开头（背景） +- `本文针对...问题` +- `本研究聚焦于...` +- `本文探讨了...这一基本挑战` +- `...始终面临诸多挑战` + +### 挑战描述 +- `尽管...，但现有方法面临...` +- `然而，现有方法存在...` +- `...高度异构，而以往...难以兼顾...` +- `针对这些问题，本文提出...` + +### 方法描述 +- `为此，本文提出...` +- `该研究提出...` +- `本文提出...，一种...` +- `该方法通过...` + +### 实验结果 +- `实验结果表明...` +- `在...数据集上，该方法...` +- `实验在...上取得了...` +- `结果表明，...` + +### 分析与局限 +- `从而验证了...的可行性` +- `为...奠定方法学基础` +- `该工作打破了...` +- `从而验证了...在实际应用中的可行性` + +## 高质量示例分析 + +### 示例 1：ECHO (Toward Contextual Seq2Seq Paradigms in Large EEG Models) + +**结构分析：** +``` +[背景] 从脑电信号中统一刻画和理解多样化认知任务始终面临诸多挑战 +[挑战] 不同任务形式与标签空间差异显著，不同数据集在电极布局和采集范式上高度异构， + 而以往以编码器为中心、依赖任务专用预测头的建模方式难以兼顾泛化性与灵活性 +[方法] 为此，本文提出 ECHO，一种以解码器为核心的大规模脑电建模范式， + 将 EEG 分析重构为统一的序列到序列学习问题 +[技术细节] 该方法将连续脑电片段、任务标识与标签符号共同组织进自回归解码序列中， + 使模型能够在同一框架下理解任务语境并生成对应预测 +[实验] 在涵盖 12 个公开数据集、6 类脑电任务的统一多任务评测中， + ECHO 在整体性能、跨数据集泛化以及零样本场景下均显著优于多种代表性基线方法 +[意义] 为新一代灵活、可扩展的脑机接口系统奠定方法学基础 +``` + +### 示例 2：EEG-to-Voice Decoding + +**结构分析：** +``` +[背景] 本研究聚焦于从非侵入式 EEG 信号中重建有声语音与想象语音， + 以辅助存在言语障碍的个体进行交流 +[方法] 其技术框架包括一个被试特异的生成器，以开环方式将预处理后的 EEG 信号映射为 Mel 频谱 +[技术细节] 随后通过预训练的 HiFi-GAN 声码器和 HuBERT ASR 模块生成语音波形并解码文本 +[创新点] 该方法避免了显式的时间对齐过程，采用迁移学习将基于有声语音预训练的生成器 + 适配到想象语音任务中，并使用双损失函数进行训练 +[实验结果] 在有声语音和想象语音两种情形下均实现了稳定的声学重建性能和语言层面的重建性能 +[额外特点] 在语句长度增加的情况下仍能保持文本层面的解码性能 +[意义] 从而验证了 EEG 到语音通信在实际应用中的可行性 +``` + +## 写作要点 + +### 1. 学术语言规范 +- 使用正式的学术书面语 +- 避免口语化表达 +- 使用精确的技术术语 + +### 2. 逻辑连贯 +- 各部分之间有清晰的逻辑关系 +- 使用恰当的连接词（然而、为此、从而、同时） +- 从问题到解决方案到验证结果 + +### 3. 信息密度 +- 每句话都承载有效信息 +- 避免冗余表述 +- 突出核心贡献 + +### 4. 客观评价 +- 准确描述实验结果 +- 指出方法的局限性 +- 不夸大成果 + +## 英文评语写作 + +英文评语应与中文评语对应，保持流畅的学术英语风格： + +- 使用正式的学术英语 +- 保持与中文评语相同的结构 +- 注意时态一致性（描述论文内容用现在时，描述实验结果用过去时） +- 使用准确的学术词汇 + +### 常用句式 + +**Opening:** +- `This paper addresses the...` +- `This study focuses on...` +- `The paper proposes...` + +**Problem:** +- `While existing...` +- `However, current methods face...` +- `Despite progress in...` + +**Method:** +- `To tackle this, the research proposes...` +- `The authors present...` +- `This work introduces...` + +**Results:** +- `Experiments demonstrate that...` +- `The findings show...` +- `Results indicate that...` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/scripts/arxiv_search.py b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/scripts/arxiv_search.py new file mode 100755 index 0000000..85f5b11 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/daily-paper-generator/scripts/arxiv_search.py @@ -0,0 +1,280 @@ +#!/usr/bin/env python3 +""" +Research paper search helper for arXiv and bioRxiv. + +Usage: + python arxiv_search.py --query "test-time adaptation" --source both --max-results 30 + python arxiv_search.py --keywords multimodal representation learning --source arxiv + python arxiv_search.py --query "protein language model" --source biorxiv --months 6 +""" + +from __future__ import annotations + +import argparse +import json +import re +from datetime import datetime, timedelta +from typing import Dict, List, Optional +from urllib.parse import quote_plus +from urllib.request import urlopen + +import feedparser + + +def _safe_parse_date(value: str) -> Optional[datetime]: + if not value: + return None + for fmt in ("%Y-%m-%d", "%Y-%m-%dT%H:%M:%SZ", "%Y-%m-%dT%H:%M:%S"): + try: + return datetime.strptime(value[:19], fmt) + except ValueError: + continue + return None + + +def _in_time_window(date_text: str, months: int) -> bool: + parsed = _safe_parse_date(date_text) + if parsed is None: + return True + cutoff = datetime.now() - timedelta(days=months * 30) + return parsed >= cutoff + + +def _token_match(text: str, query: str) -> bool: + query_tokens = [t.lower() for t in re.split(r"\s+", query.strip()) if t.strip()] + if not query_tokens: + return True + hay = text.lower() + return all(tok in hay for tok in query_tokens) + + +def search_arxiv( + query: str, + max_results: int = 50, + categories: Optional[List[str]] = None, + months: int = 3, +) -> List[Dict]: + base_url = "https://export.arxiv.org/api/query?" + + if categories: + cat_query = " OR ".join([f"cat:{cat}" for cat in categories]) + search_query = f"search_query=({quote_plus(cat_query)})+AND+all:{quote_plus(query)}" + else: + search_query = f"search_query=all:{quote_plus(query)}" + + params = f"&start=0&max_results={max_results}&sortBy=submittedDate&sortOrder=descending" + url = base_url + search_query + params + + print(f"[arXiv] searching: {url}") + feed = feedparser.parse(url) + papers: List[Dict] = [] + + for entry in feed.entries: + published = datetime(*entry.published_parsed[:6]) + if not _in_time_window(published.strftime("%Y-%m-%d"), months): + continue + + authors = [author.name for author in entry.authors] if getattr(entry, "authors", None) else [] + first_author = authors[0] if authors else "Unknown" + arxiv_id = entry.id.split("/abs/")[-1] + arxiv_link = f"https://arxiv.org/abs/{arxiv_id}" + summary = re.sub(r"\s+", " ", entry.summary).strip() + + papers.append( + { + "source": "arxiv", + "title": entry.title.strip(), + "authors": authors, + "first_author": first_author, + "summary": summary, + "published": published.strftime("%Y-%m-%d"), + "id": arxiv_id, + "arxiv_id": arxiv_id, + "link": arxiv_link, + "arxiv_link": arxiv_link, + "pdf_link": f"https://arxiv.org/pdf/{arxiv_id}.pdf", + "categories": [tag.term for tag in getattr(entry, "tags", [])], + } + ) + + print(f"[arXiv] found {len(papers)} papers in last {months} month(s)") + return papers + + +def search_biorxiv(query: str, max_results: int = 50, months: int = 3) -> List[Dict]: + end_date = datetime.now().date() + start_date = (datetime.now() - timedelta(days=months * 30)).date() + + cursor = 0 + page_size = 100 + papers: List[Dict] = [] + + # bioRxiv API may reject future date ranges in environments with shifted system dates. + # Probe and step back by year until the API accepts the interval. + shift_days = 0 + while True: + probe_start = start_date - timedelta(days=shift_days) + probe_end = end_date - timedelta(days=shift_days) + probe_url = ( + "https://api.biorxiv.org/details/biorxiv/" + f"{probe_start.isoformat()}/{probe_end.isoformat()}/0" + ) + with urlopen(probe_url, timeout=30) as response: + probe_payload = json.loads(response.read().decode("utf-8")) + status = ( + probe_payload.get("messages", [{}])[0].get("status", "").strip().lower() + ) + if status != "not available at this time": + break + shift_days += 365 + if shift_days > 365 * 8: + print("[bioRxiv] API unavailable for probed date ranges.") + return [] + + if shift_days: + print( + "[bioRxiv] adjusted date window for API availability: " + f"{probe_start.isoformat()} to {probe_end.isoformat()}" + ) + + while len(papers) < max_results: + window_start = start_date - timedelta(days=shift_days) + window_end = end_date - timedelta(days=shift_days) + url = ( + "https://api.biorxiv.org/details/biorxiv/" + f"{window_start.isoformat()}/{window_end.isoformat()}/{cursor}" + ) + print(f"[bioRxiv] fetching: {url}") + with urlopen(url, timeout=30) as response: + payload = json.loads(response.read().decode("utf-8")) + + collection = payload.get("collection", []) + if not collection: + break + + for item in collection: + title = item.get("title", "").strip() + abstract = re.sub(r"\s+", " ", item.get("abstract", "")).strip() + merged_text = f"{title} {abstract}" + if not _token_match(merged_text, query): + continue + + published = item.get("date", "") + if not _in_time_window(published, months): + continue + + author_text = item.get("authors", "") + authors = [a.strip() for a in re.split(r";|,", author_text) if a.strip()] + first_author = authors[0] if authors else "Unknown" + + doi = item.get("doi", "").strip() + version = str(item.get("version", "1")).strip() or "1" + if doi: + link = f"https://www.biorxiv.org/content/{doi}v{version}" + else: + link = item.get("url", "") + + papers.append( + { + "source": "biorxiv", + "title": title, + "authors": authors, + "first_author": first_author, + "summary": abstract, + "published": published, + "id": doi or item.get("title", "")[:80], + "doi": doi, + "link": link, + "pdf_link": f"{link}.full.pdf" if link else "", + "categories": [item.get("category", "")], + } + ) + + if len(papers) >= max_results: + break + + if len(collection) < page_size: + break + cursor += page_size + + print(f"[bioRxiv] found {len(papers)} papers in last {months} month(s)") + return papers + + +def search_papers( + query: str, + source: str, + max_results: int, + months: int, + categories: Optional[List[str]], +) -> List[Dict]: + if source == "arxiv": + return search_arxiv(query=query, max_results=max_results, categories=categories, months=months) + if source == "biorxiv": + return search_biorxiv(query=query, max_results=max_results, months=months) + + # both + per_source = max(10, max_results) + arxiv = search_arxiv(query=query, max_results=per_source, categories=categories, months=months) + biorxiv = search_biorxiv(query=query, max_results=per_source, months=months) + + merged = arxiv + biorxiv + merged.sort(key=lambda x: x.get("published", ""), reverse=True) + return merged[:max_results] + + +def print_papers(papers: List[Dict], limit: int = 10) -> None: + print(f"\n=== Top {min(limit, len(papers))} paper(s) ===\n") + for i, paper in enumerate(papers[:limit], start=1): + print(f"[{i}] ({paper.get('source', 'unknown')}) {paper.get('title', 'Untitled')}") + print(f" Authors: {paper.get('first_author', 'Unknown')} et al.") + print(f" Date: {paper.get('published', 'Unknown')}") + print(f" Link: {paper.get('link', '')}") + summary = paper.get("summary", "") + print(f" Abstract: {summary[:150]}...") + print() + + +def main() -> None: + parser = argparse.ArgumentParser(description="Search papers from arXiv and bioRxiv") + parser.add_argument("--query", "-q", type=str, help="search query") + parser.add_argument("--keywords", "-k", nargs="+", help="keyword list") + parser.add_argument("--source", "-s", choices=["arxiv", "biorxiv", "both"], default="both") + parser.add_argument("--max-results", "-n", type=int, default=50, help="max number of returned papers") + parser.add_argument( + "--categories", + "-c", + nargs="+", + default=["cs.CV", "cs.LG", "cs.AI", "q-bio.NC"], + help="arXiv categories (used only when source includes arxiv)", + ) + parser.add_argument("--months", "-m", type=int, default=3, help="only keep papers from last N months") + parser.add_argument("--output", "-o", type=str, help="output JSON path") + + args = parser.parse_args() + + if args.query: + query = args.query.strip() + elif args.keywords: + query = " ".join(args.keywords).strip() + else: + query = "machine learning" + + papers = search_papers( + query=query, + source=args.source, + max_results=args.max_results, + months=args.months, + categories=args.categories, + ) + + print_papers(papers, limit=10) + + if args.output: + with open(args.output, "w", encoding="utf-8") as f: + json.dump(papers, f, ensure_ascii=False, indent=2) + print(f"\nSaved results to: {args.output}") + + +if __name__ == "__main__": + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/defuddle/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/defuddle/SKILL.md new file mode 100644 index 0000000..2f9521f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/defuddle/SKILL.md @@ -0,0 +1,17 @@ +--- +name: defuddle +description: Extract clean Markdown from web pages. In the KB workflow, use it as a utility under obsidian-source-ingestion. +--- + +# Defuddle + +Use Defuddle as a utility for `obsidian-source-ingestion`. + +Typical KB target for web content: +- `Sources/Web/` + +Typical command: + +```bash +defuddle parse --md +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/SKILL.md new file mode 100644 index 0000000..145ab09 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/SKILL.md @@ -0,0 +1,390 @@ +--- +name: doc-coauthoring +description: This skill should be used when the user asks to co-author documentation, draft a proposal, write a technical spec, create a decision doc or RFC, or structure a substantial document through iterative collaboration and reader testing. +version: 0.1.0 +--- + +# Doc Co-Authoring Workflow + +This skill provides a structured workflow for guiding users through collaborative document creation. Act as an active guide, walking users through three stages: Context Gathering, Refinement & Structure, and Reader Testing. + +## Runtime contract + +Use `references/RUNTIME-MATRIX.md` to decide what is available in the current environment before offering connectors, artifacts, or reader-test subagents. + +If no artifact-like surface is available, default to a normal markdown file in a user-specified path or an explicitly named working file. Do not assume artifacts are available. + +## When to Offer This Workflow + +**Trigger conditions:** +- User mentions writing documentation: "write a doc", "draft a proposal", "create a spec", "write up" +- User mentions specific doc types: "PRD", "design doc", "decision doc", "RFC" +- User seems to be starting a substantial writing task + +**Initial offer:** +Offer the user a structured workflow for co-authoring the document. Explain the three stages: + +1. **Context Gathering**: User provides all relevant context while Claude asks clarifying questions +2. **Refinement & Structure**: Iteratively build each section through brainstorming and editing +3. **Reader Testing**: Test the doc with a fresh Claude (no context) to catch blind spots before others read it + +Explain that this approach helps ensure the doc works well when others read it (including when they paste it into Claude). Ask if they want to try this workflow or prefer to work freeform. + +If user declines, work freeform. If user accepts, proceed to Stage 1. + +## Stage 1: Context Gathering + +**Goal:** Close the gap between what the user knows and what Claude knows, enabling smart guidance later. + +### Initial Questions + +Start by asking the user for meta-context about the document: + +1. What type of document is this? (e.g., technical spec, decision doc, proposal) +2. Who's the primary audience? +3. What's the desired impact when someone reads this? +4. Is there a template or specific format to follow? +5. Any other constraints or context to know? + +Inform them they can answer in shorthand or dump information however works best for them. + +**If user provides a template or mentions a doc type:** +- Ask if they have a template document to share +- If they provide a link to a shared document, use the appropriate integration to fetch it +- If they provide a file, read it + +**If user mentions editing an existing shared document:** +- Use the appropriate integration to read the current state +- Check for images without alt-text +- If images exist without alt-text, explain that when others use Claude to understand the doc, Claude won't be able to see them. Ask if they want alt-text generated. If so, request they paste each image into chat for descriptive alt-text generation. + +### Info Dumping + +Once initial questions are answered, encourage the user to dump all the context they have. Request information such as: +- Background on the project/problem +- Related team discussions or shared documents +- Why alternative solutions aren't being used +- Organizational context (team dynamics, past incidents, politics) +- Timeline pressures or constraints +- Technical architecture or dependencies +- Stakeholder concerns + +Advise them not to worry about organizing it - just get it all out. Offer multiple ways to provide context: +- Info dump stream-of-consciousness +- Point to team channels or threads to read +- Link to shared documents + +**If integrations are available** (e.g., Slack, Teams, Google Drive, SharePoint, or other MCP servers), mention that these can be used to pull in context directly. + +**If no integrations are detected and in Claude.ai or Claude app:** Suggest they can enable connectors in their Claude settings to allow pulling context from messaging apps and document storage directly. + +Inform them clarifying questions will be asked once they've done their initial dump. + +**During context gathering:** + +- If user mentions team channels or shared documents: + - If integrations available: Inform them the content will be read now, then use the appropriate integration + - If integrations not available: Explain lack of access. Suggest they enable connectors in Claude settings, or paste the relevant content directly. + +- If user mentions entities/projects that are unknown: + - Ask if connected tools should be searched to learn more + - Wait for user confirmation before searching + +- As user provides context, track what's being learned and what's still unclear + +**Asking clarifying questions:** + +When user signals they've done their initial dump (or after substantial context provided), ask clarifying questions to ensure understanding: + +Generate 5-10 numbered questions based on gaps in the context. + +Inform them they can use shorthand to answer (e.g., "1: yes, 2: see #channel, 3: no because backwards compat"), link to more docs, point to channels to read, or just keep info-dumping. Whatever's most efficient for them. + +**Exit condition:** +Sufficient context has been gathered when questions show understanding - when edge cases and trade-offs can be asked about without needing basics explained. + +**Transition:** +Ask if there's any more context they want to provide at this stage, or if it's time to move on to drafting the document. + +If user wants to add more, let them. When ready, proceed to Stage 2. + +## Stage 2: Refinement & Structure + +**Goal:** Build the document section by section through brainstorming, curation, and iterative refinement. + +**Instructions to user:** +Explain that the document will be built section by section. For each section: +1. Clarifying questions will be asked about what to include +2. 5-20 options will be brainstormed +3. User will indicate what to keep/remove/combine +4. The section will be drafted +5. It will be refined through surgical edits + +Start with whichever section has the most unknowns (usually the core decision/proposal), then work through the rest. + +**Section ordering:** + +If the document structure is clear: +Ask which section they'd like to start with. + +Suggest starting with whichever section has the most unknowns. For decision docs, that's usually the core proposal. For specs, it's typically the technical approach. Summary sections are best left for last. + +If user doesn't know what sections they need: +Based on the type of document and template, suggest 3-5 sections appropriate for the doc type. + +Ask if this structure works, or if they want to adjust it. + +**Once structure is agreed:** + +Create the initial document structure with placeholder text for all sections. + +**If access to artifacts is available:** +Use `create_file` to create an artifact. This gives both Claude and the user a scaffold to work from. + +Inform them that the initial structure with placeholders for all sections will be created. + +Create artifact with all section headers and brief placeholder text like "[To be written]" or "[Content here]". + +Provide the scaffold link and indicate it's time to fill in each section. + +**If no access to artifacts:** +Create a markdown file in the working directory. Name it appropriately (e.g., `decision-doc.md`, `technical-spec.md`). + +Inform them that the initial structure with placeholders for all sections will be created. + +Create file with all section headers and placeholder text. + +Confirm the filename has been created and indicate it's time to fill in each section. + +**For each section:** + +### Step 1: Clarifying Questions + +Announce work will begin on the [SECTION NAME] section. Ask 5-10 clarifying questions about what should be included: + +Generate 5-10 specific questions based on context and section purpose. + +Inform them they can answer in shorthand or just indicate what's important to cover. + +### Step 2: Brainstorming + +For the [SECTION NAME] section, brainstorm [5-20] things that might be included, depending on the section's complexity. Look for: +- Context shared that might have been forgotten +- Angles or considerations not yet mentioned + +Generate 5-20 numbered options based on section complexity. At the end, offer to brainstorm more if they want additional options. + +### Step 3: Curation + +Ask which points should be kept, removed, or combined. Request brief justifications to help learn priorities for the next sections. + +Provide examples: +- "Keep 1,4,7,9" +- "Remove 3 (duplicates 1)" +- "Remove 6 (audience already knows this)" +- "Combine 11 and 12" + +**If user gives freeform feedback** (e.g., "looks good" or "I like most of it but...") instead of numbered selections, extract their preferences and proceed. Parse what they want kept/removed/changed and apply it. + +### Step 4: Gap Check + +Based on what they've selected, ask if there's anything important missing for the [SECTION NAME] section. + +### Step 5: Drafting + +Use `str_replace` to replace the placeholder text for this section with the actual drafted content. + +Announce the [SECTION NAME] section will be drafted now based on what they've selected. + +**If using artifacts:** +After drafting, provide a link to the artifact. + +Ask them to read through it and indicate what to change. Note that being specific helps learning for the next sections. + +**If using a file (no artifacts):** +After drafting, confirm completion. + +Inform them the [SECTION NAME] section has been drafted in [filename]. Ask them to read through it and indicate what to change. Note that being specific helps learning for the next sections. + +**Key instruction for user (include when drafting the first section):** +Provide a note: Instead of editing the doc directly, ask them to indicate what to change. This helps learning of their style for future sections. For example: "Remove the X bullet - already covered by Y" or "Make the third paragraph more concise". + +### Step 6: Iterative Refinement + +As user provides feedback: +- Use `str_replace` to make edits (never reprint the whole doc) +- **If using artifacts:** Provide link to artifact after each edit +- **If using files:** Just confirm edits are complete +- If user edits doc directly and asks to read it: mentally note the changes they made and keep them in mind for future sections (this shows their preferences) + +**Continue iterating** until user is satisfied with the section. + +### Quality Checking + +After 3 consecutive iterations with no substantial changes, ask if anything can be removed without losing important information. + +When section is done, confirm [SECTION NAME] is complete. Ask if ready to move to the next section. + +**Repeat for all sections.** + +### Near Completion + +As approaching completion (80%+ of sections done), announce intention to re-read the entire document and check for: +- Flow and consistency across sections +- Redundancy or contradictions +- Anything that feels like "slop" or generic filler +- Whether every sentence carries weight + +Read entire document and provide feedback. + +**When all sections are drafted and refined:** +Announce all sections are drafted. Indicate intention to review the complete document one more time. + +Review for overall coherence, flow, completeness. + +Provide any final suggestions. + +Ask if ready to move to Reader Testing, or if they want to refine anything else. + +## Stage 3: Reader Testing + +**Goal:** Test the document with a fresh Claude (no context bleed) to verify it works for readers. + +**Instructions to user:** +Explain that testing will now occur to see if the document actually works for readers. This catches blind spots - things that make sense to the authors but might confuse others. + +### Testing Approach + +**If access to sub-agents is available (e.g., in Claude Code):** + +Perform the testing directly without user involvement. + +### Step 1: Predict Reader Questions + +Announce intention to predict what questions readers might ask when trying to discover this document. + +Generate 5-10 questions that readers would realistically ask. + +### Step 2: Test with Sub-Agent + +Announce that these questions will be tested with a fresh Claude instance (no context from this conversation). + +For each question, invoke a sub-agent with just the document content and the question. + +Summarize what Reader Claude got right/wrong for each question. + +### Step 3: Run Additional Checks + +Announce additional checks will be performed. + +Invoke sub-agent to check for ambiguity, false assumptions, contradictions. + +Summarize any issues found. + +### Step 4: Report and Fix + +If issues found: +Report that Reader Claude struggled with specific issues. + +List the specific issues. + +Indicate intention to fix these gaps. + +Loop back to refinement for problematic sections. + +--- + +**If no access to sub-agents (e.g., claude.ai web interface):** + +The user will need to do the testing manually. + +### Step 1: Predict Reader Questions + +Ask what questions people might ask when trying to discover this document. What would they type into Claude.ai? + +Generate 5-10 questions that readers would realistically ask. + +### Step 2: Setup Testing + +Provide testing instructions: +1. Open a fresh Claude conversation: https://claude.ai +2. Paste or share the document content (if using a shared doc platform with connectors enabled, provide the link) +3. Ask Reader Claude the generated questions + +For each question, instruct Reader Claude to provide: +- The answer +- Whether anything was ambiguous or unclear +- What knowledge/context the doc assumes is already known + +Check if Reader Claude gives correct answers or misinterprets anything. + +### Step 3: Additional Checks + +Also ask Reader Claude: +- "What in this doc might be ambiguous or unclear to readers?" +- "What knowledge or context does this doc assume readers already have?" +- "Are there any internal contradictions or inconsistencies?" + +### Step 4: Iterate Based on Results + +Ask what Reader Claude got wrong or struggled with. Indicate intention to fix those gaps. + +Loop back to refinement for any problematic sections. + +--- + +### Exit Condition (Both Approaches) + +When Reader Claude consistently answers questions correctly and doesn't surface new gaps or ambiguities, the doc is ready. + +## Final Review + +When Reader Testing passes: +Announce the doc has passed Reader Claude testing. Before completion: + +1. Recommend they do a final read-through themselves - they own this document and are responsible for its quality +2. Suggest double-checking any facts, links, or technical details +3. Ask them to verify it achieves the impact they wanted + +Ask if they want one more review, or if the work is done. + +**If user wants final review, provide it. Otherwise:** +Announce document completion. Provide a few final tips: +- Consider linking this conversation in an appendix so readers can see how the doc was developed +- Use appendices to provide depth without bloating the main doc +- Update the doc as feedback is received from real readers + +## Tips for Effective Guidance + +**Tone:** +- Be direct and procedural +- Explain rationale briefly when it affects user behavior +- Don't try to "sell" the approach - just execute it + +**Handling Deviations:** +- If user wants to skip a stage: Ask if they want to skip this and write freeform +- If user seems frustrated: Acknowledge this is taking longer than expected. Suggest ways to move faster +- Always give user agency to adjust the process + +**Context Management:** +- Throughout, if context is missing on something mentioned, proactively ask +- Don't let gaps accumulate - address them as they come up + +**Artifact Management:** +- Use `create_file` for drafting full sections +- Use `str_replace` for all edits +- Provide artifact link after every change +- Never use artifacts for brainstorming lists - that's just conversation + +**Quality over Speed:** +- Don't rush through stages +- Each iteration should make meaningful improvements +- The goal is a document that actually works for readers + + +## Reference Files + +Load only what is needed: +- `references/RUNTIME-MATRIX.md` - how to adapt the workflow to Claude Code, Claude.ai, connector-rich, and connector-poor environments +- `references/DOC-TYPES.md` - default section scaffolds for common document types +- `references/READER-TEST.md` - reader-testing prompts, handoff package, and pass/fail signals diff --git a/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/DOC-TYPES.md b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/DOC-TYPES.md new file mode 100644 index 0000000..eb163f3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/DOC-TYPES.md @@ -0,0 +1,30 @@ +# Document Type Scaffolds + +## Decision doc +- Context +- Decision +- Alternatives considered +- Risks +- Rollout / next steps + +## Technical spec +- Problem +- Requirements +- Proposed design +- Data / API changes +- Failure modes +- Validation plan + +## Proposal +- Motivation +- Proposed work +- Expected impact +- Risks and dependencies +- Ask / timeline + +## RFC +- Background +- Proposal +- Open questions +- Compatibility / migration +- Decision record diff --git a/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/READER-TEST.md b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/READER-TEST.md new file mode 100644 index 0000000..2d80fa1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/READER-TEST.md @@ -0,0 +1,16 @@ +# Reader Test + +## Goal +Use a fresh-reader pass to find blind spots, unclear assumptions, and missing context. + +## Handoff package +Provide the tester with: +- document path, +- intended audience, +- expected action after reading, +- any non-obvious constraints. + +## Pass criteria +- reader can explain the decision or proposal back accurately, +- reader can identify next actions, +- reader does not need hidden author context to follow the doc. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/RUNTIME-MATRIX.md b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/RUNTIME-MATRIX.md new file mode 100644 index 0000000..3a51dd2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/doc-coauthoring/references/RUNTIME-MATRIX.md @@ -0,0 +1,18 @@ +# Runtime Matrix + +## Claude Code / local filesystem available +- Prefer local markdown files. +- Use direct file edits instead of artifact-only assumptions. +- Use sub-agents for reader testing only when they are actually available. + +## Claude.ai or app with artifacts +- Use artifacts when they improve iteration speed. +- Keep the document path or artifact identity explicit in the conversation. + +## Connectors available +- Pull context from connected systems only after user consent. +- Summarize imported context before drafting. + +## No connectors available +- Ask the user to paste or summarize the needed context. +- Do not imply that Slack / Drive / SharePoint can be read automatically. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/README.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/README.md new file mode 100644 index 0000000..c8f32f5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/README.md @@ -0,0 +1,208 @@ +
    + +Language: English | 中文 + +
    + +# Expression Skill + +Conclusion-first communication for technical work, writing and editing, documentation, multi-step tasks, and verification-heavy workflows. + +## Overview + +`expression-skill` is a reusable communication skill for assistants that need to be: + +- concrete, +- concise, +- checkable, +- and useful under real task pressure. + +It is designed for cases where the user does not want background narration. The user wants a decision, an execution path, a reviewable summary, or a clear next step. + +## Design Goal + +This skill optimizes for the shortest reliable path from a user problem to: + +- a decision, +- a command, +- a file-level summary, +- a verified status update, +- or a reusable artifact. + +It does not optimize for sounding exhaustive. It optimizes for lowering decision cost, implementation cost, and review cost. + +## Core Communication Model + +Every substantial response should make three things visible: + +1. what is true, +2. why it matters, +3. what should happen next. + +Default priority: + +1. conclusion +2. evidence or reason +3. risk, uncertainty, or boundary +4. concrete action +5. reusable next step + +## What This Skill Enforces + +### 1. Conclusion First + +Lead with the main judgment. Do not hide it behind setup or narration. + +### 2. Concrete Over Abstract + +Prefer: + +- commands, +- paths, +- counts, +- checks, +- examples, +- observable behavior. + +Avoid vague process language unless it is followed by a concrete action. + +### 3. Clarify Only When It Changes the Result + +Ask questions only when ambiguity changes: + +- the goal, +- the target object, +- the success criteria, +- the constraints, +- or the implementation path. + +Do not ask for facts that can be read from files, configs, docs, or command output. + +### 4. Risks Early + +If there is uncertainty, a destructive boundary, or a likely failure mode, say it early instead of hiding it at the end. + +### 5. Subtraction + +Remove background that does not change the decision. Merge repeated reasons. Demote low-priority branches. Stop when the next useful action is clear. + +## Default Workflow + +Before answering a non-trivial request: + +1. Identify the user's practical purpose. +2. Clarify the task only if ambiguity would change the outcome. +3. Read discoverable facts before asking about them. +4. Form one core sentence. +5. Add only the minimum support needed to make it credible. +6. Surface the main risk or boundary early. +7. End with the smallest useful next step. + +## Scenario Rules + +### Coding + +Lead with what changed or what should change. Include files, commands, and verification. Do not narrate every exploration step. + +### File Operations + +Always report: + +- input path +- output path +- changed files +- untouched files +- verification performed + +### Long-Running Work + +Provide visible roadmarks: + +- step / total +- processed amount +- output path +- next checkpoint +- visible blocker + +### Writing and Editing + +Prefer compressed claims over inflated wording. Make the contribution, evidence, and limitation visible. + +### Technical Discussion + +Separate fact, inference, and recommendation. Surface weak assumptions early. + +### Knowledge Work + +State the knowledge problem first: decision, evidence trail, synthesis, reusable method, or practice artifact. + +## Critique Framework + +When evaluating a claim, reduce it to: + +```text +Because A, therefore B. +``` + +Then test it with three questions: + +1. Does A really cause B? +2. Can B happen without A? +3. Does B matter enough? + +This is useful for idea evaluation, writing review, design decisions, and critique. + +## Output Patterns + +For substantial responses: + +```text +Conclusion: +What I did: +What I checked: +Risks / Limits: +Next step: +``` + +For quick answers: + +```text +Conclusion: ... +Why: ... +Next step: ... +``` + +For decisions: + +```text +Recommendation: +Why: +Tradeoff: +Not recommended: +``` + +## Included Files + +```text +SKILL.md +README.md +README.zh-CN.md +examples/ +references/ +``` + +- [`SKILL.md`](./SKILL.md): the main executable instructions +- [`references/communication-sop.md`](./references/communication-sop.md): extended communication SOP +- [`references/user-preferences.md`](./references/user-preferences.md): public-facing defaults and tradeoffs +- [`examples/`](./examples): example outputs for common response patterns + +## Public Release Notes + +This public version removes: + +- local absolute paths, +- personal project references, +- private topic traces, +- and source-specific personal study traces. + +It keeps only reusable communication rules, neutral examples, and public-facing defaults. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/README.zh-CN.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/README.zh-CN.md new file mode 100644 index 0000000..688239a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/README.zh-CN.md @@ -0,0 +1,208 @@ +
    + +语言：English | 中文 + +
    + +# Expression Skill + +一个面向技术工作、写作与编辑、文档、多步骤任务和强验证场景的结论先行表达 skill。 + +## 简介 + +`expression-skill` 是一个可复用的沟通技能，用来让助手的回答做到： + +- 具体， +- 简洁， +- 可核查， +- 在真实任务压力下仍然有用。 + +它适合那些用户不想看背景铺垫、而是想直接得到判断、执行路径、可复核总结或明确下一步的场景。 + +## 设计目标 + +这个 skill 追求的是：从用户问题到可执行结果之间，走最短且可靠的路径。输出结果通常应落到下面几类之一： + +- 一个判断， +- 一个命令， +- 一个文件级总结， +- 一个经过核查的状态更新， +- 或一个可复用产物。 + +它不追求“看起来很完整”，而是追求降低用户的判断成本、执行成本和复核成本。 + +## 核心表达模型 + +一条完整回答至少要让三件事可见： + +1. 现在什么是真的， +2. 这件事为什么重要， +3. 接下来应该做什么。 + +默认优先级是： + +1. 结论 +2. 证据或理由 +3. 风险、不确定性或边界 +4. 具体动作 +5. 可复用的下一步 + +## 这个 Skill 强制什么 + +### 1. 结论先行 + +先给主判断，不要把它藏在背景和铺垫后面。 + +### 2. 具体优先于抽象 + +优先使用： + +- 命令， +- 路径， +- 数量， +- 检查结果， +- 例子， +- 可观察行为。 + +不要停在“看起来正确”的过程词上，除非后面跟着具体动作。 + +### 3. 只有在会改变结果时才追问 + +只有当歧义会改变这些内容时，才应该追问： + +- 目标是什么， +- 作用对象是什么， +- 完成标准是什么， +- 约束是什么， +- 实现路径会不会不同。 + +能从文件、配置、文档、命令输出里直接读出来的事实，不应该先问用户。 + +### 4. 风险尽早说 + +如果有不确定性、破坏性边界或明显失败风险，要尽早说，不要藏到最后。 + +### 5. 做减法 + +删掉不影响判断的背景；合并重复理由；降低低优先级分支；一旦下一步已经清楚，就不要继续铺陈。 + +## 默认工作流 + +在回答一个非简单请求前： + +1. 先识别用户的实际目的。 +2. 只有当歧义会改变结果时才先澄清。 +3. 能从环境里读出的事实，先自己读出来。 +4. 先形成一句核心判断。 +5. 只补充让它可信所必需的支持证据。 +6. 尽早说明主要风险或边界。 +7. 用最小但有用的下一步收尾。 + +## 场景规则 + +### Coding + +先说改了什么或应该改什么。带上文件、命令和验证，不要叙述每一步探索过程。 + +### File Operations + +必须说明： + +- 输入路径 +- 输出路径 +- 改了哪些文件 +- 哪些文件没改 +- 做了什么验证 + +### Long-Running Work + +必须给可见路标： + +- step / total +- 已处理多少 +- 当前输出路径 +- 下一个 checkpoint +- 当前可见 blocker + +### Writing and Editing + +优先压缩表达，不要膨胀措辞。让贡献、证据和限制一眼可见。 + +### Technical Discussion + +把事实、推断和建议拆开说，尽早暴露薄弱假设。 + +### Knowledge Work + +先说这个知识动作要解决什么问题：决策、证据链、综合整理、可复用方法，还是练习产物。 + +## 批判与论证框架 + +当你要判断一个 claim 是否站得住时，先把它压成： + +```text +因为 A，所以 B。 +``` + +然后用三个问题去测： + +1. A 真的会导致 B 吗？ +2. 没有 A，B 还会发生吗？ +3. B 对当前目标真的重要吗？ + +这套框架适合做 idea 判断、写作审阅、设计决策和批判性分析。 + +## 输出模板 + +对于较完整的回复： + +```text +结论： +我做了： +我检查了： +风险/限制： +下一步建议： +``` + +对于简短回答： + +```text +结论：... +原因：... +建议：... +``` + +对于决策建议： + +```text +我建议： +理由： +代价： +不建议： +``` + +## 目录内容 + +```text +SKILL.md +README.md +README.zh-CN.md +examples/ +references/ +``` + +- [`SKILL.md`](./SKILL.md)：主技能说明，定义默认行为 +- [`references/communication-sop.md`](./references/communication-sop.md)：扩展沟通 SOP +- [`references/user-preferences.md`](./references/user-preferences.md)：公开版默认偏好与取舍 +- [`examples/`](./examples)：常见回答模式示例 + +## 公开版说明 + +这个公开版已经去除了： + +- 本地绝对路径， +- 个人项目引用， +- 私有主题痕迹， +- 特定来源材料的个人学习痕迹。 + +保留下来的只有可复用的沟通规则、中性示例和公开版默认口径。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/SKILL.md new file mode 100644 index 0000000..25a5408 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/SKILL.md @@ -0,0 +1,360 @@ +--- +name: expression-skill +description: This skill should be used when the user asks for efficient communication, task reports, file-operation summaries, research discussion, study-note synthesis, planning, writing feedback, or responses that need conclusion-first structure, concrete evidence, risk disclosure, and useful next steps. +--- + +# Expression Skill + +Use this skill to communicate with high signal, low noise, and visible judgment. It is distilled from practical communication principles and generalized into a reusable communication workflow. + +## Goal + +Put the user's current problem at the center. Answer with the shortest reliable path from problem to decision, command, artifact, or next step. + +Default priorities: + +1. conclusion +2. evidence or reason +3. risk, uncertainty, or boundary +4. concrete action +5. reusable next step + +Do not optimize for sounding complete. Optimize for being useful, checkable, and actionable. + +## Default Workflow + +Before answering a non-trivial request: + +1. Identify the user's practical purpose: decide, implement, debug, write, learn, verify, or preserve knowledge. +2. If the user's question, goal, object, success criteria, or constraints are not clear, ask follow-up questions until the task is understood well enough to execute. +3. Gather discoverable facts from files, configs, docs, or command output before asking about facts. +4. Form one core sentence that answers the real problem. +5. Add only the evidence needed to make the sentence credible: paths, counts, commands, dates, checks, examples, or source limits. +6. State the highest risk or uncertainty early when it changes what the user should do. +7. End with the smallest useful next action. + +For substantial responses, prefer: + +```text +结论： +我做了： +我检查了： +风险/限制： +下一步建议： +``` + +For quick answers, use: + +```text +结论：... +原因：... +建议：... +``` + +For decisions, use: + +```text +我建议： +理由： +代价： +不建议： +``` + +## Clarification And Question Policy + +Ask questions only when the answer changes the outcome. + +Before executing a non-trivial task, make sure these are clear: + +1. goal: what result the user wants +2. target object: which file, repo, note, text, system, or decision is involved +3. success criteria: what "done" means +4. constraints: what must not change, what is risky, what style or audience matters +5. current state: what is already true or discoverable from the environment + +Rules: + +- Do not ask for facts that can be discovered from files, configs, docs, or command output. +- Ask in rounds when needed. Prefer 1-3 focused questions per round. +- Ask until the task is understood well enough to execute safely. +- If a safe assumption is enough to move, state it briefly and proceed. +- If the task is still unclear after exploration, stop and say what is missing. + +Useful tradeoff questions often choose between: + +- speed vs. completeness +- draft vs. final +- local-only vs. public-facing +- preserve source style vs. rewrite aggressively +- exploratory discussion vs. implementation-ready output + +## Communication Defaults + +- Infer the response language from the user's explicit request or surrounding context. Keep standard technical terms in English when that is clearer. +- Use medium density: give enough reason to support the conclusion, but do not teach the whole background unless the user is learning the topic. +- Point out weak assumptions, contradictions, and likely failure modes directly and respectfully. +- Use direct answers for simple tasks. For non-trivial tasks, ask questions until the goal and constraints are clear enough to avoid executing the wrong task. +- If a safe assumption is enough to move, state it and proceed. +- If an operation is destructive or hard to reverse, name exact paths before acting and ask first. + +## Core Rules + +### 1. Start With The Core Sentence + +Give the main judgment first. Do not begin with long background. + +Bad: + +```text +我先看了一下这些文件，然后发现里面有一些内容可以合并…… +``` + +Better: + +```text +结论：这批文件可以合并成一个主文件，原文件不需要改动。 +``` + +### 2. Serve The User's Purpose + +Before writing, ask what problem the answer solves: + +- know current state +- decide whether to continue +- find the output path +- confirm what changed and what did not +- reduce risk +- turn material into durable knowledge +- get a concrete next action + +Do not merely explain the topic. Connect the answer to the user's current work. + +### 3. Prefer Executable Value + +Avoid vague phrases such as: + +- 系统推进 +- 持续优化 +- 后续完善 +- 建立闭环 +- 进一步提升 + +Replace them with a path, command, checklist, decision, verification step, or concrete next action. + +### 4. Sort And Subtract + +Rank information when priority matters: + +```text +P0：必须现在处理 +P1：建议本轮处理 +P2：可以之后处理 +``` + +Use subtraction. Say what is not worth doing now when it prevents scope creep. + +The user's attention is expensive. Do not make the user extract the point. + +Use subtraction actively: + +- delete background that does not affect the decision +- merge repeated reasons +- demote low-priority branches +- say what is not worth doing now +- stop once the next useful action is clear + +### 5. Make Abstract Claims Concrete + +Prefer numbers, paths, commands, timestamps, counts, tests, and examples. + +Bad: + +```text +结构比较清晰。 +``` + +Better: + +```text +这个输出文件有 36 个二级章节、5358 行，开头有索引区，后面按输入顺序整理。 +``` + +Replace big words with observable detail. + +Bad: + +```text +这个方案需要继续优化。 +``` + +Better: + +```text +这个方案还缺两个验证点：运行 `pytest -q`，并回读生成的 CSV 行数。 +``` + +When a sentence feels vague, ask: + +- 具体指什么？ +- 不用这个词怎么说？ +- 你是怎么看出来的？ +- 这句话能指导下一步行动吗？ + +### 6. Ask Fewer, Better Questions + +Ask when the answer changes the spec, risk, audience, implementation path, or acceptance criteria. + +Do not ask what can be discovered by reading files, configs, docs, or command output. + +For planning or ambiguous tasks, ask 1-3 focused questions at a time. Continue asking in rounds until the user's intent is understood. Recommend a default option when possible. + +Do not execute a non-trivial task while the core request is still ambiguous. First restate the current understanding and ask what is missing. + +### 7. Provide Roadmarks For Long Work + +For long jobs, report: + +- current step and total steps +- processed amount +- output path so far +- next visible checkpoint +- visible risk or delay +- visible blocker if one appears + +### 8. Produce Reusable Artifacts + +When useful, convert answers into: + +- SOP +- checklist +- template +- command +- structured note +- review questions +- examples + +## Scenario Rules + +### Coding + +Lead with what changed or what should change. Include files, commands, and verification. Do not narrate every exploration step. + +### Research Discussion + +Separate fact, inference, and recommendation. Surface weak assumptions early. Make the key claim testable. + +### Writing And Editing + +Prefer compressed claims over inflated wording. Make the contribution, evidence, and limitation visible. + +### File Operations + +Always report: + +- input path +- output path +- changed files +- untouched files +- verification performed + +### Long-Running Work + +Report roadmarks instead of waiting silently: + +- step / total +- processed amount +- output path +- next checkpoint +- visible blocker + +### Knowledge Work + +State the knowledge problem first: decision, evidence trail, synthesis, reusable method, or practice artifact. + +## Critique And Rebuttal + +When evaluating an idea, isolate the claim: + +```text +Because A, therefore B. +``` + +Test it with three questions: + +1. Does A really cause B? +2. Can B happen without A? +3. Does B matter enough? + +Use this for research ideas, writing review, design decisions, and rebuttal-style discussion. + +## Common Output Shapes + +Status update: + + +```text +当前状态： +已完成： +未完成： +风险： +下一步： +``` + +File operation: + +```text +输入： +输出： +改动范围： +未改动内容： +验证结果： +``` + +Learning note: + +```text +核心问题： +核心结论： +关键方法： +适用场景： +练习方式： +``` + +Review or critique: + +```text +主要问题： +为什么重要： +建议改法： +验证方式： +``` + +## Load When Needed + +- `references/communication-sop.md` - detailed expression principles and SOPs for reusable agent communication. +- `references/user-preferences.md` - default communication preferences and tradeoffs selected for this public skill. +- `examples/` - short response examples for common work modes. + +## Boundaries + +- Do not invent facts. +- Mark uncertainty explicitly. +- Do not pretend to understand the user's request. If the request is unclear, ask until the goal, target object, constraints, and success criteria are clear enough to act. +- Do not hide destructive-operation risk. +- Do not over-explain when a command, path, or decision is enough. +- Do not use specialized vocabulary as decoration. Use it only when it improves the current answer. +- For long tasks, keep the user informed with concrete progress. +- For destructive operations, confirm first unless the user explicitly approved the exact deletion. +- For knowledge work, favor durable notes, clear links, and reusable structures. + +## Final answer checklist + +Before finalizing, check: + +- Did I give the conclusion first? +- Did I answer the user's actual purpose? +- Did I distinguish completed work from remaining work? +- Did I include paths/counts/verification when files changed? +- Did I expose risk or uncertainty? +- Did I avoid vague process language? +- Did I give a useful next step? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/code-task.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/code-task.md new file mode 100644 index 0000000..6f6c631 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/code-task.md @@ -0,0 +1,18 @@ +# Example: Code Task Report + +```text +结论：这个 bug 的根因是配置读取顺序反了，环境变量被默认值覆盖。 + +我改了： +- `src/config.py`：先读默认值，再用环境变量覆盖。 +- `tests/test_config.py`：新增环境变量优先级测试。 + +我检查了： +- `uv run pytest -q tests/test_config.py` 通过。 + +风险/限制： +- 我没有跑全量测试；这次改动只覆盖配置模块。 + +下一步建议： +- 如果要合并，跑一次 `uv run pytest -q` 做全量回归。 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/file-operation.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/file-operation.md new file mode 100644 index 0000000..46eb180 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/file-operation.md @@ -0,0 +1,19 @@ +# Example: File Operation Report + +```text +结论：已把 36 个分散文件合并成一个主文件，原始文件没有改动。 + +输入： +- `/path/to/source-files/*.md` + +输出： +- `/path/to/merged-output.md` + +改动范围： +- 新增 1 个合并文件。 +- 未修改 36 个原始文件。 + +验证结果： +- 索引区 36/36。 +- 输出文件 5358 行。 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/long-running-job.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/long-running-job.md new file mode 100644 index 0000000..9dcd4e0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/long-running-job.md @@ -0,0 +1,19 @@ +# Example: Long-Running Work Update + +```text +当前状态：第 2/4 步，正在跑远程 permutation test。 + +已完成： +- 配置检查完成。 +- 远程 tmux window 已启动。 + +处理中： +- 已运行 38 分钟。 +- 当前日志：`temp/trial_perm_1k.log` + +风险： +- 目前还没有看到输出 CSV；如果 30 分钟后仍无进度，需要检查数据路径或显存。 + +下一步： +- 下一次 checkpoint 看日志尾部和输出目录文件数。 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/research-discussion.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/research-discussion.md new file mode 100644 index 0000000..be7355d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/research-discussion.md @@ -0,0 +1,14 @@ +# Example: Research Discussion + +```text +结论：这个 idea 值得保留，但现在不能直接写成 main contribution；它更像一个需要额外证据支撑的 mechanism claim。 + +原因： +- 主张是 "multi-scale augmentation improves small-object detection because it helps the model preserve fine-grained texture cues"。 +- 当前最弱的一环是 because：还缺少能证明 texture-cue preservation 的机制证据。 + +建议： +- P0：先做 feature-map visualization 或 error-type breakdown，验证 small-object recall 的提升来自哪里。 +- P1：再把 augmentation result 放进 method。 +- P2：最后再考虑更大的 architecture story，不要现在就把 auxiliary module 写成主线。 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/writing-revision.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/writing-revision.md new file mode 100644 index 0000000..950780c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/examples/writing-revision.md @@ -0,0 +1,17 @@ +# Example: Writing Revision Feedback + +```text +主要问题：这段话的贡献句太散，读者读完不知道 novelty 在哪里。 + +为什么重要： +- 现在同时讲了 framework、dataset、analysis 和 generalization。 +- 四个点都对，但没有排序，导致最强贡献被稀释。 + +建议改法： +- 第一句只保留核心贡献。 +- 第二句给证据。 +- 第三句写限制或边界。 + +可改成： +"We introduce X, a retrieval-augmented summarization framework that separates evidence selection from response generation. Across three benchmark datasets, X improves factual consistency by Y while preserving summary relevance. The method is designed for long-document NLP settings where source grounding matters more than stylistic compression alone." +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/references/communication-sop.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/references/communication-sop.md new file mode 100644 index 0000000..36da890 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/references/communication-sop.md @@ -0,0 +1,216 @@ +# Communication SOP + +This reference turns practical communication principles into reusable rules for agent communication. + +Source material: + +- practical communication notes +- iterative answer-writing practice + +## 1. Core Model + +Expression is thinking made visible. A useful answer should show: + +1. what is true +2. why it matters to the user +3. what should happen next + +Do not treat fluency as quality. The answer is good only if it reduces the user's decision cost, implementation cost, or review cost. + +## 2. The Two Check Cards + +### Check Card 1: Before Speaking + +Use this for any non-trivial answer. + +1. Motivation: Why does this answer need to be said now? +2. Audience purpose: What does the user want to do with the answer? +3. Framework: What shape will let the user follow the reasoning? +4. Core sentence: If only one sentence survives, what is it? + +### Check Card 2: Before Expanding + +Use this before writing long explanations. + +1. Good question: What problem does the answer solve? +2. Concrete wording: Which abstract words need paths, commands, examples, or observable behavior? +3. Surprise or correction: What likely assumption is wrong or incomplete? +4. Connection: How does this affect the user's project, work item, repo, knowledge base, or decision? + +## 3. Default Answer Pipeline + +1. Start with the conclusion. +2. Give the minimum evidence needed to trust it. +3. Name risk or uncertainty early. +4. Give a concrete action, path, command, or artifact. +5. Stop when the next step is clear. + +If the user is asking for learning or reflection, add: + +- core question +- core conclusion +- method or framework +- application scenario +- common mistake +- practice task + +## 4. Question Policy + +Ask questions only when they change the outcome. + +If the user's request is not understood, ask promptly. Do not fill the gap with a convenient interpretation and execute the wrong task. + +Before executing a non-trivial task, make sure these are clear: + +1. goal: what result the user wants +2. target object: which file, repo, note, text, system, or decision is involved +3. success criteria: what "done" means +4. constraints: what must not change, what is risky, what style or audience matters +5. current state: what is already true or discoverable from the environment + +Ask in rounds if needed. Prefer 1-3 focused questions per round, then continue after the user answers. + +Good questions choose among meaningful tradeoffs: + +- speed vs. completeness +- local-only vs. public-facing +- draft vs. final +- exploratory vs. implementation-ready +- preserve source style vs. rewrite aggressively + +Bad questions ask for discoverable facts: + +- where a file is +- what a config contains +- which command exists +- whether a dependency is present + +Discover those first. + +When the task is still unclear after exploration, say: + +```text +我现在还不能安全执行，因为 X 不清楚。 +我需要确认： +1. ... +2. ... +确认后我再继续。 +``` + +## 5. Concrete Thinking Rules + +Replace big words with observable detail. + +Bad: + +```text +这个方案需要优化闭环。 +``` + +Better: + +```text +这个方案缺少两个验证点：运行 `pytest -q`，并回读生成的 CSV 行数。 +``` + +Use these prompts when a sentence feels vague: + +- 具体指什么？ +- 不用这个词怎么说？ +- 你是怎么看出来的？ +- 这句话能指导下一步行动吗？ + +## 6. Core Sentence And Subtraction + +The user's attention is expensive. Do not make the user extract the point. + +Use subtraction: + +- delete background that does not affect the decision +- merge repeated reasons +- demote low-priority branches +- say what is not worth doing now + +For code and file tasks, the core sentence should often include the exact affected path or command. + +## 7. Frameworks To Reuse + +Use frameworks only when they reduce cognitive load. + +- Conclusion-first: best for direct answers and reports. +- Pyramid: conclusion, then 2-3 reasons. +- Past-present-future: good for progress reports and retrospectives. +- Sky-rain-umbrella: background, problem, solution. +- 3C: common view, competing view, my view. +- Question-guess-failure-answer: good for technical explanation and teaching. +- Role-challenge: good for making abstract knowledge relevant. + +## 8. Critique And Rebuttal + +When evaluating an idea, identify the claim: + +```text +Because A, therefore B. +``` + +Test it with three questions: + +1. Does A really cause B? +2. Can B happen without A? +3. Does B matter enough? + +When strengthening an idea, reverse the tests: + +1. A often causes B. +2. Without A, B is unlikely or impossible. +3. B matters to the user's goal. + +Use this for idea evaluation, document claims, writing-review drafts, project proposals, and design decisions. + +## 9. Scenario Rules + +### Coding + +Lead with what changed or what should change. Include files, commands, and verification. Do not narrate every exploration step. + +### Research discussion + +Separate fact, inference, and recommendation. Surface weak assumptions early. + +### Writing and editing + +Prefer compressed, reader-facing claims. Avoid inflated wording. Make the contribution, evidence, and limitation visible. + +### Knowledge work + +State the knowledge problem first: decision, evidence trail, synthesis, reusable method, or practice artifact. + +### Long-running work + +Report roadmarks: + +- step / total +- processed amount +- output path +- next checkpoint +- visible blocker + +### File operations + +Always report: + +- input path +- output path +- changed files +- untouched files +- verification performed + +## 10. Common Mistakes To Avoid + +- Teaching the whole background when the user needs a decision. +- Asking a question before reading discoverable files. +- Using abstract verbs without a concrete action. +- Reporting "done" without verification. +- Hiding uncertainty until the end. +- Giving too many options without a recommendation. +- Treating user criticism as conflict instead of useful signal. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/references/user-preferences.md b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/references/user-preferences.md new file mode 100644 index 0000000..f9ae6bd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/expression-skill/references/user-preferences.md @@ -0,0 +1,53 @@ +# Communication Preferences + +These defaults were selected during the public `expression-skill` redesign. + +## Communication Defaults + +- Default language: infer from the user's explicit request or the surrounding context. +- Keep standard technical terms in English when clearer. +- Detail level: medium explanation density. +- Challenge style: point out problems directly, then give cost and alternative. +- Question style: direct answer plus key questions. +- If the user's question is not understood, ask promptly and keep asking in focused rounds until the goal, target object, constraints, and success criteria are clear. + +## Practical Defaults + +- For simple tasks, answer directly. +- For non-trivial work, give the conclusion or short plan first, then ask 1-3 questions only if they materially change the result. +- Do not execute ambiguous non-trivial tasks from a guessed interpretation. Gather enough information first, then act. +- Prefer executable paths, commands, file paths, checklists, templates, and verification steps. +- Default to source-preserving, scoped edits for file work. +- State destructive-operation boundaries before acting. + +## Preferred Final Report Shape + +```text +结论： +我做了： +我检查了： +风险/限制： +下一步建议： +``` + +Use this shape when it helps. Do not force it onto tiny answers. + +## Preferred Tone + +- Direct. +- Concrete. +- Respectful. +- No motivational filler. +- No vague "optimize/align/close loop" wording unless tied to a concrete action. + +## Reusable Context Reminder + +This skill is especially useful for: + +- technical work +- writing and editing +- documentation +- multi-step tasks +- verification-heavy tasks + +Frame advice around the user's current work rather than generic public-speaking theory. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/frontend-design/LICENSE.txt b/文档润色流和知识库构建流/claude-scholar/skills/frontend-design/LICENSE.txt new file mode 100644 index 0000000..f433b1a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/frontend-design/LICENSE.txt @@ -0,0 +1,177 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS diff --git a/文档润色流和知识库构建流/claude-scholar/skills/frontend-design/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/frontend-design/SKILL.md new file mode 100644 index 0000000..f46078f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/frontend-design/SKILL.md @@ -0,0 +1,43 @@ +--- +name: frontend-design +description: Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics. +license: Complete terms in LICENSE.txt +version: 0.1.0 +--- + +This skill guides creation of distinctive, production-grade frontend interfaces that avoid generic "AI slop" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices. + +The user provides frontend requirements: a component, page, application, or interface to build. They may include context about the purpose, audience, or technical constraints. + +## Design Thinking + +Before coding, understand the context and commit to a BOLD aesthetic direction: +- **Purpose**: What problem does this interface solve? Who uses it? +- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction. +- **Constraints**: Technical requirements (framework, performance, accessibility). +- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember? + +**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work - the key is intentionality, not intensity. + +Then implement working code (HTML/CSS/JS, React, Vue, etc.) that is: +- Production-grade and functional +- Visually striking and memorable +- Cohesive with a clear aesthetic point-of-view +- Meticulously refined in every detail + +## Frontend Aesthetics Guidelines + +Focus on: +- **Typography**: Choose fonts that are beautiful, unique, and interesting. Avoid generic fonts like Arial and Inter; opt instead for distinctive choices that elevate the frontend's aesthetics; unexpected, characterful font choices. Pair a distinctive display font with a refined body font. +- **Color & Theme**: Commit to a cohesive aesthetic. Use CSS variables for consistency. Dominant colors with sharp accents outperform timid, evenly-distributed palettes. +- **Motion**: Use animations for effects and micro-interactions. Prioritize CSS-only solutions for HTML. Use Motion library for React when available. Focus on high-impact moments: one well-orchestrated page load with staggered reveals (animation-delay) creates more delight than scattered micro-interactions. Use scroll-triggering and hover states that surprise. +- **Spatial Composition**: Unexpected layouts. Asymmetry. Overlap. Diagonal flow. Grid-breaking elements. Generous negative space OR controlled density. +- **Backgrounds & Visual Details**: Create atmosphere and depth rather than defaulting to solid colors. Add contextual effects and textures that match the overall aesthetic. Apply creative forms like gradient meshes, noise textures, geometric patterns, layered transparencies, dramatic shadows, decorative borders, custom cursors, and grain overlays. + +NEVER use generic AI-generated aesthetics like overused font families (Inter, Roboto, Arial, system fonts), cliched color schemes (particularly purple gradients on white backgrounds), predictable layouts and component patterns, and cookie-cutter design that lacks context-specific character. + +Interpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices (Space Grotesk, for example) across generations. + +**IMPORTANT**: Match implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details. Elegance comes from executing the vision well. + +Remember: Claude is capable of extraordinary creative work. Don't hold back, show what can truly be created when thinking outside the box and committing fully to a distinctive vision. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/SKILL.md new file mode 100644 index 0000000..edfcc9f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/SKILL.md @@ -0,0 +1,477 @@ +--- +name: git-workflow +description: This skill should be used when the user asks to "create git commit", "manage branches", "follow git workflow", "use Conventional Commits", "handle merge conflicts", or asks about git branching strategies, version control best practices, pull request workflows. Provides comprehensive Git workflow guidance for team collaboration. +version: 1.2.0 +--- + +# Git Workflow Standards + +This document defines the project's Git usage standards, including commit message format, branch management strategy, workflows, merge strategies, and more. Following these standards improves collaboration efficiency, enables traceability, supports automation, and reduces conflicts. + +## Commit Message Standards + +The project follows the **Conventional Commits** specification: + +``` +(): + + + +
    +``` + +### Type Reference + +| Type | Description | Example | +| :--- | :--- | :--- | +| `feat` | New feature | `feat(user): add user export functionality` | +| `fix` | Bug fix | `fix(login): fix captcha not refreshing` | +| `docs` | Documentation update | `docs(api): update API documentation` | +| `refactor` | Refactoring | `refactor(utils): refactor utility functions` | +| `perf` | Performance improvement | `perf(list): optimize list performance` | +| `test` | Test related | `test(user): add unit tests` | +| `chore` | Other changes | `chore: update dependency versions` | + +### Subject Rules + +- Start with a verb: add, fix, update, remove, optimize +- No more than 50 characters +- No period at the end + +For more detailed conventions and examples, see `references/commit-conventions.md`. + +## Branch Management Strategy + +### Branch Types + +| Branch Type | Naming Convention | Description | Lifecycle | +| :--- | :--- | :--- | :--- | +| master | `master` | Main branch, releasable state | Permanent | +| develop | `develop` | Development branch, latest integrated code | Permanent | +| feature | `feature/feature-name` | Feature branch | Delete after completion | +| bugfix | `bugfix/issue-description` | Bug fix branch | Delete after fix | +| hotfix | `hotfix/issue-description` | Emergency fix branch | Delete after fix | +| release | `release/version-number` | Release branch | Delete after release | + +### Branch Naming Examples + +``` +feature/user-management # User management feature +feature/123-add-export # Issue-linked feature +bugfix/login-error # Login error fix +hotfix/security-vulnerability # Security vulnerability fix +release/v1.0.0 # Version release +``` + +### Branch Protection Rules + +**master branch:** +- No direct pushes allowed +- Must merge via Pull Request +- Must pass CI checks +- Requires at least one Code Review approval + +**develop branch:** +- Direct pushes restricted +- Pull Request merges recommended +- Must pass CI checks + +For detailed branch strategies and workflows, see `references/branching-strategies.md`. + +## Workflows + +### Daily Development Workflow + +```bash +# 1. Sync latest code +git checkout develop +git pull origin develop + +# 2. Create feature branch +git checkout -b feature/user-management + +# 3. Develop and commit +git add . +git commit -m "feat(user): add user list page" + +# 4. Push to remote +git push -u origin feature/user-management + +# 5. Create Pull Request and request Code Review + +# 6. Merge to develop (via PR) + +# 7. Delete feature branch +git branch -d feature/user-management +git push origin -d feature/user-management +``` + +### Hotfix Workflow + +```bash +# 1. Create fix branch from master +git checkout master +git pull origin master +git checkout -b hotfix/critical-bug + +# 2. Fix and commit +git add . +git commit -m "fix(auth): fix authentication bypass vulnerability" + +# 3. Merge to master +git checkout master +git merge --no-ff hotfix/critical-bug +git tag -a v1.0.1 -m "hotfix: fix authentication bypass vulnerability" +git push origin master --tags + +# 4. Sync to develop +git checkout develop +git merge --no-ff hotfix/critical-bug +git push origin develop +``` + +### Release Workflow + +```bash +# 1. Create release branch +git checkout develop +git checkout -b release/v1.0.0 + +# 2. Update version numbers and documentation + +# 3. Commit version update +git add . +git commit -m "chore(release): prepare release v1.0.0" + +# 4. Merge to master +git checkout master +git merge --no-ff release/v1.0.0 +git tag -a v1.0.0 -m "release: v1.0.0 official release" +git push origin master --tags + +# 5. Sync to develop +git checkout develop +git merge --no-ff release/v1.0.0 +git push origin develop +``` + +## Merge Strategy + +### Merge vs Rebase + +| Feature | Merge | Rebase | +| :--- | :--- | :--- | +| History | Preserves complete history | Linear history | +| Use case | Public branches | Private branches | +| Recommended for | Merging to main branch | Syncing upstream code | + +### Recommendations + +- **Feature branch syncing develop**: Use `rebase` +- **Feature branch merging to develop**: Use `merge --no-ff` +- **develop merging to master**: Use `merge --no-ff` + +```bash +# ✅ Recommended: Feature branch syncing develop +git checkout feature/user-management +git rebase develop + +# ✅ Recommended: Merge feature branch to develop +git checkout develop +git merge --no-ff feature/user-management + +# ❌ Not recommended: Rebase on public branch +git checkout develop +git rebase feature/xxx # Dangerous operation +``` + +**Project convention**: Use `--no-ff` when merging feature branches to preserve branch history. + +For detailed merge strategies and techniques, see `references/merge-strategies.md`. + +## Conflict Resolution + +### Identifying Conflicts + +``` +<<<<<<< HEAD +// Current branch code +const name = 'Alice' +======= +// Branch being merged +const name = 'Bob' +>>>>>>> feature/user-management +``` + +### Resolving Conflicts + +```bash +# 1. View conflicting files +git status + +# 2. Manually edit files to resolve conflicts + +# 3. Mark as resolved +git add + +# 4. Complete the merge +git commit # merge conflict +# or +git rebase --continue # rebase conflict +``` + +### Conflict Resolution Strategies + +```bash +# Keep current branch version +git checkout --ours + +# Keep incoming branch version +git checkout --theirs + +# Abort merge +git merge --abort +git rebase --abort +``` + +### Preventing Conflicts + +1. **Sync code regularly** - Pull latest code before starting work each day +2. **Small commits** - Commit small changes frequently +3. **Modular features** - Implement different features in different files +4. **Communication** - Avoid modifying the same file simultaneously + +For detailed conflict handling and advanced techniques, see `references/conflict-resolution.md`. + +## .gitignore Standards + +### Basic Rules + +``` +# Ignore all .log files +*.log + +# Ignore directories +node_modules/ + +# Ignore directory at root +/temp/ + +# Ignore files in all directories +**/.env + +# Don't ignore specific files +!.gitkeep +``` + +### Common .gitignore + +``` +node_modules/ +dist/ +build/ +.idea/ +.vscode/ +.env +.env.local +logs/ +*.log +.DS_Store +Thumbs.db +``` + +For detailed .gitignore patterns and project-specific configurations, see `references/gitignore-guide.md`. + +## Tag Management + +Uses **Semantic Versioning**: + +``` +MAJOR.MINOR.PATCH[-PRERELEASE] +``` + +### Version Change Rules + +- **MAJOR**: Incompatible API changes (v1.0.0 → v2.0.0) +- **MINOR**: Backward-compatible new features (v1.0.0 → v1.1.0) +- **PATCH**: Backward-compatible bug fixes (v1.0.0 → v1.0.1) + +### Tag Operations + +```bash +# Create annotated tag (recommended) +git tag -a v1.0.0 -m "release: v1.0.0 official release" + +# Push tags +git push origin v1.0.0 +git push origin --tags + +# View tags +git tag +git show v1.0.0 + +# Delete tag +git tag -d v1.0.0 +git push origin :refs/tags/v1.0.0 +``` + +## Team Collaboration Standards + +### Pull Request Standards + +PRs should include: + +```markdown +## Change Description + + +## Change Type +- [ ] New feature (feat) +- [ ] Bug fix (fix) +- [ ] Code refactoring (refactor) + +## Testing Method + + +## Related Issue +Closes #xxx + +## Checklist +- [ ] Code has been self-tested +- [ ] Documentation has been updated +``` + +### Code Review Standards + +Review focus areas: +- **Code quality**: Clear and readable, proper naming, no duplicate code +- **Logic correctness**: Business logic correct, edge cases handled +- **Security**: No security vulnerabilities, sensitive information protected +- **Performance**: No obvious performance issues, resources properly released + +For detailed collaboration standards and best practices, see `references/collaboration.md`. + +## Common Issues + +### Amending the Last Commit + +```bash +# Amend commit content (not yet pushed) +git add forgotten-file.ts +git commit --amend --no-edit + +# Amend commit message +git commit --amend -m "new commit message" +``` + +### Push Rejected + +```bash +# Pull then push +git pull origin master +git push origin master + +# Use rebase for cleaner history +git pull --rebase origin master +git push origin master +``` + +### Rollback to Previous Version + +```bash +# Reset to specific commit (discards subsequent commits) +git reset --hard abc123 + +# Create reverse commit (recommended, preserves history) +git revert abc123 +``` + +### Stash Current Work + +```bash +git stash save "work in progress" +git stash list +git stash pop +``` + +### View File Modification History + +```bash +git log -- # Commit history +git log -p -- # Detailed content +git blame # Per-line author +``` + +## Best Practices Summary + +### Commit Standards + +✅ **Recommended**: +- Follow Conventional Commits specification +- Write clear commit messages describing changes +- One commit for one logical change +- Run code checks before committing + +❌ **Prohibited**: +- Vague commit messages +- Multiple unrelated changes in one commit +- Committing sensitive information (passwords, keys) +- Developing directly on main branch + +### Branch Management + +✅ **Recommended**: +- Use feature branches for development +- Regularly sync main branch code +- Delete branches promptly after feature completion +- Use `--no-ff` merge to preserve history + +❌ **Prohibited**: +- Developing directly on main branch +- Long-lived unmerged feature branches +- Non-standard branch naming +- Rebasing on public branches + +### Code Review + +✅ **Recommended**: +- All code goes through Pull Requests +- At least one reviewer approval before merging +- Provide constructive feedback + +❌ **Prohibited**: +- Merging without review +- Reviewing your own code + +## Additional Resources + +### Reference Files + +For detailed guidance on specific topics: + +- **`references/commit-conventions.md`** - Commit message detailed conventions and examples +- **`references/branching-strategies.md`** - Comprehensive branch management strategies +- **`references/merge-strategies.md`** - Merge, rebase, and conflict resolution strategies +- **`references/conflict-resolution.md`** - Detailed conflict handling and prevention +- **`references/advanced-usage.md`** - Git performance optimization, security, submodules, and advanced techniques +- **`references/collaboration.md`** - Pull request and code review guidelines +- **`references/gitignore-guide.md`** - .gitignore patterns and project-specific configurations + +### Example Files + +Working examples in `examples/`: +- **`examples/commit-messages.txt`** - Good commit message examples +- **`examples/workflow-commands.sh`** - Common workflow command snippets + +## Summary + +This document defines the project's Git standards: + +1. **Commit Messages** - Follow Conventional Commits specification +2. **Branch Management** - master/develop/feature/bugfix/hotfix/release branch strategy +3. **Workflows** - Standard processes for daily development, hotfixes, and releases +4. **Merge Strategy** - Use rebase to sync feature branches, merge --no-ff to merge +5. **Tag Management** - Semantic versioning, annotated tags +6. **Conflict Resolution** - Regular syncing, small commits, team communication + +Following these standards improves collaboration efficiency, ensures code quality, and simplifies version management. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/examples/commit-messages.txt b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/examples/commit-messages.txt new file mode 100644 index 0000000..566a7fb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/examples/commit-messages.txt @@ -0,0 +1,50 @@ +# 好的 Commit Message 示例 + +## 简单提交 + +feat(user): 添加用户导出功能 + +fix(login): 修复验证码不刷新问题 + +docs(readme): 更新安装说明 + +## 带 Body 的提交 + +feat(user): 添加用户批量导入功能 + +- 支持 Excel 文件导入 +- 支持数据校验和错误提示 +- 支持导入进度显示 + +相关需求: #123 + +fix(login): 修复验证码不刷新问题 + +原因: 缓存时间设置过长导致验证码一直显示同一张图片 +方案: 将缓存时间从5分钟调整为1分钟 + +## 带 Footer 的提交 + +feat(api): 重构用户接口 + +BREAKING CHANGE: 用户查询接口路径变更 +旧路径: /api/user/list +新路径: /api/system/user/list + +Closes #789 + +## 特殊类型提交 + +revert: 回滚 feat(user) + +回滚提交 abc123，因为引入了性能问题 + +chore(release): 准备发布 v1.0.0 + +- 更新版本号到 1.0.0 +- 更新 CHANGELOG.md +- 更新 README.md + +test(user): 添加用户模块单元测试 + +覆盖用户注册、登录、资料修改功能 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/examples/workflow-commands.sh b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/examples/workflow-commands.sh new file mode 100644 index 0000000..71b0f19 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/examples/workflow-commands.sh @@ -0,0 +1,132 @@ +#!/bin/bash +# Git 工作流常用命令示例 + +# ============================================ +# 日常开发流程 +# ============================================ + +# 1. 同步最新代码 +git checkout develop +git pull origin develop + +# 2. 创建功能分支 +git checkout -b feature/user-management + +# 3. 开发并提交 +git add . +git commit -m "feat(user): 添加用户列表页面" + +# 4. 推送到远程 +git push -u origin feature/user-management + +# 5. 同步上游更新到功能分支 +git fetch origin develop +git rebase origin/develop + +# 6. 合并到 develop（通过 PR 或直接） +git checkout develop +git merge --no-ff feature/user-management +git push origin develop + +# 7. 删除功能分支 +git branch -d feature/user-management +git push origin -d feature/user-management + +# ============================================ +# 紧急修复流程 +# ============================================ + +# 1. 从 master 创建修复分支 +git checkout master +git pull origin master +git checkout -b hotfix/security-fix + +# 2. 修复并提交 +git add . +git commit -m "fix(auth): 修复认证绕过漏洞" + +# 3. 合并到 master +git checkout master +git merge --no-ff hotfix/security-fix +git tag -a v1.0.1 -m "hotfix: 修复认证绕过漏洞" +git push origin master --tags + +# 4. 同步到 develop +git checkout develop +git merge --no-ff hotfix/security-fix +git push origin develop + +# 5. 删除修复分支 +git branch -d hotfix/security-fix + +# ============================================ +# 版本发布流程 +# ============================================ + +# 1. 创建发布分支 +git checkout develop +git checkout -b release/v1.0.0 + +# 2. 更新版本号和文档 +# 手动编辑 package.json、CHANGELOG.md 等 + +# 3. 提交版本更新 +git add . +git commit -m "chore(release): 准备发布 v1.0.0" + +# 4. 合并到 master +git checkout master +git merge --no-ff release/v1.0.0 +git tag -a v1.0.0 -m "release: v1.0.0 正式版本" +git push origin master --tags + +# 5. 同步到 develop +git checkout develop +git merge --no-ff release/v1.0.0 +git push origin develop + +# 6. 删除发布分支 +git branch -d release/v1.0.0 + +# ============================================ +# 冲突处理 +# ============================================ + +# Merge 冲突处理 +git merge feature/xxx +# 编辑冲突文件... +git add +git commit + +# Rebase 冲突处理 +git rebase develop +# 编辑冲突文件... +git add +git rebase --continue + +# 放弃合并 +git merge --abort +git rebase --abort + +# ============================================ +# 常用工具命令 +# ============================================ + +# 查看状态 +git status + +# 查看日志 +git log --oneline --graph --all + +# 查看分支 +git branch -a + +# 暂存工作 +git stash save "工作进行中" +git stash list +git stash pop + +# 查看文件修改 +git diff +git diff --staged +git log -p -- diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/advanced-usage.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/advanced-usage.md new file mode 100644 index 0000000..9e92251 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/advanced-usage.md @@ -0,0 +1,393 @@ +# Git 高级用法 + +## 标签管理 + +### 版本号规范 + +采用 **语义化版本**（Semantic Versioning）： + +``` +主版本号.次版本号.修订号[-预发布标识] +MAJOR.MINOR.PATCH[-PRERELEASE] +``` + +| 版本变化 | 说明 | 示例 | +| :------- | :----------------- | :---------------- | +| 主版本号 | 不兼容的 API 修改 | `v1.0.0 → v2.0.0` | +| 次版本号 | 向下兼容的功能新增 | `v1.0.0 → v1.1.0` | +| 修订号 | 向下兼容的问题修正 | `v1.0.0 → v1.0.1` | + +### 预发布标识 + +- `alpha` - 内测版本 +- `beta` - 公测版本 +- `rc` - 候选版本 + +``` +v1.0.0-alpha.1 # 第一个内测版本 +v1.0.0-beta.1 # 第一个公测版本 +v1.0.0-rc.1 # 第一个候选版本 +v1.0.0 # 正式版本 +``` + +### 标签操作 + +#### 创建附注标签（推荐） + +```bash +git tag -a v1.0.0 -m "release: v1.0.0 正式版本 + +主要更新: +- 新增用户管理模块 +- 新增支付功能 +- 优化查询性能" +``` + +#### 推送标签 + +```bash +# 推送单个标签 +git push origin v1.0.0 + +# 推送所有标签 +git push origin --tags +``` + +#### 查看标签 + +```bash +git tag +git tag -l "v1.*" +git show v1.0.0 +``` + +#### 删除标签 + +```bash +# 删除本地标签 +git tag -d v1.0.0 + +# 删除远程标签 +git push origin :refs/tags/v1.0.0 +``` + +## Git 性能优化 + +### 大型仓库优化 + +```bash +# 浅克隆（只获取最近的提交） +git clone --depth 1 https://github.com/repo/project.git + +# 部分克隆（按需获取） +git clone --filter=blob:none https://github.com/repo/project.git + +# 稀疏检出（只检出需要的目录） +git clone --filter=blob:none --sparse https://github.com/repo/project.git +cd project +git sparse-checkout init --cone +git sparse-checkout set src/frontend +``` + +### 清理仓库 + +```bash +# 查看仓库大小 +git count-objects -vH + +# 清理无用对象 +git gc --aggressive --prune=now + +# 清理远程已删除的分支引用 +git remote prune origin + +# 清理本地已合并的分支 +git branch --merged master | grep -v "\\*\\|master\\|develop" | xargs -n 1 git branch -d +``` + +### 提升操作速度 + +```bash +# 启用文件系统缓存 +git config --global core.fscache true + +# 启用并行获取 +git config --global fetch.parallel 4 + +# 启用未跟踪文件缓存 +git config --global core.untrackedCache true +``` + +## Git 安全规范 + +### 敏感信息保护 + +```bash +# 检查历史提交中的敏感信息 +git log -p | grep -E "(password|secret|api_key)" + +# 从历史记录中删除敏感文件 +git filter-branch --force --index-filter \ + 'git rm --cached --ignore-unmatch config/secrets.yml' \ + --prune-empty --tag-name-filter cat -- --all + +# 使用 git-secrets 预防敏感信息提交 +git secrets --install +git secrets --register-aws +``` + +### 签名验证 + +```bash +# 配置 GPG 签名 +git config --global user.signingkey YOUR_KEY_ID +git config --global commit.gpgsign true + +# 创建签名提交 +git commit -S -m "feat: 签名提交" + +# 验证签名 +git log --show-signature +``` + +### 仓库权限控制 + +| 规则 | master | develop | feature/* | +| :--------------- | :----- | :------ | :-------- | +| 禁止强制推送 | ✅ | ✅ | ❌ | +| 禁止删除 | ✅ | ✅ | ❌ | +| 必须 Code Review | ✅ | ✅ | ❌ | +| 必须通过 CI | ✅ | ✅ | ❌ | +| 必须签名提交 | ✅ | ❌ | ❌ | + +## 子模块管理 + +### 添加子模块 + +```bash +git submodule add https://github.com/user/repo.git libs/repo + +# 克隆包含子模块的项目 +git clone --recurse-submodules https://github.com/user/project.git + +# 初始化已有项目的子模块 +git submodule init +git submodule update +``` + +### 更新子模块 + +```bash +# 更新单个子模块 +cd libs/repo +git pull origin main + +# 更新所有子模块 +git submodule update --remote + +# 提交子模块更新 +cd .. +git add libs/repo +git commit -m "chore: 更新子模块版本" +``` + +### 删除子模块 + +```bash +# 删除子模块条目 +git submodule deinit -f libs/repo + +# 删除 .git/modules 中的缓存 +rm -rf .git/modules/libs/repo + +# 删除子模块目录 +git rm -f libs/repo +``` + +## 常见问题解决 + +### 1. 修改最后一次提交 + +```bash +# 修改提交内容（未推送） +git add forgotten-file.ts +git commit --amend --no-edit + +# 修改提交消息 +git commit --amend -m "新的提交消息" + +# 回滚最后一次提交，保留更改 +git reset --soft HEAD~1 +``` + +### 2. 推送被拒绝 + +```bash +# 先拉取再推送 +git pull origin master +git push origin master + +# 使用 rebase 保持历史清晰 +git pull --rebase origin master +git push origin master +``` + +### 3. 回滚到之前版本 + +```bash +# 重置到指定提交（丢弃之后的提交） +git reset --hard abc123 + +# 创建反向提交（推荐，保留历史） +git revert abc123 +``` + +### 4. 恢复误删的分支 + +```bash +# 查看操作历史 +git reflog + +# 恢复分支 +git checkout -b feature/xxx def456 +``` + +### 5. 合并多个提交 + +```bash +# 交互式 rebase（只能合并未推送的提交） +git rebase -i HEAD~5 + +# 在编辑器中将要合并的提交标记为 squash +``` + +### 6. 暂存当前工作 + +```bash +git stash save "工作进行中" +git stash list +git stash pop +git stash apply stash@{0} +``` + +### 7. 查看文件修改历史 + +```bash +git log -- # 提交历史 +git log -p -- # 详细内容 +git blame # 每行修改人 +``` + +### 8. 处理大文件 + +```bash +# 使用 Git LFS +git lfs install +git lfs track "*.zip" +git add .gitattributes +``` + +## 实用技巧 + +### 配置别名 + +```bash +git config --global alias.co checkout +git config --global alias.br branch +git config --global alias.ci commit +git config --global alias.st status +git config --global alias.lg "log --graph --oneline --all" +``` + +### 美化日志 + +```bash +# 图形化历史 +git log --graph --oneline --all + +# 搜索提交消息 +git log --grep="用户管理" + +# 搜索代码变更 +git log -S"function_name" +``` + +### 快速操作 + +```bash +# 放弃所有未提交更改 +git reset --hard HEAD + +# 放弃某个文件更改 +git checkout -- filename + +# 删除未跟踪文件 +git clean -fd + +# 批量删除已合并分支 +git branch --merged master | grep -v "\* master" | xargs -n 1 git branch -d +``` + +### 安全操作 + +```bash +# 查看将要推送的内容 +git push --dry-run + +# 安全的强制推送 +git push --force-with-lease + +# 备份分支 +git branch backup-master master +``` + +### 查找问题提交 + +```bash +# 二分查找引入Bug的提交 +git bisect start +git bisect bad # 标记当前有问题 +git bisect good v1.0.0 # 标记某版本是好的 +# Git会自动切换提交，测试后标记 good/bad +git bisect reset # 结束查找 +``` + +## CHANGELOG 管理 + +### 自动生成 CHANGELOG + +使用 `conventional-changelog` 自动生成： + +```bash +# 安装 +pnpm install -D conventional-changelog-cli + +# 生成 CHANGELOG +npx conventional-changelog -p angular -i CHANGELOG.md -s +``` + +### CHANGELOG 格式 + +```markdown +# 更新日志 + +## [1.2.0] - 2024-01-15 + +### 新增 +- 新增用户导出功能 (#123) +- 新增数据备份模块 + +### 修复 +- 修复登录验证码不刷新问题 (#456) +- 修复列表分页异常 + +### 变更 +- 优化用户查询性能 +- 调整菜单权限校验逻辑 + +### 移除 +- 移除废弃的API接口 + +## [1.1.0] - 2024-01-01 +... +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/branching-strategies.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/branching-strategies.md new file mode 100644 index 0000000..570cf1d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/branching-strategies.md @@ -0,0 +1,175 @@ +# 分支管理策略详解 + +## 分支类型 + +| 分支类型 | 命名规范 | 说明 | 生命周期 | +| :------- | :---------------- | :------------------------- | :------------- | +| master | `master` | 主分支，始终保持可发布状态 | 永久 | +| develop | `develop` | 开发分支，集成最新开发代码 | 永久 | +| feature | `feature/功能名` | 功能分支 | 开发完成后删除 | +| bugfix | `bugfix/问题描述` | Bug修复分支 | 修复完成后删除 | +| hotfix | `hotfix/问题描述` | 紧急修复分支 | 修复完成后删除 | +| release | `release/版本号` | 发布分支 | 发布完成后删除 | + +## 分支命名规范 + +### 功能分支 + +``` +feature/user-management # ✅ 用户管理功能 +feature/123-add-export # ✅ 关联Issue的功能 +``` + +### Bug修复分支 + +``` +bugfix/login-error # ✅ 登录错误修复 +bugfix/456-fix-timeout # ✅ 关联Issue的修复 +``` + +### 紧急修复分支 + +``` +hotfix/security-vulnerability # ✅ 安全漏洞修复 +hotfix/v1.0.1 # ✅ 版本号修复 +``` + +### 发布分支 + +``` +release/v1.0.0 # ✅ 版本发布 +release/v2.0.0-beta.1 # ✅ 预发布版本 +``` + +## 分支保护规则 + +### master 分支 + +- 禁止直接推送 +- 必须通过 Pull Request 合并 +- 必须通过 CI 检查 +- 必须至少一人 Code Review + +### develop 分支 + +- 限制直接推送 +- 建议通过 Pull Request 合并 +- 必须通过 CI 检查 + +## 分支操作命令 + +### 创建功能分支 + +```bash +git checkout develop +git pull origin develop +git checkout -b feature/user-management +``` + +### 创建Bug修复分支 + +```bash +git checkout develop +git pull origin develop +git checkout -b bugfix/login-error +``` + +### 创建紧急修复分支（从master创建） + +```bash +git checkout master +git pull origin master +git checkout -b hotfix/security-fix +``` + +### 删除分支 + +```bash +git branch -d feature/user-management # 删除本地分支 +git push origin -d feature/user-management # 删除远程分支 +``` + +## 工作流程详解 + +### 日常开发流程 + +```bash +# 1. 同步最新代码 +git checkout develop +git pull origin develop + +# 2. 创建功能分支 +git checkout -b feature/user-management + +# 3. 开发并提交 +git add . +git commit -m "feat(user): 添加用户列表页面" + +# 4. 推送到远程 +git push -u origin feature/user-management + +# 5. 创建 Pull Request 并请求 Code Review + +# 6. 合并到 develop（通过 PR） + +# 7. 删除功能分支 +git branch -d feature/user-management +git push origin -d feature/user-management +``` + +### 紧急修复流程 + +```bash +# 1. 从 master 创建修复分支 +git checkout master +git pull origin master +git checkout -b hotfix/critical-bug + +# 2. 修复并提交 +git add . +git commit -m "fix(auth): 修复认证绕过漏洞" + +# 3. 合并到 master +git checkout master +git merge --no-ff hotfix/critical-bug +git tag -a v1.0.1 -m "hotfix: 修复认证绕过漏洞" +git push origin master --tags + +# 4. 同步到 develop +git checkout develop +git merge --no-ff hotfix/critical-bug +git push origin develop + +# 5. 删除修复分支 +git branch -d hotfix/critical-bug +``` + +### 版本发布流程 + +```bash +# 1. 创建发布分支 +git checkout develop +git checkout -b release/v1.0.0 + +# 2. 更新版本号和文档 +# 修改 package.json 版本号 +# 更新 CHANGELOG.md + +# 3. 提交版本更新 +git add . +git commit -m "chore(release): 准备发布 v1.0.0" + +# 4. 合并到 master +git checkout master +git merge --no-ff release/v1.0.0 +git tag -a v1.0.0 -m "release: v1.0.0 正式版本" +git push origin master --tags + +# 5. 同步到 develop +git checkout develop +git merge --no-ff release/v1.0.0 +git push origin develop + +# 6. 删除发布分支 +git branch -d release/v1.0.0 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/collaboration.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/collaboration.md new file mode 100644 index 0000000..76cb4a3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/collaboration.md @@ -0,0 +1,119 @@ +# 多人协作规范 + +## Pull Request 规范 + +创建 PR 时应包含以下内容： + +```markdown +## 变更说明 + + +## 变更类型 +- [ ] 新功能 (feat) +- [ ] Bug 修复 (fix) +- [ ] 代码重构 (refactor) +- [ ] 文档更新 (docs) +- [ ] 其他 + +## 测试方式 + + +## 关联 Issue +Closes #xxx + +## 检查清单 +- [ ] 代码已自测 +- [ ] 文档已更新 +- [ ] 变更已添加到 CHANGELOG +``` + +## Code Review 规范 + +### 审查要点 + +#### 1. 代码质量 + +- 代码是否清晰易读 +- 命名是否规范 +- 是否有重复代码 + +#### 2. 逻辑正确性 + +- 业务逻辑是否正确 +- 边界条件是否处理 +- 异常情况是否考虑 + +#### 3. 安全性 + +- 是否有安全漏洞 +- 敏感信息是否暴露 +- 输入是否校验 + +#### 4. 性能 + +- 是否有性能问题 +- 资源是否正确释放 +- 算法复杂度是否合理 + +### 反馈格式 + +```markdown + +🔴 **必须修改**: 这里有 SQL 注入风险，需要使用参数化查询 + + +🟡 **建议修改**: 这个方法可以提取为工具函数，提高复用性 + + +💬 **讨论**: 这里是否可以考虑使用缓存？ + + +👍 **赞**: 这个封装很优雅！ +``` + +## 最佳实践总结 + +### 提交规范 + +✅ **推荐：** + +- 使用 Conventional Commits 规范 +- 提交消息清晰描述改动 +- 一次提交只做一件事 +- 提交前进行代码检查 + +❌ **禁止：** + +- 提交消息模糊不清 +- 一次提交多个不相关改动 +- 提交敏感信息（密码、密钥） +- 直接在主分支开发 + +### 分支管理 + +✅ **推荐：** + +- 使用 feature 分支开发 +- 定期同步主分支代码 +- 功能完成后及时删除分支 +- 使用 `--no-ff` 合并保留历史 + +❌ **禁止：** + +- 在主分支直接开发 +- 长期不合并的功能分支 +- 分支命名不规范 +- 在公共分支上 rebase + +### 代码审查 + +✅ **推荐：** + +- 所有代码通过 Pull Request +- 至少一人审核通过才能合并 +- 提供建设性反馈 + +❌ **禁止：** + +- 未经审查直接合并 +- 自己审查自己的代码 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/commit-conventions.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/commit-conventions.md new file mode 100644 index 0000000..7bb06da --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/commit-conventions.md @@ -0,0 +1,128 @@ +# Commit Message 详细规范 + +## Conventional Commits 格式 + +采用 **Conventional Commits** 规范，提交消息格式如下： + +``` +(): + + + +
    +``` + +## 字段说明 + +| 字段 | 必填 | 说明 | +| :------ | :--- | :------- | +| type | ✅ | 提交类型 | +| scope | ❌ | 影响范围 | +| subject | ✅ | 简短描述 | +| body | ❌ | 详细描述 | +| footer | ❌ | 脚注信息 | + +## Type 类型 + +| 类型 | 说明 | 示例 | +| :--------- | :------- | :---------------------------------- | +| `feat` | 新功能 | `feat(user): 新增用户导出功能` | +| `fix` | 修复Bug | `fix(login): 修复验证码不刷新问题` | +| `docs` | 文档更新 | `docs(api): 更新接口文档` | +| `style` | 代码格式 | `style: 调整代码缩进` | +| `refactor` | 重构 | `refactor(utils): 重构日期工具函数` | +| `perf` | 性能优化 | `perf(list): 优化列表渲染性能` | +| `test` | 测试相关 | `test(user): 添加用户模块单元测试` | +| `build` | 构建相关 | `build: 升级 vite 到 5.0` | +| `ci` | CI配置 | `ci: 添加 GitHub Actions` | +| `chore` | 其他修改 | `chore: 更新依赖版本` | +| `revert` | 回滚提交 | `revert: 回滚 feat(user)` | + +## Scope 范围 + +Scope 用于说明提交影响的范围，常用的 scope 包括： + +- `data` - 数据处理 +- `utils` - 工具函数 +- `model` - 模型架构 +- `config` - 参数配置 +- `trainer` - 训练 +- `evaluator` - 测评 +- `workflow` - 工作流 + +## Subject 规范 + +- 使用动词开头：添加、修复、更新、移除、优化 +- 不超过50个字符 +- 不以句号结尾 +- 使用中文或英文，保持一致 + +### 正确与错误示例 + +``` +# ✅ 正确示例 +feat(user): 添加用户导出功能 +fix(login): 修复验证码不刷新问题 + +# ❌ 错误示例 +feat(user): 添加用户导出功能。 # 不要句号 +feat(user): 用户导出 # 要用动词开头 +feat: 添加了一个新的用户导出功能 # 太长 +``` + +## Body 详细描述 + +当改动较大或需要说明原因时，使用 Body 提供详细描述： + +``` +feat(user): 添加用户批量导入功能 + +- 支持 Excel 文件导入 +- 支持数据校验和错误提示 +- 支持导入进度显示 + +相关需求: #123 +``` + +## Footer 脚注 + +用于关联 Issue 或说明破坏性变更： + +``` +# 关联 Issue +Closes #123, #456 + +# 破坏性变更 +BREAKING CHANGE: 用户接口返回格式变更 +旧格式: { data: user } +新格式: { code: 200, data: user, msg: 'success' } +``` + +## 完整示例 + +### 简单提交 + +```bash +git commit -m "feat(user): 添加用户导出功能" +``` + +### 带 Body 的提交 + +```bash +git commit -m "fix(login): 修复验证码不刷新问题 + +原因: 缓存时间设置过长导致验证码一直显示同一张图片 +方案: 将缓存时间从5分钟调整为1分钟" +``` + +### 带 Footer 的提交 + +```bash +git commit -m "feat(api): 重构用户接口 + +BREAKING CHANGE: 用户查询接口路径变更 +旧路径: /api/user/list +新路径: /api/system/user/list + +Closes #789" +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/conflict-resolution.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/conflict-resolution.md new file mode 100644 index 0000000..0200343 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/conflict-resolution.md @@ -0,0 +1,148 @@ +# 冲突处理详解 + +## 识别冲突 + +当 Git 无法自动合并时，会标记冲突： + +``` +<<<<<<< HEAD +// 当前分支的代码 +const name = '张三' +======= +// 要合并的分支的代码 +const name = '李四' +>>>>>>> feature/user-management +``` + +## 解决冲突步骤 + +### 1. 查看冲突文件 + +```bash +git status +``` + +### 2. 手动编辑文件，解决冲突 + +打开冲突文件，找到冲突标记（`<<<<<<<`、`=======`、`>>>>>>>`），手动编辑选择保留的内容或合并两者。 + +### 3. 标记已解决 + +```bash +git add +``` + +### 4. 完成合并 + +```bash +# 对于 merge 冲突 +git commit + +# 对于 rebase 冲突 +git rebase --continue +``` + +## 冲突处理策略 + +### 保留当前分支版本 + +```bash +git checkout --ours +git add +``` + +### 保留传入分支版本 + +```bash +git checkout --theirs +git add +``` + +### 放弃合并 + +```bash +# 放弃 merge +git merge --abort + +# 放弃 rebase +git rebase --abort +``` + +## 预防冲突的最佳实践 + +1. **及时同步代码** - 每天开始工作前拉取最新代码 +2. **小步提交** - 频繁提交小的改动 +3. **功能模块化** - 不同功能在不同文件中实现 +4. **沟通协作** - 避免同时修改同一文件 + +## 常见冲突场景 + +### 场景1：同一文件不同位置修改 + +这种情况 Git 通常能自动合并，无需人工干预。 + +### 场景2：同一行不同修改 + +需要手动决定保留哪个版本或合并两者。 + +### 场景3：文件重命名 + +Git 通常能智能识别，但如果一个分支重命名而另一个分支修改内容，可能需要手动处理。 + +### 场景4：二进制文件冲突 + +对于图片、PDF 等二进制文件，需要决定保留哪个版本： + +```bash +# 保留当前分支的版本 +git checkout --ours image.png + +# 或保留传入分支的版本 +git checkout --theirs image.png +``` + +## 冲突解决工具 + +### 使用 merge 工具 + +```bash +# 配置合并工具 +git config --global merge.tool vimdiff +git config --global mergetool.prompt false + +# 使用合并工具 +git mergetool +``` + +### 使用 diff 工具 + +```bash +# 查看详细差异 +git diff --ours +git diff --theirs +git diff --base +``` + +## Rebase 冲突特殊处理 + +Rebase 时冲突会逐个提交出现，处理方式： + +```bash +git rebase develop +# 冲突1 -> 解决 -> git add -> git rebase --continue +# 冲突2 -> 解决 -> git add -> git rebase --continue +# ... +# 直到完成 +``` + +如果某一步想跳过： + +```bash +git rebase --skip +``` + +如果整体想放弃： + +```bash +git rebase --abort +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/gitignore-guide.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/gitignore-guide.md new file mode 100644 index 0000000..9bc1a06 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/gitignore-guide.md @@ -0,0 +1,276 @@ +# .gitignore 规范 + +## 基本规则 + +``` +# 空行：不匹配任何文件 +# 注释：以 # 开头 +# 目录：以 / 结尾 +# 取反：以 ! 开头表示不忽略 +# 根目录：以 / 开头表示项目根目录 + +*.log # 忽略所有 .log 文件 +node_modules/ # 忽略 node_modules 目录 +/temp/ # 忽略根目录下的 temp 目录 +**/.env # 忽略所有目录下的 .env 文件 +!.gitkeep # 不忽略 .gitkeep 文件 +``` + +## 通用 .gitignore + +``` +# ============================================ +# 依赖目录 +# ============================================ +node_modules/ +vendor/ + +# ============================================ +# 构建产物 +# ============================================ +dist/ +build/ +target/ + +# ============================================ +# 编辑器和 IDE +# ============================================ +.idea/ +.vscode/ +*.sw? + +# ============================================ +# 环境配置 +# ============================================ +.env +.env.local +.env.*.local + +# ============================================ +# 日志文件 +# ============================================ +logs/ +*.log +npm-debug.log* + +# ============================================ +# 系统文件 +# ============================================ +.DS_Store +Thumbs.db + +# ============================================ +# 缓存文件 +# ============================================ +.cache/ +.eslintcache +.stylelintcache +``` + +## 项目特定配置 + +### 前端/文档项目补充 + +``` +# VitePress +docs/.vitepress/dist +docs/.vitepress/cache + +# Node.js +package-lock.json +yarn.lock +pnpm-lock.yaml +``` + +### 后端项目补充 + +``` +# Maven +target/ +pom.xml.tag +*.jar +!**/src/main/**/target/ + +# 敏感配置 +application-local.yml +application-dev.yml +``` + +### Python 项目补充 + +``` +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +venv/ +env/ +ENV/ +.pytest_cache/ + +# Jupyter Notebook +.ipynb_checkpoints + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype +.pytype/ +``` + +### Go 项目补充 + +``` +# Binaries for programs and plugins +*.exe +*.exe~ +*.dll +*.so +*.dylib + +# Test binary, built with `go test -c` +*.test + +# Output of the go coverage tool +*.out + +# Dependency directories +vendor/ + +# Go workspace file +go.work +``` + +### Rust 项目补充 + +``` +# Rust +/target/ +**/*.rs.bk +*.pdb +Cargo.lock +``` + +## .gitignore 技巧 + +### 忽略文件但保留目录 + +``` +logs/* +!logs/.gitkeep +``` + +### 检查忽略规则 + +```bash +git check-ignore -v filename +``` + +### 清理已提交的忽略文件 + +```bash +git rm --cached filename +git commit -m "chore: 移除不应提交的文件" +``` + +### 调试 .gitignore + +```bash +# 查看文件是否被忽略以及被哪条规则匹配 +git check-ignore -v path/to/file + +# 查看所有被忽略的文件 +git ls-files --others --ignored --exclude-standard +``` + +## 常见模式 + +### 忽略特定文件 + +``` +# 忽略特定文件 +config/local.json +secrets.yaml +``` + +### 忽略特定类型 + +``` +# 忽略所有 .log 文件 +*.log + +# 忽略所有临时文件 +*.tmp +*.temp +``` + +### 忽略目录 + +``` +# 忽略所有 node_modules 目录 +node_modules/ + +# 忽略根目录下的 build 目录 +/build/ + +# 忽略任何位置的 build 目录 +**/build/ +``` + +### 取反规则 + +``` +# 忽略所有 .a 文件 +*.a + +# 但不忽略 lib.a +!lib.a + +# 忽略所有 TODO 文件 +TODO* + +# 但不忽略 TODO.md +!TODO.md +``` + +### 通配符 + +``` +# * 匹配任意字符 +*.log + +# ** 匹配任意目录 +**/temp/ + +# ? 匹配单个字符 +file?.txt + +# [] 匹配括号内任意字符 +file[0-9].txt +``` + +## .gitignore 优先级 + +1. 命令行指定的文件（如 `git add -f`） +2. `.git/info/exclude`（本地排除规则） +3. `.gitignore`（项目级别，提交到仓库） +4. `~/.gitignore_global`（全局级别） + +### 本地排除规则 + +对于不想提交到仓库的本地忽略规则： + +```bash +# 编辑本地排除文件 +git config --global core.excludesfile ~/.gitignore_global + +# 或者使用 .git/info/exclude（仅当前仓库） +echo "secrets.yaml" >> .git/info/exclude +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/merge-strategies.md b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/merge-strategies.md new file mode 100644 index 0000000..ba9735b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/git-workflow/references/merge-strategies.md @@ -0,0 +1,121 @@ +# 合并策略详解 + +## Merge vs Rebase + +| 特性 | Merge | Rebase | +| :------- | :------------------------- | :----------------------- | +| 历史记录 | 保留完整历史，创建合并提交 | 线性历史，不创建合并提交 | +| 适用场景 | 公共分支、需要保留历史 | 私有分支、保持历史清晰 | +| 冲突处理 | 一次性处理所有冲突 | 逐个提交处理冲突 | +| 推荐用法 | 合并到主分支 | 同步上游代码 | + +## 使用建议 + +### 功能分支同步 develop：使用 rebase + +```bash +git checkout feature/user-management +git rebase develop +``` + +### 功能分支合并到 develop：使用 merge --no-ff + +```bash +git checkout develop +git merge --no-ff feature/user-management +``` + +### develop 合并到 master：使用 merge --no-ff + +```bash +git checkout master +git merge --no-ff develop +``` + +### 禁止在公共分支上 rebase + +```bash +# ❌ 危险操作 +git checkout develop +git rebase feature/xxx # 会改写公共历史 +``` + +## Fast-Forward vs No-Fast-Forward + +### Fast-Forward 合并（不创建合并提交） + +```bash +git merge feature/xxx +``` + +``` +# A---B---C (master) +# \ +# D---E (feature) +# 结果: A---B---C---D---E (master) +``` + +### No-Fast-Forward 合并（创建合并提交） + +```bash +git merge --no-ff feature/xxx +``` + +``` +# A---B---C---------M (master) +# \ / +# D---E (feature) +``` + +**项目约定**：合并功能分支时使用 `--no-ff`，保留分支历史信息。 + +## Squash 合并 + +将多个提交压缩成一个： + +```bash +git checkout develop +git merge --squash feature/user-management +git commit -m "feat(user): 添加用户管理功能" +``` + +### 适用场景 + +- 功能分支有太多琐碎提交 +- 想要保持主分支历史清晰 +- 不需要保留开发过程中的细节 + +### Squash vs Merge --no-ff + +| 策略 | 优点 | 缺点 | 适用场景 | +| :---------- | :----------------------- | :----------------------- | :--------------------- | +| merge --no-ff | 保留完整历史和开发过程 | 历史可能比较复杂 | 功能分支、重要功能 | +| squash | 历史清晰，一个提交一个功能 | 丢失开发过程信息 | 小功能、实验性功能 | +| rebase | 线性历史，易于理解 | 改写历史，可能引起问题 | 个人分支、同步上游 | + +## Rebase 高级用法 + +### 交互式 Rebase + +```bash +# 编辑最近5个提交 +git rebase -i HEAD~5 +``` + +在编辑器中可以使用以下命令： +- `pick` - 保留该提交 +- `reword` - 修改提交消息 +- `edit` - 修改提交内容 +- `squash` - 合并到前一个提交 +- `drop` - 删除该提交 + +### Rebase 时解决冲突 + +```bash +git rebase develop +# 出现冲突后，编辑文件解决冲突 +git add +git rebase --continue +# 如果想放弃 rebase +git rebase --abort +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/SKILL.md new file mode 100644 index 0000000..6317441 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/SKILL.md @@ -0,0 +1,712 @@ +--- +name: hook-development +description: This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API. +version: 0.1.0 +--- + +# Hook Development for Claude Code Plugins + +## Overview + +Hooks are event-driven automation scripts that execute in response to Claude Code events. Use hooks to validate operations, enforce policies, add context, and integrate external tools into workflows. + +**Key capabilities:** +- Validate tool calls before execution (PreToolUse) +- React to tool results (PostToolUse) +- Enforce completion standards (Stop, SubagentStop) +- Load project context (SessionStart) +- Automate workflows across the development lifecycle + +## Hook Types + +### Prompt-Based Hooks (Recommended) + +Use LLM-driven decision making for context-aware validation: + +```json +{ + "type": "prompt", + "prompt": "Evaluate if this tool use is appropriate: $TOOL_INPUT", + "timeout": 30 +} +``` + +**Supported events:** Stop, SubagentStop, UserPromptSubmit, PreToolUse + +**Benefits:** +- Context-aware decisions based on natural language reasoning +- Flexible evaluation logic without bash scripting +- Better edge case handling +- Easier to maintain and extend + +### Command Hooks + +Execute bash commands for deterministic checks: + +```json +{ + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/validate.sh", + "timeout": 60 +} +``` + +**Use for:** +- Fast deterministic validations +- File system operations +- External tool integrations +- Performance-critical checks + +## Hook Configuration Formats + +### Plugin hooks.json Format + +**For plugin hooks** in `hooks/hooks.json`, use wrapper format: + +```json +{ + "description": "Brief explanation of hooks (optional)", + "hooks": { + "PreToolUse": [...], + "Stop": [...], + "SessionStart": [...] + } +} +``` + +**Key points:** +- `description` field is optional +- `hooks` field is required wrapper containing actual hook events +- This is the **plugin-specific format** + +**Example:** +```json +{ + "description": "Validation hooks for code quality", + "hooks": { + "PreToolUse": [ + { + "matcher": "Write", + "hooks": [ + { + "type": "command", + "command": "${CLAUDE_PLUGIN_ROOT}/hooks/validate.sh" + } + ] + } + ] + } +} +``` + +### Settings Format (Direct) + +**For user settings** in `.claude/settings.json`, use direct format: + +```json +{ + "PreToolUse": [...], + "Stop": [...], + "SessionStart": [...] +} +``` + +**Key points:** +- No wrapper - events directly at top level +- No description field +- This is the **settings format** + +**Important:** The examples below show the hook event structure that goes inside either format. For plugin hooks.json, wrap these in `{"hooks": {...}}`. + +## Hook Events + +### PreToolUse + +Execute before any tool runs. Use to approve, deny, or modify tool calls. + +**Example (prompt-based):** +```json +{ + "PreToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "Validate file write safety. Check: system paths, credentials, path traversal, sensitive content. Return 'approve' or 'deny'." + } + ] + } + ] +} +``` + +**Output for PreToolUse:** +```json +{ + "hookSpecificOutput": { + "permissionDecision": "allow|deny|ask", + "updatedInput": {"field": "modified_value"} + }, + "systemMessage": "Explanation for Claude" +} +``` + +### PostToolUse + +Execute after tool completes. Use to react to results, provide feedback, or log. + +**Example:** +```json +{ + "PostToolUse": [ + { + "matcher": "Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "Analyze edit result for potential issues: syntax errors, security vulnerabilities, breaking changes. Provide feedback." + } + ] + } + ] +} +``` + +**Output behavior:** +- Exit 0: stdout shown in transcript +- Exit 2: stderr fed back to Claude +- systemMessage included in context + +### Stop + +Execute when main agent considers stopping. Use to validate completeness. + +**Example:** +```json +{ + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Verify task completion: tests run, build succeeded, questions answered. Return 'approve' to stop or 'block' with reason to continue." + } + ] + } + ] +} +``` + +**Decision output:** +```json +{ + "decision": "approve|block", + "reason": "Explanation", + "systemMessage": "Additional context" +} +``` + +### SubagentStop + +Execute when subagent considers stopping. Use to ensure subagent completed its task. + +Similar to Stop hook, but for subagents. + +### UserPromptSubmit + +Execute when user submits a prompt. Use to add context, validate, or block prompts. + +**Example:** +```json +{ + "UserPromptSubmit": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Check if prompt requires security guidance. If discussing auth, permissions, or API security, return relevant warnings." + } + ] + } + ] +} +``` + +### SessionStart + +Execute when Claude Code session begins. Use to load context and set environment. + +**Example:** +```json +{ + "SessionStart": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/load-context.sh" + } + ] + } + ] +} +``` + +**Special capability:** Persist environment variables using `$CLAUDE_ENV_FILE`: +```bash +echo "export PROJECT_TYPE=nodejs" >> "$CLAUDE_ENV_FILE" +``` + +See `examples/load-context.sh` for complete example. + +### SessionEnd + +Execute when session ends. Use for cleanup, logging, and state preservation. + +### PreCompact + +Execute before context compaction. Use to add critical information to preserve. + +### Notification + +Execute when Claude sends notifications. Use to react to user notifications. + +## Hook Output Format + +### Standard Output (All Hooks) + +```json +{ + "continue": true, + "suppressOutput": false, + "systemMessage": "Message for Claude" +} +``` + +- `continue`: If false, halt processing (default true) +- `suppressOutput`: Hide output from transcript (default false) +- `systemMessage`: Message shown to Claude + +### Exit Codes + +- `0` - Success (stdout shown in transcript) +- `2` - Blocking error (stderr fed back to Claude) +- Other - Non-blocking error + +## Hook Input Format + +All hooks receive JSON via stdin with common fields: + +```json +{ + "session_id": "abc123", + "transcript_path": "/path/to/transcript.txt", + "cwd": "/current/working/dir", + "permission_mode": "ask|allow", + "hook_event_name": "PreToolUse" +} +``` + +**Event-specific fields:** + +- **PreToolUse/PostToolUse:** `tool_name`, `tool_input`, `tool_result` +- **UserPromptSubmit:** `user_prompt` +- **Stop/SubagentStop:** `reason` + +Access fields in prompts using `$TOOL_INPUT`, `$TOOL_RESULT`, `$USER_PROMPT`, etc. + +## Environment Variables + +Available in all command hooks: + +- `$CLAUDE_PROJECT_DIR` - Project root path +- `$CLAUDE_PLUGIN_ROOT` - Plugin directory (use for portable paths) +- `$CLAUDE_ENV_FILE` - SessionStart only: persist env vars here +- `$CLAUDE_CODE_REMOTE` - Set if running in remote context + +**Always use ${CLAUDE_PLUGIN_ROOT} in hook commands for portability:** + +```json +{ + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/validate.sh" +} +``` + +## Plugin Hook Configuration + +In plugins, define hooks in `hooks/hooks.json`: + +```json +{ + "PreToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "Validate file write safety" + } + ] + } + ], + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Verify task completion" + } + ] + } + ], + "SessionStart": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/load-context.sh", + "timeout": 10 + } + ] + } + ] +} +``` + +Plugin hooks merge with user's hooks and run in parallel. + +## Matchers + +### Tool Name Matching + +**Exact match:** +```json +"matcher": "Write" +``` + +**Multiple tools:** +```json +"matcher": "Read|Write|Edit" +``` + +**Wildcard (all tools):** +```json +"matcher": "*" +``` + +**Regex patterns:** +```json +"matcher": "mcp__.*__delete.*" // All MCP delete tools +``` + +**Note:** Matchers are case-sensitive. + +### Common Patterns + +```json +// All MCP tools +"matcher": "mcp__.*" + +// Specific plugin's MCP tools +"matcher": "mcp__plugin_asana_.*" + +// All file operations +"matcher": "Read|Write|Edit" + +// Bash commands only +"matcher": "Bash" +``` + +## Security Best Practices + +### Input Validation + +Always validate inputs in command hooks: + +```bash +#!/bin/bash +set -euo pipefail + +input=$(cat) +tool_name=$(echo "$input" | jq -r '.tool_name') + +# Validate tool name format +if [[ ! "$tool_name" =~ ^[a-zA-Z0-9_]+$ ]]; then + echo '{"decision": "deny", "reason": "Invalid tool name"}' >&2 + exit 2 +fi +``` + +### Path Safety + +Check for path traversal and sensitive files: + +```bash +file_path=$(echo "$input" | jq -r '.tool_input.file_path') + +# Deny path traversal +if [[ "$file_path" == *".."* ]]; then + echo '{"decision": "deny", "reason": "Path traversal detected"}' >&2 + exit 2 +fi + +# Deny sensitive files +if [[ "$file_path" == *".env"* ]]; then + echo '{"decision": "deny", "reason": "Sensitive file"}' >&2 + exit 2 +fi +``` + +See `examples/validate-write.sh` and `examples/validate-bash.sh` for complete examples. + +### Quote All Variables + +```bash +# GOOD: Quoted +echo "$file_path" +cd "$CLAUDE_PROJECT_DIR" + +# BAD: Unquoted (injection risk) +echo $file_path +cd $CLAUDE_PROJECT_DIR +``` + +### Set Appropriate Timeouts + +```json +{ + "type": "command", + "command": "bash script.sh", + "timeout": 10 +} +``` + +**Defaults:** Command hooks (60s), Prompt hooks (30s) + +## Performance Considerations + +### Parallel Execution + +All matching hooks run **in parallel**: + +```json +{ + "PreToolUse": [ + { + "matcher": "Write", + "hooks": [ + {"type": "command", "command": "check1.sh"}, // Parallel + {"type": "command", "command": "check2.sh"}, // Parallel + {"type": "prompt", "prompt": "Validate..."} // Parallel + ] + } + ] +} +``` + +**Design implications:** +- Hooks don't see each other's output +- Non-deterministic ordering +- Design for independence + +### Optimization + +1. Use command hooks for quick deterministic checks +2. Use prompt hooks for complex reasoning +3. Cache validation results in temp files +4. Minimize I/O in hot paths + +## Temporarily Active Hooks + +Create hooks that activate conditionally by checking for a flag file or configuration: + +**Pattern: Flag file activation** +```bash +#!/bin/bash +# Only active when flag file exists +FLAG_FILE="$CLAUDE_PROJECT_DIR/.enable-strict-validation" + +if [ ! -f "$FLAG_FILE" ]; then + # Flag not present, skip validation + exit 0 +fi + +# Flag present, run validation +input=$(cat) +# ... validation logic ... +``` + +**Pattern: Configuration-based activation** +```bash +#!/bin/bash +# Check configuration for activation +CONFIG_FILE="$CLAUDE_PROJECT_DIR/.claude/plugin-config.json" + +if [ -f "$CONFIG_FILE" ]; then + enabled=$(jq -r '.strictMode // false' "$CONFIG_FILE") + if [ "$enabled" != "true" ]; then + exit 0 # Not enabled, skip + fi +fi + +# Enabled, run hook logic +input=$(cat) +# ... hook logic ... +``` + +**Use cases:** +- Enable strict validation only when needed +- Temporary debugging hooks +- Project-specific hook behavior +- Feature flags for hooks + +**Best practice:** Document activation mechanism in plugin README so users know how to enable/disable temporary hooks. + +## Hook Lifecycle and Limitations + +### Hooks Load at Session Start + +**Important:** Hooks are loaded when Claude Code session starts. Changes to hook configuration require restarting Claude Code. + +**Cannot hot-swap hooks:** +- Editing `hooks/hooks.json` won't affect current session +- Adding new hook scripts won't be recognized +- Changing hook commands/prompts won't update +- Must restart Claude Code: exit and run `claude` again + +**To test hook changes:** +1. Edit hook configuration or scripts +2. Exit Claude Code session +3. Restart: `claude` or `cc` +4. New hook configuration loads +5. Test hooks with `claude --debug` + +### Hook Validation at Startup + +Hooks are validated when Claude Code starts: +- Invalid JSON in hooks.json causes loading failure +- Missing scripts cause warnings +- Syntax errors reported in debug mode + +Use `/hooks` command to review loaded hooks in current session. + +## Debugging Hooks + +### Enable Debug Mode + +```bash +claude --debug +``` + +Look for hook registration, execution logs, input/output JSON, and timing information. + +### Test Hook Scripts + +Test command hooks directly: + +```bash +echo '{"tool_name": "Write", "tool_input": {"file_path": "/test"}}' | \ + bash ${CLAUDE_PLUGIN_ROOT}/scripts/validate.sh + +echo "Exit code: $?" +``` + +### Validate JSON Output + +Ensure hooks output valid JSON: + +```bash +output=$(./your-hook.sh < test-input.json) +echo "$output" | jq . +``` + +## Quick Reference + +### Hook Events Summary + +| Event | When | Use For | +|-------|------|---------| +| PreToolUse | Before tool | Validation, modification | +| PostToolUse | After tool | Feedback, logging | +| UserPromptSubmit | User input | Context, validation | +| Stop | Agent stopping | Completeness check | +| SubagentStop | Subagent done | Task validation | +| SessionStart | Session begins | Context loading | +| SessionEnd | Session ends | Cleanup, logging | +| PreCompact | Before compact | Preserve context | +| Notification | User notified | Logging, reactions | + +### Best Practices + +**DO:** +- ✅ Use prompt-based hooks for complex logic +- ✅ Use ${CLAUDE_PLUGIN_ROOT} for portability +- ✅ Validate all inputs in command hooks +- ✅ Quote all bash variables +- ✅ Set appropriate timeouts +- ✅ Return structured JSON output +- ✅ Test hooks thoroughly + +**DON'T:** +- ❌ Use hardcoded paths +- ❌ Trust user input without validation +- ❌ Create long-running hooks +- ❌ Rely on hook execution order +- ❌ Modify global state unpredictably +- ❌ Log sensitive information + +## Additional Resources + +### Reference Files + +For detailed patterns and advanced techniques, consult: + +- **`references/patterns.md`** - Common hook patterns (8+ proven patterns) +- **`references/migration.md`** - Migrating from basic to advanced hooks +- **`references/advanced.md`** - Advanced use cases and techniques + +### Example Hook Scripts + +Working examples in `examples/`: + +- **`validate-write.sh`** - File write validation example +- **`validate-bash.sh`** - Bash command validation example +- **`load-context.sh`** - SessionStart context loading example + +### Utility Scripts + +Development tools in `scripts/`: + +- **`validate-hook-schema.sh`** - Validate hooks.json structure and syntax +- **`test-hook.sh`** - Test hooks with sample input before deployment +- **`hook-linter.sh`** - Check hook scripts for common issues and best practices + +### External Resources + +- **Official Docs**: https://docs.claude.com/en/docs/claude-code/hooks +- **Examples**: See security-guidance plugin in marketplace +- **Testing**: Use `claude --debug` for detailed logs +- **Validation**: Use `jq` to validate hook JSON output + +## Implementation Workflow + +To implement hooks in a plugin: + +1. Identify events to hook into (PreToolUse, Stop, SessionStart, etc.) +2. Decide between prompt-based (flexible) or command (deterministic) hooks +3. Write hook configuration in `hooks/hooks.json` +4. For command hooks, create hook scripts +5. Use ${CLAUDE_PLUGIN_ROOT} for all file references +6. Validate configuration with `scripts/validate-hook-schema.sh hooks/hooks.json` +7. Test hooks with `scripts/test-hook.sh` before deployment +8. Test in Claude Code with `claude --debug` +9. Document hooks in plugin README + +Focus on prompt-based hooks for most use cases. Reserve command hooks for performance-critical or deterministic checks. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/load-context.sh b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/load-context.sh new file mode 100644 index 0000000..9754f32 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/load-context.sh @@ -0,0 +1,55 @@ +#!/bin/bash +# Example SessionStart hook for loading project context +# This script detects project type and sets environment variables + +set -euo pipefail + +# Navigate to project directory +cd "$CLAUDE_PROJECT_DIR" || exit 1 + +echo "Loading project context..." + +# Detect project type and set environment +if [ -f "package.json" ]; then + echo "📦 Node.js project detected" + echo "export PROJECT_TYPE=nodejs" >> "$CLAUDE_ENV_FILE" + + # Check if TypeScript + if [ -f "tsconfig.json" ]; then + echo "export USES_TYPESCRIPT=true" >> "$CLAUDE_ENV_FILE" + fi + +elif [ -f "Cargo.toml" ]; then + echo "🦀 Rust project detected" + echo "export PROJECT_TYPE=rust" >> "$CLAUDE_ENV_FILE" + +elif [ -f "go.mod" ]; then + echo "🐹 Go project detected" + echo "export PROJECT_TYPE=go" >> "$CLAUDE_ENV_FILE" + +elif [ -f "pyproject.toml" ] || [ -f "setup.py" ]; then + echo "🐍 Python project detected" + echo "export PROJECT_TYPE=python" >> "$CLAUDE_ENV_FILE" + +elif [ -f "pom.xml" ]; then + echo "☕ Java (Maven) project detected" + echo "export PROJECT_TYPE=java" >> "$CLAUDE_ENV_FILE" + echo "export BUILD_SYSTEM=maven" >> "$CLAUDE_ENV_FILE" + +elif [ -f "build.gradle" ] || [ -f "build.gradle.kts" ]; then + echo "☕ Java/Kotlin (Gradle) project detected" + echo "export PROJECT_TYPE=java" >> "$CLAUDE_ENV_FILE" + echo "export BUILD_SYSTEM=gradle" >> "$CLAUDE_ENV_FILE" + +else + echo "❓ Unknown project type" + echo "export PROJECT_TYPE=unknown" >> "$CLAUDE_ENV_FILE" +fi + +# Check for CI configuration +if [ -f ".github/workflows" ] || [ -f ".gitlab-ci.yml" ] || [ -f ".circleci/config.yml" ]; then + echo "export HAS_CI=true" >> "$CLAUDE_ENV_FILE" +fi + +echo "Project context loaded successfully" +exit 0 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/validate-bash.sh b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/validate-bash.sh new file mode 100644 index 0000000..e364324 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/validate-bash.sh @@ -0,0 +1,43 @@ +#!/bin/bash +# Example PreToolUse hook for validating Bash commands +# This script demonstrates bash command validation patterns + +set -euo pipefail + +# Read input from stdin +input=$(cat) + +# Extract command +command=$(echo "$input" | jq -r '.tool_input.command // empty') + +# Validate command exists +if [ -z "$command" ]; then + echo '{"continue": true}' # No command to validate + exit 0 +fi + +# Check for obviously safe commands (quick approval) +if [[ "$command" =~ ^(ls|pwd|echo|date|whoami)(\s|$) ]]; then + exit 0 +fi + +# Check for destructive operations +if [[ "$command" == *"rm -rf"* ]] || [[ "$command" == *"rm -fr"* ]]; then + echo '{"hookSpecificOutput": {"permissionDecision": "deny"}, "systemMessage": "Dangerous command detected: rm -rf"}' >&2 + exit 2 +fi + +# Check for other dangerous commands +if [[ "$command" == *"dd if="* ]] || [[ "$command" == *"mkfs"* ]] || [[ "$command" == *"> /dev/"* ]]; then + echo '{"hookSpecificOutput": {"permissionDecision": "deny"}, "systemMessage": "Dangerous system operation detected"}' >&2 + exit 2 +fi + +# Check for privilege escalation +if [[ "$command" == sudo* ]] || [[ "$command" == su* ]]; then + echo '{"hookSpecificOutput": {"permissionDecision": "ask"}, "systemMessage": "Command requires elevated privileges"}' >&2 + exit 2 +fi + +# Approve the operation +exit 0 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/validate-write.sh b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/validate-write.sh new file mode 100644 index 0000000..e665193 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/examples/validate-write.sh @@ -0,0 +1,38 @@ +#!/bin/bash +# Example PreToolUse hook for validating Write/Edit operations +# This script demonstrates file write validation patterns + +set -euo pipefail + +# Read input from stdin +input=$(cat) + +# Extract file path and content +file_path=$(echo "$input" | jq -r '.tool_input.file_path // empty') + +# Validate path exists +if [ -z "$file_path" ]; then + echo '{"continue": true}' # No path to validate + exit 0 +fi + +# Check for path traversal +if [[ "$file_path" == *".."* ]]; then + echo '{"hookSpecificOutput": {"permissionDecision": "deny"}, "systemMessage": "Path traversal detected in: '"$file_path"'"}' >&2 + exit 2 +fi + +# Check for system directories +if [[ "$file_path" == /etc/* ]] || [[ "$file_path" == /sys/* ]] || [[ "$file_path" == /usr/* ]]; then + echo '{"hookSpecificOutput": {"permissionDecision": "deny"}, "systemMessage": "Cannot write to system directory: '"$file_path"'"}' >&2 + exit 2 +fi + +# Check for sensitive files +if [[ "$file_path" == *.env ]] || [[ "$file_path" == *secret* ]] || [[ "$file_path" == *credentials* ]]; then + echo '{"hookSpecificOutput": {"permissionDecision": "ask"}, "systemMessage": "Writing to potentially sensitive file: '"$file_path"'"}' >&2 + exit 2 +fi + +# Approve the operation +exit 0 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/advanced.md b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/advanced.md new file mode 100644 index 0000000..a84a38f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/advanced.md @@ -0,0 +1,479 @@ +# Advanced Hook Use Cases + +This reference covers advanced hook patterns and techniques for sophisticated automation workflows. + +## Multi-Stage Validation + +Combine command and prompt hooks for layered validation: + +```json +{ + "PreToolUse": [ + { + "matcher": "Bash", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/quick-check.sh", + "timeout": 5 + }, + { + "type": "prompt", + "prompt": "Deep analysis of bash command: $TOOL_INPUT", + "timeout": 15 + } + ] + } + ] +} +``` + +**Use case:** Fast deterministic checks followed by intelligent analysis + +**Example quick-check.sh:** +```bash +#!/bin/bash +input=$(cat) +command=$(echo "$input" | jq -r '.tool_input.command') + +# Immediate approval for safe commands +if [[ "$command" =~ ^(ls|pwd|echo|date|whoami)$ ]]; then + exit 0 +fi + +# Let prompt hook handle complex cases +exit 0 +``` + +The command hook quickly approves obviously safe commands, while the prompt hook analyzes everything else. + +## Conditional Hook Execution + +Execute hooks based on environment or context: + +```bash +#!/bin/bash +# Only run in CI environment +if [ -z "$CI" ]; then + echo '{"continue": true}' # Skip in non-CI + exit 0 +fi + +# Run validation logic in CI +input=$(cat) +# ... validation code ... +``` + +**Use cases:** +- Different behavior in CI vs local development +- Project-specific validation +- User-specific rules + +**Example: Skip certain checks for trusted users:** +```bash +#!/bin/bash +# Skip detailed checks for admin users +if [ "$USER" = "admin" ]; then + exit 0 +fi + +# Full validation for other users +input=$(cat) +# ... validation code ... +``` + +## Hook Chaining via State + +Share state between hooks using temporary files: + +```bash +# Hook 1: Analyze and save state +#!/bin/bash +input=$(cat) +command=$(echo "$input" | jq -r '.tool_input.command') + +# Analyze command +risk_level=$(calculate_risk "$command") +echo "$risk_level" > /tmp/hook-state-$$ + +exit 0 +``` + +```bash +# Hook 2: Use saved state +#!/bin/bash +risk_level=$(cat /tmp/hook-state-$$ 2>/dev/null || echo "unknown") + +if [ "$risk_level" = "high" ]; then + echo "High risk operation detected" >&2 + exit 2 +fi +``` + +**Important:** This only works for sequential hook events (e.g., PreToolUse then PostToolUse), not parallel hooks. + +## Dynamic Hook Configuration + +Modify hook behavior based on project configuration: + +```bash +#!/bin/bash +cd "$CLAUDE_PROJECT_DIR" || exit 1 + +# Read project-specific config +if [ -f ".claude-hooks-config.json" ]; then + strict_mode=$(jq -r '.strict_mode' .claude-hooks-config.json) + + if [ "$strict_mode" = "true" ]; then + # Apply strict validation + # ... + else + # Apply lenient validation + # ... + fi +fi +``` + +**Example .claude-hooks-config.json:** +```json +{ + "strict_mode": true, + "allowed_commands": ["ls", "pwd", "grep"], + "forbidden_paths": ["/etc", "/sys"] +} +``` + +## Context-Aware Prompt Hooks + +Use transcript and session context for intelligent decisions: + +```json +{ + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Review the full transcript at $TRANSCRIPT_PATH. Check: 1) Were tests run after code changes? 2) Did the build succeed? 3) Were all user questions answered? 4) Is there any unfinished work? Return 'approve' only if everything is complete." + } + ] + } + ] +} +``` + +The LLM can read the transcript file and make context-aware decisions. + +## Performance Optimization + +### Caching Validation Results + +```bash +#!/bin/bash +input=$(cat) +file_path=$(echo "$input" | jq -r '.tool_input.file_path') +cache_key=$(echo -n "$file_path" | md5sum | cut -d' ' -f1) +cache_file="/tmp/hook-cache-$cache_key" + +# Check cache +if [ -f "$cache_file" ]; then + cache_age=$(($(date +%s) - $(stat -f%m "$cache_file" 2>/dev/null || stat -c%Y "$cache_file"))) + if [ "$cache_age" -lt 300 ]; then # 5 minute cache + cat "$cache_file" + exit 0 + fi +fi + +# Perform validation +result='{"decision": "approve"}' + +# Cache result +echo "$result" > "$cache_file" +echo "$result" +``` + +### Parallel Execution Optimization + +Since hooks run in parallel, design them to be independent: + +```json +{ + "PreToolUse": [ + { + "matcher": "Write", + "hooks": [ + { + "type": "command", + "command": "bash check-size.sh", // Independent + "timeout": 2 + }, + { + "type": "command", + "command": "bash check-path.sh", // Independent + "timeout": 2 + }, + { + "type": "prompt", + "prompt": "Check content safety", // Independent + "timeout": 10 + } + ] + } + ] +} +``` + +All three hooks run simultaneously, reducing total latency. + +## Cross-Event Workflows + +Coordinate hooks across different events: + +**SessionStart - Set up tracking:** +```bash +#!/bin/bash +# Initialize session tracking +echo "0" > /tmp/test-count-$$ +echo "0" > /tmp/build-count-$$ +``` + +**PostToolUse - Track events:** +```bash +#!/bin/bash +input=$(cat) +tool_name=$(echo "$input" | jq -r '.tool_name') + +if [ "$tool_name" = "Bash" ]; then + command=$(echo "$input" | jq -r '.tool_result') + if [[ "$command" == *"test"* ]]; then + count=$(cat /tmp/test-count-$$ 2>/dev/null || echo "0") + echo $((count + 1)) > /tmp/test-count-$$ + fi +fi +``` + +**Stop - Verify based on tracking:** +```bash +#!/bin/bash +test_count=$(cat /tmp/test-count-$$ 2>/dev/null || echo "0") + +if [ "$test_count" -eq 0 ]; then + echo '{"decision": "block", "reason": "No tests were run"}' >&2 + exit 2 +fi +``` + +## Integration with External Systems + +### Slack Notifications + +```bash +#!/bin/bash +input=$(cat) +tool_name=$(echo "$input" | jq -r '.tool_name') +decision="blocked" + +# Send notification to Slack +curl -X POST "$SLACK_WEBHOOK" \ + -H 'Content-Type: application/json' \ + -d "{\"text\": \"Hook ${decision} ${tool_name} operation\"}" \ + 2>/dev/null + +echo '{"decision": "deny"}' >&2 +exit 2 +``` + +### Database Logging + +```bash +#!/bin/bash +input=$(cat) + +# Log to database +psql "$DATABASE_URL" -c "INSERT INTO hook_logs (event, data) VALUES ('PreToolUse', '$input')" \ + 2>/dev/null + +exit 0 +``` + +### Metrics Collection + +```bash +#!/bin/bash +input=$(cat) +tool_name=$(echo "$input" | jq -r '.tool_name') + +# Send metrics to monitoring system +echo "hook.pretooluse.${tool_name}:1|c" | nc -u -w1 statsd.local 8125 + +exit 0 +``` + +## Security Patterns + +### Rate Limiting + +```bash +#!/bin/bash +input=$(cat) +command=$(echo "$input" | jq -r '.tool_input.command') + +# Track command frequency +rate_file="/tmp/hook-rate-$$" +current_minute=$(date +%Y%m%d%H%M) + +if [ -f "$rate_file" ]; then + last_minute=$(head -1 "$rate_file") + count=$(tail -1 "$rate_file") + + if [ "$current_minute" = "$last_minute" ]; then + if [ "$count" -gt 10 ]; then + echo '{"decision": "deny", "reason": "Rate limit exceeded"}' >&2 + exit 2 + fi + count=$((count + 1)) + else + count=1 + fi +else + count=1 +fi + +echo "$current_minute" > "$rate_file" +echo "$count" >> "$rate_file" + +exit 0 +``` + +### Audit Logging + +```bash +#!/bin/bash +input=$(cat) +tool_name=$(echo "$input" | jq -r '.tool_name') +timestamp=$(date -Iseconds) + +# Append to audit log +echo "$timestamp | $USER | $tool_name | $input" >> ~/.claude/audit.log + +exit 0 +``` + +### Secret Detection + +```bash +#!/bin/bash +input=$(cat) +content=$(echo "$input" | jq -r '.tool_input.content') + +# Check for common secret patterns +if echo "$content" | grep -qE "(api[_-]?key|password|secret|token).{0,20}['\"]?[A-Za-z0-9]{20,}"; then + echo '{"decision": "deny", "reason": "Potential secret detected in content"}' >&2 + exit 2 +fi + +exit 0 +``` + +## Testing Advanced Hooks + +### Unit Testing Hook Scripts + +```bash +# test-hook.sh +#!/bin/bash + +# Test 1: Approve safe command +result=$(echo '{"tool_input": {"command": "ls"}}' | bash validate-bash.sh) +if [ $? -eq 0 ]; then + echo "✓ Test 1 passed" +else + echo "✗ Test 1 failed" +fi + +# Test 2: Block dangerous command +result=$(echo '{"tool_input": {"command": "rm -rf /"}}' | bash validate-bash.sh) +if [ $? -eq 2 ]; then + echo "✓ Test 2 passed" +else + echo "✗ Test 2 failed" +fi +``` + +### Integration Testing + +Create test scenarios that exercise the full hook workflow: + +```bash +# integration-test.sh +#!/bin/bash + +# Set up test environment +export CLAUDE_PROJECT_DIR="/tmp/test-project" +export CLAUDE_PLUGIN_ROOT="$(pwd)" +mkdir -p "$CLAUDE_PROJECT_DIR" + +# Test SessionStart hook +echo '{}' | bash hooks/session-start.sh +if [ -f "/tmp/session-initialized" ]; then + echo "✓ SessionStart hook works" +else + echo "✗ SessionStart hook failed" +fi + +# Clean up +rm -rf "$CLAUDE_PROJECT_DIR" +``` + +## Best Practices for Advanced Hooks + +1. **Keep hooks independent**: Don't rely on execution order +2. **Use timeouts**: Set appropriate limits for each hook type +3. **Handle errors gracefully**: Provide clear error messages +4. **Document complexity**: Explain advanced patterns in README +5. **Test thoroughly**: Cover edge cases and failure modes +6. **Monitor performance**: Track hook execution time +7. **Version configuration**: Use version control for hook configs +8. **Provide escape hatches**: Allow users to bypass hooks when needed + +## Common Pitfalls + +### ❌ Assuming Hook Order + +```bash +# BAD: Assumes hooks run in specific order +# Hook 1 saves state, Hook 2 reads it +# This can fail because hooks run in parallel! +``` + +### ❌ Long-Running Hooks + +```bash +# BAD: Hook takes 2 minutes to run +sleep 120 +# This will timeout and block the workflow +``` + +### ❌ Uncaught Exceptions + +```bash +# BAD: Script crashes on unexpected input +file_path=$(echo "$input" | jq -r '.tool_input.file_path') +cat "$file_path" # Fails if file doesn't exist +``` + +### ✅ Proper Error Handling + +```bash +# GOOD: Handles errors gracefully +file_path=$(echo "$input" | jq -r '.tool_input.file_path') +if [ ! -f "$file_path" ]; then + echo '{"continue": true, "systemMessage": "File not found, skipping check"}' >&2 + exit 0 +fi +``` + +## Conclusion + +Advanced hook patterns enable sophisticated automation while maintaining reliability and performance. Use these techniques when basic hooks are insufficient, but always prioritize simplicity and maintainability. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/migration.md b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/migration.md new file mode 100644 index 0000000..587cae3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/migration.md @@ -0,0 +1,369 @@ +# Migrating from Basic to Advanced Hooks + +This guide shows how to migrate from basic command hooks to advanced prompt-based hooks for better maintainability and flexibility. + +## Why Migrate? + +Prompt-based hooks offer several advantages: + +- **Natural language reasoning**: LLM understands context and intent +- **Better edge case handling**: Adapts to unexpected scenarios +- **No bash scripting required**: Simpler to write and maintain +- **More flexible validation**: Can handle complex logic without coding + +## Migration Example: Bash Command Validation + +### Before (Basic Command Hook) + +**Configuration:** +```json +{ + "PreToolUse": [ + { + "matcher": "Bash", + "hooks": [ + { + "type": "command", + "command": "bash validate-bash.sh" + } + ] + } + ] +} +``` + +**Script (validate-bash.sh):** +```bash +#!/bin/bash +input=$(cat) +command=$(echo "$input" | jq -r '.tool_input.command') + +# Hard-coded validation logic +if [[ "$command" == *"rm -rf"* ]]; then + echo "Dangerous command detected" >&2 + exit 2 +fi +``` + +**Problems:** +- Only checks for exact "rm -rf" pattern +- Doesn't catch variations like `rm -fr` or `rm -r -f` +- Misses other dangerous commands (`dd`, `mkfs`, etc.) +- No context awareness +- Requires bash scripting knowledge + +### After (Advanced Prompt Hook) + +**Configuration:** +```json +{ + "PreToolUse": [ + { + "matcher": "Bash", + "hooks": [ + { + "type": "prompt", + "prompt": "Command: $TOOL_INPUT.command. Analyze for: 1) Destructive operations (rm -rf, dd, mkfs, etc) 2) Privilege escalation (sudo) 3) Network operations without user consent. Return 'approve' or 'deny' with explanation.", + "timeout": 15 + } + ] + } + ] +} +``` + +**Benefits:** +- Catches all variations and patterns +- Understands intent, not just literal strings +- No script file needed +- Easy to extend with new criteria +- Context-aware decisions +- Natural language explanation in denial + +## Migration Example: File Write Validation + +### Before (Basic Command Hook) + +**Configuration:** +```json +{ + "PreToolUse": [ + { + "matcher": "Write", + "hooks": [ + { + "type": "command", + "command": "bash validate-write.sh" + } + ] + } + ] +} +``` + +**Script (validate-write.sh):** +```bash +#!/bin/bash +input=$(cat) +file_path=$(echo "$input" | jq -r '.tool_input.file_path') + +# Check for path traversal +if [[ "$file_path" == *".."* ]]; then + echo '{"decision": "deny", "reason": "Path traversal detected"}' >&2 + exit 2 +fi + +# Check for system paths +if [[ "$file_path" == "/etc/"* ]] || [[ "$file_path" == "/sys/"* ]]; then + echo '{"decision": "deny", "reason": "System file"}' >&2 + exit 2 +fi +``` + +**Problems:** +- Hard-coded path patterns +- Doesn't understand symlinks +- Missing edge cases (e.g., `/etc` vs `/etc/`) +- No consideration of file content + +### After (Advanced Prompt Hook) + +**Configuration:** +```json +{ + "PreToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "File path: $TOOL_INPUT.file_path. Content preview: $TOOL_INPUT.content (first 200 chars). Verify: 1) Not system directories (/etc, /sys, /usr) 2) Not credentials (.env, tokens, secrets) 3) No path traversal 4) Content doesn't expose secrets. Return 'approve' or 'deny'." + } + ] + } + ] +} +``` + +**Benefits:** +- Context-aware (considers content too) +- Handles symlinks and edge cases +- Natural understanding of "system directories" +- Can detect secrets in content +- Easy to extend criteria + +## When to Keep Command Hooks + +Command hooks still have their place: + +### 1. Deterministic Performance Checks + +```bash +#!/bin/bash +# Check file size quickly +file_path=$(echo "$input" | jq -r '.tool_input.file_path') +size=$(stat -f%z "$file_path" 2>/dev/null || stat -c%s "$file_path" 2>/dev/null) + +if [ "$size" -gt 10000000 ]; then + echo '{"decision": "deny", "reason": "File too large"}' >&2 + exit 2 +fi +``` + +**Use command hooks when:** Validation is purely mathematical or deterministic. + +### 2. External Tool Integration + +```bash +#!/bin/bash +# Run security scanner +file_path=$(echo "$input" | jq -r '.tool_input.file_path') +scan_result=$(security-scanner "$file_path") + +if [ "$?" -ne 0 ]; then + echo "Security scan failed: $scan_result" >&2 + exit 2 +fi +``` + +**Use command hooks when:** Integrating with external tools that provide yes/no answers. + +### 3. Very Fast Checks (< 50ms) + +```bash +#!/bin/bash +# Quick regex check +command=$(echo "$input" | jq -r '.tool_input.command') + +if [[ "$command" =~ ^(ls|pwd|echo)$ ]]; then + exit 0 # Safe commands +fi +``` + +**Use command hooks when:** Performance is critical and logic is simple. + +## Hybrid Approach + +Combine both for multi-stage validation: + +```json +{ + "PreToolUse": [ + { + "matcher": "Bash", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/quick-check.sh", + "timeout": 5 + }, + { + "type": "prompt", + "prompt": "Deep analysis of bash command: $TOOL_INPUT", + "timeout": 15 + } + ] + } + ] +} +``` + +The command hook does fast deterministic checks, while the prompt hook handles complex reasoning. + +## Migration Checklist + +When migrating hooks: + +- [ ] Identify the validation logic in the command hook +- [ ] Convert hard-coded patterns to natural language criteria +- [ ] Test with edge cases the old hook missed +- [ ] Verify LLM understands the intent +- [ ] Set appropriate timeout (usually 15-30s for prompt hooks) +- [ ] Document the new hook in README +- [ ] Remove or archive old script files + +## Migration Tips + +1. **Start with one hook**: Don't migrate everything at once +2. **Test thoroughly**: Verify prompt hook catches what command hook caught +3. **Look for improvements**: Use migration as opportunity to enhance validation +4. **Keep scripts for reference**: Archive old scripts in case you need to reference the logic +5. **Document reasoning**: Explain why prompt hook is better in README + +## Complete Migration Example + +### Original Plugin Structure + +``` +my-plugin/ +├── .claude-plugin/plugin.json +├── hooks/hooks.json +└── scripts/ + ├── validate-bash.sh + ├── validate-write.sh + └── check-tests.sh +``` + +### After Migration + +``` +my-plugin/ +├── .claude-plugin/plugin.json +├── hooks/hooks.json # Now uses prompt hooks +└── scripts/ # Archive or delete + └── archive/ + ├── validate-bash.sh + ├── validate-write.sh + └── check-tests.sh +``` + +### Updated hooks.json + +```json +{ + "PreToolUse": [ + { + "matcher": "Bash", + "hooks": [ + { + "type": "prompt", + "prompt": "Validate bash command safety: destructive ops, privilege escalation, network access" + } + ] + }, + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "Validate file write safety: system paths, credentials, path traversal, content secrets" + } + ] + } + ], + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Verify tests were run if code was modified" + } + ] + } + ] +} +``` + +**Result:** Simpler, more maintainable, more powerful. + +## Common Migration Patterns + +### Pattern: String Contains → Natural Language + +**Before:** +```bash +if [[ "$command" == *"sudo"* ]]; then + echo "Privilege escalation" >&2 + exit 2 +fi +``` + +**After:** +``` +"Check for privilege escalation (sudo, su, etc)" +``` + +### Pattern: Regex → Intent + +**Before:** +```bash +if [[ "$file" =~ \.(env|secret|key|token)$ ]]; then + echo "Credential file" >&2 + exit 2 +fi +``` + +**After:** +``` +"Verify not writing to credential files (.env, secrets, keys, tokens)" +``` + +### Pattern: Multiple Conditions → Criteria List + +**Before:** +```bash +if [ condition1 ] || [ condition2 ] || [ condition3 ]; then + echo "Invalid" >&2 + exit 2 +fi +``` + +**After:** +``` +"Check: 1) condition1 2) condition2 3) condition3. Deny if any fail." +``` + +## Conclusion + +Migrating to prompt-based hooks makes plugins more maintainable, flexible, and powerful. Reserve command hooks for deterministic checks and external tool integration. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/patterns.md b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/patterns.md new file mode 100644 index 0000000..4475386 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/references/patterns.md @@ -0,0 +1,346 @@ +# Common Hook Patterns + +This reference provides common, proven patterns for implementing Claude Code hooks. Use these patterns as starting points for typical hook use cases. + +## Pattern 1: Security Validation + +Block dangerous file writes using prompt-based hooks: + +```json +{ + "PreToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "File path: $TOOL_INPUT.file_path. Verify: 1) Not in /etc or system directories 2) Not .env or credentials 3) Path doesn't contain '..' traversal. Return 'approve' or 'deny'." + } + ] + } + ] +} +``` + +**Use for:** Preventing writes to sensitive files or system directories. + +## Pattern 2: Test Enforcement + +Ensure tests run before stopping: + +```json +{ + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Review transcript. If code was modified (Write/Edit tools used), verify tests were executed. If no tests were run, block with reason 'Tests must be run after code changes'." + } + ] + } + ] +} +``` + +**Use for:** Enforcing quality standards and preventing incomplete work. + +## Pattern 3: Context Loading + +Load project-specific context at session start: + +```json +{ + "SessionStart": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/load-context.sh" + } + ] + } + ] +} +``` + +**Example script (load-context.sh):** +```bash +#!/bin/bash +cd "$CLAUDE_PROJECT_DIR" || exit 1 + +# Detect project type +if [ -f "package.json" ]; then + echo "📦 Node.js project detected" + echo "export PROJECT_TYPE=nodejs" >> "$CLAUDE_ENV_FILE" +elif [ -f "Cargo.toml" ]; then + echo "🦀 Rust project detected" + echo "export PROJECT_TYPE=rust" >> "$CLAUDE_ENV_FILE" +fi +``` + +**Use for:** Automatically detecting and configuring project-specific settings. + +## Pattern 4: Notification Logging + +Log all notifications for audit or analysis: + +```json +{ + "Notification": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/log-notification.sh" + } + ] + } + ] +} +``` + +**Use for:** Tracking user notifications or integration with external logging systems. + +## Pattern 5: MCP Tool Monitoring + +Monitor and validate MCP tool usage: + +```json +{ + "PreToolUse": [ + { + "matcher": "mcp__.*__delete.*", + "hooks": [ + { + "type": "prompt", + "prompt": "Deletion operation detected. Verify: Is this deletion intentional? Can it be undone? Are there backups? Return 'approve' only if safe." + } + ] + } + ] +} +``` + +**Use for:** Protecting against destructive MCP operations. + +## Pattern 6: Build Verification + +Ensure project builds after code changes: + +```json +{ + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Check if code was modified. If Write/Edit tools were used, verify the project was built (npm run build, cargo build, etc). If not built, block and request build." + } + ] + } + ] +} +``` + +**Use for:** Catching build errors before committing or stopping work. + +## Pattern 7: Permission Confirmation + +Ask user before dangerous operations: + +```json +{ + "PreToolUse": [ + { + "matcher": "Bash", + "hooks": [ + { + "type": "prompt", + "prompt": "Command: $TOOL_INPUT.command. If command contains 'rm', 'delete', 'drop', or other destructive operations, return 'ask' to confirm with user. Otherwise 'approve'." + } + ] + } + ] +} +``` + +**Use for:** User confirmation on potentially destructive commands. + +## Pattern 8: Code Quality Checks + +Run linters or formatters on file edits: + +```json +{ + "PostToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/check-quality.sh" + } + ] + } + ] +} +``` + +**Example script (check-quality.sh):** +```bash +#!/bin/bash +input=$(cat) +file_path=$(echo "$input" | jq -r '.tool_input.file_path') + +# Run linter if applicable +if [[ "$file_path" == *.js ]] || [[ "$file_path" == *.ts ]]; then + npx eslint "$file_path" 2>&1 || true +fi +``` + +**Use for:** Automatic code quality enforcement. + +## Pattern Combinations + +Combine multiple patterns for comprehensive protection: + +```json +{ + "PreToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "Validate file write safety" + } + ] + }, + { + "matcher": "Bash", + "hooks": [ + { + "type": "prompt", + "prompt": "Validate bash command safety" + } + ] + } + ], + "Stop": [ + { + "matcher": "*", + "hooks": [ + { + "type": "prompt", + "prompt": "Verify tests run and build succeeded" + } + ] + } + ], + "SessionStart": [ + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/load-context.sh" + } + ] + } + ] +} +``` + +This provides multi-layered protection and automation. + +## Pattern 9: Temporarily Active Hooks + +Create hooks that only run when explicitly enabled via flag files: + +```bash +#!/bin/bash +# Hook only active when flag file exists +FLAG_FILE="$CLAUDE_PROJECT_DIR/.enable-security-scan" + +if [ ! -f "$FLAG_FILE" ]; then + # Quick exit when disabled + exit 0 +fi + +# Flag present, run validation +input=$(cat) +file_path=$(echo "$input" | jq -r '.tool_input.file_path') + +# Run security scan +security-scanner "$file_path" +``` + +**Activation:** +```bash +# Enable the hook +touch .enable-security-scan + +# Disable the hook +rm .enable-security-scan +``` + +**Use for:** +- Temporary debugging hooks +- Feature flags for development +- Project-specific validation that's opt-in +- Performance-intensive checks only when needed + +**Note:** Must restart Claude Code after creating/removing flag files for hooks to recognize changes. + +## Pattern 10: Configuration-Driven Hooks + +Use JSON configuration to control hook behavior: + +```bash +#!/bin/bash +CONFIG_FILE="$CLAUDE_PROJECT_DIR/.claude/my-plugin.local.json" + +# Read configuration +if [ -f "$CONFIG_FILE" ]; then + strict_mode=$(jq -r '.strictMode // false' "$CONFIG_FILE") + max_file_size=$(jq -r '.maxFileSize // 1000000' "$CONFIG_FILE") +else + # Defaults + strict_mode=false + max_file_size=1000000 +fi + +# Skip if not in strict mode +if [ "$strict_mode" != "true" ]; then + exit 0 +fi + +# Apply configured limits +input=$(cat) +file_size=$(echo "$input" | jq -r '.tool_input.content | length') + +if [ "$file_size" -gt "$max_file_size" ]; then + echo '{"decision": "deny", "reason": "File exceeds configured size limit"}' >&2 + exit 2 +fi +``` + +**Configuration file (.claude/my-plugin.local.json):** +```json +{ + "strictMode": true, + "maxFileSize": 500000, + "allowedPaths": ["/tmp", "/home/user/projects"] +} +``` + +**Use for:** +- User-configurable hook behavior +- Per-project settings +- Team-specific rules +- Dynamic validation criteria diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/README.md b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/README.md new file mode 100644 index 0000000..02a556f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/README.md @@ -0,0 +1,164 @@ +# Hook Development Utility Scripts + +These scripts help validate, test, and lint hook implementations before deployment. + +## validate-hook-schema.sh + +Validates `hooks.json` configuration files for correct structure and common issues. + +**Usage:** +```bash +./validate-hook-schema.sh path/to/hooks.json +``` + +**Checks:** +- Valid JSON syntax +- Required fields present +- Valid hook event names +- Proper hook types (command/prompt) +- Timeout values in valid ranges +- Hardcoded path detection +- Prompt hook event compatibility + +**Example:** +```bash +cd my-plugin +./validate-hook-schema.sh hooks/hooks.json +``` + +## test-hook.sh + +Tests individual hook scripts with sample input before deploying to Claude Code. + +**Usage:** +```bash +./test-hook.sh [options] +``` + +**Options:** +- `-v, --verbose` - Show detailed execution information +- `-t, --timeout N` - Set timeout in seconds (default: 60) +- `--create-sample ` - Generate sample test input + +**Example:** +```bash +# Create sample test input +./test-hook.sh --create-sample PreToolUse > test-input.json + +# Test a hook script +./test-hook.sh my-hook.sh test-input.json + +# Test with verbose output and custom timeout +./test-hook.sh -v -t 30 my-hook.sh test-input.json +``` + +**Features:** +- Sets up proper environment variables (CLAUDE_PROJECT_DIR, CLAUDE_PLUGIN_ROOT) +- Measures execution time +- Validates output JSON +- Shows exit codes and their meanings +- Captures environment file output + +## hook-linter.sh + +Checks hook scripts for common issues and best practices violations. + +**Usage:** +```bash +./hook-linter.sh [hook-script2.sh ...] +``` + +**Checks:** +- Shebang presence +- `set -euo pipefail` usage +- Stdin input reading +- Proper error handling +- Variable quoting (injection prevention) +- Exit code usage +- Hardcoded paths +- Long-running code detection +- Error output to stderr +- Input validation + +**Example:** +```bash +# Lint single script +./hook-linter.sh ../examples/validate-write.sh + +# Lint multiple scripts +./hook-linter.sh ../examples/*.sh +``` + +## Typical Workflow + +1. **Write your hook script** + ```bash + vim my-plugin/scripts/my-hook.sh + ``` + +2. **Lint the script** + ```bash + ./hook-linter.sh my-plugin/scripts/my-hook.sh + ``` + +3. **Create test input** + ```bash + ./test-hook.sh --create-sample PreToolUse > test-input.json + # Edit test-input.json as needed + ``` + +4. **Test the hook** + ```bash + ./test-hook.sh -v my-plugin/scripts/my-hook.sh test-input.json + ``` + +5. **Add to hooks.json** + ```bash + # Edit my-plugin/hooks/hooks.json + ``` + +6. **Validate configuration** + ```bash + ./validate-hook-schema.sh my-plugin/hooks/hooks.json + ``` + +7. **Test in Claude Code** + ```bash + claude --debug + ``` + +## Tips + +- Always test hooks before deploying to avoid breaking user workflows +- Use verbose mode (`-v`) to debug hook behavior +- Check the linter output for security and best practice issues +- Validate hooks.json after any changes +- Create different test inputs for various scenarios (safe operations, dangerous operations, edge cases) + +## Common Issues + +### Hook doesn't execute + +Check: +- Script has shebang (`#!/bin/bash`) +- Script is executable (`chmod +x`) +- Path in hooks.json is correct (use `${CLAUDE_PLUGIN_ROOT}`) + +### Hook times out + +- Reduce timeout in hooks.json +- Optimize hook script performance +- Remove long-running operations + +### Hook fails silently + +- Check exit codes (should be 0 or 2) +- Ensure errors go to stderr (`>&2`) +- Validate JSON output structure + +### Injection vulnerabilities + +- Always quote variables: `"$variable"` +- Use `set -euo pipefail` +- Validate all input fields +- Run the linter to catch issues diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/hook-linter.sh b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/hook-linter.sh new file mode 100644 index 0000000..64f6041 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/hook-linter.sh @@ -0,0 +1,153 @@ +#!/bin/bash +# Hook Linter +# Checks hook scripts for common issues and best practices + +set -euo pipefail + +# Usage +if [ $# -eq 0 ]; then + echo "Usage: $0 [hook-script2.sh ...]" + echo "" + echo "Checks hook scripts for:" + echo " - Shebang presence" + echo " - set -euo pipefail usage" + echo " - Input reading from stdin" + echo " - Proper error handling" + echo " - Variable quoting" + echo " - Exit code usage" + echo " - Hardcoded paths" + echo " - Timeout considerations" + exit 1 +fi + +check_script() { + local script="$1" + local warnings=0 + local errors=0 + + echo "🔍 Linting: $script" + echo "" + + if [ ! -f "$script" ]; then + echo "❌ Error: File not found" + return 1 + fi + + # Check 1: Executable + if [ ! -x "$script" ]; then + echo "⚠️ Not executable (chmod +x $script)" + ((warnings++)) + fi + + # Check 2: Shebang + first_line=$(head -1 "$script") + if [[ ! "$first_line" =~ ^#!/ ]]; then + echo "❌ Missing shebang (#!/bin/bash)" + ((errors++)) + fi + + # Check 3: set -euo pipefail + if ! grep -q "set -euo pipefail" "$script"; then + echo "⚠️ Missing 'set -euo pipefail' (recommended for safety)" + ((warnings++)) + fi + + # Check 4: Reads from stdin + if ! grep -q "cat\|read" "$script"; then + echo "⚠️ Doesn't appear to read input from stdin" + ((warnings++)) + fi + + # Check 5: Uses jq for JSON parsing + if grep -q "tool_input\|tool_name" "$script" && ! grep -q "jq" "$script"; then + echo "⚠️ Parses hook input but doesn't use jq" + ((warnings++)) + fi + + # Check 6: Unquoted variables + if grep -E '\$[A-Za-z_][A-Za-z0-9_]*[^"]' "$script" | grep -v '#' | grep -q .; then + echo "⚠️ Potentially unquoted variables detected (injection risk)" + echo " Always use double quotes: \"\$variable\" not \$variable" + ((warnings++)) + fi + + # Check 7: Hardcoded paths + if grep -E '^[^#]*/home/|^[^#]*/usr/|^[^#]*/opt/' "$script" | grep -q .; then + echo "⚠️ Hardcoded absolute paths detected" + echo " Use \$CLAUDE_PROJECT_DIR or \$CLAUDE_PLUGIN_ROOT" + ((warnings++)) + fi + + # Check 8: Uses CLAUDE_PLUGIN_ROOT + if ! grep -q "CLAUDE_PLUGIN_ROOT\|CLAUDE_PROJECT_DIR" "$script"; then + echo "💡 Tip: Use \$CLAUDE_PLUGIN_ROOT for plugin-relative paths" + fi + + # Check 9: Exit codes + if ! grep -q "exit 0\|exit 2" "$script"; then + echo "⚠️ No explicit exit codes (should exit 0 or 2)" + ((warnings++)) + fi + + # Check 10: JSON output for decision hooks + if grep -q "PreToolUse\|Stop" "$script"; then + if ! grep -q "permissionDecision\|decision" "$script"; then + echo "💡 Tip: PreToolUse/Stop hooks should output decision JSON" + fi + fi + + # Check 11: Long-running commands + if grep -E 'sleep [0-9]{3,}|while true' "$script" | grep -v '#' | grep -q .; then + echo "⚠️ Potentially long-running code detected" + echo " Hooks should complete quickly (< 60s)" + ((warnings++)) + fi + + # Check 12: Error messages to stderr + if grep -q 'echo.*".*error\|Error\|denied\|Denied' "$script"; then + if ! grep -q '>&2' "$script"; then + echo "⚠️ Error messages should be written to stderr (>&2)" + ((warnings++)) + fi + fi + + # Check 13: Input validation + if ! grep -q "if.*empty\|if.*null\|if.*-z" "$script"; then + echo "💡 Tip: Consider validating input fields aren't empty" + fi + + echo "" + echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" + + if [ $errors -eq 0 ] && [ $warnings -eq 0 ]; then + echo "✅ No issues found" + return 0 + elif [ $errors -eq 0 ]; then + echo "⚠️ Found $warnings warning(s)" + return 0 + else + echo "❌ Found $errors error(s) and $warnings warning(s)" + return 1 + fi +} + +echo "🔎 Hook Script Linter" +echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" +echo "" + +total_errors=0 + +for script in "$@"; do + if ! check_script "$script"; then + ((total_errors++)) + fi + echo "" +done + +if [ $total_errors -eq 0 ]; then + echo "✅ All scripts passed linting" + exit 0 +else + echo "❌ $total_errors script(s) had errors" + exit 1 +fi diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/test-hook.sh b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/test-hook.sh new file mode 100644 index 0000000..527b119 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/test-hook.sh @@ -0,0 +1,252 @@ +#!/bin/bash +# Hook Testing Helper +# Tests a hook with sample input and shows output + +set -euo pipefail + +# Usage +show_usage() { + echo "Usage: $0 [options] " + echo "" + echo "Options:" + echo " -h, --help Show this help message" + echo " -v, --verbose Show detailed execution information" + echo " -t, --timeout N Set timeout in seconds (default: 60)" + echo "" + echo "Examples:" + echo " $0 validate-bash.sh test-input.json" + echo " $0 -v -t 30 validate-write.sh write-input.json" + echo "" + echo "Creates sample test input with:" + echo " $0 --create-sample " + exit 0 +} + +# Create sample input +create_sample() { + event_type="$1" + + case "$event_type" in + PreToolUse) + cat <<'EOF' +{ + "session_id": "test-session", + "transcript_path": "/tmp/transcript.txt", + "cwd": "/tmp/test-project", + "permission_mode": "ask", + "hook_event_name": "PreToolUse", + "tool_name": "Write", + "tool_input": { + "file_path": "/tmp/test.txt", + "content": "Test content" + } +} +EOF + ;; + PostToolUse) + cat <<'EOF' +{ + "session_id": "test-session", + "transcript_path": "/tmp/transcript.txt", + "cwd": "/tmp/test-project", + "permission_mode": "ask", + "hook_event_name": "PostToolUse", + "tool_name": "Bash", + "tool_result": "Command executed successfully" +} +EOF + ;; + Stop|SubagentStop) + cat <<'EOF' +{ + "session_id": "test-session", + "transcript_path": "/tmp/transcript.txt", + "cwd": "/tmp/test-project", + "permission_mode": "ask", + "hook_event_name": "Stop", + "reason": "Task appears complete" +} +EOF + ;; + UserPromptSubmit) + cat <<'EOF' +{ + "session_id": "test-session", + "transcript_path": "/tmp/transcript.txt", + "cwd": "/tmp/test-project", + "permission_mode": "ask", + "hook_event_name": "UserPromptSubmit", + "user_prompt": "Test user prompt" +} +EOF + ;; + SessionStart|SessionEnd) + cat <<'EOF' +{ + "session_id": "test-session", + "transcript_path": "/tmp/transcript.txt", + "cwd": "/tmp/test-project", + "permission_mode": "ask", + "hook_event_name": "SessionStart" +} +EOF + ;; + *) + echo "Unknown event type: $event_type" + echo "Valid types: PreToolUse, PostToolUse, Stop, SubagentStop, UserPromptSubmit, SessionStart, SessionEnd" + exit 1 + ;; + esac +} + +# Parse arguments +VERBOSE=false +TIMEOUT=60 + +while [ $# -gt 0 ]; do + case "$1" in + -h|--help) + show_usage + ;; + -v|--verbose) + VERBOSE=true + shift + ;; + -t|--timeout) + TIMEOUT="$2" + shift 2 + ;; + --create-sample) + create_sample "$2" + exit 0 + ;; + *) + break + ;; + esac +done + +if [ $# -ne 2 ]; then + echo "Error: Missing required arguments" + echo "" + show_usage +fi + +HOOK_SCRIPT="$1" +TEST_INPUT="$2" + +# Validate inputs +if [ ! -f "$HOOK_SCRIPT" ]; then + echo "❌ Error: Hook script not found: $HOOK_SCRIPT" + exit 1 +fi + +if [ ! -x "$HOOK_SCRIPT" ]; then + echo "⚠️ Warning: Hook script is not executable. Attempting to run with bash..." + HOOK_SCRIPT="bash $HOOK_SCRIPT" +fi + +if [ ! -f "$TEST_INPUT" ]; then + echo "❌ Error: Test input not found: $TEST_INPUT" + exit 1 +fi + +# Validate test input JSON +if ! jq empty "$TEST_INPUT" 2>/dev/null; then + echo "❌ Error: Test input is not valid JSON" + exit 1 +fi + +echo "🧪 Testing hook: $HOOK_SCRIPT" +echo "📥 Input: $TEST_INPUT" +echo "" + +if [ "$VERBOSE" = true ]; then + echo "Input JSON:" + jq . "$TEST_INPUT" + echo "" +fi + +# Set up environment +export CLAUDE_PROJECT_DIR="${CLAUDE_PROJECT_DIR:-/tmp/test-project}" +export CLAUDE_PLUGIN_ROOT="${CLAUDE_PLUGIN_ROOT:-$(pwd)}" +export CLAUDE_ENV_FILE="${CLAUDE_ENV_FILE:-/tmp/test-env-$$}" + +if [ "$VERBOSE" = true ]; then + echo "Environment:" + echo " CLAUDE_PROJECT_DIR=$CLAUDE_PROJECT_DIR" + echo " CLAUDE_PLUGIN_ROOT=$CLAUDE_PLUGIN_ROOT" + echo " CLAUDE_ENV_FILE=$CLAUDE_ENV_FILE" + echo "" +fi + +# Run the hook +echo "▶️ Running hook (timeout: ${TIMEOUT}s)..." +echo "" + +start_time=$(date +%s) + +set +e +output=$(timeout "$TIMEOUT" bash -c "cat '$TEST_INPUT' | $HOOK_SCRIPT" 2>&1) +exit_code=$? +set -e + +end_time=$(date +%s) +duration=$((end_time - start_time)) + +# Analyze results +echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" +echo "Results:" +echo "" +echo "Exit Code: $exit_code" +echo "Duration: ${duration}s" +echo "" + +case $exit_code in + 0) + echo "✅ Hook approved/succeeded" + ;; + 2) + echo "🚫 Hook blocked/denied" + ;; + 124) + echo "⏱️ Hook timed out after ${TIMEOUT}s" + ;; + *) + echo "⚠️ Hook returned unexpected exit code: $exit_code" + ;; +esac + +echo "" +echo "Output:" +if [ -n "$output" ]; then + echo "$output" + echo "" + + # Try to parse as JSON + if echo "$output" | jq empty 2>/dev/null; then + echo "Parsed JSON output:" + echo "$output" | jq . + fi +else + echo "(no output)" +fi + +# Check for environment file +if [ -f "$CLAUDE_ENV_FILE" ]; then + echo "" + echo "Environment file created:" + cat "$CLAUDE_ENV_FILE" + rm -f "$CLAUDE_ENV_FILE" +fi + +echo "" +echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" + +if [ $exit_code -eq 0 ] || [ $exit_code -eq 2 ]; then + echo "✅ Test completed successfully" + exit 0 +else + echo "❌ Test failed" + exit 1 +fi diff --git a/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/validate-hook-schema.sh b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/validate-hook-schema.sh new file mode 100644 index 0000000..fed0a1f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/hook-development/scripts/validate-hook-schema.sh @@ -0,0 +1,159 @@ +#!/bin/bash +# Hook Schema Validator +# Validates hooks.json structure and checks for common issues + +set -euo pipefail + +# Usage +if [ $# -eq 0 ]; then + echo "Usage: $0 " + echo "" + echo "Validates hook configuration file for:" + echo " - Valid JSON syntax" + echo " - Required fields" + echo " - Hook type validity" + echo " - Matcher patterns" + echo " - Timeout ranges" + exit 1 +fi + +HOOKS_FILE="$1" + +if [ ! -f "$HOOKS_FILE" ]; then + echo "❌ Error: File not found: $HOOKS_FILE" + exit 1 +fi + +echo "🔍 Validating hooks configuration: $HOOKS_FILE" +echo "" + +# Check 1: Valid JSON +echo "Checking JSON syntax..." +if ! jq empty "$HOOKS_FILE" 2>/dev/null; then + echo "❌ Invalid JSON syntax" + exit 1 +fi +echo "✅ Valid JSON" + +# Check 2: Root structure +echo "" +echo "Checking root structure..." +VALID_EVENTS=("PreToolUse" "PostToolUse" "UserPromptSubmit" "Stop" "SubagentStop" "SessionStart" "SessionEnd" "PreCompact" "Notification") + +for event in $(jq -r 'keys[]' "$HOOKS_FILE"); do + found=false + for valid_event in "${VALID_EVENTS[@]}"; do + if [ "$event" = "$valid_event" ]; then + found=true + break + fi + done + + if [ "$found" = false ]; then + echo "⚠️ Unknown event type: $event" + fi +done +echo "✅ Root structure valid" + +# Check 3: Validate each hook +echo "" +echo "Validating individual hooks..." + +error_count=0 +warning_count=0 + +for event in $(jq -r 'keys[]' "$HOOKS_FILE"); do + hook_count=$(jq -r ".\"$event\" | length" "$HOOKS_FILE") + + for ((i=0; i Last updated: 2026-01-21 +> Source count: 0 + +## Original Summaries +_No sources yet._ + +## Code Templates +_No templates yet._ + +## Best Practices +_No practices yet._ + +## Metadata +| Source | Date | Tags | +|--------|------|------| diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/multimodal.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/multimodal.md new file mode 100644 index 0000000..5d3997d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/multimodal.md @@ -0,0 +1,17 @@ +# Multimodal Knowledge Base + +> Last updated: 2026-01-21 +> Source count: 0 + +## Original Summaries +_No sources yet._ + +## Code Templates +_No templates yet._ + +## Best Practices +_No practices yet._ + +## Metadata +| Source | Date | Tags | +|--------|------|------| diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/nlp.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/nlp.md new file mode 100644 index 0000000..6ca0be4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/nlp.md @@ -0,0 +1,3502 @@ +# NLP Knowledge Base + +> Last updated: 2026-01-23 +> Source count: 4 + +## Competition Brief (竞赛简介) + +### Eedi - Mining Misconceptions in Mathematics (2024) + +**竞赛背景：** +- **主办方**：The Learning Agency (TLA) +- **目标**：从数学问题中识别学生的误解 +- **应用场景**：教育科技、个性化学习、智能辅导系统 +- **社会意义**：自动化误解检测，帮助教师针对性教学 + +**任务描述：** +从数学问题文本中识别最相关的误解（Misconception）： +- **输入**：数学问题文本 + 4 个选项（1 个正确，3 个错误） +- **输出**：Top 3 最相关的误解类别（2,587 种类型） +- **评估**：MAP@3 (Mean Average Precision at 3) + +**数据集规模：** +- 训练集：1,868 个数学问题 +- 误解类别：2,587 种类型 +- 数据来源：Vanderbilt 专家标注 + +**数据特点：** +1. **多标签问题**：一个问题可能有多个相关的误解 +2. **解释依赖**：需要理解问题的推理过程 +3. **领域知识**：需要深入的数学专业知识 + +**评估指标：** +- **MAP@3**：预测的前 3 个误解的平均精度 +- 需要对误解类别进行排序 + +**竞赛约束：** +- 奖金池：$12,000 +- 时间限制：约 2 个月 + +**最终排名：** +- 1st Place: Team MTH 101 (Raja Biswas) - Score ~0.637 +- 2nd Place: - +- 3rd Place: - + +**技术趋势：** +- **检索增强生成 (RAG)**：检索相似问题 + LLM 生成答案 +- **多阶段流水线**：检索 + 重排的分离架构 +- **LLM 微调**：Qwen 系列 LLM 用于教育任务 + +**关键创新：** +- **多阶段检索+重排流水线** (1st Place) +- **Distractor prediction** (1st Place)：预测错误答案与误解的亲和度 +- **Retrieval-augmented approach** (1st Place)：嵌入模型检索候选误解 + +--- + +### MAP - Charting Student Math Misunderstandings (2024) + +**竞赛背景：** +- **主办方**：The Learning Agency (TLA) +- **目标**：从学生回答中识别数学误解 +- **应用场景**：教育评估、学习进度跟踪 +- **社会意义**：大规模数学误解诊断，改进教学方法 + +**任务描述：** +从学生回答和题目文本中识别误解： +- **输入**：题目文本 + 学生回答（可能是文本、图像、混合） +- **输出**：Top 3 相关误解 +- **挑战**：回答可能是部分正确、完全错误、或包含多步推理 + +**数据集规模：** +- 训练集：1,850+ 个回答（来自多个来源） +- 误解类别：2,587 种类型 +- 答案类型：文本、图像、混合 + +**数据特点：** +1. **多模态输入**：文本、图像、混合数据 +2. **推理链依赖**：需要分析多步推理过程 +3. **部分正确答案**：答案可能包含正确和错误元素的混合 + +**评估指标：** +- **MAP@3**：平均精度 +- 需要考虑部分正确的情况 + +**竞赛约束：** +- 计算资源限制 +- 数据隐私保护 + +**最终排名：** +- 1st Place: Team MTH 101 (Raja Biswas) - Score >0.948 MAP@3 +- 2nd Place: - +- 3rd Place: - +- 总参赛队伍：1,850+ + +**技术趋势：** +- **多阶段推理**：分步骤处理复杂推理 +- **合成数据**：LLM 生成额外训练数据 +- **知识蒸馏**：大模型 → 小模型 + +**关键创新：** +- **MiRAGE 框架** (1st Place)：Retrieval-guided Multi-stage Reasoning and Ensemble Fusion +- **Shared-prefix attention** (1st Place)：FlexAttention masks for suffix classification +- **Multi-loss training** (2nd Place)：Soft labels + synthetic data +- **CoT distillation** (通用)：20B → 8B 知识蒸馏 + +**Note:** MAP 是 Eedi 竞赛的后续版本，扩展到更完整的学生回答分析 + +--- + +## Original Summaries + +### Eedi - Mining Misconceptions in Mathematics (2024) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/eedi-mining-misconceptions-in-mathematics) | [Lessons Learned](https://the-learning-agency.com/the-cutting-ed/article/lessons-learned-from-hosting-ai-competitions-in-edtech/) +**Category:** NLP/LLM (教育 AI / 误解检测) +**Key Techniques:** +- **多阶段检索+重排流水线**: Qwen LLMs 用于初始检索和重排序 +- **Distractor prediction**: 预测错误答案与误解的亲和度 +- **Retrieval-augmented approach**: 嵌入模型检索候选误解 +- **Same winner as MAP**: Team MTH 101 (Raja Biswas) 赢得了 Eedi 和 MAP + +**Results:** 1st Place score ~0.637, $12,000 奖金, 数据集 1,868 个数学问题 + +#### 前排方案详细技术分析 + +**1st Place - Team MTH 101 (Raja Biswas)** + +核心技巧： +- **多阶段检索+重排流水线**：Qwen LLMs 用于初始检索和重排序 +- **Distractor prediction**：预测错误答案与误解的亲和度 +- **Retrieval-augmented approach**：嵌入模型检索候选误解 +- **LLM 微调**：Qwen 系列 LLM 在教育数据上微调 +- **集成融合**：多个模型的加权组合 + +实现细节： +- 检索阶段：使用嵌入模型检索相似历史问题和误解 +- 重排序：Qwen LLM 对检索结果进行精排 +- Distractor prediction：单独的模型预测错误选项的迷惑性 +- 最终 MAP@3：~0.637，获得 $12,000 奖金 + +**与 MAP 的关系**： +- 同一冠军团队（Team MTH 101） +- 技术框架一脉相承：检索 + 推理 + 集成 +- MAP 是 Eedi 的扩展版本，处理更复杂的学生回答数据 + +**2nd Place - Kazuhito Yonekawa et al.** + +核心技巧： +- **多阶段 retrieve-and-rank**：嵌入检索 + LLM 重排 +- **Qwen2.5-72B 主模型**：大规模 LLM 用于推理和重排 +- **CoT 提示工程**：思维链提示引导模型推理 +- **后处理优化**：基于误解层次结构的后处理 + +实现细节： +- Qwen2.5-72B 用于重排，小模型用于检索 +- CoT 提示："Let's think step by step about what misconception this might show." +- 后处理：父子误解关系的层次约束 +- 最终 MAP@3：~0.636 + +**3rd Place - waseda-pochi** + +核心技巧： +- **Magic boost post-processing**：针对特定误解类型的 boost +- **Unknown misconception correction**：修正"未知"误解的预测 +- **Qwen2.5-32B 模型**：平衡性能和效率 +- **特征工程**：问题难度、选项分布等特征 + +实现细节： +- Magic boost：为低召回但高精度误解提升权重 +- Unknown correction：使用相似误解替换"Unknown"标签 +- 特征：问题长度、选项数量、数字密度等 +- 最终 MAP@3：~0.635 + +**4th Place - (匿名团队)** + +核心技巧： +- **CoT features 辅助**：思维链特征作为额外输入 +- **分组合成数据**：按问题类型分组生成合成数据 +- **Qwen2.5-32B 集成**：多个模型集成 +- **两阶段训练**：预训练 + 微调 + +实现细节： +- CoT features：提取推理链中的关键步骤作为特征 +- 分组合成：按代数、几何、概率等分组生成合成问题 +- 两阶段：在通用数学数据上预训练，Eedi 数据微调 +- 最终 MAP@3：~0.634 + +**5th Place - ebi-ktr** + +核心技巧： +- **Bi-encoder 检索**：双编码器架构高效检索 +- **Listwise reranking**：列表级重排代替点级 +- **多模型融合**：嵌入模型 + LLM 融合 +- **负采样策略**：困难负样本挖掘 + +实现细节： +- Bi-encoder：Question 和 Misconception 分别编码 +- Listwise：LambdaLoss 优化整个排序列表 +- 负采样：选择与问题相似但不是正确误解的样本 +- 最终 MAP@3：~0.633 + +**6th Place - (匿名团队)** + +核心技巧： +- **QLoRA 微调**：参数高效微调大模型 +- **Qwen2.5-14B 架构**：较小模型降低成本 +- **集成策略**：多个 LoRA 适配器集成 +- **数据增强**：数学问题改写增强 + +实现细节： +- QLoRA：rank=64, α=16, dropout=0.05 +- LoRA 适配器：在 Qwen2.5-14B 上训练 4-6 个适配器 +- 数据增强：改写问题表述，保持误解类型不变 +- 最终 MAP@3：~0.632 + +**7th (Private) / 2nd (Public) - terekaerumasahmet** + +核心技巧： +- **Multi-loss 组合**：多种损失函数组合 +- **Soft labels 蒸馏**：从大模型蒸馏软标签 +- **Qwen2.5-32B 主模型**：平衡性能 +- **多种采样策略**：Top-k, Nucleus, Temperature sampling + +实现细节： +- Multi-loss：BCE + Focal + Label Smoothing 组合 +- Soft labels：从 72B 教师模型蒸馏，温度 T=2 +- 采样策略：推理时结合多种采样方法 +- 最终 MAP@3：~0.631 (Private), ~0.64 (Public) + +**8th Place - (匿名团队)** + +核心技巧： +- **多阶段检索系统**：粗检索 + 精检索两级架构 +- **Listwise reranking**：列表级排序优化 +- **Qwen2.5-32B 系列**：多个变体模型集成 +- **特征融合**：语义特征 + 统计特征融合 + +实现细节： +- 两级检索：第一级 BM25，第二级向量检索 +- Listwise：ListMLE 损失优化排序列表 +- 特征融合：TF-IDF + Embedding + 统计特征 +- 最终 MAP@3：~0.630 + +**9th (Private) / 7th (Public) - (匿名团队)** + +核心技巧： +- **QLoRA 微调**：参数高效微调 +- **多任务学习**：同时预测误解和选项正确性 +- **Qwen2.5-14B 架构**：效率优先 +- **集成学习**：多个微调模型集成 + +实现细节： +- QLoRA：在嵌入层和注意力层添加 LoRA +- 多任务：主任务误解预测，辅助任务选项正确性 +- 集成：5-7 个不同随机种子的 QLoRA 模型 +- 最终 MAP@3：~0.629 (Private), ~0.631 (Public) + +**10th Place - (匿名团队)** + +核心技巧： +- **合成数据生成**：LLM 生成额外训练数据 +- **知识蒸馏**：20B → 8B 模型蒸馏 +- **Qwen2.5-32B 教师 → Qwen2.5-8B 学生**：4:1 压缩 +- **集成融合**：教师 + 学生模型集成 + +实现细节： +- 合成数据：GPT-4 生成相似问题和误解配对 +- 蒸馏：教师软标签 + 学生硬标签联合训练 +- 集成：教师权重 0.7，学生权重 0.3 +- 最终 MAP@3：~0.628 + +--- + +### MAP - Charting Student Math Misunderstandings (2024) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/map-charting-student-math-misunderstandings) | [Case Study](https://the-learning-agency.com/the-cutting-ed/article/case-study-math-misconceptions-competition/) | [MiRAGE Paper](https://arxiv.org/html/2511.01182v1) +**Category:** NLP/LLM (教育 AI / 误解检测) +**Key Techniques:** +- **MiRAGE 框架**: Retrieval-guided Multi-stage Reasoning and Ensemble Fusion +- **Shared-prefix attention**: FlexAttention masks for suffix classification (1st Place) +- **Multi-loss training**: Soft labels + synthetic data (2nd Place) +- **Auxiliary tasks**: Correctness + reasoning error prediction (3rd Place) +- **CoT distillation**: 20B → 8B knowledge distillation +- **Ensemble fusion**: Weighted combination of retrieval + reranking +- **Label taxonomy**: 2,587 misconception types from Vanderbilt experts + +**Results:** Top score >0.948 MAP@3 (baseline 0.75), 1,850+ teams, 39,760+ entries + +**Note:** MAP 是 Eedi 竞赛的后续版本，扩展到完整的学生回答分析 + +#### 前排方案详细技术分析 + +**1st Place - Team MTH 101 (Raja Biswas) - MAP@3 >0.948** + +核心技巧： +- **Shared-prefix attention**：使用 FlexAttention masks 让每个 suffix 只关注共享前缀，避免候选标签之间的干扰 +- **Multi-stage reasoning pipeline**：检索 → CoT 推理 → 重排的三阶段框架 +- **Soft labels with multi-loss training**：结合硬标签和软标签减少标签模糊性的影响 +- **Large ranker ensemble**：72B + 32B ranker 模型集成 +- **Distractor prediction**：预测错误答案与误解的亲和度 + +实现细节： +- 使用 FlexAttention masks 实现共享前缀注意力机制 +- 每个 suffix 可以关注共享前缀（问题 + 回答 + 解释） +- 每个 suffix 之间相互独立，避免信息泄露 +- 使用每个 suffix 的最后一个 token 的特征进行分类 +- 最终 MAP@3 >0.948，获得 $20,000 奖金 + +**2nd Place - MAP@3 ~0.947** + +核心技巧： +- **Multi-loss training with soft labels**：使用软标签（soft labels）进行训练 +- **Synthetic data augmentation**：生成 80K 合成训练数据 +- **Ensemble of LLMs**：多个 LLM 的加权集成 +- **Auxiliary tasks**：同时训练多个辅助任务（正确性、推理错误类型） + +实现细节： +- 生成软标签：平均多个模型的预测 +- 多损失训练：结合 hard labels 和 soft labels +- 解决标签模糊性问题 +- 使用温度参数调整软标签分布 + +**3rd Place - monsaraida & Masaya - MAP@3 ~0.946** + +核心技巧： +- **Multi-stage inference**：分步骤处理复杂推理 +- **Auxiliary task training**：同时训练主任务和辅助任务 +- **Confidence-based routing**：基于置信度选择模型 +- **Large models on low-confidence samples**：对低置信度样本使用 72B 大模型 + +实现细节： +- 主任务：预测误解类型 +- 辅助任务 1：预测答案是否正确 +- 辅助任务 2：预测推理错误类型 +- 多任务学习提升整体性能 + +**6th Place - Manan Jhaveri - MAP@3 ~0.944** + +核心技巧： +- **Qwen-semble**：多个 Qwen 模型的集成 +- **Data-centric approach**：重视数据质量和处理 +- **Synthetic data generation**：LLM 生成额外训练数据 + +**8th Place - MAP@3 ~0.942** + +核心技巧： +- **Embedding + ensemble**：嵌入模型与 LLM 集成 +- **Deberta + Qwen**：结合不同架构的模型 + +**4th Place - (匿名团队) - MAP@3 ~0.945** + +核心技巧： +- **多阶段推理 pipeline**：检索 → 推理 → 验证三阶段 +- **集成多样性**：不同架构和大小的模型组合 +- **软标签融合**：从多个教师模型蒸馏软标签 +- **置信度阈值**：动态调整预测阈值 + +实现细节： +- 三阶段：BM25 检索 → LLM 推理 → 交叉验证 +- 集成：72B + 32B + 8B 模型组合 +- 软标签：温度 T=2.0 的教师蒸馏 +- 动态阈值：根据验证集最优阈值选择 + +**5th Place - (匿名团队) - MAP@3 ~0.944** + +核心技巧： +- **Cross-encoder 检索**：交叉编码器精确匹配 +- **Few-shot prompting**：少样本提示增强推理 +- **数据增强**：数学问题改写和变体生成 +- **知识蒸馏**：大模型 → 小模型压缩 + +实现细节： +- Cross-encoder：Question-Misconception 对联合编码 +- Few-shot：3-5 个示例的 in-context learning +- 数据增强：改写问题、交换选项顺序、生成变体 +- 蒸馏：72B → 14B 知识蒸馏 + +**7th Place - (匿名团队) - MAP@3 ~0.943** + +核心技巧： +- **混合检索系统**：稀疏 + 密集向量检索结合 +- **Learning to Rank**：学习排序模型优化检索 +- **领域适应**：从 Eedi 迁移学习到 MAP +- **主动学习**：选择最有价值的样本标注 + +实现细节： +- 混合检索：BM25（稀疏）+ DPR（密集） +- L2R：LambdaMART 或 RankNet 学习排序 +- 领域适应：Eedi 预训练权重初始化 +- 主动学习：不确定性采样选择标注样本 + +**9th Place - (匿名团队) - MAP@3 ~0.941** + +核心技巧： +- **检索增强生成 (RAG)**：检索相关示例作为上下文 +- **提示工程优化**：精心设计的提示模板 +- **多候选筛选**：生成多个候选，选择最优 +- **后处理规则**：基于约束规则的后处理 + +实现细节： +- RAG：检索 Top-10 相似问题作为上下文 +- 提示模板：包含问题、答案、示例的结构化提示 +- 多候选：生成 5-10 个候选，选择最高置信度 +- 后处理：误解层次关系、父子关系约束 + +**10th Place - (匿名团队) - MAP@3 ~0.940** + +核心技巧： +- **对比学习**：学习问题-误解的相似度表示 +- **难样本挖掘**：挖掘困难负样本提升模型 +- **集成策略**：多个检索器的集成 +- **查询扩展**：扩展查询提高召回率 + +实现细节： +- 对比学习：InfoNCE 损失学习嵌入表示 +- 难样本挖掘：选择与查询相似但不是正确误解的样本 +- 集成：多个检索器（DPR、ColBERT、ANCE）的投票 +- 查询扩展：使用同义词、上位词扩展查询 + +**11th-20th Place 总结** + +| 排名 | 核心技术 | 关键创新 | +|------|---------|---------| +| **11th** | 多模态特征 | 结合文本、数值、图像特征 | +| **12th** | 图神经网络 | 建模误解之间的关联 | +| **13th** | 集成学习 | Stacking 多层模型集成 | +| **14th** | 特征选择 | 自动选择最相关特征 | +| **15th** | 数据清洗 | 清洗低质量和噪声数据 | +| **16th** | 迁移学习 | 从通用 NLP 任务迁移 | +| **17th** | 元学习 | 少样本学习适应新误解 | +| **18th** | 自动提示 | 自动优化提示模板 | +| **19th** | 强化学习 | RL 优化预测策略 | +| **20th** | 神经架构搜索 | NAS 自动搜索最优架构 | + +**与 Eedi 的技术演进：** + +| 技术方面 | Eedi (2024年9月) | MAP (2024年) | +|---------|------------------|--------------| +| **任务** | 错误答案与误解的亲和度 | 学生解释中的误解 | +| **输入** | 问题 + 错误答案 | 问题 + 答案 + 解释 | +| **检索** | Embedding similarity | Embedding + CoT | +| **重排** | Pointwise/Listwise | Multi-stage reasoning | +| **数据增强** | Synthetic data (LLM生成) | Synthetic data (80K) | +| **核心创新** | Distractor prediction | Shared-prefix attention | + +**MiRAGE 框架详解：** +- **M**: Misconception detection（误解检测） +- **R**: Retrieval-guided（检索引导） +- **A**: Multi-stage reasoning（多阶段推理） +- **G**: Ensemble fusion（集成融合） +- **E**: Education（教育应用） + +**关键数据：** +- 标签空间：2,587 种误解类型 +- 数据来源：Eedi + NAEP 数学问题 +- 标注者：15 名受过培训的标注员 +- 学生群体：9-14 岁（4-8 年级） + +--- + +### ARC Prize 2025 (2025) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/arc-prize-2025) | [Official Analysis](https://arcprize.org/blog/arc-prize-2025-results-analysis) +**Category:** NLP/LLM (抽象推理/程序合成) +**Key Techniques:** +- **Refinement Loops**：递归优化是 2025 年的核心主题 +- **合成数据生成**：260,000 个合成任务从 3,000 个基础描述组合 +- **LLM 微调**：Qwen-4B 在合成数据上微调 +- **Tiny Recursive Model (TRM)**：7M 参数实现递归推理 +- **进化程序合成**：LLM 在搜索轨迹上微调 (SOAR) +- **Test-Time Training (TTT)**：在测试时训练 +- **Tokenizer 优化**：减少到 16 tokens (digits 0-9 + newline/padding) +- **数据增强**：几何变换 + 颜色排列 (factorial-10 × 8) + +**Results:** NVARC 24.03% (1st), TRM 45% on ARC-AGI-1, SOAR 52% on ARC-AGI-1 + +#### 前排方案详细技术分析 + +**1st Place - NVARC - 24.03% (ARC-AGI-2)** + +核心技巧： +- **合成数据生成**：从 3,000 基础描述生成 260,000 合成任务 +- **Qwen-4B 微调**：在合成数据上微调，而非预训练大模型 +- **Tokenizer 优化**：减少到 16 tokens（0-9 + newline/padding） +- **Refinement Loop**：递归优化改进预测 +- **数据增强**：几何变换（旋转、翻转）× 10! 颜色排列 + +实现细节： +- 基础数据：Human-ARC (1K+) + BARC (600) = ~1,600 原始任务 +- 合成策略：从 3,000 基础描述采样 2 个组合生成新任务 +- Qwen-4B：4B 参数，相比前沿模型小 1000 倍 +- 成本：~$0.20/task，远低于前沿模型的 $30-$60/task +- 最终成绩：24.03% (ARC-AGI-2), 54% (ARC-AGI-1 with refinement) + +**2nd Place - the ARChitects - 16.53%** + +核心技巧： +- **Masked-Diffusion LLM**：扩散模型用于程序合成 +- **Masked 语言建模**：自回归生成程序 +- **多阶段生成**：粗略想法 → 精细程序 +- **验证机制**：执行生成程序验证正确性 + +实现细节： +- Diffusion 模型：逐步去噪生成程序 +- Masked LM：类似 BERT 的掩码语言建模 +- 两阶段：先生成高级描述，再生成具体代码 +- 验证：在示例上执行生成程序 + +**3rd Place - MindsAI - 12.64%** + +核心技巧： +- **Test-Time Fine-Tuning (TTFT)**：在测试时微调每个任务 +- **Augmentation Ensemble**：数据增强集成（几何 + 颜色） +- **Tokenizer Dropout**：随机丢弃 token 增强鲁棒性 +- **Pretraining Tricks**：来自前沿模型的预训练技巧 + +实现细节： +- TTFT：每个任务单独训练 20-100 步 +- 增强：旋转（4 种）× 翻转（2 种）× 颜色排列（采样） +- Tokenizer Dropout：随机替换 token 为 [MASK] +- 增强级别：24-256 不同数据源不同增强 + +**Paper Awards (ARC-AGI-1):** + +**1st Paper Award - Tiny Recursive Model (TRM) - 45%** + +核心技巧： +- **递归推理**：16 次迭代改进答案 y +- **极小参数**：7M 参数，无预训练 +- **分别维护状态**：answer y 和 latent z 分开维护 +- **线性复杂度**：O(n) 优于 Transformer 的 O(n²) + +实现细节： +- 迭代：y 和 z 分别更新，y 更新一次，z 更新 3 次 +- 参数：7M，d_model=512, n_heads=8 +- 无预训练：随机初始化训练 +- 最终成绩：45% (ARC-AGI-1) + +**2nd Paper Award - SOAR (Self-Improving Language Models) - 52%** + +核心技巧： +- **进化程序合成**：进化搜索生成程序 +- **LLM 在轨迹上微调**：在搜索轨迹上微调 LLM +- **迭代改进**：每次迭代改进搜索策略 +- **知识迁移**：从搜索中学到的知识迁移 + +实现细节： +- 进化：遗传算法变异和交叉程序 +- 微调：在搜索轨迹上微调 LLM +- 迭代：多轮进化，每轮改进策略 +- 最终成绩：52% (ARC-AGI-1) + +**3rd Paper Award - CompressARC - 4% (ARC-AGI-2) / 20-34% (ARC-AGI-1)** + +核心技巧： +- **MDL 原理**：最小描述长度，无预训练 +- **VAE 框架**：编码器-解码器架构 +- **Decoder 正则化**：防止过拟合 +- **测试时训练**：每个任务单独训练 + +实现细节： +- 参数：仅 76K 参数 +- VAE：编码器 128 → 64 → 128，解码器镜像 +- 测试时训练：每个任务训练 ~20 分钟 +- 最终成绩：4% (ARC-AGI-2), 20-34% (ARC-AGI-1) + +### AIMO-2 (2025) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-2) | [Paper](https://arxiv.org/abs/2504.16891) +**Category:** NLP/LLM (数学推理) +**Key Techniques:** +- **MARIO 框架**: MAth Reasoning with code Interpreter +- **代码执行集成**: Python 代码在沙盒中执行 +- **OpenMathReasoning 数据集**: ~290K 高质量数学问题，3.2M CoT，1.7M TIR +- **三阶段训练**: CoT → TIR → GenSelect +- **GenSelect**: 多答案生成 + 基于排序的投票 +- **Qwen2.5 架构**: 1.5B/7B/14B/32B 模型家族 +- **自一致性 + TIR**: 32 候答案生成 + 多数投票 +- **AoPS 数据源**: 从 Art of Problem Solving 论坛提取 + +**Results:** NVIDIA (NemoSkills) 34/50 正确 (68%), OpenMath-Nemotron-32B 达到 SOTA + +--- + +## Competition Brief (竞赛简介) + +### AIMO-2 - AI Mathematical Olympiad Progress Prize 2 + +**竞赛背景：** +- **主办方**：AIMO (AI Mathematical Olympiad) +- **目标**：解决国家奥林匹克级数学问题 +- **特殊性质**：测试 AI 的**数学推理能力**，不是传统 NLP 任务 + +**竞赛规模：** +- **问题数量**: 50 道国家奥林匹克级数学问题 +- **时间限制**: 5 小时解决所有问题 +- **总队伍数**: 约 100+ teams +- **奖项池**: >$2,000,000 + +**任务格式：** +``` +数学问题文本 + ↓ +生成解决方案（推理 + 代码） + ↓ +执行代码（如有） + ↓ +提取最终答案 +``` + +**评估指标：** +- **准确率**: 完全正确才算对（34/50 = 68%） +- **答案格式**: 多选题（A-E）或数值答案 +- **时间限制**: 5 小时，平均每题 6 分钟 + +**关键洞察：** +1. **代码执行是关键**: 纯 LLM 推理不够，需要代码执行进行计算 +2. **数据质量 > 数量**: 从 AoPS 提取的高质量数据 +3. **三阶段训练有效**: CoT → TIR → GenSelect +4. **小模型可以很强**: 1.5B 模型达到有竞争力的性能 +5. **自一致性 + 排序投票**: 比简单多数投票更有效 + +**前排方案总结（Top 12+）：** + +| 排名 | 队伍 | 正确数 | 核心技术 | 模型 | 推理引擎 | +|------|------|--------|---------|------|---------| +| **1st** | NVIDIA (NemoSkills) | 34/50 | MARIO, TIR, GenSelect, OpenMathReasoning | Qwen2.5-14B | TensorRT-LLM | +| **2nd** | imagination-research | ~30/50 | SFT + DPO (长度优化), 代码执行 | DeepSeek-R1-Distill-Qwen-14B | lmdeploy | +| **3rd** | Aliev | ~29/50 | Self-consistency, Early stopping | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **4th** | Soren Ravn Andersen | ~28/50 | AWQ 量化, Self-consistency | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **5th** | usernam | ~27/50 | lmdeploy 高吞吐量 | DeepSeek-R1-Distill-Qwen-14B AWQ | lmdeploy | +| **7th** | tascj | ~26/50 | AWQ 量化 | DeepSeek-R1-Distill-Qwen-14B AWQ | lmdeploy | +| **8th** | MPWARE | ~25/50 | 自定义 AWQ 量化, Self-consistency | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **9th** | Fast-Math-R1–14B | ~24/50 | SFT + GRPO (效率优化) | Fine-tuned DeepSeek-R1-Distill-Qwen-14B | - | +| **11th** | farsail | ~22/50 | One-shot prompting, 自定义 vLLM | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **17th** | ippeiogawa | ~18/50 | Multi-stage prompting, 代码生成 | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **20th** | Arek Paterek | ~15/50 | AWQ 量化 | DeepSeek-R1-Distill-Qwen-32B AWQ | - | +| **22nd** | K-Piece | ~13/50 | Base model + prompting | DeepSeek-R1 系列 | - | + +**技术趋势分析：** + +1. **模型选择**：几乎所有前排方案都使用 `DeepSeek-R1-Distill-Qwen-14B AWQ`（4-bit 量化） +2. **微调方法**： + - **SFT**：几乎所有队伍的基础起点 + - **DPO**：第 2 名用于减少输出长度 + - **TIR**：第 1 名的核心创新（工具集成推理） + - **GRPO**：第 9 名尝试用于效率优化（结果不稳定） +3. **推理引擎**： + - **vLLM**：最常用（4th, 7th, 8th, 11th, 17th） + - **lmdeploy**：高吞吐量选择（2nd, 5th, 7th） + - **TensorRT-LLM**：第 1 名专用 +4. **推理策略**： + - **Self-consistency/Majority voting**：通用标配 + - **Early stopping**：节省时间和 tokens + - **代码执行**：提升计算精度 + +**核心创新 - MARIO 框架（1st Place）：** +- **MA**: Math（数学推理） +- **RI**: Reasoning（推理）+ Interpreter（代码解释器） +- **O**: Open（开源） + +**数据集规模：** +- OpenMathReasoning: ~290K 问题 +- 3.2M CoT（长思维链） +- 1.7M TIR（工具集成推理） + +#### 前排方案详细技术分析 + +**1st Place - NVIDIA (NemoSkills) - 34/50 (68%)** + +核心技巧： +- **MARIO 框架**：Math + Reasoning + Interpreter 整合 +- **OpenMathReasoning 数据集**：从 AoPS 提取的 ~290K 高质量数据 +- **三阶段训练**：CoT → TIR → GenSelect 逐步训练 +- **代码执行集成**：Python 代码在沙盒中执行 +- **GenSelect 策略**：32 候选答案 + 基于排序的投票 + +实现细节： +- Qwen2.5-14B 主模型，TensorRT-LLM 推理优化 +- CoT：长思维链推理，提取推理过程 +- TIR：生成推理 + Python 代码，代码执行验证结果 +- GenSelect：32 候选答案，基于推理质量排序选择 +- 数据：3.2M CoT + 1.7M TIR 格式 +- 最终成绩：34/50 正确（68%） + +**2nd Place - imagination-research - ~30/50 (60%)** + +核心技巧： +- **SFT + DPO 组合**：监督微调 + 直接偏好优化 +- **DPO 长度优化**：第 2 阶段减少输出长度，提升效率 +- **代码执行集成**：Python 代码生成和执行 +- **DeepSeek-R1-Distill-Qwen-14B AWQ**：4-bit 量化模型 + +实现细节： +- SFT：OpenR1 Math + Light-R1 数据集监督微调 +- DPO：第 2 阶段训练，优化输出长度和推理质量 +- 量化：AWQ 4-bit 量化，降低内存占用 +- 推理引擎：lmdeploy 高吞吐量推理 +- 最终成绩：~30/50 正确 + +**3rd Place - Aliev - ~29/50 (58%)** + +核心技巧： +- **Self-consistency**：自洽性，生成多个解取最频繁答案 +- **Early stopping**：提前停止节省推理时间 +- **DeepSeek-R1-Distill-Qwen-14B AWQ**：4-bit 量化 +- **vLLM 推理引擎**：高效推理框架 + +实现细节： +- Self-consistency：生成多个候选答案，多数投票 +- Early stopping：前 5 个候选中出现 4 个相同则停止 +- vLLM：PagedAttention 高效内存管理 +- 量化：AWQ Activation-aware Weight Quantization +- 最终成绩：~29/50 正确 + +**4th Place - Soren Ravn Andersen - ~28/50 (56%)** + +核心技巧： +- **AWQ 量化**：Activation-aware Weight Quantization +- **Self-consistency**：多候选答案生成 +- **vLLM 推理引擎**：PagedAttention 优化 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- AWQ：识别关键权重，保护重要权重，量化其他 +- Self-consistency：标准多数投票策略 +- vLLM：PagedAttention 减少 KV Cache 内存占用 +- 最终成绩：~28/50 正确 + +**5th Place - usernam - ~27/50 (54%)** + +核心技巧： +- **lmdeploy 高吞吐量**：高吞吐量推理框架 +- **DeepSeek-R1-Distill-Qwen-14B AWQ**：4-bit 量化 +- **Batch 推理优化**：大 batch 推理提升吞吐 + +实现细节： +- lmdeploy：连续批处理优化 +- 量化：AWQ 4-bit，减少内存和计算 +- Batch size：根据 GPU 内存动态调整 +- 最终成绩：~27/50 正确 + +**7th Place - tascj - ~26/50 (52%)** + +核心技巧： +- **AWQ 量化**：4-bit 量化优化 +- **lmdeploy 推理**：高吞吐量推理 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- AWQ：自定义量化配置 +- lmdeploy：高吞吐量，多 GPU 并行 +- 最终成绩：~26/50 正确 + +**8th Place - MPWARE - ~25/50 (50%)** + +核心技巧： +- **自定义 AWQ 量化**：自定义量化策略 +- **Self-consistency**：多候选投票 +- **vLLM 推理引擎** + +实现细节： +- 自定义 AWQ：根据模型特性定制量化 +- vLLM：PagedAttention 内存优化 +- 最终成绩：~25/50 正确 + +**9th Place - Fast-Math-R1–14B - ~24/50 (48%)** + +核心技巧： +- **SFT + GRPO**：监督微调 + Group Relative Policy Optimization +- **GRPO 效率优化**：减少推理步数，提升效率（结果不稳定） +- **Fine-tuned DeepSeek-R1-Distill-Qwen-14B**：微调模型 + +实现细节： +- SFT：OpenR1 Math 数据集微调 +- GRPO：优化推理步骤数，减少 tokens +- 不稳定性：优化到一定程度后"灾难性偏移" +- 使用早期 checkpoint 获得最佳结果 +- 最终成绩：~24/50 正确 + +**11th Place - farsail - ~22/50 (44%)** + +核心技巧： +- **One-shot prompting**：单样本提示，无需微调 +- **自定义 vLLM**：自定义推理引擎配置 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- One-shot：提供 1-2 个示例作为提示 +- 自定义 vLLM：优化 PagedAttention 参数 +- 最终成绩：~22/50 正确 + +**17th Place - ippeiogawa - ~18/50 (36%)** + +核心技巧： +- **Multi-stage prompting**：多阶段提示策略 +- **代码生成**：强制生成 Python 代码 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- Multi-stage：分解问题，逐步生成代码 +- 代码生成：要求模型生成可执行代码 +- vLLM：高效推理引擎 +- 最终成绩：~18/50 正确 + +**20th Place - Arek Paterek - ~15/50 (30%)** + +核心技巧： +- **AWQ 量化**：4-bit 量化 +- **DeepSeek-R1-Distill-Qwen-32B AWQ**：32B 大模型量化 +- **Base model + prompting**：基础模型 + 提示工程 + +实现细节： +- 32B 模型：更大模型，更多知识 +- AWQ 量化：4-bit 量化降低内存 +- 无微调：直接使用提示 +- 最终成绩：~15/50 正确 + +**22nd Place - K-Piece - ~13/50 (26%)** + +核心技巧： +- **Base model + prompting**：基础模型 + 提示工程 +- **DeepSeek-R1 系列**：使用不同大小的 DeepSeek-R1 +- **Self-consistency**：多候选投票 + +实现细节： +- 提示工程：精心设计的提示模板 +- DeepSeek-R1：14B, 32B 等不同变体 +- Self-consistency：生成 5-10 个候选答案 +- 最终成绩：~13/50 正确 + +**技术总结：** + +| 技术维度 | 关键发现 | +|---------|---------| +| **模型选择** | DeepSeek-R1-Distill-Qwen-14B AWQ 是最受欢迎 | +| **微调方法** | SFT（基础）+ DPO（长度优化）+ TIR（工具集成） | +| **推理引擎** | vLLM（通用）
    lmdeploy（高吞吐）
    TensorRT-LLM（第 1 名专用） | +| **推理策略** | Self-consistency（标配）
    Early stopping（节省时间）
    代码执行（提升精度） | +| **核心创新** | MARIO 框架：Math + Reasoning + Interpreter | + +--- + +### MAP - Charting Student Math Misunderstandings + +**竞赛背景：** +- **主办方**：The Learning Agency + Eedi + Vanderbilt University +- **目标**：预测学生数学回答中的误解（Misconception） +- **特殊性质**：测试 AI 的**教育诊断能力**，帮助教师识别学生的错误思维模式 + +**竞赛演变：** +- **Eedi (2024年9月)**: "Mining Misconceptions in Mathematics" - 第一个竞赛，预测错误答案与误解的亲和度 +- **MAP (2024年)**: "Charting Student Math Misunderstandings" - 第二个竞赛，扩展到完整的学生回答分析 +- **相同获胜者**: Team MTH 101 (Raja Biswas) 赢得了两个竞赛 + +**竞赛规模（MAP）：** +- **数据来源**：Eedi + NAEP 数学问题 +- **标注者**：15 名受过培训的标注员（有数学辅导经验） +- **学生群体**：9-14 岁（4-8 年级） +- **总队伍数**：1,850+ teams +- **总提交数**：39,760+ entries +- **奖项池**：$55,000（第 1 名 $20,000） + +**任务格式对比：** + +| 竞赛 | 任务 | 输入 | 输出 | +|------|------|------|------| +| **Eedi** | 预测错误答案与误解的亲和度 | 问题 + 错误答案 | 误解类型 | +| **MAP** | 预测学生解释中的误解 | 问题 + 答案 + 解释 | Top 25 误解预测 | + +**任务格式：** +``` +[问题文本 + 学生选择答案 + 学生解释] + ↓ +预测误解类型（Top 25 预测） + ↓ +MAP@3 评估（前 3 个预测） +``` + +**评估指标：** +- **MAP@3**: Mean Average Precision at 3 + - 第 1 次预测正确：1.0 分 + - 第 2 次预测正确：0.5 分 + - 第 3 次预测正确：0.33 分 + - 未预测正确：0 分 +- **标签空间**：2,587 种误解类型 + +**关键洞察：** +1. **误解 vs 错误**：误解是系统性的、持续的，需要针对性干预 +2. **标签层次**：正确性 → 解释质量 → 误解类型 +3. **噪声标签**：多种子验证是处理噪声的关键 +4. **检索+重排**：先用 embedding 检索，再用 CoT 推理重排 +5. **集成融合**：加权融合多个模块提升鲁棒性 + +**前排方案总结（MAP Top 10+）：** + +| 排名 | 团队 | MAP@3 | 核心技术 | 模型 | +|------|------|-------|---------|------| +| **1st** | Team MTH 101 | >0.948 | Shared-prefix attention, FlexAttention | 72B ranker + 32B ranker | +| **2nd** | - | ~0.947 | Multi-loss training, soft labels, 80K synthetic | Ensemble of LLMs | +| **3rd** | monsaraida & Masaya | ~0.946 | Auxiliary tasks, multi-stage inference | 72B models on low-confidence | +| **6th** | Manan Jhaveri | ~0.944 | Qwen-semble, data-centric | Qwen ensemble | +| **8th** | - | ~0.942 | Embedding + ensemble | Deberta + Qwen | +| **15th** | - | ~0.938 | Embedding models, semantic grouping | Manual inspection | + +--- + +**前排方案总结（Eedi Top 12）：** + +| 排名 | 团队 | MAP@25 | 核心技术 | 模型 | +|------|------|--------|---------|------| +| **1st** | Team MTH 101 | ~0.637 | Co-occurrence stats, Claude 3.5 Sonnet context | 72B + 32B ranker | +| **2nd** | Kazuhito Yonekawa et al. | ~0.636 | Multi-stage retrieve-and-rank | Qwen2.5-72B | +| **3rd** | waseda-pochi | ~0.635 | Magic boost post-processing, unknown misconception correction | Qwen2.5-32B | +| **4th** | - | ~0.634 | CoT features, grouped synthetic data | Qwen2.5-32B | +| **5th** | ebi-ktr | ~0.633 | Bi-encoder, listwise reranking | Qwen2.5-32B | +| **6th** | - | ~0.632 | QLoRA fine-tuning, ensemble | Qwen2.5-14B | +| **7th (Private) / 2nd (Public)** | terekaerumasahmet | ~0.631 | Multi-loss, soft labels | Qwen2.5-32B | +| **8th** | - | ~0.630 | Multi-stage retrieval, listwise reranking | Qwen2.5-32B | +| **9th (Private) / 7th (Public)** | - | ~0.629 | QLoRA fine-tuning | Qwen2.5-14B | +| **10th** | - | ~0.628 | Synthetic data, knowledge distillation | Qwen2.5-32B | + +**Eedi vs MAP 技术对比：** + +| 技术方面 | Eedi (2024年9月) | MAP (2024年) | +|---------|------------------|--------------| +| **任务** | 错误答案与误解的亲和度 | 学生解释中的误解 | +| **输入** | 问题 + 错误答案 | 问题 + 答案 + 解释 | +| **输出** | Top 25 误解预测 | Top 25 误解预测 | +| **检索** | Embedding similarity | Embedding + CoT | +| **重排** | Pointwise/Listwise | Multi-stage reasoning | +| **数据增强** | Synthetic data (LLM生成) | Synthetic data (80K) | +| **后处理** | Unknown misconception correction | - | + +**核心创新 - MiRAGE 框架：** +- **M**: Misconception detection（误解检测） +- **R**: Retrieval-guided（检索引导） +- **A**: Multi-stage reasoning（多阶段推理） +- **G**: Ensemble fusion（集成融合） +- **E**: Education（教育应用） + +--- + +### ARC Prize 2025 - Abstraction and Reasoning Corpus + +**竞赛背景：** +- **主办方**：ARC Prize Organization (François Chollet, Mike Knoop) +- **目标**：测试 AI 的**抽象推理和泛化能力**，这是 AGI 的核心基准 +- **竞赛主题**：Year of the Refinement Loop（优化循环之年） +- **特殊性质**：不是传统 ML 竞赛，而是**推理能力基准测试** + +**数据集规模：** +- **ARC-AGI-1**: 800 tasks (400 training + 400 evaluation) +- **ARC-AGI-2**: 训练与 ARC-AGI-1 重叠，评估是新的难题 +- **总队伍数**：1,455 teams +- **总提交数**：15,154 entries + +**任务格式：** +``` +输入网格 (训练示例 1-10 对) + ↓ +推断变换规则 + ↓ +应用规则到测试输入 + ↓ +输出网格 +``` + +**评估指标：** +- **准确率**: 完全正确的任务占比（部分正确 = 0 分） +- **成本**: $/task（获胜方案约 $0.20/task，前沿模型 $2-$30/task） +- **泛化能力**: Public/Private 分离，Private 才是真实泛化 + +**关键洞察：** +1. **AI 推理系统**: 2025 年诞生了 AI 推理系统，与 LLM 的发明同等重要 +2. **Refinement = Intelligence**: 优化循环是智能的核心 +3. **知识 vs 推理**: 当前 AI 推理能力受限于模型知识 +4. **Overfitting on Knowledge**: 前沿模型可能"过拟合"了 ARC 数据 + +**前排方案总结：** + +| 排名 | 队伍 | 分数 | 关键技术 | +|------|------|------|---------| +| **1st** | NVARC | 24.03% | 合成数据 + Qwen-4B + TRM | +| **2nd** | the ARChitects | 16.53% | Masked-Diffusion LLM | +| **3rd** | MindsAI | 12.64% | TTFT + Augmentation | + +**Paper Awards:** + +| 排名 | 作者 | 标题 | 成绩 | +|------|------|------|------| +| **1st** | Alexia Jolicoeur-Martineau | Tiny Recursive Model (TRM) | 45% (ARC-AGI-1) | +| **2nd** | Julien Pourcel et al. | SOAR (进化程序合成) | 52% (ARC-AGI-1) | +| **3rd** | Isaac Liao | CompressARC (76K 参数) | 20-34% (ARC-AGI-1) | + +--- + +## Code Templates + +### MiRAGE Framework - 检索引导的多阶段推理 + +**关键洞察：** 通过检索 + 推理 + 重排的三阶段框架，实现高效的误解检测 + +```python +import torch +import torch.nn as nn +from typing import List, Tuple, Dict +import numpy as np + +class MiRAGEFramework: + """ + MiRAGE: Misconception detection with Retrieval-guided + Multi-stage reasoning and Ensemble fusion + + 基于论文: https://arxiv.org/html/2511.01182v1 + + 核心思想： + 1. Retrieval module: 嵌入模型检索语义相似的候选标签 + 2. Reasoning module: CoT 推理生成结构化解释 + 3. Reranking module: 基于推理结果重排候选标签 + 4. Ensemble fusion: 加权融合检索和重排分数 + """ + + def __init__(self, + embedder: nn.Module, + reasoner: nn.Module, + reranker: nn.Module, + alpha: float = 0.7, + beta: float = 0.3, + top_k: int = 25): + """ + Args: + embedder: 嵌入模型（如 MathBERT） + reasoner: 推理模型（如 Qwen3-8B） + reranker: 重排模型（如 Qwen3-7B） + alpha: 重排分数权重 + beta: 检索分数权重 + top_k: 检索候选数量 + """ + self.embedder = embedder + self.reasoner = reasoner + self.reranker = reranker + self.alpha = alpha + self.beta = beta + self.top_k = top_k + + # 缓存数据库嵌入 + self.embed_db = None + self.label_db = None + + def build_embedding_index(self, dataset: List[Dict]): + """ + 构建嵌入索引 + + Args: + dataset: [{"question": str, "answer": str, "explanation": str, "label": str}, ...] + """ + embeddings = [] + labels = [] + + for item in dataset: + # 生成三元组嵌入 + emb = self.embedder.encode( + item["question"], + item["answer"], + item["explanation"] + ) + embeddings.append(emb) + labels.append(item["label"]) + + self.embed_db = torch.stack(embeddings) + self.label_db = labels + + def retrieval_module(self, query: Tuple[str, str, str]) -> List[Tuple[str, float]]: + """ + 检索模块：基于语义相似度检索候选标签 + + Args: + query: (question, answer, explanation) + + Returns: + [(label, score), ...] 按相似度排序 + """ + q, a, e = query + query_emb = self.embedder.encode(q, a, e) + + # 计算与所有数据库条目的相似度 + similarities = torch.matmul(self.embed_db, query_emb) + + # 按标签聚合（取最大相似度） + label_scores = {} + for label, sim in zip(self.label_db, similarities): + if label not in label_scores: + label_scores[label] = sim + else: + label_scores[label] = max(label_scores[label], sim) + + # 排序并返回 top-k + sorted_labels = sorted(label_scores.items(), key=lambda x: x[1], reverse=True) + return sorted_labels[:self.top_k] + + def reasoning_module(self, query: Tuple[str, str, str]) -> str: + """ + 推理模块：生成 CoT 推理链 + + Args: + query: (question, answer, explanation) + + Returns: + reasoning: 结构化推理文本 + """ + q, a, e = query + prompt = f""" +Analyze the following student response to a math problem. + +Question: {q} +Student Answer: {a} +Student Explanation: {e} + +Think step by step: +1. Is the answer correct? +2. Does the explanation contain any misconceptions? +3. If so, what type of misconception is it? + +Provide your reasoning: +""" + reasoning = self.reasoner.generate(prompt) + return reasoning + + def reranking_module(self, + query: Tuple[str, str, str], + reasoning: str, + candidates: List[str]) -> List[Tuple[str, float]]: + """ + 重排模块：基于推理结果重排候选标签 + + Args: + query: (question, answer, explanation) + reasoning: CoT 推理 + candidates: 候选标签列表 + + Returns: + [(label, score), ...] 重排后的标签 + """ + q, a, e = query + reranked_scores = [] + + for label in candidates: + prompt = f""" +Question: {q} +Student Answer: {a} +Student Explanation: {e} + +Reasoning: {reasoning} + +Is the misconception "{label}" consistent with the above analysis? +Answer Yes or No: +""" + # 获取模型输出的 logits + logits = self.reranker.get_logits(prompt) + + # 计算 Yes/No 的 logit 差值 + yes_logit = logits["Yes"] + no_logit = logits["No"] + score = yes_logit - no_logit + + reranked_scores.append((label, score.item())) + + # 按分数排序 + reranked_scores.sort(key=lambda x: x[1], reverse=True) + return reranked_scores + + def ensemble_fusion(self, + retrieval_scores: List[Tuple[str, float]], + rerank_scores: List[Tuple[str, float]]) -> List[Tuple[str, float]]: + """ + 集成融合：加权融合检索和重排分数 + + Args: + retrieval_scores: [(label, retrieval_score), ...] + rerank_scores: [(label, rerank_score), ...] + + Returns: + [(label, fused_score), ...] + """ + # 归一化分数 + retrieval_dict = dict(retrieval_scores) + rerank_dict = dict(rerank_scores) + + all_labels = set(retrieval_dict.keys()) | set(rerank_dict.keys()) + + fused_scores = [] + for label in all_labels: + ret_score = retrieval_dict.get(label, 0) + rerank_score = rerank_dict.get(label, 0) + + # 加权融合 + fused = self.alpha * rerank_score + self.beta * ret_score + fused_scores.append((label, fused)) + + # 排序 + fused_scores.sort(key=lambda x: x[1], reverse=True) + return fused_scores + + def predict(self, query: Tuple[str, str, str]) -> List[Tuple[str, float]]: + """ + 完整预测流程 + + Args: + query: (question, answer, explanation) + + Returns: + [(label, score), ...] 最终预测结果 + """ + # Stage 1: Retrieval + retrieval_results = self.retrieval_module(query) + candidates = [label for label, _ in retrieval_results] + + # Stage 2: Reasoning + reasoning = self.reasoning_module(query) + + # Stage 3: Reranking + rerank_results = self.reranking_module(query, reasoning, candidates) + + # Stage 4: Ensemble fusion + final_results = self.ensemble_fusion(retrieval_results, rerank_results) + + return final_results + + +# 使用示例 +if __name__ == "__main__": + # 假设我们有预训练的模型 + embedder = MathBERTEmbedder() + reasoner = QwenReasoner() + reranker = QwenReranker() + + # 创建 MiRAGE 框架 + miracle = MiRAGEFramework( + embedder=embedder, + reasoner=reasoner, + reranker=reranker, + alpha=0.7, + beta=0.3, + top_k=25 + ) + + # 构建索引 + train_data = load_training_data() + miracle.build_embedding_index(train_data) + + # 预测 + query = ( + "What is 2/3 + 1/6?", + "3/4", + "I added the numerators and denominators: 2+1=3, 3+6=9, so 3/9=1/3. Wait, that's wrong..." + ) + + predictions = miracle.predict(query) + print("Top 3 predictions:") + for label, score in predictions[:3]: + print(f"{label}: {score:.4f}") +``` + +### Shared-Prefix Attention (1st Place) + +**关键洞察：** 将每个标签候选编码为输入 token，使用 FlexAttention masks 让每个 suffix 只关注共享前缀 + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SharedPrefixClassifier(nn.Module): + """ + Shared-Prefix Attention Classifier + MAP Competition 1st Place Solution + + 核心思想： + 1. 将任务重新定义为 suffix classification + 2. 每个标签候选被编码为一个输入 token + 3. 所有候选标签拼接成一个字符串 + 4. 使用 FlexAttention masks 让每个 suffix 只关注共享前缀 + 5. 使用每个 suffix 的最后一个 token 的特征进行分类 + """ + + def __init__(self, model_name: str, num_labels: int): + super().__init__() + self.num_labels = num_labels + + # 加载预训练模型 + from transformers import AutoModel, AutoTokenizer + self.model = AutoModel.from_pretrained(model_name) + self.tokenizer = AutoTokenizer.from_pretrained(model_name) + + # 分类头 + hidden_size = self.model.config.hidden_size + self.classifier = nn.Linear(hidden_size, num_labels) + + def create_flex_attention_mask(self, + prefix_len: int, + suffix_len: int, + num_candidates: int) -> torch.Tensor: + """ + 创建 FlexAttention mask + + 每个 suffix 只能关注共享前缀，不能关注其他 suffix + + Args: + prefix_len: 前缀长度（问题 + 回答） + suffix_len: 每个 suffix 长度 + num_candidates: 候选数量 + + Returns: + attention_mask: [batch, seq_len, seq_len] + """ + total_len = prefix_len + suffix_len * num_candidates + device = self.model.device + + mask = torch.zeros(total_len, total_len, device=device) + + # 前缀可以关注前缀 + mask[:prefix_len, :prefix_len] = 1 + + # 每个 suffix 可以关注前缀 + for i in range(num_candidates): + start = prefix_len + i * suffix_len + end = start + suffix_len + mask[start:end, :prefix_len] = 1 + + return mask.unsqueeze(0) # [1, seq_len, seq_len] + + def forward(self, + question: str, + answer: str, + explanation: str, + candidate_labels: List[str]) -> torch.Tensor: + """ + Forward pass + + Args: + question: 问题文本 + answer: 学生选择的答案 + explanation: 学生的解释 + candidate_labels: 候选误解标签列表 + + Returns: + logits: [batch, num_labels] + """ + # 构建输入 + prefix = f"Question: {question}\nAnswer: {answer}\nExplanation: {explanation}\n\n" + + # 拼接所有候选标签 + suffixes = [] + for label in candidate_labels: + suffixes.append(f"Misconception: {label}") + + # 构建完整输入 + full_text = prefix + "".join(suffixes) + inputs = self.tokenizer(full_text, return_tensors="pt") + input_ids = inputs["input_ids"].to(self.model.device) + + # 计算 prefix 和 suffix 长度 + prefix_len = len(self.tokenizer(prefix)["input_ids"]) + suffix_len = len(self.tokenizer(suffixes[0])["input_ids"]) + + # 创建 attention mask + attention_mask = self.create_flex_attention_mask( + prefix_len, suffix_len, len(candidate_labels) + ) + + # 获取模型输出 + outputs = self.model( + input_ids=input_ids, + attention_mask=attention_mask + ) + hidden_states = outputs.last_hidden_state # [batch, seq_len, hidden] + + # 提取每个 suffix 的最后一个 token + suffix_last_tokens = [] + for i in range(len(candidate_labels)): + pos = prefix_len + (i + 1) * suffix_len - 1 + suffix_last_tokens.append(hidden_states[:, pos, :]) + + # 堆叠所有 suffix 特征 + suffix_features = torch.stack(suffix_last_tokens, dim=1) # [batch, num_labels, hidden] + + # 分类 + logits = self.classifier(suffix_features) # [batch, num_labels, num_labels] + + # 取对角线（每个 candidate 对应自己的 logit） + batch_size = logits.size(0) + logits = logits[range(batch_size), range(len(candidate_labels)), :] + + return logits + + +# 使用示例 +if __name__ == "__main__": + classifier = SharedPrefixClassifier("microsoft/deberta-v3-large", num_labels=2587) + + question = "What is 2/3 + 1/6?" + answer = "3/4" + explanation = "I added the numerators and denominators." + + # 候选标签（从检索模块获得） + candidates = [ + "Adds denominators when adding fractions", + "Incorrectly adds numerators and denominators", + "Misunderstands fraction addition", + # ... more candidates + ] + + logits = classifier(question, answer, explanation, candidates) + probs = F.softmax(logits, dim=-1) + + # Top-3 预测 + top3_probs, top3_indices = torch.topk(probs, 3) + for prob, idx in zip(top3_probs[0], top3_indices[0]): + print(f"{candidates[idx]}: {prob:.4f}") +``` + +### Multi-Loss Training with Soft Labels (2nd Place) + +**关键洞察：** 使用软标签（soft labels）进行训练，减少标签模糊性的影响 + +```python +import torch +import torch.nn as nn +from typing import List, Dict + +class MultiLossTrainer: + """ + Multi-Loss Training with Soft Labels + MAP Competition 2nd Place Solution + + 核心思想： + 1. 生成软标签：平均多个模型的预测 + 2. 多损失训练：结合 hard labels 和 soft labels + 3. 解决标签模糊性问题 + """ + + def __init__(self, model: nn.Module, num_labels: int): + self.model = model + self.num_labels = num_labels + + # 损失函数 + self.ce_loss = nn.CrossEntropyLoss() + self.kl_loss = nn.KLDivLoss(reduction="batchmean") + + def generate_soft_labels(self, + models: List[nn.Module], + dataloader: torch.utils.data.DataLoader, + device: str) -> torch.Tensor: + """ + 生成软标签 + + Args: + models: 用于生成软标签的模型列表 + dataloader: 数据加载器 + device: 设备 + + Returns: + soft_labels: [num_samples, num_labels] + """ + all_soft_labels = [] + + for batch in dataloader: + input_ids = batch["input_ids"].to(device) + attention_mask = batch["attention_mask"].to(device) + + # 收集所有模型的预测 + all_probs = [] + for model in models: + with torch.no_grad(): + outputs = model(input_ids, attention_mask=attention_mask) + probs = torch.softmax(outputs.logits, dim=-1) + all_probs.append(probs) + + # 平均所有模型的预测 + soft_labels = torch.stack(all_probs).mean(dim=0) + all_soft_labels.append(soft_labels.cpu()) + + return torch.cat(all_soft_labels, dim=0) + + def compute_loss(self, + logits: torch.Tensor, + hard_labels: torch.Tensor, + soft_labels: torch.Tensor, + alpha: float = 0.5, + temperature: float = 2.0) -> torch.Tensor: + """ + 计算多损失 + + Args: + logits: 模型输出 [batch, num_labels] + hard_labels: 真实标签 [batch] + soft_labels: 软标签 [batch, num_labels] + alpha: hard loss 权重 + temperature: soft label 温度 + + Returns: + loss: 总损失 + """ + # Hard loss (交叉熵) + hard_loss = self.ce_loss(logits, hard_labels) + + # Soft loss (KL 散度) + log_probs = torch.log_softmax(logits / temperature, dim=-1) + soft_labels_smooth = soft_labels / temperature + soft_loss = self.kl_loss(log_probs, soft_labels_smooth) * (temperature ** 2) + + # 组合损失 + total_loss = alpha * hard_loss + (1 - alpha) * soft_loss + + return total_loss + + def train_epoch(self, + train_loader: torch.utils.data.DataLoader, + soft_labels: torch.Tensor, + optimizer: torch.optim.Optimizer, + device: str): + """ + 训练一个 epoch + + Args: + train_loader: 训练数据加载器 + soft_labels: 预生成的软标签 + optimizer: 优化器 + device: 设备 + """ + self.model.train() + total_loss = 0 + + for batch_idx, batch in enumerate(train_loader): + input_ids = batch["input_ids"].to(device) + attention_mask = batch["attention_mask"].to(device) + hard_labels = batch["labels"].to(device) + + # 获取对应的软标签 + start_idx = batch_idx * train_loader.batch_size + end_idx = start_idx + len(hard_labels) + batch_soft_labels = soft_labels[start_idx:end_idx].to(device) + + # Forward + outputs = self.model(input_ids, attention_mask=attention_mask) + logits = outputs.logits + + # 计算损失 + loss = self.compute_loss(logits, hard_labels, batch_soft_labels) + + # Backward + optimizer.zero_grad() + loss.backward() + optimizer.step() + + total_loss += loss.item() + + return total_loss / len(train_loader) + + +# 使用示例 +if __name__ == "__main__": + from transformers import AutoModelForSequenceClassification + + # 创建模型 + model = AutoModelForSequenceClassification.from_pretrained( + "microsoft/deberta-v3-large", + num_labels=2587 + ) + + # 创建训练器 + trainer = MultiLossTrainer(model, num_labels=2587) + + # 生成软标签（使用多个预训练模型） + teacher_models = [ + AutoModelForSequenceClassification.from_pretrained("teacher1"), + AutoModelForSequenceClassification.from_pretrained("teacher2"), + AutoModelForSequenceClassification.from_pretrained("teacher3"), + ] + + soft_labels = trainer.generate_soft_labels(teacher_models, train_loader, "cuda") + + # 训练 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-5) + for epoch in range(3): + loss = trainer.train_epoch(train_loader, soft_labels, optimizer, "cuda") + print(f"Epoch {epoch}, Loss: {loss:.4f}") +``` + +### Auxiliary Task Training (3rd Place) + +**关键洞察：** 同时训练多个辅助任务（正确性、推理错误类型），提升主任务性能 + +```python +import torch +import torch.nn as nn +from typing import Dict, Tuple + +class AuxiliaryTaskModel(nn.Module): + """ + Auxiliary Task Model + MAP Competition 3rd Place Solution + + 核心思想： + 1. 主任务：预测误解类型 + 2. 辅助任务 1：预测答案是否正确 + 3. 辅助任务 2：预测推理错误类型 + 4. 多任务学习提升性能 + """ + + def __init__(self, + encoder_name: str, + num_misconceptions: int, + num_error_types: int): + super().__init__() + + from transformers import AutoModel + + # 共享编码器 + self.encoder = AutoModel.from_pretrained(encoder_name) + hidden_size = self.encoder.config.hidden_size + + # 任务特定头 + self.misconception_head = nn.Linear(hidden_size, num_misconceptions) + self.correctness_head = nn.Linear(hidden_size, 2) # Binary: correct/incorrect + self.error_type_head = nn.Linear(hidden_size, num_error_types) + + # Dropout + self.dropout = nn.Dropout(0.1) + + def forward(self, + input_ids: torch.Tensor, + attention_mask: torch.Tensor) -> Dict[str, torch.Tensor]: + """ + Forward pass with multiple outputs + + Args: + input_ids: [batch, seq_len] + attention_mask: [batch, seq_len] + + Returns: + outputs: { + "misconception_logits": [batch, num_misconceptions], + "correctness_logits": [batch, 2], + "error_type_logits": [batch, num_error_types] + } + """ + # 编码 + outputs = self.encoder(input_ids=input_ids, attention_mask=attention_mask) + pooled = outputs.last_hidden_state[:, 0, :] # [CLS] token + pooled = self.dropout(pooled) + + # 多任务输出 + misconception_logits = self.misconception_head(pooled) + correctness_logits = self.correctness_head(pooled) + error_type_logits = self.error_type_head(pooled) + + return { + "misconception_logits": misconception_logits, + "correctness_logits": correctness_logits, + "error_type_logits": error_type_logits + } + + +class MultiTaskTrainer: + """ + Multi-task Training + """ + + def __init__(self, + model: AuxiliaryTaskModel, + alpha: float = 1.0, + beta: float = 0.5, + gamma: float = 0.3): + """ + Args: + model: 多任务模型 + alpha: 主任务权重 + beta: 辅助任务 1 权重 + gamma: 辅助任务 2 权重 + """ + self.model = model + self.alpha = alpha + self.beta = beta + self.gamma = gamma + + # 损失函数 + self.ce_loss = nn.CrossEntropyLoss() + + def compute_loss(self, + outputs: Dict[str, torch.Tensor], + misconception_labels: torch.Tensor, + correctness_labels: torch.Tensor, + error_type_labels: torch.Tensor) -> Tuple[torch.Tensor, Dict[str, float]]: + """ + 计算多任务损失 + + Args: + outputs: 模型输出 + misconception_labels: 误解标签 [batch] + correctness_labels: 正确性标签 [batch] + error_type_labels: 错误类型标签 [batch] + + Returns: + total_loss: 总损失 + loss_dict: 各任务损失 + """ + # 主任务损失 + misconception_loss = self.ce_loss( + outputs["misconception_logits"], + misconception_labels + ) + + # 辅助任务 1：正确性 + correctness_loss = self.ce_loss( + outputs["correctness_logits"], + correctness_labels + ) + + # 辅助任务 2：错误类型 + error_type_loss = self.ce_loss( + outputs["error_type_logits"], + error_type_labels + ) + + # 总损失 + total_loss = ( + self.alpha * misconception_loss + + self.beta * correctness_loss + + self.gamma * error_type_loss + ) + + loss_dict = { + "misconception": misconception_loss.item(), + "correctness": correctness_loss.item(), + "error_type": error_type_loss.item(), + "total": total_loss.item() + } + + return total_loss, loss_dict + + +# 使用示例 +if __name__ == "__main__": + # 创建模型 + model = AuxiliaryTaskModel( + encoder_name="microsoft/deberta-v3-large", + num_misconceptions=2587, + num_error_types=10 + ) + + # 创建训练器 + trainer = MultiTaskTrainer(model, alpha=1.0, beta=0.5, gamma=0.3) + + # 训练步骤 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-5) + + for batch in train_loader: + input_ids = batch["input_ids"].cuda() + attention_mask = batch["attention_mask"].cuda() + misconception_labels = batch["misconception_labels"].cuda() + correctness_labels = batch["correctness_labels"].cuda() + error_type_labels = batch["error_type_labels"].cuda() + + # Forward + outputs = model(input_ids, attention_mask) + + # Compute loss + loss, loss_dict = trainer.compute_loss( + outputs, misconception_labels, correctness_labels, error_type_labels + ) + + # Backward + optimizer.zero_grad() + loss.backward() + optimizer.step() + + print(f"Losses: {loss_dict}") +``` + +### Tiny Recursive Model (TRM) - 递归推理 + +**关键洞察：** 用极小参数（7M）实现递归推理，通过多次迭代改进答案 + +```python +import torch +import torch.nn as nn + +class TinyRecursiveModel(nn.Module): + """ + Tiny Recursive Model (TRM) + Paper: "Less is More: Recursive Reasoning with Tiny Networks" + Alexia Jolicoeur-Martineau, ARC Prize 2025 Paper Award 1st Place + + 核心思想： + - 递归地改进预测答案 y + - 分别维护 answer 和 latent 状态 + - 通过多次迭代逐步优化（类似思维链） + """ + def __init__(self, d_model=512, n_heads=8, n_iterations=16): + super().__init__() + self.d_model = d_model + self.n_heads = n_heads + self.n_iterations = n_iterations + + # Embedding layers + self.embed_x = nn.Linear(10, d_model) # input grid embedding (10 colors) + self.embed_y = nn.Linear(10, d_model) # output grid embedding + self.embed_z = nn.Linear(10, d_model) # latent embedding + + # Single transformer block (iterated, not stacked) + self.attention = nn.MultiheadAttention(d_model, n_heads, batch_first=True) + self.ffn = nn.Sequential( + nn.Linear(d_model, 4 * d_model), + nn.GELU(), + nn.Linear(4 * d_model, d_model) + ) + self.norm1 = nn.LayerNorm(d_model) + self.norm2 = nn.LayerNorm(d_model) + + # Output heads + self.head_y = nn.Linear(d_model, 10) # update answer + self.head_z = nn.Linear(d_model, 10) # update latent + + def forward(self, x, y_init=None, z_init=None): + """ + Args: + x: input grid (batch, seq_len, 10) + y_init: initial answer (random if None) + z_init: initial latent (random if None) + + Returns: + y: refined answer (batch, seq_len, 10) + """ + batch_size, seq_len, _ = x.shape + + # Initialize + y = y_init if y_init is not None else torch.randn_like(x) + z = z_init if z_init is not None else torch.randn(batch_size, seq_len, self.d_model) + + # Embed inputs + h_x = self.embed_x(x) # (batch, seq_len, d_model) + h_y = self.embed_y(y) # (batch, seq_len, d_model) + + # Iterative refinement + for iteration in range(self.n_iterations): + # Combine context: input + current answer + latent + h = h_x + h_y + self.permute_to_latent(z) + + # Single transformer block + h_norm = self.norm1(h) + attn_out, _ = self.attention(h_norm, h_norm, h_norm) + h = h + attn_out + + h_norm = self.norm2(h) + ffn_out = self.ffn(h_norm) + h = h + ffn_out + + # Update latent z (n times) + for _ in range(3): # recursive reasoning + z = z + self.head_z(h) + + # Update answer y (once) + y_delta = self.head_y(h) + y = y + y_delta + h_y = self.embed_y(y) + + return y + + def permute_to_latent(self, z): + """Permute latent to match input shape""" + return z # simplify for example +``` + +### 合成数据生成 - GPT-OSS 方法 + +**关键洞察：** 从现有任务生成新任务，通过组合实现二次方空间采样 + +```python +import openai + +def generate_synthetic_puzzles(base_descriptions, n_generate=260000): + """ + 使用 GPT-OSS 从基础描述生成合成任务 + NVARC 团队方法：从 3,000 基础描述生成 260,000 合成任务 + + Args: + base_descriptions: 基础任务描述列表 + n_generate: 要生成的任务数 + + Returns: + generated_tasks: 生成的任务列表 + """ + generated_tasks = [] + + # 采样二次方组合空间 + # 从 3,000 基础描述完整组合是 9M，采样 260K 是有意义的子集 + for i in range(n_generate): + # 随机选择 2 个基础描述 + desc1 = base_descriptions[i % len(base_descriptions)] + desc2 = base_descriptions[(i + 1) % len(base_descriptions)] + + # 组合描述 + combined_prompt = f""" + Combine these two ARC tasks: + + Task 1: {desc1} + Task 2: {desc2} + + Generate a new task that combines concepts from both. + Output format: + - Input grid generation code + - Transformation code + """ + + # 使用 GPT 生成 + response = openai.chat.completions.create( + model="gpt-4o", + messages=[{"role": "user", "content": combined_prompt}], + temperature=0.7 + ) + + generated_tasks.append(response.choices[0].message.content) + + return generated_tasks + + +def verify_generated_puzzles(tasks, min_valid_grids=30): + """ + 验证生成的任务质量 + + NVARC 方法： + 1. 生成输入网格代码 + 单元测试 + 2. 至少 30 个有效网格通过测试 + 3. 生成 20 种变换实现 + 4. 至少 8/20 产生相同输出 + """ + valid_tasks = [] + + for task in tasks: + # 执行生成的代码 + input_grids = generate_input_grids(task['input_code']) + + # 验证网格约束 + if len(input_grids) < min_valid_grids: + continue + + # 生成多种变换实现 + transformations = [] + for _ in range(20): + transform_result = execute_transformation(task['transform_code'], input_grids[0]) + transformations.append(transform_result) + + # 检查共识 + if check_consensus(transformations, threshold=8): + valid_tasks.append(task) + + return valid_tasks + + +def check_consensus(results, threshold=8): + """ + 检查是否至少 threshold 个结果相同 + """ + from collections import Counter + counts = Counter(results) + return counts.most_common(1)[0][1] >= threshold +``` + +### Tokenizer 优化 - 16 Tokens + +**关键洞察：** ARC 只需要 10 个颜色 + 格式 tokens，大幅减少 tokenizer + +```python +from transformers import AutoTokenizer, AutoModelForVision2Seq + +def optimize_arc_tokenizer(model_name="Qwen/Qwen2-VL-7B-Instruct"): + """ + 优化 tokenizer 用于 ARC 任务 + NVARC 方法：从 150K tokens 减少到 16 tokens + + ARC 只需要： + - 10 个颜色 (0-9) + - 新行符 + - 输入开始标记 + - 输出开始标记 + - 填充 + """ + # 加载原始 tokenizer + tokenizer = AutoTokenizer.from_pretrained(model_name) + + # 定义 ARC 词汇表 + arc_vocab = { + '0': 0, '1': 1, '2': 2, '3': 3, '4': 4, + '5': 5, '6': 6, '7': 7, '8': 8, '9': 9, # colors + '\\n': 10, # newline + '': 11, # input start + '': 12, # output start + '': 13, # padding + } + + # Patch embedding table + model = AutoModelForVision2Seq.from_pretrained(model_name) + original_embed = model.model.model.embed_tokens + new_embed = nn.Embedding(16, original_embed.embedding_dim) + + # 复制相关 tokens + for token, idx in arc_vocab.items(): + original_idx = tokenizer.convert_tokens_to_ids(token) + if original_idx is not None: + new_embed.weight[idx] = original_embed.weight[original_idx] + + # 替换 embedding 层 + model.model.model.embed_tokens = new_embed + + return tokenizer, model +``` + +### Test-Time Training (TTT) + +**关键洞察：** 在测试时训练模型，每个任务单独训练 + +```python +import torch +import torch.nn as nn + +def test_time_training(model, train_examples, test_input, n_steps=100, lr=0.001): + """ + Test-Time Training (TTT) + MindsAI 方法：在测试时训练模型 + + Args: + model: 基础模型 + train_examples: 训练示例 (input, output) 对列表 + test_input: 测试输入 + n_steps: 训练步数 + lr: 学习率 + + Returns: + prediction: 对测试输入的预测 + """ + optimizer = torch.optim.Adam(model.parameters(), lr=lr) + criterion = nn.MSELoss() + + # 训练阶段 + for step in range(n_steps): + total_loss = 0 + + for x, y in train_examples: + # 前向传播 + pred = model(x) + + # 计算损失 + loss = criterion(pred, y) + total_loss += loss + + # 反向传播 + optimizer.zero_grad() + total_loss.backward() + optimizer.step() + + # 预测阶段 + with torch.no_grad(): + prediction = model(test_input) + + return prediction + + +# MindsAI 的完整 TTT pipeline +def tft_with_augmentation(model, train_examples, test_input): + """ + TTFT + Augmentation Ensemble + + MindsAI 方法： + 1. Test-Time Fine-Tuning + 2. 数据增强集成（旋转、翻转、颜色排列） + 3. Tokenizer Dropout + """ + # 1. 数据增强 + augmented_examples = [] + for x, y in train_examples: + # 几何变换 + for rotation in [0, 90, 180, 270]: + x_rot = rotate_grid(x, rotation) + y_rot = rotate_grid(y, rotation) + augmented_examples.append((x_rot, y_rot)) + + x_flip = flip_grid(x_rot) + y_flip = flip_grid(y_rot) + augmented_examples.append((x_flip, y_flip)) + + # 颜色排列（10! = 3.6M，采样一部分） + color_perms = sample_color_permutations(n=10) + for perm in color_perms: + x_perm = apply_color_permutation(x, perm) + y_perm = apply_color_permutation(y, perm) + augmented_examples.append((x_perm, y_perm)) + + # 2. TTT with augmented data + predictions = [] + for _ in range(10): # 10 runs with different augmentation subsets + subset = random_subset(augmented_examples, size=100) + pred = test_time_training(model, subset, test_input) + predictions.append(pred) + + # 3. Ensemble predictions + final_pred = ensemble_predictions(predictions) + + return final_pred +``` + +### 数据增强 - 几何 + 颜色 + +**关键洞察：** 因子级别的数据增强（10! × 8 = 2900 万种） + +```python +import numpy as np +from itertools import permutations + +def augment_arc_task(input_grid, output_grid): + """ + ARC 任务的数据增强 + + NVARC 方法： + - 几何变换：8 种（旋转 4 × 翻转 2） + - 颜色排列：10! = 3,628,800 种 + - 总计：~2900 万种每个任务 + """ + augmented = [] + + # 1. 几何变换 + rotations = [0, 90, 180, 270] + flips = [False, True] + + for rotation in rotations: + for flip in flips: + x_aug = rotate_grid(input_grid, rotation) + if flip: + x_aug = flip_grid(x_aug) + + y_aug = rotate_grid(output_grid, rotation) + if flip: + y_aug = flip_grid(y_aug) + + augmented.append((x_aug, y_aug)) + + # 2. 颜色排列（采样，因为 10! 太大） + color_perms = sample_color_permutations(n=100) + for perm in color_perms: + for x, y in augmented[:8]: # 只对原始 8 个几何变换 + x_perm = apply_color_permutation(x, perm) + y_perm = apply_color_permutation(y, perm) + augmented.append((x_perm, y_perm)) + + return augmented + + +def sample_color_permutations(n=100, seed=42): + """ + 采样颜色排列（10! 太大，无法遍历） + """ + rng = np.random.default_rng(seed) + colors = np.arange(10) + perms = [] + + for _ in range(n): + perm = rng.permutation(colors) + perms.append(perm) + + return perms + + +def apply_color_permutation(grid, perm): + """ + 应用颜色排列到网格 + """ + permuted = grid.copy() + + # 创建映射 + mapping = {i: perm[i] for i in range(10)} + + # 应用映射 + for old_color in range(10): + new_color = mapping[old_color] + permuted[grid == old_color] = new_color + + return permuted +``` + +### SOAR - 进化程序合成 + +**关键洞察：** LLM 在自己的搜索轨迹上微调 + +```python +import openai + +class SOAR: + """ + SOAR: Self-Improving Language Models for Evolutionary Program Synthesis + Julien Pourcel et al., ARC Prize 2025 Paper Award 2nd Place + + 核心思想： + 1. 进化搜索生成程序 + 2. LLM 在搜索轨迹上微调 + 3. 迭代改进 + """ + def __init__(self, base_model="gpt-4"): + self.base_model = base_model + self.search_trajectory = [] + + def evolutionary_search(self, task, n_generations=100): + """ + 进化搜索生成程序 + """ + population = self.initialize_population(task) + + for gen in range(n_generations): + # 评估当前种群 + evaluated = self.evaluate_population(population, task) + + # 选择最好的 + best = sorted(evaluated, key=lambda x: x['fitness'], reverse=True)[:10] + + # 变异和交叉 + offspring = self.mutate_and_crossover(best, task) + + # 记录搜索轨迹 + self.search_trajectory.extend([ + {'generation': gen, 'programs': best, 'task': task} + ]) + + population = offspring + + return best[0] + + def fine_tune_on_trajectories(self, n_epochs=10): + """ + 在搜索轨迹上微调 LLM + """ + # 准备训练数据 + training_data = [] + for trajectory in self.search_trajectory: + for program in trajectory['programs']: + prompt = f""" + Task: {trajectory['task']} + Program: {program['code']} + Fitness: {program['fitness']} + + Generate a better program. + """ + training_data.append({'prompt': prompt, 'completion': program['code']}) + + # 微调（伪代码） + for epoch in range(n_epochs): + for sample in training_data: + response = openai.chat.completions.create( + model=self.base_model, + messages=[{"role": "user", "content": sample['prompt']}], + temperature=0.7 + ) + + # 计算损失并更新（实际需要训练循环） + # loss = compute_loss(response, sample['completion']) + # backward(loss) + + return self.base_model +``` + +### CompressARC - MDL 原理 + +**关键洞察：** 76K 参数，无预训练，仅用 VAE loss + decoder regularization + +```python +import torch +import torch.nn as nn + +class CompressARC(nn.Module): + """ + CompressARC: ARC-AGI Without Pretraining + Isaac Liao, ARC Prize 2025 Paper Award 3rd Place + + 核心思想： + - 仅 76K 参数 + - 无预训练，随机初始化 + - 使用 MDL (Minimum Description Length) 原理 + - VAE loss + decoder regularization + - 测试时训练（每个任务单独训练） + """ + def __init__(self, latent_dim=64, grid_size=30): + super().__init__() + self.latent_dim = latent_dim + self.grid_size = grid_size + + # Encoder: grid -> latent + self.encoder = nn.Sequential( + nn.Linear(10, 128), # 10 colors + nn.ReLU(), + nn.Linear(128, latent_dim * 2) # mean + logvar + ) + + # Decoder: latent -> grid + self.decoder = nn.Sequential( + nn.Linear(latent_dim, 128), + nn.ReLU(), + nn.Linear(128, 10) # 10 colors + ) + + def encode(self, x): + """编码网格到潜在空间""" + h = self.encoder(x) # (batch, latent_dim * 2) + mu, logvar = h.chunk(2, dim=-1) + return mu, logvar + + def decode(self, z): + """从潜在空间解码网格""" + return self.decoder(z) + + def forward(self, x): + """前向传播""" + mu, logvar = self.encode(x) + + # Reparameterization trick + std = torch.exp(0.5 * logvar) + eps = torch.randn_like(std) + z = mu + eps * std + + # Decode + recon_x = self.decode(z) + + return recon_x, mu, logvar + + def loss_function(self, recon_x, x, mu, logvar, beta=0.1): + """ + VAE loss + decoder regularization (MDL principle) + + CompressARC 关键创新：用 VAE 代替组合搜索 + """ + # Reconstruction loss + recon_loss = nn.functional.cross_entropy(recon_x, x) + + # KL divergence + kl_loss = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp()) + + # Decoder regularization (MDL) + decoder_reg = sum(p.pow(2).sum() for p in self.decoder.parameters()) + + # Total loss + total_loss = recon_loss + beta * kl_loss + 0.01 * decoder_reg + + return total_loss + + +def test_time_train_compressarc(task, n_minutes=20): + """ + 测试时训练 CompressARC + 每个 puzzle 单独训练，约 20 分钟在 RTX 4070 上 + """ + model = CompressARC() + optimizer = torch.optim.Adam(model.parameters(), lr=0.001) + + # 训练（直到收敛或超时） + for step in range(10000): # 最多 10K 步 + total_loss = 0 + + for input_grid, output_grid in task['train_examples']: + # 前向传播 + recon, mu, logvar = model(input_grid) + + # 计算损失 + loss = model.loss_function(recon, output_grid, mu, logvar) + total_loss += loss + + # 反向传播 + optimizer.zero_grad() + total_loss.backward() + optimizer.step() + + # 早停检查 + if total_loss < 0.01: + break + + # 预测 + with torch.no_grad(): + test_input = task['test_input'] + recon, mu, logvar = model(test_input) + prediction = recon.argmax(dim=-1) + + return prediction +``` + +### MARIO 框架 - 数学推理 + 代码解释器 + +**关键洞察：** 纯 LLM 推理不够，需要代码执行进行计算 + +```python +import subprocess +import tempfile +import os + +class MARIOFramework: + """ + MARIO: MAth Reasoning with code Interpreter + NVIDIA AIMO-2 第 1 名方案 + + 核心思想： + 1. LLM 生成自然语言推理 + Python 代码 + 2. 代码在沙盒环境中执行 + 3. 执行结果指导后续推理 + 4. 迭代直到得到最终答案 + """ + def __init__(self, model, max_iterations=10): + self.model = model + self.max_iterations = max_iterations + + def solve_math_problem(self, problem_text): + """ + 解决数学问题 + + Args: + problem_text: 数学问题文本 + + Returns: + answer: 最终答案（多选 A-E 或数值） + """ + # 初始化对话 + conversation = [ + {"role": "system", "content": "You are a math expert. Solve the problem step by step."}, + {"role": "user", "content": problem_text} + ] + + for iteration in range(self.max_iterations): + # 生成推理 + 代码 + response = self.model.generate(conversation) + + # 提取 Python 代码 + code_blocks = self.extract_code_blocks(response) + + if code_blocks: + # 执行代码 + execution_results = [] + for code in code_blocks: + result = self.execute_code_safely(code) + execution_results.append(result) + + # 将执行结果添加到对话 + conversation.append({"role": "assistant", "content": response}) + conversation.append({ + "role": "user", + "content": f"Execution results: {execution_results}. Continue reasoning." + }) + else: + # 没有代码，直接返回答案 + conversation.append({"role": "assistant", "content": response}) + break + + # 提取最终答案 + answer = self.extract_final_answer(conversation[-1]['content']) + return answer + + def extract_code_blocks(self, text): + """ + 提取 Python 代码块 + """ + import re + pattern = r'```python\n(.*?)```' + matches = re.findall(pattern, text, re.DOTALL) + return matches + + def execute_code_safely(self, code, timeout=10): + """ + 在沙盒环境中安全执行代码 + """ + try: + # 创建临时文件 + with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f: + f.write(code) + temp_file = f.name + + # 执行代码，设置超时和资源限制 + result = subprocess.run( + ['python', temp_file], + capture_output=True, + text=True, + timeout=timeout, + # 资源限制 + # (实际实现需要更严格的沙盒) + ) + + # 删除临时文件 + os.unlink(temp_file) + + return result.stdout + except subprocess.TimeoutExpired: + return "Execution timeout" + except Exception as e: + return f"Error: {str(e)}" +``` + +### 三阶段训练 (CoT → TIR → GenSelect) + +**关键洞察：** 逐步训练模型掌握推理、工具使用和答案选择 + +```python +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer + +class ThreeStageTraining: + """ + NVIDIA 三阶段训练流程 + Stage 1: CoT (Chain-of-Thought) - 知识获取 + Stage 2: TIR (Tool-Integrated Reasoning) - 工具集成推理 + Stage 3: GenSelect - 生成选择 + """ + def __init__(self, model_name="Qwen/Qwen2.5-32B"): + self.model = AutoModelForCausalLM.from_pretrained(model_name) + self.tokenizer = AutoTokenizer.from_pretrained(model_name) + + def stage1_cot_training(self, cot_dataset): + """ + Stage 1: Chain-of-Thought 训练 + 纯推理训练，不使用代码执行 + """ + for example in cot_dataset: + problem = example['problem'] + cot_solution = example['cot_solution'] # 长思维链 + + prompt = f""" + Problem: {problem} + + Solution: + {cot_solution} + + Answer: {example['answer']} + """ + + # 训练模型生成推理链 + inputs = self.tokenizer(prompt, return_tensors="pt") + labels = self.tokenizer(cot_solution, return_tensors="pt") + + outputs = self.model(**inputs, labels=labels) + loss = outputs.loss + + # 反向传播（简化） + loss.backward() + + def stage2_tir_training(self, tir_dataset): + """ + Stage 2: Tool-Integrated Reasoning 训练 + 训练模型生成推理 + Python 代码 + """ + for example in tir_dataset: + problem = example['problem'] + tir_solution = example['tir_solution'] # 推理 + 代码 + + prompt = f""" + Problem: {problem} + + Solve the problem step by step. Use Python code for calculations. + + Solution: + {tir_solution} + + Answer: {example['answer']} + """ + + inputs = self.tokenizer(prompt, return_tensors="pt") + labels = self.tokenizer(tir_solution, return_tensors="pt") + + outputs = self.model(**inputs, labels=labels) + loss = outputs.loss + + loss.backward() + + def stage3_genselect_training(self, validation_dataset): + """ + Stage 3: GenSelect 训练 + 学习多答案生成 + 排序投票 + """ + # 训练时模拟多个答案生成 + predictions = [] + + for example in validation_dataset: + problem = example['problem'] + + # 生成多个候选答案 + candidate_answers = [] + for _ in range(32): # 32 个候选答案 + prompt = f"Problem: {problem}\nSolution: Let's think step by step." + inputs = self.tokenizer(prompt, return_tensors="pt") + outputs = self.model.generate(**inputs, max_new_tokens=2048) + + answer = self.extract_answer(outputs) + candidate_answers.append(answer) + + # 基于排序的投票 + final_answer = self.rank_based_voting(candidate_answers) + predictions.append(final_answer) + + def rank_based_voting(self, answers): + """ + 基于排序的投票（优于简单多数投票） + + NVIDIA 创新： + - 不只是计数答案出现次数 + - 根据推理质量加权 + - 考虑答案的置信度 + """ + # 统计每个答案的投票数 + from collections import Counter + counts = Counter(answers) + + # 加权投票（推理质量） + # 这里简化为多数投票 + return counts.most_common(1)[0][0] +``` + +### GenSelect - 多答案生成与投票 + +**关键洞察：** 候选答案的排序投票优于简单多数投票 + +```python +import numpy as np +from collections import Counter + +def genselect_answer(model, problem_text, n_candidates=32): + """ + GenSelect: 生成选择方法 + + NVIDIA AIMO-2 核心创新： + 1. 生成多个候选答案 + 2. 对每个答案评分 + 3. 基于排序选择最终答案 + """ + candidate_answers = [] + scores = [] + + for _ in range(n_candidates): + # 生成推理 + 答案 + prompt = f""" +Problem: {problem_text} + +Let's think step by step. We need to find the final answer. +""" + response = model.generate(prompt, max_new_tokens=2048) + + # 提取答案 + answer = extract_answer(response) + confidence = estimate_confidence(response) + + candidate_answers.append(answer) + scores.append(confidence) + + # 基于排序的投票 + # 不只是选择出现最多的答案 + # 考虑答案的置信度排序 + sorted_indices = np.argsort(scores)[::-1] # 降序 + + # 选择置信度最高的答案 + # 或者使用加权组合 + final_answer = candidate_answers[sorted_indices[0]] + + return final_answer + + +def extract_answer(response_text): + """ + 从推理文本中提取最终答案 + """ + import re + + # 匹配模式 1: "Answer: X" + match = re.search(r'Answer:\s*([A-E]|-?\d+)', response_text) + if match: + return match.group(1) + + # 匹配模式 2: "最终答案是 X" + match = re.search(r'最终答案[是为]\s*([A-E]|-?\d+)', response_text) + if match: + return match.group(1) + + # 匹配模式 3: "Therefore, the answer is X" + match = re.search(r'Therefore,?\s*the\s+answer\s+is\s+([A-E]|-?\d+)', response_text) + if match: + return match.group(1) + + return None + + +def estimate_confidence(response_text): + """ + 估计答案的置信度 + + 方法： + - 推理链的完整性 + - "Therefore"、"Thus"等确定性词汇 + - 答案的明确程度 + """ + confidence = 0.5 # 基础置信度 + + # 检查确定性词汇 + certainty_keywords = ['therefore', 'thus', 'hence', 'consequently'] + for keyword in certainty_keywords: + if keyword in response_text.lower(): + confidence += 0.1 + + # 检查不确定性词汇 + uncertainty_keywords = ['maybe', 'perhaps', 'possibly', 'probably'] + for keyword in uncertainty_keywords: + if keyword in response_text.lower(): + confidence -= 0.1 + + # 检查推理链长度 + reasoning_length = len(response_text.split('.')) + confidence += min(reasoning_length / 100, 0.3) + + return np.clip(confidence, 0, 1) +``` + +### OpenMathReasoning 数据集构建 + +**关键洞察：** 从 AoPS 论坛提取高质量数学问题 + +```python +import requests +from bs4 import BeautifulSoup + +def build_openmath_dataset(): + """ + 从 AoPS (Art of Problem Solving) 论坛构建数据集 + + NVIDIA AIMO-2 方法： + 1. 爬取 AoPS 论坛的高质量回答 + 2. 使用 LLM 提取结构化信息 + 3. 过滤低质量数据 + 4. 生成 CoT 和 TIR 格式 + """ + base_url = "https://artofproblemsolving.com" + + # 1. 爬取论坛帖子 + posts = [] + for forum in ["algebra", "combinatorics", "number_theory"]: + url = f"{base_url}/{forum}" + posts.extend(scrape_aops_forum(url)) + + # 2. 提取问题和解答 + extracted_data = [] + for post in posts: + # 使用 LLM 提取结构化信息 + prompt = f""" + Extract from this AoPS forum post: + {post['content']} + + Extract: + 1. Problem statement + 2. Solution steps + 3. Final answer + """ + + extraction = llm_extract(prompt) + + extracted_data.append({ + 'problem': extraction['problem'], + 'solution': extraction['solution'], + 'answer': extraction['answer'], + 'source': post['url'] + }) + + # 3. 过滤质量 + filtered_data = filter_quality(extracted_data) + + # 4. 生成 CoT 格式 + cot_data = [] + for item in filtered_data: + cot = generate_cot_from_solution(item['solution']) + cot_data.append({ + 'problem': item['problem'], + 'cot_solution': cot, + 'answer': item['answer'] + }) + + # 5. 生成 TIR 格式 + tir_data = [] + for item in filtered_data: + tir = generate_tir_from_solution(item['solution']) + tir_data.append({ + 'problem': item['problem'], + 'tir_solution': tir, + 'answer': item['answer'] + }) + + return cot_data, tir_data + + +def generate_cot_from_solution(solution): + """ + 从解答生成长思维链 (CoT) + """ + prompt = f""" + Convert this solution into a step-by-step chain-of-thought explanation: + + Solution: {solution} + + Make sure to: + 1. Explain each step clearly + 2. Show your work + 3. Explain why we take each step + """ + + return llm_generate(prompt) + + +def generate_tir_from_solution(solution): + """ + 从解答生成工具集成推理 (TIR) + """ + prompt = f""" + Convert this solution into a format that includes Python code: + + Solution: {solution} + + Make sure to: + 1. Include Python code for calculations + 2. Explain what the code does + 3. Show intermediate results + """ + + return llm_generate(prompt) +``` + +### 2nd Place 方案 - 代码生成 + 执行流水线 + +**关键洞察：** 先生成 Python 代码，再执行验证 + +```python +def solve_math_with_code_generation(model, problem_text): + """ + 2nd Place (imagination-research) 方法 + + 流水线： + 1. 提示模型生成 Python 代码 + 2. 提取 Python 代码 + 3. 在解释器中执行代码 + 4. 验证结果 + 5. 返回最终答案 + """ + # Step 1: 生成代码 + prompt = f""" + Write a Python program to solve this math problem: + + {problem_text} + + The program should: + 1. Define the problem + 2. Implement the solution + 3. Print the final answer + """ + + response = model.generate(prompt) + python_code = extract_python_code(response) + + # Step 2: 执行代码 + result = execute_python_code(python_code) + + # Step 3: 提取答案 + answer = extract_answer_from_output(result) + + return answer + + +def extract_python_code(text): + """ + 从响应中提取 Python 代码 + """ + import re + pattern = r'```python\n(.*?)\n```' + match = re.search(pattern, text, re.DOTALL) + if match: + return match.group(1) + + # 备选：找 indented 代码块 + lines = text.split('\n') + code_lines = [] + in_code_block = False + indent_level = 0 + + for line in lines: + if '```' in line: + in_code_block = not in_code_block + elif in_code_block: + code_lines.append(line) + + return '\n'.join(code_lines) + + +def execute_python_code(code): + """ + 执行 Python 代码并返回输出 + """ + import sys + from io import StringIO + + old_stdout = sys.stdout + old_stderr = sys.stderr + + sys.stdout = StringIO() + sys.stderr = StringIO() + + try: + exec(code, {}) + output = sys.stdout.getvalue() + error = sys.stderr.getvalue() + except Exception as e: + output = "" + error = str(e) + finally: + sys.stdout = old_stdout + sys.stderr = old_stderr + + return output if output else error +``` + +--- + +## Best Practices + +### ARC/抽象推理任务策略 + +| 策略 | 何时使用 | 说明 | +|------|---------|------| +| **Refinement Loops** | 需要逐步优化答案 | 递归改进是智能的核心 (TRM) | +| **合成数据生成** | 原始任务不足时 | 通过组合生成新任务，采样二次方空间 | +| **LLM 微调** | 有基础模型可用 | Qwen-4B 在合成数据上微调 | +| **Test-Time Training** | 每个任务独立 | 在测试时为每个任务单独训练 | +| **进化程序合成** | 需要探索程序空间 | LLM 在搜索轨迹上微调 (SOAR) | +| **极小模型** | 计算受限或追求效率 | TRM (7M), CompressARC (76K) | +| **数据增强** | 任务数量有限时 | 几何变换 + 颜色排列 | +| **Tokenizer 优化** | 词汇表冗余时 | 减少到任务需要的最小 tokens | + +### 抽象推理 vs 传统 NLP + +| 方面 | 传统 NLP | ARC/抽象推理 | +|------|----------|-------------| +| **任务类型** | 分类、序列标注、生成 | 程序合成、推理 | +| **评估方式** | Accuracy/F1/Perplexity | 完全正确才算对 | +| **数据格式** | 文本序列 | 网格变换 | +| **泛化挑战** | 分布偏移 | Out-of-Distribution | +| **训练方式** | 大规模预训练 | 测试时训练为主 | +| **模型大小** | 越大越好 | 越小越高效 (TRM, CompressARC) | + +### Refinement Loops（优化循环） + +**核心思想：** Refinement = Intelligence（优化即智能） + +**应用场景：** + +| 方法 | 实现 | 适用场景 | +|------|------|---------| +| **递归推理** | TRM: 16 次迭代改进答案 | 需要逐步优化 | +| **进化搜索** | SOAR: 进化 + 微调 LLM | 程序合成 | +| **Test-Time Training** | 在测试时训练 | 每个任务独立 | +| **模型精炼** | 应用层优化 (Poetiq) | 提升基础模型 | + +**NVIDIA Refinement (Poetiq) 示例：** +- 基础: Gemini 3 Pro → 31% +- 精炼后: 54% (+23%) +- 成本: $0.81 → $31 + +### 合成数据生成策略 + +**NVARC 方法：** + +1. **基础数据收集** + - Human-ARC: 1K+ 任务描述 + - BARC: 600 可用任务 + - 总计: ~700 原始任务 + +2. **结构化描述** + - 5 个组件：输入生成、解决步骤、规则总结、关键洞察、概念 + - 使用 Claude/GPT-4o 结构化 + +3. **二次方组合** + - 3,000 基础描述 + - 完整组合: 9M (3,000²) + - 采样: 260K 合成任务 + +4. **质量验证** + - 生成输入代码 + 单元测试 + - 至少 30 个有效网格 + - 20 种实现，8/20 共识 + - 过滤后: ~100K 任务 + +### 模型架构对比 + +| 方法 | 参数量 | 预训练 | 成绩 | 特点 | +|------|--------|--------|------|------| +| **NVARC** | 4B (Qwen) | ✅ | 24% | 合成数据 + 微调 | +| **TRM** | 7M | ❌ | 8% (ARC-AGI-2) | 递归推理，极小模型 | +| **CompressARC** | 76K | ❌ | 4% (ARC-AGI-2) | MDL，无预训练 | +| **SOAR** | 变化 | ❌ | 52% (ARC-AGI-1) | 进化 + 自微调 | +| **ARChitects** | 变化 | ✅ | 16.53% | Masked-Diffusion | + +### 成本效益对比 + +| 方案 | 准确率 (ARC-AGI-2) | 成本 | 性价比 | +|------|---------------------|------|--------| +| **NVARC (获胜)** | 24.03% | $0.20/task | 最高 | +| **Gemini 3 Pro (基线)** | 31% | $0.81/task | 中等 | +| **Gemini 3 Pro (精炼)** | 54% | $31/task | 低 | +| **Claude Opus (精炼)** | ~54% | $60/task | 最低 | +| **GPT-4o (开始)** | 1.9% | - | - | + +### 前沿模型的问题 + +**"Overfitting on Knowledge"（知识过拟合）：** + +**现象：** 前沿模型可能在训练数据上"过拟合"了 ARC +- **证据**：Gemini 3 Deep Think 使用正确的 ARC 颜色映射 +- **原因**：ARC 数据在预训练数据中充分表示 +- **含义**：即使设计良好的 benchmark 也会被"过拟合" + +**解决方案：** +- **ARC-AGI-3**: 新格式，测试交互推理 +- **新任务生成**: 持续更新 benchmark +- **私有数据**: 保持测试集未知 + +### Test-Time Training 最佳实践 + +**何时使用：** +- 每个任务独立 +- 训练示例少（2-10 对） +- 需要快速适应 + +**实现步骤：** +1. 使用训练示例作为 mini-batch +2. 训练 n 步（100-1000） +3. 在测试输入上预测 +4. 可选：数据增强集成 + +**MindsAI TTFT Pipeline：** +1. Test-Time Fine-Tuning +2. Augmentation Ensemble（几何 + 颜色） +3. Tokenizer Dropout +4. Pretraining Tricks + +### 极小模型的优势 + +**TRM (7M 参数)：** +- **效率**: 参数少，推理快 +- **泛化**: 不易过拟合 +- **可解释**: 递归结构清晰 + +**CompressARC (76K 参数)：** +- **无预训练**: 随机初始化 +- **MDL 原理**: 最小描述长度 +- **测试时训练**: 每个任务 20 分钟 + +**结论：** 对于推理任务，小模型 + TTT 可能优于大模型 + +### 数据增强策略 + +**几何变换 (8 种)：** +- 旋转: 0°, 90°, 180°, 270° +- 翻转: 水平、垂直 + +**颜色排列:** +- 10! = 3,628,800 种 +- 实际采样: 100-1000 种 + +**增强策略：** +- **NVARC**: 不同数据源不同增强级别 (24-256) +- **MindsAI**: 采样 + 集成 + +### Tokenizer 优化 + +**为什么优化：** +- 原始: ~150K tokens +- ARC 需要: 16 tokens (10 颜色 + 6 格式) +- 减少: ~99.99% + +**NVARC 方法：** +1. 保留 16 个相关 tokens +2. Patch embedding table +3. 微调时只更新这些 tokens + +### 前沿模型的使用 + +**竞赛开始时 (2025-03)：** +- Claude Sonnet: 1.3% +- GPT-4o: 1.9% + +**竞赛结束后 (2025-11)：** +- Gemini 3: 31% → 54% (精炼) +- Claude Opus: >30% +- Grok: >30% + +**原因：** +- 前沿模型在合成 ARC 数据上预训练 +- 代码生成 + 执行在推理时 + +### 关键数据洞察总结 + +1. **Refinement = Intelligence**: 优化循环是智能的核心 +2. **合成数据是关键**: 从 700 任务生成 260K 合成任务 +3. **极小模型很强大**: TRM (7M), CompressARC (76K) +4. **Test-Time Training 有效**: 每个任务单独训练 +5. **LLM 可以自改进**: SOAR 在搜索轨迹上微调 +6. **Overfitting on Knowledge**: 前沿模型可能"过拟合" ARC +7. **成本差异巨大**: $0.20 vs $60 per task +8. **公共排行榜不可靠**: Public/Private Shake 严重 + +### 抽象推理任务的最佳实践 + +| 方面 | 推荐 | +|------|------| +| **数据准备** | 合成数据生成 + 质量验证 | +| **模型选择** | 小模型 + TTT (TRM, CompressARC) | +| **训练策略** | Test-Time Training | +| **优化方法** | Refinement Loops | +| **数据增强** | 几何变换 + 颜色排列 | +| **Tokenizer** | 优化到最小 tokens | +| **评估** | 使用本地验证，忽略 Public LB | +| **成本控制** | TTT < 模型精炼 < 前沿模型 | + +### 数学推理任务策略 + +| 策略 | 何时使用 | 说明 | +|------|---------|------| +| **代码执行集成** | 需要精确计算 | 纯推理不够，需要 Python 代码执行 | +| **多答案生成 + 投票** | 答案不确定时 | 32 个候选 + 排序投票 | +| **三阶段训练** | 有大量高质量数据时 | CoT → TIR → GenSelect | +| **高质量数据源** | 数据不足时 | 从 AoPS 等专业论坛提取 | +| **小模型竞争力** | 计算受限时 | 1.5B 模型可达有竞争力 | + +### 数学推理 vs 抽象推理 vs 传统 NLP + +| 方面 | 传统 NLP | 数学推理 | 抽象推理 | +|------|----------|---------|-------------| +| **任务类型** | 分类、序列标注 | 数学问题求解 | 程序合成、推理 | +| **输出格式** | 标签、文本 | 数值答案、选项 | 网格变换 | +| **核心挑战** | 语义理解 | 逻辑推理、计算 | 泛化能力 | +| **关键能力** | 语言理解 | 数学知识、推理 | 抽象能力 | +| **解决方案** | 微调 LLM | 代码执行 + GenSelect | Refinement Loops | + +### MARIO 框架详解 + +**核心组件：** + +| 组件 | 功能 | 实现方式 | +|------|------|---------| +| **MA** | Math（数学推理） | 理解问题、生成推理 | +| **RI** | Reasoning + Interpreter | 生成代码、执行、验证 | +| **O** | Open（开源） | 开源模型和数据 | + +**流程：** +``` +问题文本 + ↓ +[LLM 推理 + Python 代码] + ↓ +[沙盒环境执行代码] + ↓ +[执行结果反馈] + ↓ +[迭代优化] + ↓ +最终答案 +``` + +### 数据质量 vs 数量 + +**NVIDIA 发现：** + +| 方面 | 传统方法 | NVIDIA 方法 | +|------|---------|-----------| +| **数据量** | 追求数量 | 质量优先 | +| **数据源** | 通用数据集 | 专业论坛 (AoPS) | +| **质量验证** | 简单过滤 | LLM 提取 + 人工验证 | +| **效果** | 300K 低质量 | 290K 高质量 | + +**OpenMathReasoning 数据集：** +- **问题数量**: ~290K（不是最初宣传的 540K） +- **CoT 格式**: 3.2M 长思维链 +- **TIR 格式**: 1.7M 工具集成推理 +- **来源**: AoPS (Art of Problem Solving) 论坛 + +### GenSelect vs 简单多数投票 + +| 方法 | 准确率 | 计算成本 | 说明 | +|------|--------|----------|------| +| **GenSelect** | 68% (34/50) | 32 × 推理 | 基于排序投票 | +| **简单多数投票** | ~60% | 32 × 推理 | 只选出现最多的 | +| **单次推理** | ~50% | 1 × 推理 | 不生成多次 | + +**GenSelect 优势：** +- 考虑推理质量 +- 加权置信度 +- 处理答案分布不均 + +### 模型大小 vs 性能 + +| 模型 | 参数量 | 性能 | 成本 | +|------|--------|------|------| +| **OpenMath-Nemotron-1.5B** | 1.5B | ~40% | 低 | +| **OpenMath-Nemotron-7B** | 7B | ~50% | 中 | +| **OpenMath-Nemotron-14B** | 14B | ~60% | 高 | +| **OpenMath-Nemotron-32B** | 32B | 68% | 最高 | +| **DeepSeek-R1** | ~? | ~70% | 未知 | + +**结论：** 小模型（1.5B）在有良好训练的情况下可达有竞争力的性能 + +### AoPS 数据提取策略 + +**关键步骤：** + +1. **论坛选择** + - Algebra（代数） + - Combinatorics（组合） + - Number Theory（数论） + +2. **质量指标** + - 回答质量（被选为最佳回答） + - 推理完整性 + - 可验证性 + +3. **LLM 提取** + - 问题陈述 + - 解决步骤 + - 最终答案 + - 结构化格式 + +4. **过滤策略** + - 移除低质量解答 + - 验证数学正确性 + - 去重 + +### 代码执行安全 + +**沙盒环境要求：** + +| 方面 | 要求 | +|------|------| +| **隔离** | 独立进程，不污染主环境 | +| **超时** | 10 秒执行时间限制 | +| **资源限制** CPU、内存、磁盘限制 | +| **网络** | 禁止网络访问 | +| **文件系统** | 临时文件，只读访问 | + +**实现方式：** +- Docker 容器 +- subprocess + resource limits +- 云端执行环境 + +### 前沿模型的进展 + +**竞赛期间（2024-08）：** +- Claude Sonnet: ~30% +- GPT-4o: ~35% + +**竞赛结束后（2024-12）：** +- Gemini 2 Pro: ~50% +- DeepSeek-R1: ~70% +- Claude Opus: ~65% + +**原因：** +- 前沿模型在数学数据上预训练 +- 代码生成能力增强 +- 推理能力提升 + +--- + +### 前排方案技术细节（Top 12+） + +#### 微调方法总结 + +| 方法 | 使用队伍 | 效果 | 说明 | +|------|---------|------|------| +| **SFT** | 几乎所有队伍 | 基础必备 | 使用 OpenR1 Math, Light-R1, 自定义数据集 | +| **DPO** | 2nd place | 长度优化 | 第 2 阶段减少输出长度，保持推理能力 | +| **TIR** | 1st place | 核心创新 | 训练模型使用外部工具（Python 沙盒） | +| **GRPO** | 9th place | 效率提升（不稳定） | 奖励优化到一定程度后"灾难性偏移" | + +**微调方法对比：** + +1. **SFT (Supervised Fine-Tuning)** - 基础起点 + - 数据集：OpenR1 Math, Light-R1, 自定义数学问题 + - 目标：学习数学推理模式 + - 阶段：几乎所有队伍的第一阶段 + +2. **DPO (Direct Preference Optimization)** - 第 2 名使用 + - 目标：减少输出长度（提升效率） + - 数据构建：基于正确性、长度比、最小长度、相似性 + - 效果：第 2 阶段有效减少输出长度 + +3. **TIR (Tool-Integrated Reasoning)** - 第 1 名核心 + - 目标：集成外部工具（Python 代码执行） + - 效果：显著提升计算精度和推理能力 + - 数据：OpenMathReasoning (1.7M TIR 格式) + +4. **GRPO (Generative Reinforcement Preference Optimization)** - 第 9 名尝试 + - 目标：用更少 tokens 达到准确结论 + - 奖励函数：格式正确性、余弦相似性、长度奖励 + - 结果：优化到一定程度后出现"灾难性偏移"，需使用早期 checkpoint + +#### 推理策略总结 + +| 策略 | 使用队伍 | 效果 | 说明 | +|------|---------|------|------| +| **Self-consistency** | 1st, 2nd, 3rd, 5th, 11th, 17th | 标配 | 生成多个解，取最频繁答案 | +| **Early Stopping (Sample)** | 2nd | 节省 tokens | 找到答案或生成代码后立即停止 | +| **Early Stopping (Question)** | 1st, 2nd, 3rd, 11th, 17th | 节省时间 | 早期共识出现后停止整个问题生成 | +| **Time Management** | 多个队伍 | 动态资源分配 | 根据剩余时间/问题难度调整参数 | + +**Self-consistency 实现：** +```python +def self_consistency_solve(model, problem, n_samples=32): + """ + 自一致性求解：生成多个解，取最频繁答案 + """ + answers = [] + for _ in range(n_samples): + ans = model.generate(problem) + answers.append(ans) + + # 多数投票 + from collections import Counter + counter = Counter(answers) + return counter.most_common(1)[0][0] +``` + +**Early Stopping 变体（1st Place）：** +```python +def early_stopping_genselect(model, problem, n_candidates=32): + """ + 第 1 名的 Early Stopping 策略 + 如果前 5 个生成中有 4 个相同，取消剩余生成 + """ + answers = [] + for i in range(n_candidates): + ans = model.generate(problem) + answers.append(ans) + + # Early stopping check + if i >= 4: + from collections import Counter + counter = Counter(answers) + most_common_count = counter.most_common(1)[0][1] + if most_common_count >= 4: + break # 提前停止 + + return counter.most_common(1)[0][0] +``` + +#### 推理引擎对比 + +| 引擎 | 使用队伍 | 优势 | 劣势 | +|------|---------|------|------| +| **vLLM** | 4th, 7th, 8th, 11th, 17th | 最常用，成熟 | 默认配置可能不够优化 | +| **lmdeploy** | 2nd, 5th, 7th | 高吞吐量 | 配置相对复杂 | +| **TensorRT-LLM** | 1st | 最优性能 | 需要专业优化 | + +#### 量化技术 + +| 量化方法 | 使用队伍 | 效果 | 说明 | +|---------|---------|------|------| +| **AWQ 4-bit** | 几乎所有队伍 | 平衡性能和效率 | Activation-aware Weight Quantization | +| **FP8** | 1st place | 进一步优化 | 第 1 名使用 | +| **8-bit KV cache** | 2nd, 7th | 节省内存 | KV cache 量化 | + +**AWQ 原理：** +- 不是所有权重都同等重要 +- 识别被大激活值乘以的关键权重 +- 保护这些关键权重，牺牲不重要的权重 +- 结果：更小、更快的模型，性能几乎不变 + +#### Prompt Engineering 最佳实践 + +**1. System Prompts（角色设置）：** + +```python +# 基础版 +"You are a helpful math assistant." + +# 更权威（8th Place 风格） +"You are an expert in solving AIMO-level mathematics problems. Your goal is to solve the following problem with high accuracy and minimal reasoning steps." + +# 行为 + 模型特定（Fast-Math-R1-14B） +"You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step..." + +# 特定特质（21st Place 教师模型） +"You are the most powerful math expert. Please solve the problems with deep reasoning. You are careful and always recheck your deductions. You will never give an answer directly until you have enough confidence." +``` + +**2. User Instructions（任务定义）：** + +```python +# 核心输出格式（通用） +""" +You must put the final answer in \\boxed{}. +If the final answer is greater than 1000, then take the modulo of 1000. +""" + +# 鼓励 CoT（2nd Place） +""" +You excel at reasoning. +Think carefully and thoroughly, avoid duplication. +""" + +# 鼓励代码输出（2nd Place） +""" +You excel at coding. +You must provide the python code, avoid redundant analysis. +The answer must be integer. +There is only one answer for each question. +Import necessary libraries. +""" + +# 特定行动序列（8th Place） +""" +1. Read the problem carefully and identify the key components. +2. Plan your approach in 1-2 concise steps, focusing on the most efficient method. +3. Execute the solution with clear, logical reasoning, but limit your reasoning to a maximum of 1-2 steps. +4. Verify your answer for correctness by double-checking each step before finalizing. +5. Provide the final answer in a boxed format... and stop further reasoning. +""" +``` + +**3. Few-Shot / One-Shot Prompts（11th Place）：** + +```python +# One-shot prompting 示例 +system_prompt = """ +You are a Python code assistant. You will be given a mathematical problem that has integer solutions. Your task is to convert this complex math problem into Python code. Let's have Python do the tedious calculations for us! + +- There are multiple ways to solve this problem, so find the most efficient one. +- The final answer should be an integer. +- The final answer should be modulo 1000. +- Please return Python code only following the format below. +""" + +few_shot_example = """ +```python +import math + +# Intermediate calculations +result = ... +print(result % 1000) +``` +""" +``` + +**4. Multi-Stage Prompting（17th Place）：** + +```python +# Stage 1: Initial thought +stage1_output = model.generate(f"{problem}\nThink step by step:") + +# Stage 2: Code generation +stage2_prompt = f""" +Problem: {problem} +Previous thought: {stage1_output} + +Please make a short summary of your approach, including python code. +""" +stage2_output = model.generate(stage2_prompt) + +# Stage 3: Error fixing (if needed) +if execution_failed: + stage3_prompt = f""" +Problem: {problem} +Previous code: {stage2_output} +Error: {error_message} + +Please fix the code. +""" + stage3_output = model.generate(stage3_prompt) +``` + +#### 模型选择建议 + +**前排方案共识：** + +1. **DeepSeek-R1-Distill-Qwen-14B AWQ** 是最受欢迎的选择 + - 4-bit 量化，内存效率高 + - 推理能力强 + - 推理速度快 + +2. **Qwen2.5-14B** 是第 1 名的基础模型 + - 更强的推理能力 + - 需要更多优化 + +3. **模型大小选择：** + - 14B AWQ：最佳平衡（3rd-22nd） + - 32B AWQ：更大但更慢（20th） + - 7B AWQ：更快但精度略低 + +--- + +## Metadata + +| Source | Date | Tags | +|--------|------|------| +| [ARC Prize 2025](https://www.kaggle.com/competitions/arc-prize-2025) | 2025-01-22 | 抽象推理, Refinement Loops, 合成数据, Test-Time Training, TRM, SOAR, CompressARC | +| [AI Mathematical Olympiad Progress Prize 2](https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-2) | 2025-01-22 | 数学推理, MARIO, 代码执行集成, OpenMathReasoning, GenSelect, 三阶段训练, AoPS | +| [Eedi - Mining Misconceptions in Mathematics](https://www.kaggle.com/competitions/eedi-mining-misconceptions-in-mathematics) | 2024-09 | 教育 AI, 误解检测, 检索+重排, Qwen LLM, Distractor prediction,亲和度预测 | +| [MAP - Charting Student Math Misunderstandings](https://www.kaggle.com/competitions/map-charting-student-math-misunderstandings) | 2025-01-22 | 教育 AI, 误解检测, MiRAGE, Shared-prefix attention, Soft labels, Multi-task learning, CoT distillation, Ensemble fusion, Eedi 后续竞赛 | diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/tabular.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/tabular.md new file mode 100644 index 0000000..81f6e71 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/tabular.md @@ -0,0 +1,829 @@ +# Tabular Knowledge Base + +> Last updated: 2025-01-22 +> Source count: 1 + +## Original Summaries + +### CMI - Problematic Internet Use (2024) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/child-mind-institute-problematic-internet-use) +**Category:** Tabular (表格数据 + 时序混合) +**Key Techniques:** +- **中间分数预测**：预测 PCIAT-PCIAT_Total 而非直接预测 sii +- **多seed平均**：减少seed引起的方差 +- **高fold交叉验证**：10-fold stratified KFold +- **Pseudo Labeling**：填充缺失target +- **GBM主导的集成**：LGBM + XGBoost + CatBoost +- **Tweedie Loss**：处理偏态分布 +- **时序特征工程**：k-means聚类 +- **特征清洗**：去除异常特征、PCA降维 + +**Results:** 多seed平均、预测中间分数、Pseudo Labeling 是关键技术 + +--- + +## Competition Brief (竞赛简介) + +### CMI - Problematic Internet Use (2024) + +**竞赛背景：** +- **主办方**：Child Mind Institute +- **目标**：预测儿童和青少年的问题性网络使用严重程度（sii） +- **应用场景**：理解与抑郁和焦虑等心理健康问题相关的网络使用行为 + +**数据集规模：** +- 总样本数：约 3,900+（训练集） +- 特征：表格数据 + 部分时序数据 +- 类别：4 分类（sii = 0, 1, 2, 3） + +**数据特点：** +1. **混合数据类型**：表格数据（身体活动、健康指标）+ 时序数据 +2. **target 缺失**：训练集中部分样本的 sii 缺失 +3. **中间分数**：PCIAT-PCIAT_Total 是 sii 的连续分数版本 +4. **类别分布不均**：约 58.3% 为 0 类（无问题） + +**评估指标：** +- **Quadratic Weighted Kappa (QWK)**：衡量预测与实际的一致性 +- 分数范围：-1 到 1，越高越好 +- 特点：对分类错误的惩罚与严重程度成正比 + +**关键挑战：** +1. **Seed 敏感**：不同 seed 导致 LB 分数剧烈波动 +2. **数据泄露**：公开 notebook 泄露了训练数据 +3. **LB 不可靠**：Private LB 大幅 shake（波动） +4. **Target 缺失**：需要 Pseudo Labeling 处理 + +--- + +## Code Templates + +### 中间分数预测 (PCIAT-PCIAT_Total) + +**关键洞察：** 预测连续分数比直接预测类别更有效 + +```python +import numpy as np +import pandas as pd +from lightgbm import LGBMRegressor +from sklearn.model_selection import StratifiedKFold + +# 原始 sii 标签: 0, 1, 2, 3 +# PCIAT-PCIAT_Total: 连续分数 (0-100) + +def train_intermediate_target_model(X_train, y_train_total, X_test): + """ + 预测 PCIAT-PCIAT_Total (中间分数)，然后转换为 sii + """ + # 根据 sii 创建分层的 bins + # 这确保每个 fold 中各类别比例一致 + train_df = X_train.copy() + train_df['sii'] = (y_train_total > 30).astype(int) + \ + (y_train_total > 50).astype(int) + \ + (y_train_total > 80).astype(int) + + # 10-fold stratified KFold + n_folds = 10 + skf = StratifiedKFold(n_splits=n_folds, shuffle=True, random_state=42) + + # 存储预测结果 + oof_preds = np.zeros(len(X_train)) + test_preds = np.zeros(len(X_test)) + + for fold, (train_idx, val_idx) in enumerate(skf.split(X_train, train_df['sii'])): + X_tr, X_val = X_train.iloc[train_idx], X_train.iloc[val_idx] + y_tr, y_val = y_train_total.iloc[train_idx], y_train_total.iloc[val_idx] + + # LightGBM 回归器 + model = LGBMRegressor( + n_estimators=1000, + learning_rate=0.05, + num_leaves=31, + max_depth=-1, + random_state=42 + fold # 每个 fold 不同 seed + ) + + model.fit(X_tr, y_tr, eval_set=[(X_val, y_val)], + early_stopping_rounds=100, verbose=False) + + # 预测中间分数 + oof_preds[val_idx] = model.predict(X_val) + test_preds += model.predict(X_test) / n_folds + + return oof_preds, test_preds + +def convert_total_to_sii(pred_total): + """ + 将 PCIAT-PCIAT_Total 转换为 sii 标签 + 阈值: 0-30→0, 31-50→1, 51-80→2, 81-100→3 + """ + pred_sii = np.zeros(len(pred_total)) + pred_sii[pred_total > 30] = 1 + pred_sii[pred_total > 50] = 2 + pred_sii[pred_total > 80] = 3 + return pred_sii.astype(int) +``` + +### 多 Seed 平均 + +**关键洞察：** 多个 seed 平均可以减少预测方差 + +```python +import numpy as np +from lightgbm import LGBMRegressor + +def multi_seed_prediction(X_train, y_train, X_test, seeds=[42, 123, 456, 789, 1011]): + """ + 多个 seed 训练模型，取平均预测 + """ + test_preds_all = [] + + for seed in seeds: + model = LGBMRegressor( + n_estimators=1000, + learning_rate=0.05, + random_state=seed + ) + + model.fit(X_train, y_train) + test_preds_all.append(model.predict(X_test)) + + # 平均预测 + test_preds_mean = np.mean(test_preds_all, axis=0) + + return test_preds_mean + +# 更进一步：多 fold × 多 seed +def multi_fold_multi_seed(X_train, y_train, X_test, n_folds=5, seeds=10): + """ + 多 fold × 多 seed = 更稳定的预测 + """ + n_folds = 5 + seeds = list(range(10)) # 10 个 seeds + + test_preds = [] + + for seed in seeds: + for fold in range(n_folds): + model = LGBMRegressor( + n_estimators=1000, + random_state=seed + fold * 100 + ) + # ... train and predict + test_preds.append(model.predict(X_test)) + + # 50 个模型的平均 (5 folds × 10 seeds) + return np.mean(test_preds, axis=0) +``` + +### Pseudo Labeling + +**关键洞察：** 用模型预测填充缺失的 target + +```python +import numpy as np +import pandas as pd + +def pseudo_labeling(X_train, y_train, X_missing, n_iterations=3): + """ + Pseudo Labeling 迭代填充缺失 target + """ + # 分割有标签和无标签数据 + has_label = ~y_train.isna() + X_labeled = X_train[has_label] + y_labeled = y_train[has_label] + X_unlabeled = X_train[~has_label] + + # 初始模型（仅用有标签数据训练） + model = LGBMRegressor(random_state=42) + model.fit(X_labeled, y_labeled) + + # 迭代预测和训练 + for iteration in range(n_iterations): + # 预测无标签数据 + pseudo_labels = model.predict(X_unlabeled) + + # 合并有标签和伪标签数据 + X_combined = pd.concat([X_labeled, X_unlabeled]) + y_combined = pd.concat([y_labeled, pd.Series(pseudo_labels, index=X_unlabeled.index)]) + + # 重新训练模型 + model = LGBMRegressor(random_state=42 + iteration) + model.fit(X_combined, y_combined) + + return model + +# 注意：CV 计算时不使用 pseudo labels +def cv_with_pseudo(X_train, y_train, X_missing): + """ + 交叉验证时不使用 pseudo labels + """ + has_label = ~y_train.isna() + X_labeled = X_train[has_label] + y_labeled = y_train[has_label] + + # 训练 pseudo 模型（用于最终预测） + pseudo_model = pseudo_labeling(X_train, y_train, X_missing) + + # CV 仅用有标签数据 + from sklearn.model_selection import cross_val_score + cv_model = LGBMRegressor(random_state=42) + cv_scores = cross_val_score(cv_model, X_labeled, y_labeled, cv=5) + + return pseudo_model, cv_scores +``` + +### Tweedie Loss + +**关键洞察：** 处理偏态分布的目标变量 + +```python +import lightgbm as lgb + +def train_with_tweedie_loss(X_train, y_train, X_val, y_val): + """ + 使用 Tweedie Loss 训练 LightGBM + 适用于偏态分布（如保险索赔、疾病严重程度） + """ + train_data = lgb.Dataset(X_train, label=y_train) + val_data = lgb.Dataset(X_val, label=y_val, reference=train_data) + + params = { + 'objective': 'tweedie', + 'tweedie_variance_power': 1.5, # 1 < p < 2，控制偏态程度 + 'metric': 'rmse', + 'learning_rate': 0.05, + 'num_leaves': 31, + 'max_depth': -1, + 'verbose': -1 + } + + model = lgb.train( + params, + train_data, + num_boost_round=1000, + valid_sets=[val_data], + early_stopping_rounds=100, + verbose_eval=False + ) + + return model +``` + +### 时序特征 k-means 聚类 + +**关键洞察：** 将时序数据聚类成类别特征 + +```python +import numpy as np +from sklearn.cluster import KMeans +from sklearn.preprocessing import StandardScaler + +def extract_time_series_cluster_features(time_series_data, n_clusters=5): + """ + 时序数据 k-means 聚类作为特征 + """ + # 假设 time_series_data 是 (n_samples, n_timesteps, n_features) + n_samples = time_series_data.shape[0] + + # 展平时序数据: (n_samples, n_timesteps * n_features) + ts_flat = time_series_data.reshape(n_samples, -1) + + # 标准化 + scaler = StandardScaler() + ts_scaled = scaler.fit_transform(ts_flat) + + # k-means 聚类 + kmeans = KMeans(n_clusters=n_clusters, random_state=42, n_init=10) + cluster_labels = kmeans.fit_predict(ts_scaled) + + # 聚类距离作为特征 + cluster_distances = kmeans.transform(ts_scaled) + + # 创建特征 DataFrame + cluster_features = pd.DataFrame({ + f'ts_cluster_dist_{i}': cluster_distances[:, i] + for i in range(n_clusters) + }) + cluster_features['ts_cluster_label'] = cluster_labels + + return cluster_features + +# 使用示例 +# time_series_data 是原始时序数据 +# cluster_features = extract_time_series_cluster_features(time_series_data) +# X_final = pd.concat([tabular_features, cluster_features], axis=1) +``` + +### 特征清洗和 PCA 降维 + +**关键洞察：** 去除异常特征，PCA 降维减少噪声 + +```python +import numpy as np +import pandas as pd +from sklearn.decomposition import PCA +from sklearn.preprocessing import StandardScaler + +def clean_features(X, threshold=0.99): + """ + 清洗异常特征 + - 去除高度相关的特征 + - 去除方差过小的特征 + """ + # 计算相关性矩阵 + corr_matrix = X.corr().abs() + + # 找到高度相关的特征对 + upper_tri = corr_matrix.where( + np.triu(np.ones(corr_matrix.shape), k=1).astype(bool) + ) + + # 找出相关性 > threshold 的特征 + to_drop = [column for column in upper_tri.columns if any(upper_tri[column] > threshold)] + + # 去除高度相关的特征 + X_cleaned = X.drop(columns=to_drop) + + return X_cleaned, to_drop + +def pca_reduction(X_train, X_test, variance_ratio=0.95): + """ + PCA 降维 + """ + # 标准化 + scaler = StandardScaler() + X_train_scaled = scaler.fit_transform(X_train) + X_test_scaled = scaler.transform(X_test) + + # PCA + pca = PCA(n_components=variance_ratio) + X_train_pca = pca.fit_transform(X_train_scaled) + X_test_pca = pca.transform(X_test_scaled) + + print(f"Original features: {X_train.shape[1]}") + print(f"PCA components: {X_train_pca.shape[1]}") + print(f"Variance explained: {pca.explained_variance_ratio_.sum():.4f}") + + return X_train_pca, X_test_pca, pca +``` + +### GBM Ensemble (LGBM + XGBoost + CatBoost) + +**关键洞察：** 不同 GBM 的集成提升稳定性 + +```python +import numpy as np +from lightgbm import LGBMRegressor +from xgboost import XGBRegressor +from catboost import CatBoostRegressor + +def train_gbm_ensemble(X_train, y_train, X_test): + """ + 训练 GBM 集成: LGBM + XGBoost + CatBoost + """ + models = [] + test_preds = [] + + # 1. LightGBM + lgbm = LGBMRegressor( + n_estimators=1000, + learning_rate=0.05, + num_leaves=31, + max_depth=-1, + random_state=42, + verbose=-1 + ) + lgbm.fit(X_train, y_train) + models.append(lgbm) + test_preds.append(lgbm.predict(X_test)) + + # 2. XGBoost + xgb = XGBRegressor( + n_estimators=1000, + learning_rate=0.05, + max_depth=6, + random_state=42, + verbosity=0 + ) + xgb.fit(X_train, y_train) + models.append(xgb) + test_preds.append(xgb.predict(X_test)) + + # 3. CatBoost + cat = CatBoostRegressor( + iterations=1000, + learning_rate=0.05, + depth=6, + random_state=42, + verbose=False + ) + cat.fit(X_train, y_train) + models.append(cat) + test_preds.append(cat.predict(X_test)) + + # 简单平均 + ensemble_pred = np.mean(test_preds, axis=0) + + return models, ensemble_pred + +# 带权重的集成 +def weighted_gbm_ensemble(X_train, y_train, X_test, weights=[0.4, 0.3, 0.3]): + """ + 带权重的 GBM 集成 + weights: [lgbm, xgb, cat] + """ + lgbm = LGBMRegressor(random_state=42, verbose=-1).fit(X_train, y_train) + xgb = XGBRegressor(random_state=42, verbosity=0).fit(X_train, y_train) + cat = CatBoostRegressor(random_state=42, verbose=False).fit(X_train, y_train) + + pred_lgbm = lgbm.predict(X_test) + pred_xgb = xgb.predict(X_test) + pred_cat = cat.predict(X_test) + + # 加权平均 + ensemble_pred = ( + weights[0] * pred_lgbm + + weights[1] * pred_xgb + + weights[2] * pred_cat + ) + + return ensemble_pred +``` + +### 数据增强（随机 NaN + 高斯噪声） + +**关键洞察：** 添加噪声提高模型鲁棒性 + +```python +import numpy as np + +def augment_data_with_noise(X_train, y_train, n_augmented=2, nan_ratio=0.1, noise_std=0.01): + """ + 数据增强：随机插入 NaN + 添加高斯噪声 + """ + X_aug_list = [X_train.copy()] + y_aug_list = [y_train.copy()] + + for _ in range(n_augmented): + X_aug = X_train.copy() + + # 1. 随机插入 NaN + mask = np.random.random(X_aug.shape) < nan_ratio + X_aug[mask] = np.nan + + # 2. 添加高斯噪声 + noise = np.random.normal(0, noise_std, X_aug.shape) + X_aug = X_aug + noise + + X_aug_list.append(X_aug) + y_aug_list.append(y_train.copy()) + + # 合并原始数据和增强数据 + X_final = pd.concat(X_aug_list, axis=0, ignore_index=True) + y_final = pd.concat(y_aug_list, axis=0, ignore_index=True) + + return X_final, y_final + +# 使用示例（需要支持 NaN 处理的模型） +# X_aug, y_aug = augment_data_with_noise(X_train, y_train) +# model = LGBMRegressor().fit(X_aug, y_aug) +``` + +### 阈值优化（CGAS=80, SDS=35） + +**关键洞察：** 特定健康分数的阈值可预测严重问题 + +```python +import numpy as np +from scipy.optimize import minimize + +def optimize_thresholds(y_true, y_pred_total): + """ + 优化将 PCIAT-PCIAT_Total 转换为 sii 的阈值 + 默认阈值: [30, 50, 80] + """ + def qwk_loss(thresholds): + t1, t2, t3 = thresholds + pred_sii = np.zeros(len(y_pred_total)) + pred_sii[y_pred_total > t1] = 1 + pred_sii[y_pred_total > t2] = 2 + pred_sii[y_pred_total > t3] = 3 + + # 计算 QWK（简化版本） + from sklearn.metrics import cohen_kappa_score + kappa = cohen_kappa_score(y_true, pred_sii, weights='quadratic') + return -kappa # 最小化负 QWK + + # 初始阈值 + x0 = [30, 50, 80] + + # 优化（确保 t1 < t2 < t3） + bounds = [(0, 40), (40, 60), (60, 100)] + constraints = {'type': 'ineq', 'fun': lambda x: x[1] - x[0]} + + result = minimize(qwk_loss, x0, bounds=bounds, constraints=constraints) + + optimal_thresholds = result.x + print(f"Optimal thresholds: {optimal_thresholds}") + + return optimal_thresholds + +# 特定阈值的使用（4th Place 发现） +def apply_specific_thresholds(pred_total): + """ + 使用特定健康分数阈值 + CGAS=80, SDS=35 可预测严重问题 + """ + pred_sii = np.zeros(len(pred_total)) + + # 默认阈值 + pred_sii[pred_total > 30] = 1 + pred_sii[pred_total > 50] = 2 + pred_sii[pred_total > 80] = 3 + + # 特殊情况：如果有 CGAS 或 SDS 数据，结合判断 + # 这需要原始数据中的这些特征 + # if has_cgas_data and cgas_score > 80: + # pred_sii = 3 + + return pred_sii.astype(int) +``` + +--- + +## Best Practices + +### 表格数据竞赛策略 + +| 策略 | 何时使用 | 说明 | +|------|---------|------| +| **预测中间分数** | 有连续分数和类别标签时 | 预测 PCIAT-PCIAT_Total 比直接预测 sii 更有效 | +| **多 Seed 平均** | Seed 导致结果波动大时 | 多个 seed 训练，取平均减少方差 | +| **高 Fold CV** | 数据量较小或类别不平衡时 | 10-fold stratified KFold 稳定验证 | +| **Pseudo Labeling** | Target 有缺失时 | 用模型预测填充缺失 target | +| **GBM Ensemble** | 单模型不够稳定时 | LGBM + XGBoost + CatBoost 集成 | +| **Tweedie Loss** | 目标变量偏态分布时 | 处理保险、疾病严重程度等偏态数据 | +| **时序聚类特征** | 有时序数据时 | k-means 聚类将时序转为类别特征 | +| **特征清洗** | 特征过多或有噪声时 | 去除高度相关特征，PCA 降维 | + +### QWK 评估指标的优化 + +**Quadratic Weighted Kappa (QWK)：** +- 衡量预测与实际的一致性 +- 分数范围：-1 到 1，越高越好 +- 特点：对严重错误的惩罚更重 + +**优化策略：** + +| 策略 | 效果 | +|------|------| +| **预测中间分数** | 预测连续值比直接分类更精细 | +| **阈值优化** | 在验证集上优化转换阈值 | +| **分层 KFold** | 确保每个 fold 中类别比例一致 | +| **多 Seed 平均** | 减少 seed 引起的 QWK 波动 | + +### 数据增强策略 + +**表格数据增强：** + +| 方法 | 适用场景 | 注意事项 | +|------|---------|---------| +| **随机 NaN** | 提高缺失值鲁棒性 | 需要模型支持 NaN 处理 | +| **高斯噪声** | 提高模型泛化能力 | 噪声强度需调参 | +| **特征 Shuffle** | 特征独立性强时 | 破坏特征相关性时慎用 | +| **SMOTE** | 类别不平衡时 | 可能导致过拟合 | + +### Target 缺失处理 + +**处理策略对比：** + +| 策略 | 优点 | 缺点 | +|------|------|------| +| **删除缺失样本** | 简单直接 | 损失数据，减少样本量 | +| **Pseudo Labeling** | 利用无标签数据 | 可能引入噪声 | +| **两阶段训练** | Stage 1 用有标签，Stage 2 用全部 | 需要精心设计 | + +**推荐做法：** +```python +# 1. CV 计算时不使用 pseudo labels +# 2. 最终模型用 pseudo labels +# 3. 迭代多次，每次用上一轮的预测 +``` + +### 模型选择指南 + +**表格数据竞赛模型选择：** + +| 场景 | 推荐模型 | 理由 | +|------|---------|------| +| **表格数据（主要）** | LightGBM | 速度快，效果好 | +| **类别特征多** | CatBoost | 自动处理类别特征 | +| **需要调参灵活性** | XGBoost | 参数丰富，调参空间大 | +| **数据量大** | LightGBM | 内存效率高 | +| **集成** | LGBM + XGB + Cat | 多样性提升稳定性 | + +**不推荐场景：** +- 神经网络：表格数据通常不如 GBM +- 深度学习：除非有特殊结构（如图嵌入） + +--- + +## Top 10 Solutions Comparison (前 10 名方案对比分析) + +> 基于前排解决方案的横向对比分析，提取共性技术和差异创新 + +### 前 5 名详细对比 + +#### 1st Place - Lennart Haupts + +**核心架构：** GBM Ensemble (LGBM + XGBoost + CatBoost + ExtraTrees) + +**关键技术：** +- **预测 PCIAT-PCIAT_Total**：预测中间分数而非直接预测 sii +- **10-Fold Stratified KFold**：高 fold 提升稳定性 +- **特征清洗**：去除异常特征 +- **PCA 降维**：减少特征噪声 + +**模型组合：** +``` +LGBMRegressor ++ XGBoost Regressors ++ CatBoostRegressor ++ ExtraTreesRegressor +→ Ensemble (平均/加权) +``` + +#### 3rd Place + +**核心架构：** LightGBM with Multi-Seed + +**关键技术：** +- **Multi-Seed Training**：seed 不固定，5-fold 重复 100 次 +- **Optuna 调参**：自动化超参数优化 +- **数据增强**： + - 随机插入 NaN + - 添加高斯噪声 +- **特征工程**：多样化的特征变换 + +**训练策略：** +```python +for seed in range(100): + for fold in range(5): + model = LGBMRegressor(random_state=seed) + train_and_evaluate() +``` + +#### 5th Place + +**核心架构：** Multi-Model Ensemble + +**关键技术：** +- **时序特征工程**：k-means 聚类将时序转为类别特征 +- **Pseudo Labeling**：填充缺失 target +- **多模型集成**：LGB + Cat + XGB + Lasso + NN + +**模型组合：** +``` +LGBM + CatBoost + XGBoost ++ Lasso (线性模型) ++ Neural Network +→ Ensemble +``` + +#### 7th Place + +**核心架构：** LGBM + XGBoost Ensemble + +**关键技术：** +- **Tweedie Loss**：处理偏态分布 +- **Pseudo Labeling**：有效提升分数 +- **缺失值处理**：用中位数填补 +- **Multi-Seed Ensemble**：10 个 seed 平均 + +#### 4th Place (underfit squad) + +**核心发现：** +- **CGAS=80 阈值**：CGAS 分数 > 80 可预测严重问题 +- **SDS=35 阈值**：SDS 分数 > 35 可预测严重问题 + +**关键技术：** +- TabNet（效果不佳） +- 预测 PCIAT-PCIAT_Total +- 特征工程：CGAS, SDS 阈值 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **预测中间分数** | 1st, 3rd, 5th, 7th | 预测 PCIAT-PCIAT_Total 比直接预测 sii | +| **多 Seed 平均** | 3rd, 7th | 减少 seed 引起的方差 | +| **Pseudo Labeling** | 5th, 7th | 填充缺失 target | +| **GBM Ensemble** | 1st, 5th, 7th | LGBM + XGBoost + CatBoost | +| **高 Fold CV** | 1st | 10-fold stratified KFold | +| **特征清洗** | 1st | 去除异常特征，PCA 降维 | + +### 差异创新 + +**1st Place vs 其他：** + +| 方面 | 1st Place | 其他 | +|------|-----------|------| +| **模型组合** | LGBM + XGB + Cat + ExtraTrees | 主要 3 个 GBM | +| **Fold 数量** | 10-fold | 5-fold 或更多 | +| **特征处理** | 严格清洗 + PCA | 较少使用 PCA | + +**3rd Place vs 其他：** + +| 方面 | 3rd Place | 其他 | +|------|-----------|------| +| **训练策略** | 5-fold × 100-seed | 单次训练或少 seed | +| **调参方法** | Optuna 自动调参 | 手动调参 | +| **数据增强** | 随机 NaN + 高斯噪声 | 较少数据增强 | + +**5th Place vs 其他：** + +| 方面 | 5th Place | 其他 | +|------|-----------|------| +| **时序处理** | k-means 聚类 | 较少特殊处理 | +| **模型多样性** | GBM + 线性 + NN | 主要是 GBM | +| **Pseudo Labeling** | 显著有效 | 效果不一 | + +**7th Place vs 其他：** + +| 方面 | 7th Place | 其他 | +|------|-----------|------| +| **Loss 函数** | Tweedie Loss | 主要是 MSE/MAE | +| **缺失值处理** | 中位数填补 | 其他方法 | +| **Ensemble 策略** | 10-seed 平均 | 少 seed 或不用 | + +### Target 预测策略对比 + +| 排名 | 预测目标 | 理由 | +|------|---------|------| +| **1st** | PCIAT-PCIAT_Total | 连续值比类别更精细 | +| **3rd** | PCIAT-PCIAT_Total | 同左 | +| **5th** | PCIAT-PCIAT_Total | 同左 | +| **7th** | PCIAT-PCIAT_Total | 同左 | + +**结论：** 所有前排方案都选择预测中间分数 + +### 特征工程对比 + +| 排名 | 特征工程策略 | +|------|-------------| +| **1st** | 清洗异常特征 + PCA 降维 | +| **3rd** | 随机 NaN + 高斯噪声 | +| **5th** | 时序 k-means 聚类 | +| **7th** | 中位数填补缺失值 | + +### 数据增强对比 + +| 排名 | 数据增强策略 | +|------|-------------| +| **1st** | 较少数据增强 | +| **3rd** | 随机 NaN + 高斯噪声 | +| **5th** | Pseudo Labeling | +| **7th** | Multi-Seed 平均 | + +### Pseudo Labeling 对比 + +| 排名 | 是否使用 | 效果 | +|------|---------|------| +| **1st** | 未提及 | - | +| **3rd** | 未提及 | - | +| **5th** | 使用 | 显著有效 | +| **7th** | 使用 | 显著有效 | + +**结论：** Pseudo Labeling 在 5th 和 7th 有效，可能需要正确实现 + +### 关键数据洞察总结 + +1. **预测中间分数是关键**：所有前排方案都预测 PCIAT-PCIAT_Total +2. **多 Seed 平均有效**：减少 seed 引起的方差 +3. **Pseudo Labeling 需要正确实现**：5th 和 7th 报告有效 +4. **GBM Ensemble 是主流**：LGBM + XGBoost + CatBoost +5. **高 Fold CV 提升稳定性**：10-fold 比 5-fold 更稳定 +6. **特征清洗很重要**：去除异常特征，PCA 降维 +7. **Tweedie Loss 适用于偏态数据**：7th Place 使用 +8. **时序数据可聚类处理**：k-means 将时序转为类别特征 + +### 表格数据竞赛的最佳实践 + +| 方面 | 推荐 | +|------|------| +| **目标预测** | 预测中间分数（如有），而非直接预测类别 | +| **交叉验证** | 高 Fold（10-fold）Stratified KFold | +| **模型选择** | LGBM + XGBoost + CatBoost Ensemble | +| **Seed 策略** | Multi-Seed 平均减少方差 | +| **Target 缺失** | Pseudo Labeling（CV 不用 pseudo） | +| **特征工程** | 清洗异常特征，PCA 降维 | +| **数据增强** | 随机 NaN + 高斯噪声（需模型支持） | +| **Loss 函数** | Tweedie Loss（偏态数据） | +| **时序数据** | k-means 聚类转为类别特征 | + +--- + +## Metadata +| Source | Date | Tags | +|--------|------|------| +| [Child Mind Institute - Problematic Internet Use](https://www.kaggle.com/competitions/child-mind-institute-problematic-internet-use) | 2025-01-22 | 表格数据, QWK, Pseudo Labeling, 多Seed平均, GBM Ensemble, Tweedie Loss | diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/time-series.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/time-series.md new file mode 100644 index 0000000..38f46ab --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/.archive/time-series.md @@ -0,0 +1,10564 @@ +# Time Series Knowledge Base + +> Last updated: 2026-01-23 +> Source count: 10 + +--- + +## Competition Brief (竞赛简介) + +### HMS - Harmful Brain Activity Classification (2024) + +**竞赛背景：** +- **主办方**：Harvard Medical School (哈佛医学院) +- **目标**：自动分类患者脑电图（EEG）中的有害脑活动类型 +- **应用场景**：重症监护室的实时癫痫和异常脑活动检测 +- **社会意义**：减少神经科医生手动分析 EEG 的工作量，提高诊断速度和准确性 + +**任务描述：** +从 19 个电极记录的脑电信号中，分类 6 种有害脑活动类型： +- Seizure（癫痫发作） +- LPD（左侧周期性放电模式） +- GPD（广义周期性放电模式） +- LRDA（右侧周期性放电模式） +- Other（其他类型） +- Seizure 和其他模式的混合 + +**数据集规模：** +- 总样本数：106,800 个标注样本 +- EEG 记录：17,089 个（每个 50 秒，200 Hz 采样） +- Spectrogram：11,138 个（每个 10 分钟，从 EEG 计算的频谱图） +- 标注者：119 名大众标注者 + 20 名专家标注者 + +**数据特点：** +1. **双模态数据**：同时提供原始 EEG 信号和 Spectrogram 图像 +2. **标签不唯一**：每个样本由多人标注，输出是投票分布而非单一标签 +3. **质量不均**：投票数从 1 到 28 不等，双峰分布 +4. **时序对齐**：EEG 的中心 50 秒与 Spectrogram 的中心段对应 + +**评估指标：** +- **KL Divergence**：衡量预测分布与真实分布的差异 +- 这是非对称指标，对 0 值敏感 +- 需要预测 6 个类别的概率分布 + +**竞赛约束：** +- 代码提交：GPU/CPU 环境，最多 9 小时运行时间 +- 模型大小限制：需要考虑推理时间和内存占用 +- 数据隐私：医疗数据，需遵守隐私保护 + +**最终排名：** +- 1st Place: Team Sony - KL-Divergence **0.272332** +- 2nd Place: COOLZ - KL-Divergence ~0.275 +- 3rd Place: nvidia-dd (DIETER) - KL-Divergence ~0.280 +- 总参赛队伍：2,767 支 + +**技术趋势：** +- 前 10 名方案大量使用 CWT/MelSpectrogram 时频分析 +- 几乎所有高分者使用 Clip 归一化：`x.clip(-1024, 1024) / 32` +- 普遍采用 2-Stage Training：Stage 1 全数据，Stage 2 高质量样本 +- 集成策略是获胜关键：最少 3 个模型，最多 6+ 个模型 + +**关键创新：** +- Entmax 替换 Softmax (1st Place)：LB +0.004 提升 +- 数据质量筛选 (3rd Place)：从 100,000+ 行筛选到 6,350 行 +- 3D-CNN 处理 Spectrogram (2nd Place)：保留通道位置信息 +- Superlet CWT (1st Place)：最高时频分辨率 + +**后续影响：** +- 比赛后发表了 Nature 论文，介绍自动化分类方法 +- 该竞赛推动医疗 EEG 分析的自动化发展 +- 多个参赛方案开源，促进了技术共享 + +#### 前排方案详细技术分析 + +**1st Place - Team Sony (yamash, suguuuuu, kfuji, Muku)** + +核心技巧： +- **Entmax 替代 Softmax**：产生稀疏激活，LB +0.004 提升 +- **Superlet CWT 时频分析**：最高时频分辨率，比 STFT 更适合非平稳信号 +- **Bipolar Montage 预处理**：纵向双极导联 + 带通滤波 +- **非负线性回归集成**：4人模型集成，即使过拟合也能保持相关性 +- **2-Stage Training**：Stage 1 全数据，Stage 2 仅高质量样本 (votes ≥10) + +实现细节： +- 使用 1D EEG 信号，通过 CWT 转换为 Scalograms +- Entmax 参数 α=1.5，产生更稀疏的概率分布 +- 集成 4 个模型，使用非负线性回归组合预测 +- Group K-Fold 确保同一 patient 的 EEG 不分散 +- 最终 KL-Divergence：0.272332 + +**2nd Place - COOLZ** + +核心技巧： +- **3D-CNN 处理 Spectrogram**：保留通道位置信息 +- **时频图双路径**：同时利用原始 EEG 和 Spectrogram +- **数据增强组合**：SpecAugment + MixUp + CutMix +- **多尺度特征提取**：不同时间窗口的特征融合 + +实现细节： +- 输入：50 秒 EEG 转换的 Spectrogram（256×256×3 通道） +- 3D-CNN：3D 卷积核同时处理时间和频率维度 +- 两阶段训练：第一阶段 100 epoch，第二阶段 50 epoch +- 最终 KL-Divergence：~0.275 + +**3rd Place - nvidia-dd (DIETER)** + +核心技巧： +- **数据质量筛选**：从 100,000+ 行筛选到 6,350 行高质量样本 +- **高质量样本验证**：仅使用 votes ≥10 的样本建立验证集 +- **频域特征工程**：FFT 频谱 + 功率谱密度特征 +- **集成学习**：多模型集成 + 投票策略 + +实现细节： +- 筛选条件：votes ≥10，consensus 标签一致性高 +- 特征：时域（统计特征）+ 频域（FFT、PSD）+ 时频（CWT） +- 模型：ResNet-1D + EfficientNet-2D 双路径 +- 最终 KL-Divergence：~0.280 + +**4th Place - Grzegorz Gurdziel (ggurdziel)** + +核心技巧： +- **专家混合系统**：多个专家模型针对不同脑活动模式 +- **频带特征分离**：Alpha、Beta、Gamma 等频带独立建模 +- **时序一致性建模**：确保相邻时间步预测的连贯性 +- **双模态融合策略**：1D EEG 和 Spectrogram 的晚期融合 + +实现细节： +- 使用不同 EEG 频段训练专门模型 +- 融合 5-7 个专家模型的预测 +- 频带分离：Delta (0.5-4Hz), Theta (4-8Hz), Alpha (8-13Hz), Beta (13-30Hz), Gamma (30-100Hz) +- 最终 KL-Divergence：~0.283 + +**5th Place - cvtzf** + +核心技巧： +- **Wavelet Scattering Transform**：比 CWT 更稳定的时频表示 +- **深度残差网络**：ResNet-1D 处理 EEG 信号 +- **标签平滑策略**：处理标签模糊性 +- **模型蒸馏**：从大模型蒸馏到小模型提升推理速度 + +实现细节： +- 使用 Scattering Transform 替代传统 CWT +- ResNet-1D 架构：20-30 层深度 +- 标签平滑系数：0.1-0.2 +- 最终 KL-Divergence：~0.285 + +**6th Place - CHRTL Team** + +核心技巧： +- **注意力机制**：Self-Attention 捕获长程依赖 +- **多尺度特征提取**：并行处理不同时间窗口 +- **数据增强组合**：Time masking + Frequency masking + MixUp +- **集成策略优化**：加权平均代替简单平均 + +实现细节： +- Transformer 架构：8-12 层注意力层 +- 多尺度窗口：[5s, 10s, 20s, 50s] +- SpecAugment 风格的数据增强 +- 最终 KL-Divergence：~0.287 + +**7th Place - Tung Le (tungld)** + +核心技巧： +- **自适应频谱图**：根据 EEG 信号特性动态调整频谱参数 +- **类别平衡采样**：处理类别不平衡问题 +- **两阶段集成**：第一阶段多样模型，第二阶段精选最优组合 +- **后处理校准**：Platt Scaling 校准概率输出 + +实现细节： +- 自适应 Mel 频率：n_mels 从 64-256 动态调整 +- 过采样少数类，欠采样多数类 +- 第一阶段 20 个模型，第二阶段精选 8 个 +- Platt Scaling 校准：使用验证集学习校准参数 +- 最终 KL-Divergence：~0.289 + +**8th Place - Vialactea (Volodymyr)** + +核心技巧： +- **信号重建预处理**：去除 EEG 信号中的噪声和伪影 +- **频域归一化**：在频域进行标准化，更鲁棒 +- **时频图分割**：将长 EEG 分割为重叠片段处理 +- **模型集成多样性**：不同架构（ResNet, EfficientNet, DenseNet） + +实现细节： +- 信号重建：ICA 去除眼电、肌电伪影 +- 频域归一化：每通道独立标准化 +- 片段长度：10 秒，重叠 50% +- 5 种不同架构的模型集成 +- 最终 KL-Divergence：~0.291 + +**9th Place - Warati Kaewchada** + +核心技巧： +- **特征工程自动化**：AutoML 自动搜索最优特征组合 +- **时序建模增强**：BiLSTM + Attention 组合 +- **多视角学习**：从不同电极视角学习特征 +- **早停策略优化**：基于 KL-Divergence 的早停 + +实现细节： +- AutoML 工具：AutoGluon/TPOT +- BiLSTM：2 层双向，隐藏层 256 单位 +- 多视角：额叶区、颞叶区、顶叶区、枕叶区 +- 早停耐心值：15-20 epoch +- 最终 KL-Divergence：~0.293 + +**10th Place - Dmitry Ershov (dim)** + +核心技巧： +- **迁移学习**：从预训练 EEG 模型迁移到本任务 +- **领域适应**：适应不同患者间的 EEG 差异 +- **半监督学习**：利用未标注 EEG 数据 +- **知识蒸馏**：教师-学生模型架构 + +实现细节： +- 预训练模型：在大规模 EEG 数据集上预训练 +- 领域适应：对抗训练消除患者间差异 +- 半监督：一致性正则化 + 伪标签 +- 知识蒸馏：大教师模型 → 小学生模型（3:1 压缩） +- 最终 KL-Divergence：~0.295 + +--- + +### Child Mind Institute - Detect Sleep States (2023) + +**竞赛背景：** +- **主办方**：Child Mind Institute +- **目标**：从手腕佩戴的加速度计数据中检测睡眠事件（入睡 onset 和觉醒 wakeup） +- **应用场景**：睡眠健康监测、可穿戴设备、睡眠质量分析 +- **社会意义**：自动化睡眠监测，减少人工标注成本，改善睡眠障碍诊断 + +**任务描述：** +从 5 秒间隔的加速度计时间序列数据中检测两类事件： +- **Onset**：入睡时刻 +- **Wakeup**：觉醒时刻 + +**数据集规模：** +- 总样本数：~500 个多日记录 +- 数据点：每个 series 最多 17280 步（24 小时 × 12 步/分钟 × 60 分钟） +- 特征：anglez（手臂角度）、enmo（加速度计信号） +- 标注：每夜 1 个 onset + 1 个 wakeup 事件 + +**数据特点：** +1. **稀疏标注**：17280 步中仅有 2 步有标签（0.01%） +2. **标签偏移**：真实事件总是发生在 hh:mm:00 整分钟时刻 +3. **周期性模式**：存在 24 小时周期性重复的数据（未标注事件） +4. **评估容差**：多个 tolerance 窗口（1, 3, 5, 7.5, 10, 12.5, 15, 20, 25, 30 分钟） + +**评估指标：** +- **Average Precision (AP)**：多 tolerance 平均 +- 对每个 tolerance 窗口，计算最高置信度匹配的 AP +- 最终分数 = 各 tolerance AP 的平均 × 各类别 AP 的平均 + +**竞赛约束：** +- 提交格式：series_id, step, event, score +- 每个系列最多预测多个事件（需后处理筛选） +- 事件必须成对（onset + wakeup） + +**最终排名：** +- 1st Place: shimacos vs sakami vs kami - Private LB: **0.852** +- 2nd Place: K-Mat - Private LB: ~0.850 +- 3rd Place: cucutzik - Private LB: ~0.849 +- 总参赛队伍：1,877 支 + +**技术趋势：** +- 几乎所有前排方案使用**两阶段建模**：5秒概率预测 → 1分钟精化 +- **分钟偏差处理**是关键涨分点：事件总是发生在整分钟 +- **未标注事件检测**：利用周期性识别缺失标签 +- **后处理优化**：针对 tolerance 指标的 greedy search +- **Daily Normalization**：按天归一化 2nd level 预测 + +**关键创新：** +- **15/45秒技巧** (1st Place)：针对 tolerance 边缘优化 +- **两阶段建模** (1st, 2nd)：5秒检测 + 1分钟精化 +- **Error Modeling** (2nd Place)：将差分变化转为分类任务 +- **数据增强** (3rd Place)：序列反转提升 CV +0.01 + +**后续影响：** +- 该竞赛推动可穿戴设备睡眠监测技术发展 +- 前排方案广泛开源，成为事件检测任务的参考 +- 后处理优化策略被后续竞赛采用 + +#### 前排方案详细技术分析 + +**1st Place - shimacos vs sakami vs kami (kami, sakami0000, shimacos)** + +核心技巧： +- **15/45秒技巧**：针对 tolerance 边缘优化，事件可能发生在整点前/后 15/45 秒 +- **两阶段建模**：Stage 1（5秒概率预测）→ Stage 2（1分钟精化） +- **Daily Normalization**：按天归一化 2nd level 预测，减少个体差异 +- **Greedy Post-Processing**：针对 AP 指标优化，选择最佳事件对 +- **衰减目标**：按 tolerance_steps 加权 + epoch 衰减 + +实现细节： +- Stage 1：LSTM + MLP，输出 5 秒间隔的概率预测 +- Stage 2：基于 Stage 1 预测，在 1 分钟窗口内精化事件位置 +- 考虑事件必须在整分钟时刻（label shift 0） +- 最终 Private LB：0.852 + +**2nd Place - K-Mat** + +核心技巧： +- **Error Modeling**：将差分变化转为分类任务（上升/下降/平稳） +- **序列反转数据增强**：提升 CV +0.01 +- **集成策略**：多个模型的不同配置集成 +- **后处理优化**：考虑事件对的约束条件 + +实现细节： +- 输入特征：anglez + enmo + 时间戳特征 +- 模型架构：LSTM + Attention 机制 +- Error Modeling：预测信号变化模式，辅助事件检测 +- 最终 Private LB：~0.850 + +**3rd Place - cucutzik** + +核心技巧： +- **序列反转数据增强**：镜像序列，增加数据多样性 +- **未标注事件利用**：利用周期性模式识别未标注事件 +- **时间窗口滑动**：多尺度窗口检测事件 +- **事件对约束**：确保 onset 和 wakeup 成对出现 + +实现细节： +- 数据增强：时间序列反转，保持标签一致性 +- 模型集成：3-5 个不同随机种子的模型 +- 后处理：基于置信度和时间约束筛选事件对 +- 最终 Private LB：~0.849 + +**4th Place - RSI (Recurring Sleep Inertia)** + +核心技巧： +- **周期性模式检测**：自动识别 24 小时周期性睡眠模式 +- **多时域建模**：5 秒、30 秒、5 分钟多尺度预测 +- **事件链预测**：预测 onset-wakeup 事件链而非单独事件 +- **置信度校准**：温度缩放校准预测概率 + +实现细节： +- 周期性检测：FFT 频谱分析识别 24 小时周期 +- 多尺度模型：不同时间窗口的 LSTM 集成 +- 事件链：onset → [sleep] → wakeup 约束 +- 最终 Private LB：~0.848 + +**5th Place - Andris (Andris Apinis)** + +核心技巧： +- **特征工程自动化**：时域、频域、时频域特征自动提取 +- **XGBoost 集成**：梯度提升树处理统计特征 +- **深度学习混合**：LSTM + XGBoost 混合架构 +- **滑动窗口集成**：多窗口大小预测融合 + +实现细节： +- 特征：统计特征（均值、方差、峰度）+ 频域特征（FFT 功率谱） +- XGBoost：100+ 棵树，max_depth=8 +- 混合架构：LSTM 处理时序 + XGBoost 处理特征 +- 滑动窗口：[30s, 60s, 120s, 300s] +- 最终 Private LB：~0.847 + +**6th Place - CPMP (Cyprien) 1000 +2. **混合叫声**：一个音频可能包含多种鸟类 +3. **背景噪声**：风声、雨声、人声等环境噪声 +4. **未标注数据**：大量未标注 soundscape 可用于伪标签 + +**评估指标：** +- **AUC-ROC**：每个类别单独计算，然后取平均 +- 需要预测所有 182 个类别的概率 +- 对正负样本不平衡较为鲁棒 + +**竞赛约束：** +- **推理限制**：仅 CPU，最多 120 分钟 +- 这是 BirdCLEF 2024 最关键的约束 +- 需要优化推理速度，不能使用太大模型 + +**前排方案排名：** +| 排名 | 团队 | Private LB | Public LB | 关键技术 | +|------|------|------------|-----------|----------| +| **1st** | Team Kefir | **0.690** | **0.729** | Statistics T 过滤, Google Classifier 预标注, Min() Ensemble | +| **2nd** | ADSR | 0.685 | 0.733 | 伪标签迭代训练, Checkpoint Soup, 邻居窗口后处理 | +| **3rd** | NVBird | 0.68+ | 0.72+ | EfficientViT 快速推理, 两级模型架构 | +| **4th** | - | ~0.68 | ~0.72 | 邻居窗口 0.5 倍后处理 | +| **5th+** | - | ~0.67 | ~0.71 | 各种集成策略 | + +**技术演进（与 BirdCLEF 2023 对比）：** +| 技术点 | BirdCLEF 2023 | BirdCLEF 2024 | +|--------|---------------|---------------| +| **模型架构** | EfficientNetV2 + SED | EfficientNet B0 + RegNetY | +| **数据策略** | Xeno-Canto 外部数据重要 | 只使用 2024 数据更优 | +| **损失函数** | BCE + FocalLoss | CE Loss（训练用 softmax，推理用 sigmoid）| +| **伪标签** | 高低阈值筛选 | Google Classifier 预标注 + 小系数 | +| **推理优化** | ONNX | OpenVINO | +| **集成策略** | 简单平均 | Min() ensemble 降低不确定预测 | + +#### 前排方案详细技术分析 + +**1st Place - Team Kefir (vkop, great_alex, etc.)** + +核心技巧： +- **Statistics T 噪声过滤**：T = std + var + rms + pwr，使用 0.8 分位数过滤噪声数据 +- **Google Bird Classifier 预标注**：使用 Google 模型过滤低质量数据，添加伪标签（系数 0.05） +- **CE Loss + Sigmoid 推理**：训练用 CE Loss + Softmax（多分类），推理用 Sigmoid（多标签） +- **Min() Ensemble**：降低不确定预测，比简单平均更稳定 +- **OpenVINO 推理优化**：固定输入大小，加速推理 +- **只使用 2024 数据**：不使用外部数据更优 + +实现细节： +- 使用 efficientnet_b0_ns 和 regnety_008 架构 +- 6 模型集成：mean[3 efficientnet, 3 regnety] +- 训练时使用 CE Loss + Softmax，推理时使用 Sigmoid +- 最终 Private LB：0.690，Public LB：0.729 + +**2nd Place - ADSR** + +核心技巧： +- **伪标签迭代训练**：3 次迭代循环，集成自我改进 +- **Checkpoint Soup**：平均 13-50 epoch checkpoint，代替 early stopping +- **邻居窗口后处理**：相邻窗口 0.5 倍权重 +- **数据增强**：局部和全局时间/频率拉伸 +- **只用前 5 秒数据**：后续信息贡献小 + +实现细节： +- EfficientNet B0 backbone +- 不同 Mel 参数、数据子集、图像大小实现模型多样性 +- 模型间伪标签概率：25-45% +- 最终 Private LB：0.685，Public LB：0.733 + +**3rd Place - NVBird (Theo Viel)** + +核心技巧： +- **EfficientViT 快速推理**：b0/b1/m3 变体，ONNX 优化 +- **两级模型架构**：第一级（CNN + EfficientViT）→ 第二级（EfficientViT-b0 + MNASNet-100） +- **添加性 Mixup**：两段音频混合，标签取 max +- **5 fold 40 分钟推理**：ONNX 加速 + +实现细节： +- 第一级：多种 CNN（efficientnets, mobilenets, tinynets, mnasnets）和 EfficientViT +- 第二级：EfficientViT-b0 + MNASNet-100，使用伪标签训练 +- 推理时间：5 fold 40 分钟 +- 最终 Private LB：0.68+，Public LB：0.72+ + +--- + +### BirdCLEF 2024 关键创新 + +1. **Statistics T 噪声过滤（1st Place）** + ```python + # T = std + var + rms + pwr + # 使用 0.8 分位数过滤噪声数据 + T = std + var + rms + pwr + threshold = np.quantile(T, 0.8) + clean_data = data[T < threshold] + ``` + +2. **Google Bird Classifier 预标注（1st Place）** + - 使用 Google 模型过滤低质量数据 + - 如果 Google 预测与 primary label 不匹配，丢弃该 chunk + - 如果与 secondary label 匹配，替换 primary label + - 添加 Google 预测作为伪标签（系数 0.05） + +3. **CE Loss + Sigmoid 推理（1st Place）** + - 训练：CE Loss + Softmax（多分类问题） + - 推理：Sigmoid（多标签预测） + - 原因：数据大多只有 1-2 个标签，可视为多分类 + +4. **Min() Ensemble（1st Place）** + ```python + # 降低不确定预测 + predictions = np.min([model1_pred, model2_pred, model3_pred], axis=0) + ``` + +5. **伪标签迭代训练（2nd Place）** + - 3 次迭代循环 + - 每次用新集成生成伪标签 + - 25-45% 概率添加伪标签数据 + +6. **Checkpoint Soup（2nd Place）** + - 平均 13-50 epoch 的 checkpoint + - 代替 early stopping + +**与 BirdCLEF+ 2025 的差异：** +| 维度 | BirdCLEF 2024 | BirdCLEF+ 2025 | +|------|---------------|----------------| +| **物种数量** | 182 种鸟类 | 206 种（鸟类+两栖+哺乳+昆虫）| +| **评估指标** | AUC-ROC | Multi-Label AUC-ROC | +| **推理限制** | 120 分钟 CPU | 90 分钟 CPU | +| **数据策略** | 不用外部数据 | Xeno-Canto 预训练重要 | +| **关键创新** | Statistics T 过滤 | Noisy Student + 自蒸馏 | + +**参考资料：** +- [1st Place Writeup](https://www.kaggle.com/competitions/birdclef-2024/writeups/team-kefir-1st-place-solution) +- [2nd Place Solution (Japanese)](https://zenn.dev/yuto_mo/articles/85eee84a753159) +- [3rd Place GitHub](https://github.com/TheoViel/kaggle_birdclef2024) +- [1st Place Explanation (Japanese)](https://zenn.dev/yuto_mo/articles/ad43c630729073) + +**4th Place - Team** + +核心技巧： +- **邻居窗口 0.5 倍后处理**：相邻窗口 0.5 倍权重平滑 +- **多模型集成**：不同 backbone 和参数组合 +- **数据增强优化**：SpecAugment 参数调优 +- **推理加速**：ONNX + OpenVINO 优化 + +实现细节： +- 后处理：相邻窗口权重 0.5，中心窗口权重 1.0 +- 模型：EfficientNet B0/B1 + RegNet Y +- 最终 Private LB：~0.68，Public LB：~0.72 + +**5th Place - HiddenLayer** + +核心技巧： +- **两级训练策略**：第一阶段全数据，第二阶段高质量数据 +- **高质量样本筛选**：基于置信度和预测一致性 +- **Mel 频谱图优化**：n_mels=128, fmin=64, fmax=16000 +- **集成多样性**：不同随机种子和初始化 + +实现细节： +- 两级训练：Stage 1 全数据，Stage 2 筛选高置信度样本 +- 筛选条件：预测置信度 >0.7，多模型预测一致 +- Mel 参数：128 Mel bins, 10ms hop length +- 最终 Private LB：~0.677 + +**6th Place - BirdWhisperer** + +核心技巧： +- **Whisper 架构改编**：音频编码器 + 解码器结构 +- **时间掩码增强**：SpecAugment 时间掩码变体 +- **标签平滑**：防止过拟合 +- **学习率预热**：前 5 epoch warmup + +实现细节： +- Whisper改编：使用音频编码器，忽略解码器 +- 时间掩码：随机掩码 10-30% 连续时间步 +- 标签平滑：ε=0.1 +- 学习率预热：linear warmup，peak lr=1e-3 +- 最终 Private LB：~0.676 + +**7th Place - AudioZenith** + +核心技巧： +- **频域数据增强**：频率掩码、频率混合 +- **多尺度 Mel 频谱**：64/128/256 Mel bins 多尺度 +- **模型集成**：加权平均代替简单平均 +- **后处理优化**：基于物种出现时间的后处理 + +实现细节： +- 频域增强：随机屏蔽 5-15% 频带 +- 多尺度：并行训练不同 Mel 参数模型 +- 加权集成：基于验证集性能学习权重 +- 后处理：考虑物种日活动时间模式 +- 最终 Private LB：~0.675 + +**8th Place - SpecDroid** + +核心技巧： +- **Spectrogram 数据增强**：时间/频率 masking + mixup +- **ResNeSt 架构**：Split-Attention 机制 +- **Focal Loss**：处理类别不平衡 +- **TTA（测试时增强）**：多次预测平均 + +实现细节： +- ResNeSt：26-9t layers, Split-Attention blocks +- Focal Loss：γ=2.0, α=0.25 +- TTA：5 次不同增强预测平均 +- 最终 Private LB：~0.674 + +**9th Place - MelMaster** + +核心技巧： +- **自适应 Mel 频谱**：根据音频长度动态调整参数 +- **全局平均池化**：替换全连接层减少参数 +- **混合精度训练**：FP16+FP32 混合精度 +- **梯度累积**：模拟大 batch size + +实现细节： +- 自适应 Mel：短音频 n_mels=256，长音频 n_mels=128 +- GAP：全局平均池化 + 单层分类器 +- 混合精度：AMP 自动损失缩放 +- 梯度累积：accumulation_steps=4 +- 最终 Private LB：~0.673 + +**10th Place - SoundScape** + +核心技巧： +- **背景噪声去除**：基于能量的噪声门限 +- **音频切片策略**：智能选择包含鸟叫的片段 +- **轻量级模型**：MobileNetV3 快速推理 +- **知识蒸馏**：从大模型蒸馏到小模型 + +实现细节： +- 噪声门限：能量阈值 -60dB，去除静音片段 +- 音频切片：选择能量 >阈值的 5 秒片段 +- MobileNetV3：small 变体，onnx 优化 +- 知识蒸馏：EfficientNet-B0 → MobileNetV3，3:1 压缩 +- 最终 Private LB：~0.672 + +--- + +### BirdCLEF+ 2025 - Multi-Taxonomic Sound Identification (2025) + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology, LifeCLEF, Chemnitz University of Technology +- **目标**：通过声学特征识别研究不足的物种（鸟类、两栖、哺乳、昆虫） +- **应用场景**：生物多样性监测、生态恢复项目评估、被动声学监测（PAM） +- **社会意义**：自动化物种识别，支持保护行动的调整和优化 + +**任务描述：** +从连续音频数据中识别 206 个物种的声音： +- **鸟类**：主要分类群 +- **两栖动物**：青蛙和蟾蜍 +- **哺乳动物**：各种哺乳动物声音 +- **昆虫**：昆虫鸣声 + +**数据集规模：** +- 训练音频：~20,000 个标注文件（5 秒片段） +- 训练音景：未标注的连续音频（train_soundscapes） +- 测试音频：~200 个连续音频文件（需 5 秒滑动窗口预测） +- 物种数量：206 个物种 + +**数据特点：** +1. **多分类群**：涵盖鸟类、两栖、哺乳、昆虫四大类 +2. **未标注数据丰富**：大量未标注的 soundscape 数据可用于半监督学习 +3. **长尾分布**：稀有物种样本极少（某些物种 <10 个样本） +4. **领域偏移**：训练数据（哥伦比亚）与测试数据存在分布差异 +5. **背景噪声**：包含人声、环境噪声等干扰 + +**评估指标：** +- **宏平均 ROC-AUC**：跳过没有真实正标签的类别 +- 每个物种独立计算 AUC，然后宏平均 +- 对每个 row_id（5 秒窗口），预测各物种存在概率 + +**竞赛约束：** +- **90 分钟 CPU 推理限制**：这是最关键的约束 +- 提交格式：row_id × 206物种的概率矩阵 +- 需要高效推理（ONNX、OpenVINO 等） + +**最终排名：** +- 1st Place: Nikita Babych - Private LB **0.927** +- 2nd Place: Volodymyr Vialactea - Private LB ~0.926 +- 3rd Place: Team - Private LB ~0.925 +- 总参赛队伍：~2,000+ 支 + +**技术趋势：** +- **半监督学习**：伪标签技术被所有前排方案使用 +- **SED 模型**：Sound Event Detection 架构成为主流 +- **数据增强**：MixUp、Sumix、SpecAugment 广泛应用 +- **模型集成**：5-20 个模型的集成是常态 +- **领域适应**：针对训练-测试分布差异的各种处理策略 + +**关键创新：** +- **多迭代 Noisy Student** (1st Place)：MixUp + 幂次变换伪标签 +- **Soft AUC Loss** (4th Place)：支持软标签的 AUC 损失函数 +- **自蒸馏技术** (5th Place)：迭代丰富次要标签 +- **Silero VAD 预处理** (5th Place)：去除人声干扰 +- **滑动窗口推理** (1st Place)：帧预测平均，避免数据丢弃 + +**前排方案总结（Top 14）：** + +| 排名 | 团队/作者 | 核心技术 | 模型 | 关键创新 | +|------|----------|---------|------|----------| +| **1st** | Nikita Babych | Multi-Iterative Noisy Student + MixUp | SED模型 | 幂次变换伪标签 + 滑动窗口推理 | +| **2nd** | Volodymyr Vialactea | Pseudo-labeling + 预训练 | tf_efficientnetv2_s + eca_nfnet_l0 | Xeno-Canto 预训练 + 5秒片段 | +| **3rd** | - | 20 模型集成（10 CNN + 10 SED） | 多种 backbone | BirdCLEF 2023+2025 数据合并 | +| **4th** | dylan.liu | Soft AUC Loss + 半监督 | EfficientNet 系列 | 自定义 soft AUC 损失函数 | +| **5th** | Noir | Self-Distillation | EfficientNet 系列 | Silero VAD + 三阶段自蒸馏 | +| **6th** | - | SED + 自定义 AttBlockV2 | tf_efficientnet_b3 | segmentwise_logit 伪标签 | +| **7th** | - | 伪标签迭代训练 | 多种 CNN | BirdNET 提取音频片段 | +| **8th** | - | 硬 Mixup + 双向蒸馏 | SED + CNN | 在线伪标签 + 帧级监督 | +| **9th** | - | 两阶段策略 | SED + CNN | RMS 采样 + FocalBCE | +| **10th** | lhwcv | 领域适应 + 改进损失 | 多模型 | 高低阈值筛选 + 负样本惩罚 | +| **11th** | - | CE Loss + 熵值筛选 | tf_efficientnetv2_b3/s | 206→316 类扩展 | +| **12th** | - | Checkpoint Soups + EMA | 12 个 SED 模型 | OpenVINO 推理加速 | +| **13th** | H.K.Z. | 领域偏移处理 | seresnext26t + v2_b3 | Sumix + 罕见物种模型 | +| **14th** | - | 知识蒸馏 | tf_efficientnetv2_m | 块级伪标签 + 加权蒸馏 | + +#### 前排方案详细技术分析 + +**1st Place - Multi-Iterative Noisy Student (Nikita Babych)** + +核心技巧： +- **多迭代 Noisy Student 自训练**：MixUp + 幂次变换伪标签，固定混合权重 0.5 +- **SED 帧预测推理**：相邻音频块的帧预测平均（1D 滑动窗口），避免丢弃有价值数据 +- **幂次变换伪标签**：直接温度缩放会提高噪声概率，幂次变换可防止噪声放大 +- **Xeno-Canto 扩展数据**：针对两栖类和昆虫类标签组训练单独模型 + +实现细节： +- 使用 20 秒音频块处理 +- 伪标签采样器根据每个 soundscape 标签最大值之和分配权重 +- 推理通过平均相邻块重叠的帧预测，然后平滑和 delta shift + +**2nd Place - Pseudo-labeling + 预训练 (Volodymyr Vialactea)** + +核心技巧： +- **Xeno-Canto 预训练**：下载外部数据并清洗，过滤当年比赛物种避免数据泄漏 +- **5 秒随机片段**：尝试多种采样方法减少误报 +- **预训练模型微调**：AUC 从 0.83-0.84 跳升至 0.86-0.87 +- **多种验证策略**：确保每个类至少有一个样本 +- **平衡采样策略**：平衡、平方和上采样等多种策略 + +实现细节： +- 使用 tf_efficientnetv2_s 和 eca_nfnet_l0 作为骨干网络 +- Spec → 2D CNN 方法 +- 保留 RandomFiltering 和 SpecAug 设置 + +**3rd Place - 20 模型集成 (Team)** + +核心技巧： +- **BirdCLEF 2023+2025 数据合并**：结合历年数据扩充训练集 +- **20 模型集成**：10 CNN + 10 SED 模型 +- **两组 Mel 参数**：n_mels=128 和 96 探索不同频谱分辨率 +- **随机抽样代替前 5 秒**：基于 RMS 的抽样方法 +- **人声作为背景噪声**：提高环境适应性 + +实现细节： +- 使用多种 backbone：tf_efficientnet、mnasnet 等 +- CutMix、MixUp、Sumix 数据增强 +- Focal BCE 损失函数处理类别不平衡 +- 所有模型导出为 ONNX 格式 + +**4th Place - Soft AUC Loss (dylan.liu)** + +核心技巧： +- **Soft AUC 损失函数**：支持软标签，解决 AUC 损失不支持软标签问题 +- **半监督学习**：10 个 SED 模型对前 10 秒音频生成伪标签 +- **音频混合增强**：两段音频混合，标签取最大值 + +实现细节： +- Soft AUC 损失使 LB 从 0.850 提升到 0.901 +- 使用 EfficientNet 和 EfficientNetV2 系列 +- 10 个使用 EfficientNet 系列模型训练的 SED 模型 + +**5th Place - Self-Distillation (Noir)** + +核心技巧： +- **Silero VAD 数据清洗**：检测并去除包含人声的音频片段 +- **自蒸馏技术**：迭代将模型预测作为新标签丰富次要标签 +- **三阶段训练**： + 1. 初始训练 + 2. 仅使用 train_audio 自蒸馏 + 3. 结合 train_audio 和 train_soundscapes 自蒸馏 + +实现细节： +- 样本量 <30 的类别手动筛选 +- 清洗后文件使用前 60 秒，其他文件使用前 30 秒 +- 样本量 <20 的类别复制以平衡数据集 + +**6th Place - SED + AttBlockV2** + +核心技巧： +- **自定义 AttBlockV2**：通过 softmax 和 tanh 归一化，默认使用 sigmoid +- **segmentwise_logit 伪标签**：clipwise_output 值过小，使用 segmentwise_logit 生成伪标签 +- **伪标签迭代**：多轮训练，每轮使用多模型的 segmentwise_logit 输出 + +实现细节： +- 使用 tf_efficientnet_b3.ns_jft_in1k 和 tf_efficientnetv2_b3.in21k +- nn.BCEWithLogitsLoss 对 clipwise_output 和 segmentwise_logit 进行训练 + +**7th Place - BirdNET 片段提取** + +核心技巧： +- **BirdNET 提取音频片段**：对 train_soundscapes 推断，提取置信度 >0.1 的片段 +- **50% 伪标签概率**：训练期间随机从 soundscape 采样，50% 概率使用伪标签 +- **模型融合限制**：3 个模型足够，过多会损害分数 + +实现细节： +- 伪标签需归一化：`labels = labels - np.min(labels)` +- 使用原始信号模型和简单 CNN 增加集成多样性 + +**8th Place - 硬 Mixup + 双向蒸馏** + +核心技巧： +- **硬 Mixup**：数据混合后，损失为混合标签的损失 +- **在线伪标签**：训练过程中在线生成伪标签（片段级和帧级） +- **双向知识蒸馏**：不同模型相互学习 +- **MLD 知识蒸馏**：按 2023 年方案进行 + +实现细节： +- 伪标签阈值选择 0.4，平衡假阴性和假阳性 +- 两个 SED 模型 + 一个 CNN 模型 + +**9th Place - 两阶段策略** + +核心技巧： +- **RMS 采样**：基于信号能量的采样方法，比随机采样更有效 +- **去除 50% 人声**：完全去除会影响性能 +- **两阶段模型**： + 1. SED + CNN 模型（FocalBCE 和 CE+BCE） + 2. 伪标签再训练（提升 0.02+） + +实现细节： +- TTA：10 秒片段和 2 秒窗口长度 +- 原始信号：PitchShift、Shift、Sumix +- Mel-Spectrogram：Mixup2、Time masking、FilterAugment、FrequencyMasking、PinkNoise + +**10th Place - 领域适应 + 改进损失 (lhwcv)** + +核心技巧： +- **高低阈值筛选**：从 stage1 模型生成软标签，筛选可信正负样本 +- **负样本惩罚策略**：对置信度较低的正样本也进行惩罚 +- **多分辨率 Mel 参数**：384x160、384x256、320x192、320x160 等 + +实现细节： +- SED + CE loss 基线 +- 平滑核预测平滑，alpha 值根据参考频率动态调整 + +**11th Place - CE Loss + 类扩展** + +核心技巧： +- **类别扩展**：从 206 类扩展至 316 类 +- **熵值筛选**：选择高质量伪标签 +- **CE Loss 替代 BCE**：性能从 0.83 提升至 0.88 + +实现细节： +- 最大样本 500，<10 样本类别上采样 +- 集成 5 个 v2b3 + 1 个 v2s 模型 + +**12th Place - Checkpoint Soups + EMA** + +核心技巧： +- **Checkpoint Soups**：平均第 30-50 epoch 权重，缓解稀有类宏 AUC 不稳定 +- **EMA（指数移动平均）**：衰减系数 0.999 +- **少数类子集训练**：冻结所有类预训练主干，仅对少数类 SED 头训练 + +实现细节： +- 12 个 OpenVINO 转换的 SED 模型 +- 加权移动平均 + 文件级平均概率后处理（提升 0.07-0.08） +- 三种不同管道类型集成 + +**13th Place - 领域偏移处理 (H.K.Z.)** + +核心技巧： +- **Sumix 替代 Mixup**：在原始音频信号上应用 +- **移除人声**：减少训练-测试分布差异 +- **罕见物种模型**：训练特定罕见物种模型，显著提升分数 + +实现细节： +- 基于 2023 年第二名代码训练基础 SED 模型 +- 四个步骤：基础模型、伪标签增强、模型集成、罕见物种模型 + +**14th Place - 知识蒸馏** + +核心技巧： +- **块级伪标签**：来自教师模型的 10 秒块级伪标签 +- **加权蒸馏**：全音频平均伪标签（0.3）+ 块级伪标签（0.7） +- **多轮蒸馏**：每轮基于 LB 改进选择最佳教师模型 + +实现细节： +- 仅使用 tf_efficientnetv2_m.in21k +- 邻近剪辑平滑：权重 0.1、0.8、0.1 +- OpenVINO 加速推理 + +--- + +## Original Summaries + +### HMS - Harmful Brain Activity Classification (2024) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/hms-harmful-brain-activity-classification) +**Category:** Time Series (EEG 信号分类) +**Summary:** 患者脑波有害活动分类竞赛。数据包含 1D EEG 信号（50秒，200Hz）和 2D Spectrogram（10分钟），需要预测专家投票分布。**1st Place: Team Sony** (yamash, suguuuuu, kfuji, Muku)，KL-Divergence 0.272332。 + +**Key Techniques:** +- **CWT (连续小波变换)**: 将 EEG 转换为 Scalograms，比 STFT 更适合非平稳信号 +- **Entmax**: 用 entmax 替换 softmax 实现稀疏激活 +- **Bipolar Montage**: 纵向双极导联 + 带通滤波预处理 +- **Ensemble**: 4人模型集成，使用非负线性回归 +- **2-Stage Training**: Stage1 全数据，Stage2 仅高质量样本 (votes ≥10) + +**Results:** 1st place (KL-Divergence: 0.272332, 2767 teams) + +### Child Mind Institute - Detect Sleep States (2023) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states) +**Category:** Time Series (事件检测) +**Summary:** 手腕加速度计睡眠事件检测竞赛。数据包含 anglez 和 enmo 两特征，5秒间隔，需检测 onset 和 wakeup 事件。**1st Place: shimacos vs sakami vs kami** (kami, sakami0000, shimacos)，Private LB 0.852。 + +**Key Techniques:** +- **两阶段建模**：5秒概率预测 → 1分钟精化 +- **15/45秒技巧**：针对 tolerance 边缘优化 +- **Daily Normalization**：按天归一化 2nd level 预测 +- **Greedy Post-Processing**：针对 AP 指标优化 +- **衰减目标**：按 tolerance_steps 加权 + epoch 衰减 + +**Results:** 1st place (Private LB: 0.852, 1877 teams) + +**Resources:** +- [1st Place Solution (Kaggle)](https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459715) +- [1st Place GitHub](https://github.com/sakami0000/child-mind-institute-detect-sleep-states-1st-place) +- [Comprehensive Chinese Summary](https://zhuanlan.zhihu.com/p/675470807) +- [Japanese Presentation](https://speakerdeck.com/unonao/shui-mian-konpe-1st-place-solution) + +### CMI - Detect Behavior with Sensor Data (2025) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/cmi-detect-behavior-with-sensor-data) +**Category:** Time Series (多模态行为识别) +**Summary:** 多模态传感器数据行为识别竞赛。数据包含 IMU、THM、TOF 三种传感器，需分类 18 种手势行为（BFRB vs 非BFRB）。**1st Place: Devin | Ogurtsov | zyz** (Andrey Ogurtsov, Devin, zyz)。 + +**Key Techniques:** +- **多模态融合**：IMU + THM + TOF 特征融合 +- **TOF 图像化**：2×2 正方形 9 个区域平均 +- **四元数 6D 表现**：避免四元数不连续性 +- **阶段感知 Attention**：分阶段（Transition/Pause/Gesture）应用不同 attention +- **匈牙利算法**：全局最优标签分配 +- **数据增强**：mixup, cutmix, timeshift, rotation + +**Results:** 1st place (2657 teams) + +**Resources:** +- [1st Place Solution (Kaggle)](https://www.kaggle.com/competitions/cmi-detect-behavior-with-sensor-data/writeups/cmi-1st-place-solution) +- [Japanese Summary](https://zenn.dev/ottantachinque/articles/2025-09-14_cmi-detect-behavior-with-sensor-data) +- [Chinese EDA](https://zhuanlan.zhihu.com/p/1943779452640273827) + +### BirdCLEF 2024 - Bird Sound Identification (2024) - 2026-01-23 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/birdclef-2024) +**Category:** Time Series (音频分类 / 生物声学) +**Summary:** 182 种鸟类叫声多标签分类竞赛。数据包含 240,000+ 标注样本和未标注 soundscape。AUC-ROC 评估，CPU 120 分钟推理限制。**1st Place: Team Kefir** (vkop, great_alex, etc.)，Private LB 0.690。 + +**Key Techniques:** +- **Statistics T 噪声过滤**: T = std + var + rms + pwr，0.8 分位数过滤 +- **Google Bird Classifier 预标注**: 过滤低质量数据 + 伪标签生成（系数 0.05） +- **CE Loss + Sigmoid 推理**: 训练用 softmax（多分类），推理用 sigmoid（多标签） +- **Min() Ensemble**: 降低不确定预测，比简单平均更稳定 +- **伪标签迭代训练** (2nd Place): 3 次迭代循环，集成自我改进 +- **Checkpoint Soup** (2nd Place): 平均 13-50 epoch checkpoint 代替 early stopping +- **EfficientViT 快速推理** (3rd Place): ONNX 优化，5 fold 40 分钟 + +**Results:** 1st place (Private LB: 0.690, Public LB: 0.729, 2935 teams) + +**Resources:** +- [1st Place Writeup](https://www.kaggle.com/competitions/birdclef-2024/writeups/team-kefir-1st-place-solution) +- [2nd Place Solution (Japanese)](https://zenn.dev/yuto_mo/articles/85eee84a753159) +- [3rd Place GitHub](https://github.com/TheoViel/kaggle_birdclef2024) +- [1st Place Explanation (Japanese)](https://zenn.dev/yuto_mo/articles/ad43c630729073) + +### BirdCLEF+ 2025 - Multi-Taxonomic Sound Identification (2025) - 2026-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/birdclef-2025) | [知乎 14个高分方案](https://zhuanlan.zhihu.com/p/1920582942931019095) +**Category:** Time Series (音频分类 / 生物声学) +**Summary:** 多分类群声音识别竞赛。数据包含 206 个物种（鸟类、两栖、哺乳、昆虫），需从连续音频中识别物种。**1st Place: Nikita Babych**，Private LB 0.927。 + +**Key Techniques:** +- **Noisy Student 自训练**: 多迭代半监督学习，MixUp 混合伪标签与训练数据 +- **自蒸馏 (Self-Distillation)**: 模型预测作为新标签迭代训练 +- **SED (Sound Event Detection)**: 帧级预测 + 滑动窗口推理 +- **伪标签技术**: 利用未标注 train_soundscapes 数据 +- **领域适应**: 解决训练-测试分布差异 +- **Soft AUC Loss**: 支持软标签的 AUC 损失函数 +- **Silero VAD**: 去除人声干扰 + +**Results:** 1st place (Private LB: 0.927, ~2000 teams) + +**Resources:** +- [1st Place Solution (Kaggle)](https://www.kaggle.com/competitions/birdclef-2025/discussion/583577) +- [2nd Place Solution](https://www.kaggle.com/competitions/birdclef-2025/discussion/583699) +- [5th Place Solution](https://www.kaggle.com/competitions/birdclef-2025/discussion/583312) +- [Chinese Summary - 14 Solutions](https://zhuanlan.zhihu.com/p/1920582942931019095) + +--- + +## Code Templates + +### CWT Scalogram 生成 (suguuuuu's approach) +```python +import numpy as np +import pywt + +def create_scalogram(eeg_data): + """ + EEG 时间序列生成 Scalogram (连续小波变换) + + 参数: + eeg_data: shape (18, 10000) - 18通道，50秒 (200Hz) + + 返回: + scalogram: shape (18, 40, 625) - 可拼接后resize到512x512 + """ + # 1. 归一化: clip到[-1024, 1024]，除以32 + x = np.clip(eeg_data, -1024, 1024) / 32.0 + + # 2. CWT参数 + scales = np.arange(1, 41) # n_scales=40 + wavelet = 'morl' # Morlet小波 + sampling_rate = 200 # fs=200 + + # 3. 对每个通道应用CWT + scalograms = [] + for channel in x: # 18个通道 + coeffs, freqs = pywt.cwt(channel, scales, wavelet, + sampling_period=1/sampling_rate) + scalograms.append(np.abs(coeffs)) + + return np.array(scalograms) # (18, 40, 625) + +# 使用示例 +# eeg_data: (18, 10000) - 18通道EEG，50秒 +# scalogram = create_scalogram(eeg_data) +# vertical_stack = np.vstack(scalograms) # 拼接后resize到512x512 +``` + +### Bipolar Montage 预处理 (yamash's approach) +```python +import numpy as np +from scipy import signal + +def longitudinal_bipolar_montage(eeg_raw): + """ + 纵向双极导联 - 从原始EEG创建差分信号 + + 参数: + eeg_raw: dict or array, shape (n_channels, n_samples) + + 返回: + bipolar: shape (18, n_samples) - 纵向拼接后的差分信号 + """ + # 10-20系统的纵向配对 + pairs = [ + ('Fp1-F7', 'Fp1', 'F7'), ('F7-T3', 'F7', 'T3'), + ('T3-T5', 'T3', 'T5'), ('T5-O1', 'T5', 'O1'), + ('Fp2-F8', 'Fp2', 'F8'), ('F8-T4', 'F8', 'T4'), + ('T4-T6', 'T4', 'T6'), ('T6-O2', 'T6', 'O2'), + ('Fz-Cz', 'Fz', 'Cz'), ('Cz-Pz', 'Cz', 'Pz'), + # ... 更多配对 + ] + + bipolar_signals = [] + for _, ch1, ch2 in pairs: + diff = eeg_raw[ch1] - eeg_raw[ch2] + bipolar_signals.append(diff) + + return np.array(bipolar_signals) + +def bandpass_filter(eeg, lowcut=0.5, highcut=40, fs=200, order=5): + """ + 带通滤波 - 仅保留特定频段 + + 参数: + eeg: shape (n_samples,) - 单通道EEG信号 + lowcut: 低频截止 (Hz) + highcut: 高频截止 (Hz) + fs: 采样率 (Hz) + """ + nyquist = 0.5 * fs + low = lowcut / nyquist + high = highcut / nyquist + b, a = signal.butter(order, [low, high], btype='band') + filtered = signal.filtfilt(b, a, eeg) + return filtered + +# 完整预处理流程 +def preprocess_eeg(eeg_raw): + """ + 完整EEG预处理流程 + """ + # 1. 双极导联 + bipolar = longitudinal_bipolar_montage(eeg_raw) + + # 2. 带通滤波 (0.5-40Hz) + filtered = np.array([bandpass_filter(ch) for ch in bipolar]) + + # 3. 归一化 + normalized = filtered / np.median(np.abs(filtered)) + + return normalized +``` + +### Entmax 替换 Softmax +```python +import torch +import torch.nn.functional as F + +def entmax(x, alpha=1.5, dim=-1): + """ + Entmax激活函数 - 比softmax更稀疏 + + 参数: + x: 输入logits + alpha: 稀疏参数 (1.0=softmax, >1.0更稀疏) + dim: 计算维度 + """ + # 简化实现，实际使用时可用pytorch-entmax库 + # 当alpha->inf时，趋近于argmax + return torch.softmax(x * alpha, dim=dim) + +# 模型输出层替换 +# 原来: F.softmax(logits, dim=-1) +# 改为: entmax(logits, alpha=1.5, dim=-1) + +# 带Entmax的分类头 +class ClassificationHead(nn.Module): + def __init__(self, in_features, num_classes, alpha=1.5): + super().__init__() + self.fc = nn.Linear(in_features, num_classes) + self.alpha = alpha + + def forward(self, x): + logits = self.fc(x) + return entmax(logits, alpha=self.alpha, dim=-1) +``` + +### 非负线性回归集成 +```python +from sklearn.linear_model import LinearRegression +import numpy as np + +class NonNegativeEnsemble: + """ + 非负线性回归集成 - 即使过拟合也能保持CV/LB相关性 + """ + def __init__(self): + self.model = LinearRegression(positive=True) # non-negative + self.weights = None + + def fit(self, predictions, targets): + """ + 参数: + predictions: (n_samples, n_models) - 各模型预测 + targets: (n_samples, n_classes) - 真实标签 + """ + self.model.fit(predictions, targets) + self.weights = self.model.coef_ # 非负权重 + return self + + def predict(self, predictions): + """加权预测""" + return predictions @ self.weights.T + +# 使用示例 +# train_preds = np.stack([model1.predict(X), model2.predict(X), ...], axis=1) +# ensemble = NonNegativeEnsemble().fit(train_preds, y_train) +# final_pred = ensemble.predict(test_preds) +``` + +### 2-Stage Training 训练流程 +```python +import torch +from torch.optim import Adam +from torch.optim.lr_scheduler import CosineAnnealingLR + +def two_stage_training(model, train_loader, hq_loader, device): + """ + 两阶段训练: Stage1全数据，Stage2高质量样本 + + 适用于标签质量不均的场景 + """ + optimizer = Adam(model.parameters(), lr=1e-3) + scheduler = CosineAnnealingLR(optimizer, T_max=20) + + # Stage 1: 全部数据 (votes > 1) + print("Stage 1: All data") + for epoch in range(5): # 5 epochs + train_one_epoch(model, train_loader, optimizer, device) + scheduler.step() + + # Stage 2: 高质量样本 (votes >= 10) + print("Stage 2: High-quality samples only") + for param_group in optimizer.param_groups: + param_group['lr'] = 1e-4 # 降低学习率 + + for epoch in range(15): # 15 epochs + train_one_epoch(model, hq_loader, optimizer, device) + scheduler.step() + +def train_one_epoch(model, dataloader, optimizer, device): + """单轮训练""" + model.train() + for batch in dataloader: + x, y = batch['x'].to(device), batch['y'].to(device) + optimizer.zero_grad() + pred = model(x) + loss = kl_div_loss(pred, y) # KL散度损失 + loss.backward() + optimizer.step() +``` + +### Group K-Fold 验证 +```python +from sklearn.model_selection import GroupKFold +import numpy as np + +def get_group_kfold_splits(df, n_splits=5, group_col='eeg_id'): + """ + Group K-Fold: 确保同一患者的EEG不会分散到train/val + + 对时间序列数据很重要 - 防止数据泄露 + """ + gkf = GroupKFold(n_splits=n_splits) + splits = [] + + for train_idx, val_idx in gkf.split(df, groups=df[group_col]): + train_df = df.iloc[train_idx] + val_df = df.iloc[val_idx] + + # 仅使用投票数>=10的样本 + train_df = train_df[train_df['total_votes'] >= 10] + val_df = val_df[val_df['total_votes'] >= 10] + + splits.append((train_df, val_df)) + + return splits +``` + +### Superlet CWT (Muku's approach) +```python +# Superlet Transform - 比STFT更高的时间/频率分辨率 +# 参考: https://github.com/antoninlff/superlet + +def superlet_cwt(eeg_signal): + """ + Superlet连续小波变换 + 提供比STFT更高的时间-频率分辨率 + """ + from superlet import superlet + + # 配置 + min_freq, max_freq = 0.5, 20.0 + base_cycle, min_order, max_order = 1, 1, 16 + + # 应用Superlet CWT + scalogram = superlet( + eeg_signal, + samplerate=200, + freqs=np.linspace(min_freq, max_freq, 40), + order_min=min_order, + order_max=max_order, + base_cycle=base_cycle + ) + + return scalogram +``` + +### 1D CNN for EEG (Muku's approach) +```python +import torch.nn as nn + +class EEGNet1D(nn.Module): + """ + 1D CNN用于EEG时间序列分类 + 参考: EEGNet, G2Net Gravitational Wave Detection + """ + def __init__(self, n_channels=18, n_classes=6): + super().__init__() + + # 1D卷积提取特征 + self.conv1d = nn.Conv1d( + n_channels, 64, + kernel_size=200, # 与采样率相同 + stride=1, + padding=0 + ) + + # 特征提取后可接2D CNN或GRU + self.feature_maps = nn.Sequential( + nn.BatchNorm1d(64), + nn.ReLU(), + ) + + # 分类头 + self.classifier = nn.Sequential( + nn.AdaptiveAvgPool1d(1), + nn.Flatten(), + nn.Linear(64, n_classes) + ) + + def forward(self, x): + # x: (batch, channels, time) + x = self.conv1d(x) + x = self.feature_maps(x) + return self.classifier(x) +``` + +### 衰减目标创建 (1st Place approach) +```python +import polars as pl +import numpy as np + +def create_decaying_target(train_df, train_events_df, n_epochs=20): + """ + 创建衰减目标 - 按 tolerance_steps 加权 + epoch 衰减 + + 适用于事件检测任务中标签稀疏的场景 + """ + tolerance_steps = [12, 36, 60, 90, 120, 150, 180, 240, 300, 360] # 1min~30min + target_columns = ["event_onset", "event_wakeup"] + + # Step 1: 按 tolerance 加权创建目标 + train_df = ( + train_df.join(train_events_df.select(["series_id", "step", "event"]), + on=["series_id", "step"], how="left") + .to_dummies(columns=["event"]) + .with_columns( + pl.max_horizontal( + pl.col(target_columns) + .rolling_max(window_size * 2 - 1, min_periods=1, center=True) + .over("series_id") + * (1 - i / len(tolerance_steps)) + for i, window_size in enumerate(tolerance_steps) + ) + ) + ) + + # Step 2: 训练过程中进一步衰减 + def update_targets_epoch(targets, epoch, n_epochs): + """每个 epoch 增加衰减强度""" + return np.where( + targets == 1.0, + 1.0, + (targets - (1.0 / n_epochs)).clip(min=0.0) + ) + + return train_df, update_targets_epoch + +# 使用示例 +# train_df, update_fn = create_decaying_target(train_df, train_events, n_epochs=20) +# for epoch in range(n_epochs): +# targets = update_fn(targets, epoch, n_epochs) +# # 训练... +``` + +### 15/45秒 Tolerance 优化 (1st Place approach) +```python +import numpy as np + +def optimize_tolerance_edges(predictions_2nd_level): + """ + 针对 tolerance 边缘优化 - 使用 15/45 秒时刻 + + 原理：评估 tolerance 为 1,3,5,7.5,10,12.5,15,20,25,30 分钟 + - 预测 hh:mm:00 会导致 tolerance 5,10,15,20,25,30 时边缘漏检 + - 预测 hh:mm:30 会导致 tolerance 7.5,12.5 时边缘漏检 + - 预测 hh:mm:15 或 hh:mm:45 可以覆盖所有 tolerance + """ + # 预测点为每分钟的 15 秒或 45 秒时刻 + # step 格式：hh:mm:15 或 hh:mm:45 + + # Step 1: 计算所有候选点的分数 + def calculate_candidate_scores(predictions): + """计算每个候选点的分数""" + tolerance_steps = [12, 36, 60, 90, 120, 150, 180, 240, 300, 360] + scores = {} + + for candidate_idx in range(len(predictions)): + score = 0 + for tol_step in tolerance_steps: + # 累加 tolerance 范围内的预测值 + start = max(0, candidate_idx - tol_step) + end = min(len(predictions), candidate_idx + tol_step) + score += predictions[start:end].sum() + scores[candidate_idx] = score + + return scores + + # Step 2: Greedy 选择事件 + def greedy_event_selection(predictions, max_events=500): + """ + Greedy 选择事件，每次选择后更新分数 + + 每次选择： + 1. 选择分数最高的点 + 2. 将该点 tolerance 范围内的 ground-truth (0秒点) 预测值设为 0 + 3. 将该点 tolerance 范围内的候选点 (15/45秒点) 分数打折 + """ + selected_events = [] + remaining_predictions = predictions.copy() + + for _ in range(min(max_events, len(predictions) // 12)): + scores = calculate_candidate_scores(remaining_predictions) + best_idx = max(scores, key=scores.get) + selected_events.append(best_idx) + + # 更新剩余预测值（差分更新，加速） + for tol_step in tolerance_steps: + # Ground-truth 候选点 (0秒) -> 设为 0 + start_gt = max(0, best_idx - tol_step) + end_gt = min(len(remaining_predictions), best_idx + tol_step) + remaining_predictions[start_gt:end_gt] = 0 + + # 检测候选点 (15/45秒) -> 分数打折 + # 这里简化处理，实际可以只打折不置零 + + return selected_events + + return greedy_event_selection(predictions_2nd_level) +``` + +### Daily Normalization (1st Place approach) +```python +import numpy as np + +def daily_normalize(predictions, series_ids): + """ + 按天归一化预测值 - 利用每天只有1次 onset + 1次 wakeup 的先验 + + 原理： + - 每天只有 2 个事件（1 onset + 1 wakeup） + - 按天归一化可以使每天的最高预测值具有可比性 + """ + normalized = predictions.copy() + + for series_id in np.unique(series_ids): + mask = series_ids == series_id + daily_preds = predictions[mask] + + # 按天分组（17280 步 = 1 天） + n_days = len(daily_preds) // 17280 + + for day in range(n_days): + start = day * 17280 + end = start + 17280 + day_preds = daily_preds[start:end] + + # 归一化到 [0, 1] + day_min, day_max = day_preds.min(), day_preds.max() + if day_max > day_min: + normalized[mask][start:end] = (day_preds - day_min) / (day_max - day_min) + + return normalized +``` + +### Find Peaks 事件检测 +```python +from scipy.signal import find_peaks + +def detect_events_find_peaks(predictions, score_th=0.005, distance=72): + """ + 使用 find_peaks 检测事件 + + 参数: + predictions: 事件概率预测 (shape: [n_steps]) + score_th: 分数阈值（低于此值不检测） + distance: 最小峰值间隔（步数）72 = 6分钟 + + 返回: + events: 检测到的事件索引列表 + """ + onset_preds = predictions[:, 0] # onset 概率 + wakeup_preds = predictions[:, 1] # wakeup 概率 + + # 检测 onset 峰值 + onset_peaks, _ = find_peaks( + onset_preds, + height=score_th, + distance=distance + ) + + # 检测 wakeup 峰值 + wakeup_peaks, _ = find_peaks( + wakeup_preds, + height=score_th, + distance=distance + ) + + return { + 'onset': onset_peaks, + 'wakeup': wakeup_peaks + } +``` + +### Rolling Mean 平滑 (3rd Place approach) +```python +import numpy as np + +def rolling_mean_smooth(predictions, window=12, center=True): + """ + 使用滚动均值平滑预测结果 + + 参数: + predictions: 原始预测值 + window: 窗口大小（12 = 1分钟） + center: 是否居中 + """ + smoothed = np.zeros_like(predictions) + + for i in range(len(predictions)): + start = max(0, i - window // 2) + end = min(len(predictions), i + window // 2 + 1) + smoothed[i] = predictions[start:end].mean() + + return smoothed + +# 然后检测峰值 +def detect_events_with_smooth(predictions, window=12, distance=72): + """平滑后检测事件""" + smoothed = rolling_mean_smooth(predictions, window=window) + return detect_events_find_peaks(smoothed, distance=distance) +``` + +### 两阶段建模框架 (1st Place approach) +```python +def two_level_modeling(train_series, train_events): + """ + 两阶段建模框架 + + 1st Level: 5秒间隔预测事件概率 + 2nd Level: 1分钟间隔精化预测 + """ + # ==================== 1st Level ==================== + # 输入：5秒间隔的数据 + # 输出：5秒间隔的 onset/wakeup 概率 + + # 1st Level 模型示例 + first_level_models = [ + CNNGRUModel(), # CNN + GRU + CNN + CNNTransformerModel(), # CNN + GRU + Transformer + CNN + LSTMUNetModel(), # LSTM + UNet1d + UNet + # ... 更多模型 + ] + + # 训练 1st level + for model in first_level_models: + model.fit(train_series, train_events) + + # 生成 1st level 预测（5秒间隔） + first_level_preds = [] + for model in first_level_models: + pred = model.predict(train_series) # shape: [n_steps_5sec, 2] + first_level_preds.append(pred) + + # ==================== 2nd Level ==================== + # 输入：1st level 预测 + 原始特征（整合到整分钟） + # 输出：1分钟间隔的 onset/wakeup 概率 + + # 整合 1st level 预测到整分钟 + minute_features = aggregate_to_minute(first_level_preds, train_series) + + # 2nd Level 模型示例 + second_level_models = [ + LightGBMRegressor(), + CatBoostRegressor(), + CNNGRUModel(), + CNNTransformerModel(), + CNNModel() + ] + + # 训练 2nd level + for model in second_level_models: + model.fit(minute_features, train_events) + + # 生成 2nd level 预测（1分钟间隔） + second_level_preds = [] + for model in second_level_models: + pred = model.predict(minute_features) # shape: [n_steps_1min, 2] + second_level_preds.append(pred) + + # ==================== 后处理 ==================== + # Daily normalization + final_preds = np.mean(second_level_preds, axis=0) + final_preds = daily_normalize(final_preds, series_ids) + + # Greedy 事件选择（15/45秒技巧） + events = optimize_tolerance_edges(final_preds) + + return events + +def aggregate_to_minute(first_level_preds, train_series): + """将 5 秒预测整合到 1 分钟""" + # 每个 1 分钟包含 12 个 5 秒步 + n_steps_minute = len(train_series) // 12 + + minute_features = [] + for i in range(n_steps_minute): + start = i * 12 + end = start + 12 + + # 整合 1st level 预测（均值、最大值等） + preds_5sec = [p[start:end] for p in first_level_preds] + + # 整合原始特征（anglez, enmo 的统计量） + raw_feats = train_series[start:end] + + # 合并特征 + minute_feat = np.concatenate([ + np.mean([p.mean(axis=0) for p in preds_5sec], axis=0), # 预测均值 + np.max([p.max(axis=0) for p in preds_5sec], axis=0), # 预测最大值 + raw_feats.mean(axis=0), # 原始特征均值 + raw_feats.std(axis=0), # 原始特征标准差 + ]) + + minute_features.append(minute_feat) + + return np.array(minute_features) +``` + +### 时间序列特征工程 (基线方案) +```python +import pandas as pd +import numpy as np + +def create_sleep_features(series_df): + """ + 创建睡眠检测特征 + + 基于基线方案（银牌）的特征工程 + """ + df = series_df.copy() + + # ========== 传感器特征 ========== + # 平滑 + 一阶差分 + df['enmo_abs_diff'] = df['enmo'].diff().abs() + df['enmo'] = df['enmo_abs_diff'].rolling(window=5, center=True, min_periods=1).mean() + + df['anglez_abs_diff'] = df['anglez'].diff().abs() + df['anglez'] = df['anglez_abs_diff'].rolling(window=5, center=True, min_periods=1).mean() + + # ========== 时间特征 ========== + df['timestamp'] = pd.to_datetime(df['timestamp']) + df['hour'] = df['timestamp'].dt.hour + df['minute'] = df['timestamp'].dt.minute + df['weekday'] = df['timestamp'].dt.weekday + df['is_weekend'] = df['weekday'].isin([5, 6]).astype(int) + + # Sin/Cos 编码（周期性时间） + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + + # ========== 滚动特征 ========== + for col in ['enmo', 'anglez']: + for window in [10, 30, 60]: + df[f'{col}_rolling_mean_{window}'] = df[col].rolling(window=window, min_periods=1).mean() + df[f'{col}_rolling_std_{window}'] = df[col].rolling(window=window, min_periods=1).std() + df[f'{col}_rolling_max_{window}'] = df[col].rolling(window=window, min_periods=1).max() + df[f'{col}_rolling_min_{window}'] = df[col].rolling(window=window, min_periods=1).min() + + # ========== 交互特征 ========== + df['anglez_times_enmo'] = df['anglez_abs_diff'] * df['enmo_abs_diff'] + df['anglez_div_enmo'] = df['anglez_abs_diff'] / (df['enmo_abs_diff'] + 1e-6) + + return df +``` + +### TOF 图像化处理 (1st Place approach) +```python +import numpy as np + +def tof_image_2x2_pooling(tof_data): + """ + TOF 图像化处理 - 2×2 正方形 9 个区域平均 + + 将每个 8×8 的 TOF 传感器数据转换为 2×2 的特征图 + + 参数: + tof_data: shape (n_timesteps, n_tof_sensors * 64) 或 (n_timesteps, n_tof_sensors, 8, 8) + 每个 TOF 传感器有 64 个像素（8×8） + + 返回: + pooled: shape (n_timesteps, n_tof_sensors * 9) - 每个 TOF 传感器 9 个区域 + """ + n_timesteps = tof_data.shape[0] + + # 如果是 2D 形状，重塑为 (n_timesteps, n_tof_sensors, 8, 8) + if len(tof_data.shape) == 2: + n_tof_sensors = tof_data.shape[1] // 64 + tof_reshaped = tof_data.reshape(n_timesteps, n_tof_sensors, 8, 8) + else: + tof_reshaped = tof_data + + n_tof_sensors = tof_reshaped.shape[1] + pooled_features = [] + + for t in range(n_timesteps): + for sensor in range(n_tof_sensors): + sensor_data = tof_reshaped[t, sensor] # (8, 8) + + # 2×2 池化，得到 9 个区域（每个 4×4） + # 也可以直接 2×2 池化得到 4 个区域 + # 这里假设使用 2×2 池化，步长为 2 + pooled = sensor_data.reshape(4, 4).mean(axis=1).mean(axis=0) # 得到 4 个值 + + # 或者更细粒度的 3×3 网格，得到 4 个区域，再加上全局统计 + # 根据日语描述："2x2の正方形を9つ" - 9 个正方形区域 + # 可能是 3×3 网格，步长为 2，得到 4 个区域，再加上某些额外特征 + + # 这里实现一种可能的解释：滑动窗口 2×2，步长 2 + patches = [] + for i in range(0, 8, 2): + for j in range(0, 8, 2): + patch = sensor_data[i:i+2, j:j+2] + patches.append(patch.mean()) + # 如果 4×4 网格，步长 2，得到 9 个区域 (4×4 / 2×2 = 4 区域 + 1 个额外) + # 这里简化处理，使用 4 个区域均值 + 全局均值 + pooled = np.array(patches) + + pooled_features.append(pooled) + + return np.array(pooled_features) # (n_timesteps, n_tof_sensors * n_patches) +``` + +### 四元数 6D 表现 (2nd Place approach) +```python +import numpy as np + +def quaternion_to_6d(quaternion_data): + """ + 四元数转 6D 连续表示 - 避免四元数不连续性 + + 参数: + quaternion_data: shape (..., 4) - 四元数 (w, x, y, z) + + 返回: + rotation_6d: shape (..., 6) - 6D 连续旋转表示 + + 参考: "On the Continuity of Rotation Representations in Neural Networks" + """ + # 提取四元数的最后两个分量 + # 有多种 6D 表现方法，这里使用其中一种 + # 方法 1: 使用旋转矩阵的前两列 + # 方法 2: 使用四元数的向量部分 + + w = quaternion_data[..., 0:1] + x = quaternion_data[..., 1:2] + y = quaternion_data[..., 2:3] + z = quaternion_data[..., 3:4] + + # 归一化 + norm = np.sqrt(w**2 + x**2 + y**2 + z**2) + w, x, y, z = w/norm, x/norm, y/norm, z/norm + + # 方法: 使用旋转矩阵的前两列 + # R = [w -z y z] + # [z w -x y] + # [-y x w z] + # 取前两列作为 6D 表现 + # col1 = [w, z, -y] + # col2 = [-z, w, x] + # 这里简化处理，使用更直接的 6D 表现 + + # 简化版本: 直接使用 (x, y, z) 和旋转角度/轴 + # 更好的方法: 将四元数转换为旋转矩阵，取前两列 + + # 计算 6D 表现: 取旋转矩阵的前两列 + # R[0,:] = [1 - 2(y^2 + z^2), 2(xy - wz), 2(xz + wy)] + # R[1,:] = [ 2(xy + wz), 1 - 2(x^2 + z^2), 2(yz - wx)] + + x2 = x * x + y2 = y * y + z2 = z * z + + # 旋转矩阵的第一行和第二行 + r00 = 1 - 2 * (y2 + z2) + r01 = 2 * (x * y - w * z) + r02 = 2 * (x * z + w * y) + r10 = 2 * (x * y + w * z) + r11 = 1 - 2 * (x2 + z2) + r12 = 2 * (y * z - w * x) + + # 取前两列作为 6D 表现 + rotation_6d = np.concatenate([ + r00, r01, r02, r10, r11, r12 + ], axis=-1) + + return rotation_6d + +# 使用示例 +# rot_data shape: (n_timesteps, 4) or (n_timesteps, n_samples, 4) +# rot_6d = quaternion_to_6d(rot_data) +``` + +### 阶段感知 Attention (2nd Place approach) +```python +import torch +import torch.nn as nn + +class PhaseAwareAttention(nn.Module): + """ + 阶段感知 Attention - 分阶段独立建模和加权 + + 利用 Transition/Pause/Gesture 三阶段结构 + """ + def __init__(self, d_model, n_heads=8, dropout=0.1): + super().__init__() + self.phase_embedding = nn.Embedding(3, d_model) # 3 个阶段 + + # 每个阶段独立的 Attention + self.attentions = nn.ModuleList([ + nn.MultiheadAttention(d_model, n_heads, dropout=dropout) + for _ in range(3) + ]) + self.norms = nn.ModuleList([nn.LayerNorm(d_model) for _ in range(3)]) + self.fcs = nn.ModuleList([nn.Linear(d_model, d_model) for _ in range(3)]) + + self.phase_classifier = nn.Sequential( + nn.Linear(d_model, d_model // 2), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(d_model // 2, 3) # 3 个阶段 + ) + + def forward(self, x, phase_labels=None): + """ + 参数: + x: (batch, seq_len, d_model) - 输入特征 + phase_labels: (batch, seq_len) - 阶段标签 (0=Transition, 1=Pause, 2=Gesture) + """ + batch_size, seq_len, d_model = x.shape + + # 预测阶段概率 + phase_probs = self.phase_classifier(x.mean(dim=1)) # (batch, 3) + phase_probs = torch.softmax(phase_probs, dim=-1) # (batch, 3) + + # 如果没有提供阶段标签，使用 argmax + if phase_labels is None: + phase_labels = torch.argmax(phase_probs, dim=-1) # (batch,) + + # 初始化输出 + output = torch.zeros_like(x) + + # 对每个样本应用对应的阶段 Attention + for b in range(batch_size): + phase = phase_labels[b].item() # 该样本的主要阶段 + + # 应用该阶段的 Attention + x_b = x[b:b+1] # (1, seq_len, d_model) + attn = self.attentions[phase] + norm = self.norms[phase] + fc = self.fcs[phase] + + x_b = norm(x_b) + x_b, _ = attn(x_b, x_b, x_b) + x_b = fc(x_b) + + # 用阶段概率加权 + weight = phase_probs[b, phase] + output[b:b+1] = x_b * weight + + return output, phase_probs +``` + +### 匈牙利算法全局最优标签分配 (2nd/3rd Place approach) +```python +import numpy as np +from scipy.optimize import linear_sum_assignment + +def hungarian_global_label_assignment(pred_probs, subject_ids, sequence_ids, + gesture_ids, orientation_ids): + """ + 匈牙利算法全局最优标签分配 + + 利用约束: 每个 subject × gesture × orientation 只出现一次 + + 参数: + pred_probs: (n_sequences, n_classes) - 预测概率 + subject_ids: (n_sequences,) - 每个 sequence 的 subject ID + sequence_ids: (n_sequences,) - sequence ID + gesture_ids: (n_sequences,) - 约束前的 gesture 标签 + orientation_ids: (n_sequences,) - 每个 sequence 的 orientation + + 返回: + final_labels: (n_sequences,) - 全局最优的标签分配 + """ + n_sequences = pred_probs.shape[0] + n_classes = pred_probs.shape[1] + + # 构建代价矩阵: cost[i, j] = -log(prob_i[j]) 表示将 sequence i 分配给标签 j 的代价 + cost_matrix = -np.log(pred_probs + 1e-10) + + # 构建约束矩阵: 不能违反 subject × gesture × orientation 唯一性约束 + # 这里简化处理，实际实现需要更复杂的约束 + + # 对每个 subject 单独处理 + final_labels = np.zeros(n_sequences, dtype=int) + + for subject_id in np.unique(subject_ids): + # 该 subject 的所有序列 + mask = subject_ids == subject_id + subject_seqs = np.where(mask)[0] + + if len(subject_seqs) == 0: + continue + + # 该 subject 的预测概率 + subject_probs = pred_probs[subject_seqs] # (n_subject_seqs, n_classes) + + # 使用匈牙利算法进行最优分配 + row_ind, col_ind = linear_sum_assignment(subject_probs) + + # 分配标签 + for seq_idx, label_idx in zip(row_ind, col_ind): + final_labels[subject_seqs[seq_idx]] = label_idx + + return final_labels + +# 备选方案：更简单的实现（仅针对 orientation × gesture 约束） +def simple_hungarian_assignment(pred_probs, sequence_ids, gesture_ids, orientation_ids): + """ + 简化的匈牙利算法实现 - 利用 orientation × gesture 唯一性约束 + + 参数: + pred_probs: (n_sequences, n_classes) + sequence_ids: (n_sequences,) + gesture_ids: (n_sequences,) + orientation_ids: (n_sequences,) + """ + n_sequences = pred_probs.shape[0] + n_classes = pred_probs.shape[1] + + # 构建 (orientation, gesture) 组合 + # 每个 orientation × gesture 组合只分配一次 + + final_labels = np.zeros(n_sequences, dtype=int) + + # 对每个 orientation 单独处理 + for orientation_id in np.unique(orientation_ids): + mask = orientation_ids == orientation_id + orientation_seqs = np.where(mask)[0] + + if len(orientation_seqs) == 0: + continue + + # 该 orientation 的所有序列 + orientation_probs = pred_probs[orientation_seqs] + orientation_gestures = gesture_ids[orientation_seqs] + + # 使用匈牙利算法 + row_ind, col_ind = linear_sum_assignment(orientation_probs) + + # 分配标签（考虑 gesture 约束） + # 这里需要更复杂的实现，确保每个 gesture 只分配一次 + + for seq_idx, label_idx in zip(row_ind, col_ind): + final_labels[orientation_seqs[seq_idx]] = label_idx + + return final_labels +``` + +### 相位 Mixup (2nd Place approach) +```python +import numpy as np + +def phase_aware_mixup(X, y, phase_labels, alpha=0.2, beta=0.2): + """ + 相位感知 Mixup - 按阶段分割后在同阶段内进行 Mixup + + 参数: + X: (batch, seq_len, n_features) - 输入特征 + y: (batch, n_classes) - 标签 + phase_labels: (batch, seq_len) - 阶段标签 (0=Transition, 1=Pause, 2=Gesture) + alpha: Mixup 强度 + beta: CutMix 强度 + + 返回: + mixed_X, mixed_y, lambda_a, lambda_b, phase_labels + """ + batch_size, seq_len, n_features = X.shape + + if phase_labels is None: + # 简单 Mixup + return standard_mixup(X, y, alpha) + + # 对每个样本进行相位 Mixup + mixed_X = X.copy() + mixed_y = y.copy() + lambda_as = np.zeros(batch_size) + lambda_bs = np.zeros(batch_size) + + for i in range(batch_size): + # 找到同一阶段的其他样本 + same_phase_mask = (phase_labels[i, 0] == phase_labels[:, 0]) + + if same_phase_mask.sum() == 0: + # 没有同阶段样本，跳过 + continue + + # 随机选择同阶段样本 j + same_phase_indices = np.where(same_phase_mask)[0] + j = np.random.choice(same_phase_indices) + + # Mixup + mixed_X[i] = alpha * X[i] + (1 - alpha) * X[j] + mixed_y[i] = alpha * y[i] + (1 - alpha) * y[j] + lambda_as[i] = alpha + + # CutMix（对标签） + if beta > 0: + # 简化的 CutMix 实现 + # 实际应该对特征进行 CutMix + pass + + return mixed_X, mixed_y, lambda_as, lambda_bs, phase_labels + +def standard_mixup(X, y, alpha=0.2): + """标准 Mixup""" + batch_size = X.shape[0] + + if batch_size < 2: + return X, y, np.zeros(batch_size), None, None + + mixed_X = X.copy() + mixed_y = y.copy() + lambda_as = np.random.beta(alpha, alpha, batch_size) + + for i in range(batch_size): + j = i + while j == i: + j = np.random.randint(0, batch_size) + + mixed_X[i] = lambda_as[i] * X[i] + (1 - lambda_as[i]) * X[j] + mixed_y[i] = lambda_as[i] * y[i] + (1 - lambda_as[i]) * y[j] + + return mixed_X, mixed_y, lambda_as, None, None +``` + +### 重力去除和特征工程 (1st Place approach) +```python +import numpy as np + +def remove_gravity_and_extract_features(acc_data): + """ + 去除重力影响并提取 35 个特征 + + 1st Place 的特征工程方法 + + 参数: + acc_data: shape (n_timesteps, 3) - 加速度数据 (acc_x, acc_y, acc_z) + + 返回: + features: shape (n_timesteps, 35) - 提取的特征 + """ + n_timesteps = acc_data.shape[0] + + # 1. 去除重力 + # 假设重力加速度约为 9.8 m/s² + # 计算重力方向（可以使用平均加速度估计） + gravity = np.mean(acc_data, axis=0) # 简化方法 + acc_no_gravity = acc_data - gravity + + # 2. 提取 35 个特征 + # 这里需要根据实际实现来定义这 35 个特征 + # 可能的特征类型： + # - 统计特征：均值、标准差、最大值、最小值等 + # - 频域特征：FFT 后的能量分布 + # - 时域特征：过零率、峰值数等 + # - 差分特征：一阶差分、二阶差分等 + + features = [] + + for t in range(n_timesteps): + feat = [] + + # 原始加速度（去除重力后） + feat.extend(acc_no_gravity[t]) # 3 个特征 + + # 加速度的范数 + feat.append(np.linalg.norm(acc_no_gravity[t])) # 1 个特征 + + # 加速度的绝对值 + feat.extend(np.abs(acc_no_gravity[t])) # 3 个特征 + + # 一阶差分 + if t > 0: + diff = acc_no_gravity[t] - acc_no_gravity[t-1] + feat.append(np.linalg.norm(diff)) # 1 个特征 + feat.extend(diff) # 3 个特征 + else: + feat.extend([0, 0, 0, 0]) # 4 个特征 + + # 统计特征（滑动窗口） + window = 10 + start = max(0, t - window) + end = min(n_timesteps, t + window + 1) + window_data = acc_no_gravity[start:end] + + feat.append(np.mean(window_data, axis=0)) # 3 个特征 + feat.append(np.std(window_data, axis=0)) # 3 个特征 + feat.append(np.max(window_data, axis=0) - np.min(window_data, axis=0)) # 3 个特征 + + # 频域特征（FFT） + if t >= window: + fft_data = np.fft.fft(acc_data[start:end, 0]) # 仅对 x 轴 + fft_energy = np.abs(fft_data) + feat.append(fft_energy[:5].mean()) # 前 5 个频点的能量 # 1 个特征 + else: + feat.append(0) + + features.append(feat) + + features = np.array(features) # (n_timesteps, n_features) + # 确保 n_features = 35 + if features.shape[1] < 35: + # 填充或截断到 35 个特征 + # 这里简化处理 + pass + + return features +``` + +### 时序转图像 (7th Place approach) +```python +import numpy as np + +def time_series_to_image(series_data, image_size=(224, 224)): + """ + 时序转图像 - 将时序数据转换为图像 + + 7th Place 的方法：使用 2D-CNN 处理时序数据 + + 参数: + series_data: shape (n_timesteps, n_features) - 时序数据 + image_size: 目标图像大小 (height, width) + + 返回: + images: (n_channels, height, width) - 图像数据 + """ + n_timesteps, n_features = series_data.shape + height, width = image_size + + # 方法 1: 直接重塑（如果 n_timesteps × n_features 适合） + # 如果 n_timesteps × n_features = height × width，直接重塑 + if n_timesteps * n_features == height * width: + image = series_data.reshape(height, width) + return image[np.newaxis, :, :] # (1, height, width) + + # 方法 2: 使用波形图（类似声谱图） + # 将时序数据转换为图像的灰度值 + # 可以使用 matplotlib 的 imshow 方法 + + # 简化实现：将每个特征作为一个通道 + # 如果 n_features == 3，可以直接作为 RGB 图像 + if n_features == 3: + # 归一化到 [0, 255] + normalized = (series_data - series_data.min()) / (series_data.max() - series_data.min() + 1e-10) + image = (normalized * 255).astype(np.uint8) + + # 调整大小 + # 这里可以使用 cv2.resize 或 interpolation + # 简化处理：直接采样 + if n_timesteps != height or n_features != width: + # 使用最近邻插值 + image = image.reshape(height, width, 3) + # 实际应该使用 cv2.resize + + return image.transpose(2, 0, 1) # (3, height, width) + + # 方法 3: 创建多通道图像（每个特征一个通道） + # 如果 n_features < 3，复制通道 + # 如果 n_features > 3，选择前 3 个特征或使用 PCA + + # 简化处理：只使用前 3 个特征 + if n_features >= 3: + selected_data = series_data[:, :3] + else: + selected_data = np.concatenate([series_data, series_data, series_data], axis=1)[:, :3] + + # 归一化到 [0, 255] + normalized = (selected_data - selected_data.min()) / (selected_data.max() - selected_data.min() + 1e-10) + image = (normalized * 255).astype(np.uint8) + + # 调整大小 + image = image.reshape(n_timesteps, 3, 1).reshape(height, width, 3) + + return image.transpose(2, 0, 1) # (3, height, width) +``` + +### 异常数据处理 +```python +import polars as pl +import numpy as np + +def remove_invalid_sequences(train_df, train_events): + """ + 删除无效序列 + + 1st Place 和其他前排方案的共同处理： + - SUBJ_019262: 没有正确佩戴设备 + - SUBJ_045235: 数据异常 + + 参数: + train_df: 训练数据 + train_events: 训练事件 + + 返回: + cleaned_df: 清理后的数据 + """ + # 删除特定 subject 的数据 + invalid_subjects = ['SUBJ_019262', 'SUBJ_045235'] + + # 方法 1: 完全删除 + cleaned_df = train_df.filter(~pl.col('subject').is_in(invalid_subjects)) + + # 方法 2: 数据转换（如果某些序列可以恢复） + # 这里需要根据实际情况处理 + + # 删除 gesture 不存在的序列 + # 统计每个 sequence_id 的 unique gesture 数量 + gesture_counts = train_df.groupby('sequence_id')['gesture'].n_unique() + valid_gestures = gesture_counts.filter(pl.col('gesture') > 0) + cleaned_df = cleaned_df.filter(pl.col('sequence_id').is_in(valid_gestures['sequence_id'])) + + return cleaned_df +``` + +### 左手系 → 右手系对齐 +```python +import numpy as np + +def align_left_to_right_handed(sensor_data, sensor_type='IMU'): + """ + 左手系 → 右手系对齐 + + 将左手佩戴设备的传感器数据转换为右手系的等效数据 + + 参数: + sensor_data: 传感器数据 + sensor_type: 'IMU' 或 'THM' 或 'TOF' + + 返回: + aligned_data: 对齐后的数据 + """ + if sensor_type == 'IMU': + # 对于 IMU（加速度计和陀螺仪）： + # 加速度：x → -x（左右翻转） + # 陀螺仪：某些分量需要取反 + + # 假设 sensor_data 的格式：(acc_x, acc_y, acc_z, rot_w, rot_x, rot_y, rot_z, ...) + # 或者其他格式 + + # 加速度：翻转 x 分量 + acc_x = sensor_data[:, 0] # 假设第 0 列是 acc_x + acc_y = sensor_data[:, 1] # acc_y + acc_z = sensor_data[:, 2] # acc_z + + aligned_acc_x = -acc_x # 左右翻转 + aligned_acc_y = acc_y + aligned_acc_z = acc_z + + # 陀螺仪：需要根据实际佩戴方式调整 + # 这里简化处理，保持不变 + + # 组合对齐后的数据 + aligned_data = sensor_data.copy() + aligned_data[:, 0] = aligned_acc_x + + elif sensor_type == 'THM': + # 对于热电堆传感器： + # 可能需要镜像处理 + + aligned_data = sensor_data.copy() + # 根据传感器位置进行镜像 + + elif sensor_type == 'TOF': + # 对于飞行时间传感器： + # 可能需要镜像处理 8×8 像素阵列 + + aligned_data = sensor_data.copy() + # 根据传感器位置进行镜像 + + return aligned_data +``` + +### Statistics T 噪声过滤（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 的噪声过滤技巧，使用信号统计量过滤低质量数据： + +```python +import numpy as np +import librosa + +class StatisticsTNoiseFilter: + """ + Statistics T 噪声过滤 + 参考：BirdCLEF 2024 1st Place Solution + """ + + def __init__(self, quantile: float = 0.8): + self.quantile = quantile + + def compute_statistics(self, audio: np.ndarray, sample_rate: int) -> dict: + """计算音频统计量""" + # RMS (Root Mean Square) + rms = librosa.feature.rms(y=audio)[0] + + # 零交叉率 (Zero Crossing Rate) + zcr = librosa.feature.zero_crossing_rate(audio)[0] + + # 标准差 + std = np.std(audio) + + # 方差 + var = np.var(audio) + + # 功率 + pwr = np.mean(audio ** 2) + + return { + 'std': std, + 'var': var, + 'rms': np.mean(rms), + 'pwr': pwr, + 'zcr': np.mean(zcr), + } + + def compute_T(self, stats: dict) -> float: + """计算统计量 T""" + T = ( + stats['std'] + + stats['var'] + + stats['rms'] + + stats['pwr'] + ) + return T + + def filter_audio( + self, + audio_paths: list[str], + sample_rate: int = 32000 + ) -> list[str]: + """ + 过滤噪声音频 + + Args: + audio_paths: 音频文件路径列表 + sample_rate: 采样率 + + Returns: + filtered_paths: 过滤后的音频路径列表 + """ + T_values = [] + + # 计算所有音频的 T 值 + for path in audio_paths: + audio, _ = librosa.load(path, sr=sample_rate) + stats = self.compute_statistics(audio, sample_rate) + T = self.compute_T(stats) + T_values.append(T) + + # 使用分位数过滤 + threshold = np.quantile(T_values, self.quantile) + + # 只保留 T 值低于阈值的音频（噪声较小） + filtered_paths = [ + path for path, T in zip(audio_paths, T_values) + if T < threshold + ] + + print(f"过滤前: {len(audio_paths)} 过滤后: {len(filtered_paths)}") + return filtered_paths +``` + +### Google Bird Classifier 预标注（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 使用 Google Bird Vocalization Classifier 进行数据过滤和预标注： + +```python +import numpy as np +import pandas as pd +from typing import Optional + +class GoogleClassifierPreLabeler: + """ + Google Bird Classifier 预标注 + 参考：BirdCLEF 2024 1st Place Solution + """ + + def __init__(self, model, pseudo_label_coeff: float = 0.05): + """ + Args: + model: Google Bird Vocalization Classifier + pseudo_label_coeff: 伪标签系数 + """ + self.model = model + self.pseudo_label_coeff = pseudo_label_coeff + + def predict(self, audio_chunk: np.ndarray) -> dict: + """使用 Google 模型预测""" + # 假设 model 返回 {class_name: probability} + predictions = self.model.predict(audio_chunk) + return predictions + + def filter_and_relabel( + self, + audio_path: str, + primary_label: str, + secondary_labels: Optional[list[str]] = None + ) -> Optional[dict]: + """ + 过滤低质量数据并重新标注 + + Args: + audio_path: 音频路径 + primary_label: 主要标签 + secondary_labels: 次要标签 + + Returns: + filtered_label: 过滤后的标签字典，None 表示应丢弃 + """ + # 获取 Google 预测 + predictions = self.predict(audio_path) + max_class = max(predictions, key=predictions.get) + max_prob = predictions[max_class] + + # 过滤：如果最大预测与 primary label 不匹配，丢弃 + if max_class != primary_label: + # 检查是否与 secondary label 匹配 + if secondary_labels and max_class in secondary_labels: + # 替换 primary label + primary_label = max_class + else: + # 丢弃该 chunk + return None + + # 构建标签向量 + num_classes = len(predictions) + label_vector = np.zeros(num_classes) + + # Primary label 权重 0.5 + label_vector[primary_label] = 0.5 + + # Secondary labels 分配剩余 0.5 + if secondary_labels: + for sec_label in secondary_labels: + label_vector[sec_label] += 0.5 / len(secondary_labels) + + # 添加 Google 预测作为伪标签 + for class_name, prob in predictions.items(): + label_vector[class_name] += self.pseudo_label_coeff * prob + + return {'label_vector': label_vector, 'primary': primary_label} + + def relabel_soundscape(self, audio_path: str) -> np.ndarray: + """为 soundscape 生成伪标签""" + predictions = self.predict(audio_path) + return np.array([predictions.get(cls, 0) for cls in range(self.num_classes)]) +``` + +### CE Loss + Sigmoid 推理（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 的创新：训练用 CE Loss + Softmax，推理用 Sigmoid： + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class CESigmoidTrainer: + """ + CE Loss 训练 + Sigmoid 推理 + 参考：BirdCLEF 2024 1st Place Solution + + 核心思想： + - 训练时用 CE Loss + Softmax（多分类问题） + - 推理时用 Sigmoid（多标签预测） + - 原因：数据大多只有 1-2 个标签，可视为多分类 + """ + + def __init__(self, model: nn.Module, num_classes: int): + self.model = model + self.num_classes = num_classes + self.criterion = nn.CrossEntropyLoss() + + def train_step(self, batch: dict) -> torch.Tensor: + """ + 训练步骤：使用 CE Loss + Softmax + + Args: + batch: 包含 'mel_spec' 和 'labels' + + Returns: + loss: CE Loss + """ + mel_spec = batch['mel_spec'] # (B, C, H, W) + labels = batch['labels'] # (B, num_classes) + + # 前向传播 + logits = self.model(mel_spec) # (B, num_classes) + + # 对于多标签数据，取最大标签作为训练目标 + # （因为 CE Loss 是多分类损失） + target_labels = torch.argmax(labels, dim=1) # (B,) + + # CE Loss + Softmax + loss = self.criterion(logits, target_labels) + + return loss + + @torch.no_grad() + def predict(self, mel_spec: torch.Tensor) -> torch.Tensor: + """ + 推理步骤：使用 Sigmoid + + Args: + mel_spec: (B, C, H, W) + + Returns: + probabilities: (B, num_classes), Sigmoid 概率 + """ + logits = self.model(mel_spec) # (B, num_classes) + + # 推理时使用 Sigmoid（多标签预测） + probabilities = torch.sigmoid(logits) + + return probabilities + + def fit(self, train_loader, val_loader, num_epochs: int, lr: float = 1e-3): + """训练循环""" + optimizer = torch.optim.AdamW(self.model.parameters(), lr=lr) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=num_epochs + ) + + for epoch in range(num_epochs): + # 训练 + self.model.train() + train_loss = 0 + for batch in train_loader: + loss = self.train_step(batch) + loss.backward() + optimizer.step() + optimizer.zero_grad() + train_loss += loss.item() + + # 验证（用 Sigmoid） + self.model.eval() + val_preds = [] + val_labels = [] + for batch in val_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + probs = self.predict(mel_spec) + val_preds.append(probs.cpu().numpy()) + val_labels.append(labels.cpu().numpy()) + + # 计算验证指标 + val_preds = np.concatenate(val_preds) + val_labels = np.concatenate(val_labels) + val_auc = self.compute_auc(val_labels, val_preds) + + print(f"Epoch {epoch}: Train Loss={train_loss/len(train_loader):.4f}, Val AUC={val_auc:.4f}") + scheduler.step() +``` + +### Min() Ensemble（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 的 Min() Ensemble，降低不确定预测： + +```python +import numpy as np +import torch + +class MinEnsemble: + """ + Min() Ensemble + 参考：BirdCLEF 2024 1st Place Solution + + 核心思想： + - 使用 min() 而不是 mean() 聚合模型预测 + - 降低不确定预测，提高稳定性 + """ + + def __init__(self, models: list[nn.Module]): + self.models = models + + @torch.no_grad() + def predict_min(self, mel_spec: torch.Tensor) -> np.ndarray: + """ + 使用 Min() 聚合预测 + + Args: + mel_spec: (B, C, H, W) + + Returns: + predictions: (B, num_classes), min() 聚合后的概率 + """ + predictions = [] + + # 获取所有模型的预测 + for model in self.models: + model.eval() + logits = model(mel_spec) + probs = torch.sigmoid(logits) # Sigmoid + predictions.append(probs.cpu().numpy()) + + # Stack: (num_models, B, num_classes) + predictions = np.stack(predictions, axis=0) + + # Min() 聚合 + min_predictions = np.min(predictions, axis=0) + + return min_predictions + + def predict_mean(self, mel_spec: torch.Tensor) -> np.ndarray: + """传统 Mean() 聚合（对比用）""" + predictions = [] + + for model in self.models: + model.eval() + logits = model(mel_spec) + probs = torch.sigmoid(logits) + predictions.append(probs.cpu().numpy()) + + predictions = np.stack(predictions, axis=0) + mean_predictions = np.mean(predictions, axis=0) + + return mean_predictions + +# 使用示例 +# min_ensemble = MinEnsemble([model1, model2, model3, model4, model5]) +# predictions = min_ensemble.predict_min(test_mel_spec) +``` + +### Checkpoint Soup（BirdCLEF 2024 - 2nd Place） + +2nd Place ADSR 的 Checkpoint Soup 技巧： + +```python +import torch +import torch.nn as nn +from typing import list + +class CheckpointSoup: + """ + Checkpoint Soup + 参考：BirdCLEF 2024 2nd Place Solution + + 核心思想： + - 平均多个 epoch 的 checkpoint 权重 + - 代替 early stopping + - 通常更稳定 + """ + + def __init__(self, model: nn.Module, metrics: list[str] = ['auc', 'lrap', 'f1']): + self.model = model + self.metrics = metrics + self.checkpoints = [] # 存储 (epoch, state_dict, scores) + + def add_checkpoint(self, epoch: int, state_dict: dict, scores: dict): + """ + 添加 checkpoint + + Args: + epoch: epoch 编号 + state_dict: 模型权重 + scores: 验证指标 {metric_name: score} + """ + # 检查是否有任意指标改进 + should_save = False + for metric in self.metrics: + if epoch == 0: + should_save = True + break + best_score = max([ckpt[2].get(metric, 0) for ckpt in self.checkpoints]) + if scores.get(metric, 0) >= best_score: + should_save = True + break + + if should_save: + self.checkpoints.append((epoch, state_dict.copy(), scores)) + print(f"Checkpoint {epoch} saved: {scores}") + + def make_soup(self) -> dict: + """ + 制作 Checkpoint Soup + + Returns: + soup_state_dict: 平均后的权重 + """ + if not self.checkpoints: + raise ValueError("No checkpoints to average") + + # 初始化 soup + soup_state_dict = self.checkpoints[0][1].copy() + + # 累加所有 checkpoint + for _, ckpt, _ in self.checkpoints[1:]: + for key in soup_state_dict.keys(): + if key in ckpt: + soup_state_dict[key] += ckpt[key] + + # 平均 + num_checkpoints = len(self.checkpoints) + for key in soup_state_dict.keys(): + soup_state_dict[key] /= num_checkpoints + + print(f"Soup made from {num_checkpoints} checkpoints (epochs: {[ckpt[0] for ckpt in self.checkpoints]})") + return soup_state_dict + + def load_soup(self, model: nn.Module): + """加载 soup 到模型""" + soup = self.make_soup() + model.load_state_dict(soup) + return model + +# 使用示例 +# checkpoint_soup = CheckpointSoup(model, metrics=['auc', 'lrap', 'f1']) +# +# # 训练循环中 +# for epoch in range(num_epochs): +# train(...) +# scores = validate(...) +# checkpoint_soup.add_checkpoint(epoch, model.state_dict(), scores) +# +# # 训练结束后 +# final_model = checkpoint_soup.load_soup(model) +``` + +### 伪标签迭代训练（BirdCLEF 2024 - 2nd Place） + +2nd Place ADSR 的伪标签迭代训练循环： + +```python +import numpy as np +import torch +from typing import list + +class IterativePseudoLabeling: + """ + 伪标签迭代训练 + 参考：BirdCLEF 2024 2nd Place Solution + + 核心思想： + - 用当前集成生成伪标签 + - 用伪标签训练新模型 + - 新模型加入集成，重复循环 + """ + + def __init__( + self, + base_model_class, + pseudo_label_chance: float = 0.35, + amp_exp_min: float = -0.5, + amp_exp_max: float = 0.1, + num_iterations: int = 3, + ): + self.base_model_class = base_model_class + self.pseudo_label_chance = pseudo_label_chance + self.amp_exp_min = amp_exp_min + self.amp_exp_max = amp_exp_max + self.num_iterations = num_iterations + self.ensemble_models = [] + + def generate_pseudo_labels( + self, + unlabeled_audio_paths: list[str], + unlabeled_soundscapes: list[str] + ) -> list[dict]: + """ + 生成伪标签 + + Args: + unlabeled_audio_paths: 未标注音频路径 + unlabeled_soundscapes: 未标注 soundscape 路径 + + Returns: + pseudo_samples: [{audio_path, label_vector}, ...] + """ + pseudo_samples = [] + + for audio_path in unlabeled_soundscapes: + # 用集成模型预测 + predictions = [] + for model in self.ensemble_models: + pred = self.predict_with_model(model, audio_path) + predictions.append(pred) + + # 平均预测 + avg_pred = np.mean(predictions, axis=0) + pseudo_samples.append({ + 'audio_path': audio_path, + 'label_vector': avg_pred + }) + + return pseudo_samples + + def mix_pseudo_labels( + self, + train_sample: dict, + pseudo_sample: dict, + ) -> tuple[torch.Tensor, torch.Tensor]: + """ + 混合训练样本和伪标签样本 + + Args: + train_sample: 训练样本 {audio, label_vector} + pseudo_sample: 伪标签样本 {audio, label_vector} + + Returns: + mixed_audio: 混合后的音频 + mixed_label: 混合后的标签 + """ + train_audio = train_sample['audio'] + train_label = train_sample['label_vector'] + pseudo_audio = pseudo_sample['audio'] + pseudo_label = pseudo_sample['label_vector'] + + # 随机幅度系数 + amp_factor = 10 ** np.random.uniform(self.amp_exp_min, self.amp_exp_max) + + # 混合音频 + mixed_audio = train_audio * amp_factor + pseudo_audio * amp_factor + + # 混合标签（取 max） + mixed_label = np.maximum(train_label, pseudo_label) + + return mixed_audio, mixed_label + + def train_with_pseudo_labels( + self, + train_data: list[dict], + pseudo_samples: list[dict], + num_epochs: int = 50, + ): + """使用伪标签训练新模型""" + model = self.base_model_class() + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3) + criterion = torch.nn.BCEWithLogitsLoss() + + for epoch in range(num_epochs): + for train_sample in train_data: + # 随机决定是否添加伪标签 + if np.random.random() < self.pseudo_label_chance: + # 随机选择一个伪标签样本 + pseudo_sample = np.random.choice(pseudo_samples) + audio, label = self.mix_pseudo_labels(train_sample, pseudo_sample) + else: + audio = train_sample['audio'] + label = train_sample['label_vector'] + + # 训练步骤 + loss = self.train_step(model, audio, label, criterion) + loss.backward() + optimizer.step() + optimizer.zero_grad() + + return model + + def fit(self, train_data, unlabeled_soundscapes): + """完整的迭代训练循环""" + for iteration in range(self.num_iterations): + print(f"\n=== Iteration {iteration + 1}/{self.num_iterations} ===") + + # 生成伪标签 + pseudo_samples = self.generate_pseudo_labels(train_data, unlabeled_soundscapes) + print(f"Generated {len(pseudo_samples)} pseudo labels") + + # 训练新模型 + new_model = self.train_with_pseudo_labels(train_data, pseudo_samples) + self.ensemble_models.append(new_model) + + # 评估集成性能 + ensemble_score = self.evaluate_ensemble() + print(f"Ensemble score: {ensemble_score:.4f}") + + return self.ensemble_models +``` + +### Mel-Spectrogram 特征提取（BirdCLEF+ 2025） + +基于前排方案，统一的 mel-spectrogram 提取流程： + +```python +import torch +import torchaudio +import torch.nn as nn +import numpy as np + +class MelSpectrogramExtractor: + """统一的 Mel-Spectrogram 提取器""" + + def __init__( + self, + sample_rate: int = 32000, + n_mels: int = 128, + n_fft: int = 2048, + hop_length: int = 512, + fmin: float = 0.0, + fmax: float = 16000.0, + power: float = 2.0, + normalize: bool = True, + ): + self.sample_rate = sample_rate + self.n_mels = n_mels + self.n_fft = n_fft + self.hop_length = hop_length + self.fmin = fmin + self.fmax = fmax + + # 使用 torchaudio 的 MelSpectrogram + self.mel_transform = torchaudio.transforms.MelSpectrogram( + sample_rate=sample_rate, + n_fft=n_fft, + hop_length=hop_length, + n_mels=n_mels, + f_min=fmin, + f_max=fmax, + power=power, + normalized=normalize, + ) + + def extract(self, waveform: torch.Tensor) -> torch.Tensor: + """ + 提取 mel-spectrogram + + Args: + waveform: (num_samples,) 或 (batch, num_samples) + + Returns: + mel_spec: (n_mels, time) 或 (batch, n_mels, time) + """ + if waveform.dim() == 1: + waveform = waveform.unsqueeze(0) + + mel_spec = self.mel_transform(waveform) + + # 转换为对数尺度 + mel_spec = torch.log(mel_spec + 1e-9) + + return mel_spec + + def extract_fixed_length( + self, waveform: torch.Tensor, target_length: int + ) -> torch.Tensor: + """ + 提取固定长度的 mel-spectrogram（用于 5 秒音频） + + Args: + waveform: (num_samples,) + target_length: 目标时间维度 + + Returns: + mel_spec: (n_mels, target_length) + """ + mel_spec = self.extract(waveform).squeeze(0) + + # 调整到固定长度 + if mel_spec.shape[1] < target_length: + # 填充 + pad_length = target_length - mel_spec.shape[1] + mel_spec = nn.functional.pad(mel_spec, (0, pad_length)) + else: + # 裁剪（从中心） + start = (mel_spec.shape[1] - target_length) // 2 + mel_spec = mel_spec[:, start:start + target_length] + + return mel_spec + + +# 常用配置（前排方案） +CONFIGS = { + "config_128": { # tf_efficientnet 系列 + "n_mels": 128, + "n_fft": 2048, + "hop_length": 512, + "fmin": 0.0, + "fmax": 16000.0, + }, + "config_96": { # 轻量级模型 + "n_mels": 96, + "n_fft": 2048, + "hop_length": 512, + "fmin": 0.0, + "fmax": 16000.0, + }, + "config_256": { # 高分辨率 + "n_mels": 256, + "n_fft": 4096, + "hop_length": 1024, + "fmin": 0.0, + "fmax": 16000.0, + }, +} + +# 使用示例 +extractor = MelSpectrogramExtractor(**CONFIGS["config_128"]) +waveform, sr = torchaudio.load("audio.wav") +mel_spec = extractor.extract_fixed_length(waveform.squeeze(0), target_length=313) # 5秒 -> 313帧 +``` + +### 伪标签生成（BirdCLEF+ 2025） + +```python +import torch +import torch.nn as nn +import numpy as np +from pathlib import Path + +class PseudoLabelGenerator: + """伪标签生成器 - 基于前排方案""" + + def __init__( + self, + model: nn.Module, + threshold: float = 0.4, + use_segmentwise: bool = True, + power_transform: float = 1.0, + ): + """ + Args: + model: 训练好的模型 + threshold: 置信度阈值（前排方案使用 0.3-0.5） + use_segmentwise: 是否使用 segmentwise_logit（更细粒度） + power_transform: 幂次变换参数（1st Place 使用） + """ + self.model = model + self.model.eval() + self.threshold = threshold + self.use_segmentwise = use_segmentwise + self.power_transform = power_transform + + @torch.no_grad() + def generate_pseudo_labels( + self, + audio_path: str, + segment_duration: int = 5, + overlap: float = 0.5, + ) -> list[dict]: + """ + 生成伪标签 + + Returns: + List of {"start": float, "end": float, "labels": np.ndarray} + """ + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + + # 分段处理 + samples_per_segment = int(segment_duration * sr) + hop_length = int(samples_per_segment * (1 - overlap)) + + pseudo_labels = [] + + for start_idx in range(0, len(waveform) - samples_per_segment, hop_length): + end_idx = start_idx + samples_per_segment + segment = waveform[:, start_idx:end_idx] + + # 提取特征 + mel_spec = self.extract_mel(segment) + + # 模型预测 + if self.use_segmentwise: + # segmentwise_logit: 更细粒度的预测 + logits = self.model(mel_spec, return_segmentwise=True) + # 时间维度平均 + logits = logits.mean(dim=1) # (batch, num_classes) + else: + logits = self.model(mel_spec) + + # Sigmoid 激活 + probs = torch.sigmoid(logits).squeeze(0).cpu().numpy() + + # 幂次变换（1st Place 创新） + if self.power_transform != 1.0: + probs = np.power(probs, self.power_transform) + + # 高低阈值筛选（10th Place 方法） + mask = self._apply_threshold(probs) + + if mask.sum() > 0: + pseudo_labels.append({ + "start": start_idx / sr, + "end": end_idx / sr, + "labels": probs, + "mask": mask, + }) + + return pseudo_labels + + def _apply_threshold(self, probs: np.ndarray) -> np.ndarray: + """应用高低阈值筛选""" + # 高阈值：正样本 + high_threshold = 0.7 + # 低阈值：负样本 + low_threshold = 0.3 + + mask = np.zeros_like(probs, dtype=bool) + mask[probs >= high_threshold] = True # 高置信度正样本 + mask[probs <= low_threshold] = True # 低置信度负样本 + + return mask + + def extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram（简化版本）""" + # 实际使用中应该与训练时的提取器一致 + pass + + +# 使用示例（前排方案风格） +generator = PseudoLabelGenerator( + model=model, + threshold=0.4, + use_segmentwise=True, # 6th Place 关键 + power_transform=1.5, # 1st Place 幂次变换 +) + +pseudo_labels = generator.generate_pseudo_labels("train_soundscape_01.wav") +``` + +### MixUp 数据增强（BirdCLEF+ 2025） + +```python +import torch +import torch.nn as nn +import numpy as np + +class AudioMixUp: + """音频 MixUp 增强 - 前排方案风格""" + + def __init__( + self, + alpha: float = 0.5, + mixup_type: str = "hard", # "hard" 或 "soft" + probability: float = 0.5, + ): + """ + Args: + alpha: Beta 分布参数 + mixup_type: + - "soft": 标准混合标签（MixUp） + - "hard": 硬混合标签（8th Place 创新） + probability: 应用 MixUp 的概率 + """ + self.alpha = alpha + self.mixup_type = mixup_type + self.probability = probability + + def __call__( + self, + batch: dict, + ) -> dict: + """ + 应用 MixUp + + Args: + batch: {"mel": (B, C, H, W), "labels": (B, num_classes)} + + Returns: + Mixed batch + """ + if torch.rand(1).item() > self.probability: + return batch + + mel = batch["mel"] + labels = batch["labels"] + + batch_size = mel.size(0) + + # 生成混合权重 + lam = np.random.beta(self.alpha, self.alpha) + + # 随机排列 + index = torch.randperm(batch_size) + + # 混合特征 + mixed_mel = lam * mel + (1 - lam) * mel[index] + + # 混合标签 + if self.mixup_type == "soft": + # 标准 MixUp: 软标签混合 + mixed_labels = lam * labels + (1 - lam) * labels[index] + elif self.mixup_type == "hard": + # 硬 MixUp (8th Place): 混合标签的最大值 + mixed_labels = torch.maximum(labels, labels[index]) + else: + raise ValueError(f"Unknown mixup_type: {self.mixup_type}") + + return { + "mel": mixed_mel, + "labels": mixed_labels, + "lam": lam, # 可能用于损失调整 + } + + +# Sumix 增强（13th Place 使用） +class Sumix: + """Sumix: 原始信号上的 MixUp""" + + def __init__(self, alpha: float = 0.5, probability: float = 1.0): + self.alpha = alpha + self.probability = probability + + def __call__( + self, + waveform: torch.Tensor, + labels: torch.Tensor, + ) -> tuple[torch.Tensor, torch.Tensor]: + """ + 在原始波形上应用 Sumix + + Args: + waveform: (batch, num_samples) + labels: (batch, num_classes) + + Returns: + Mixed waveform and labels + """ + if torch.rand(1).item() > self.probability: + return waveform, labels + + batch_size = waveform.size(0) + lam = np.random.beta(self.alpha, self.alpha) + index = torch.randperm(batch_size) + + # 混合波形 + mixed_waveform = lam * waveform + (1 - lam) * waveform[index] + + # 混合标签（最大值） + mixed_labels = torch.maximum(labels, labels[index]) + + return mixed_waveform, mixed_labels + + +# 使用示例 +mixup = AudioMixUp(alpha=0.5, mixup_type="hard", probability=0.5) +sumix = Sumix(alpha=0.5, probability=1.0) + +# 训练循环中 +for batch in dataloader: + # Sumix 在原始波形 + waveform, labels = sumix(batch["waveform"], batch["labels"]) + + # 提取 mel-spectrogram + mel = extract_mel(waveform) + + # MixUp 在 mel-spectrogram + batch = mixup({"mel": mel, "labels": labels}) +``` + +### Soft AUC Loss（BirdCLEF+ 2025 - 4th Place） + +支持软标签的 AUC 损失函数： + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SoftAUCLoss(nn.Module): + """ + Soft AUC Loss - 4th Place 创新 + + 支持 soft labels，适用于知识蒸馏和半监督学习 + """ + + def __init__(self, reduction: str = "mean"): + super().__init__() + self.reduction = reduction + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) - 原始 logits + targets: (batch, num_classes) - 软标签 [0, 1] + + Returns: + AUC loss + """ + # Sigmoid 激活 + probs = torch.sigmoid(predictions) + + # 计算 AUC loss + # 对每个类别独立计算 + num_classes = predictions.size(1) + losses = [] + + for c in range(num_classes): + # 当前类别的预测和目标 + prob_c = probs[:, c] + target_c = targets[:, c] + + # 按目标值排序（软标签） + sorted_indices = torch.argsort(target_c, descending=True) + + # 计算正负样本的得分差异 + # 对于软标签，我们需要加权处理 + positive_scores = prob_c[sorted_indices[:len(sorted_indices)//2]] + negative_scores = prob_c[sorted_indices[len(sorted_indices)//2:]] + + # AUC 近似：正样本得分应该高于负样本 + # 使用 sigmoid 差异 + diff = positive_scores.unsqueeze(1) - negative_scores.unsqueeze(0) + loss_c = torch.sigmoid(-diff).mean() + + losses.append(loss_c) + + losses = torch.stack(losses) + + if self.reduction == "mean": + return losses.mean() + elif self.reduction == "sum": + return losses.sum() + else: + return losses + + +# 改进的 AUC Loss（更稳定） +class ImprovedAUCLoss(nn.Module): + """ + 改进的 AUC Loss - 更稳定且支持软标签 + """ + + def __init__(self, margin: float = 1.0): + super().__init__() + self.margin = margin + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) + targets: (batch, num_classes) - 软标签 + """ + probs = torch.sigmoid(predictions) + num_classes = predictions.size(1) + + losses = [] + for c in range(num_classes): + prob_c = probs[:, c] + target_c = targets[:, c] + + # 计算成对损失 + # 对于每个样本对 (i, j): + # 如果 target_i > target_j，则希望 prob_i > prob_j + n = prob_c.size(0) + if n < 2: + continue + + # 创建样本对矩阵 + target_diff = target_c.unsqueeze(1) - target_c.unsqueeze(0) + prob_diff = prob_c.unsqueeze(1) - prob_c.unsqueeze(0) + + # 只考虑 target_i > target_j 的对 + mask = target_diff > 0 + + if mask.sum() > 0: + # Hinge loss: max(0, margin - (prob_i - prob_j)) + loss_c = F.relu(self.margin - prob_diff)[mask].mean() + losses.append(loss_c) + + if len(losses) == 0: + return torch.tensor(0.0, device=predictions.device) + + return torch.stack(losses).mean() + + +# 使用示例 +criterion = SoftAUCLoss(reduction="mean") + +# 训练循环 +for batch in dataloader: + predictions = model(batch["mel"]) + + # 支持软标签 + loss = criterion(predictions, batch["labels"]) + + loss.backward() + optimizer.step() +``` + +### 滑动窗口推理（BirdCLEF+ 2025 - 1st Place） + +```python +import torch +import torch.nn as nn +from scipy.ndimage import gaussian_filter1d + +class SlidingWindowInference: + """ + 滑动窗口推理 - 1st Place 创新 + + 使用帧预测的平均值，而不是仅使用中心窗口的最大值 + """ + + def __init__( + self, + model: nn.Module, + window_size: int = 5, # 秒 + hop_size: int = 5, # 秒（步长） + sample_rate: int = 32000, + smoothing_sigma: float = 1.0, + ): + self.model = model + self.model.eval() + self.window_size = window_size + self.hop_size = hop_size + self.sample_rate = sample_rate + self.smoothing_sigma = smoothing_sigma + + @torch.no_grad() + def predict( + self, + audio_path: str, + ) -> dict[str, float]: + """ + 对整个音频进行预测，返回 5 秒窗口的预测 + + Returns: + Dict of {row_id: {species_id: probability}} + """ + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + + # 计算窗口参数 + samples_per_window = int(self.window_size * sr) + samples_per_hop = int(self.hop_size * sr) + + # 存储所有帧预测 + all_frame_predictions = [] + + # 滑动窗口 + window_id = 0 + for start_idx in range(0, len(waveform) - samples_per_window, samples_per_hop): + end_idx = start_idx + samples_per_window + window = waveform[:, start_idx:end_idx] + + # 提取特征 + mel_spec = self.extract_mel(window) + + # 模型预测 + frame_output = self.model(mel_spec) + + # 如果是 SED 模型，可能有 clipwise 和 segmentwise 输出 + if isinstance(frame_output, dict): + frame_pred = frame_output["clipwise_output"] + else: + frame_pred = frame_output + + all_frame_predictions.append(frame_pred.cpu().numpy()) + + window_id += 1 + + # 转换为 numpy array + all_frame_predictions = np.array(all_frame_predictions) # (num_windows, num_classes) + + # 1st Place 创新: 相邻窗口帧预测平均 + # 这是一种 1D 滑动窗口分割，类似于大图像的 2D 滑动窗口分割 + smoothed_predictions = self._smooth_predictions(all_frame_predictions) + + # 生成最终预测 + predictions = {} + for window_id in range(len(smoothed_predictions)): + row_id = f"soundscape_{window_id}_{self.window_size}" + predictions[row_id] = { + f"species_{i}": float(prob) + for i, prob in enumerate(smoothed_predictions[window_id]) + } + + return predictions + + def _smooth_predictions( + self, + predictions: np.ndarray, + ) -> np.ndarray: + """ + 平滑预测 - 使用高斯滤波和时间平均 + + Args: + predictions: (num_windows, num_classes) + + Returns: + Smoothed predictions + """ + # 1. 时间维度高斯平滑 + if self.smoothing_sigma > 0: + smoothed = gaussian_filter1d( + predictions, + sigma=self.smoothing_sigma, + axis=0, + mode="nearest", + ) + else: + smoothed = predictions + + # 2. 相邻窗口平均（1st Place 创新） + # 使用相邻 3 个窗口的平均 + kernel_size = 3 + if len(smoothed) >= kernel_size: + # Padding + padded = np.pad( + smoothed, + ((kernel_size // 2, kernel_size // 2), (0, 0)), + mode="edge", + ) + + # 一维卷积平均 + kernel = np.ones(kernel_size) / kernel_size + averaged = np.zeros_like(smoothed) + + for c in range(smoothed.shape[1]): + averaged[:, c] = np.convolve( + padded[:, c], + kernel, + mode="valid", + ) + + return averaged + else: + return smoothed + + def extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram""" + # 实际使用中应该与训练时的提取器一致 + pass + + +# 使用示例 +inference = SlidingWindowInference( + model=model, + window_size=5, + hop_size=5, + smoothing_sigma=1.0, +) + +predictions = inference.predict("test_soundscape_01.wav") + +# 后处理（可选） +# - Delta shift: 调整低置信度类别的概率 +# - Min-max 缩放 +# - 频率范围调整 +``` + +### SED 模型架构（BirdCLEF+ 2025 标准） + +前排方案广泛使用的 SED (Sound Event Detection) 模型架构： + +```python +import torch +import torch.nn as nn +import timm + +class SEDModel(nn.Module): + """ + Sound Event Detection 模型 + + 参考 BirdCLEF 2023 2nd Place 和 BirdCLEF+ 2025 前排方案 + """ + + def __init__( + self, + backbone: str = "tf_efficientnetv2_s.in21k", + num_classes: int = 206, + in_channels: int = 1, + pretrained: bool = True, + ): + super().__init__() + + self.num_classes = num_classes + + # 使用 timm 的 EfficientNet 作为 backbone + self.backbone = timm.create_model( + backbone, + pretrained=pretrained, + in_chans=in_channels, + num_classes=0, # 移除分类头 + ) + + # 获取 backbone 输出特征维度 + self.features_dim = self.backbone.num_features + + # 自定义注意力块 (6th Place AttBlockV2) + self.att_block = AttBlockV2( + self.features_dim, + num_classes, + activation="sigmoid", + ) + + def forward(self, x, return_segmentwise=False): + """ + Args: + x: (batch, in_channels, n_mels, time) + return_segmentwise: 是否返回 segmentwise_logit + + Returns: + 如果 return_segmentwise=False: + clipwise_output: (batch, num_classes) + 如果 return_segmentwise=True: + dict with: + clipwise_output: (batch, num_classes) + segmentwise_output: (batch, num_classes, time_frames) + """ + # Backbone 特征提取 + features = self.backbone(x) # (batch, features_dim, time_frames) + + # 全局池化 + pooled_features = features.mean(dim=[2]) # (batch, features_dim) + + # 片级预测 + clipwise_output = self.att_block(pooled_features) # (batch, num_classes) + + if not return_segmentwise: + return clipwise_output + + # 帧级预测（用于伪标签生成） + segmentwise_output = self.att_block(features) # (batch, num_classes, time_frames) + + return { + "clipwise_output": clipwise_output, + "segmentwise_output": segmentwise_output, + } + + +class AttBlockV2(nn.Module): + """ + 自定义注意力块 - 6th Place 创新 + + 使用 softmax 和 tanh 进行归一化，结合非线性变换 + """ + + def __init__( + self, + in_features: int, + out_features: int, + activation: str = "sigmoid", + ): + super().__init__() + + self.activation = activation + self.att = nn.Conv1d(in_features, out_features, kernel_size=1) + self.cla = nn.Conv1d(in_features, out_features, kernel_size=1) + + # 初始化权重（6th Place 关键） + self.apply(self._init_weights) + + def _init_weights(self, m): + if isinstance(m, nn.Conv1d): + nn.init.kaiming_normal_(m.weight, mode="fan_out", nonlinearity="relu") + if m.bias is not None: + nn.init.constant_(m.bias, 0) + + def forward(self, x): + """ + Args: + x: (batch, in_features, time_frames) 或 (batch, in_features) + + Returns: + output: (batch, out_features) 或 (batch, out_features, time_frames) + """ + if x.dim() == 2: + # 全局池化特征 + x = x.unsqueeze(-1) # (batch, in_features, 1) + + # 注意力权重 + att = self.att(x) + att = torch.softmax(att, dim=1) # 时间维度归一化 + + # 分类特征 + cla = self.cla(x) + + # 加权求和 + output = torch.clamp(torch.clamp((cla * att).sum(dim=-1), min=1e-7, max=1-1e-7), min=1e-7) + + # 激活函数 + if self.activation == "sigmoid": + output = torch.sigmoid(output) + elif self.activation == "none": + pass + else: + raise ValueError(f"Unknown activation: {self.activation}") + + return output.squeeze(-1) if output.size(-1) == 1 else output + + +# 常用 backbone 配置（前排方案） +BACKBONES = { + "tf_efficientnetv2_s.in21k": { + "features_dim": 1280, + "description": "2nd Place 使用，平衡性能和速度", + }, + "tf_efficientnetv2_b3.in21k": { + "features_dim": 1536, + "description": "6th Place 使用，更强性能", + }, + "tf_efficientnetv2_m.in21k": { + "features_dim": 2048, + "description": "14th Place 使用，更高精度", + }, + "eca_nfnet_l0": { + "features_dim": 2304, + "description": "2nd Place 使用，增加多样性", + }, +} + +# 使用示例 +model = SEDModel( + backbone="tf_efficientnetv2_s.in21k", + num_classes=206, + in_channels=1, + pretrained=True, +) + +# 训练时：片级预测 +clipwise_output = model(mel_spec) +loss = criterion(clipwise_output, labels) + +# 伪标签生成时：帧级预测 +output = model(mel_spec, return_segmentwise=True) +segmentwise_logits = output["segmentwise_output"] # (batch, 206, time_frames) +segmentwise_probs = torch.sigmoid(segmentwise_logits) +# 时间维度平均得到更稳定的伪标签 +avg_segmentwise_probs = segmentwise_probs.mean(dim=-1) # (batch, 206) +``` + +### 前排方案详细技术分析 + +#### 2nd Place - Xeno-Canto 预训练详细流程 + +**作者**: Volodymyr Vialactea +**核心创新**: 使用外部数据预训练 + 5秒音频片段训练 + +**完整流程：** + +```python +import torch +import torchaudio +import pandas as pd +from pathlib import Path + +class XenoCantoPretraining: + """ + 2nd Place 方案：Xeno-Canto 预训练流程 + + 关键点： + 1. 下载额外的 Xeno-Canto 数据 + 2. 数据清洗和预处理 + 3. 预训练 + 4. 在主数据集上微调 + """ + + def __init__( + self, + species_list: list, + target_sample_rate: int = 32000, + segment_duration: int = 5, + ): + self.species_list = species_list + self.target_sample_rate = target_sample_rate + self.segment_duration = segment_duration + + def download_xeno_canto_data(self, output_dir: str = "data/xeno_canto"): + """ + 步骤 1: 从 Xeno-Canto 下载数据 + + 注意事项： + - 过滤掉当年比赛中的物种（避免数据泄漏） + - 只下载高质量录音（评分 ≥ 3.0） + - 限制每个物种的下载量（避免数据不平衡） + """ + # 使用 xeno-canto-api 或手动下载 + # 这里提供框架代码 + + xc_species = [s for s in self.species_list if self._should_download(s)] + + for species in xc_species: + # 调用 Xeno-Canto API + # 下载音频文件 + # 保存到 output_dir/species_name/ + pass + + def _should_download(self, species: str) -> bool: + """检查物种是否应该下载（避免数据泄漏）""" + # 过滤比赛数据集中的物种 + competition_species = set(self._get_competition_species()) + return species not in competition_species + + def preprocess_xeno_canto(self, audio_dir: str): + """ + 步骤 2: 数据清洗和预处理 + + 2nd Place 的关键步骤： + 1. 去除人声（如果可能） + 2. 统一采样率到 32kHz + 3. 音频归一化 + 4. 质量检查（SNR、时长等） + """ + audio_files = list(Path(audio_dir).rglob("*.mp3")) + + cleaned_data = [] + + for audio_file in audio_files: + # 加载音频 + waveform, sr = torchaudio.load(audio_file) + + # 重采样到 32kHz + if sr != self.target_sample_rate: + resampler = torchaudio.transforms.Resample(sr, self.target_sample_rate) + waveform = resampler(waveform) + + # 质量检查 + if self._check_quality(waveform): + # 提取 5 秒片段 + segments = self._extract_segments(waveform) + + for segment in segments: + cleaned_data.append({ + "file_path": str(audio_file), + "species": audio_file.parent.name, + "waveform": segment, + }) + + return cleaned_data + + def _check_quality(self, waveform: torch.Tensor) -> bool: + """质量检查""" + # 检查 1: 时长至少 5 秒 + if waveform.shape[1] < self.target_sample_rate * self.segment_duration: + return False + + # 检查 2: SNR（信噪比） + # snr = self._calculate_snr(waveform) + # if snr < 10: # 最低 10dB + # return False + + # 检查 3: 削波检测 + if torch.abs(waveform).max() > 0.99: + return False + + return True + + def _extract_segments(self, waveform: torch.Tensor) -> list: + """ + 提取 5 秒音频片段 + + 2nd Place 使用了多种采样策略： + 1. 随机采样 + 2. 基于能量的采样（RMS） + 3. 重叠采样 + """ + segment_samples = self.segment_duration * self.target_sample_rate + + if waveform.shape[1] <= segment_samples: + # 填充到 5 秒 + padding = segment_samples - waveform.shape[1] + waveform = torch.nn.functional.pad(waveform, (0, padding)) + return [waveform] + + # 方法 1: 随机采样 + # 2nd Place 尝试了多种方法，最终发现随机采样效果最好 + + # 方法 2: 基于能量的采样（RMS） + # 计算每个 5 秒窗口的 RMS 能量 + # 选择能量最高的窗口 + + # 方法 3: 重叠采样 + # 滑动窗口，hop_size = 2.5 秒 + + # 这里实现随机采样 + max_start = waveform.shape[1] - segment_samples + start_idx = torch.randint(0, max_start, (1,)).item() + + segment = waveform[:, start_idx:start_idx + segment_samples] + return [segment] + + def pretrain(self, xc_data, model, save_path: str = "checkpoints/pretrained.pth"): + """ + 步骤 3: 预训练 + + 2nd Place 的预训练策略： + - 使用 Xeno-Canto 数据训练 + - BCE Loss + - SpecAugment 增强 + - 50-100 epochs + """ + # 创建 dataloader + train_loader = self._create_dataloader(xc_data) + + # 优化器 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3) + + # 学习率调度器 + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=50, eta_min=1e-6 + ) + + # 损失函数 + criterion = nn.BCEWithLogitsLoss() + + # 训练循环 + model.train() + for epoch in range(50): # 50 epochs + for batch in train_loader: + mel_spec = self._extract_mel(batch["waveform"]) + labels = batch["labels"] + + # 前向传播 + logits = model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + scheduler.step() + + print(f"Epoch {epoch+1}/50, Loss: {loss.item():.4f}") + + # 保存预训练模型 + torch.save(model.state_dict(), save_path) + print(f"Pretrained model saved to {save_path}") + + def finetune(self, model, train_data, val_data, pretrained_path: str): + """ + 步骤 4: 微调 + + 2nd Place 的微调策略： + - 加载预训练权重 + - 使用更小的学习率 + - 选择最佳 checkpoint（不是最后一个） + - 关键：AUC 从 0.83-0.84 跳升至 0.86-0.87 + """ + # 加载预训练权重 + model.load_state_dict(torch.load(pretrained_path)) + + # 优化器（更小的学习率） + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-4) + + # 学习率调度器 + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=30, eta_min=1e-7 + ) + + # 损失函数 + criterion = nn.BCEWithLogitsLoss() + + best_val_score = 0 + best_epoch = 0 + + # 微调循环 + model.train() + for epoch in range(30): # 30 epochs + # 训练 + for batch in train_data: + mel_spec = self._extract_mel(batch["waveform"]) + labels = batch["labels"] + + logits = model(mel_spec) + loss = criterion(logits, labels) + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + # 验证 + val_score = self._validate(model, val_data) + + print(f"Epoch {epoch+1}/30, Val AUC: {val_score:.4f}") + + # 保存最佳模型 + if val_score > best_val_score: + best_val_score = val_score + best_epoch = epoch + torch.save(model.state_dict(), f"checkpoints/best_finetuned_epoch{epoch}.pth") + + scheduler.step() + + print(f"Best epoch: {best_epoch}, Best Val AUC: {best_val_score:.4f}") + + def _extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram（应该与训练时一致）""" + # 实现 mel-spectrogram 提取 + pass + + def _create_dataloader(self, data): + """创建 dataloader""" + pass + + def _validate(self, model, val_data): + """验证""" + pass + + def _get_competition_species(self) -> list: + """获取竞赛数据集中的物种（避免数据泄漏）""" + pass + + def _calculate_snr(self, waveform: torch.Tensor) -> float: + """计算 SNR""" + pass + + +# 2nd Place 关键技术总结 +""" +关键发现（来自 2nd Place writeup）： + +1. **预训练效果显著**： + - 无预训练：AUC 0.83-0.84 + - 有预训练：AUC 0.86-0.87 + - 提升：+0.02-0.03 AUC + +2. **Checkpoint 选择很重要**： + - 不是最后一个 epoch 最好 + - 需要验证集选择最佳 checkpoint + - 通常在 epoch 10-20 之间 + +3. **采样策略**： + - 随机采样效果最好 + - 基于能量的采样没有明显优势 + - 5 秒片段是最佳长度 + +4. **数据增强**： + - SpecAugment 必须保留 + - RandomFiltering 有效 + - 即使关闭略微提高 CV，但保留确保 LB 稳定性 +""" +``` + +#### 5th Place - Self-Distillation 详细实现 + +**作者**: Noir +**核心创新**: 三阶段自蒸馏 + Silero VAD 数据清洗 + +**完整流程：** + +```python +import torch +import torch.nn as nn +import numpy as np + +class SelfDistillationTrainer: + """ + 5th Place 方案：Self-Distillation 三阶段训练 + + 核心思想： + 1. 使用 Silero VAD 去除人声 + 2. 三阶段自蒸馏训练 + 3. 迭代丰富次要标签 + """ + + def __init__( + self, + model: nn.Module, + num_classes: int = 206, + ): + self.model = model + self.num_classes = num_classes + + def stage1_initial_training(self, train_loader, val_loader, epochs=30): + """ + 阶段 1: 初始训练 + + 使用清洗后的训练音频（train_audio）进行初始训练 + """ + print("=== Stage 1: Initial Training ===") + + optimizer = torch.optim.AdamW(self.model.parameters(), lr=1e-3) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-6 + ) + criterion = nn.BCEWithLogitsLoss() + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + for batch in train_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + # 前向传播 + logits = self.model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证 + val_loss = self._validate(self.model, val_loader, criterion) + + # 学习率更新 + scheduler.step() + + print(f"Epoch {epoch+1}/{epochs}, Train Loss: {train_loss/len(train_loader):.4f}, " + f"Val Loss: {val_loss:.4f}") + + # 保存最佳模型 + if val_loss < best_val_loss: + best_val_loss = val_loss + torch.save(self.model.state_dict(), "checkpoints/stage1_best.pth") + + print(f"Stage 1 complete. Best Val Loss: {best_val_loss:.4f}") + + # 加载最佳模型用于下一阶段 + self.model.load_state_dict(torch.load("checkpoints/stage1_best.pth")) + + def stage2_self_distillation_train_audio( + self, + train_loader, + epochs=20, + temperature=3.0, + alpha=0.7, + ): + """ + 阶段 2: 使用 train_audio 的自蒸馏 + + 使用 stage 1 模型的预测作为软标签进行蒸馏 + """ + print("=== Stage 2: Self-Distillation on train_audio ===") + + # stage 1 模型作为教师 + teacher_model = type(self.model)( + backbone=self.model.backbone, + num_classes=self.num_classes, + ) + teacher_model.load_state_dict(torch.load("checkpoints/stage1_best.pth")) + teacher_model.eval() + + # 学生模型（可以重置权重或继续训练） + # 5th Place 选择继续训练 + + optimizer = torch.optim.AdamW(self.model.parameters(), lr=5e-4) # 更小的学习率 + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-7 + ) + + # 蒸馏损失 + distillation_criterion = nn.KLDivLoss(reduction="batchmean") + bce_criterion = nn.BCEWithLogitsLoss() + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + for batch in train_loader: + mel_spec = batch['mel_spec'] + hard_labels = batch['labels'] + + with torch.no_grad(): + # 教师模型预测（软标签） + teacher_logits = teacher_model(mel_spec) + teacher_probs = torch.sigmoid(teacher_logits / temperature) + + # 学生模型预测 + student_logits = self.model(mel_spec) + student_log_probs = torch.log_softmax(student_logits / temperature, dim=-1) + + # 蒸馏损失 + distill_loss = distillation_criterion(student_log_probs, teacher_probs) + + # 硬标签损失 + bce_loss = bce_criterion(student_logits, hard_labels) + + # 组合损失 + loss = alpha * (temperature ** 2) * distill_loss + (1 - alpha) * bce_loss + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证 + val_loss = self._validate(self.model, train_loader, bce_criterion) # 用训练集验证 + + scheduler.step() + + print(f"Epoch {epoch+1}/{epochs}, Train Loss: {train_loss/len(train_loader):.4f}, " + f"Val Loss: {val_loss:.4f}") + + if val_loss < best_val_loss: + best_val_loss = val_loss + torch.save(self.model.state_dict(), "checkpoints/stage2_best.pth") + + print(f"Stage 2 complete. Best Val Loss: {best_val_loss:.4f}") + + self.model.load_state_dict(torch.load("checkpoints/stage2_best.pth")) + + def stage3_self_distillation_soundscape( + self, + train_audio_loader, + soundscape_files, + epochs=20, + temperature=3.0, + alpha=0.5, # 更重视伪标签 + ): + """ + 阶段 3: 结合 train_audio 和 train_soundscapes 的自蒸馏 + + 关键创新：丰富次要标签 + - 许多音频包含未标注的鸟叫声 + - 通过自蒸馏发现这些次要标签 + """ + print("=== Stage 3: Self-Distillation with soundscape ===") + + # stage 2 模型作为教师 + teacher_model = type(self.model)( + backbone=self.model.backbone, + num_classes=self.num_classes, + ) + teacher_model.load_state_dict(torch.load("checkpoints/stage2_best.pth")) + teacher_model.eval() + + optimizer = torch.optim.AdamW(self.model.parameters(), lr=3e-4) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-7 + ) + + distillation_criterion = nn.KLDivLoss(reduction="batchmean") + bce_criterion = nn.BCEWithLogitsLoss() + + # 生成 soundscape 的伪标签 + soundscape_pseudo_labels = self._generate_pseudo_labels( + teacher_model, soundscape_files + ) + + # 合并 train_audio 和 soundscape 数据 + # 50% train_audio + 50% soundscape + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + # 训练 train_audio（带硬标签） + for batch in train_audio_loader: + if np.random.rand() > 0.5: + continue # 50% 概率使用 train_audio + + mel_spec = batch['mel_spec'] + hard_labels = batch['labels'] + + with torch.no_grad(): + teacher_logits = teacher_model(mel_spec) + teacher_probs = torch.sigmoid(teacher_logits / temperature) + + student_logits = self.model(mel_spec) + student_log_probs = torch.log_softmax(student_logits / temperature, dim=-1) + + distill_loss = distillation_criterion(student_log_probs, teacher_probs) + bce_loss = bce_criterion(student_logits, hard_labels) + loss = alpha * (temperature ** 2) * distill_loss + (1 - alpha) * bce_loss + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 训练 soundscape（伪标签） + for batch in soundscape_pseudo_labels: + if np.random.rand() <= 0.5: + continue # 50% 概率使用 soundscape + + mel_spec = batch['mel_spec'] + pseudo_labels = batch['labels'] # 软标签 + + with torch.no_grad(): + teacher_logits = teacher_model(mel_spec) + teacher_probs = torch.sigmoid(teacher_logits / temperature) + + student_logits = self.model(mel_spec) + student_log_probs = torch.log_softmax(student_logits / temperature, dim=-1) + + # 只使用蒸馏损失（没有硬标签） + distill_loss = distillation_criterion(student_log_probs, teacher_probs) + + optimizer.zero_grad() + distill_loss.backward() + optimizer.step() + + train_loss += distill_loss.item() + + scheduler.step() + + print(f"Epoch {epoch+1}/{epochs}, Train Loss: {train_loss:.4f}") + + # 保存检查点 + if epoch % 5 == 0: + torch.save(self.model.state_dict(), f"checkpoints/stage3_epoch{epoch}.pth") + + print("Stage 3 complete") + + def _generate_pseudo_labels( + self, + model: nn.Module, + audio_files: list, + ) -> list: + """ + 生成 soundscape 的伪标签 + + 关键：丰富次要标签 + - 使用帧级预测（segmentwise） + - 时间维度平均 + """ + model.eval() + pseudo_labels = [] + + with torch.no_grad(): + for audio_file in audio_files: + # 加载音频 + waveform, sr = torchaudio.load(audio_file) + + # 分段处理（5秒窗口） + segments = self._split_audio(waveform, sr) + + for segment in segments: + mel_spec = self._extract_mel(segment) + + # 获取帧级预测 + output = model(mel_spec, return_segmentwise=True) + segmentwise_logits = output["segmentwise_output"] # (1, 206, time) + segmentwise_probs = torch.sigmoid(segmentwise_logits) + + # 时间维度平均（关键：丰富次要标签） + avg_probs = segmentwise_probs.mean(dim=-1).squeeze(0) # (206,) + + pseudo_labels.append({ + "mel_spec": mel_spec, + "labels": avg_probs, + }) + + return pseudo_labels + + def _split_audio(self, waveform: torch.Tensor, sr: int) -> list: + """分段处理音频""" + segment_samples = 5 * sr + segments = [] + + for i in range(0, waveform.shape[1], segment_samples): + segment = waveform[:, i:i+segment_samples] + if segment.shape[1] == segment_samples: + segments.append(segment) + else: + # 填充 + padding = segment_samples - segment.shape[1] + segment = torch.nn.functional.pad(segment, (0, padding)) + segments.append(segment) + + return segments + + def _extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram""" + pass + + def _validate(self, model, val_loader, criterion): + """验证""" + model.eval() + total_loss = 0 + + with torch.no_grad(): + for batch in val_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + logits = model(mel_spec) + loss = criterion(logits, labels) + total_loss += loss.item() + + return total_loss / len(val_loader) + + +class SileroVADDataCleaner: + """ + Silero VAD 数据清洗 + + 5th Place 使用 Silero VAD 检测并去除人声片段 + """ + + def __init__(self): + # 加载 Silero VAD 模型 + self.model, utils = torch.hub.load( + repo_or_dir='snakers4/silero-vad', + model='silero_vad', + force_reload=False, + onnx=False + ) + self.model.eval() + + def clean_audio(self, audio_path: str, output_path: str): + """ + 去除包含人声的音频片段 + + Returns: + 清洗后的音频（去除人声部分） + """ + waveform, sr = torchaudio.load(audio_path) + + # 转换为单声道 + if waveform.shape[0] > 1: + waveform = waveform.mean(dim=0, keepdim=True) + + # 重采样到 16kHz（Silero VAD 要求） + if sr != 16000: + resampler = torchaudio.transforms.Resample(sr, 16000) + waveform = resampler(waveform) + sr = 16000 + + # VAD 检测 + speech_chunks = self._detect_speech(waveform, sr) + + # 如果检测到人声，去除这些片段 + if speech_chunks: + cleaned_waveform = self._remove_speech_chunks(waveform, speech_chunks) + else: + cleaned_waveform = waveform + + # 保存清洗后的音频 + torchaudio.save(output_path, cleaned_waveform, sr) + + return cleaned_waveform + + def _detect_speech(self, waveform: torch.Tensor, sr: int) -> list: + """ + 检测人声片段 + + Returns: + List of (start_ms, end_ms) tuples + """ + # 获取语音概率 + speech_probs = [] + window_size = 512 # 32ms at 16kHz + + for i in range(0, waveform.shape[1], window_size): + chunk = waveform[:, i:i+window_size] + if chunk.shape[1] < window_size: + continue + + with torch.no_grad(): + speech_prob = self.model(chunk, sr).item() + speech_probs.append(speech_prob) + + # 阈值检测（人声概率 > 0.5） + speech_chunks = [] + in_speech = False + start_idx = 0 + + for i, prob in enumerate(speech_probs): + if prob > 0.5 and not in_speech: + in_speech = True + start_idx = i * window_size + elif prob <= 0.5 and in_speech: + in_speech = False + end_idx = i * window_size + speech_chunks.append((start_idx, end_idx)) + + # 转换为毫秒 + speech_chunks_ms = [(s * 1000 / sr, e * 1000 / sr) for s, e in speech_chunks] + + return speech_chunks_ms + + def _remove_speech_chunks( + self, + waveform: torch.Tensor, + speech_chunks: list, + ) -> torch.Tensor: + """去除人声片段""" + sr = 16000 + + # 将时间转换为样本索引 + speech_ranges = [(int(s * sr / 1000), int(e * sr / 1000)) for s, e in speech_chunks] + + # 创建掩码（True 表示保留） + mask = torch.ones(waveform.shape[1], dtype=torch.bool) + + for start, end in speech_ranges: + mask[start:end] = False + + # 应用掩码 + cleaned_waveform = waveform[:, mask] + + return cleaned_waveform + + +# 5th Place 关键技术总结 +""" +关键发现（来自 5th Place writeup）： + +1. **Silero VAD 有效**： + - 去除人声减少误检 + - 清洗后数据质量提升 + +2. **三阶段自蒸馏**： + - Stage 1: 基础训练 + - Stage 2: train_audio 自蒸馏 + - Stage 3: 加入 soundscape 伪标签 + - 每个阶段都带来提升 + +3. **丰富次要标签**： + - 许多音频包含未标注的鸟叫声 + - 使用帧级预测和时间平均 + - 迭代训练发现更多标签 + +4. **数据平衡重要**： + - 样本 <20 的类别复制到 20 + - 样本 <30 的类别手动筛选 + - 使用前 30/60 秒数据 +""" +``` + +#### 1st Place - Multi-Iterative Noisy Student 详细流程 + +**作者**: Nikita Babych +**核心创新**: 多迭代 Noisy Student + MixUp + 幂次变换 + +**完整流程：** + +```python +import torch +import torch.nn as nn +import numpy as np + +class MultiIterativeNoisyStudent: + """ + 1st Place 方案：多迭代 Noisy Student 自训练 + + 核心创新： + 1. 多迭代自训练，每次使用 MixUp + 2. 伪标签幂次变换减少噪声 + 3. 滑动窗口推理，帧预测平均 + """ + + def __init__( + self, + model: nn.Module, + num_classes: int = 206, + num_iterations: int = 3, + ): + self.model = model + self.num_classes = num_classes + self.num_iterations = num_iterations + + # 1st Place 关键参数 + self.mixup_alpha = 0.5 + self.power_transform = 1.5 # 幂次变换参数（减少伪标签噪声） + + def train_iteration( + self, + train_audio_loader, + train_soundscape_files, + iteration: int, + epochs=30, + ): + """ + 执行一次 Noisy Student 迭代 + + Args: + iteration: 当前迭代编号（0, 1, 2, ...） + """ + print(f"=== Noisy Student Iteration {iteration + 1} ===") + + # 准备数据 + # 50% train_audio + 50% 伪标签 soundscape + if iteration == 0: + # 第一次迭代：只使用 train_audio + train_loader = train_audio_loader + else: + # 后续迭代：混合 train_audio 和伪标签 + train_loader = self._prepare_mixed_data( + train_audio_loader, + train_soundscape_files, + iteration, + ) + + # 优化器 + optimizer = torch.optim.AdamW(self.model.parameters(), lr=1e-3) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-6 + ) + criterion = nn.BCEWithLogitsLoss() + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + for batch in train_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + # MixUp 数据增强（1st Place 关键） + if np.random.rand() < 0.5: # 50% 概率应用 MixUp + mel_spec, labels = self._apply_mixup(mel_spec, labels) + + # 前向传播 + logits = self.model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证（使用训练集的一个子集） + val_loss = self._quick_validate(train_audio_loader, criterion) + + scheduler.step() + + print(f"Iteration {iteration+1}, Epoch {epoch+1}/{epochs}, " + f"Train Loss: {train_loss/len(train_loader):.4f}, " + f"Val Loss: {val_loss:.4f}") + + if val_loss < best_val_loss: + best_val_loss = val_loss + torch.save(self.model.state_dict(), + f"checkpoints/noisy_student_iter{iteration}_best.pth") + + print(f"Iteration {iteration+1} complete. Best Val Loss: {best_val_loss:.4f}") + + def _prepare_mixed_data( + self, + train_audio_loader, + soundscape_files, + iteration: int, + ): + """ + 准备混合数据：train_audio + 伪标签 soundscape + + 关键：幂次变换减少伪标签噪声（1st Place 创新） + """ + # 生成伪标签 + pseudo_labels = self._generate_pseudo_labels_power_transform( + soundscape_files, + self.power_transform, + ) + + # 创建混合 dataloader + mixed_data = [] + + # 添加 train_audio + for batch in train_audio_loader: + mixed_data.append(batch) + + # 添加伪标签 soundscape + for item in pseudo_labels: + mixed_data.append(item) + + # 打乱顺序 + np.random.shuffle(mixed_data) + + return mixed_data + + def _generate_pseudo_labels_power_transform( + self, + audio_files: list, + power: float = 1.5, + ) -> list: + """ + 生成伪标签并应用幂次变换 + + 1st Place 关键创新：幂次变换减少噪声 + + 原理： + - 直接对概率进行温度缩放会提高噪声的概率 + - 通过幂次变换，防止噪声的放大，并保留重要的标签信号 + """ + self.model.eval() + pseudo_labels = [] + + with torch.no_grad(): + for audio_file in audio_files: + waveform, sr = torchaudio.load(audio_file) + + # 分段处理（5秒窗口） + segments = self._split_audio(waveform, sr) + + for segment in segments: + mel_spec = self._extract_mel(segment) + + # 获取预测 + logits = self.model(mel_spec) + probs = torch.sigmoid(logits).squeeze(0).cpu().numpy() # (206,) + + # 幂次变换（1st Place 创新） + # power > 1: 压缩低概率，扩展高概率 + # power < 1: 扩展低概率，压缩高概率 + probs_transformed = np.power(probs, power) + + pseudo_labels.append({ + "mel_spec": mel_spec, + "labels": torch.tensor(probs_transformed, dtype=torch.float32), + }) + + return pseudo_labels + + def _apply_mixup( + self, + mel_spec: torch.Tensor, + labels: torch.Tensor, + ) -> tuple: + """ + MixUp 数据增强 + + 1st Place 关键：使用固定混合权重 0.5 + """ + batch_size = mel_spec.size(0) + + # 生成混合权重 + lam = np.random.beta(self.mixup_alpha, self.mixup_alpha) + # 1st Place 发现固定权重 0.5 效果更好 + # lam = 0.5 + + # 随机排列 + index = torch.randperm(batch_size) + + # 混合特征 + mixed_mel = lam * mel_spec + (1 - lam) * mel_spec[index] + + # 混合标签（取最大值） + mixed_labels = torch.maximum(labels, labels[index]) + + return mixed_mel, mixed_labels + + def _split_audio(self, waveform: torch.Tensor, sr: int) -> list: + """分段处理音频""" + segment_samples = 5 * sr + segments = [] + + for i in range(0, waveform.shape[1], segment_samples): + segment = waveform[:, i:i+segment_samples] + if segment.shape[1] == segment_samples: + segments.append(segment) + else: + padding = segment_samples - segment.shape[1] + segment = torch.nn.functional.pad(segment, (0, padding)) + segments.append(segment) + + return segments + + def _extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram""" + pass + + def _quick_validate(self, val_loader, criterion): + """快速验证""" + self.model.eval() + total_loss = 0 + count = 0 + + with torch.no_grad(): + for i, batch in enumerate(val_loader): + if i >= 10: # 只验证前 10 个 batch + break + + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + logits = self.model(mel_spec) + loss = criterion(logits, labels) + total_loss += loss.item() + count += 1 + + return total_loss / max(count, 1) + + +# 1st Place 关键技术总结 +""" +关键发现（来自 1st Place writeup）： + +1. **多迭代 Noisy Student 有效**： + - 每次迭代都带来提升 + - 3 次迭代是最优的 + - 更多迭代可能导致噪声累积 + +2. **幂次变换是关键**： + - 直接使用伪标签：性能提升有限 + - 幂次变换（power=1.5）：显著提升 + - 防止噪声放大，保留信号 + +3. **MixUp 策略**： + - 固定权重 0.5 比随机权重更稳定 + - 迫使模型学习更鲁棒的特征 + - 减少过拟合 + +4. **滑动窗口推理**： + - 使用帧预测的平均值 + - 避免丢弃有价值的预测数据 + - 类似图像的 2D 滑动窗口分割 +""" + + +# 1st Place 完整训练流程示例 +def train_noisy_student_full_pipeline(): + """ + 完整的 Noisy Student 训练流程 + """ + # 初始化 + model = SEDModel(num_classes=206) + trainer = MultiIterativeNoisyStudent(model, num_iterations=3) + + # 准备数据 + train_audio_loader = ... # 训练音频 loader + soundscape_files = ... # soundscape 文件列表 + + # 迭代 0: 只使用 train_audio + print("=== Iteration 0: Training on train_audio only ===") + trainer.train_iteration(train_audio_loader, soundscape_files, iteration=0, epochs=30) + + # 迭代 1: 加入伪标签 soundscape + print("=== Iteration 1: Adding pseudo-labeled soundscape ===") + trainer.train_iteration(train_audio_loader, soundscape_files, iteration=1, epochs=30) + + # 迭代 2: 使用新的伪标签 + print("=== Iteration 2: Refreshing pseudo labels ===") + trainer.train_iteration(train_audio_loader, soundscape_files, iteration=2, epochs=30) + + # 最终集成：使用不同迭代的模型 + model_iter0 = SEDModel(num_classes=206) + model_iter0.load_state_dict(torch.load("checkpoints/noisy_student_iter0_best.pth")) + + model_iter1 = SEDModel(num_classes=206) + model_iter1.load_state_dict(torch.load("checkpoints/noisy_student_iter1_best.pth")) + + model_iter2 = SEDModel(num_classes=206) + model_iter2.load_state_dict(torch.load("checkpoints/noisy_student_iter2_best.pth")) + + # 集成预测 + def ensemble_predict(mel_spec): + pred0 = torch.sigmoid(model_iter0(mel_spec)) + pred1 = torch.sigmoid(model_iter1(mel_spec)) + pred2 = torch.sigmoid(model_iter2(mel_spec)) + + # 简单平均 + ensemble_pred = (pred0 + pred1 + pred2) / 3 + return ensemble_pred + + return ensemble_predict +``` + +#### 4th Place - Soft AUC Loss 详细分析 + +**作者**: dylan.liu +**核心创新**: 支持软标签的 AUC 损失函数 + +**问题背景：** +- 标准 AUC 损失函数不支持软标签（适用于知识蒸馏和半监督学习） +- 4th Place 通过自定义 soft AUC loss 解决这个问题 +- 效果：从 11 名跃升至 4 名（LB 从 0.850 → 0.901） + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SoftAUCLoss_v4(nn.Module): + """ + 4th Place Soft AUC Loss 实现 + + 参考：4th Place writeup + 效果：LB 从 0.850 → 0.901（显著提升） + + 核心思想： + 1. 支持 soft labels（适用于知识蒸馏和半监督学习） + 2. 通过正负样本对的排序关系优化 AUC + 3. 减少 overfitting + """ + + def __init__( + self, + margin: float = 1.0, + reduction: str = "mean", + ): + super().__init__() + self.margin = margin + self.reduction = reduction + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) - 原始 logits + targets: (batch, num_classes) - 软标签 [0, 1] + + Returns: + AUC loss + """ + probs = torch.sigmoid(predictions) + num_classes = predictions.size(1) + losses = [] + + for c in range(num_classes): + prob_c = probs[:, c] # (batch,) + target_c = targets[:, c] # (batch,) + + # 计算所有样本对的差异 + # 对于软标签，我们需要加权处理 + + # 创建样本对矩阵 + # target_diff > 0 表示 target_i > target_j + target_diff = target_c.unsqueeze(1) - target_c.unsqueeze(0) # (batch, batch) + prob_diff = prob_c.unsqueeze(1) - prob_c.unsqueeze(0) # (batch, batch) + + # 只考虑 target_i > target_j 的对 + # 即正样本（高 target）应该有更高的预测概率 + mask = target_diff > 0 + + if mask.sum() > 0: + # Hinge loss: max(0, margin - (prob_i - prob_j)) + # 理想情况：prob_i > prob_j（正样本预测高于负样本） + # margin - (prob_i - prob_j) 应该 <= 0 + # 如果 > 0，说明违反了排序关系 + + loss_c = F.relu(self.margin - prob_diff)[mask].mean() + + # 4th Place 发现加权版本更有效 + # 使用 target_diff 作为权重 + # weight = target_diff[mask] + # weighted_loss = F.relu(self.margin - prob_diff)[mask] * weight + # loss_c = weighted_loss.sum() / weight.sum() + + losses.append(loss_c) + + if len(losses) == 0: + return torch.tensor(0.0, device=predictions.device, requires_grad=True) + + losses = torch.stack(losses) + + if self.reduction == "mean": + return losses.mean() + elif self.reduction == "sum": + return losses.sum() + else: + return losses + + +class SoftAUCLoss_Advanced(nn.Module): + """ + 改进的 Soft AUC Loss + + 结合 4th Place 的发现和其他优化： + 1. 温度缩放 + 2. 自适应 margin + 3. 类别加权 + """ + + def __init__( + self, + margin: float = 1.0, + temperature: float = 1.0, + use_class_weighting: bool = True, + ): + super().__init__() + self.margin = margin + self.temperature = temperature + self.use_class_weighting = use_class_weighting + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) + targets: (batch, num_classes) - 软标签 + """ + # 温度缩放 + probs = torch.sigmoid(predictions / self.temperature) + num_classes = predictions.size(1) + + losses = [] + + for c in range(num_classes): + prob_c = probs[:, c] + target_c = targets[:, c] + + # 样本对矩阵 + target_diff = target_c.unsqueeze(1) - target_c.unsqueeze(0) + prob_diff = prob_c.unsqueeze(1) - prob_c.unsqueeze(0) + + # mask: target_i > target_j + mask = target_diff > 0 + + if mask.sum() > 0: + # Hinge loss + base_loss = F.relu(self.margin - prob_diff)[mask] + + # 可选：使用 target_diff 作为权重 + # 这给予高 target 差异的样本对更高权重 + weights = target_diff[mask] + weighted_loss = base_loss * weights + + loss_c = weighted_loss.sum() / weights.sum() + + # 可选：类别权重（处理长尾分布） + if self.use_class_weighting: + # 稀有类别更高权重 + class_weight = self._get_class_weight(c, num_classes) + loss_c = loss_c * class_weight + + losses.append(loss_c) + + if len(losses) == 0: + return torch.tensor(0.0, device=predictions.device, requires_grad=True) + + return torch.stack(losses).mean() + + def _get_class_weight(self, class_idx: int, num_classes: int) -> float: + """ + 计算类别权重（处理长尾分布） + + 简单版本：可以基于样本频率 + """ + # 这里使用简单策略：可以替换为实际的类别频率 + #稀有类获得更高权重 + return 1.0 # 可以自定义 + + +# 4th Place 关键发现总结 +""" +关键发现（来自 4th Place writeup）： + +1. **Soft AUC Loss 显著提升性能**： + - LB 从 0.850 → 0.901 + - 排名从 11 名 → 4 名 + - +0.05 AUC 提升是巨大的 + +2. **为什么 Soft AUC Loss 有效**： + - 标准 AUC loss 只支持硬标签（0 或 1） + - Soft AUC Loss 支持软标签（0 到 1 之间） + - 适用于知识蒸馏和半监督学习 + - 减少 overfitting + +3. **实现细节**： + - 使用样本对的排序关系 + - Hinge loss: max(0, margin - (prob_i - prob_j)) + - 只考虑 target_i > target_j 的对 + - margin 通常设为 1.0 + +4. **适用场景**： + - 半监督学习（伪标签） + - 知识蒸馏（软标签） + - 长尾分布（稀有类别） + - 标签噪声（软标签更鲁棒） + +5. **与其他损失函数对比**： + - BCE Loss: 简单但易过拟合 + - Focal Loss: 处理类别不平衡，但不优化 AUC + - Soft AUC Loss: 直接优化 AUC，支持软标签 +""" + + +# 使用示例 +def train_with_soft_auc_loss(): + """使用 Soft AUC Loss 训练""" + + model = SEDModel(num_classes=206) + + # 标准训练：BCE Loss + criterion_bce = nn.BCEWithLogitsLoss() + + # 半监督训练：Soft AUC Loss + criterion_soft_auc = SoftAUCLoss_v4(margin=1.0) + + # 优化器 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3) + + # 训练循环 + for epoch in range(30): + model.train() + + for batch in train_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] # 可能是软标签 + + # 选择损失函数 + if batch.get('is_pseudo', False): # 伪标签数据 + # 使用 Soft AUC Loss + loss = criterion_soft_auc(model(mel_spec), labels) + else: # 真实标签 + # 可以使用 BCE Loss 或 Soft AUC Loss + loss = criterion_bce(model(mel_spec), labels) + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + print(f"Epoch {epoch+1}/30, Loss: {loss.item():.4f}") +``` + +--- + +## Best Practices + +### 时间序列分类竞赛策略 + +| 策略 | 何时使用 | 说明 | +|------|---------|------| +| **CWT over STFT** | 非平稳信号 | CWT提供更好的时间-频率局部化 | +| **Entmax over Softmax** | 标签稀疏时 | Entmax产生更稀疏的输出 | +| **非负线性回归集成** | 多模型集成时 | 即使过拟合也能保持相关性 | +| **2-Stage Training** | 标签质量不均时 | Stage1全数据，Stage2高质量样本 | +| **Group K-Fold** | 有重复样本时 | 确保同一patient/EEG不分散 | +| **仅用高质量样本** | 评估时 | 使用votes≥10的样本建立验证集 | + +### 时频分析方法对比 + +| 方法 | 优点 | 缺点 | 适用场景 | +|------|------|------|---------| +| **STFT** | 简单，易实现 | 固定窗口，时频分辨率权衡 | 平稳信号 | +| **CWT** | 多分辨率分析，捕捉局部特征 | 需要选择小波函数 | 非平稳信号，EEG | +| **Superlet** | 最高时频分辨率 | 计算成本高 | 复杂脑波模式 | + +### 频率配置经验 + +| 配置 | 范围 | 说明 | +|------|------|------| +| **标准CWT** | 0.5-20 Hz | Kaggle提供的spectrogram默认范围 | +| **扩展CWT** | 0.5-40 Hz | 更好的结果 (suguuuuu) | +| **带通滤波** | 0.5-40 Hz | 高频噪声增加'other'投票 | + +### 数据增强策略 + +**时间序列 (1D):** +- 随机时间偏移 (±5秒) +- 随机带通滤波 (不同频率范围) +- 通道翻转 (水平/垂直) +- 幅值缩放 + +**Scalogram/Spectrogram (2D):** +- XYMasking (随机遮挡) +- Mixup +- 时间方向翻转 + +### Backbone选择 + +**时间序列 (1D):** +- 1D CNN + GRU +- Transformer (Time-series Transformer) +- LSTM/GRU + +**Scalogram (2D):** +- SwinV2: swinv2_tiny_window16 (最佳: CV 0.2229) +- MaxVIT: maxvit_base_tf_512 +- ConvNeXt: convnextv2_atto + +### 标签处理技巧 + +| 技巧 | 效果 | +|------|------| +| 标签平滑 (加0.02 offset) | 使低投票数标签获得更强正则化 | +| 仅用votes≥10评估 | CV/LB相关性接近1:1 | +| 投票数归一化 | 多专家投票转换为分布 | + +### 常见误区 + +| 误区 | 正确做法 | +|------|---------| +| STFT不够好就放弃时频分析 | 尝试CWT或Superlet | +| Softmax输出不够稀疏 | 使用Entmax | +| 集成权重手动调参 | 使用非负线性回归 | +| 用全部样本验证 | 仅用高质量样本 (votes≥10) | +| 忽略Group K-Fold | 防止同一patient的数据泄露 | + +### EEG预处理最佳流程 + +1. **双极导联** - 减少共模噪声 +2. **带通滤波** (0.5-40 Hz) - 保留有效频段 +3. **归一化** - MAD或标准化 +4. **CWT变换** - 生成Scalograms +5. **数据增强** - 时间偏移、滤波等 + +### 时间序列特征提取 + +| 方法 | 适用场景 | +|------|---------| +| **原始1D CNN** | 保留时序信息 | +| **CWT + 2D CNN** | 需要频域信息 | +| **统计特征** | 传统机器学习 | +| **Wavelet Scattering** | 信号分解 | + +--- + +## Top 10 Solutions Comparison (前 10 名方案对比分析) + +> 基于前 10 名解决方案的横向对比分析，提取共性技术和差异创新 + +### 架构分类总结 + +根据整体解决方案，前 10 名可分为两大架构流派： + +| 架构类型 | 代表排名 | 核心特点 | +|---------|---------|---------| +| **独立编码器** | 2nd, 3rd, 8th | 分别处理 EEG 和 Spectrogram，后期融合 | +| **单一编码器** | 1st, 4th, 5th, 6th, 7th, 9th, 10th | 早期合并信号，统一编码 | + +### 前 3 名详细对比 + +#### 1st Place - Team Sony (yamash, suguuuuu, kfuji, Muku) + +**核心架构：** 多模型集成 (4人独立方案) + +| 成员 | 技术 | Score | +|------|------|-------| +| yamash | 纵向双极导联 + 2D CNN (不同时长) | - | +| suguuuuu | CWT + MaxVIT (Morlet 小波) | - | +| kfuji | CWT + MaxVIT (Paul 小波) | - | +| Muku | 1D CNN 特征 + Superlet CWT + SwinV2 | CV: 0.2229 | + +**关键技术：** +- CWT (0.5-40 Hz 扩展频段) +- Entmax 替换 Softmax +- 非负线性回归集成 +- 2-Stage Training (votes ≥10) + +#### 2nd Place - COOLZ + +**核心架构：** 3D-CNN + 2D-CNN 双路模型 + +``` +输入 (16 channels EEG) + ↓ +┌─────┴─────┐ +↓ ↓ +3D-CNN 2D-CNN +(x3d-l) (EfficientNetB5) + ↓ ↓ +Spectrogram Raw EEG + └─────┬─────┘ + ↓ + Double Head + (特征融合) + ↓ + Ensemble +``` + +**关键技术：** +- **3D-CNN (x3d-l)** 处理 Spectrogram - CV: 0.21, PB: 0.25 +- **2D-CNN (EfficientNetB5)** 处理 Raw EEG - PB: 0.28 +- **双特征头**：EEG + Spectrum 特征融合 +- **不同滤波器**：MNE vs scipy.signal 增加多样性 +- **2-Stage Training**： + - Stage 1: 全数据 + loss weight = voters_num/20 + - Stage 2: votes ≥6 数据 +- **随机偏移采样**：根据 eeg_id 随机选择偏移 + +**归一化：** `x.clip(-1024, 1024) / 32` + +**最终集成权重：** [0.1, 0.1, 0.2, 0.2, 0.2, 0.2] (6 模型) + +#### 3rd Place - nvidia-dd (DIETER) + +**核心架构：** MelSpectrogram + Squeezeformer + +``` +EEG → MelSpectrogram → 2D CNN + ↓ +EEG → 1D-Convolutions → Squeezeformer + ↓ + Ensemble +``` + +**关键技术：** +- **数据质量筛选**：仅使用 6350 行高质量数据（从 100000+ 行中筛选） +- **反向 Augmentation**：发现并移除数据创建者应用的 augmentation +- **MelSpectrogram** 替代标准 Spectrogram +- **Squeezeformer** 用于时序建模 +- **信号配对**：左右脑节点一起处理 +- **归一化**：`x.clip(-1024, 1024) / 32` + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **带通滤波 (0.5-20/40 Hz)** | 1st, 2nd, 3rd | 几乎所有高分者使用 | +| **Clip 归一化** | 1st, 2nd, 3rd | `x.clip(-1024, 1024) / 32` | +| **2-Stage Training** | 1st, 2nd, 3rd | Stage 1 全数据，Stage 2 高质量样本 | +| **Votes ≥10 筛选** | 1st, 2nd, 3rd | 仅用高质量样本评估 | +| **Group K-Fold** | 1st, 2nd, 3rd | 按患者分组，防止数据泄露 | +| **Ensemble/Stacking** | 1st, 2nd, 3rd | 多模型集成 | +| **数据增强** | 1st, 2nd, 3rd | 时间偏移、通道翻转、Mixup | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st - Sony** | Entmax 替换 Softmax | LB +0.004 提升 | +| **1st - Sony** | Superlet CWT | 最高时频分辨率 | +| **2nd - COOLZ** | 3D-CNN 处理 Spectrogram | 保留通道位置信息 | +| **2nd - COOLZ** | 双特征头 (EEG + Spectrum) | 多模态融合 | +| **3rd - nvidia-dd** | 数据质量筛选 (6350→100000) | 性能提升显著 | +| **3rd - nvidia-dd** | 反向 Augmentation | 数据纯净度提升 | +| **4th - Cerberus** | 左右对称对比学习 | 位置编码 | +| **9th - ishikei** | Contrastive Learning | 特征对比 | + +### 归一化方法对比 + +| 方法 | 支持者 | 效果 | +|------|--------|------| +| **`x.clip(-1024, 1024) / 32`** | 1st, 2nd, 3rd | 最佳选择 | +| **MAD 归一化** | 3rd | 对异常值更鲁棒 | +| **Batch/Sample 归一化** | 部分尝试者 | 效果不佳 (3rd 发现) | +| **Standardize** | 低排名者 | 不推荐 | + +### 时频变换方法对比 + +| 方法 | 使用排名 | 优点 | 缺点 | +|------|---------|------|------| +| **CWT** | 1st, 4th, 5th, 6th | 多分辨率，适合非平稳信号 | 需选择小波 | +| **Superlet CWT** | 1st | 最高分辨率 | 计算成本高 | +| **MelSpectrogram** | 2nd, 3rd | 人耳感知特性 | 频率分辨率固定 | +| **STFT** | 7th, 8th, 10th | 简单易实现 | 时频权衡 | + +### 集成策略对比 + +| 排名 | 集成方法 | 模型数 | 权重确定 | +|------|---------|--------|---------| +| **1st** | 非负线性回归 | 6 (4人) | 自动学习 | +| **2nd** | 加权平均 | 6 | 手动调参 | +| **3rd** | 简单平均 | 多个 | 均等权重 | + +### 验证策略对比 + +| 策略 | 使用排名 | Votes 阈值 | 说明 | +|------|---------|------------|------| +| **≥10** | 1st, 2nd, 3rd | ≥10 | 专家 vs 大众一致意见 | +| **≥6** | 2nd | ≥6 | 较宽松 | +| **≥9** | 部分 | ≥9 | 接近专家标准 | +| **加权** | 部分 | 按投票数加权 | 少投票获得更高正则化 | + +### 频率范围选择 + +| 范围 | 使用排名 | 应用场景 | +|------|---------|---------| +| **0.5-20 Hz** | 标准, 2nd | Kaggle 默认 | +| **0.5-40 Hz** | 1st (suguuuuu) | 扩展信息，更佳结果 | +| **0.5-50 Hz** | 部分 | 包含更多高频信息 | + +### 训练 Epoch 配置 + +| 排名 | Stage 1 | Stage 2 | 说明 | +|------|---------|---------|------| +| **1st** | 5 epochs | 15 epochs | 保守选择 | +| **2nd** | 15 epochs | 5 epochs | 更长 Stage 1 | +| **3rd** | - | - | 单阶段或灵活配置 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **带通滤波 (0.5-20/40 Hz)** +2. **Clip 归一化**：`x.clip(-1024, 1024) / 32` +3. **2-Stage Training**：Stage 1 全数据，Stage 2 高质量样本 +4. **Votes ≥10 筛选**：仅用高质量样本评估 +5. **Group K-Fold**：按患者分组 +6. **Ensemble**：至少 3+ 模型集成 + +#### 推荐选项（根据情况选择） +- **时频分析**：CWT (最佳) > MelSpectrogram > STFT +- **归一化**：clip/32 (最佳) > MAD > batch/sample normalize +- **集成方法**：非负线性回归 (最佳) > 加权平均 > 简单平均 +- **模型架构**：根据数据特征选择 1D/2D/3D CNN + +#### 创新方向 +- **数据质量**：反向 Augmentation，质量筛选 +- **稀疏激活**：Entmax 替换 Softmax +- **位置编码**：3D-CNN 保留通道信息，左右对称对比 +- **特征融合**：双特征头，多模态集成 + +--- + +## Child Mind Institute - Top 10 Solutions Comparison + +> 基于前 10 名解决方案的横向对比分析，提取共性技术和差异创新 + +### 竞赛特点总结 + +与 HMS 不同，这是一个**事件检测任务**，核心挑战包括： +- **稀疏标注**：17280 步中仅 2 步有标签（0.01%） +- **分钟偏差**：真实事件总是发生在 hh:mm:00 +- **未标注事件**：存在周期性重复数据（缺失标签） +- **多 Tolerance AP**：需要同时优化多个容差窗口 + +### 前 3 名详细对比 + +#### 1st Place - shimacos vs sakami vs kami (kami, sakami0000, shimacos) + +**核心架构：** 两阶段建模 + Greedy 后处理优化 + +``` +1st Level (5秒间隔) + CNN+GRU+CNN, CNN+GRU+Transformer+CNN, + LSTM+UNet1d+UNet, LSTM+UNet1d+UNet, 1dCNN+UNet1d+Transformer + ↓ +2nd Level (1分钟间隔) + LightGBM, CatBoost, CNN+GRU, CNN+Transformer, CNN + ↓ +Post Processing (15/45秒技巧) + Daily Normalize → Greedy Search → Final Events +``` + +**关键技术：** +- **两阶段建模**：5秒检测 + 1分钟精化 +- **衰减目标**：按 tolerance_steps 加权 + epoch 衰减 +- **15/45秒技巧**：针对 tolerance 边缘优化 +- **Daily Normalization**：按天归一化 2nd level 预测 +- **Greedy 后处理**：针对 AP 指标的 greedy search + +**效果：** Public LB: 0.768 (18th) → Private LB: 0.852 (1st) + +#### 2nd Place - K-Mat + +**核心架构：** 三阶段建模 + Error Modeling + +``` +Stage 1: 事件检测 + 睡眠/清醒分类 + 多个模型预测 onset/wakeup/asleep 概率 + ↓ +Stage 2: Error Modeling (LGBM) + 基于 1st level 预测，计算 Error → Correctness → Target + 将分数差分转为分类任务 + ↓ +Stage 3: 时刻偏移 + WBF 融合 + 对 step 做时刻偏移，重新预测 + 用 WBF 整合结果 +``` + +**关键技术：** +- **Error Modeling**：将差分变化转为分类标签 +- **三阶段架构**：检测 → 重打分 → 偏移 +- **Minute Embedding**：将 minute_embedding 残差连接到输出层 +- **时刻偏移**：应对 15 分钟周期模式 +- **WBF 融合**：Weighted Box Fusion + +#### 3rd Place - cucutzik + +**核心架构：** 简洁干净的 GRU + UNET + LGB 集成 + +**关键技术：** +- **频率编码**：hour_min_onset, hour_min_wakeup +- **序列反转增强**：反转所有序列，CV +0.01 +- **目标扩展**：event step 前加2步，后加1步 +- **模型融合**：GRU (0.68) + UNET (0.2) + LGB (0.12) +- **Rolling Mean 平滑**：center=True，每隔距离取最高预测 +- **噪声检测**：相同 hour+step+anglez 重复值即为噪声 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **两阶段建模** | 1st, 2nd | 5秒检测 → 1分钟精化 | +| **分钟偏差处理** | 1st, 2nd, 3rd, 5th, 6th | 事件总是发生在整分钟 | +| **多模型集成** | 1st, 2nd, 3rd | 至少 5+ 模型 | +| **Daily Normalization** | 1st, 3rd | 按天归一化预测值 | +| **后处理优化** | 1st, 2nd, 3rd | find_peaks, NMS, greedy search | +| **多任务学习** | 2nd, 4th | onset, wakeup, asleep | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st** | 15/45秒技巧 | Public 18th → Private 1st | +| **1st** | 衰减目标 + epoch 衰减 | 使峰值更尖锐 | +| **1st** | Daily Normalization | 利用每天只有2次活动的先验 | +| **2nd** | Error Modeling | 将差分转为分类标签 | +| **2nd** | Minute Embedding | 残差连接到输出层 | +| **3rd** | 序列反转增强 | CV +0.01 | +| **3rd** | 频率编码特征 | hour_min_onset/wakeup | +| **4th** | Patch-based 模型 | 不同的 patch_size (3/4/5/6) | +| **5th** | Window Operations | left/right window 交互特征 | +| **6th** | Hash-based 周期检测 | 本地 CV +0.015 | + +### 分钟偏差处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **Minute Embedding** | 1st | 残差连接到输出层 | +| **频率编码** | 3rd | hour_min_onset, hour_min_wakeup | +| **Step 偏移** | 2nd | 偏移 step 重新预测 + WBF | +| **标签偏移** | 5th | target shift ~-11 步 | +| **特征工程** | 6th | `(step // 12) % 15` | + +### 未标注事件处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **周期性检测** | 1st | 降采样 + 相似度计算，标记日周期性 | +| **噪声检测** | 3rd | 相同 hour+step+anglez 重复值 | +| **样本加权** | 5th | 训练时权重设为 0 | +| **Hash 算法** | 6th | 散列和散列图查找重复模式 | +| **过滤序列** | 大部分 | 剔除未标注 events 出现多的序列 | + +### 后处理策略对比 + +| 排名 | 方法 | 参数 | 效果 | +|------|------|------|------| +| **1st** | Greedy + 15/45秒 | 500次迭代 | Public 18th → Private 1st | +| **2nd** | Step偏移 + WBF | 多个偏移量 | 显著提升 | +| **3rd** | Rolling Mean + find_peaks | window=12, distance=72 | 清晰方案 | +| **基线** | find_peaks + NMS | distance=72, IOU=0.995 | 银牌基础 | + +### 1st Level 模型对比 + +| 排名 | 模型数量 | 模型类型 | 集成方式 | +|------|---------|---------|---------| +| **1st** | 5 | CNN+GRU, CNN+Transformer, LSTM+UNet 等 | 加权平均 | +| **2nd** | 多个 | Spec2DCNN, PANNs, Transformer 等 | 融合后处理 | +| **3rd** | 10 | 8个GRU + 2个UNET | GRU 0.68 + UNET 0.2 + LGB 0.12 | + +### 2nd Level 模型对比 + +| 排名 | 模型类型 | 输入特征 | 说明 | +|------|---------|---------|------| +| **1st** | LGB, CatBoost, CNN+GRU 等 | 1st level 预测 + 原始特征 | 整合到整分钟 | +| **2nd** | LGBM | Error, Correctness, Top-k Accuracy | 重新打分 | +| **3rd** | LGB | 1st level 预测 | 加权融合 | + +### 数据增强策略对比 + +| 方法 | 使用排名 | 效果 | +|------|---------|------| +| **序列反转** | 3rd | CV +0.01 | +| **时间偏移** | 基线 | 标准增强 | +| **标签扩展** | 3rd | 前2步+后1步 | +| **周期性特征** | 1st | 日周期 flag | + +### 验证策略对比 + +| 策略 | 使用排名 | 说明 | +|------|---------|------| +| **Group K-Fold** | 1st, 2nd, 3rd | 按 series_id 分组 | +| **Stratified (事件数)** | 1st | 事件数 qcut(10) 分层 | +| **全部 fold 训练** | 1st | 单 fold 结果不稳定，需全 fold | +| **Trust CV** | 1st | Public 数据少且分布相似 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **两阶段建模**：5秒检测 → 1分钟精化 +2. **分钟偏差处理**：使用 minute 相关特征 +3. **Daily Normalization**：按天归一化预测值 +4. **多模型集成**：至少 5+ 模型 +5. **后处理优化**：find_peaks, NMS, greedy search +6. **Group K-Fold**：按 series_id 分组 + +#### 推荐选项（根据情况选择） +- **后处理方法**：Greedy (最佳) > WBF > NMS > find_peaks +- **2nd level 模型**：LGB/CatBoost > Neural Networks +- **分钟偏差处理**：Minute Embedding (最佳) > 频率编码 > step 偏移 +- **数据增强**：序列反转 > 时间偏移 + +#### 创新方向 +- **评估指标优化**：针对 tolerance 的 greedy search +- **Error Modeling**：将差分转为分类标签 +- **衰减目标**：按 tolerance 加权 + epoch 衰减 +- **周期性检测**：识别未标注 events + +--- + +## CMI - Detect Behavior with Sensor Data - Top 10 Solutions Comparison + +> 基于日语总结和前排方案的综合分析，提取共性技术和差异创新 + +### 竞赛特点总结 + +与之前竞赛不同，这是一个**多模态时序行为识别**任务，核心挑战包括： +- **多模态传感器融合**：IMU + THM + TOF +- **严重数据缺失**：TOF 约 60% 缺失（-1），THM 约 3-4% 缺失 +- **细粒度分类**：18 个手势类别，区分 BFRB vs 日常动作 +- **个体约束**：每个 subject × gesture × orientation 只出现一次 +- **测试集变化**：约 50% 序列仅有 IMU 数据 + +### 前 3 名详细对比 + +#### 1st Place - Devin | Ogurtsov | zyz (Andrey Ogurtsov, Devin, zyz) + +**核心架构：** 多成员协作 + 多模型集成 + +``` +Devin's part: + TOF 处理: 2×2 正方形 9 个区域平均 + TOF-only 模型也加入集成 + +Ogurtsov's part: + 数据清理: 删除 gesture 不存在的序列 + 特征工程: 从 acc（去除重力后）提取 35 个特征 + 模型: LSTM, Attention, CNN 组合 + 增强: timeshift, timistretch + 集成: 每 Fold 选择 3 run 中最佳结果 + 推理: 序列延伸降低模型相关性 + +zyz part: + RNN + CNN1D 组合 +``` + +**关键技术：** +- **TOF 图像化**：2×2 正方形 9 个区域平均降维 +- **TOF-only 集成**：单独使用 TOF 数据的模型也加入集成 +- **数据清理**：删除无效序列（如 SUBJ_019262, SUBJ_045235） +- **特征工程**：35 个特征从 acc（去除重力后）提取 +- **多模型集成**：LSTM + Attention + CNN 组合 +- **推理优化**：序列延伸降低模型相关性，提升集成效果 + +#### 2nd Place - cucutzik + +**核心架构：** 4 模型系统 + 阶段感知 Attention + +``` +4 个独立模型: + IMU rotation 缺失/存在 × THM/TOF 缺失/存在 = 4 组合 + +核心创新: + 四元数 6D 表现 (避免不连续性) + Residual SE-CNN Block + Attention + +关键技巧: + 阶段感知 Attention: + 预测 3 类阶段概率 (移动中/目标位置/手势执行中) + 每个阶段独立 Attention，概率加权 + 相位 Mixup: + 按阶段分割序列 + 同阶段内进行 Mixup + "moves to target" 阶段对齐结束点 + Pseudo Label: + 测试数据生成 pseudo-label + 小 LR (5e-5) 1 step fine-tune + +后处理: + 匈牙利算法全局最优标签分配 + 约束: subject × gesture × orientation 唯一性 +``` + +**关键技术：** +- **四元数 6D 表现**：避免四元数不连续性问题 +- **阶段感知 Attention**：分阶段独立建模和加权 +- **相位 Mixup**：按阶段分割后同阶段内 Mixup +- **Pseudo Label**：测试数据生成伪标签进行微调 +- **匈牙利算法**：全局最优标签分配（利用个体约束） + +#### 3rd Place - Team RIST + +**核心架构：** 2D-CNN + 图像化时序 + +``` +数据预处理: + 四元数平滑处理 + 符号反转扩展 + Block 扩展 + +模型: + MaxViT, ConvNeXt-V2, EfficientNetB5 等 2D-CNN + 输入: 适当尺寸的图像 + +增强: + 世界坐标系 Z 轴旋转 (-60° 到 60°) + 本地坐标系 Y 轴旋转 (-7° 到 7°) + +后处理: + 匈牙利算法全局最优标签分配 +``` + +**关键技术：** +- **时序图像化**：时序数据转换为图像，使用 2D-CNN +- **四元数处理**：平滑、符号反转、Block 扩展 +- **双重旋转增强**：世界坐标 + 本地坐标旋转 +- **多 2D-CNN 集成**：MaxViT + ConvNeXt + EfficientNetB5 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **个体约束利用** | 1st, 2nd, 3rd, 4th | subject × gesture × orientation 唯一性 | +| **数据增强** | 1st, 2nd, 3rd, 4th, 6th... | mixup, cutmix, timeshift, rotation | +| **异常数据处理** | 几乎所有 | SUBJ_019262, SUBJ_045235 删除或转换 | +| **左手系 → 右手系对齐** | 大部分 | 将左手系传感器数据转换为右手系 | +| **多模型集成** | 1st, 2nd, 3rd | 至少 3+ 模型 | +| **阶段感知建模** | 2nd, 3rd, 6th | 利用 Transition/Pause/Gesture 结构 | +| **BatchNorm（无归一化）** | 9th | 不使用 scaler，用 BatchNorm | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st** | TOF 图像化（2×2 区域平均） | 简化 TOF 处理 | +| **1st** | TOF-only 模型集成 | 单独 TOF 也有价值 | +| **1st** | 序列延伸推理 | 降低模型相关性 | +| **2nd** | 四元数 6D 表现 | 避免不连续性 | +| **2nd** | 阶段感知 Attention | 分阶段独立建模 | +| **2nd** | 相位 Mixup | 同阶段内 Mixup，对齐结束点 | +| **2nd** | Pseudo Label fine-tune | 测试数据微调 | +| **3rd** | 时序转图像 | 使用 2D-CNN 处理 | +| **3rd** | 双重旋转增强 | 世界坐标 + 本地坐标 | +| **6th** | gesture segment U-Net | 估计手势时间段 | +| **9th** | 正向 + 反向模型 | 同时训练标准分类和反向分类 | +| **13th** | 双向 Mamba | 长期时序依赖建模 | +| **13th** | Hard Margin Loss | 针对困难样本的损失 | +| **13th** | Hard Mining | 困难样本采样率提升 | + +### 多模态传感器处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **TOF 图像化** | 1st | 2×2 正方形 9 个区域平均 | +| **TOF 2D-CNN** | 7th | 时序数据转图像，用 2D-CNN | +| **TOF U-Net** | 6th | gesture segment 估计 | +| **THM/TOF 独立模型** | 2nd | 4 个模型（缺失/存在组合） | +| **多模态融合** | 1st, 2nd, 3rd | IMU + THM + TOF 特征融合 | + +### 四元数处理对比 + +| 方法 | 使用排名 | 说明 | +|------|---------|------| +| **6D 表现** | 2nd | 避免四元数不连续性 | +| **平滑处理** | 3rd | 处理四元数不连续性 | +| **符号反转扩展** | 3rd | 扩展四元数表示 | +| **Block 扩展** | 3rd | 添加额外 Block | + +### 后处理策略对比 + +| 排名 | 方法 | 具体实现 | +|------|------|---------| +| **1st** | 简单集成 + 推理优化 | 序列延伸 | +| **2nd** | 匈牙利算法 | 全局最优标签分配，利用个体约束 | +| **3rd** | 匈牙利算法 | 全局最优标签分配 | +| **4th-15th** | 多种方法 | argmax, 约束优化等 | + +### 数据增强策略对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **Mixup** | 1st, 2nd, 4th, 10th | 标准或相位 Mixup | +| **CutMix** | 1st | 标准 CutMix | +| **Time Shift** | 1st | 时间偏移 | +| **Time Stretch** | 1st | 时间拉伸 | +| **Rotation** | 2nd, 3rd | 世界坐标 + 本地坐标旋转 | +| **Time Warping** | 7th | 时间非线性伸缩 | +| **Magnitude Warping** | 7th | 幅度时间变化 | +| **双重 Mixup** | 10th | `Mixup(Mixup(Mixup(x)))` | + +### 缺失数据处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **独立模型** | 2nd | 4 个模型（缺失/存在组合） | +| **TOF-only** | 1st | 单独 TOF 模型也集成 | +| **gesture segment** | 6th | U-Net 估计手势时间段 | +| **删除异常序列** | 1st | 删除无效序列 | +| **数据转换** | 几乎所有 | 左手系 → 右手系对齐 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **个体约束利用**：subject × gesture × orientation 唯一性 +2. **数据增强**：mixup, cutmix, timeshift, rotation +3. **异常数据处理**：SUBJ_019262, SUBJ_045235 删除或转换 +4. **左手系 → 右手系对齐**：统一左右手传感器数据 +5. **多模型集成**：至少 3+ 模型 +6. **阶段感知建模**：利用 Transition/Pause/Gesture 结构 + +#### 推荐选项（根据情况选择） +- **TOF 处理**：图像化 (1st) > 2D-CNN (7th) > U-Net (6th) +- **四元数处理**：6D 表现 (2nd) > 平滑 + 扩展 (3rd) +- **后处理**：匈牙利算法 (2nd, 3rd) > 简单集成 (1st) +- **模型架构**：根据数据特征选择 1D-CNN / 2D-CNN / Mamba + +#### 创新方向 +- **阶段感知建模**：分阶段独立 Attention 和特征提取 +- **相位 Mixup**：按阶段分割后同阶段内 Mixup +- **Pseudo Label**：测试数据生成伪标签微调 +- **时序图像化**：将时序数据转为图像，用 2D-CNN +- **双向 Mamba**：长期时序依赖建模 + +--- + +## 数据洞察与分析 + +### 数据特征理解 + +#### 标签质量的双峰分布 + +**发现：** 投票数呈现双峰分布 +- **低质量样本**：1-7 票 +- **高质量样本**：10-28 票 +- **关键发现**：**没有 8-9 票的样本** + +**含义：** +- 存在两组标注者：专家组（20人）和大众组（119人） +- 低投票数样本更不可靠，标签噪声更大 +- 高投票数样本代表专家共识，质量更高 + +**策略：** +- 使用 votes ≥10 作为高质量阈值 +- 仅用高质量样本建立验证集（CV/LB 相关性接近 1:1） +- 考虑对低投票样本进行更强正则化 + +**第 3 名的洞察：** 从 100,000+ 行筛选到 6,350 行高质量数据，性能反而提升 → **"少即是多"**，精确数据胜过大量噪声数据 + +#### 标签稀疏性 + +**发现：** 训练标签中某些类别的概率为 0 +- Softmax 输出所有值 > 0（数学性质） +- 但真实标签中某些类为 0 + +**解决方案（1st Place）：** +- 使用 **Entmax** 替换 Softmax +- Entmax 可以产生真正的 0 输出（稀疏激活） +- 结果：LB +0.004 提升 + +**实现：** +```python +def entmax(x, alpha=1.5, dim=-1): + return torch.softmax(x * alpha, dim=dim) +``` + +#### 双模态数据的时间对齐 + +**数据结构：** +- **Spectrogram**：10 分钟（低时间分辨率，高频率信息） +- **EEG**：50 秒中心段（高时间分辨率，低频率信息） +- 两者中心 50 秒是同一数据 + +**洞察：** +- Spectrogram 提供全局上下文（10分钟趋势） +- EEG 提供精细时序信息（50 秒细节） +- 这是**同一数据的两种表示**，不是独立信息 + +**处理策略：** +- 大多数获胜者**专注于 EEG**（2nd, 3rd） +- 1st Place 同时使用两种并集成 +- 时频分析（CWT/MelSpectrogram）比纯时序或纯频域更有效 + +#### 信号配对的重要性 + +**发现：** +- 脑电信号存在空间关系 +- 左右对称位置的电极信号应该成对处理 +- 通道顺序影响模型性能 + +**策略（3rd Place）：** +- 将左右脑节点配对：Fp1-F7, Fp2-F8, F7-T3, F8-T4 等 +- 而不是简单按顺序堆叠 +- 这样保留了脑部空间结构的先验知识 + +#### 频率范围选择的影响 + +**对比分析：** +| 频率范围 | 使用者 | 效果 | +|---------|--------|------| +| 0.5-20 Hz | 标准, 2nd | Kaggle 默认 | +| 0.5-40 Hz | 1st (suguuuuu) | 更佳结果 | +| 0.5-50 Hz | 部分 | 高频噪声可能增加 | + +**洞察：** +- 标准范围可能遗漏重要信息 +- 扩展到 40 Hz 能捕捉更多特征 +- 但过高频率（50 Hz+）可能引入噪声 +- 需要根据具体任务调整 + +#### 归一化的选择 + +**实验发现（3rd Place）：** +- Batch/Sample 归一化：效果不佳 +- MAD 归一化：对异常值更鲁棒 +- **Clip 归一化** `x.clip(-1024, 1024) / 32`：**最佳选择**（所有前 3 名都使用） + +**为什么 Clip/32 最好？** +1. **限制极端值**：EEG 信号存在大幅伪影 +2. **固定除数 32**：简单、可复现、不过拟合 +3. **保留信息**：相比标准化，保留更多原始信号特征 + +#### 数据增强的反向工程 + +**3rd Place 的关键发现：** +- 数据创建者对训练数据应用了 augmentation +- 这些 augmentation 在测试时不存在 +- **反向工程并移除这些 augmentation** 后，模型性能显著提升 + +**启示：** +- 理解数据来源和预处理历史很重要 +- "干净"的原始数据可能比"增强"的数据更好 +- 深入数据分析能发现隐藏的改进机会 + +### 数据质量评估框架 + +基于前 10 名的分析，可以建立以下数据质量评估维度： + +| 维度 | 评估方法 | 高质量指标 | +|------|---------|-----------| +| **投票数** | 统计每个样本的专家投票数 | votes ≥10 | +| **一致性** | 计算投票分布的熵 | 高一致性（低熵） | +| **标注者类型** | 区分专家 vs 大众 | 专家共识权重更高 | +| **信号质量** | 检查伪影、噪声水平 | 低噪声、少伪影 | +| **时序完整性** | 检查 50 秒段连续性 | 无断裂、无缺失 | + +### 数据预处理最佳流程 + +综合前 10 名方案，推荐的数据预处理流程： + +```python +def preprocess_eeg_optimal(eeg_raw, votes): + """ + 基于 Top 10 方案的最佳预处理流程 + """ + # 1. 双极导联（减少共模噪声） + bipolar = longitudinal_bipolar_montage(eeg_raw) + + # 2. 带通滤波（0.5-40 Hz，扩展频段） + filtered = bandpass_filter(bipolar, lowcut=0.5, highcut=40, fs=200) + + # 3. Clip 归一化（所有前 3 名使用） + normalized = np.clip(filtered, -1024, 1024) / 32.0 + + # 4. 数据质量筛选 + if votes < 10: + # 考虑降权重或使用 Pseudo Label + weight = votes / 20.0 # 2nd Place 方法 + else: + weight = 1.0 + + return normalized, weight +``` + +### 标签处理最佳实践 + +| 技术 | 目的 | 使用排名 | +|------|------|---------| +| **投票数归一化** | 转换为概率分布 | 所有 | +| **标签平滑（加 0.02）** | 防止过度自信 | 部分 | +| **Loss 权重** | 按投票数加权样本 | 2nd | +| **Offset 加法** | 低投票数更强正则化 | 部分 | + +### 关键数据洞察总结 + +1. **质量 > 数量**：6,350 行高质量数据 > 100,000 行噪声数据 +2. **稀疏标签需要稀疏激活**：Entmax > Softmax +3. **时频分析优于纯时序或纯频域**：CWT > STFT +4. **空间先验知识很重要**：信号配对、左右对称 +5. **归一化方法影响巨大**：Clip/32 是最佳选择 +6. **理解数据来源至关重要**：反向 Augmentation 提升性能 +7. **标签质量分布不均**：需要分层训练和评估 + +--- + +## Child Mind Institute - 数据洞察与分析 + +### 数据特征理解 + +#### 极度稀疏的标签 + +**发现：** 17280 步（24小时）中仅有 2 步有标签 +- **标签密度**：0.01%（1/10000） +- **事件类型**：onset（入睡）+ wakeup（觉醒） +- **标注粒度**：每夜 1 个 onset + 1 个 wakeup + +**含义：** +- 传统逐帧分类方法不适用 +- 需要特殊的目标创建策略（衰减目标） +- 后处理比模型预测更重要 +- 数据增强对缓解稀疏性至关重要 + +**策略：** +- **衰减目标**：按 tolerance_steps 创建衰减的标签分布 +- **多任务学习**：同时预测 onset, wakeup, asleep +- **后处理优化**：find_peaks, NMS, greedy search +- **数据增强**：序列反转、时间偏移等 + +#### 分钟偏差模式 + +**发现：** 真实事件总是发生在 hh:mm:00 整分钟时刻 + +**数据分布（YOURI MATIOUNINE 发现）：** +``` +标签分钟数 % 15 的分布： +- 0分钟：明显峰值 +- 3分钟：明显峰值 +- 7分钟：明显峰值 +- 11分钟：明显峰值 +- 其他分钟：很少出现 +``` + +**含义：** +- 手动标注导致精度有限 +- 存在 15 分钟的周期性模式 +- 模型应该学习这种模式 + +**策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | Minute Embedding | 残差连接到输出层 | +| **2nd** | Step 偏移 | 对预测 step 做偏移后重新预测 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | +| **5th** | 标签偏移 | target shift ~-11 步 | +| **6th** | 特征工程 | `(step // 12) % 15` | + +#### 未标注事件问题 + +**发现（YOURI MATIOUNINE）：** 很多序列有明显的 events 未被标注 + +**两类情况：** +1. **日周期性重复**：缺失 events 的夜晚跟前 24 小时数据完全一样 + - 推测：组织方用历史正常数据填补了缺失数据 +2. **无法解释的缺失**：没有明显规律的缺失标注 + +**处理策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | 周期性检测 + flag | 降采样 + 相似度计算，标记日周期性 | +| **3rd** | 噪声检测 | 相同 hour+step+anglez 重复值即为噪声 | +| **5th** | 样本加权 | 训练时权重设为 0 | +| **6th** | Hash 算法 | 散列和散列图查找重复模式，本地 CV +0.015 | +| **大部分** | 过滤序列 | 剔除未标注 events 出现多的序列 | + +**1st Place 的周期性检测方法：** +```python +def detect_periodicity(series): + """检测 24 小时周期性重复""" + # 1. 降采样 + downsampled = series[::12] # 5秒 → 1分钟 + + # 2. 分割序列（按天） + n_days = len(downsampled) // 1440 # 1440 = 24小时 + daily_chunks = [downsampled[i*1440:(i+1)*1440] for i in range(n_days)] + + # 3. 计算相邻天的相似度 + for i in range(n_days - 1): + # 方法1: 元素级比较 + similarity = np.mean(daily_chunks[i] == daily_chunks[i+1]) + + # 方法2: 余弦相似度 + cos_sim = np.dot(daily_chunks[i], daily_chunks[i+1]) / ( + np.linalg.norm(daily_chunks[i]) * np.linalg.norm(daily_chunks[i+1]) + ) + + if similarity > threshold or cos_sim > threshold: + return True # 检测到周期性 + + return False +``` + +#### 多 Tolerance AP 评估指标 + +**评估方式：** +```python +tolerances = [1, 3, 5, 7.5, 10, 12.5, 15, 20, 25, 30] # 分钟 +# 对每个 tolerance，计算 AP +# 最终分数 = mean(各tolerance AP) × mean(onset AP, wakeup AP) +``` + +**关键洞察（1st Place）：** +- **预测 hh:mm:00 不好**：tolerance 5,10,15,20,25,30 时边缘漏检 +- **预测 hh:mm:30 不好**：tolerance 7.5, 12.5 时边缘漏检 +- **预测 hh:mm:15 或 hh:mm:45 最佳**：覆盖所有 tolerance + +**原理示意：** +``` +00:23:15 ← 检测事件（15秒） + ← tolerance 7.5 分 → +00:23:00 ← 真实事件（0秒） + ← tolerance 7.5 分 → +00:22:45 + +如果检测事件在 00:23:00，则 tolerance 7.5 的右边缘会漏检 +如果检测事件在 00:23:15 或 00:22:45，则正好覆盖 +``` + +#### 15分钟周期性模式 + +**发现：** events 以 15 分钟为周期重复出现 + +**数据分布：** +- **峰值分钟**：0, 3, 7, 11（间隔 3-4 分钟） +- **周期**：15 分钟 +- **含义**：可能与定时检查或记录习惯有关 + +**应对策略：** +| 排名 | 策略 | 说明 | +|------|------|------| +| **1st** | 15/45秒技巧 | 无论 1-29秒 还是31-59秒，选15/45秒代表 | +| **2nd** | Step偏移 | 对step做多个偏移，覆盖所有可能时刻 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **周期性重复** | 降采样+相似度 | 与前24小时完全相同 | 标记 periodicity flag | +| **噪声重复** | hour+step+anglez计数 | 重复值>1 | 标记 noise | +| **未标注events** | 统计每夜events数 | <2 events | 过滤或降权 | +| **数据异常** | enmo统计 | enmo值异常大 | clip到1 | + +### 关键数据洞察总结 + +1. **极度稀疏标签**：需要衰减目标和后处理优化 +2. **分钟偏差是关键**：所有前排方案都处理了这个问题 +3. **未标注events普遍存在**：周期性检测可识别 +4. **多tolerance AP需要特殊优化**：15/45秒技巧是制胜关键 +5. **评估指标与数据分布不匹配**：需要针对tolerance优化 +6. **Daily Normalization有效**：利用每天只有2次活动的先验 +7. **15分钟周期性模式**：step偏移或频率编码可利用 + +### 事件检测任务的最佳实践 + +与分类任务不同，事件检测任务的特殊考虑： + +| 方面 | 分类任务 | 事件检测任务 | +|------|---------|-------------| +| **目标创建** | 单标签 | 衰减目标（按tolerance加权） | +| **评估指标** | Accuracy/F1 | 多tolerance AP | +| **后处理** | Threshold | find_peaks, NMS, Greedy | +| **模型集成** | 概率平均 | 两阶段建模 | +| **验证策略** | K-Fold | Group K-Fold + 全fold训练 | + +--- + +## CMI - Detect Behavior 数据洞察与分析 + +### 数据特征理解 + +#### 多模态传感器数据 + +**三种传感器类型：** + +| 传感器 | 数据维度 | 特征 | 缺失率 | +|-------|---------|------|--------| +| **IMU** | 加速度计(x,y,z) + 陀螺仪(x,y,z) | 运动和旋转 | 无缺失 | +| **THM** | 5个温度传感器 | 温度分布 | ~3-4% | +| **TOF** | 5个8×8传感器阵列 | 距离映射 | ~60% | + +**IMU (Inertial Measurement Unit)：** +- 6 列：`X_accel`, `Y_accel`, `Z_accel`, `X_gyro`, `Y_gyro`, `Z_gyro` +- **重力分量**：加速度计包含重力，需去除 +- **四元数**：`orientation_X`, `orientation_Y`, `orientation_Z`, `orientation_W` + - 表示设备旋转姿态 + - **不连续性问题**：四元数在表示相同旋转时有多个值（q和-q表示相同旋转） + - **解决方案**：使用旋转矩阵前两列（6D连续表示） + +**THM (Thermopile)：** +- 5 列：`thermopile_0` ~ `thermopile_4` +- 温度传感器，用于检测物体接近 +- **缺失标记**：-1 表示缺失 +- **缺失率较低**：约3-4% + +**TOF (Time-of-Flight)：** +- 320 列：`tof_0` ~ `tof_319`（5个8×8阵列） +- 距离传感器，检测物体到设备距离 +- **缺失标记**：-1 表示缺失 +- **缺失严重**：约60%的数据为-1 +- **图像化处理**：将8×8阵列降采样为2×2特征图（1st Place创新） + +#### 严重数据缺失问题 + +**缺失分布：** +``` +TOF: ~60% 缺失 (-1 标记) +THM: ~3-4% 缺失 (-1 标记) +IMU: 无缺失 +``` + +**前排处理策略：** + +| 排名 | TOF 处理 | THM 处理 | +|------|---------|---------| +| **1st** | 2×2 pooling后标记缺失mask | 简单插值或mask | +| **2nd** | 特征工程提取有效点统计量 | 类似TOF处理 | +| **3rd** | 转图像，缺失填0 | 不使用或简单处理 | +| **其他** | 丢弃或mask | 丢弃或mask | + +**1st Place 的 TOF 处理创新：** +```python +def tof_2x2_pooling_with_mask(tof_data): + """ + TOF 数据 2×2 pooling + 缺失 mask + """ + # 每个 8×8 传感器 + for sensor_idx in range(5): + sensor = tof_data[:, sensor_idx*64:(sensor_idx+1)*64] + sensor = sensor.reshape(-1, 8, 8) + + # 2×2 pooling + pooled = sensor.reshape(-1, 4, 2, 2).mean(axis=(2, 3)) + + # 缺失 mask + mask = (sensor == -1).reshape(-1, 4, 2, 2).any(axis=(2, 3)) + + # 组合：特征 + mask + features[:, sensor_idx*4:(sensor_idx+1)*4] = pooled + features[:, 20+sensor_idx*4:20+(sensor_idx+1)*4] = mask + + return features +``` + +#### 个体约束利用 + +**关键约束：** 每个 subject × gesture × orientation 组合只出现一次 + +**含义：** +- 训练集中没有重复的 subject × gesture × orientation +- 验证时可以确保预测结果也满足这个约束 +- 可以用匈牙利算法做全局最优标签分配 + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **1st** | 匈牙利算法 | 全局最优分配，提升 LB 0.01 | +| **2nd** | 阶段感知建模 | 利用三阶段结构 | +| **其他** | 个体特征 embedding | 添加 subject embedding | + +**匈牙利算法实现（1st Place）：** +```python +from scipy.optimize import linear_sum_assignment + +def hungarian_post_process(predictions, subject_ids, sequence_ids): + """ + 利用 subject × gesture × orientation 唯一约束 + """ + # 对于每个 subject + for subject in unique(subject_ids): + # 获取该 subject 的所有预测 + mask = subject_ids == subject + preds = predictions[mask] + seqs = sequence_ids[mask] + + # 构建代价矩阵：-log(概率) + cost_matrix = -np.log(preds + 1e-10) + + # 匈牙利算法：找到最优分配 + row_ind, col_ind = linear_sum_assignment(cost_matrix) + + # 更新预测结果 + for i, j in zip(row_ind, col_ind): + predictions[mask][i] = np.zeros(n_classes) + predictions[mask][i][j] = 1.0 + + return predictions +``` + +#### 三阶段结构 + +**发现：** 行为序列有明显的三阶段结构 + +``` +Transition → Pause → Gesture +``` + +**阶段特征：** + +| 阶段 | 持续时间 | 特征 | 识别要点 | +|------|---------|------|---------| +| **Transition** | 变化 | 从上一个状态移动到手势位置 | 运动幅度大 | +| **Pause** | 短暂 | 手势开始前的准备 | 运动幅度小 | +| **Gesture** | 重复 | 核心行为模式（如咬指甲） | 周期性模式 | + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **2nd** | 阶段感知 Attention | 每个阶段独立的 attention 权重 | +| **6th** | U-Net分割 | 将手势阶段作为分割任务 | +| **其他** | 特征工程 | 添加阶段分类特征 | + +**2nd Place 阶段感知 Attention：** +```python +class PhaseAwareAttention(nn.Module): + """ + 阶段感知 Attention - 每个阶段独立建模 + """ + def __init__(self, d_model, n_heads=8): + super().__init__() + # 3个阶段 embedding + self.phase_emb = nn.Embedding(3, d_model) + + # 每个阶段独立的 attention + self.transition_attn = nn.MultiheadAttention(d_model, n_heads) + self.pause_attn = nn.MultiheadAttention(d_model, n_heads) + self.gesture_attn = nn.MultiheadAttention(d_model, n_heads) + + def forward(self, x, phase_labels): + # phase_labels: [batch, seq_len] ∈ {0, 1, 2} + batch, seq_len, d_model = x.shape + + outputs = [] + for t in range(seq_len): + phase = phase_labels[:, t] # [batch] + + if phase == 0: # Transition + attn_out, _ = self.transition_attn(x[:, t:t+1], x, x) + elif phase == 1: # Pause + attn_out, _ = self.pause_attn(x[:, t:t+1], x, x) + else: # Gesture + attn_out, _ = self.gesture_attn(x[:, t:t+1], x, x) + + outputs.append(attn_out) + + return torch.cat(outputs, dim=1) +``` + +#### BFRB vs 非BFRB 类别分布 + +**18个手势类别：** + +| 类别 | BFRB类型 | 典型行为 | +|------|---------|---------| +| 0-7 | BFRB | 咬指甲、拉头发、抠皮肤等 | +| 8-17 | 非BFRB | 拍手、挥手、其他手势 | + +**分布特点：** +- **训练集**：BFRB 和非BFRB 数量相近 +- **个体差异**：不同 subject 的手势偏好不同 +- **方向差异**：同一手势不同方向的表现不同 + +**处理策略：** +- **Phase-aware Mixup**：仅在 Gesture 阶段进行 mixup（2nd Place） +- **个体 normalization**：按 subject 做归一化 +- **类别平衡**：确保每个类别有足够样本 + +#### 测试集变化 + +**关键发现：** 测试集约50%的序列仅有 IMU 数据 + +**含义：** +- 不能过度依赖 TOF 和 THM 特征 +- 模型必须能够仅用 IMU 数据做出预测 +- 需要训练仅用 IMU 的模型作为集成成员 + +**前排应对策略：** + +| 排名 | 应对方法 | +|------|---------| +| **1st** | 训练IMU-only模型，集成时加权 | +| **2nd** | 4个模型：IMU-only, IMU+TOF, IMU+THM, All | +| **3rd** | TOF填0处理，但效果受限 | +| **其他** | 简单丢弃缺失传感器 | + +**推荐策略：** +```python +# 训练时模拟测试集情况 +def get_model_input(data): + """ + 根据可用传感器选择模型输入 + """ + has_tof = (data['tof'] != -1).any() + has_thm = (data['thm'] != -1).any() + + if has_tof and has_thm: + return model_all(data['imu'], data['tof'], data['thm']) + elif has_tof: + return model_imu_tof(data['imu'], data['tof']) + elif has_thm: + return model_imu_thm(data['imu'], data['thm']) + else: + return model_imu(data['imu']) +``` + +#### 异常数据识别 + +**两个异常 subject：** + +| Subject | 问题 | 处理策略 | +|---------|------|---------| +| **SUBJ_019262** | 数据异常，预测困难 | 训练时过滤或降权 | +| **SUBJ_045235** | 数据异常，预测困难 | 训练时过滤或降权 | + +**识别方法：** +- 训练集上该 subject 的 loss 异常高 +- 交叉验证该 subject 的预测准确率低 +- 可视化该 subject 的传感器数据，发现异常模式 + +**处理代码：** +```python +# 异常 subject 黑名单 +ANOMALY_SUBJECTS = ['SUBJ_019262', 'SUBJ_045235'] + +def filter_anomaly_subjects(dataframe): + """ + 过滤异常 subject + """ + mask = ~dataframe['subject'].isin(ANOMALY_SUBJECTS) + return dataframe[mask] +``` + +#### 左手系 vs 右手系对齐 + +**发现：** 测试集存在左手和右手两种设备朝向 + +**问题：** +- 左手系和右手系的传感器读数方向相反 +- 四元数表示旋转的方式不同 +- 直接混合训练会引入噪声 + +**解决方案（前排通用）：** +```python +def align_right_handed_system(data): + """ + 左手系 → 右手系对齐 + """ + # 翻转陀螺仪的 x, y 轴 + data['X_gyro'] = -data['X_gyro'] + data['Y_gyro'] = -data['Y_gyro'] + + # 调整四元数（取决于具体定义） + # 这里假设是绕 z 轴旋转 180 度 + data['orientation_X'] = -data['orientation_X'] + data['orientation_Y'] = -data['orientation_Y'] + + return data +``` + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **传感器缺失** | 统计-1值比例 | TOF>50%, THM>5% | mask处理或训练IMU-only模型 | +| **异常subject** | 按subject统计loss | loss > threshold | 过滤SUBJ_019262, SUBJ_045235 | +| **设备朝向** | 检测左右手系 | 四元数和陀螺仪方向 | 统一到右手系 | +| **三阶段一致性** | 检测阶段标签 | 阶段跳变 | 利用三阶段结构特征 | + +### 关键数据洞察总结 + +1. **多模态融合是关键**：IMU + THM + TOF，但测试集仅50%有完整数据 +2. **TOF 缺失严重（60%）**：需要创新处理（2×2 pooling + mask） +3. **个体约束必须利用**：subject × gesture × orientation 唯一约束可用匈牙利算法 +4. **三阶段结构重要**：Transition/Pause/Gesture，阶段感知建模有效 +5. **四元数不连续性**：需转换为6D连续表示（旋转矩阵前两列） +6. **测试集只有IMU数据**：必须训练IMU-only模型作为集成成员 +7. **异常数据需处理**：SUBJ_019262和SUBJ_045235应该过滤或降权 +8. **左手系右手系对齐**：统一到右手系避免噪声 + +### 多模态时间序列分类的最佳实践 + +与单模态分类任务不同，多模态任务的特殊考虑： + +| 方面 | 单模态任务 | 多模态任务 | +|------|-----------|-----------| +| **特征提取** | 单一特征工程 | 每个模态独立提取后融合 | +| **模型架构** | 单一编码器 | 多编码器或早期融合 | +| **缺失处理** | 插值或丢弃 | mask处理或模态specific模型 | +| **数据增强** | 简单增强 | 模态感知增强（Phase-aware Mixup） | +| **后处理** | 阈值或NMS | 利用约束（匈牙利算法） | + +### 音频分类竞赛的最佳实践（BirdCLEF 2024） + +**与 BirdCLEF+ 2025 的主要差异：** +| 维度 | BirdCLEF 2024 | BirdCLEF+ 2025 | +|------|---------------|----------------| +| **物种数量** | 182 种鸟类 | 206 种（多分类群） | +| **推理限制** | 120 分钟 CPU | 90 分钟 CPU | +| **数据策略** | 不用外部数据更优 | Xeno-Canto 预训练重要 | +| **关键创新** | Statistics T 过滤 | Noisy Student + 自蒸馏 | +| **损失函数** | CE Loss（训练）+ Sigmoid（推理） | BCE + FocalLoss | + +#### BirdCLEF 2024 前排方案共性技术 + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **只用前 5 秒** | 1st, 2nd | 后续信息贡献小，节省计算 | +| **伪标签** | 1st, 2nd, 3rd | 利用未标注 soundscape | +| **Ensemble** | 所有前排 | 5-20 模型集成 | +| **OpenVINO/ONNX** | 1st, 3rd | CPU 推理加速必需 | +| **小模型** | 所有前排 | B0/ViT-b0 级别，控制推理时间 | + +#### BirdCLEF 2024 独特技术（与 2025 不同） + +**1. Statistics T 噪声过滤（1st Place）** +```python +# T = std + var + rms + pwr +# 使用 0.8 分位数过滤噪声音频 +T = std + var + rms + pwr +threshold = np.quantile(T, 0.8) +clean_data = data[T < threshold] +``` + +**2. CE Loss + Sigmoid 推理（1st Place）** +- 训练：CE Loss + Softmax（多分类问题） +- 推理：Sigmoid（多标签预测） +- 原因：数据大多只有 1-2 个标签，可视为多分类 +- **注意**：这与 BirdCLEF+ 2025 不同，2025 使用 BCE + FocalLoss + +**3. Min() Ensemble（1st Place）** +```python +# 降低不确定预测，比 mean() 更稳定 +predictions = np.min([model1_pred, model2_pred, model3_pred], axis=0) +``` + +**4. Google Bird Classifier 预标注（1st Place）** +- 使用 Google 模型过滤低质量数据 +- 如果预测与 primary label 不匹配，丢弃 +- 添加 Google 预测作为伪标签（系数 0.05） + +**5. Checkpoint Soup（2nd Place）** +- 平均 13-50 epoch 的 checkpoint +- 代替 early stopping +- 比单 checkpoint 更稳定 + +**6. 伪标签迭代训练（2nd Place）** +- 3 次迭代循环 +- 每次用新集成生成伪标签 +- 25-45% 概率添加伪标签数据 + +#### BirdCLEF 2024 推理优化（120 分钟限制） + +**前排方案的优化策略：** + +| 技术 | 说明 | 排名 | +|------|------|------| +| **OpenVINO 编译** | 固定输入大小，加速推理 | 1st | +| **并行 Mel 计算** | joblib 并行预处理 | 1st, 2nd | +| **RAM 缓存** | 预计算所有 mel spec 存入内存 | 1st | +| **小图像尺寸** | 64x64, 128x128 等 | 2nd | +| **ONNX 优化** | 5 fold 40 分钟 | 3rd | + +#### BirdCLEF 2024 数据处理最佳实践 + +**数据过滤：** +| 问题 | 解决方案 | +|------|----------| +| **噪声数据** | Statistics T 过滤（0.8 分位数） | +| **低质量标注** | Google Classifier 过滤 | +| **重复数据** | 去重处理 | + +**数据增强（2nd Place）：** +```python +# 局部和全局时间/频率拉伸 +# 通过调整图像大小实现 +augmented = resize(mel_spec, (new_height, new_width)) +``` + +#### BirdCLEF 2024 vs 2025：为何策略不同？ + +| 方面 | BirdCLEF 2024 | BirdCLEF+ 2025 | 原因 | +|------|---------------|----------------|------| +| **外部数据** | 不用更优 | Xeno-Canto 关键 | 2024 数据质量高，2025 需要预训练 | +| **损失函数** | CE Loss | BCE + Focal | 2024 数据大多 1-2 标签，2025 更复杂 | +| **集成策略** | Min() | Mean() | 2024 用 Sigmoid 噪声大，Min 更稳定 | + +#### BirdCLEF 2024 常见陷阱 + +| 陷阱 | 说明 | 解决方案 | +|------|------|----------| +| **使用外部数据** | Xeno-Canto 反而降低分数 | 只用 2024 数据 | +| **BCE Loss** | 比 CE Loss 效果差 | CE Loss + Sigmoid 推理 | +| **Mean Ensemble** | 对 Sigmoid 输出不稳定 | Min() Ensemble | +| **忽略 Statistics T** | fold0 优于其他 fold | 用统计量过滤噪声 | +| **太大模型** | 推理超时 | B0/RegNetY 级别 | + +### 音频分类竞赛的最佳实践（BirdCLEF+ 2025） + +与通用时间序列分类不同，音频分类（生物声学）有特殊的挑战和技术： + +| 方面 | 通用时序分类 | 音频分类（生物声学） | +|------|-------------|---------------------| +| **特征表示** | 原始信号/统计特征 | Mel-Spectrogram（时频表示） | +| **模型架构** | 1D-CNN/RNN/Transformer | SED 模型（2D-CNN + Attention） | +| **数据特点** | 通常标注完整 | 大量未标注数据（半监督学习关键） | +| **类别分布** | 相对均衡 | 极端长尾（稀有物种 <10 样本） | +| **推理约束** | 通常无特殊限制 | 严格时间限制（90分钟CPU） | +| **评估指标** | Accuracy/F1/ MSE | 宏平均 AUC（每个类独立） | + +#### BirdCLEF+ 2025 前排方案共性技术 + +**"银弹" - 所有前排方案共同使用：** + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **伪标签技术** | 1st-14th | 利用未标注 train_soundscapes 数据 | +| **Mel-Spectrogram** | 1st-14th | 将音频转换为图像表示 | +| **SED 模型架构** | 1st-14th | 帧级 + 片级预测 | +| **模型集成** | 1st-14th | 5-20 个模型集成 | +| **SpecAugment** | 1st-14th | 时间/频率掩码增强 | +| **EfficientNet 系列** | 多数 | tf_efficientnetv2_s/b3/m 作为 backbone | + +#### Mel-Spectrogram 配置最佳实践 + +前排方案使用的配置总结： + +| 配置 | n_mels | n_fft | hop_length | 使用场景 | +|------|--------|-------|-------------|----------| +| **标准配置** | 128 | 2048 | 512 | tf_efficientnetv2 系列（最常用） | +| **轻量配置** | 96 | 2048 | 512 | 轻量级模型，推理加速 | +| **高分辨率** | 256 | 4096 | 1024 | 高精度要求 | + +**频率范围设置（关键）：** +```python +# 鸟类声音频率范围 +FMIN = 0.0 # 最低频率（有些方案用 50Hz 过滤低频噪声） +FMAX = 16000.0 # 最高频率（32kHz 采样率的一半） + +# 稀有物种可能需要调整 +FMIN_RARE = 100.0 # 过滤低频环境噪声 +FMAX_RARE = 15000.0 # 避免高频噪声 +``` + +#### 半监督学习最佳实践（伪标签） + +**伪标签生成流程（前排方案共识）：** + +``` +阶段 1: 基础模型训练 + └── 使用 train_audio（有标签）训练 SED 模型 + +阶段 2: 伪标签生成 + ├── 对 train_soundscapes 进行推理 + ├── 应用高低阈值筛选 + │ ├── 高阈值（≥0.7）: 正样本 + │ └── 低阈值（≤0.3）: 负样本 + └── 幂次变换减少噪声（1st Place 创新） + +阶段 3: 混合训练 + ├── 50% train_audio + 50% 伪标签数据 + ├── MixUp 增强混合数据 + └── 迭代 2-3 次 +``` + +**关键参数（前排方案范围）：** +| 参数 | 范围 | 推荐值 | 说明 | +|------|------|--------|------| +| **高阈值** | 0.6-0.8 | 0.7 | 正样本置信度阈值 | +| **低阈值** | 0.2-0.4 | 0.3 | 负样本置信度阈值 | +| **幂次变换** | 1.2-2.0 | 1.5 | 减少伪标签噪声 | +| **混合比例** | 30%-50% | 50% | 伪标签数据占比 | + +**伪标签质量检查（10th Place 方法）：** +```python +# 高低阈值筛选 +high_threshold = 0.7 +low_threshold = 0.3 + +# 正样本：高置信度 +positive_mask = probs >= high_threshold + +# 负样本：低置信度 +negative_mask = probs <= low_threshold + +# 中等置信度：不使用（可能是噪声） +uncertain_mask = (probs > low_threshold) & (probs < high_threshold) + +# 只使用正负样本 +valid_mask = positive_mask | negative_mask +``` + +#### 推理优化最佳实践（90 分钟约束） + +BirdCLEF+ 2025 最关键的约束是 90 分钟 CPU 推理限制。前排方案的优化策略： + +**模型优化：** +| 技术 | 使用排名 | 加速比 | 说明 | +|------|---------|--------|------| +| **ONNX 导出** | 3rd, 12th, 14th | 2-3x | 标准化推理格式 | +| **OpenVINO** | 12th | 3-5x | Intel 优化，CPU 最优 | +| **模型量化** | 部分方案 | 1.5-2x | INT8 量化（可能损失精度） | +| **Batch 推理** | 所有方案 | 2-4x | 批量推理提高利用率 | + +**Mel-Spectrogram 预计算：** +```python +# 推理阶段预先计算所有 mel-spectrogram +# 避免 GPU-CPU 数据传输开销 + +def precompute_mel_spectrograms(audio_files, cache_dir="cache/mel"): + """预计算并缓存 mel-spectrogram""" + os.makedirs(cache_dir, exist_ok=True) + + for audio_file in tqdm(audio_files): + cache_path = os.path.join(cache_dir, f"{Path(audio_file).stem}.npy") + + if not os.path.exists(cache_path): + # 计算 mel-spectrogram + waveform, sr = torchaudio.load(audio_file) + mel_spec = extract_mel_spectrogram(waveform, sr) + + # 缓存 + np.save(cache_path, mel_spec.numpy()) +``` + +**滑动窗口优化（1st Place 创新）：** +```python +# 使用相邻窗口预测的平均值 +# 避免重复计算，提高推理效率 + +def sliding_window_inference_optimized(model, audio_path): + """优化的滑动窗口推理""" + waveform, sr = torchaudio.load(audio_path) + + # 一次性提取所有窗口的 mel-spectrogram + # 避免重复计算 + all_windows = extract_all_windows(waveform, sr) + + # Batch 推理 + with torch.no_grad(): + predictions = model(all_windows) # (num_windows, num_classes) + + # 相邻窗口平均（1st Place 创新） + smoothed_predictions = smooth_adjacent_windows(predictions) + + return smoothed_predictions +``` + +**前后处理优化：** +| 技术 | 说明 | +|------|------| +| **NumPy 向量化** | 避免循环，使用 NumPy 内置函数 | +| **多进程推理** | 并行处理多个音频文件 | +| **结果缓存** | 避免重复计算 | +| **精简后处理** | 简单平滑即可，避免复杂操作 | + +#### 长尾分布处理最佳实践 + +BirdCLEF+ 2025 数据集存在极端长尾分布（某些物种 <10 样本）： + +**前排方案的处理策略：** + +| 策略 | 使用排名 | 说明 | +|------|---------|------| +| **过采样** | 多数 | 复制稀有类样本至 20-50 | +| **损失加权** | 部分方案 | 稀有类更高权重 | +| **Focal Loss** | 9th Place | 自动处理难样本 | +| **分开训练** | 7th, 13th | 稀有类单独训练模型 | +| **数据增强** | 所有方案 | MixUp/SpecAugment 增加多样性 | + +**稀有物种模型训练（13th Place 策略）：** +```python +# 识别稀有物种（样本数 < 30） +rare_species = [species for species in all_species + if get_sample_count(species) < 30] + +# 训练稀有物种专用模型 +rare_model = create_model(num_classes=len(rare_species)) +rare_model.train_on(rare_species_data) + +# 集成时加入稀有模型预测 +final_prediction = 0.7 * general_model + 0.3 * rare_model +``` + +#### 模型集成最佳实践 + +前排方案的集成策略总结： + +**集成规模：** +| 排名 | 模型数量 | 架构多样性 | 说明 | +|------|---------|-----------|------| +| **1st** | ~10 | 多迭代 Noisy Student | 同一模型不同迭代 | +| **2nd** | ~5-8 | 不同 backbone | tf_efficientnetv2_s + eca_nfnet_l0 | +| **3rd** | 20 | 10 CNN + 10 SED | 最大规模集成 | +| **5th** | ~5-10 | EfficientNet 系列 | 自蒸馏不同阶段 | + +**集成方法：** +```python +# 简单平均（最常用） +predictions = np.mean([model1_pred, model2_pred, model3_pred], axis=0) + +# 加权平均（需要验证集调优） +weights = [0.3, 0.3, 0.4] +predictions = np.average([model1_pred, model2_pred, model3_pred], + axis=0, weights=weights) + +# Min-max 缩放后平均（7th Place） +for i in range(len(predictions)): + pred_min = predictions[i].min() + pred_max = predictions[i].max() + predictions[i] = (predictions[i] - pred_min) / (pred_max - pred_min) + +predictions = np.mean(predictions, axis=0) +``` + +**集成多样性（关键）：** +| 维度 | 多样性来源 | 说明 | +|------|-----------|------| +| **架构** | 不同 backbone | EfficientNetV2 vs NFNet | +| **数据** | 不同训练数据 | 原始 vs 伪标签 vs Xeno-Canto | +| **阶段** | 不同训练阶段 | Checkpoint Soups (12th Place) | +| **配置** | 不同 mel 参数 | n_mels=128 vs 96 | +| **随机性** | 不同随机种子 | 数据增强和初始化差异 | + +#### 常见陷阱和注意事项 + +基于前排方案经验： + +| 陷阱 | 说明 | 解决方案 | +|------|------|---------| +| **过拟合验证集** | LB 和 CV 分数差距大 | 更保守的集成，减少后处理 | +| **伪标签噪声累积** | 多次迭代后性能下降 | 幂次变换 + 高低阈值筛选 | +| **稀有物种检测失败** | 长尾类预测全为 0 | 单独训练稀有模型 + Focal Loss | +| **推理超时** | 90 分钟不够 | ONNX/OpenVINO + Batch 推理 | +| **人声干扰** | 背景人声导致误检 | Silero VAD 去除人声片段 | +| **测试集分布偏移** | 训练/测试环境差异 | 领域适应技术（13th Place） | + +--- + +--- + +## Google Brain - Ventilator Pressure Prediction (2021) + +### Competition Brief (竞赛简介) + +**竞赛背景：** +- **主办方**：Google Brain +- **目标**：预测机械呼吸机气道压力（时序回归任务） +- **应用场景**：自动化机械通气控制，辅助重症监护治疗 +- **社会意义**：减少医护人员手动调整呼吸机的工作量，提高治疗精度 + +**任务描述：** +从呼吸机的控制信号和肺部属性中，预测气道压力： +- **输入**：时间序列控制信号（u_in, u_out）+ 肺部属性（R, C） +- **输出**：每个时间步的气道压力（连续值） +- **约束**：测试集中 66% 的数据由 PID 控制器生成 + +**数据集规模：** +- 训练样本：6,036,000 条时间步 +- 测试样本：4,024,000 条时间步 +- 呼吸次数：约 75,450 次呼吸（训练）+ 40,240 次呼吸（测试） +- 患者数量：数千个不同患者的肺部特征 + +**数据特点：** +1. **PID 控制模式**：测试集中 2/3 的数据遵循 PID 控制规律 +2. **双重输入**：控制信号（u_in 连续，u_out 二值）+ 肺部属性（R 电阻，C 顺应性） +3. **时间步长**：80 步/次呼吸，不同患者呼吸模式不同 +4. **物理约束**：压力变化需遵循呼吸力学规律 + +**评估指标：** +- **MAE (Mean Absolute Error)**：平均绝对误差 +- 目标：最小化预测压力与真实压力的绝对差异 + +**竞赛约束：** +- 代码提交：Kaggle Notebooks 环境 +- 推理时间：无严格限制，但需考虑实用性 +- 模型大小：需平衡精度和推理速度 + +**最终排名：** +- 1st Place: group16 (Gilles Vandewiele et al.) - MAE ~0.104 +- 2nd Place: ambrosm - MAE ~0.105 +- 3rd Place: Upstage - MAE ~0.106 +- 总参赛队伍：2,605 支 + +**技术趋势：** +- **PID 逆向建模**：前排方案的核心创新 +- **多任务学习**：同时预测压力和压力变化 +- **LSTM/Transformer 混合**：结合时序建模和注意力机制 +- **集成策略**：3-10 个模型集成 + +**关键创新：** +- **PID Controller Matching**：利用 PID 控制规律直接拟合（1st, 2nd, 4th Place） +- **Delta Pressure 辅助任务**：预测压力差提升主任务（6th, 14th, 20th Place） +- **物理约束嵌入**：将呼吸力学知识融入模型（3rd Place） + +**后续影响：** +- 推动了医疗时序预测的发展 +- PID 逆向建模成为经典技巧 +- 多篇研究论文引用该比赛方法 + +--- + +### Original Summaries (原始总结) + +**前排方案概述：** + +1. **PID 控制器逆向流派（1st, 2nd, 4th Place）** + - 利用测试集中 66% 数据遵循 PID 控制的规律 + - 通过逆向 PID 公式直接预测压力 + - 无需深度学习即可获得极好结果 + +2. **深度学习流派（3rd, 6th, 14th Place）** + - 使用 LSTM/Transformer 建模时序依赖 + - 多任务学习预测压力和压力差 + - 不依赖 PID 规律，更通用 + +3. **混合流派（16th, 20th Place）** + - 结合 PID 匹配和深度学习 + - 使用辅助任务提升性能 + - 中间排名的务实策略 + +--- + +### 前排方案详细技术分析 + +#### 1st Place - group16 (Gilles Vandewiele et al.) + +**核心技巧：** +- **PID Controller Matching**：核心创新，拟合测试集 PID 控制规律 +- **LSTM + CNN + Transformer 混合架构**：深度学习部分 +- **两阶段预测**：先用 PID 匹配 66% 数据，再用 DL 预测剩余 34% +- **模型集成**：多个模型组合提升稳定性 + +**实现细节：** +- **PID 逆向公式**： + - 从 u_in 信号逆向推导目标压力 + - 拟合 PID 参数：Kp, Ki, Kd + - 对于 PID 控制的呼吸，MAE 可达到 0.05-0.08 + +- **深度学习模型**： + ```python + # LSTM + CNN + Transformer 混合架构 + class VentilatorModel(nn.Module): + def __init__(self): + self.cnn = CNN1D(input_dim=5) # u_in, u_out, R, C, time_step + self.lstm = LSTM(hidden_dim=256, num_layers=2) + self.transformer = TransformerEncoder(num_layers=2, nhead=8) + self.fc = Linear(256, 1) # 预测压力 + + def forward(self, x): + # CNN 提取局部特征 + x = self.cnn(x) + # LSTM 建模时序依赖 + x = self.lstm(x) + # Transformer 捕获长距离依赖 + x = self.transformer(x) + # 预测压力 + return self.fc(x) + ``` + +- **两阶段策略**： + 1. 识别测试集中哪些呼吸由 PID 控制（约 66%） + 2. 对 PID 呼吸使用逆向公式 + 3. 对非 PID 呼吸使用深度学习模型 + 4. 最终集成两种预测 + +- **特征工程**： + - 原始特征：u_in, u_out, R, C, time_step + - 衍生特征：u_in 的累积和、差分、滚动统计 + - 位置编码：sin/cos 位置嵌入 + - 肺部属性编码：R 和 C 的 embedding + +- **训练策略**： + - 损失函数：MAE + delta_pressure_MAE（多任务） + - 优化器：AdamW (lr=1e-3, weight_decay=0.01) + - 学习率调度：CosineAnnealingWarmRestarts + - 早停：CV 15 epochs 无改善则停止 + +- **最终 MAE**：约 0.104 + +**代码仓库**：[GillesVandewiele/google-brain-ventilator](https://github.com/GillesVandewiele/google-brain-ventilator) + +--- + +#### 2nd Place - ambrosm + +**核心技巧：** +- **The Inverse of a PID Controller**：纯粹的 PID 逆向方法 +- **无需深度学习**：完全基于物理规律 +- **数学拟合**：优化 PID 参数最小化误差 + +**实现细节：** +- **PID 逆向公式**： + ```python + def pid_inverse(u_in, u_out, R, C): + """ + PID 控制器的逆向函数 + 从控制信号 u_in 推导目标压力 + + PID 公式：u_in = Kp * e + Ki * ∫e dt + Kd * de/dt + 逆向：从 u_in 拟合目标压力 + """ + # 对每个呼吸单独拟合 + pressures = [] + + for breath_id in unique_breaths: + u_in_breath = u_in[breath_id] + u_out_breath = u_out[breath_id] + + # 拟合 PID 参数 + # 目标：最小化 u_in_pred - u_in_actual + Kp, Ki, Kd = fit_pid_parameters(u_in_breath, u_out_breath) + + # 逆向计算压力 + pressure = inverse_pid(u_in_breath, Kp, Ki, Kd, R, C) + pressures.append(pressure) + + return pressures + ``` + +- **参数优化**： + - 使用 Scipy.optimize.minimize 优化 PID 参数 + - 约束：Kp, Ki, Kd > 0 + - 损失：MSE between u_in_pred 和 u_in_actual + +- **最终 MAE**：约 0.105 + +**技术特点**： +- 最简洁的前排方案 +- 无需训练模型 +- 推理速度极快 +- 但仅适用于 PID 控制的呼吸 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/ambrosm-2-solution-the-inverse-of-a-pid-controller) + +--- + +#### 3rd Place - Upstage + +**核心技巧：** +- **Single Model without PID**：唯一不使用 PID 的前排方案 +- **多任务损失**：同时预测压力和压力变化 +- **数据增强**：时间扭曲、幅值缩放 +- **物理约束损失**：加入呼吸力学先验 + +**实现细节：** +- **模型架构**： + ```python + class UpstageModel(nn.Module): + def __init__(self): + self.embedding = Embedding(num_r_values * num_c_values, 64) + self.lstm1 = LSTM(input_dim=64+3, hidden_dim=256, num_layers=2, bidirectional=True) + self.lstm2 = LSTM(input_dim=512, hidden_dim=128, num_layers=1) + self.fc_pressure = Linear(128, 1) + self.fc_delta = Linear(128, 1) # 辅助任务 + + def forward(self, u_in, u_out, R, C): + # 肺部属性嵌入 + rc_embed = self.embedding(R * 100 + C) + + # 拼接输入 + x = torch.cat([u_in, u_out, rc_embed], dim=-1) + + # LSTM 建模 + x = self.lstm1(x) + x = self.lstm2(x) + + # 多任务预测 + pressure = self.fc_pressure(x) + delta = self.fc_delta(x) + + return pressure, delta + ``` + +- **多任务损失**： + ```python + def loss_function(pressure_pred, delta_pred, pressure_true): + # 主任务：压力预测 + loss_pressure = F.l1_loss(pressure_pred, pressure_true) + + # 辅助任务：压力差预测 + delta_true = pressure_true[:, 1:] - pressure_true[:, :-1] + loss_delta = F.l1_loss(delta_pred[:, :-1], delta_true) + + # 加权组合 + return loss_pressure + 0.3 * loss_delta + ``` + +- **数据增强**： + - 时间扭曲：随机拉伸/压缩时间轴 + - 幅值缩放：u_in 乘以 0.8-1.2 随机因子 + - 噪声注入：加入高斯噪声 + +- **物理约束**： + - 压力变化率约束：|dP/dt| < threshold + - 压力范围约束：0 < P < 60 cmH2O + +- **最终 MAE**：0.0975（不含 PID 后处理） + +**技术特点**： +- 最通用的前排方案 +- 不依赖 PID 规律 +- 可应用于新数据分布 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/upstage-making-ai-beneficial-3rd-place-single-mode) + +--- + +#### 4th Place - Jun Koda + +**核心技巧：** +- **Hacking the PID Control**：深入分析 PID 控制规律 +- **线性关系发现**：u_in 与目标压力线性相关 +- **分段处理**：对不同阶段使用不同策略 + +**实现细节：** +- **核心发现**： + ```python + # 吸气阶段（u_out = 0） + # u_in 与目标 pressure 呈线性关系 + u_in = α * pressure_target + β + + # 呼气阶段（u_out = 1） + # 压力按指数衰减 + pressure = pressure_peak * exp(-t / τ) + + # 其中 τ = R * C（时间常数） + ``` + +- **逆向求解**： + ```python + def predict_pressure(u_in, u_out, R, C): + pressures = [] + + for t in range(len(u_in)): + if u_out[t] == 0: # 吸气 + # 线性关系 + pressure[t] = (u_in[t] - β) / α + else: # 呼气 + # 指数衰减 + pressure[t] = pressure_peak * exp(-t / (R * C)) + + return pressures + ``` + +- **参数拟合**： + - α, β 通过线性回归拟合 + - τ 通过非线性优化拟合 + - 不同 R, C 组合使用不同参数 + +- **最终 MAE**：约 0.106 + +**技术特点**： +- 深入理解 PID 控制原理 +- 利用物理规律简化问题 +- 计算效率极高 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/jun-koda-4th-place-solution-hacking-the-pid-contro) + +--- + +#### 6th Place - 0-0ggg + +**核心技巧：** +- **Single Multi-task LSTM**：单模型多任务学习 +- **Delta Pressure 预测**：辅助任务提升主任务 +- **特征工程**：丰富的时序特征 + +**实现细节：** +- **模型架构**： + ```python + class MultiTaskLSTM(nn.Module): + def __init__(self, input_dim=5, hidden_dim=128): + super().__init__() + self.lstm = LSTM(input_dim, hidden_dim, num_layers=2, dropout=0.2) + self.fc_pressure = Linear(hidden_dim, 1) + self.fc_delta = Linear(hidden_dim, 1) + + def forward(self, x): + # LSTM 编码 + x, _ = self.lstm(x) + + # 多任务预测 + pressure = self.fc_pressure(x) + delta = self.fc_delta(x) + + return pressure, delta + ``` + +- **特征工程**： + - 原始特征：u_in, u_out, R, C + - 时序特征：u_in 的 lag-1, lag-2, lag-3 + - 统计特征：rolling mean, rolling std + - 交互特征：u_in * R, u_in * C + - 时间特征：sin/cos 时间编码 + +- **多任务训练**： + ```python + def train_step(model, batch): + pressure_pred, delta_pred = model(batch) + + # 主任务损失 + loss_pressure = mae_loss(pressure_pred, batch.pressure) + + # 辅助任务损失 + delta_true = batch.pressure[:, 1:] - batch.pressure[:, :-1] + loss_delta = mae_loss(delta_pred[:, :-1], delta_true) + + # 总损失 + loss = loss_pressure + 0.2 * loss_delta + return loss + ``` + +- **最终 MAE**：约 0.108 + +**技术特点**： +- 简洁有效的架构 +- 多任务学习提升性能 +- CV/LB 一致性好 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/0-0ggg-6th-place-solution-single-multi-task-lstm) + +--- + +#### 14th Place - pksha (Team "no pressure") + +**核心技巧：** +- **Multitask LSTM**：同时预测压力和压力变化 +- **Delta Pressure 辅助任务**：关键创新 +- **集成策略**：多模型融合 + +**实现细节：** +- **多任务设计**： + ```python + class MultitaskLSTM(nn.Module): + def __init__(self): + self.lstm = LSTM(input_dim=6, hidden_dim=128, num_layers=2, bidirectional=True) + self.fc1 = Linear(256, 64) + self.fc_pressure = Linear(64, 1) + self.fc_delta = Linear(64, 1) + + def forward(self, x): + x, _ = self.lstm(x) + x = F.relu(self.fc1(x)) + pressure = self.fc_pressure(x) + delta = self.fc_delta(x) + return pressure, delta + ``` + +- **辅助任务价值**： + - 预测 delta pressure：P[t] - P[t-1] + - 帮助模型学习压力变化趋势 + - CV/LB 提升 +0.01 ~ +0.015 + +- **最终 MAE**：约 0.112 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/pksha-no-pressure-14th-place-solution-multitask-ls) + +--- + +#### 16th Place - player2-has-flatlined + +**核心技巧：** +- **Journey Writeup**：详细的开发历程 +- **渐进优化**：从 baseline 到最终方案 +- **务实策略**：平衡效果和复杂度 + +**实现细节：** +- **开发历程**： + 1. Baseline LSTM：MAE ~0.15 + 2. 加入特征工程：MAE ~0.13 + 3. 多任务学习：MAE ~0.115 + 4. 模型集成：MAE ~0.113 + +- **关键改进**： + - 丰富特征工程 + - 多任务学习（delta pressure） + - 交叉验证策略优化 + - 简单平均集成 + +- **最终 MAE**：约 0.113 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/player2-has-flatlined-16th-place-journey-writeup-n) + +--- + +#### 20th Place - hyeongchan-nikita / kozistr + +**核心技巧：** +- **Model & Multi-task Learning**：深度学习 + 多任务 +- **Delta Pressure Auxiliary Loss**：核心技术 +- **Top 1% 铜牌边界**：进入前 1% 的方案 + +**实现细节（kozistr）：** +- **多任务损失**： + ```python + def multi_task_loss(pressure_pred, delta_pred, pressure_true): + # 主任务 + loss_pressure = F.l1_loss(pressure_pred, pressure_true) + + # 辅助任务：delta pressure + delta_true = torch.diff(pressure_true, dim=1) + loss_delta = F.l1_loss(delta_pred[:, :-1], delta_true) + + return loss_pressure + 0.15 * loss_delta + ``` + +- **模型架构**： + - LSTM（2 层，128 隐藏单元） + - 特征：u_in, u_out, R, C + 统计特征 + - Dropout：0.3 + +- **最终 MAE**：约 0.116（Top 1% 边界） + +**技术特点**： +- 最简单的前排方案之一 +- 证明了多任务学习的有效性 +- CV/LB 提升 +0.01 ~ +0.015 + +**参考文章**：[Blog Post](https://kozistr.tech/2021-11-03-ventilator-pressure-prediction/) + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/hyeongchan-nikita-20th-place-solution-model-multi-) + +--- + +### Code Templates (代码模板) + +#### PID Controller Matching (1st Place 核心技巧) + +```python +import numpy as np +from scipy.optimize import minimize + +def fit_pid_parameters(u_in, u_out, initial_pressure=0): + """ + 拟合 PID 控制器参数 + + Args: + u_in: 控制信号 (array) + u_out: 吸气/呼气标志 (array) + initial_pressure: 初始压力 + + Returns: + Kp, Ki, Kd: PID 参数 + """ + + def pid_loss(params, u_in, u_out): + Kp, Ki, Kd = params + + # 模拟 PID 控制器 + pressure_pred = simulate_pid(u_in, u_out, Kp, Ki, Kd, initial_pressure) + + # 计算误差（逆向：从 u_in 预测 pressure 的误差） + error = np.mean((u_in - target_from_pressure(pressure_pred)) ** 2) + return error + + # 初始参数 + x0 = [1.0, 0.1, 0.5] + + # 约束：参数必须为正 + bounds = [(0, None), (0, None), (0, None)] + + # 优化 + result = minimize(pid_loss, x0, args=(u_in, u_out), bounds=bounds) + + return result.x + +def simulate_pid(u_in, u_out, Kp, Ki, Kd, initial_pressure): + """ + PID 控制器模拟 + + Args: + u_in: 控制信号 + u_out: 吸气/呼气标志 + Kp, Ki, Kd: PID 参数 + initial_pressure: 初始压力 + + Returns: + pressure: 预测的压力序列 + """ + n_steps = len(u_in) + pressure = np.zeros(n_steps) + pressure[0] = initial_pressure + + integral = 0 + prev_error = 0 + + for t in range(1, n_steps): + # 设定值（目标压力） + setpoint = pressure[t-1] # 维持当前压力 + + # 过程变量（当前压力） + pv = pressure[t-1] + + # 误差 + error = setpoint - pv + + # 积分项 + integral += error + + # 微分项 + derivative = error - prev_error + prev_error = error + + # PID 输出 + output = Kp * error + Ki * integral + Kd * derivative + + # 肺部响应（一阶系统） + # dP/dt = (u_in - P) / (R * C) + R, C = get_rc_params(t) # 获取 R, C 参数 + tau = R * C # 时间常数 + + pressure[t] = pressure[t-1] + (output - pressure[t-1]) / tau + + # 呼气阶段处理 + if u_out[t] == 1: + pressure[t] = pressure[t] * 0.9 # 衰减 + + return pressure + +def predict_pressure_pid(u_in, u_out, R, C): + """ + 使用 PID 逆向方法预测压力 + + Args: + u_in: 控制信号 + u_out: 吸气/呼气标志 + R: 肺部电阻 + C: 肺部顺应性 + + Returns: + pressure: 预测压力 + """ + # 按呼吸分组 + breath_ids = get_breath_ids(u_out) + + pressures = [] + + for breath_id in breath_ids: + u_in_breath = u_in[breath_id] + u_out_breath = u_out[breath_id] + + # 拟合 PID 参数 + Kp, Ki, Kd = fit_pid_parameters(u_in_breath, u_out_breath) + + # 逆向预测压力 + pressure_breath = inverse_pid(u_in_breath, u_out_breath, Kp, Ki, Kd, R, C) + pressures.extend(pressure_breath) + + return np.array(pressures) + +def inverse_pid(u_in, u_out, Kp, Ki, Kd, R, C): + """ + PID 逆向：从 u_in 推导压力 + + 简化版本：假设比例控制主导 + u_in ≈ Kp * (target - current) + => target ≈ u_in / Kp + current + """ + n_steps = len(u_in) + pressure = np.zeros(n_steps) + + pressure[0] = 5 # 初始压力 + + for t in range(1, n_steps): + if u_out[t] == 0: # 吸气 + # 比例控制 + pressure[t] = pressure[t-1] + u_in[t] / Kp + else: # 呼气 + # 指数衰减 + tau = R * C + pressure[t] = pressure[t-1] * np.exp(-1 / tau) + + return pressure +``` + +#### Multi-task LSTM (6th, 14th, 20th Place 技巧) + +```python +import torch +import torch.nn as nn + +class MultiTaskVentilatorLSTM(nn.Module): + """多任务 LSTM 模型""" + + def __init__(self, input_dim=5, hidden_dim=128, num_layers=2, dropout=0.2): + super().__init__() + + # LSTM 层 + self.lstm = nn.LSTM( + input_size=input_dim, + hidden_size=hidden_dim, + num_layers=num_layers, + dropout=dropout, + batch_first=True, + bidirectional=True + ) + + # 全连接层 + self.fc1 = nn.Linear(hidden_dim * 2, 64) + self.dropout = nn.Dropout(dropout) + + # 多任务输出 + self.fc_pressure = nn.Linear(64, 1) # 主任务：压力预测 + self.fc_delta = nn.Linear(64, 1) # 辅助任务：压力差预测 + + def forward(self, x): + # LSTM 编码 + lstm_out, _ = self.lstm(x) # (batch, seq, hidden*2) + + # 全连接 + out = F.relu(self.fc1(lstm_out)) + out = self.dropout(out) + + # 多任务预测 + pressure = self.fc_pressure(out).squeeze(-1) # (batch, seq) + delta = self.fc_delta(out).squeeze(-1) # (batch, seq) + + return pressure, delta + +def multi_task_loss(pressure_pred, delta_pred, pressure_true, delta_weight=0.2): + """ + 多任务损失函数 + + Args: + pressure_pred: 压力预测 (batch, seq) + delta_pred: 压力差预测 (batch, seq) + pressure_true: 真实压力 (batch, seq) + delta_weight: 辅助任务权重 + + Returns: + total_loss: 总损失 + """ + # 主任务：压力预测 MAE + loss_pressure = F.l1_loss(pressure_pred, pressure_true) + + # 辅助任务：压力差预测 MAE + # 计算真实压力差 + delta_true = pressure_true[:, 1:] - pressure_true[:, :-1] + delta_pred_trimmed = delta_pred[:, 1:] + + loss_delta = F.l1_loss(delta_pred_trimmed, delta_true) + + # 加权组合 + total_loss = loss_pressure + delta_weight * loss_delta + + return total_loss + +# 训练循环 +def train_model(model, train_loader, val_loader, num_epochs=30, lr=1e-3): + optimizer = torch.optim.AdamW(model.parameters(), lr=lr, weight_decay=0.01) + scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( + optimizer, T_0=10, T_mult=2 + ) + + best_val_loss = float('inf') + patience = 5 + patience_counter = 0 + + for epoch in range(num_epochs): + # 训练 + model.train() + train_loss = 0 + + for batch in train_loader: + x = batch['features'] # (batch, seq, 5) + y = batch['pressure'] # (batch, seq) + + optimizer.zero_grad() + + # 前向传播 + pressure_pred, delta_pred = model(x) + + # 计算损失 + loss = multi_task_loss(pressure_pred, delta_pred, y) + + # 反向传播 + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证 + model.eval() + val_loss = 0 + + with torch.no_grad(): + for batch in val_loader: + x = batch['features'] + y = batch['pressure'] + + pressure_pred, delta_pred = model(x) + loss = multi_task_loss(pressure_pred, delta_pred, y) + val_loss += loss.item() + + # 学习率调度 + scheduler.step() + + # 早停 + if val_loss < best_val_loss: + best_val_loss = val_loss + patience_counter = 0 + # 保存最佳模型 + torch.save(model.state_dict(), 'best_model.pth') + else: + patience_counter += 1 + if patience_counter >= patience: + print(f'Early stopping at epoch {epoch}') + break + + print(f'Epoch {epoch}: Train Loss={train_loss/len(train_loader):.4f}, ' + f'Val Loss={val_loss/len(val_loader):.4f}') + + # 加载最佳模型 + model.load_state_dict(torch.load('best_model.pth')) + return model +``` + +#### 特征工程模板 + +```python +import numpy as np +import pandas as pd + +def create_features(df): + """ + 创建时序特征 + + Args: + df: 原始数据，包含列： + - u_in: 控制信号 + - u_out: 吸气/呼气标志 + - R: 肺部电阻 + - C: 肺部顺应性 + - breath_id: 呼吸ID + + Returns: + features: 特征 DataFrame + """ + df = df.copy() + + # 1. 基础特征 + features = df[['u_in', 'u_out', 'R', 'C']].copy() + + # 2. 时序特征：滞后 + for lag in [1, 2, 3]: + features[f'u_in_lag{lag}'] = df['u_in'].shift(lag) + + # 3. 时序特征：差分 + features['u_in_diff1'] = df['u_in'].diff() + features['u_in_diff2'] = df['u_in'].diff(2) + + # 4. 统计特征：滚动窗口 + for window in [5, 10]: + features[f'u_in_rolling_mean_{window}'] = df['u_in'].rolling(window).mean() + features[f'u_in_rolling_std_{window}'] = df['u_in'].rolling(window).std() + features[f'u_in_rolling_max_{window}'] = df['u_in'].rolling(window).max() + features[f'u_in_rolling_min_{window}'] = df['u_in'].rolling(window).min() + + # 5. 累积特征 + features['u_in_cumsum'] = df['u_in'].cumsum() + features['u_in_cummax'] = df['u_in'].cummax() + + # 6. 交互特征 + features['u_in_R'] = df['u_in'] * df['R'] + features['u_in_C'] = df['u_in'] * df['C'] + features['R_C'] = df['R'] * df['C'] # 时间常数 + + # 7. 时间特征（位置编码） + features['time_step'] = np.arange(len(df)) + features['time_sin'] = np.sin(2 * np.pi * features['time_step'] / 80) + features['time_cos'] = np.cos(2 * np.pi * features['time_step'] / 80) + + # 8. 呼吸级别特征 + breath_groups = df.groupby('breath_id') + + features['u_in_breath_mean'] = breath_groups['u_in'].transform('mean') + features['u_in_breath_max'] = breath_groups['u_in'].transform('max') + features['u_in_breath_std'] = breath_groups['u_in'].transform('std') + + # 9. 阶段特征 + features['u_out_lag1'] = df['u_out'].shift(1) + features['inhale_start'] = (features['u_out_lag1'] == 1) & (df['u_out'] == 0) + features['exhale_start'] = (features['u_out_lag1'] == 0) & (df['u_out'] == 1) + + # 10. 填充缺失值 + features = features.fillna(method='bfill').fillna(0) + + return features + +# 使用示例 +# df = pd.read_csv('train.csv') +# features = create_features(df) +# print(features.shape) +``` + +--- + +### Best Practices (最佳实践) + +#### PID 控制器逆向策略 + +**适用场景：** +- 测试集存在已知控制规律（如 PID） +- 控制信号与目标存在可逆向的关系 + +**实现步骤：** +1. **分析控制规律**： + - 绘制 u_in 与 pressure 的关系图 + - 识别线性/非线性关系 + - 分析不同阶段（吸气/呼气）的规律 + +2. **拟合逆向函数**： + - 使用优化方法拟合参数 + - 添加物理约束（如参数 > 0） + - 分组拟合（不同 R, C 组合） + +3. **混合策略**： + - 对 PID 控制样本使用逆向方法 + - 对非 PID 样本使用深度学习 + - 加权融合两种预测 + +**注意事项：** +| 问题 | 解决方案 | +|------|---------| +| 非线性关系 | 分段线性或使用非线性优化 | +| 参数不稳定 | 正则化或参数约束 | +| 部分样本不符合 PID | 使用残差模型校正 | + +#### 多任务学习策略 + +**辅助任务选择：** +- **Delta Pressure**：预测 P[t] - P[t-1]（最常用） +- **压力分类**：同时预测压力范围（辅助回归） +- **阶段预测**：预测吸气/呼气阶段（多任务） + +**损失权重调优：** +```python +# 网格搜索最佳权重 +for delta_weight in [0.1, 0.15, 0.2, 0.25, 0.3]: + loss = multi_task_loss(pressure_pred, delta_pred, pressure_true, delta_weight) + # 验证集评估 + val_mae = evaluate(val_loader, delta_weight) + print(f'delta_weight={delta_weight}: val_mae={val_mae:.4f}') +``` + +**最佳实践：** +| 技巧 | 说明 | +|------|------| +| 渐进式训练 | 先训练主任务，再加入辅助任务 | +| 权重衰减 | 逐渐降低辅助任务权重 | +| 多个辅助任务 | 可组合多个辅助任务 | +| 早停基于主任务 | 验证集只看主任务性能 | + +#### 交叉验证策略 + +**Group K-Fold：** +```python +from sklearn.model_selection import GroupKFold + +# 确保同一 breath 的样本不分散 +gkf = GroupKFold(n_splits=5) + +for fold, (train_idx, val_idx) in enumerate(gkf.split(X, y, groups=df['breath_id'])): + print(f'Fold {fold}: Train={len(train_idx)}, Val={len(val_idx)}') + + X_train, X_val = X[train_idx], X[val_idx] + y_train, y_val = y[train_idx], y[val_idx] + + # 训练模型 + model = train_model(X_train, y_train) +``` + +**时间序列分割：** +```python +from sklearn.model_selection import TimeSeriesSplit + +# 按时间顺序分割 +tscv = TimeSeriesSplit(n_splits=5) + +for fold, (train_idx, val_idx) in enumerate(tscv.split(X)): + # 训练集在验证集之前 + X_train, X_val = X[train_idx], X[val_idx] + y_train, y_val = y[train_idx], y[val_idx] +``` + +#### 模型集成策略 + +**集成方法：** +| 方法 | 使用排名 | 说明 | +|------|---------|------| +| **简单平均** | 所有排名 | 最常用，稳定可靠 | +| **加权平均** | 部分排名 | 需要验证集调优权重 | +| **Stacking** | 高排名 | 用元模型学习组合 | +| **不同架构** | 1st, 3rd | LSTM + Transformer + CNN | + +**集成代码：** +```python +def ensemble_predictions(predictions_list, weights=None): + """ + 集成多个模型的预测 + + Args: + predictions_list: 预测列表 [(n_samples, n_steps), ...] + weights: 权重列表，None 表示简单平均 + + Returns: + ensemble_pred: 集成预测 + """ + if weights is None: + # 简单平均 + ensemble_pred = np.mean(predictions_list, axis=0) + else: + # 加权平均 + ensemble_pred = np.average(predictions_list, axis=0, weights=weights) + + return ensemble_pred + +# 使用示例 +# pred1 = model1.predict(X_val) +# pred2 = model2.predict(X_val) +# pred3 = model3.predict(X_val) +# +# # 简单平均 +# ensemble = ensemble_predictions([pred1, pred2, pred3]) +# +# # 加权平均 +# weights = [0.3, 0.3, 0.4] +# ensemble = ensemble_predictions([pred1, pred2, pred3], weights) +``` + +#### 常见陷阱和注意事项 + +| 陷阱 | 说明 | 解决方案 | +|------|------|---------| +| **过拟合 PID 规律** | 模型只对 PID 样本有效 | 加入真实呼吸样本训练 | +| **数据泄露** | 使用未来信息 | 严格按时间切分 | +| **多任务权重不当** | 辅助任务干扰主任务 | 调优权重或渐进训练 | +| **集成过拟合** | 集成太多模型 | 3-5 个模型即可 | +| **特征工程过度** | 特征比样本还多 | 特征选择和降维 | +| **验证集策略错误** | 同一 breath 分散到训练和验证 | Group K-Fold | + +--- + +## Metadata + +| Source | Date | Tags | +|--------|------|------| +| [HMS - Harmful Brain Activity Classification](https://www.kaggle.com/competitions/hms-harmful-brain-activity-classification) | 2025-01-22 | EEG, 分类, CWT, Entmax, 2-Stage Training, KL-Divergence | +| [Child Mind Institute - Detect Sleep States](https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states) | 2025-01-22 | 睡眠检测, 事件检测, 两阶段建模, 后处理优化, 多tolerance AP | +| [Child Mind Institute - Detect Behavior with Sensor Data](https://www.kaggle.com/competitions/cmi-detect-behavior-with-sensor-data) | 2025-01-22 | 多模态时序, IMU+TOF+THM, 行为识别, 阶段感知Attention, 匈牙利算法 | +| [BirdCLEF 2024](https://www.kaggle.com/competitions/birdclef-2024) | 2026-01-23 | 音频分类, 生物声学, Statistics T过滤, Google Classifier预标注, CE Loss, Sigmoid推理, Min Ensemble, Checkpoint Soup, 伪标签迭代, 120分钟推理限制 | +| [BirdCLEF+ 2025](https://www.kaggle.com/competitions/birdclef-2025) | 2026-01-22 | 音频分类, 生物声学, Noisy Student, 自蒸馏, SED模型, 伪标签, Mel-Spectrogram, Soft AUC Loss, 90分钟推理限制 | +| [Google Brain - Ventilator Pressure Prediction](https://www.kaggle.com/c/ventilator-pressure-prediction) | 2026-01-23 | 时序回归, PID逆向, 多任务学习, Delta Pressure, LSTM+Transformer, MAE, 2,605队伍 | +| [Cornell Birdcall Identification (BirdCLEF 2020)](https://www.kaggle.com/competitions/birdsong-recognition) | 2026-01-23 | 音频分类, 生物声学, ResNeSt, Attention Pooling, Mel-Spectrogram, Weak Supervision, GAN伪标签, Ensemble, F1-Score, 1,390队伍 | +| [BirdCLEF 2021 - Birdcall Identification](https://www.kaggle.com/competitions/birdclef-2021) | 2026-01-23 | 音频分类, 生物声学, PANNs, 弱监督, Mixup, SpecAugment, Attention Mechanism, F1-Score, 1,700队伍 | +| [BirdCLEF 2022 - Endangered Bird Sounds](https://www.kaggle.com/competitions/birdclef-2022) | 2026-01-23 | 音频分类, 濒危物种, BirdNet, Perch, SED, 多尺度输入, AND规则, Framewise预测, F1-Score, 1,600队伍 | +| [Rainforest Connection Species Audio Detection 2021](https://www.kaggle.com/competitions/rfcx-species-audio-detection) | 2026-01-23 | 音频检测, 生物声学, LWLRAP, Mel-Spectrogram as Image, ResNeSt, EfficientNet, ImageNet预训练, 2,200队伍 | +| [AMP®-Parkinson's Disease Progression Prediction](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction) | 2026-01-23 | 表格时序回归, 蛋白质数据, Gradient Boosting, SMAPE, XGBoost/LightGBM, 2,500队伍 | + +--- + +## Cornell Birdcall Identification (BirdCLEF 2020) + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology +- **目标**：识别音频录音中的鸟类叫声（多标签音频分类） +- **应用场景**：鸟类种群监测，生物声学研究，生态系统保护 +- **数据集规模**： + - 训练音频：2,000+ 段录音，涵盖 264 种鸟类 + - 测试音频：约 200 段连续录音（soundscape） + - 采样率： varied (通常 44.1kHz 或 48kHz) +- **评估指标**：micro-averaged F1-score（需要预测鸟类在 5 秒时间窗口内的出现） +- **最终排名**： + - 1st Place: Ryan Wong - F1 ~0.71 + - 2nd Place: niw + - 3rd Place: TheoViel + - 总参赛队伍：1,390 支 + +### 前排方案详细技术分析 + +#### 1st Place - ResNeSt + Attention Pooling + Large Ensemble (Ryan Wong) + +核心技巧： +- **ResNeSt Split-Attention Network**：使用 ResNeSt-50 作为主干网络 +- **Attention Pooling**：替代传统的全局平均池化 +- **Large Voting Ensemble**：13 模型投票集成，需要至少 4 票 +- **Mel-Spectrogram Preprocessing**：对数 Mel 频谱特征 +- **数据增强**：粉红噪声、高斯噪声、音量调整 +- **Multi-Scale Training**：不同音频片段长度 + +实现细节： +- **音频预处理**： + - 重采样到 32kHz 或 44.1kHz + - 使用短时傅里叶变换（STFT）计算 Mel-spectrogram + - 对数尺度转换：log(1 + mel) + - 时间维度：5 秒窗口 +- **模型架构**： + - ResNeSt-50 (Split-Attention variants of ResNet) + - 在 ImageNet 上预训练 + - 替换最后的全连接层为 Attention Pooling + - 输出层：264 类二分类（多标签） +- **Attention Pooling 实现**： + ```python + class AttentionPooling(nn.Module): + def __init__(self, input_dim, hidden_dim=128): + super().__init__() + self.attention = nn.Sequential( + nn.Linear(input_dim, hidden_dim), + nn.Tanh(), + nn.Linear(hidden_dim, 1) + ) + + def forward(self, x): + # x: (batch, time, features) + weights = F.softmax(self.attention(x), dim=1) + return (x * weights).sum(dim=1) + ``` +- **集成策略**： + - 13 个模型的投票集成 + - 每个预测需要至少 4 票才认为鸟类存在 + - 基于 LB 分数选择模型 + - 不同 checkpoint 和数据增强配置 +- **数据增强**： + - Mixup（混合增强） + - 背景噪声添加 + - 音高变换（pitch shifting） + - 时间拉伸（time stretching） +- **训练配置**： + - Loss：Binary Cross-Entropy + - Optimizer：AdamW + - Learning Rate：1e-3（带 cosine annealing） + - Batch Size：32 + - Epochs：~30 + +#### 2nd Place - Efficient Ensemble with Strong Data Augmentation (niw) + +核心技巧： +- **ResNet50-based Models**：多个 ResNet50 变体 +- **Aggressive Data Augmentation**：激进的音频增强 +- **Spectral Features**：多种频谱特征组合 +- **Prediction Thresholding**：预测阈值优化 +- **Cross-Validation Ensemble**：交叉验证集成 + +实现细节： +- **特征工程**： + - Mel-spectrogram（128 Mel bins） + - MFCC（Mel-Frequency Cepstral Coefficients） + - Chroma features + - Spectral contrast +- **模型变体**： + - ResNet50（预训练） + - EfficientNet-B0 + - DenseNet-121 +- **增强策略**： + - 时间遮罩（SpecAugment Time Masking） + - 频率遮罩（Frequency Masking） + - 添加背景噪声 + - 音量随机化 +- **后处理**： + - 类别特定的阈值优化 + - 时间平滑（temporal smoothing） + - 最小持续时间过滤 + +#### 3rd Place - Simple yet Effective Approach (TheoViel) + +核心技巧： +- **Pre-trained ResNeSt**：使用预训练的 ResNeSt 模型 +- **Mel-Spectrogram Input**：标准 Mel 频谱 +- **Strong Baseline**：简洁但强大的基线模型 +- **Moderate Ensemble**：中等规模集成 +- **Careful Validation**：仔细的验证策略 + +实现细节： +- **音频处理**： + - 重采样到 44.1kHz + - 5 秒固定窗口 + - 128 Mel bins + - 对数幅度压缩 +- **模型架构**： + - ResNeSt50（预训练） + - Global Average Pooling + - Sigmoid 激活 +- **训练策略**： + - 5-fold 交叉验证 + - Early stopping + - Learning rate scheduling +- **集成方法**： + - 5-7 个模型的平均 + - 不同随机种子 + +#### 4th Place - Logmels Spectral Features (dimabert & ususani) + +核心技巧： +- **Logmels Features**：对数 Mel 频谱作为主要特征 +- **Audio Normalization**：音频标准化处理 +- **32kHz Resampling**：统一采样率 +- **CNN Ensemble**：多个 CNN 模型集成 + +实现细节： +- **音频预处理**： + - 重采样到 32,000 Hz + - 音频归一化（RMS normalization） + - 固定长度窗口 +- **特征提取**： + - Logmels（对数 Mel-spectrogram） + - 128 Mel bins + - 时间帧数：约 500 帧/5秒 +- **模型选择**： + - ResNet50 + - ResNeSt50 + - EfficientNet +- **Loss Function**： + - Binary Cross-Entropy + - Label Smoothing + +#### 5th Place - Dual Approach with Different Architectures (Kramarenko Vladislav) + +核心技巧： +- **Multiple Approaches**：尝试了两种不同的方法 +- **Different CNN Architectures**：不同的 CNN 架构 +- **Feature Engineering**：特征工程优化 +- **Prediction Blending**：预测结果混合 + +实现细节： +- **方法 1**：ResNet50 + Mel-spectrogram +- **方法 2**：Custom CNN + MFCC features +- **最终集成**：两种方法的加权平均 + +#### 6th Place - Sound Event Detection with Attention (Deep) + +核心技巧： +- **SED Framework**：声音事件检测框架 +- **ResNeSt50 Encoder**：ResNeSt50 编码器 +- **Attention Mechanism**：注意力机制 +- **Strong Augmentation**：强数据增强 +- **Post-processing**：后处理优化 + +实现细节： +- **模型架构**： + - ResNeSt50 作为特征提取器 + - Temporal Attention Module + - Multi-head Attention +- **训练技巧**： + - Mixup augmentation + - CutMix + - SpecAugment + +#### 7th Place - Three Geese and a GAN (CPJKU) + +核心技巧： +- **Weak Supervision**：弱监督学习 +- **Generative Augmentation**：使用 GAN 生成增强数据 +- **Pseudo-labeling**：伪标签策略 +- **Strong Single Model**：强大的单模型 +- **Note**：该方案可修改后达到 1-2 名成绩 + +实现细节： +- **GAN-based Augmentation**： + - 使用生成对抗网络生成合成音频 + - 增加稀有鸟类的样本 + - 条件 GAN（conditional GAN） +- **弱监督策略**： + - 利用未标注数据 + - 自训练（self-training） + - 伪标签迭代优化 +- **模型架构**： + - Modified ResNet + - Attention pooling + - Multi-task learning +- **训练流程**： + - Stage 1: 在标注数据上训练 + - Stage 2: 生成伪标签 + - Stage 3: 在标注+伪标签数据上微调 + +#### 17th Place - File-level Post-processing + +核心技巧： +- **File-level Aggregation**：文件级别聚合 +- **Temporal Smoothing**：时间平滑 +- **Threshold Optimization**：阈值优化 +- **Ensemble Diversification**：集成多样化 + +实现细节： +- **后处理策略**： + - 同一文件内的预测平滑 + - 移除短于阈值的检测 + - 类别特定的阈值 +- **集成方法**： + - 多个 checkpoint 平均 + - 不同架构的集成 + +### 代码模板 + +#### Mel-Spectrogram 特征提取 +```python +import torch +import torch.nn as nn +import torchaudio +import numpy as np + +class MelSpectrogramExtractor: + def __init__(self, sample_rate=32000, n_mels=128, n_fft=2048, hop_length=512): + self.sample_rate = sample_rate + self.n_mels = n_mels + self.n_fft = n_fft + self.hop_length = hop_length + + # Mel-spectrogram transform + self.mel_transform = torchaudio.transforms.MelSpectrogram( + sample_rate=sample_rate, + n_fft=n_fft, + hop_length=hop_length, + n_mels=n_mels, + f_min=0, + f_max=16000 + ) + + # Amplitude to dB + self.amplitude_to_db = torchaudio.transforms.AmplitudeToDB() + + def extract(self, waveform): + """提取 Mel-spectrogram 特征""" + # Compute mel-spectrogram + mel_spec = self.mel_transform(waveform) + + # Convert to dB scale + mel_spec_db = self.amplitude_to_db(mel_spec) + + # Normalize to [0, 1] + mel_spec_norm = (mel_spec_db - mel_spec_db.min()) / (mel_spec_db.max() - mel_spec_db.min() + 1e-8) + + return mel_spec_norm + +# 使用示例 +extractor = MelSpectrogramExtractor(sample_rate=32000, n_mels=128) +waveform, sr = torchaudio.load("bird_audio.wav") +if sr != 32000: + resampler = torchaudio.transforms.Resample(sr, 32000) + waveform = resampler(waveform) +mel_spec = extractor.extract(waveform) +``` + +#### ResNeSt + Attention Pooling 模型 +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class AttentionPooling2d(nn.Module): + """2D Attention Pooling for spectrograms""" + def __init__(self, in_channels, hidden_dim=128): + super().__init__() + self.attention = nn.Sequential( + nn.Conv2d(in_channels, hidden_dim, kernel_size=1), + nn.BatchNorm2d(hidden_dim), + nn.Tanh(), + nn.Conv2d(hidden_dim, 1, kernel_size=1) + ) + + def forward(self, x): + # x: (batch, channels, time, freq) + attn_weights = F.softmax(self.attention(x), dim=(2, 3)) + return (x * attn_weights).sum(dim=(2, 3)) + +class BirdcallClassifier(nn.Module): + def __init__(self, num_classes=264, pretrained=True): + super().__init__() + + # ResNeSt backbone (需要安装 resnest 库) + from resnest.torch import resnest50 + + self.backbone = resnest50(pretrained=pretrained) + + # 替换最后的全连接层 + self.backbone.fc = nn.Identity() + + # Attention pooling + self.attention_pool = AttentionPooling2d(2048, hidden_dim=128) + + # Classifier head + self.classifier = nn.Sequential( + nn.Dropout(0.3), + nn.Linear(2048, 512), + nn.ReLU(), + nn.Dropout(0.2), + nn.Linear(512, num_classes) + ) + + def forward(self, x): + # x: (batch, channels, time, freq) - Mel-spectrogram + features = self.backbone(x) # (batch, 2048, H, W) + pooled = self.attention_pool(features) # (batch, 2048) + logits = self.classifier(pooled) # (batch, num_classes) + return logits + +# 使用示例 +model = BirdcallClassifier(num_classes=264, pretrained=True) +mel_spec_batch = torch.randn(8, 3, 224, 512) # (batch, channels, freq, time) +logits = model(mel_spec_batch) +probs = torch.sigmoid(logits) # Multi-label prediction +``` + +#### 数据增强 +```python +import torch +import torchaudio +import random + +class BirdcallAugmentation: + def __init__(self, sample_rate=32000): + self.sample_rate = sample_rate + + def add_noise(self, waveform, noise_level=0.005): + """添加高斯噪声""" + noise = torch.randn_like(waveform) * noise_level + return waveform + noise + + def add_pink_noise(self, waveform, alpha=1): + """添加粉红噪声（1/f 噪声）""" + # 简化的粉红噪声生成 + white_noise = torch.randn_like(waveform) + # 在频域应用 1/f 滤波 + freq_noise = torch.fft.rfft(white_noise) + freqs = torch.fft.rfftfreq(waveform.shape[-1], 1/self.sample_rate) + pink_filter = 1 / (freqs[1:] + 1e-8) ** alpha + freq_noise[:, 1:] *= pink_filter + pink_noise = torch.fft.irfft(freq_noise, n=waveform.shape[-1]) + return waveform + pink_noise * 0.01 + + def time_mask(self, mel_spec, max_mask_pct=0.1): + """时间遮罩（SpecAugment）""" + batch, channels, time, freq = mel_spec.shape + mask_len = int(time * max_mask_pct) + t = random.randint(0, mask_len) + t0 = random.randint(0, time - t) + mel_spec[:, :, t0:t0+t, :] = 0 + return mel_spec + + def freq_mask(self, mel_spec, max_mask_pct=0.1): + """频率遮罩""" + batch, channels, time, freq = mel_spec.shape + mask_len = int(freq * max_mask_pct) + f = random.randint(0, mask_len) + f0 = random.randint(0, freq - f) + mel_spec[:, :, :, f0:f0+f] = 0 + return mel_spec + + def pitch_shift(self, waveform, shift=2.0): + """音高变换""" + # 简化实现：使用 resampling + # 实际应用中可用更高级的库如 pydub 或 librosa + n_steps = int(shift * 10) + resampler = torchaudio.transforms.Resample( + self.sample_rate, + int(self.sample_rate * (1 + shift * 0.1)) + ) + return resampler(waveform) + + def gain(self, waveform, min_gain=0.5, max_gain=1.5): + """音量调整""" + gain = random.uniform(min_gain, max_gain) + return waveform * gain + +# 使用示例 +augmentation = BirdcallAugmentation(sample_rate=32000) +waveform, sr = torchaudio.load("bird_audio.wav") + +# 应用增强 +waveform_aug = augmentation.add_noise(waveform) +waveform_aug = augmentation.gain(waveform_aug) +``` + +#### 训练循环 +```python +import torch +import torch.nn as nn +from torch.utils.data import DataLoader + +def train_epoch(model, dataloader, criterion, optimizer, device, augmentation=None): + model.train() + total_loss = 0 + + for batch in dataloader: + waveforms, labels = batch + waveforms = waveforms.to(device) + labels = labels.to(device) + + # 数据增强（训练时） + if augmentation is not None: + # 在 Mel-spectrogram 上应用增强 + pass + + # 前向传播 + logits = model(waveforms) + loss = criterion(logits, labels.float()) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + total_loss += loss.item() + + return total_loss / len(dataloader) + +def train_model(model, train_loader, val_loader, num_epochs=30, device='cuda'): + criterion = nn.BCEWithLogitsLoss() + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3, weight_decay=1e-4) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_epochs) + + best_val_score = 0 + + for epoch in range(num_epochs): + # 训练 + train_loss = train_epoch(model, train_loader, criterion, optimizer, device) + + # 验证 + val_score, val_loss = validate(model, val_loader, criterion, device) + + # 学习率调度 + scheduler.step() + + print(f"Epoch {epoch+1}/{num_epochs}") + print(f"Train Loss: {train_loss:.4f}") + print(f"Val Loss: {val_loss:.4f}") + print(f"Val F1: {val_score:.4f}") + + # 保存最佳模型 + if val_score > best_val_score: + best_val_score = val_score + torch.save(model.state_dict(), 'best_model.pth') + + return model +``` + +#### 集成与后处理 +```python +import numpy as np +import pandas as pd + +class EnsemblePredictor: + def __init__(self, models, threshold=0.5, min_votes=4): + """ + Args: + models: 模型列表 + threshold: 二值化阈值 + min_votes: 最小投票数（如 1st place 用 4 票） + """ + self.models = models + self.threshold = threshold + self.min_votes = min_votes + + def predict(self, mel_spec_batch): + """集成预测""" + all_predictions = [] + + for model in self.models: + model.eval() + with torch.no_grad(): + logits = model(mel_spec_batch) + probs = torch.sigmoid(logits) + binary = (probs > self.threshold).float() + all_predictions.append(binary.cpu().numpy()) + + # 投票集成 + all_predictions = np.array(all_predictions) # (n_models, batch, num_classes) + votes = all_predictions.sum(axis=0) # (batch, num_classes) + + # 需要至少 min_votes 票 + final_pred = (votes >= self.min_votes).astype(int) + + return final_pred + +def temporal_post_process(predictions, window_size=3, min_duration=3): + """ + 时间后处理 + + Args: + predictions: (time_steps, num_classes) 二值预测 + window_size: 平滑窗口大小 + min_duration: 最小持续时间（时间步） + """ + smoothed = predictions.copy() + + # 时间平滑（多数投票） + for i in range(predictions.shape[0]): + start = max(0, i - window_size // 2) + end = min(predictions.shape[0], i + window_size // 2 + 1) + window = predictions[start:end] + smoothed[i] = (window.sum(axis=0) > window_size // 2).astype(int) + + # 移除短于阈值的检测 + final = smoothed.copy() + for c in range(predictions.shape[1]): + col = smoothed[:, c] + # 找连续段 + changes = np.diff(col, prepend=0, append=0) + starts = np.where(changes == 1)[0] + ends = np.where(changes == -1)[0] + + for s, e in zip(starts, ends): + if e - s < min_duration: + final[s:e, c] = 0 + + return final + +def create_submission(predictions, audio_ids, bird_species): + """ + 创建提交文件 + + Args: + predictions: (n_samples, num_classes) 二值预测 + audio_ids: 音频文件 ID 列表 + bird_species: 鸟类名称列表 + """ + rows = [] + for audio_id, pred in zip(audio_ids, predictions): + active_birds = [bird_species[i] for i, p in enumerate(pred) if p == 1] + if active_birds: + rows.append({ + 'row_id': f"{audio_id}", + 'birds': ' '.join(active_birds) + }) + else: + rows.append({ + 'row_id': f"{audio_id}", + 'birds': 'nocall' + }) + + submission = pd.DataFrame(rows) + return submission +``` + +### 最佳实践 + +1. **音频预处理标准化**： + - 统一采样率（32kHz 或 44.1kHz） + - 使用高质量的 Mel-spectrogram 参数（n_fft=2048, hop_length=512, n_mels=128） + - 对数幅度压缩（log 或 dB 转换） + +2. **模型选择**： + - ResNeSt 表现最佳（split-attention 机制） + - 在 ImageNet 上预训练的模型迁移效果好 + - Attention Pooling 优于 Global Average Pooling + +3. **数据增强策略**： + - SpecAugment（时间/频率遮罩）是必需的 + - Mixup 有助于提高泛化能力 + - 添加背景噪声提高鲁棒性 + - GAN 生成增强数据可以提升稀有类别性能 + +4. **集成方法**： + - 投票集成优于平均集成 + - 设置最小投票数阈值（如 4 票）可减少误报 + - 使用不同 checkpoint 和随机种子增加多样性 + +5. **后处理优化**： + - 时间平滑可以减少闪烁 + - 移除短于阈值的检测 + - 类别特定的阈值优化 + +6. **验证策略**： + - 使用 5-fold 交叉验证 + - 仔细设计验证集以反映测试集分布 + - 监控 micro-F1 分数 + +7. **训练技巧**： + - 使用 AdamW 优化器 + - Cosine annealing 学习率调度 + - Binary Cross-Entropy Loss + - Label smoothing 有助于正则化 + +8. **常见陷阱**： + - 避免过度拟合训练集的音频特征 + - 注意类别不平衡问题 + - 验证集和测试集可能有不同的分布 + - 推理时间限制（如果有）需要考虑模型效率 + +--- + +## BirdCLEF 2021 - Birdcall Identification + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology + LifeCLEF +- **目标**：识别音频录音中的鸟类叫声（弱监督多标签音频分类） +- **应用场景**：鸟类种群监测，生物声学研究，生态系统保护 +- **数据集规模**： + - 训练音频：约 3,900 段录音，涵盖 397 种鸟类 + - 测试音频：约 2,600 段连续录音（soundscape） + - 弱监督标注：只有音频级别的标签，无时间戳 +- **评估指标**：micro-averaged F1-score +- **最终排名**： + - 1st Place: DR (kami634) - 弱监督方案 + - 2nd Place: Christof Henkel + - 3rd Place: shiro + - 总参赛队伍：约 1,700+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Weak Supervision with PANNs (DR) + +核心技巧： +- **Pre-trained Audio Neural Networks (PANNs)**：使用预训练的音频神经网络 +- **Weak Supervision Strategy**：弱监督学习策略 +- **Attention Mechanisms**：自注意力机制用于音频分类 +- **Spectrogram-based Features**：基于频谱图的特征 +- **Model Ensemble**：多模型集成 +- **Post-processing**：后处理优化 + +实现细节： +- **基础模型**： + - 使用预训练的 PANNs (Pre-trained Audio Neural Networks) + - 包括 CNN14, CNN10, ResNet38 等架构 + - 在 AudioSet 上预训练 + - 迁移学习到鸟类叫声分类 +- **特征提取**： + - Mel-spectrogram（64/128 Mel bins） + - 对数幅度压缩 + - 多尺度时间窗口 +- **弱监督策略**： + - 仅使用音频级别的标签（无时间戳） + - 通过注意力机制定位关键区域 + - 多实例学习（Multiple Instance Learning） +- **模型架构**： + - CNN-based 特征提取器 + - Self-Attention 层 + - Global Pooling + 分类器 +- **集成方法**： + - 多个 PANNs 模型集成 + - 不同架构和预训练权重 + - 投票或平均策略 +- **数据增强**： + - Mixup + - SpecAugment + - 背景噪声添加 +- **后处理**： + - 时间平滑 + - 阈值优化 + - 类别特定的后处理 + +#### 2nd Place - New Baseline with Strong Augmentation (Christof Henkel) + +核心技巧： +- **New Baseline Architecture**：新颖的基线架构 +- **Mixup Augmentation**：Mixup 数据增强 +- **Background Noise Addition**：背景噪声添加 +- **Pseudo-labeling**：伪标签策略 +- **5-second Segment Inference**：5秒片段推理 +- **Strong Single Model**：强大的单模型 + +实现细节： +- **模型选择**： + - ResNet50 / ResNeSt50 + - EfficientNet variants + - DenseNet-based models +- **音频预处理**： + - 重采样到 32kHz + - Mel-spectrogram 提取 + - 标准化处理 +- **增强策略**： + - Mixup（强制使用） + - 时间遮罩（Time Masking） + - 频率遮罩（Frequency Masking） + - 背景噪声混合 +- **伪标签**： + - 使用训练好的模型预测未标注数据 + - 高置信度预测作为伪标签 + - 迭代训练 +- **训练配置**： + - Binary Cross-Entropy Loss + - AdamW 优化器 + - Cosine 学习率衰减 + - 5-fold 交叉验证 +- **推理策略**： + - 5秒滑动窗口 + - 窗口间有重叠 + - 多个窗口预测聚合 + +#### 3rd Place - Ensemble with Multiple Approaches (shiro) + +核心技巧： +- **Multiple Model Families**：多族模型集成 +- **Spectral Feature Engineering**：频谱特征工程 +- **Cross-Validation Strategy**：交叉验证策略 +- **Post-processing Pipeline**：后处理流程 +- **Attention-based Models**：基于注意力的模型 + +实现细节： +- **模型选择**： + - ResNet variants + - DenseNet variants + - EfficientNet variants + - Custom CNN architectures +- **特征多样性**： + - 不同 Mel-spectrogram 参数 + - MFCC features + - Chroma features + - Spectral contrast +- **训练策略**： + - 5-fold 交叉验证 + - Early stopping + - Learning rate scheduling +- **集成方法**： + - 加权平均 + - 基于验证集权重优化 + - 不同 checkpoint 集成 + +#### 4th Place - Third Time's The Charm (tattaka) + +核心技巧： +- **Iterative Improvement**：迭代改进策略 +- **Strong Data Augmentation**：强数据增强 +- **Spectrogram Preprocessing**：频谱预处理优化 +- **Model Architecture Search**：模型架构搜索 +- **Ensemble Optimization**：集成优化 + +实现细节： +- **音频处理**： + - 高质量 Mel-spectrogram 参数调优 + - 多种时间窗口长度 + - 频率范围选择 +- **模型架构**： + - ResNet50 + - ResNeSt50 + - DenseNet-121 +- **增强组合**： + - SpecAugment（多种参数） + - Mixup + CutMix + - 噪声增强 + - 音高变换 +- **训练技巧**： + - 渐进式训练 + - 迭代优化 + - A/B 测试不同策略 + +#### 5th Place - Dual Approach Blending (Kramarenko Vladislav) + +核心技巧： +- **Multiple Approaches**：多种方法尝试 +- **Different Feature Sets**：不同特征集 +- **Blending Strategy**：混合策略 +- **Spectral Analysis**：频谱分析 + +实现细节： +- **方法 1**：CNN + Mel-spectrogram +- **方法 2**：Gradient Boosting + 手工特征 +- **最终集成**：两种方法加权混合 + +#### 6th-10th Place 概述 + +**常见技术**： +- PANNs 预训练模型广泛使用 +- SpecAugment 成为标准增强 +- Mixup 几乎所有前排方案使用 +- 5-fold 交叉验证是标准配置 +- Mel-spectrogram 是主流特征 + +**关键技术点**： +- **弱监督处理**：使用注意力机制定位音频中的鸟类叫声 +- **数据增强**：SpecAugment + Mixup + 背景噪声 +- **模型集成**：多架构、多 checkpoint 集成 +- **后处理**：时间平滑、阈值优化、类别特定处理 + +### 代码模板 + +#### PANNs 模型加载和使用 +```python +import torch +import torch.nn as nn +# 需要安装: pip install torchlibrosa +from torchlibrosa.stft import Spectrogram, LogmelFilterBank + +class PANNsCNN14(nn.Module): + """ + 基于 PANNs CNN14 的模型 + 参考: https://github.com/qiuqiangkong/audioset_tagging_cnn + """ + def __init__(self, sample_rate=32000, window_size=512, hop_size=320, + mel_bins=64, fmin=50, fmax=14000, num_classes=397): + super().__init__() + + window = 'hann' + center = True + pad_mode = 'reflect' + ref = 1.0 + amin = 1e-10 + top_db = None + + # Spectrogram extractor + self.spectrogram_extractor = Spectrogram( + n_fft=window_size, + hop_length=hop_size, + win_length=window_size, + window=window, + center=center, + pad_mode=pad_mode, + freeze_parameters=True) + + # Logmel feature extractor + self.logmel_extractor = LogmelFilterBank( + sr=sample_rate, + n_fft=window_size, + n_mels=mel_bins, + fmin=fmin, + fmax=fmax, + ref=ref, + amin=amin, + top_db=top_db, + freeze_parameters=True) + + # SpecAugment (训练时使用) + self.spec_augment = SpecAugmentation( + time_drop_width=64, + time_stripes_num=2, + freq_drop_width=8, + freq_stripes_num=2) + + # CNN14 backbone + self.bn0 = nn.BatchNorm2d(mel_bins) + + self.conv_block1 = ConvBlock(in_channels=1, out_channels=64) + self.conv_block2 = ConvBlock(in_channels=64, out_channels=128) + self.conv_block3 = ConvBlock(in_channels=128, out_channels=256) + self.conv_block4 = ConvBlock(in_channels=256, out_channels=512) + self.conv_block5 = ConvBlock(in_channels=512, out_channels=1024) + self.conv_block6 = ConvBlock(in_channels=1024, out_channels=2048) + + self.fc1 = nn.Linear(2048, 2048, bias=True) + self.fc_audioset = nn.Linear(2048, num_classes, bias=True) + + self.init_weight() + + def init_weight(self): + init_bn(self.bn0) + init_layer(self.fc1) + init_layer(self.fc_audioset) + + def forward(self, input, mixup_lambda=None, device='cuda'): + """ + Args: + input: (batch_size, time_samples) + Returns: + output: (batch_size, num_classes) + """ + # Spectrogram + x = self.spectrogram_extractor(input) # (batch, 1, time, freq) + x = self.logmel_extractor(x) # (batch, 1, time, mel_bins) + + # BN + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + + # SpecAugment (仅训练时) + if self.training: + x = self.spec_augment(x) + + # CNN blocks + x = self.conv_block1(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block2(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block3(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block4(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block5(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block6(x, pool_size=(1, 1), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + # Global pooling + x = torch.mean(x, dim=3) # (batch, channels, time) + + (x1, _) = torch.max(x, dim=2) # (batch, channels) + x2 = torch.mean(x, dim=2) # (batch, channels) + x = x1 + x2 # (batch, channels) + + x = F.dropout(x, p=0.5, training=self.training) + x = F.relu_(self.fc1(x)) + embedding = F.dropout(x, p=0.5, training=self.training) + clipwise_output = torch.sigmoid(self.fc_audioset(x)) + + return clipwise_output + + def load_from_pretrained(self, pretrained_path): + """加载预训练权重""" + checkpoint = torch.load(pretrained_path, map_location='cpu') + model_state = self.state_dict() + pretrained_state = checkpoint['model'] + + # 过滤不匹配的键 + pretrained_state = {k: v for k, v in pretrained_state.items() + if k in model_state and v.shape == model_state[k].shape} + + model_state.update(pretrained_state) + self.load_state_dict(model_state) + print(f"Loaded pretrained weights from {pretrained_path}") + +class ConvBlock(nn.Module): + def __init__(self, in_channels, out_channels): + super().__init__() + + self.conv1 = nn.Conv2d(in_channels=in_channels, + out_channels=out_channels, + kernel_size=(3, 3), stride=(1, 1), + padding=(1, 1), bias=False) + self.conv2 = nn.Conv2d(in_channels=out_channels, + out_channels=out_channels, + kernel_size=(3, 3), stride=(1, 1), + padding=(1, 1), bias=False) + self.bn1 = nn.BatchNorm2d(out_channels) + self.bn2 = nn.BatchNorm2d(out_channels) + + self.init_weight() + + def init_weight(self): + init_bn(self.bn1) + init_bn(self.bn2) + init_layer(self.conv1) + init_layer(self.conv2) + + def forward(self, input, pool_size=(2, 2), pool_type='avg'): + x = input + x = F.relu_(self.bn1(self.conv1(x))) + x = F.relu_(self.bn2(self.conv2(x))) + if pool_type == 'max': + x = F.max_pool2d(x, kernel_size=pool_size) + elif pool_type == 'avg': + x = F.avg_pool2d(x, kernel_size=pool_size) + elif pool_type == 'avg+max': + x1 = F.avg_pool2d(x, kernel_size=pool_size) + x2 = F.max_pool2d(x, kernel_size=pool_size) + x = x1 + x2 + else: + raise ValueError(f'Unknown pool type: {pool_type}') + return x + +class SpecAugmentation(nn.Module): + def __init__(self, time_drop_width, time_stripes_num, + freq_drop_width, freq_stripes_num): + super().__init__() + self.time_drop_width = time_drop_width + self.time_stripes_num = time_stripes_num + self.freq_drop_width = freq_drop_width + self.freq_stripes_num = freq_stripes_num + + def forward(self, x): + """x: (batch, channels, time, freq)""" + self._mask_along_axis(x, self.time_drop_width, + self.time_stripes_num, axis=2) + self._mask_along_axis(x, self.freq_drop_width, + self.freq_stripes_num, axis=3) + return x + + def _mask_along_axis(self, x, drop_width, stripes_num, axis): + """沿指定轴遮罩""" + for _ in range(stripes_num): + drop_width = int(drop_width) if isinstance(drop_width, int) else \ + int(drop_width * x.shape[axis]) + drop_start = int(torch.rand(1).item() * (x.shape[axis] - drop_width)) + + if axis == 2: # time axis + x[:, :, drop_start:drop_start + drop_width, :] = 0 + elif axis == 3: # freq axis + x[:, :, :, drop_start:drop_start + drop_width] = 0 + return x + +def init_layer(layer): + """Initialize a Linear or Convolutional layer.""" + nn.init.xavier_uniform_(layer.weight) + if hasattr(layer, 'bias'): + if layer.bias is not None: + layer.bias.data.fill_(0.) + +def init_bn(bn): + """Initialize a Batchnorm layer.""" + bn.bias.data.fill_(0.) + bn.weight.data.fill_(1.) + +# 使用示例 +model = PANNsCNN14( + sample_rate=32000, + window_size=512, + hop_size=320, + mel_bins=64, + num_classes=397 +) + +# 加载预训练权重（可选） +# model.load_from_pretrained('path/to/pretrained/CNN14.pth') + +waveform = torch.randn(4, 32000 * 5) # (batch, 5 seconds at 32kHz) +with torch.no_grad(): + output = model(waveform) +print(output.shape) # (4, 397) +``` + +#### Mixup 数据增强 +```python +import torch +import numpy as np + +def mixup_data(x, y, alpha=0.2): + """ + Mixup 数据增强 + + Args: + x: 输入数据 (batch_size, ...) + y: 标签 (batch_size, num_classes) + alpha: Beta 分布参数 + + Returns: + mixed_x: 混合后的输入 + y_a, y_b: 两个样本的标签 + lam: 混合系数 + """ + if alpha > 0: + lam = np.random.beta(alpha, alpha) + else: + lam = 1 + + batch_size = x.size(0) + index = torch.randperm(batch_size).to(x.device) + + mixed_x = lam * x + (1 - lam) * x[index, :] + y_a, y_b = y, y[index] + + return mixed_x, y_a, y_b, lam + +def mixup_criterion(criterion, pred, y_a, y_b, lam): + """Mixup 损失函数""" + return lam * criterion(pred, y_a) + (1 - lam) * criterion(pred, y_b) + +# 使用示例 +criterion = nn.BCEWithLogitsLoss() + +for batch_idx, (waveforms, labels) in enumerate(train_loader): + waveforms = waveforms.to(device) + labels = labels.to(device) + + # 应用 Mixup + waveforms_mixed, labels_a, labels_b, lam = mixup_data( + waveforms, labels, alpha=0.2 + ) + + # 前向传播 + outputs = model(waveforms_mixed) + + # 计算 Mixup 损失 + loss = mixup_criterion(criterion, outputs, labels_a, labels_b, lam) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() +``` + +#### 弱监督训练（音频级别标签） +```python +import torch +import torch.nn as nn +from torch.utils.data import Dataset + +class BirdcallWeakDataset(Dataset): + """ + 弱监督数据集：只有音频级别标签，无时间戳 + """ + def __init__(self, audio_files, labels, audio_transforms=None, + duration=5, sample_rate=32000): + self.audio_files = audio_files + self.labels = labels # Multi-hot labels: (num_samples, num_classes) + self.audio_transforms = audio_transforms + self.duration = duration + self.sample_rate = sample_rate + + def __len__(self): + return len(self.audio_files) + + def __getitem__(self, idx): + # 加载音频 + waveform, sr = torchaudio.load(self.audio_files[idx]) + + # 重采样 + if sr != self.sample_rate: + resampler = torchaudio.transforms.Resample(sr, self.sample_rate) + waveform = resampler(waveform) + + # 固定长度（裁剪或填充） + target_length = self.duration * self.sample_rate + if waveform.shape[1] > target_length: + # 随机裁剪 + start = torch.randint(0, waveform.shape[1] - target_length, (1,)).item() + waveform = waveform[:, start:start + target_length] + elif waveform.shape[1] < target_length: + # 填充 + padding = target_length - waveform.shape[1] + waveform = torch.nn.functional.pad(waveform, (0, padding)) + + # 获取标签（音频级别，多标签） + label = self.labels[idx] + + # 数据增强 + if self.audio_transforms is not None: + waveform = self.audio_transforms(waveform) + + return waveform, label + +class AttentionPooling(nn.Module): + """ + 注意力池化：用于弱监督学习，自动定位重要区域 + """ + def __init__(self, input_dim, hidden_dim=128): + super().__init__() + self.attention = nn.Sequential( + nn.Linear(input_dim, hidden_dim), + nn.Tanh(), + nn.Linear(hidden_dim, 1) + ) + + def forward(self, x): + """ + Args: + x: (batch, time_steps, features) + + Returns: + pooled: (batch, features) + weights: (batch, time_steps) - 可视化注意力 + """ + attn_weights = F.softmax(self.attention(x), dim=1) + pooled = (x * attn_weights).sum(dim=1) + return pooled, attn_weights + +class WeaklySupervisedBirdcallModel(nn.Module): + """ + 弱监督鸟类叫声分类模型 + """ + def __init__(self, num_classes=397, pretrained=True): + super().__init__() + + # 使用预训练的 PANNs CNN14 作为特征提取器 + self.backbone = PANNsCNN14(num_classes=num_classes, pretrained=pretrained) + + # 移除最后的分类层 + self.backbone.fc_audioset = nn.Identity() + + # 注意力池化 + feature_dim = 2048 # CNN14 的输出维度 + self.attention_pool = AttentionPooling(feature_dim, hidden_dim=128) + + # 分类器 + self.classifier = nn.Sequential( + nn.Dropout(0.3), + nn.Linear(feature_dim, 512), + nn.ReLU(), + nn.Dropout(0.2), + nn.Linear(512, num_classes) + ) + + def forward(self, x, return_attention=False): + """ + Args: + x: (batch, time_samples) + return_attention: 是否返回注意力权重用于可视化 + + Returns: + logits: (batch, num_classes) + attention_weights (optional): (batch, time_steps) + """ + # 提取特征（修改 backbone 以返回时间维度特征） + features = self.extract_features(x) # (batch, time_steps, feature_dim) + + # 注意力池化 + pooled, attn_weights = self.attention_pool(features) + + # 分类 + logits = self.classifier(pooled) + + if return_attention: + return logits, attn_weights + return logits + + def extract_features(self, x): + """ + 从 backbone 提取时间维度特征 + 这是一个简化版本，实际使用时需要修改 PANNsCNN14 + """ + # 简化实现：直接使用全局特征 + with torch.no_grad(): + features = self.backbone.fc1( + torch.mean(self.backbone.bn0( + self.backbone.logmel_extractor( + self.backbone.spectrogram_extractor(x) + ).transpose(1, 3) + ), dim=3) + ) + # 添加时间维度 + return features.unsqueeze(1) # (batch, 1, feature_dim) + +# 训练循环 +def train_weakly_supervised(model, dataloader, criterion, optimizer, device, use_mixup=True): + model.train() + + for waveforms, labels in dataloader: + waveforms = waveforms.to(device) + labels = labels.to(device).float() + + # Mixup 增强 + if use_mixup and np.random.rand() < 0.5: + waveforms, labels_a, labels_b, lam = mixup_data(waveforms, labels, alpha=0.2) + + # 前向传播 + logits = model(waveforms) + + # 计算损失 + if use_mixup and np.random.rand() < 0.5: + loss = mixup_criterion(criterion, logits, labels_a, labels_b, lam) + else: + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + +# 可视化注意力（用于理解模型关注的区域） +def visualize_attention(model, waveform, bird_name): + """可视化注意力权重，了解模型关注的音频区域""" + model.eval() + with torch.no_grad(): + logits, attention = model(waveform.unsqueeze(0), return_attention=True) + + # attention: (1, time_steps) + attention = attention.squeeze(0).cpu().numpy() + + import matplotlib.pyplot as plt + fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 6)) + + # 音频波形 + ax1.plot(waveform.cpu().numpy().T) + ax1.set_title(f'Audio Waveform - {bird_name}') + ax1.set_xlabel('Time') + ax1.set_ylabel('Amplitude') + + # 注意力权重 + ax2.plot(attention) + ax2.set_title('Attention Weights') + ax2.set_xlabel('Time Step') + ax2.set_ylabel('Attention Weight') + + plt.tight_layout() + plt.savefig('attention_visualization.png') + plt.close() +``` + +#### 5秒滑动窗口推理 +```python +import torch +import numpy as np + +def predict_with_sliding_window(model, audio_path, window_size=5, + hop_size=2.5, sample_rate=32000, + device='cuda'): + """ + 使用滑动窗口进行推理 + + Args: + model: 训练好的模型 + audio_path: 音频文件路径 + window_size: 窗口大小（秒） + hop_size: 跳跃大小（秒） + sample_rate: 采样率 + device: 设备 + + Returns: + predictions: (num_windows, num_classes) + timestamps: 窗口时间戳 + """ + model.eval() + + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + if sr != sample_rate: + resampler = torchaudio.transforms.Resample(sr, sample_rate) + waveform = resampler(waveform) + + waveform = waveform.mean(dim=0, keepdim=True) # 转为单声道 + + # 计算窗口参数 + window_samples = int(window_size * sample_rate) + hop_samples = int(hop_size * sample_rate) + + predictions = [] + timestamps = [] + + # 滑动窗口 + with torch.no_grad(): + for start in range(0, waveform.shape[1] - window_samples + 1, hop_samples): + end = start + window_samples + window = waveform[:, start:end].to(device) + + # 预测 + logits = model(window) + probs = torch.sigmoid(logits).cpu().numpy() + + predictions.append(probs[0]) + timestamps.append(start / sample_rate) + + predictions = np.array(predictions) + timestamps = np.array(timestamps) + + return predictions, timestamps + +def aggregate_predictions(predictions, threshold=0.5, min_duration=3): + """ + 聚合滑动窗口预测 + + Args: + predictions: (num_windows, num_classes) + threshold: 二值化阈值 + min_duration: 最小持续时间（窗口数） + + Returns: + final_pred: (num_windows, num_classes) 二值预测 + """ + binary_pred = (predictions > threshold).astype(int) + + # 时间平滑 + final_pred = binary_pred.copy() + for c in range(binary_pred.shape[1]): + col = binary_pred[:, c] + + # 移除短于阈值的检测 + changes = np.diff(col, prepend=0, append=0) + starts = np.where(changes == 1)[0] + ends = np.where(changes == -1)[0] + + for s, e in zip(starts, ends): + if e - s < min_duration: + final_pred[s:e, c] = 0 + + return final_pred + +def create_birdclef_submission(predictions, timestamps, audio_id, + bird_species, threshold=0.5): + """ + 创建 BirdCLEF 格式的提交文件 + + Args: + predictions: (num_windows, num_classes) 概率预测 + timestamps: (num_windows,) 时间戳 + audio_id: 音频文件 ID + bird_species: 鸟类名称列表 + threshold: 二值化阈值 + + Returns: + rows: 提交文件的行列表 + """ + rows = [] + + for i, (pred, ts) in enumerate(zip(predictions, timestamps)): + # 获取活跃的鸟类 + active_birds = [] + for j, p in enumerate(pred): + if p > threshold: + active_birds.append(bird_species[j]) + + # 创建 row_id + row_id = f"{audio_id}_{ts:.1f}" + + if active_birds: + rows.append({ + 'row_id': row_id, + 'birds': ' '.join(active_birds) + }) + else: + rows.append({ + 'row_id': row_id, + 'birds': 'nocall' + }) + + return rows + +# 使用示例 +model = WeaklySupervisedBirdcallModel(num_classes=397) +model = model.to(device) +model.load_state_dict(torch.load('best_model.pth')) + +audio_path = 'test_soundscape.wav' +predictions, timestamps = predict_with_sliding_window( + model, audio_path, window_size=5, hop_size=2.5, device=device +) + +# 聚合预测 +final_pred = aggregate_predictions(predictions, threshold=0.5, min_duration=3) + +# 创建提交 +bird_species = [...] # 397 个鸟类名称列表 +rows = create_birdclef_submission( + predictions, timestamps, 'soundscape_01', bird_species, threshold=0.5 +) + +import pandas as pd +submission = pd.DataFrame(rows) +submission.to_csv('submission.csv', index=False) +``` + +### 最佳实践 + +1. **弱监督学习策略**： + - 使用注意力机制定位音频中的关键区域 + - 多实例学习（MIL）框架处理音频级别标签 + - 时序池化（Temporal Pooling）聚合时间维度信息 + +2. **预训练模型利用**： + - PANNs（AudioSet 预训练）是最流行的起点 + - CNN14/CNN10 提供强大的基线特征 + - 迁移学习显著提升性能 + +3. **数据增强组合**： + - SpecAugment（时间+频率遮罩）必需 + - Mixup 是 BirdCLEF 2021 的关键技巧 + - 背景噪声添加提高鲁棒性 + - 组合多种增强效果最佳 + +4. **训练技巧**： + - 5-fold 交叉验证标准配置 + - AdamW + Cosine 学习率 + - Binary Cross-Entropy Loss + - Label Smoothing 有助于正则化 + - 渐进式训练策略 + +5. **推理策略**： + - 5秒滑动窗口（与标注一致） + - 窗口间有重叠（2.5秒跳跃） + - 时间平滑减少闪烁 + - 移除短于阈值的检测 + +6. **集成方法**： + - 多架构集成（ResNet, DenseNet, EfficientNet） + - 多 checkpoint 集成 + - 不同增强配置增加多样性 + - 加权平均或投票集成 + +7. **后处理优化**： + - 类别特定的阈值优化 + - 时间平滑（移动平均或中值滤波） + - 最小持续时间过滤 + - 基于验证集优化阈值 + +8. **常见陷阱**： + - 忽略弱监督的特殊性（无时间戳） + - 过度依赖单一模型 + - 验证集和测试集分布不同 + - 忘记时间平滑导致预测不稳定 + - 阈值选择不当影响 F1 分数 + +--- + +## BirdCLEF 2022 - Endangered Bird Sounds Classification + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology + LifeCLEF +- **目标**：识别夏威夷濒危鸟类的叫声（多标签音频分类） +- **应用场景**：濒危物种保护，生态系统监测 +- **数据集规模**： + - 训练音频：约 8,700 段标注录音，涵盖 152 种鸟类（主要是夏威夷物种） + - 测试音频：约 1,300 段连续录音（soundscape） + - 短片段标注：部分音频有 5 秒级别的短片段标注 + - 背景噪声：包含雨声、风声、昆虫声等复杂环境音 +- **评估指标**：micro-averaged F1-score +- **最终排名**： + - 1st Place: kdl - "It's not all BirdNet" + - 2nd Place: Leon Shangguan + - 3rd Place: uemu-slime + - 总参赛队伍：约 1,600+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Beyond BirdNet (kdl) + +核心技巧： +- **BirdNet + Perch Architecture**：结合 BirdNet 和 Perch 模型 +- **SED Framework**：声音事件检测框架 +- **Multi-scale Input**：短片段（5秒）和长片段（10秒+） +- **AND Rule**：短片段和长片段预测的 AND 逻辑 +- **Model Ensemble**：多架构集成 +- **External Data**：使用 BirdCLEF 2021 数据增强 + +实现细节： +- **模型架构组合**： + - BirdNet（预训练鸟类分类模型） + - Perch（预训练模型，类似 BirdNET-lite） + - 自训练 CNN 模型（ResNet50/ResNeSt50） + - SED 模型（framewise 输出） +- **多尺度策略**： + - 短片段（5秒）：精确分类 + - 长片段（10-15秒）：提高召回率 + - AND 规则：短片段 AND 长片段都预测为正才认为存在 +- **SED 实现**： + - 使用 framewise 输出 + - max(framewise, dim=time) 聚合 + - 时间注意力机制 +- **集成方法**： + - 多个模型集成（10+ 模型） + - 不同预训练权重 + - 不同输入长度 + - TTA（Test Time Augmentation） +- **外部数据**： + - BirdCLEF 2021 数据迁移学习 + - 额外鸟类音频数据 +- **后处理**： + - 时间平滑 + - 最小持续时间过滤 + - 类别特定阈值 + +#### 2nd Place - SED + CNN with 7 Models Ensemble (Leon Shangguan) + +核心技巧： +- **SED Framework**：声音事件检测框架 +- **10-second Chunks**：10秒片段处理 +- **Centered 5-second CNN**：中心 5 秒 CNN 预测 +- **Max Framewise Pooling**：framewise 最大值池化 +- **7 Models Ensemble**：7 模型集成 +- **TTA with 2s Shifts**：2秒偏移的测试时增强 + +实现细节： +- **SED 模型**： + - 使用 10 秒音频片段 + - 输出 framewise 预测 + - max(framewise, dim=time) 聚合 + - ResNet50/ResNeSt50 backbone +- **CNN 模型**： + - 仅对中心 5 秒进行预测 + - 减少计算量 + - Mel-spectrogram 输入 +- **集成策略**： + - 7 个模型集成 + - 不同架构和配置 + - 加权平均 +- **TTA**： + - 2 秒偏移的多个预测 + - 预测平均 +- **数据增强**： + - SpecAugment + - Mixup + - 背景噪声 + +#### 3rd Place - 18 Checkpoints Ensemble (uemu-slime) + +核心技巧： +- **18 Checkpoints Ensemble**：18 个模型检查点集成 +- **Multiple CNN Architectures**：多种 CNN 架构 +- **Different Folds**：不同折的训练 +- **Perch + BirdNet**：使用预训练模型 +- **Strong Data Augmentation**：强数据增强 + +实现细节： +- **模型架构**： + - ResNet50 + - ResNeSt50 + - EfficientNet-B0/B3 + - Perch（预训练） + - BirdNet（预训练） +- **训练策略**： + - 每个架构在 5-fold 上训练 + - 选择最佳 checkpoint + - 共 18 个模型 +- **集成方法**： + - 简单平均 + - 所有模型等权重 +- **增强组合**： + - SpecAugment + - Mixup + - 背景噪声 + - 时间遮罩/频率遮罩 + +#### 4th Place - CNN-based Ensemble (Kramarenko Vladislav) + +核心技巧： +- **CNN Ensemble**：CNN 模型集成 +- **Mel-Spectrogram Features**：Mel 频谱特征 +- **Multiple Backbones**：多种主干网络 +- **Cross-Validation**：交叉验证 + +实现细节： +- **模型选择**： + - ResNet50 + - ResNeSt50 + - DenseNet-121 +- **特征工程**： + - Mel-spectrogram + - 不同参数配置 +- **训练**： + - 5-fold 交叉验证 + - Early stopping + +#### 5th Place - Reimplementation of 2021 2nd Place (common-kestrel) + +核心技巧： +- **9 Models Ensemble**：9 模型集成 +- **BirdCLEF 2021 Baseline**：重实现 2021 年 2nd place 方案 +- **4x Backbones**：4 种主干网络 +- **Different Seeds and Folds**：不同随机种子和折 + +实现细节： +- **主干网络**： + - ResNet50 + - ResNeSt50 + - EfficientNet-B0 + - DenseNet-121 +- **配置多样性**： + - 不同随机种子 + - 不同 fold + - 不同数据增强参数 +- **集成方法**： + - 平均集成 + - 9 个模型 + +#### 6th-10th Place 概述 + +**常见技术**： +- BirdNet 预训练模型广泛使用 +- Perch 模型（类似 BirdNET-lite） +- SED（Sound Event Detection）框架 +- 多尺度输入（5秒 + 10-15秒） +- SpecAugment + Mixup 标准配置 + +**关键技术点**： +- **短片段长片段结合**：AND 规则减少误报 +- **Framewise 预测**：SED 模型的 framewise 输出 +- **外部数据利用**：BirdCLEF 2021 数据迁移学习 +- **模型集成**：10-20 个模型集成是常态 +- **后处理**：时间平滑、最小持续时间过滤 + +### 代码模板 + +#### SED 模型（Framewise 输出） +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SEDModel(nn.Module): + """ + 声音事件检测模型 - 输出 framewise 预测 + + 用于 BirdCLEF 2022 风格的音频分类 + """ + def __init__(self, num_classes=152, backbone='resnet50', + sample_rate=32000, window_size=5, hop_size=512): + super().__init__() + + self.num_classes = num_classes + self.window_size = window_size + self.sample_rate = sample_rate + + # Mel-spectrogram 提取器 + self.mel_extractor = MelSpectrogramExtractor( + sample_rate=sample_rate, + n_mels=128, + n_fft=2048, + hop_length=hop_size + ) + + # Backbone（简化版本） + if backbone == 'resnet50': + import torchvision.models as models + self.backbone = models.resnet50(pretrained=True) + # 修改第一层接受 1 通道输入（mel-spectrogram） + self.backbone.conv1 = nn.Conv2d( + 1, 64, kernel_size=7, stride=2, padding=3, bias=False + ) + feature_dim = 2048 + elif backbone == 'resnest50': + # 使用 ResNeSt50 + feature_dim = 2048 + + # 移除最后的全连接层 + self.backbone.fc = nn.Identity() + + # Framewise 分类头 + self.fc = nn.Linear(feature_dim, num_classes) + + def forward(self, waveform, return_frames=False): + """ + Args: + waveform: (batch, time_samples) + return_frames: 是否返回 framewise 预测 + + Returns: + output: (batch, num_classes) 或 (batch, time_frames, num_classes) + """ + batch_size = waveform.shape[0] + + # 提取 Mel-spectrogram + mel_spec = self.mel_extractor.extract(waveform) # (batch, 1, mel_bins, time_frames) + + # 通过 backbone（保留时间维度） + # 简化版本：实际需要修改 backbone 以保留时间维度 + features = self.extract_features_with_time(mel_spec) # (batch, time_frames, feature_dim) + + # Framewise 预测 + framewise_output = self.fc(features) # (batch, time_frames, num_classes) + + if return_frames: + return framewise_output + + # 聚合（max pooling over time） + output, _ = torch.max(framewise_output, dim=1) # (batch, num_classes) + + return output + + def extract_features_with_time(self, mel_spec): + """ + 提取特征并保留时间维度 + + 这是一个简化版本，实际使用时需要修改 backbone + """ + # 将时间维度视为 batch 维度处理 + batch, channels, mel_bins, time_frames = mel_spec.shape + + # Reshape: (batch * time_frames, channels, mel_bins, 1) + mel_spec_reshaped = mel_spec.permute(0, 3, 1, 2).reshape( + batch * time_frames, channels, mel_bins, 1 + ) + + # 通过 backbone（需要对输入维度进行调整） + # 这里简化为直接使用全局特征 + features = self.backbone(mel_spec_reshaped) # (batch * time_frames, feature_dim) + + # Reshape 回 (batch, time_frames, feature_dim) + features = features.reshape(batch, time_frames, -1) + + return features + +class MultiScaleSEDModel(nn.Module): + """ + 多尺度 SED 模型 + + 结合短片段（5秒）和长片段（10秒）预测 + """ + def __init__(self, num_classes=152, short_duration=5, long_duration=10): + super().__init__() + + self.num_classes = num_classes + + # 短片段模型（5秒） + self.short_model = SEDModel( + num_classes=num_classes, + window_size=short_duration + ) + + # 长片段模型（10秒） + self.long_model = SEDModel( + num_classes=num_classes, + window_size=long_duration + ) + + def forward(self, waveform_short, waveform_long, use_and_rule=True): + """ + Args: + waveform_short: 5秒音频 (batch, 5 * sample_rate) + waveform_long: 10秒音频 (batch, 10 * sample_rate) + use_and_rule: 是否使用 AND 规则 + + Returns: + output: (batch, num_classes) + """ + # 短片段预测 + output_short = self.short_model(waveform_short) # (batch, num_classes) + prob_short = torch.sigmoid(output_short) + + # 长片段预测 + output_long = self.long_model(waveform_long) # (batch, num_classes) + prob_long = torch.sigmoid(output_long) + + if use_and_rule: + # AND 规则：两者都为正才认为存在 + prob_final = prob_short * prob_long + else: + # OR 规则：任一为正就认为存在 + prob_final = torch.clamp(prob_short + prob_long, 0, 1) + + return prob_final + +# 使用示例 +model = MultiScaleSEDModel(num_classes=152, short_duration=5, long_duration=10) + +# 短片段和长片段 +waveform_short = torch.randn(4, 5 * 32000) # 4 samples, 5 seconds +waveform_long = torch.randn(4, 10 * 32000) # 4 samples, 10 seconds + +# 预测 +with torch.no_grad(): + prob = model(waveform_short, waveform_long, use_and_rule=True) +print(prob.shape) # (4, 152) +``` + +#### TTA（Test Time Augmentation） +```python +import torch +import numpy as np + +def predict_with_tta(model, audio_path, window_size=5, tta_shifts=[0, 1, 2], + sample_rate=32000, device='cuda'): + """ + 使用 TTA 进行推理 + + Args: + model: 训练好的模型 + audio_path: 音频文件路径 + window_size: 窗口大小（秒） + tta_shifts: TTA 偏移量（秒） + sample_rate: 采样率 + device: 设备 + + Returns: + predictions: (num_windows, num_classes) TTA 平均后的预测 + """ + model.eval() + + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + if sr != sample_rate: + resampler = torchaudio.transforms.Resample(sr, sample_rate) + waveform = resampler(waveform) + + waveform = waveform.mean(dim=0, keepdim=True) # 单声道 + + window_samples = int(window_size * sample_rate) + + # 存储所有 TTA 预测 + all_tta_predictions = [] + + for shift in tta_shifts: + shift_samples = int(shift * sample_rate) + + # 计算起始位置 + start_positions = list(range(shift_samples, waveform.shape[1] - window_samples + 1, + int(window_size * sample_rate))) + + predictions = [] + + with torch.no_grad(): + for start in start_positions: + end = start + window_samples + window = waveform[:, start:end].to(device) + + # 预测 + logits = model(window) + probs = torch.sigmoid(logits).cpu().numpy() + predictions.append(probs[0]) + + predictions = np.array(predictions) + all_tta_predictions.append(predictions) + + # TTA 平均 + all_tta_predictions = np.array(all_tta_predictions) # (num_shifts, num_windows, num_classes) + + # 对齐并平均 + avg_predictions = np.mean(all_tta_predictions, axis=0) + + return avg_predictions + +# 使用示例 +model = SEDModel(num_classes=152) +model = model.to(device) +model.load_state_dict(torch.load('best_model.pth')) + +audio_path = 'test_soundscape.wav' +predictions = predict_with_tta( + model, audio_path, window_size=5, tta_shifts=[0, 1, 2], device=device +) + +# 二值化 +threshold = 0.5 +binary_pred = (predictions > threshold).astype(int) +``` + +#### AND 规则后处理 +```python +import numpy as np + +def and_rule_post_process(short_pred, long_pred, threshold=0.5): + """ + AND 规则后处理 + + Args: + short_pred: 短片段预测 (num_windows_short, num_classes) + long_pred: 长片段预测 (num_windows_long, num_classes) + threshold: 二值化阈值 + + Returns: + final_pred: AND 规则后的预测 (num_windows_short, num_classes) + """ + # 二值化 + binary_short = (short_pred > threshold).astype(int) + binary_long = (long_pred > threshold).astype(int) + + # 长片段预测需要对应到短片段的时间位置 + # 假设长片段是短片段的两倍长度 + scale_factor = len(short_pred) / len(long_pred) + + final_pred = np.zeros_like(binary_short) + + for i in range(len(short_pred)): + # 找到对应的长片段索引 + long_idx = int(i / scale_factor) + + if long_idx < len(binary_long): + # AND 规则：两者都为 1 才认为存在 + final_pred[i] = binary_short[i] & binary_long[long_idx] + else: + # 没有对应的长片段预测，使用短片段预测 + final_pred[i] = binary_short[i] + + return final_pred + +# 使用示例 +# 短片段预测（5秒窗口） +short_pred = np.random.rand(100, 152) # 100 个窗口，152 个类别 + +# 长片段预测（10秒窗口） +long_pred = np.random.rand(50, 152) # 50 个窗口 + +# 应用 AND 规则 +final_pred = and_rule_post_process(short_pred, long_pred, threshold=0.5) +``` + +#### 模型集成 +```python +import torch +import numpy as np + +class EnsembleModel: + """ + 模型集成类 + """ + def __init__(self, models, weights=None, device='cuda'): + """ + Args: + models: 模型列表 + weights: 模型权重（可选），默认平均 + device: 设备 + """ + self.models = models + self.device = device + + if weights is None: + # 默认等权重 + self.weights = [1.0 / len(models)] * len(models) + else: + # 归一化权重 + total = sum(weights) + self.weights = [w / total for w in weights] + + # 将模型移到设备并设置为评估模式 + for model in self.models: + model.to(device) + model.eval() + + def predict(self, waveform): + """ + 集成预测 + + Args: + waveform: 输入音频 (batch, time_samples) + + Returns: + ensemble_pred: 集成后的预测 (batch, num_classes) + """ + all_predictions = [] + + with torch.no_grad(): + for model in self.models: + logits = model(waveform) + probs = torch.sigmoid(logits).cpu().numpy() + all_predictions.append(probs) + + all_predictions = np.array(all_predictions) # (num_models, batch, num_classes) + + # 加权平均 + ensemble_pred = np.zeros_like(all_predictions[0]) + for i, pred in enumerate(all_predictions): + ensemble_pred += self.weights[i] * pred + + return ensemble_pred + + def predict_from_files(self, model_paths, ModelClass, model_kwargs, waveform): + """ + 从文件加载模型并预测 + + Args: + model_paths: 模型文件路径列表 + ModelClass: 模型类 + model_kwargs: 模型初始化参数 + waveform: 输入音频 + + Returns: + ensemble_pred: 集成后的预测 + """ + all_predictions = [] + + for path in model_paths: + # 加载模型 + model = ModelClass(**model_kwargs) + model.load_state_dict(torch.load(path)) + model.to(self.device) + model.eval() + + # 预测 + with torch.no_grad(): + logits = model(waveform) + probs = torch.sigmoid(logits).cpu().numpy() + all_predictions.append(probs) + + all_predictions = np.array(all_predictions) + + # 加权平均 + ensemble_pred = np.zeros_like(all_predictions[0]) + for i, pred in enumerate(all_predictions): + ensemble_pred += self.weights[i] * pred + + return ensemble_pred + +# 使用示例 +# 假设有 7 个模型 +models = [ + SEDModel(num_classes=152, backbone='resnet50'), + SEDModel(num_classes=152, backbone='resnest50'), + SEDModel(num_classes=152, backbone='efficientnet_b0'), + # ... 更多模型 +] + +# 加载权重 +for i, model in enumerate(models): + model.load_state_dict(torch.load(f'model_{i}.pth')) + +# 创建集成 +ensemble = EnsembleModel(models, weights=None, device=device) + +# 预测 +waveform = torch.randn(4, 5 * 32000).to(device) +predictions = ensemble.predict(waveform) +print(predictions.shape) # (4, 152) +``` + +#### BirdNet/Perch 模型使用 +```python +""" +BirdNet 和 Perch 是预训练的鸟类音频分类模型 + +使用前需要： +1. 安装 birdnetlib 或 perch 库 +2. 下载预训练权重 + +这里提供一个简化接口示例 +""" + +class BirdNetModel(nn.Module): + """ + BirdNet 模型包装器 + + 实际使用时需要从官方仓库获取模型 + 参考: https://github.com/BirdVox/birdnet-library + """ + def __init__(self, num_classes=152, pretrained_path=None): + super().__init__() + + # 这里应该是 BirdNet 的实际架构 + # 简化版本：使用 ResNet50 + import torchvision.models as models + self.backbone = models.resnet50(pretrained=True) + + # 修改第一层接受 mel-spectrogram + self.backbone.conv1 = nn.Conv2d( + 1, 64, kernel_size=7, stride=2, padding=3, bias=False + ) + + feature_dim = 2048 + + # 分类头 + self.classifier = nn.Sequential( + nn.Dropout(0.5), + nn.Linear(feature_dim, num_classes) + ) + + # 加载预训练权重 + if pretrained_path is not None: + self.load_pretrained(pretrained_path) + + def load_pretrained(self, path): + """加载预训练权重""" + state_dict = torch.load(path, map_location='cpu') + + # 过滤不兼容的键 + model_state = self.state_dict() + pretrained_state = { + k: v for k, v in state_dict.items() + if k in model_state and v.shape == model_state[k].shape + } + + model_state.update(pretrained_state) + self.load_state_dict(model_state) + print(f"Loaded pretrained weights from {path}") + + def forward(self, mel_spec): + """ + Args: + mel_spec: (batch, 1, mel_bins, time_frames) + + Returns: + logits: (batch, num_classes) + """ + features = self.backbone(mel_spec) + logits = self.classifier(features) + return logits + +# 使用示例（需要实际的预训练权重） +# model = BirdNetModel(num_classes=152, pretrained_path='birdnet.pth') +# model.eval() +# with torch.no_grad(): +# logits = model(mel_spec) +# probs = torch.sigmoid(logits) +``` + +### 最佳实践 + +1. **多尺度策略**： + - 短片段（5秒）用于精确分类 + - 长片段（10-15秒）提高召回率 + - AND 规则减少误报（两个都为正才认为存在） + - OR 规则提高召回（任一为正就认为存在） + +2. **SED 框架**： + - Framewise 输出提供时间分辨率 + - Max pooling over time 聚合 + - 注意力权重加权 + +3. **模型集成**： + - 10-20 个模型集成是常态 + - 不同架构（ResNet, ResNeSt, EfficientNet） + - 不同训练配置（fold, seed, 数据增强） + - 加权平均或投票 + +4. **预训练模型利用**： + - BirdNet：强大的鸟类分类预训练模型 + - Perch：轻量级版本（BirdNET-lite） + - 迁移学习显著提升性能 + - 在目标任务上微调 + +5. **外部数据**： + - BirdCLEF 2021 数据 + - 其他鸟类音频数据集 + - 预训练模型在大规模数据上训练 + +6. **TTA（Test Time Augmentation）**： + - 时间偏移（1-2秒） + - 多个预测平均 + - 提高稳定性 + +7. **后处理**： + - 时间平滑 + - 最小持续时间过滤 + - 类别特定阈值 + - AND 规则结合短长片段 + +8. **常见陷阱**： + - 忽视短片段和长片段的互补性 + - 过度依赖单一模型或架构 + - 集成权重未优化 + - 忘记使用 TTA + - AND/OR 规则选择不当 + +--- + +## Rainforest Connection Species Audio Detection 2021 + +**竞赛背景：** +- **主办方**：Rainforest Connection (RFCx) +- **目标**：检测热带雨林录音中的鸟类和蛙类叫声（多标签音频检测） +- **应用场景**：生物多样性监测，生态系统保护，濒危物种追踪 +- **数据集规模**： + - 训练音频：约 2,000 段标注录音 + - 测试音频：约 200 段连续录音（soundscape） + - 物种数量：24 种鸟类和蛙类 + - 采样率：48 kHz +- **评估指标**：LWLRAP (Label-Weighted Label-Ranking Average Precision) +- **最终排名**： + - 1st Place: watercooled + - 7th Place: Beluga & Peter + - 11th Place: cpmp + - 13th Place: Ryan Epp + - 总参赛队伍：约 2,200+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Image Classification Approach (watercooled) + +核心技巧： +- **Mel-Spectrogram as Images**：将 Mel 频谱视为图像 +- **Pretrained Image Models**：使用预训练图像分类模型 +- **Ensemble**：多模型集成 +- **Temporal Pooling**：时间池化策略 +- **Data Augmentation**：图像和音频增强 +- **Post-processing**：后处理优化 + +实现细节： +- **模型架构**： + - ResNet50/ResNeSt50（ImageNet 预训练） + - EfficientNet-B3 + - 修改第一层接受单通道输入（Mel-spectrogram） +- **特征提取**： + - Mel-spectrogram（128 Mel bins） + - 对数幅度压缩 + - 时间维度：5 秒窗口 +- **集成方法**： + - 多个模型集成 + - 不同 checkpoint + - 加权平均 +- **后处理**： + - 时间平滑 + - 阈值优化 + - 最小持续时间过滤 + +#### 7th Place - Strong Baseline with Ensemble (Beluga & Peter) + +核心技巧： +- **ResNeSt50 Architecture**：ResNeSt-50 主干网络 +- **Mel-Spectrogram Features**：Mel 频谱特征 +- **5-fold Cross-Validation**：5 折交叉验证 +- **Model Ensemble**：模型集成 +- **Strong Data Augmentation**：强数据增强 + +实现细节： +- **模型选择**： + - ResNeSt50（预训练） + - EfficientNet-B3 + - DenseNet-121 +- **增强策略**： + - SpecAugment + - Mixup + - 背景噪声 + - 时间遮罩/频率遮罩 + +#### 11th Place - The 0.931 Magic Explained (cpmp) + +核心技巧： +- **Image Classification Approach**：图像分类方法 +- **High-Performance Architecture**：高性能架构 +- **Optimized Preprocessing**：优化的预处理 +- **LWLRAP-specific Optimization**：针对 LWLRAP 指标优化 + +实现细节： +- **关键发现**： + - 优化的 Mel-spectrogram 参数 + - 特定的数据增强组合 + - 后处理技巧达到 0.931 分数 + +#### 13th Place - Mean Co-Teachers and Noisy Students (Ryan Epp) + +核心技巧： +- **Mean Teacher**：均值教师模型 +- **Co-Teaching**：协同教学 +- **Noisy Student**：噪声学生策略 +- **Semi-Supervised Learning**：半监督学习 +- **Pseudo-labeling**：伪标签 + +实现细节： +- **半监督策略**： + - 使用未标注数据 + - 伪标签迭代优化 + - Mean Teacher 平滑预测 + +### 关键技术点 + +1. **Mel-Spectrogram 作为图像**： + - 将音频转换为 Mel-spectrogram + - 使用图像分类模型（ResNet, EfficientNet） + - 修改第一层接受单通道输入 + +2. **LWLRAP 指标**： + - Label-Weighted Label-Ranking Average Precision + - 需要优化预测的排序 + - 类别权重不平衡 + +3. **数据增强**： + - SpecAugment（时间/频率遮罩） + - Mixup + - 背景噪声 + +4. **模型集成**： + - 多架构集成 + - 不同 checkpoint + - 加权平均 + +5. **后处理**： + - 时间平滑 + - 阈值优化 + - 最小持续时间过滤 + +--- + +## AMP®-Parkinson's Disease Progression Prediction 2023 + +**注意**：此比赛主要使用蛋白质/多肽测量数据，属于**表格数据时序回归**任务，非传统的一维信号处理（如音频、EEG 等）。 + +**竞赛背景：** +- **主办方**：AMP (Accelerating Medicines Partnership) +- **目标**：预测帕金森病患者的 MDS-UPDRS 评分变化（时序回归） +- **应用场景**：帕金森病进展监测，药物效果评估 +- **数据集规模**： + - 患者数量：约 1,000+ 患者 + - 蛋白质/多肽测量：数百种蛋白质特征 + - 时间点：多个月份的访视数据 + - 访视记录：蛋白丰度数据 + 蛋白肽数据 +- **评估指标**：SMAPE (Symmetric Mean Absolute Percentage Error) +- **最终排名**： + - 1st Place: Connecting Dotts + - 2nd Place: No Luck All Skill + - 3rd Place: Hajime Tamura + - 总参赛队伍：约 2,500+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Feature Engineering + Gradient Boosting (Connecting Dotts) + +核心技巧： +- **Protein/Peptide Feature Engineering**：蛋白质/多肽特征工程 +- **Gradient Boosting Models**：梯度提升模型 +- **Ensemble**：多模型集成 +- **Cross-Validation**：交叉验证 +- **Clincal Knowledge Integration**：临床知识整合 + +实现细节： +- **特征工程**： + - 蛋白质丰度统计特征 + - 时间变化特征 + - 蛋白质-蛋白质交互特征 + - 临床协变量整合 +- **模型选择**： + - XGBoost/LightGBM + - CatBoost + - 多个模型集成 +- **训练策略**： + - 5-fold 交叉验证 + - 特征选择 + - 超参数优化 + +#### 2nd Place - Strong Feature Engineering (No Luck All Skill) + +核心技巧： +- **Advanced Feature Engineering**：高级特征工程 +- **Protein Network Features**：蛋白质网络特征 +- **Time-Series Features**：时序特征 +- **Model Ensemble**：模型集成 + +实现细节： +- **特征类型**： + - 蛋白质丰度基线 + - 时间变化趋势 + - 蛋白质-蛋白质相关性 + - 临床协变量 + +#### 3rd Place - Robust Modeling Approach (Hajime Tamura) + +核心技巧： +- **Robust Feature Selection**：稳健特征选择 +- **Gradient Boosting**：梯度提升 +- **Ensemble Strategy**：集成策略 + +实现细节： +- **特征选择**： + - 基于重要性的特征选择 + - 多重共线性处理 +- **模型**： + - XGBoost/LightGBM + - 简单平均集成 + +### 关键技术点 + +1. **蛋白质数据特征**： + - 蛋白质丰度（protein abundance） + - 肽段数据（peptide data） + - 时间序列变化 + - 临床协变量 + +2. **特征工程**： + - 基线特征 + - 时间变化特征 + - 交互特征 + - 统计特征 + +3. **模型选择**： + - Gradient Boosting (XGBoost, LightGBM, CatBoost) + - 集成多个模型 + +4. **评估指标**： + - SMAPE (Symmetric MAPE) + - 需要处理零值和异常值 + +5. **验证策略**： + - 按患者划分的交叉验证 + - 时间序列分割 + - 防止数据泄露 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/aimo-2-2025.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/aimo-2-2025.md new file mode 100644 index 0000000..4c186bf --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/aimo-2-2025.md @@ -0,0 +1,1222 @@ +# AIMO-2 +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### AIMO-2 (2025) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-2) | [Paper](https://arxiv.org/abs/2504.16891) +**Category:** NLP/LLM (数学推理) +**Key Techniques:** +- **MARIO 框架**: MAth Reasoning with code Interpreter +- **代码执行集成**: Python 代码在沙盒中执行 +- **OpenMathReasoning 数据集**: ~290K 高质量数学问题，3.2M CoT，1.7M TIR +- **三阶段训练**: CoT → TIR → GenSelect +- **GenSelect**: 多答案生成 + 基于排序的投票 +- **Qwen2.5 架构**: 1.5B/7B/14B/32B 模型家族 +- **自一致性 + TIR**: 32 候答案生成 + 多数投票 +- **AoPS 数据源**: 从 Art of Problem Solving 论坛提取 + +**Results:** NVIDIA (NemoSkills) 34/50 正确 (68%), OpenMath-Nemotron-32B 达到 SOTA + +--- + +## Competition Brief (竞赛简介) + +### AIMO-2 - AI Mathematical Olympiad Progress Prize 2 + +**竞赛背景：** +- **主办方**：AIMO (AI Mathematical Olympiad) +- **目标**：解决国家奥林匹克级数学问题 +- **特殊性质**：测试 AI 的**数学推理能力**，不是传统 NLP 任务 + +**竞赛规模：** +- **问题数量**: 50 道国家奥林匹克级数学问题 +- **时间限制**: 5 小时解决所有问题 +- **总队伍数**: 约 100+ teams +- **奖项池**: >$2,000,000 + +**任务格式：** +``` +数学问题文本 + ↓ +生成解决方案（推理 + 代码） + ↓ +执行代码（如有） + ↓ +提取最终答案 +``` + +**评估指标：** +- **准确率**: 完全正确才算对（34/50 = 68%） +- **答案格式**: 多选题（A-E）或数值答案 +- **时间限制**: 5 小时，平均每题 6 分钟 + +**关键洞察：** +1. **代码执行是关键**: 纯 LLM 推理不够，需要代码执行进行计算 +2. **数据质量 > 数量**: 从 AoPS 提取的高质量数据 +3. **三阶段训练有效**: CoT → TIR → GenSelect +4. **小模型可以很强**: 1.5B 模型达到有竞争力的性能 +5. **自一致性 + 排序投票**: 比简单多数投票更有效 + +**前排方案总结（Top 12+）：** + +| 排名 | 队伍 | 正确数 | 核心技术 | 模型 | 推理引擎 | +|------|------|--------|---------|------|---------| +| **1st** | NVIDIA (NemoSkills) | 34/50 | MARIO, TIR, GenSelect, OpenMathReasoning | Qwen2.5-14B | TensorRT-LLM | +| **2nd** | imagination-research | ~30/50 | SFT + DPO (长度优化), 代码执行 | DeepSeek-R1-Distill-Qwen-14B | lmdeploy | +| **3rd** | Aliev | ~29/50 | Self-consistency, Early stopping | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **4th** | Soren Ravn Andersen | ~28/50 | AWQ 量化, Self-consistency | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **5th** | usernam | ~27/50 | lmdeploy 高吞吐量 | DeepSeek-R1-Distill-Qwen-14B AWQ | lmdeploy | +| **7th** | tascj | ~26/50 | AWQ 量化 | DeepSeek-R1-Distill-Qwen-14B AWQ | lmdeploy | +| **8th** | MPWARE | ~25/50 | 自定义 AWQ 量化, Self-consistency | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **9th** | Fast-Math-R1–14B | ~24/50 | SFT + GRPO (效率优化) | Fine-tuned DeepSeek-R1-Distill-Qwen-14B | - | +| **11th** | farsail | ~22/50 | One-shot prompting, 自定义 vLLM | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **17th** | ippeiogawa | ~18/50 | Multi-stage prompting, 代码生成 | DeepSeek-R1-Distill-Qwen-14B AWQ | vLLM | +| **20th** | Arek Paterek | ~15/50 | AWQ 量化 | DeepSeek-R1-Distill-Qwen-32B AWQ | - | +| **22nd** | K-Piece | ~13/50 | Base model + prompting | DeepSeek-R1 系列 | - | + +**技术趋势分析：** + +1. **模型选择**：几乎所有前排方案都使用 `DeepSeek-R1-Distill-Qwen-14B AWQ`（4-bit 量化） +2. **微调方法**： + - **SFT**：几乎所有队伍的基础起点 + - **DPO**：第 2 名用于减少输出长度 + - **TIR**：第 1 名的核心创新（工具集成推理） + - **GRPO**：第 9 名尝试用于效率优化（结果不稳定） +3. **推理引擎**： + - **vLLM**：最常用（4th, 7th, 8th, 11th, 17th） + - **lmdeploy**：高吞吐量选择（2nd, 5th, 7th） + - **TensorRT-LLM**：第 1 名专用 +4. **推理策略**： + - **Self-consistency/Majority voting**：通用标配 + - **Early stopping**：节省时间和 tokens + - **代码执行**：提升计算精度 + +**核心创新 - MARIO 框架（1st Place）：** +- **MA**: Math（数学推理） +- **RI**: Reasoning（推理）+ Interpreter（代码解释器） +- **O**: Open（开源） + +**数据集规模：** +- OpenMathReasoning: ~290K 问题 +- 3.2M CoT（长思维链） +- 1.7M TIR（工具集成推理） + +#### 前排方案详细技术分析 + +**1st Place - NVIDIA (NemoSkills) - 34/50 (68%)** + +核心技巧： +- **MARIO 框架**：Math + Reasoning + Interpreter 整合 +- **OpenMathReasoning 数据集**：从 AoPS 提取的 ~290K 高质量数据 +- **三阶段训练**：CoT → TIR → GenSelect 逐步训练 +- **代码执行集成**：Python 代码在沙盒中执行 +- **GenSelect 策略**：32 候选答案 + 基于排序的投票 + +实现细节： +- Qwen2.5-14B 主模型，TensorRT-LLM 推理优化 +- CoT：长思维链推理，提取推理过程 +- TIR：生成推理 + Python 代码，代码执行验证结果 +- GenSelect：32 候选答案，基于推理质量排序选择 +- 数据：3.2M CoT + 1.7M TIR 格式 +- 最终成绩：34/50 正确（68%） + +**2nd Place - imagination-research - ~30/50 (60%)** + +核心技巧： +- **SFT + DPO 组合**：监督微调 + 直接偏好优化 +- **DPO 长度优化**：第 2 阶段减少输出长度，提升效率 +- **代码执行集成**：Python 代码生成和执行 +- **DeepSeek-R1-Distill-Qwen-14B AWQ**：4-bit 量化模型 + +实现细节： +- SFT：OpenR1 Math + Light-R1 数据集监督微调 +- DPO：第 2 阶段训练，优化输出长度和推理质量 +- 量化：AWQ 4-bit 量化，降低内存占用 +- 推理引擎：lmdeploy 高吞吐量推理 +- 最终成绩：~30/50 正确 + +**3rd Place - Aliev - ~29/50 (58%)** + +核心技巧： +- **Self-consistency**：自洽性，生成多个解取最频繁答案 +- **Early stopping**：提前停止节省推理时间 +- **DeepSeek-R1-Distill-Qwen-14B AWQ**：4-bit 量化 +- **vLLM 推理引擎**：高效推理框架 + +实现细节： +- Self-consistency：生成多个候选答案，多数投票 +- Early stopping：前 5 个候选中出现 4 个相同则停止 +- vLLM：PagedAttention 高效内存管理 +- 量化：AWQ Activation-aware Weight Quantization +- 最终成绩：~29/50 正确 + +**4th Place - Soren Ravn Andersen - ~28/50 (56%)** + +核心技巧： +- **AWQ 量化**：Activation-aware Weight Quantization +- **Self-consistency**：多候选答案生成 +- **vLLM 推理引擎**：PagedAttention 优化 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- AWQ：识别关键权重，保护重要权重，量化其他 +- Self-consistency：标准多数投票策略 +- vLLM：PagedAttention 减少 KV Cache 内存占用 +- 最终成绩：~28/50 正确 + +**5th Place - usernam - ~27/50 (54%)** + +核心技巧： +- **lmdeploy 高吞吐量**：高吞吐量推理框架 +- **DeepSeek-R1-Distill-Qwen-14B AWQ**：4-bit 量化 +- **Batch 推理优化**：大 batch 推理提升吞吐 + +实现细节： +- lmdeploy：连续批处理优化 +- 量化：AWQ 4-bit，减少内存和计算 +- Batch size：根据 GPU 内存动态调整 +- 最终成绩：~27/50 正确 + +**7th Place - tascj - ~26/50 (52%)** + +核心技巧： +- **AWQ 量化**：4-bit 量化优化 +- **lmdeploy 推理**：高吞吐量推理 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- AWQ：自定义量化配置 +- lmdeploy：高吞吐量，多 GPU 并行 +- 最终成绩：~26/50 正确 + +**8th Place - MPWARE - ~25/50 (50%)** + +核心技巧： +- **自定义 AWQ 量化**：自定义量化策略 +- **Self-consistency**：多候选投票 +- **vLLM 推理引擎** + +实现细节： +- 自定义 AWQ：根据模型特性定制量化 +- vLLM：PagedAttention 内存优化 +- 最终成绩：~25/50 正确 + +**9th Place - Fast-Math-R1–14B - ~24/50 (48%)** + +核心技巧： +- **SFT + GRPO**：监督微调 + Group Relative Policy Optimization +- **GRPO 效率优化**：减少推理步数，提升效率（结果不稳定） +- **Fine-tuned DeepSeek-R1-Distill-Qwen-14B**：微调模型 + +实现细节： +- SFT：OpenR1 Math 数据集微调 +- GRPO：优化推理步骤数，减少 tokens +- 不稳定性：优化到一定程度后"灾难性偏移" +- 使用早期 checkpoint 获得最佳结果 +- 最终成绩：~24/50 正确 + +**11th Place - farsail - ~22/50 (44%)** + +核心技巧： +- **One-shot prompting**：单样本提示，无需微调 +- **自定义 vLLM**：自定义推理引擎配置 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- One-shot：提供 1-2 个示例作为提示 +- 自定义 vLLM：优化 PagedAttention 参数 +- 最终成绩：~22/50 正确 + +**17th Place - ippeiogawa - ~18/50 (36%)** + +核心技巧： +- **Multi-stage prompting**：多阶段提示策略 +- **代码生成**：强制生成 Python 代码 +- **DeepSeek-R1-Distill-Qwen-14B AWQ** + +实现细节： +- Multi-stage：分解问题，逐步生成代码 +- 代码生成：要求模型生成可执行代码 +- vLLM：高效推理引擎 +- 最终成绩：~18/50 正确 + +**20th Place - Arek Paterek - ~15/50 (30%)** + +核心技巧： +- **AWQ 量化**：4-bit 量化 +- **DeepSeek-R1-Distill-Qwen-32B AWQ**：32B 大模型量化 +- **Base model + prompting**：基础模型 + 提示工程 + +实现细节： +- 32B 模型：更大模型，更多知识 +- AWQ 量化：4-bit 量化降低内存 +- 无微调：直接使用提示 +- 最终成绩：~15/50 正确 + +**22nd Place - K-Piece - ~13/50 (26%)** + +核心技巧： +- **Base model + prompting**：基础模型 + 提示工程 +- **DeepSeek-R1 系列**：使用不同大小的 DeepSeek-R1 +- **Self-consistency**：多候选投票 + +实现细节： +- 提示工程：精心设计的提示模板 +- DeepSeek-R1：14B, 32B 等不同变体 +- Self-consistency：生成 5-10 个候选答案 +- 最终成绩：~13/50 正确 + +**技术总结：** + +| 技术维度 | 关键发现 | +|---------|---------| +| **模型选择** | DeepSeek-R1-Distill-Qwen-14B AWQ 是最受欢迎 | +| **微调方法** | SFT（基础）+ DPO（长度优化）+ TIR（工具集成） | +| **推理引擎** | vLLM（通用）
    lmdeploy（高吞吐）
    TensorRT-LLM（第 1 名专用） | +| **推理策略** | Self-consistency（标配）
    Early stopping（节省时间）
    代码执行（提升精度） | +| **核心创新** | MARIO 框架：Math + Reasoning + Interpreter | + +--- + +### MARIO 框架 - 数学推理 + 代码解释器 + +**关键洞察：** 纯 LLM 推理不够，需要代码执行进行计算 + +```python +import subprocess +import tempfile +import os + +class MARIOFramework: + """ + MARIO: MAth Reasoning with code Interpreter + NVIDIA AIMO-2 第 1 名方案 + + 核心思想： + 1. LLM 生成自然语言推理 + Python 代码 + 2. 代码在沙盒环境中执行 + 3. 执行结果指导后续推理 + 4. 迭代直到得到最终答案 + """ + def __init__(self, model, max_iterations=10): + self.model = model + self.max_iterations = max_iterations + + def solve_math_problem(self, problem_text): + """ + 解决数学问题 + + Args: + problem_text: 数学问题文本 + + Returns: + answer: 最终答案（多选 A-E 或数值） + """ + # 初始化对话 + conversation = [ + {"role": "system", "content": "You are a math expert. Solve the problem step by step."}, + {"role": "user", "content": problem_text} + ] + + for iteration in range(self.max_iterations): + # 生成推理 + 代码 + response = self.model.generate(conversation) + + # 提取 Python 代码 + code_blocks = self.extract_code_blocks(response) + + if code_blocks: + # 执行代码 + execution_results = [] + for code in code_blocks: + result = self.execute_code_safely(code) + execution_results.append(result) + + # 将执行结果添加到对话 + conversation.append({"role": "assistant", "content": response}) + conversation.append({ + "role": "user", + "content": f"Execution results: {execution_results}. Continue reasoning." + }) + else: + # 没有代码，直接返回答案 + conversation.append({"role": "assistant", "content": response}) + break + + # 提取最终答案 + answer = self.extract_final_answer(conversation[-1]['content']) + return answer + + def extract_code_blocks(self, text): + """ + 提取 Python 代码块 + """ + import re + pattern = r'```python\n(.*?)```' + matches = re.findall(pattern, text, re.DOTALL) + return matches + + def execute_code_safely(self, code, timeout=10): + """ + 在沙盒环境中安全执行代码 + """ + try: + # 创建临时文件 + with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f: + f.write(code) + temp_file = f.name + + # 执行代码，设置超时和资源限制 + result = subprocess.run( + ['python', temp_file], + capture_output=True, + text=True, + timeout=timeout, + # 资源限制 + # (实际实现需要更严格的沙盒) + ) + + # 删除临时文件 + os.unlink(temp_file) + + return result.stdout + except subprocess.TimeoutExpired: + return "Execution timeout" + except Exception as e: + return f"Error: {str(e)}" +``` + +### 三阶段训练 (CoT → TIR → GenSelect) + +**关键洞察：** 逐步训练模型掌握推理、工具使用和答案选择 + +```python +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer + +class ThreeStageTraining: + """ + NVIDIA 三阶段训练流程 + Stage 1: CoT (Chain-of-Thought) - 知识获取 + Stage 2: TIR (Tool-Integrated Reasoning) - 工具集成推理 + Stage 3: GenSelect - 生成选择 + """ + def __init__(self, model_name="Qwen/Qwen2.5-32B"): + self.model = AutoModelForCausalLM.from_pretrained(model_name) + self.tokenizer = AutoTokenizer.from_pretrained(model_name) + + def stage1_cot_training(self, cot_dataset): + """ + Stage 1: Chain-of-Thought 训练 + 纯推理训练，不使用代码执行 + """ + for example in cot_dataset: + problem = example['problem'] + cot_solution = example['cot_solution'] # 长思维链 + + prompt = f""" + Problem: {problem} + + Solution: + {cot_solution} + + Answer: {example['answer']} + """ + + # 训练模型生成推理链 + inputs = self.tokenizer(prompt, return_tensors="pt") + labels = self.tokenizer(cot_solution, return_tensors="pt") + + outputs = self.model(**inputs, labels=labels) + loss = outputs.loss + + # 反向传播（简化） + loss.backward() + + def stage2_tir_training(self, tir_dataset): + """ + Stage 2: Tool-Integrated Reasoning 训练 + 训练模型生成推理 + Python 代码 + """ + for example in tir_dataset: + problem = example['problem'] + tir_solution = example['tir_solution'] # 推理 + 代码 + + prompt = f""" + Problem: {problem} + + Solve the problem step by step. Use Python code for calculations. + + Solution: + {tir_solution} + + Answer: {example['answer']} + """ + + inputs = self.tokenizer(prompt, return_tensors="pt") + labels = self.tokenizer(tir_solution, return_tensors="pt") + + outputs = self.model(**inputs, labels=labels) + loss = outputs.loss + + loss.backward() + + def stage3_genselect_training(self, validation_dataset): + """ + Stage 3: GenSelect 训练 + 学习多答案生成 + 排序投票 + """ + # 训练时模拟多个答案生成 + predictions = [] + + for example in validation_dataset: + problem = example['problem'] + + # 生成多个候选答案 + candidate_answers = [] + for _ in range(32): # 32 个候选答案 + prompt = f"Problem: {problem}\nSolution: Let's think step by step." + inputs = self.tokenizer(prompt, return_tensors="pt") + outputs = self.model.generate(**inputs, max_new_tokens=2048) + + answer = self.extract_answer(outputs) + candidate_answers.append(answer) + + # 基于排序的投票 + final_answer = self.rank_based_voting(candidate_answers) + predictions.append(final_answer) + + def rank_based_voting(self, answers): + """ + 基于排序的投票（优于简单多数投票） + + NVIDIA 创新： + - 不只是计数答案出现次数 + - 根据推理质量加权 + - 考虑答案的置信度 + """ + # 统计每个答案的投票数 + from collections import Counter + counts = Counter(answers) + + # 加权投票（推理质量） + # 这里简化为多数投票 + return counts.most_common(1)[0][0] +``` + +### GenSelect - 多答案生成与投票 + +**关键洞察：** 候选答案的排序投票优于简单多数投票 + +```python +import numpy as np +from collections import Counter + +def genselect_answer(model, problem_text, n_candidates=32): + """ + GenSelect: 生成选择方法 + + NVIDIA AIMO-2 核心创新： + 1. 生成多个候选答案 + 2. 对每个答案评分 + 3. 基于排序选择最终答案 + """ + candidate_answers = [] + scores = [] + + for _ in range(n_candidates): + # 生成推理 + 答案 + prompt = f""" +Problem: {problem_text} + +Let's think step by step. We need to find the final answer. +""" + response = model.generate(prompt, max_new_tokens=2048) + + # 提取答案 + answer = extract_answer(response) + confidence = estimate_confidence(response) + + candidate_answers.append(answer) + scores.append(confidence) + + # 基于排序的投票 + # 不只是选择出现最多的答案 + # 考虑答案的置信度排序 + sorted_indices = np.argsort(scores)[::-1] # 降序 + + # 选择置信度最高的答案 + # 或者使用加权组合 + final_answer = candidate_answers[sorted_indices[0]] + + return final_answer + + +def extract_answer(response_text): + """ + 从推理文本中提取最终答案 + """ + import re + + # 匹配模式 1: "Answer: X" + match = re.search(r'Answer:\s*([A-E]|-?\d+)', response_text) + if match: + return match.group(1) + + # 匹配模式 2: "最终答案是 X" + match = re.search(r'最终答案[是为]\s*([A-E]|-?\d+)', response_text) + if match: + return match.group(1) + + # 匹配模式 3: "Therefore, the answer is X" + match = re.search(r'Therefore,?\s*the\s+answer\s+is\s+([A-E]|-?\d+)', response_text) + if match: + return match.group(1) + + return None + + +def estimate_confidence(response_text): + """ + 估计答案的置信度 + + 方法： + - 推理链的完整性 + - "Therefore"、"Thus"等确定性词汇 + - 答案的明确程度 + """ + confidence = 0.5 # 基础置信度 + + # 检查确定性词汇 + certainty_keywords = ['therefore', 'thus', 'hence', 'consequently'] + for keyword in certainty_keywords: + if keyword in response_text.lower(): + confidence += 0.1 + + # 检查不确定性词汇 + uncertainty_keywords = ['maybe', 'perhaps', 'possibly', 'probably'] + for keyword in uncertainty_keywords: + if keyword in response_text.lower(): + confidence -= 0.1 + + # 检查推理链长度 + reasoning_length = len(response_text.split('.')) + confidence += min(reasoning_length / 100, 0.3) + + return np.clip(confidence, 0, 1) +``` + +### OpenMathReasoning 数据集构建 + +**关键洞察：** 从 AoPS 论坛提取高质量数学问题 + +```python +import requests +from bs4 import BeautifulSoup + +def build_openmath_dataset(): + """ + 从 AoPS (Art of Problem Solving) 论坛构建数据集 + + NVIDIA AIMO-2 方法： + 1. 爬取 AoPS 论坛的高质量回答 + 2. 使用 LLM 提取结构化信息 + 3. 过滤低质量数据 + 4. 生成 CoT 和 TIR 格式 + """ + base_url = "https://artofproblemsolving.com" + + # 1. 爬取论坛帖子 + posts = [] + for forum in ["algebra", "combinatorics", "number_theory"]: + url = f"{base_url}/{forum}" + posts.extend(scrape_aops_forum(url)) + + # 2. 提取问题和解答 + extracted_data = [] + for post in posts: + # 使用 LLM 提取结构化信息 + prompt = f""" + Extract from this AoPS forum post: + {post['content']} + + Extract: + 1. Problem statement + 2. Solution steps + 3. Final answer + """ + + extraction = llm_extract(prompt) + + extracted_data.append({ + 'problem': extraction['problem'], + 'solution': extraction['solution'], + 'answer': extraction['answer'], + 'source': post['url'] + }) + + # 3. 过滤质量 + filtered_data = filter_quality(extracted_data) + + # 4. 生成 CoT 格式 + cot_data = [] + for item in filtered_data: + cot = generate_cot_from_solution(item['solution']) + cot_data.append({ + 'problem': item['problem'], + 'cot_solution': cot, + 'answer': item['answer'] + }) + + # 5. 生成 TIR 格式 + tir_data = [] + for item in filtered_data: + tir = generate_tir_from_solution(item['solution']) + tir_data.append({ + 'problem': item['problem'], + 'tir_solution': tir, + 'answer': item['answer'] + }) + + return cot_data, tir_data + + +def generate_cot_from_solution(solution): + """ + 从解答生成长思维链 (CoT) + """ + prompt = f""" + Convert this solution into a step-by-step chain-of-thought explanation: + + Solution: {solution} + + Make sure to: + 1. Explain each step clearly + 2. Show your work + 3. Explain why we take each step + """ + + return llm_generate(prompt) + + +def generate_tir_from_solution(solution): + """ + 从解答生成工具集成推理 (TIR) + """ + prompt = f""" + Convert this solution into a format that includes Python code: + + Solution: {solution} + + Make sure to: + 1. Include Python code for calculations + 2. Explain what the code does + 3. Show intermediate results + """ + + return llm_generate(prompt) +``` + +### 2nd Place 方案 - 代码生成 + 执行流水线 + +**关键洞察：** 先生成 Python 代码，再执行验证 + +```python +def solve_math_with_code_generation(model, problem_text): + """ + 2nd Place (imagination-research) 方法 + + 流水线： + 1. 提示模型生成 Python 代码 + 2. 提取 Python 代码 + 3. 在解释器中执行代码 + 4. 验证结果 + 5. 返回最终答案 + """ + # Step 1: 生成代码 + prompt = f""" + Write a Python program to solve this math problem: + + {problem_text} + + The program should: + 1. Define the problem + 2. Implement the solution + 3. Print the final answer + """ + + response = model.generate(prompt) + python_code = extract_python_code(response) + + # Step 2: 执行代码 + result = execute_python_code(python_code) + + # Step 3: 提取答案 + answer = extract_answer_from_output(result) + + return answer + + +def extract_python_code(text): + """ + 从响应中提取 Python 代码 + """ + import re + pattern = r'```python\n(.*?)\n```' + match = re.search(pattern, text, re.DOTALL) + if match: + return match.group(1) + + # 备选：找 indented 代码块 + lines = text.split('\n') + code_lines = [] + in_code_block = False + indent_level = 0 + + for line in lines: + if '```' in line: + in_code_block = not in_code_block + elif in_code_block: + code_lines.append(line) + + return '\n'.join(code_lines) + + +def execute_python_code(code): + """ + 执行 Python 代码并返回输出 + """ + import sys + from io import StringIO + + old_stdout = sys.stdout + old_stderr = sys.stderr + + sys.stdout = StringIO() + sys.stderr = StringIO() + + try: + exec(code, {}) + output = sys.stdout.getvalue() + error = sys.stderr.getvalue() + except Exception as e: + output = "" + error = str(e) + finally: + sys.stdout = old_stdout + sys.stderr = old_stderr + + return output if output else error +``` + +--- + +## Best Practices + +### ARC/抽象推理任务策略 + +| 策略 | 何时使用 | 说明 | +|------|---------|------| +| **Refinement Loops** | 需要逐步优化答案 | 递归改进是智能的核心 (TRM) | +| **合成数据生成** | 原始任务不足时 | 通过组合生成新任务，采样二次方空间 | +| **LLM 微调** | 有基础模型可用 | Qwen-4B 在合成数据上微调 | +| **Test-Time Training** | 每个任务独立 | 在测试时为每个任务单独训练 | +| **进化程序合成** | 需要探索程序空间 | LLM 在搜索轨迹上微调 (SOAR) | +| **极小模型** | 计算受限或追求效率 | TRM (7M), CompressARC (76K) | +| **数据增强** | 任务数量有限时 | 几何变换 + 颜色排列 | +| **Tokenizer 优化** | 词汇表冗余时 | 减少到任务需要的最小 tokens | + +### 抽象推理 vs 传统 NLP + +| 方面 | 传统 NLP | ARC/抽象推理 | +|------|----------|-------------| +| **任务类型** | 分类、序列标注、生成 | 程序合成、推理 | +| **评估方式** | Accuracy/F1/Perplexity | 完全正确才算对 | +| **数据格式** | 文本序列 | 网格变换 | +| **泛化挑战** | 分布偏移 | Out-of-Distribution | +| **训练方式** | 大规模预训练 | 测试时训练为主 | +| **模型大小** | 越大越好 | 越小越高效 (TRM, CompressARC) | + +### 数学推理任务策略 + +| 策略 | 何时使用 | 说明 | +|------|---------|------| +| **代码执行集成** | 需要精确计算 | 纯推理不够，需要 Python 代码执行 | +| **多答案生成 + 投票** | 答案不确定时 | 32 个候选 + 排序投票 | +| **三阶段训练** | 有大量高质量数据时 | CoT → TIR → GenSelect | +| **高质量数据源** | 数据不足时 | 从 AoPS 等专业论坛提取 | +| **小模型竞争力** | 计算受限时 | 1.5B 模型可达有竞争力 | + +### 数学推理 vs 抽象推理 vs 传统 NLP + +| 方面 | 传统 NLP | 数学推理 | 抽象推理 | +|------|----------|---------|-------------| +| **任务类型** | 分类、序列标注 | 数学问题求解 | 程序合成、推理 | +| **输出格式** | 标签、文本 | 数值答案、选项 | 网格变换 | +| **核心挑战** | 语义理解 | 逻辑推理、计算 | 泛化能力 | +| **关键能力** | 语言理解 | 数学知识、推理 | 抽象能力 | +| **解决方案** | 微调 LLM | 代码执行 + GenSelect | Refinement Loops | + +### MARIO 框架详解 + +**核心组件：** + +| 组件 | 功能 | 实现方式 | +|------|------|---------| +| **MA** | Math（数学推理） | 理解问题、生成推理 | +| **RI** | Reasoning + Interpreter | 生成代码、执行、验证 | +| **O** | Open（开源） | 开源模型和数据 | + +**流程：** +``` +问题文本 + ↓ +[LLM 推理 + Python 代码] + ↓ +[沙盒环境执行代码] + ↓ +[执行结果反馈] + ↓ +[迭代优化] + ↓ +最终答案 +``` + +### 数据质量 vs 数量 + +**NVIDIA 发现：** + +| 方面 | 传统方法 | NVIDIA 方法 | +|------|---------|-----------| +| **数据量** | 追求数量 | 质量优先 | +| **数据源** | 通用数据集 | 专业论坛 (AoPS) | +| **质量验证** | 简单过滤 | LLM 提取 + 人工验证 | +| **效果** | 300K 低质量 | 290K 高质量 | + +**OpenMathReasoning 数据集：** +- **问题数量**: ~290K（不是最初宣传的 540K） +- **CoT 格式**: 3.2M 长思维链 +- **TIR 格式**: 1.7M 工具集成推理 +- **来源**: AoPS (Art of Problem Solving) 论坛 + +### GenSelect vs 简单多数投票 + +| 方法 | 准确率 | 计算成本 | 说明 | +|------|--------|----------|------| +| **GenSelect** | 68% (34/50) | 32 × 推理 | 基于排序投票 | +| **简单多数投票** | ~60% | 32 × 推理 | 只选出现最多的 | +| **单次推理** | ~50% | 1 × 推理 | 不生成多次 | + +**GenSelect 优势：** +- 考虑推理质量 +- 加权置信度 +- 处理答案分布不均 + +### 模型大小 vs 性能 + +| 模型 | 参数量 | 性能 | 成本 | +|------|--------|------|------| +| **OpenMath-Nemotron-1.5B** | 1.5B | ~40% | 低 | +| **OpenMath-Nemotron-7B** | 7B | ~50% | 中 | +| **OpenMath-Nemotron-14B** | 14B | ~60% | 高 | +| **OpenMath-Nemotron-32B** | 32B | 68% | 最高 | +| **DeepSeek-R1** | ~? | ~70% | 未知 | + +**结论：** 小模型（1.5B）在有良好训练的情况下可达有竞争力的性能 + +### AoPS 数据提取策略 + +**关键步骤：** + +1. **论坛选择** + - Algebra（代数） + - Combinatorics（组合） + - Number Theory（数论） + +2. **质量指标** + - 回答质量（被选为最佳回答） + - 推理完整性 + - 可验证性 + +3. **LLM 提取** + - 问题陈述 + - 解决步骤 + - 最终答案 + - 结构化格式 + +4. **过滤策略** + - 移除低质量解答 + - 验证数学正确性 + - 去重 + +### 代码执行安全 + +**沙盒环境要求：** + +| 方面 | 要求 | +|------|------| +| **隔离** | 独立进程，不污染主环境 | +| **超时** | 10 秒执行时间限制 | +| **资源限制** CPU、内存、磁盘限制 | +| **网络** | 禁止网络访问 | +| **文件系统** | 临时文件，只读访问 | + +**实现方式：** +- Docker 容器 +- subprocess + resource limits +- 云端执行环境 + +### 前沿模型的进展 + +**竞赛期间（2024-08）：** +- Claude Sonnet: ~30% +- GPT-4o: ~35% + +**竞赛结束后（2024-12）：** +- Gemini 2 Pro: ~50% +- DeepSeek-R1: ~70% +- Claude Opus: ~65% + +**原因：** +- 前沿模型在数学数据上预训练 +- 代码生成能力增强 +- 推理能力提升 + +--- + +### 前排方案技术细节（Top 12+） + +#### 微调方法总结 + +| 方法 | 使用队伍 | 效果 | 说明 | +|------|---------|------|------| +| **SFT** | 几乎所有队伍 | 基础必备 | 使用 OpenR1 Math, Light-R1, 自定义数据集 | +| **DPO** | 2nd place | 长度优化 | 第 2 阶段减少输出长度，保持推理能力 | +| **TIR** | 1st place | 核心创新 | 训练模型使用外部工具（Python 沙盒） | +| **GRPO** | 9th place | 效率提升（不稳定） | 奖励优化到一定程度后"灾难性偏移" | + +**微调方法对比：** + +1. **SFT (Supervised Fine-Tuning)** - 基础起点 + - 数据集：OpenR1 Math, Light-R1, 自定义数学问题 + - 目标：学习数学推理模式 + - 阶段：几乎所有队伍的第一阶段 + +2. **DPO (Direct Preference Optimization)** - 第 2 名使用 + - 目标：减少输出长度（提升效率） + - 数据构建：基于正确性、长度比、最小长度、相似性 + - 效果：第 2 阶段有效减少输出长度 + +3. **TIR (Tool-Integrated Reasoning)** - 第 1 名核心 + - 目标：集成外部工具（Python 代码执行） + - 效果：显著提升计算精度和推理能力 + - 数据：OpenMathReasoning (1.7M TIR 格式) + +4. **GRPO (Generative Reinforcement Preference Optimization)** - 第 9 名尝试 + - 目标：用更少 tokens 达到准确结论 + - 奖励函数：格式正确性、余弦相似性、长度奖励 + - 结果：优化到一定程度后出现"灾难性偏移"，需使用早期 checkpoint + +#### 推理策略总结 + +| 策略 | 使用队伍 | 效果 | 说明 | +|------|---------|------|------| +| **Self-consistency** | 1st, 2nd, 3rd, 5th, 11th, 17th | 标配 | 生成多个解，取最频繁答案 | +| **Early Stopping (Sample)** | 2nd | 节省 tokens | 找到答案或生成代码后立即停止 | +| **Early Stopping (Question)** | 1st, 2nd, 3rd, 11th, 17th | 节省时间 | 早期共识出现后停止整个问题生成 | +| **Time Management** | 多个队伍 | 动态资源分配 | 根据剩余时间/问题难度调整参数 | + +**Self-consistency 实现：** +```python +def self_consistency_solve(model, problem, n_samples=32): + """ + 自一致性求解：生成多个解，取最频繁答案 + """ + answers = [] + for _ in range(n_samples): + ans = model.generate(problem) + answers.append(ans) + + # 多数投票 + from collections import Counter + counter = Counter(answers) + return counter.most_common(1)[0][0] +``` + +**Early Stopping 变体（1st Place）：** +```python +def early_stopping_genselect(model, problem, n_candidates=32): + """ + 第 1 名的 Early Stopping 策略 + 如果前 5 个生成中有 4 个相同，取消剩余生成 + """ + answers = [] + for i in range(n_candidates): + ans = model.generate(problem) + answers.append(ans) + + # Early stopping check + if i >= 4: + from collections import Counter + counter = Counter(answers) + most_common_count = counter.most_common(1)[0][1] + if most_common_count >= 4: + break # 提前停止 + + return counter.most_common(1)[0][0] +``` + +#### 推理引擎对比 + +| 引擎 | 使用队伍 | 优势 | 劣势 | +|------|---------|------|------| +| **vLLM** | 4th, 7th, 8th, 11th, 17th | 最常用，成熟 | 默认配置可能不够优化 | +| **lmdeploy** | 2nd, 5th, 7th | 高吞吐量 | 配置相对复杂 | +| **TensorRT-LLM** | 1st | 最优性能 | 需要专业优化 | + +#### 量化技术 + +| 量化方法 | 使用队伍 | 效果 | 说明 | +|---------|---------|------|------| +| **AWQ 4-bit** | 几乎所有队伍 | 平衡性能和效率 | Activation-aware Weight Quantization | +| **FP8** | 1st place | 进一步优化 | 第 1 名使用 | +| **8-bit KV cache** | 2nd, 7th | 节省内存 | KV cache 量化 | + +**AWQ 原理：** +- 不是所有权重都同等重要 +- 识别被大激活值乘以的关键权重 +- 保护这些关键权重，牺牲不重要的权重 +- 结果：更小、更快的模型，性能几乎不变 + +#### Prompt Engineering 最佳实践 + +**1. System Prompts（角色设置）：** + +```python +# 基础版 +"You are a helpful math assistant." + +# 更权威（8th Place 风格） +"You are an expert in solving AIMO-level mathematics problems. Your goal is to solve the following problem with high accuracy and minimal reasoning steps." + +# 行为 + 模型特定（Fast-Math-R1-14B） +"You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step..." + +# 特定特质（21st Place 教师模型） +"You are the most powerful math expert. Please solve the problems with deep reasoning. You are careful and always recheck your deductions. You will never give an answer directly until you have enough confidence." +``` + +**2. User Instructions（任务定义）：** + +```python +# 核心输出格式（通用） +""" +You must put the final answer in \\boxed{}. +If the final answer is greater than 1000, then take the modulo of 1000. +""" + +# 鼓励 CoT（2nd Place） +""" +You excel at reasoning. +Think carefully and thoroughly, avoid duplication. +""" + +# 鼓励代码输出（2nd Place） +""" +You excel at coding. +You must provide the python code, avoid redundant analysis. +The answer must be integer. +There is only one answer for each question. +Import necessary libraries. +""" + +# 特定行动序列（8th Place） +""" +1. Read the problem carefully and identify the key components. +2. Plan your approach in 1-2 concise steps, focusing on the most efficient method. +3. Execute the solution with clear, logical reasoning, but limit your reasoning to a maximum of 1-2 steps. +4. Verify your answer for correctness by double-checking each step before finalizing. +5. Provide the final answer in a boxed format... and stop further reasoning. +""" +``` + +**3. Few-Shot / One-Shot Prompts（11th Place）：** + +```python +# One-shot prompting 示例 +system_prompt = """ +You are a Python code assistant. You will be given a mathematical problem that has integer solutions. Your task is to convert this complex math problem into Python code. Let's have Python do the tedious calculations for us! + +- There are multiple ways to solve this problem, so find the most efficient one. +- The final answer should be an integer. +- The final answer should be modulo 1000. +- Please return Python code only following the format below. +""" + +few_shot_example = """ +```python +import math + +# Intermediate calculations +result = ... +print(result % 1000) +``` +""" +``` + +**4. Multi-Stage Prompting（17th Place）：** + +```python +# Stage 1: Initial thought +stage1_output = model.generate(f"{problem}\nThink step by step:") + +# Stage 2: Code generation +stage2_prompt = f""" +Problem: {problem} +Previous thought: {stage1_output} + +Please make a short summary of your approach, including python code. +""" +stage2_output = model.generate(stage2_prompt) + +# Stage 3: Error fixing (if needed) +if execution_failed: + stage3_prompt = f""" +Problem: {problem} +Previous code: {stage2_output} +Error: {error_message} + +Please fix the code. +""" + stage3_output = model.generate(stage3_prompt) +``` + +#### 模型选择建议 + +**前排方案共识：** + +1. **DeepSeek-R1-Distill-Qwen-14B AWQ** 是最受欢迎的选择 + - 4-bit 量化，内存效率高 + - 推理能力强 + - 推理速度快 + +2. **Qwen2.5-14B** 是第 1 名的基础模型 + - 更强的推理能力 + - 需要更多优化 + +3. **模型大小选择：** + - 14B AWQ：最佳平衡（3rd-22nd） + - 32B AWQ：更大但更慢（20th） + - 7B AWQ：更快但精度略低 + +--- + +## Metadata + +| Source | Date | Tags | +|--------|------|------| +| [ARC Prize 2025](https://www.kaggle.com/competitions/arc-prize-2025) | 2025-01-22 | 抽象推理, Refinement Loops, 合成数据, Test-Time Training, TRM, SOAR, CompressARC | +| [AI Mathematical Olympiad Progress Prize 2](https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-2) | 2025-01-22 | 数学推理, MARIO, 代码执行集成, OpenMathReasoning, GenSelect, 三阶段训练, AoPS | +| [Eedi - Mining Misconceptions in Mathematics](https://www.kaggle.com/competitions/eedi-mining-misconceptions-in-mathematics) | 2024-09 | 教育 AI, 误解检测, 检索+重排, Qwen LLM, Distractor prediction,亲和度预测 | +| [MAP - Charting Student Math Misunderstandings](https://www.kaggle.com/competitions/map-charting-student-math-misunderstandings) | 2025-01-22 | 教育 AI, 误解检测, MiRAGE, Shared-prefix attention, Soft labels, Multi-task learning, CoT distillation, Ensemble fusion, Eedi 后续竞赛 | diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/arc-prize-2025.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/arc-prize-2025.md new file mode 100644 index 0000000..b6546ca --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/arc-prize-2025.md @@ -0,0 +1,1732 @@ +# ARC Prize 2025 +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### ARC Prize 2025 (2025) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/arc-prize-2025) | [Official Analysis](https://arcprize.org/blog/arc-prize-2025-results-analysis) +**Category:** NLP/LLM (抽象推理/程序合成) +**Key Techniques:** +- **Refinement Loops**：递归优化是 2025 年的核心主题 +- **合成数据生成**：260,000 个合成任务从 3,000 个基础描述组合 +- **LLM 微调**：Qwen-4B 在合成数据上微调 +- **Tiny Recursive Model (TRM)**：7M 参数实现递归推理 +- **进化程序合成**：LLM 在搜索轨迹上微调 (SOAR) +- **Test-Time Training (TTT)**：在测试时训练 +- **Tokenizer 优化**：减少到 16 tokens (digits 0-9 + newline/padding) +- **数据增强**：几何变换 + 颜色排列 (factorial-10 × 8) + +**Results:** NVARC 24.03% (1st), TRM 45% on ARC-AGI-1, SOAR 52% on ARC-AGI-1 + +#### 前排方案详细技术分析 + +**1st Place - NVARC - 24.03% (ARC-AGI-2)** + +核心技巧： +- **合成数据生成**：从 3,000 基础描述生成 260,000 合成任务 +- **Qwen-4B 微调**：在合成数据上微调，而非预训练大模型 +- **Tokenizer 优化**：减少到 16 tokens（0-9 + newline/padding） +- **Refinement Loop**：递归优化改进预测 +- **数据增强**：几何变换（旋转、翻转）× 10! 颜色排列 + +实现细节： +- 基础数据：Human-ARC (1K+) + BARC (600) = ~1,600 原始任务 +- 合成策略：从 3,000 基础描述采样 2 个组合生成新任务 +- Qwen-4B：4B 参数，相比前沿模型小 1000 倍 +- 成本：~$0.20/task，远低于前沿模型的 $30-$60/task +- 最终成绩：24.03% (ARC-AGI-2), 54% (ARC-AGI-1 with refinement) + +**2nd Place - the ARChitects - 16.53%** + +核心技巧： +- **Masked-Diffusion LLM**：扩散模型用于程序合成 +- **Masked 语言建模**：自回归生成程序 +- **多阶段生成**：粗略想法 → 精细程序 +- **验证机制**：执行生成程序验证正确性 + +实现细节： +- Diffusion 模型：逐步去噪生成程序 +- Masked LM：类似 BERT 的掩码语言建模 +- 两阶段：先生成高级描述，再生成具体代码 +- 验证：在示例上执行生成程序 + +**3rd Place - MindsAI - 12.64%** + +核心技巧： +- **Test-Time Fine-Tuning (TTFT)**：在测试时微调每个任务 +- **Augmentation Ensemble**：数据增强集成（几何 + 颜色） +- **Tokenizer Dropout**：随机丢弃 token 增强鲁棒性 +- **Pretraining Tricks**：来自前沿模型的预训练技巧 + +实现细节： +- TTFT：每个任务单独训练 20-100 步 +- 增强：旋转（4 种）× 翻转（2 种）× 颜色排列（采样） +- Tokenizer Dropout：随机替换 token 为 [MASK] +- 增强级别：24-256 不同数据源不同增强 + +**Paper Awards (ARC-AGI-1):** + +**1st Paper Award - Tiny Recursive Model (TRM) - 45%** + +核心技巧： +- **递归推理**：16 次迭代改进答案 y +- **极小参数**：7M 参数，无预训练 +- **分别维护状态**：answer y 和 latent z 分开维护 +- **线性复杂度**：O(n) 优于 Transformer 的 O(n²) + +实现细节： +- 迭代：y 和 z 分别更新，y 更新一次，z 更新 3 次 +- 参数：7M，d_model=512, n_heads=8 +- 无预训练：随机初始化训练 +- 最终成绩：45% (ARC-AGI-1) + +**2nd Paper Award - SOAR (Self-Improving Language Models) - 52%** + +核心技巧： +- **进化程序合成**：进化搜索生成程序 +- **LLM 在轨迹上微调**：在搜索轨迹上微调 LLM +- **迭代改进**：每次迭代改进搜索策略 +- **知识迁移**：从搜索中学到的知识迁移 + +实现细节： +- 进化：遗传算法变异和交叉程序 +- 微调：在搜索轨迹上微调 LLM +- 迭代：多轮进化，每轮改进策略 +- 最终成绩：52% (ARC-AGI-1) + +**3rd Paper Award - CompressARC - 4% (ARC-AGI-2) / 20-34% (ARC-AGI-1)** + +核心技巧： +- **MDL 原理**：最小描述长度，无预训练 +- **VAE 框架**：编码器-解码器架构 +- **Decoder 正则化**：防止过拟合 +- **测试时训练**：每个任务单独训练 + +实现细节： +- 参数：仅 76K 参数 +- VAE：编码器 128 → 64 → 128，解码器镜像 +- 测试时训练：每个任务训练 ~20 分钟 +- 最终成绩：4% (ARC-AGI-2), 20-34% (ARC-AGI-1) + +### ARC Prize 2025 - Abstraction and Reasoning Corpus + +**竞赛背景：** +- **主办方**：ARC Prize Organization (François Chollet, Mike Knoop) +- **目标**：测试 AI 的**抽象推理和泛化能力**，这是 AGI 的核心基准 +- **竞赛主题**：Year of the Refinement Loop（优化循环之年） +- **特殊性质**：不是传统 ML 竞赛，而是**推理能力基准测试** + +**数据集规模：** +- **ARC-AGI-1**: 800 tasks (400 training + 400 evaluation) +- **ARC-AGI-2**: 训练与 ARC-AGI-1 重叠，评估是新的难题 +- **总队伍数**：1,455 teams +- **总提交数**：15,154 entries + +**任务格式：** +``` +输入网格 (训练示例 1-10 对) + ↓ +推断变换规则 + ↓ +应用规则到测试输入 + ↓ +输出网格 +``` + +**评估指标：** +- **准确率**: 完全正确的任务占比（部分正确 = 0 分） +- **成本**: $/task（获胜方案约 $0.20/task，前沿模型 $2-$30/task） +- **泛化能力**: Public/Private 分离，Private 才是真实泛化 + +**关键洞察：** +1. **AI 推理系统**: 2025 年诞生了 AI 推理系统，与 LLM 的发明同等重要 +2. **Refinement = Intelligence**: 优化循环是智能的核心 +3. **知识 vs 推理**: 当前 AI 推理能力受限于模型知识 +4. **Overfitting on Knowledge**: 前沿模型可能"过拟合"了 ARC 数据 + +**前排方案总结：** + +| 排名 | 队伍 | 分数 | 关键技术 | +|------|------|------|---------| +| **1st** | NVARC | 24.03% | 合成数据 + Qwen-4B + TRM | +| **2nd** | the ARChitects | 16.53% | Masked-Diffusion LLM | +| **3rd** | MindsAI | 12.64% | TTFT + Augmentation | + +**Paper Awards:** + +| 排名 | 作者 | 标题 | 成绩 | +|------|------|------|------| +| **1st** | Alexia Jolicoeur-Martineau | Tiny Recursive Model (TRM) | 45% (ARC-AGI-1) | +| **2nd** | Julien Pourcel et al. | SOAR (进化程序合成) | 52% (ARC-AGI-1) | +| **3rd** | Isaac Liao | CompressARC (76K 参数) | 20-34% (ARC-AGI-1) | + +--- + +## Code Templates + +### MiRAGE Framework - 检索引导的多阶段推理 + +**关键洞察：** 通过检索 + 推理 + 重排的三阶段框架，实现高效的误解检测 + +```python +import torch +import torch.nn as nn +from typing import List, Tuple, Dict +import numpy as np + +class MiRAGEFramework: + """ + MiRAGE: Misconception detection with Retrieval-guided + Multi-stage reasoning and Ensemble fusion + + 基于论文: https://arxiv.org/html/2511.01182v1 + + 核心思想： + 1. Retrieval module: 嵌入模型检索语义相似的候选标签 + 2. Reasoning module: CoT 推理生成结构化解释 + 3. Reranking module: 基于推理结果重排候选标签 + 4. Ensemble fusion: 加权融合检索和重排分数 + """ + + def __init__(self, + embedder: nn.Module, + reasoner: nn.Module, + reranker: nn.Module, + alpha: float = 0.7, + beta: float = 0.3, + top_k: int = 25): + """ + Args: + embedder: 嵌入模型（如 MathBERT） + reasoner: 推理模型（如 Qwen3-8B） + reranker: 重排模型（如 Qwen3-7B） + alpha: 重排分数权重 + beta: 检索分数权重 + top_k: 检索候选数量 + """ + self.embedder = embedder + self.reasoner = reasoner + self.reranker = reranker + self.alpha = alpha + self.beta = beta + self.top_k = top_k + + # 缓存数据库嵌入 + self.embed_db = None + self.label_db = None + + def build_embedding_index(self, dataset: List[Dict]): + """ + 构建嵌入索引 + + Args: + dataset: [{"question": str, "answer": str, "explanation": str, "label": str}, ...] + """ + embeddings = [] + labels = [] + + for item in dataset: + # 生成三元组嵌入 + emb = self.embedder.encode( + item["question"], + item["answer"], + item["explanation"] + ) + embeddings.append(emb) + labels.append(item["label"]) + + self.embed_db = torch.stack(embeddings) + self.label_db = labels + + def retrieval_module(self, query: Tuple[str, str, str]) -> List[Tuple[str, float]]: + """ + 检索模块：基于语义相似度检索候选标签 + + Args: + query: (question, answer, explanation) + + Returns: + [(label, score), ...] 按相似度排序 + """ + q, a, e = query + query_emb = self.embedder.encode(q, a, e) + + # 计算与所有数据库条目的相似度 + similarities = torch.matmul(self.embed_db, query_emb) + + # 按标签聚合（取最大相似度） + label_scores = {} + for label, sim in zip(self.label_db, similarities): + if label not in label_scores: + label_scores[label] = sim + else: + label_scores[label] = max(label_scores[label], sim) + + # 排序并返回 top-k + sorted_labels = sorted(label_scores.items(), key=lambda x: x[1], reverse=True) + return sorted_labels[:self.top_k] + + def reasoning_module(self, query: Tuple[str, str, str]) -> str: + """ + 推理模块：生成 CoT 推理链 + + Args: + query: (question, answer, explanation) + + Returns: + reasoning: 结构化推理文本 + """ + q, a, e = query + prompt = f""" +Analyze the following student response to a math problem. + +Question: {q} +Student Answer: {a} +Student Explanation: {e} + +Think step by step: +1. Is the answer correct? +2. Does the explanation contain any misconceptions? +3. If so, what type of misconception is it? + +Provide your reasoning: +""" + reasoning = self.reasoner.generate(prompt) + return reasoning + + def reranking_module(self, + query: Tuple[str, str, str], + reasoning: str, + candidates: List[str]) -> List[Tuple[str, float]]: + """ + 重排模块：基于推理结果重排候选标签 + + Args: + query: (question, answer, explanation) + reasoning: CoT 推理 + candidates: 候选标签列表 + + Returns: + [(label, score), ...] 重排后的标签 + """ + q, a, e = query + reranked_scores = [] + + for label in candidates: + prompt = f""" +Question: {q} +Student Answer: {a} +Student Explanation: {e} + +Reasoning: {reasoning} + +Is the misconception "{label}" consistent with the above analysis? +Answer Yes or No: +""" + # 获取模型输出的 logits + logits = self.reranker.get_logits(prompt) + + # 计算 Yes/No 的 logit 差值 + yes_logit = logits["Yes"] + no_logit = logits["No"] + score = yes_logit - no_logit + + reranked_scores.append((label, score.item())) + + # 按分数排序 + reranked_scores.sort(key=lambda x: x[1], reverse=True) + return reranked_scores + + def ensemble_fusion(self, + retrieval_scores: List[Tuple[str, float]], + rerank_scores: List[Tuple[str, float]]) -> List[Tuple[str, float]]: + """ + 集成融合：加权融合检索和重排分数 + + Args: + retrieval_scores: [(label, retrieval_score), ...] + rerank_scores: [(label, rerank_score), ...] + + Returns: + [(label, fused_score), ...] + """ + # 归一化分数 + retrieval_dict = dict(retrieval_scores) + rerank_dict = dict(rerank_scores) + + all_labels = set(retrieval_dict.keys()) | set(rerank_dict.keys()) + + fused_scores = [] + for label in all_labels: + ret_score = retrieval_dict.get(label, 0) + rerank_score = rerank_dict.get(label, 0) + + # 加权融合 + fused = self.alpha * rerank_score + self.beta * ret_score + fused_scores.append((label, fused)) + + # 排序 + fused_scores.sort(key=lambda x: x[1], reverse=True) + return fused_scores + + def predict(self, query: Tuple[str, str, str]) -> List[Tuple[str, float]]: + """ + 完整预测流程 + + Args: + query: (question, answer, explanation) + + Returns: + [(label, score), ...] 最终预测结果 + """ + # Stage 1: Retrieval + retrieval_results = self.retrieval_module(query) + candidates = [label for label, _ in retrieval_results] + + # Stage 2: Reasoning + reasoning = self.reasoning_module(query) + + # Stage 3: Reranking + rerank_results = self.reranking_module(query, reasoning, candidates) + + # Stage 4: Ensemble fusion + final_results = self.ensemble_fusion(retrieval_results, rerank_results) + + return final_results + + +# 使用示例 +if __name__ == "__main__": + # 假设我们有预训练的模型 + embedder = MathBERTEmbedder() + reasoner = QwenReasoner() + reranker = QwenReranker() + + # 创建 MiRAGE 框架 + miracle = MiRAGEFramework( + embedder=embedder, + reasoner=reasoner, + reranker=reranker, + alpha=0.7, + beta=0.3, + top_k=25 + ) + + # 构建索引 + train_data = load_training_data() + miracle.build_embedding_index(train_data) + + # 预测 + query = ( + "What is 2/3 + 1/6?", + "3/4", + "I added the numerators and denominators: 2+1=3, 3+6=9, so 3/9=1/3. Wait, that's wrong..." + ) + + predictions = miracle.predict(query) + print("Top 3 predictions:") + for label, score in predictions[:3]: + print(f"{label}: {score:.4f}") +``` + +### Shared-Prefix Attention (1st Place) + +**关键洞察：** 将每个标签候选编码为输入 token，使用 FlexAttention masks 让每个 suffix 只关注共享前缀 + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SharedPrefixClassifier(nn.Module): + """ + Shared-Prefix Attention Classifier + MAP Competition 1st Place Solution + + 核心思想： + 1. 将任务重新定义为 suffix classification + 2. 每个标签候选被编码为一个输入 token + 3. 所有候选标签拼接成一个字符串 + 4. 使用 FlexAttention masks 让每个 suffix 只关注共享前缀 + 5. 使用每个 suffix 的最后一个 token 的特征进行分类 + """ + + def __init__(self, model_name: str, num_labels: int): + super().__init__() + self.num_labels = num_labels + + # 加载预训练模型 + from transformers import AutoModel, AutoTokenizer + self.model = AutoModel.from_pretrained(model_name) + self.tokenizer = AutoTokenizer.from_pretrained(model_name) + + # 分类头 + hidden_size = self.model.config.hidden_size + self.classifier = nn.Linear(hidden_size, num_labels) + + def create_flex_attention_mask(self, + prefix_len: int, + suffix_len: int, + num_candidates: int) -> torch.Tensor: + """ + 创建 FlexAttention mask + + 每个 suffix 只能关注共享前缀，不能关注其他 suffix + + Args: + prefix_len: 前缀长度（问题 + 回答） + suffix_len: 每个 suffix 长度 + num_candidates: 候选数量 + + Returns: + attention_mask: [batch, seq_len, seq_len] + """ + total_len = prefix_len + suffix_len * num_candidates + device = self.model.device + + mask = torch.zeros(total_len, total_len, device=device) + + # 前缀可以关注前缀 + mask[:prefix_len, :prefix_len] = 1 + + # 每个 suffix 可以关注前缀 + for i in range(num_candidates): + start = prefix_len + i * suffix_len + end = start + suffix_len + mask[start:end, :prefix_len] = 1 + + return mask.unsqueeze(0) # [1, seq_len, seq_len] + + def forward(self, + question: str, + answer: str, + explanation: str, + candidate_labels: List[str]) -> torch.Tensor: + """ + Forward pass + + Args: + question: 问题文本 + answer: 学生选择的答案 + explanation: 学生的解释 + candidate_labels: 候选误解标签列表 + + Returns: + logits: [batch, num_labels] + """ + # 构建输入 + prefix = f"Question: {question}\nAnswer: {answer}\nExplanation: {explanation}\n\n" + + # 拼接所有候选标签 + suffixes = [] + for label in candidate_labels: + suffixes.append(f"Misconception: {label}") + + # 构建完整输入 + full_text = prefix + "".join(suffixes) + inputs = self.tokenizer(full_text, return_tensors="pt") + input_ids = inputs["input_ids"].to(self.model.device) + + # 计算 prefix 和 suffix 长度 + prefix_len = len(self.tokenizer(prefix)["input_ids"]) + suffix_len = len(self.tokenizer(suffixes[0])["input_ids"]) + + # 创建 attention mask + attention_mask = self.create_flex_attention_mask( + prefix_len, suffix_len, len(candidate_labels) + ) + + # 获取模型输出 + outputs = self.model( + input_ids=input_ids, + attention_mask=attention_mask + ) + hidden_states = outputs.last_hidden_state # [batch, seq_len, hidden] + + # 提取每个 suffix 的最后一个 token + suffix_last_tokens = [] + for i in range(len(candidate_labels)): + pos = prefix_len + (i + 1) * suffix_len - 1 + suffix_last_tokens.append(hidden_states[:, pos, :]) + + # 堆叠所有 suffix 特征 + suffix_features = torch.stack(suffix_last_tokens, dim=1) # [batch, num_labels, hidden] + + # 分类 + logits = self.classifier(suffix_features) # [batch, num_labels, num_labels] + + # 取对角线（每个 candidate 对应自己的 logit） + batch_size = logits.size(0) + logits = logits[range(batch_size), range(len(candidate_labels)), :] + + return logits + + +# 使用示例 +if __name__ == "__main__": + classifier = SharedPrefixClassifier("microsoft/deberta-v3-large", num_labels=2587) + + question = "What is 2/3 + 1/6?" + answer = "3/4" + explanation = "I added the numerators and denominators." + + # 候选标签（从检索模块获得） + candidates = [ + "Adds denominators when adding fractions", + "Incorrectly adds numerators and denominators", + "Misunderstands fraction addition", + # ... more candidates + ] + + logits = classifier(question, answer, explanation, candidates) + probs = F.softmax(logits, dim=-1) + + # Top-3 预测 + top3_probs, top3_indices = torch.topk(probs, 3) + for prob, idx in zip(top3_probs[0], top3_indices[0]): + print(f"{candidates[idx]}: {prob:.4f}") +``` + +### Multi-Loss Training with Soft Labels (2nd Place) + +**关键洞察：** 使用软标签（soft labels）进行训练，减少标签模糊性的影响 + +```python +import torch +import torch.nn as nn +from typing import List, Dict + +class MultiLossTrainer: + """ + Multi-Loss Training with Soft Labels + MAP Competition 2nd Place Solution + + 核心思想： + 1. 生成软标签：平均多个模型的预测 + 2. 多损失训练：结合 hard labels 和 soft labels + 3. 解决标签模糊性问题 + """ + + def __init__(self, model: nn.Module, num_labels: int): + self.model = model + self.num_labels = num_labels + + # 损失函数 + self.ce_loss = nn.CrossEntropyLoss() + self.kl_loss = nn.KLDivLoss(reduction="batchmean") + + def generate_soft_labels(self, + models: List[nn.Module], + dataloader: torch.utils.data.DataLoader, + device: str) -> torch.Tensor: + """ + 生成软标签 + + Args: + models: 用于生成软标签的模型列表 + dataloader: 数据加载器 + device: 设备 + + Returns: + soft_labels: [num_samples, num_labels] + """ + all_soft_labels = [] + + for batch in dataloader: + input_ids = batch["input_ids"].to(device) + attention_mask = batch["attention_mask"].to(device) + + # 收集所有模型的预测 + all_probs = [] + for model in models: + with torch.no_grad(): + outputs = model(input_ids, attention_mask=attention_mask) + probs = torch.softmax(outputs.logits, dim=-1) + all_probs.append(probs) + + # 平均所有模型的预测 + soft_labels = torch.stack(all_probs).mean(dim=0) + all_soft_labels.append(soft_labels.cpu()) + + return torch.cat(all_soft_labels, dim=0) + + def compute_loss(self, + logits: torch.Tensor, + hard_labels: torch.Tensor, + soft_labels: torch.Tensor, + alpha: float = 0.5, + temperature: float = 2.0) -> torch.Tensor: + """ + 计算多损失 + + Args: + logits: 模型输出 [batch, num_labels] + hard_labels: 真实标签 [batch] + soft_labels: 软标签 [batch, num_labels] + alpha: hard loss 权重 + temperature: soft label 温度 + + Returns: + loss: 总损失 + """ + # Hard loss (交叉熵) + hard_loss = self.ce_loss(logits, hard_labels) + + # Soft loss (KL 散度) + log_probs = torch.log_softmax(logits / temperature, dim=-1) + soft_labels_smooth = soft_labels / temperature + soft_loss = self.kl_loss(log_probs, soft_labels_smooth) * (temperature ** 2) + + # 组合损失 + total_loss = alpha * hard_loss + (1 - alpha) * soft_loss + + return total_loss + + def train_epoch(self, + train_loader: torch.utils.data.DataLoader, + soft_labels: torch.Tensor, + optimizer: torch.optim.Optimizer, + device: str): + """ + 训练一个 epoch + + Args: + train_loader: 训练数据加载器 + soft_labels: 预生成的软标签 + optimizer: 优化器 + device: 设备 + """ + self.model.train() + total_loss = 0 + + for batch_idx, batch in enumerate(train_loader): + input_ids = batch["input_ids"].to(device) + attention_mask = batch["attention_mask"].to(device) + hard_labels = batch["labels"].to(device) + + # 获取对应的软标签 + start_idx = batch_idx * train_loader.batch_size + end_idx = start_idx + len(hard_labels) + batch_soft_labels = soft_labels[start_idx:end_idx].to(device) + + # Forward + outputs = self.model(input_ids, attention_mask=attention_mask) + logits = outputs.logits + + # 计算损失 + loss = self.compute_loss(logits, hard_labels, batch_soft_labels) + + # Backward + optimizer.zero_grad() + loss.backward() + optimizer.step() + + total_loss += loss.item() + + return total_loss / len(train_loader) + + +# 使用示例 +if __name__ == "__main__": + from transformers import AutoModelForSequenceClassification + + # 创建模型 + model = AutoModelForSequenceClassification.from_pretrained( + "microsoft/deberta-v3-large", + num_labels=2587 + ) + + # 创建训练器 + trainer = MultiLossTrainer(model, num_labels=2587) + + # 生成软标签（使用多个预训练模型） + teacher_models = [ + AutoModelForSequenceClassification.from_pretrained("teacher1"), + AutoModelForSequenceClassification.from_pretrained("teacher2"), + AutoModelForSequenceClassification.from_pretrained("teacher3"), + ] + + soft_labels = trainer.generate_soft_labels(teacher_models, train_loader, "cuda") + + # 训练 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-5) + for epoch in range(3): + loss = trainer.train_epoch(train_loader, soft_labels, optimizer, "cuda") + print(f"Epoch {epoch}, Loss: {loss:.4f}") +``` + +### Auxiliary Task Training (3rd Place) + +**关键洞察：** 同时训练多个辅助任务（正确性、推理错误类型），提升主任务性能 + +```python +import torch +import torch.nn as nn +from typing import Dict, Tuple + +class AuxiliaryTaskModel(nn.Module): + """ + Auxiliary Task Model + MAP Competition 3rd Place Solution + + 核心思想： + 1. 主任务：预测误解类型 + 2. 辅助任务 1：预测答案是否正确 + 3. 辅助任务 2：预测推理错误类型 + 4. 多任务学习提升性能 + """ + + def __init__(self, + encoder_name: str, + num_misconceptions: int, + num_error_types: int): + super().__init__() + + from transformers import AutoModel + + # 共享编码器 + self.encoder = AutoModel.from_pretrained(encoder_name) + hidden_size = self.encoder.config.hidden_size + + # 任务特定头 + self.misconception_head = nn.Linear(hidden_size, num_misconceptions) + self.correctness_head = nn.Linear(hidden_size, 2) # Binary: correct/incorrect + self.error_type_head = nn.Linear(hidden_size, num_error_types) + + # Dropout + self.dropout = nn.Dropout(0.1) + + def forward(self, + input_ids: torch.Tensor, + attention_mask: torch.Tensor) -> Dict[str, torch.Tensor]: + """ + Forward pass with multiple outputs + + Args: + input_ids: [batch, seq_len] + attention_mask: [batch, seq_len] + + Returns: + outputs: { + "misconception_logits": [batch, num_misconceptions], + "correctness_logits": [batch, 2], + "error_type_logits": [batch, num_error_types] + } + """ + # 编码 + outputs = self.encoder(input_ids=input_ids, attention_mask=attention_mask) + pooled = outputs.last_hidden_state[:, 0, :] # [CLS] token + pooled = self.dropout(pooled) + + # 多任务输出 + misconception_logits = self.misconception_head(pooled) + correctness_logits = self.correctness_head(pooled) + error_type_logits = self.error_type_head(pooled) + + return { + "misconception_logits": misconception_logits, + "correctness_logits": correctness_logits, + "error_type_logits": error_type_logits + } + + +class MultiTaskTrainer: + """ + Multi-task Training + """ + + def __init__(self, + model: AuxiliaryTaskModel, + alpha: float = 1.0, + beta: float = 0.5, + gamma: float = 0.3): + """ + Args: + model: 多任务模型 + alpha: 主任务权重 + beta: 辅助任务 1 权重 + gamma: 辅助任务 2 权重 + """ + self.model = model + self.alpha = alpha + self.beta = beta + self.gamma = gamma + + # 损失函数 + self.ce_loss = nn.CrossEntropyLoss() + + def compute_loss(self, + outputs: Dict[str, torch.Tensor], + misconception_labels: torch.Tensor, + correctness_labels: torch.Tensor, + error_type_labels: torch.Tensor) -> Tuple[torch.Tensor, Dict[str, float]]: + """ + 计算多任务损失 + + Args: + outputs: 模型输出 + misconception_labels: 误解标签 [batch] + correctness_labels: 正确性标签 [batch] + error_type_labels: 错误类型标签 [batch] + + Returns: + total_loss: 总损失 + loss_dict: 各任务损失 + """ + # 主任务损失 + misconception_loss = self.ce_loss( + outputs["misconception_logits"], + misconception_labels + ) + + # 辅助任务 1：正确性 + correctness_loss = self.ce_loss( + outputs["correctness_logits"], + correctness_labels + ) + + # 辅助任务 2：错误类型 + error_type_loss = self.ce_loss( + outputs["error_type_logits"], + error_type_labels + ) + + # 总损失 + total_loss = ( + self.alpha * misconception_loss + + self.beta * correctness_loss + + self.gamma * error_type_loss + ) + + loss_dict = { + "misconception": misconception_loss.item(), + "correctness": correctness_loss.item(), + "error_type": error_type_loss.item(), + "total": total_loss.item() + } + + return total_loss, loss_dict + + +# 使用示例 +if __name__ == "__main__": + # 创建模型 + model = AuxiliaryTaskModel( + encoder_name="microsoft/deberta-v3-large", + num_misconceptions=2587, + num_error_types=10 + ) + + # 创建训练器 + trainer = MultiTaskTrainer(model, alpha=1.0, beta=0.5, gamma=0.3) + + # 训练步骤 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-5) + + for batch in train_loader: + input_ids = batch["input_ids"].cuda() + attention_mask = batch["attention_mask"].cuda() + misconception_labels = batch["misconception_labels"].cuda() + correctness_labels = batch["correctness_labels"].cuda() + error_type_labels = batch["error_type_labels"].cuda() + + # Forward + outputs = model(input_ids, attention_mask) + + # Compute loss + loss, loss_dict = trainer.compute_loss( + outputs, misconception_labels, correctness_labels, error_type_labels + ) + + # Backward + optimizer.zero_grad() + loss.backward() + optimizer.step() + + print(f"Losses: {loss_dict}") +``` + +### Tiny Recursive Model (TRM) - 递归推理 + +**关键洞察：** 用极小参数（7M）实现递归推理，通过多次迭代改进答案 + +```python +import torch +import torch.nn as nn + +class TinyRecursiveModel(nn.Module): + """ + Tiny Recursive Model (TRM) + Paper: "Less is More: Recursive Reasoning with Tiny Networks" + Alexia Jolicoeur-Martineau, ARC Prize 2025 Paper Award 1st Place + + 核心思想： + - 递归地改进预测答案 y + - 分别维护 answer 和 latent 状态 + - 通过多次迭代逐步优化（类似思维链） + """ + def __init__(self, d_model=512, n_heads=8, n_iterations=16): + super().__init__() + self.d_model = d_model + self.n_heads = n_heads + self.n_iterations = n_iterations + + # Embedding layers + self.embed_x = nn.Linear(10, d_model) # input grid embedding (10 colors) + self.embed_y = nn.Linear(10, d_model) # output grid embedding + self.embed_z = nn.Linear(10, d_model) # latent embedding + + # Single transformer block (iterated, not stacked) + self.attention = nn.MultiheadAttention(d_model, n_heads, batch_first=True) + self.ffn = nn.Sequential( + nn.Linear(d_model, 4 * d_model), + nn.GELU(), + nn.Linear(4 * d_model, d_model) + ) + self.norm1 = nn.LayerNorm(d_model) + self.norm2 = nn.LayerNorm(d_model) + + # Output heads + self.head_y = nn.Linear(d_model, 10) # update answer + self.head_z = nn.Linear(d_model, 10) # update latent + + def forward(self, x, y_init=None, z_init=None): + """ + Args: + x: input grid (batch, seq_len, 10) + y_init: initial answer (random if None) + z_init: initial latent (random if None) + + Returns: + y: refined answer (batch, seq_len, 10) + """ + batch_size, seq_len, _ = x.shape + + # Initialize + y = y_init if y_init is not None else torch.randn_like(x) + z = z_init if z_init is not None else torch.randn(batch_size, seq_len, self.d_model) + + # Embed inputs + h_x = self.embed_x(x) # (batch, seq_len, d_model) + h_y = self.embed_y(y) # (batch, seq_len, d_model) + + # Iterative refinement + for iteration in range(self.n_iterations): + # Combine context: input + current answer + latent + h = h_x + h_y + self.permute_to_latent(z) + + # Single transformer block + h_norm = self.norm1(h) + attn_out, _ = self.attention(h_norm, h_norm, h_norm) + h = h + attn_out + + h_norm = self.norm2(h) + ffn_out = self.ffn(h_norm) + h = h + ffn_out + + # Update latent z (n times) + for _ in range(3): # recursive reasoning + z = z + self.head_z(h) + + # Update answer y (once) + y_delta = self.head_y(h) + y = y + y_delta + h_y = self.embed_y(y) + + return y + + def permute_to_latent(self, z): + """Permute latent to match input shape""" + return z # simplify for example +``` + +### 合成数据生成 - GPT-OSS 方法 + +**关键洞察：** 从现有任务生成新任务，通过组合实现二次方空间采样 + +```python +import openai + +def generate_synthetic_puzzles(base_descriptions, n_generate=260000): + """ + 使用 GPT-OSS 从基础描述生成合成任务 + NVARC 团队方法：从 3,000 基础描述生成 260,000 合成任务 + + Args: + base_descriptions: 基础任务描述列表 + n_generate: 要生成的任务数 + + Returns: + generated_tasks: 生成的任务列表 + """ + generated_tasks = [] + + # 采样二次方组合空间 + # 从 3,000 基础描述完整组合是 9M，采样 260K 是有意义的子集 + for i in range(n_generate): + # 随机选择 2 个基础描述 + desc1 = base_descriptions[i % len(base_descriptions)] + desc2 = base_descriptions[(i + 1) % len(base_descriptions)] + + # 组合描述 + combined_prompt = f""" + Combine these two ARC tasks: + + Task 1: {desc1} + Task 2: {desc2} + + Generate a new task that combines concepts from both. + Output format: + - Input grid generation code + - Transformation code + """ + + # 使用 GPT 生成 + response = openai.chat.completions.create( + model="gpt-4o", + messages=[{"role": "user", "content": combined_prompt}], + temperature=0.7 + ) + + generated_tasks.append(response.choices[0].message.content) + + return generated_tasks + + +def verify_generated_puzzles(tasks, min_valid_grids=30): + """ + 验证生成的任务质量 + + NVARC 方法： + 1. 生成输入网格代码 + 单元测试 + 2. 至少 30 个有效网格通过测试 + 3. 生成 20 种变换实现 + 4. 至少 8/20 产生相同输出 + """ + valid_tasks = [] + + for task in tasks: + # 执行生成的代码 + input_grids = generate_input_grids(task['input_code']) + + # 验证网格约束 + if len(input_grids) < min_valid_grids: + continue + + # 生成多种变换实现 + transformations = [] + for _ in range(20): + transform_result = execute_transformation(task['transform_code'], input_grids[0]) + transformations.append(transform_result) + + # 检查共识 + if check_consensus(transformations, threshold=8): + valid_tasks.append(task) + + return valid_tasks + + +def check_consensus(results, threshold=8): + """ + 检查是否至少 threshold 个结果相同 + """ + from collections import Counter + counts = Counter(results) + return counts.most_common(1)[0][1] >= threshold +``` + +### Tokenizer 优化 - 16 Tokens + +**关键洞察：** ARC 只需要 10 个颜色 + 格式 tokens，大幅减少 tokenizer + +```python +from transformers import AutoTokenizer, AutoModelForVision2Seq + +def optimize_arc_tokenizer(model_name="Qwen/Qwen2-VL-7B-Instruct"): + """ + 优化 tokenizer 用于 ARC 任务 + NVARC 方法：从 150K tokens 减少到 16 tokens + + ARC 只需要： + - 10 个颜色 (0-9) + - 新行符 + - 输入开始标记 + - 输出开始标记 + - 填充 + """ + # 加载原始 tokenizer + tokenizer = AutoTokenizer.from_pretrained(model_name) + + # 定义 ARC 词汇表 + arc_vocab = { + '0': 0, '1': 1, '2': 2, '3': 3, '4': 4, + '5': 5, '6': 6, '7': 7, '8': 8, '9': 9, # colors + '\\n': 10, # newline + '': 11, # input start + '': 12, # output start + '': 13, # padding + } + + # Patch embedding table + model = AutoModelForVision2Seq.from_pretrained(model_name) + original_embed = model.model.model.embed_tokens + new_embed = nn.Embedding(16, original_embed.embedding_dim) + + # 复制相关 tokens + for token, idx in arc_vocab.items(): + original_idx = tokenizer.convert_tokens_to_ids(token) + if original_idx is not None: + new_embed.weight[idx] = original_embed.weight[original_idx] + + # 替换 embedding 层 + model.model.model.embed_tokens = new_embed + + return tokenizer, model +``` + +### Test-Time Training (TTT) + +**关键洞察：** 在测试时训练模型，每个任务单独训练 + +```python +import torch +import torch.nn as nn + +def test_time_training(model, train_examples, test_input, n_steps=100, lr=0.001): + """ + Test-Time Training (TTT) + MindsAI 方法：在测试时训练模型 + + Args: + model: 基础模型 + train_examples: 训练示例 (input, output) 对列表 + test_input: 测试输入 + n_steps: 训练步数 + lr: 学习率 + + Returns: + prediction: 对测试输入的预测 + """ + optimizer = torch.optim.Adam(model.parameters(), lr=lr) + criterion = nn.MSELoss() + + # 训练阶段 + for step in range(n_steps): + total_loss = 0 + + for x, y in train_examples: + # 前向传播 + pred = model(x) + + # 计算损失 + loss = criterion(pred, y) + total_loss += loss + + # 反向传播 + optimizer.zero_grad() + total_loss.backward() + optimizer.step() + + # 预测阶段 + with torch.no_grad(): + prediction = model(test_input) + + return prediction + + +# MindsAI 的完整 TTT pipeline +def tft_with_augmentation(model, train_examples, test_input): + """ + TTFT + Augmentation Ensemble + + MindsAI 方法： + 1. Test-Time Fine-Tuning + 2. 数据增强集成（旋转、翻转、颜色排列） + 3. Tokenizer Dropout + """ + # 1. 数据增强 + augmented_examples = [] + for x, y in train_examples: + # 几何变换 + for rotation in [0, 90, 180, 270]: + x_rot = rotate_grid(x, rotation) + y_rot = rotate_grid(y, rotation) + augmented_examples.append((x_rot, y_rot)) + + x_flip = flip_grid(x_rot) + y_flip = flip_grid(y_rot) + augmented_examples.append((x_flip, y_flip)) + + # 颜色排列（10! = 3.6M，采样一部分） + color_perms = sample_color_permutations(n=10) + for perm in color_perms: + x_perm = apply_color_permutation(x, perm) + y_perm = apply_color_permutation(y, perm) + augmented_examples.append((x_perm, y_perm)) + + # 2. TTT with augmented data + predictions = [] + for _ in range(10): # 10 runs with different augmentation subsets + subset = random_subset(augmented_examples, size=100) + pred = test_time_training(model, subset, test_input) + predictions.append(pred) + + # 3. Ensemble predictions + final_pred = ensemble_predictions(predictions) + + return final_pred +``` + +### 数据增强 - 几何 + 颜色 + +**关键洞察：** 因子级别的数据增强（10! × 8 = 2900 万种） + +```python +import numpy as np +from itertools import permutations + +def augment_arc_task(input_grid, output_grid): + """ + ARC 任务的数据增强 + + NVARC 方法： + - 几何变换：8 种（旋转 4 × 翻转 2） + - 颜色排列：10! = 3,628,800 种 + - 总计：~2900 万种每个任务 + """ + augmented = [] + + # 1. 几何变换 + rotations = [0, 90, 180, 270] + flips = [False, True] + + for rotation in rotations: + for flip in flips: + x_aug = rotate_grid(input_grid, rotation) + if flip: + x_aug = flip_grid(x_aug) + + y_aug = rotate_grid(output_grid, rotation) + if flip: + y_aug = flip_grid(y_aug) + + augmented.append((x_aug, y_aug)) + + # 2. 颜色排列（采样，因为 10! 太大） + color_perms = sample_color_permutations(n=100) + for perm in color_perms: + for x, y in augmented[:8]: # 只对原始 8 个几何变换 + x_perm = apply_color_permutation(x, perm) + y_perm = apply_color_permutation(y, perm) + augmented.append((x_perm, y_perm)) + + return augmented + + +def sample_color_permutations(n=100, seed=42): + """ + 采样颜色排列（10! 太大，无法遍历） + """ + rng = np.random.default_rng(seed) + colors = np.arange(10) + perms = [] + + for _ in range(n): + perm = rng.permutation(colors) + perms.append(perm) + + return perms + + +def apply_color_permutation(grid, perm): + """ + 应用颜色排列到网格 + """ + permuted = grid.copy() + + # 创建映射 + mapping = {i: perm[i] for i in range(10)} + + # 应用映射 + for old_color in range(10): + new_color = mapping[old_color] + permuted[grid == old_color] = new_color + + return permuted +``` + +### SOAR - 进化程序合成 + +**关键洞察：** LLM 在自己的搜索轨迹上微调 + +```python +import openai + +class SOAR: + """ + SOAR: Self-Improving Language Models for Evolutionary Program Synthesis + Julien Pourcel et al., ARC Prize 2025 Paper Award 2nd Place + + 核心思想： + 1. 进化搜索生成程序 + 2. LLM 在搜索轨迹上微调 + 3. 迭代改进 + """ + def __init__(self, base_model="gpt-4"): + self.base_model = base_model + self.search_trajectory = [] + + def evolutionary_search(self, task, n_generations=100): + """ + 进化搜索生成程序 + """ + population = self.initialize_population(task) + + for gen in range(n_generations): + # 评估当前种群 + evaluated = self.evaluate_population(population, task) + + # 选择最好的 + best = sorted(evaluated, key=lambda x: x['fitness'], reverse=True)[:10] + + # 变异和交叉 + offspring = self.mutate_and_crossover(best, task) + + # 记录搜索轨迹 + self.search_trajectory.extend([ + {'generation': gen, 'programs': best, 'task': task} + ]) + + population = offspring + + return best[0] + + def fine_tune_on_trajectories(self, n_epochs=10): + """ + 在搜索轨迹上微调 LLM + """ + # 准备训练数据 + training_data = [] + for trajectory in self.search_trajectory: + for program in trajectory['programs']: + prompt = f""" + Task: {trajectory['task']} + Program: {program['code']} + Fitness: {program['fitness']} + + Generate a better program. + """ + training_data.append({'prompt': prompt, 'completion': program['code']}) + + # 微调（伪代码） + for epoch in range(n_epochs): + for sample in training_data: + response = openai.chat.completions.create( + model=self.base_model, + messages=[{"role": "user", "content": sample['prompt']}], + temperature=0.7 + ) + + # 计算损失并更新（实际需要训练循环） + # loss = compute_loss(response, sample['completion']) + # backward(loss) + + return self.base_model +``` + +### CompressARC - MDL 原理 + +**关键洞察：** 76K 参数，无预训练，仅用 VAE loss + decoder regularization + +```python +import torch +import torch.nn as nn + +class CompressARC(nn.Module): + """ + CompressARC: ARC-AGI Without Pretraining + Isaac Liao, ARC Prize 2025 Paper Award 3rd Place + + 核心思想： + - 仅 76K 参数 + - 无预训练，随机初始化 + - 使用 MDL (Minimum Description Length) 原理 + - VAE loss + decoder regularization + - 测试时训练（每个任务单独训练） + """ + def __init__(self, latent_dim=64, grid_size=30): + super().__init__() + self.latent_dim = latent_dim + self.grid_size = grid_size + + # Encoder: grid -> latent + self.encoder = nn.Sequential( + nn.Linear(10, 128), # 10 colors + nn.ReLU(), + nn.Linear(128, latent_dim * 2) # mean + logvar + ) + + # Decoder: latent -> grid + self.decoder = nn.Sequential( + nn.Linear(latent_dim, 128), + nn.ReLU(), + nn.Linear(128, 10) # 10 colors + ) + + def encode(self, x): + """编码网格到潜在空间""" + h = self.encoder(x) # (batch, latent_dim * 2) + mu, logvar = h.chunk(2, dim=-1) + return mu, logvar + + def decode(self, z): + """从潜在空间解码网格""" + return self.decoder(z) + + def forward(self, x): + """前向传播""" + mu, logvar = self.encode(x) + + # Reparameterization trick + std = torch.exp(0.5 * logvar) + eps = torch.randn_like(std) + z = mu + eps * std + + # Decode + recon_x = self.decode(z) + + return recon_x, mu, logvar + + def loss_function(self, recon_x, x, mu, logvar, beta=0.1): + """ + VAE loss + decoder regularization (MDL principle) + + CompressARC 关键创新：用 VAE 代替组合搜索 + """ + # Reconstruction loss + recon_loss = nn.functional.cross_entropy(recon_x, x) + + # KL divergence + kl_loss = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp()) + + # Decoder regularization (MDL) + decoder_reg = sum(p.pow(2).sum() for p in self.decoder.parameters()) + + # Total loss + total_loss = recon_loss + beta * kl_loss + 0.01 * decoder_reg + + return total_loss + + +def test_time_train_compressarc(task, n_minutes=20): + """ + 测试时训练 CompressARC + 每个 puzzle 单独训练，约 20 分钟在 RTX 4070 上 + """ + model = CompressARC() + optimizer = torch.optim.Adam(model.parameters(), lr=0.001) + + # 训练（直到收敛或超时） + for step in range(10000): # 最多 10K 步 + total_loss = 0 + + for input_grid, output_grid in task['train_examples']: + # 前向传播 + recon, mu, logvar = model(input_grid) + + # 计算损失 + loss = model.loss_function(recon, output_grid, mu, logvar) + total_loss += loss + + # 反向传播 + optimizer.zero_grad() + total_loss.backward() + optimizer.step() + + # 早停检查 + if total_loss < 0.01: + break + + # 预测 + with torch.no_grad(): + test_input = task['test_input'] + recon, mu, logvar = model(test_input) + prediction = recon.argmax(dim=-1) + + return prediction +``` + +### Refinement Loops（优化循环） + +**核心思想：** Refinement = Intelligence（优化即智能） + +**应用场景：** + +| 方法 | 实现 | 适用场景 | +|------|------|---------| +| **递归推理** | TRM: 16 次迭代改进答案 | 需要逐步优化 | +| **进化搜索** | SOAR: 进化 + 微调 LLM | 程序合成 | +| **Test-Time Training** | 在测试时训练 | 每个任务独立 | +| **模型精炼** | 应用层优化 (Poetiq) | 提升基础模型 | + +**NVIDIA Refinement (Poetiq) 示例：** +- 基础: Gemini 3 Pro → 31% +- 精炼后: 54% (+23%) +- 成本: $0.81 → $31 + +### 合成数据生成策略 + +**NVARC 方法：** + +1. **基础数据收集** + - Human-ARC: 1K+ 任务描述 + - BARC: 600 可用任务 + - 总计: ~700 原始任务 + +2. **结构化描述** + - 5 个组件：输入生成、解决步骤、规则总结、关键洞察、概念 + - 使用 Claude/GPT-4o 结构化 + +3. **二次方组合** + - 3,000 基础描述 + - 完整组合: 9M (3,000²) + - 采样: 260K 合成任务 + +4. **质量验证** + - 生成输入代码 + 单元测试 + - 至少 30 个有效网格 + - 20 种实现，8/20 共识 + - 过滤后: ~100K 任务 + +### 模型架构对比 + +| 方法 | 参数量 | 预训练 | 成绩 | 特点 | +|------|--------|--------|------|------| +| **NVARC** | 4B (Qwen) | ✅ | 24% | 合成数据 + 微调 | +| **TRM** | 7M | ❌ | 8% (ARC-AGI-2) | 递归推理，极小模型 | +| **CompressARC** | 76K | ❌ | 4% (ARC-AGI-2) | MDL，无预训练 | +| **SOAR** | 变化 | ❌ | 52% (ARC-AGI-1) | 进化 + 自微调 | +| **ARChitects** | 变化 | ✅ | 16.53% | Masked-Diffusion | + +### 成本效益对比 + +| 方案 | 准确率 (ARC-AGI-2) | 成本 | 性价比 | +|------|---------------------|------|--------| +| **NVARC (获胜)** | 24.03% | $0.20/task | 最高 | +| **Gemini 3 Pro (基线)** | 31% | $0.81/task | 中等 | +| **Gemini 3 Pro (精炼)** | 54% | $31/task | 低 | +| **Claude Opus (精炼)** | ~54% | $60/task | 最低 | +| **GPT-4o (开始)** | 1.9% | - | - | + +### 前沿模型的问题 + +**"Overfitting on Knowledge"（知识过拟合）：** + +**现象：** 前沿模型可能在训练数据上"过拟合"了 ARC +- **证据**：Gemini 3 Deep Think 使用正确的 ARC 颜色映射 +- **原因**：ARC 数据在预训练数据中充分表示 +- **含义**：即使设计良好的 benchmark 也会被"过拟合" + +**解决方案：** +- **ARC-AGI-3**: 新格式，测试交互推理 +- **新任务生成**: 持续更新 benchmark +- **私有数据**: 保持测试集未知 + +### Test-Time Training 最佳实践 + +**何时使用：** +- 每个任务独立 +- 训练示例少（2-10 对） +- 需要快速适应 + +**实现步骤：** +1. 使用训练示例作为 mini-batch +2. 训练 n 步（100-1000） +3. 在测试输入上预测 +4. 可选：数据增强集成 + +**MindsAI TTFT Pipeline：** +1. Test-Time Fine-Tuning +2. Augmentation Ensemble（几何 + 颜色） +3. Tokenizer Dropout +4. Pretraining Tricks + +### 极小模型的优势 + +**TRM (7M 参数)：** +- **效率**: 参数少，推理快 +- **泛化**: 不易过拟合 +- **可解释**: 递归结构清晰 + +**CompressARC (76K 参数)：** +- **无预训练**: 随机初始化 +- **MDL 原理**: 最小描述长度 +- **测试时训练**: 每个任务 20 分钟 + +**结论：** 对于推理任务，小模型 + TTT 可能优于大模型 + +### 数据增强策略 + +**几何变换 (8 种)：** +- 旋转: 0°, 90°, 180°, 270° +- 翻转: 水平、垂直 + +**颜色排列:** +- 10! = 3,628,800 种 +- 实际采样: 100-1000 种 + +**增强策略：** +- **NVARC**: 不同数据源不同增强级别 (24-256) +- **MindsAI**: 采样 + 集成 + +### Tokenizer 优化 + +**为什么优化：** +- 原始: ~150K tokens +- ARC 需要: 16 tokens (10 颜色 + 6 格式) +- 减少: ~99.99% + +**NVARC 方法：** +1. 保留 16 个相关 tokens +2. Patch embedding table +3. 微调时只更新这些 tokens + +### 前沿模型的使用 + +**竞赛开始时 (2025-03)：** +- Claude Sonnet: 1.3% +- GPT-4o: 1.9% + +**竞赛结束后 (2025-11)：** +- Gemini 3: 31% → 54% (精炼) +- Claude Opus: >30% +- Grok: >30% + +**原因：** +- 前沿模型在合成 ARC 数据上预训练 +- 代码生成 + 执行在推理时 + +### 关键数据洞察总结 + +1. **Refinement = Intelligence**: 优化循环是智能的核心 +2. **合成数据是关键**: 从 700 任务生成 260K 合成任务 +3. **极小模型很强大**: TRM (7M), CompressARC (76K) +4. **Test-Time Training 有效**: 每个任务单独训练 +5. **LLM 可以自改进**: SOAR 在搜索轨迹上微调 +6. **Overfitting on Knowledge**: 前沿模型可能"过拟合" ARC +7. **成本差异巨大**: $0.20 vs $60 per task +8. **公共排行榜不可靠**: Public/Private Shake 严重 + +### 抽象推理任务的最佳实践 + +| 方面 | 推荐 | +|------|------| +| **数据准备** | 合成数据生成 + 质量验证 | +| **模型选择** | 小模型 + TTT (TRM, CompressARC) | +| **训练策略** | Test-Time Training | +| **优化方法** | Refinement Loops | +| **数据增强** | 几何变换 + 颜色排列 | +| **Tokenizer** | 优化到最小 tokens | +| **评估** | 使用本地验证，忽略 Public LB | +| **成本控制** | TTT < 模型精炼 < 前沿模型 | + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/eedi-2024.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/eedi-2024.md new file mode 100644 index 0000000..5b55cba --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/eedi-2024.md @@ -0,0 +1,215 @@ +# Eedi - Mining Misconceptions in Mathematics (2024) +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### Eedi - Mining Misconceptions in Mathematics (2024) + +**竞赛背景：** +- **主办方**：The Learning Agency (TLA) +- **目标**：从数学问题中识别学生的误解 +- **应用场景**：教育科技、个性化学习、智能辅导系统 +- **社会意义**：自动化误解检测，帮助教师针对性教学 + +**任务描述：** +从数学问题文本中识别最相关的误解（Misconception）： +- **输入**：数学问题文本 + 4 个选项（1 个正确，3 个错误） +- **输出**：Top 3 最相关的误解类别（2,587 种类型） +- **评估**：MAP@3 (Mean Average Precision at 3) + +**数据集规模：** +- 训练集：1,868 个数学问题 +- 误解类别：2,587 种类型 +- 数据来源：Vanderbilt 专家标注 + +**数据特点：** +1. **多标签问题**：一个问题可能有多个相关的误解 +2. **解释依赖**：需要理解问题的推理过程 +3. **领域知识**：需要深入的数学专业知识 + +**评估指标：** +- **MAP@3**：预测的前 3 个误解的平均精度 +- 需要对误解类别进行排序 + +**竞赛约束：** +- 奖金池：$12,000 +- 时间限制：约 2 个月 + +**最终排名：** +- 1st Place: Team MTH 101 (Raja Biswas) - Score ~0.637 +- 2nd Place: - +- 3rd Place: - + +**技术趋势：** +- **检索增强生成 (RAG)**：检索相似问题 + LLM 生成答案 +- **多阶段流水线**：检索 + 重排的分离架构 +- **LLM 微调**：Qwen 系列 LLM 用于教育任务 + +**关键创新：** +- **多阶段检索+重排流水线** (1st Place) +- **Distractor prediction** (1st Place)：预测错误答案与误解的亲和度 +- **Retrieval-augmented approach** (1st Place)：嵌入模型检索候选误解 + +--- + +### Eedi - Mining Misconceptions in Mathematics (2024) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/eedi-mining-misconceptions-in-mathematics) | [Lessons Learned](https://the-learning-agency.com/the-cutting-ed/article/lessons-learned-from-hosting-ai-competitions-in-edtech/) +**Category:** NLP/LLM (教育 AI / 误解检测) +**Key Techniques:** +- **多阶段检索+重排流水线**: Qwen LLMs 用于初始检索和重排序 +- **Distractor prediction**: 预测错误答案与误解的亲和度 +- **Retrieval-augmented approach**: 嵌入模型检索候选误解 +- **Same winner as MAP**: Team MTH 101 (Raja Biswas) 赢得了 Eedi 和 MAP + +**Results:** 1st Place score ~0.637, $12,000 奖金, 数据集 1,868 个数学问题 + +#### 前排方案详细技术分析 + +**1st Place - Team MTH 101 (Raja Biswas)** + +核心技巧： +- **多阶段检索+重排流水线**：Qwen LLMs 用于初始检索和重排序 +- **Distractor prediction**：预测错误答案与误解的亲和度 +- **Retrieval-augmented approach**：嵌入模型检索候选误解 +- **LLM 微调**：Qwen 系列 LLM 在教育数据上微调 +- **集成融合**：多个模型的加权组合 + +实现细节： +- 检索阶段：使用嵌入模型检索相似历史问题和误解 +- 重排序：Qwen LLM 对检索结果进行精排 +- Distractor prediction：单独的模型预测错误选项的迷惑性 +- 最终 MAP@3：~0.637，获得 $12,000 奖金 + +**与 MAP 的关系**： +- 同一冠军团队（Team MTH 101） +- 技术框架一脉相承：检索 + 推理 + 集成 +- MAP 是 Eedi 的扩展版本，处理更复杂的学生回答数据 + +**2nd Place - Kazuhito Yonekawa et al.** + +核心技巧： +- **多阶段 retrieve-and-rank**：嵌入检索 + LLM 重排 +- **Qwen2.5-72B 主模型**：大规模 LLM 用于推理和重排 +- **CoT 提示工程**：思维链提示引导模型推理 +- **后处理优化**：基于误解层次结构的后处理 + +实现细节： +- Qwen2.5-72B 用于重排，小模型用于检索 +- CoT 提示："Let's think step by step about what misconception this might show." +- 后处理：父子误解关系的层次约束 +- 最终 MAP@3：~0.636 + +**3rd Place - waseda-pochi** + +核心技巧： +- **Magic boost post-processing**：针对特定误解类型的 boost +- **Unknown misconception correction**：修正"未知"误解的预测 +- **Qwen2.5-32B 模型**：平衡性能和效率 +- **特征工程**：问题难度、选项分布等特征 + +实现细节： +- Magic boost：为低召回但高精度误解提升权重 +- Unknown correction：使用相似误解替换"Unknown"标签 +- 特征：问题长度、选项数量、数字密度等 +- 最终 MAP@3：~0.635 + +**4th Place - (匿名团队)** + +核心技巧： +- **CoT features 辅助**：思维链特征作为额外输入 +- **分组合成数据**：按问题类型分组生成合成数据 +- **Qwen2.5-32B 集成**：多个模型集成 +- **两阶段训练**：预训练 + 微调 + +实现细节： +- CoT features：提取推理链中的关键步骤作为特征 +- 分组合成：按代数、几何、概率等分组生成合成问题 +- 两阶段：在通用数学数据上预训练，Eedi 数据微调 +- 最终 MAP@3：~0.634 + +**5th Place - ebi-ktr** + +核心技巧： +- **Bi-encoder 检索**：双编码器架构高效检索 +- **Listwise reranking**：列表级重排代替点级 +- **多模型融合**：嵌入模型 + LLM 融合 +- **负采样策略**：困难负样本挖掘 + +实现细节： +- Bi-encoder：Question 和 Misconception 分别编码 +- Listwise：LambdaLoss 优化整个排序列表 +- 负采样：选择与问题相似但不是正确误解的样本 +- 最终 MAP@3：~0.633 + +**6th Place - (匿名团队)** + +核心技巧： +- **QLoRA 微调**：参数高效微调大模型 +- **Qwen2.5-14B 架构**：较小模型降低成本 +- **集成策略**：多个 LoRA 适配器集成 +- **数据增强**：数学问题改写增强 + +实现细节： +- QLoRA：rank=64, α=16, dropout=0.05 +- LoRA 适配器：在 Qwen2.5-14B 上训练 4-6 个适配器 +- 数据增强：改写问题表述，保持误解类型不变 +- 最终 MAP@3：~0.632 + +**7th (Private) / 2nd (Public) - terekaerumasahmet** + +核心技巧： +- **Multi-loss 组合**：多种损失函数组合 +- **Soft labels 蒸馏**：从大模型蒸馏软标签 +- **Qwen2.5-32B 主模型**：平衡性能 +- **多种采样策略**：Top-k, Nucleus, Temperature sampling + +实现细节： +- Multi-loss：BCE + Focal + Label Smoothing 组合 +- Soft labels：从 72B 教师模型蒸馏，温度 T=2 +- 采样策略：推理时结合多种采样方法 +- 最终 MAP@3：~0.631 (Private), ~0.64 (Public) + +**8th Place - (匿名团队)** + +核心技巧： +- **多阶段检索系统**：粗检索 + 精检索两级架构 +- **Listwise reranking**：列表级排序优化 +- **Qwen2.5-32B 系列**：多个变体模型集成 +- **特征融合**：语义特征 + 统计特征融合 + +实现细节： +- 两级检索：第一级 BM25，第二级向量检索 +- Listwise：ListMLE 损失优化排序列表 +- 特征融合：TF-IDF + Embedding + 统计特征 +- 最终 MAP@3：~0.630 + +**9th (Private) / 7th (Public) - (匿名团队)** + +核心技巧： +- **QLoRA 微调**：参数高效微调 +- **多任务学习**：同时预测误解和选项正确性 +- **Qwen2.5-14B 架构**：效率优先 +- **集成学习**：多个微调模型集成 + +实现细节： +- QLoRA：在嵌入层和注意力层添加 LoRA +- 多任务：主任务误解预测，辅助任务选项正确性 +- 集成：5-7 个不同随机种子的 QLoRA 模型 +- 最终 MAP@3：~0.629 (Private), ~0.631 (Public) + +**10th Place - (匿名团队)** + +核心技巧： +- **合成数据生成**：LLM 生成额外训练数据 +- **知识蒸馏**：20B → 8B 模型蒸馏 +- **Qwen2.5-32B 教师 → Qwen2.5-8B 学生**：4:1 压缩 +- **集成融合**：教师 + 学生模型集成 + +实现细节： +- 合成数据：GPT-4 生成相似问题和误解配对 +- 蒸馏：教师软标签 + 学生硬标签联合训练 +- 集成：教师权重 0.7，学生权重 0.3 +- 最终 MAP@3：~0.628 + +--- + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025-6th-place-study.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025-6th-place-study.md new file mode 100644 index 0000000..9440d6a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025-6th-place-study.md @@ -0,0 +1,399 @@ +# Konwinski Prize 2025 - 6th Place 实战学习笔记 + +> 基于 quan16369 的开源解决方案 +> GitHub: https://github.com/quan16369/Kaggle-Konwinski-Prize-6th-Place-Solution- +> 排名: 6th/617 (Gold Medal) + +--- + +## 竞赛背景 + +### 任务描述 +- **目标**: 构建 AI Agent，自动修复 GitHub 真实项目中的 bug +- **挑战**: 测试集隐藏，要求模型具有强泛化能力 +- **评估**: 严格评分（错误修复重罚，跳过轻罚） +- **难度**: 极高 - 第 1 名仅 7.5% 成功率 + +### 6th Place 成绩 +| 策略 | Private LB | Public LB | +|------|------------|-----------| +| Select-Patch-Verify-Choose | 0.008237 (3 correct, 2 wrong, 115 skipped) | -0.000097 (1 correct, 1 wrong, 69 skipped) | + +--- + +## 核心架构：Select-Patch-Verify-Choose Pipeline + +### 完整流程图 + +``` +┌─────────────┐ +│ Select │ 分析 bug 报告 + 代码树 → 生成多个选择查询 +└──────┬──────┘ + │ + ▼ +┌─────────────┐ +│ Patch │ 基于选定代码段 → 生成候选补丁 (diffs) +└──────┬──────┘ + │ + ▼ +┌─────────────┐ +│ Verify │ 多次验证 (VALIDATION_COPY_COUNT) → 评估置信度 +└──────┬──────┘ + │ + ▼ +┌─────────────┐ +│ Choose │ 规则评分函数 → 选择最优补丁或跳过 +└─────────────┘ +``` + +--- + +## 关键创新点 + +### 1. 多次验证 (Multi-attempt Verification) + +**问题**: 单次 LLM 自我评估可能产生幻觉 + +**解决方案**: 强制模型验证每个候选补丁多次 + +```python +# judgments_aggregated 示例 +[ + [], # Candidate 1: 无 Yes 票 + [True, True, True], # Candidate 2: 强信号 (3/3 Yes) + [], # Candidate 3: 无 Yes 票 + [], # Candidate 4: 无 Yes 票 + [], # Candidate 5: 无 Yes 票 + [True, True, True], # Candidate 6: 强信号 (3/3 Yes) + [] # Candidate 7: 无 Yes 票 +] +``` + +**关键参数**: `VALIDATION_COPY_COUNT` +- 推荐值: 3 +- 作用: 只有高一致性的补丁才被认为是可靠的 + +--- + +### 2. 基于评分的补丁选择 + +**核心思想**: 不简单地选择 "Yes" 票最多的补丁，而是使用复杂的评分公式 + +#### 评分公式 + +```python +def calculate_patch_score(patch, judgments): + # 无效或无 Yes 票 → 重罚 + if not is_valid(patch) or judgments.count(True) == 0: + return -LARGE_PENALTY + + # 基础分 = (Yes 票数)^2 × 权重 + score = (judgments.count(True) ** 2) * 5.0 + + # 减去指数级大小惩罚 + score -= (np.exp(len(patch) / 10) - 1) + + return score +``` + +#### 多标准过滤 + +补丁只有在满足以下所有条件时才被选择： +1. 正分数 +2. 位于 top 百分位（如 top 1%） +3. 显著优于第二名补丁 +4. 满足最小 "Yes" 票要求 + +否则：**SKIP**（确保安全） + +--- + +### 3. 指数级大小惩罚 + +**目的**: 强制 LLM 找到最简洁、精确的解决方案 + +**效果**: 避免不必要的修改，减少副作用 + +**数学表达**: +``` +penalty = exp(patch_length / 10) - 1 +``` + +**示例**: +- 10 字符补丁: penalty ≈ 0.72 +- 50 字符补丁: penalty ≈ 148 +- 100 字符补丁: penalty ≈ 22026 + +--- + +## 核心代码实现 + +### choose_patch_string_optimized 函数 + +```python +def choose_patch_string_optimized( + patches: List[str], + judgments_aggregated: List[List[bool]], + dry_run_results: List[bool], + top_percentile: float = 0.01, + min_yes_votes: int = 3, + large_penalty: float = 1e6 +) -> Optional[int]: + """ + 基于评分的补丁选择函数 + + Args: + patches: 候选补丁列表 + judgments_aggregated: 聚合的验证结果 + dry_run_results: 干运行结果 + top_percentile: 前 N% 考虑 + min_yes_votes: 最小 Yes 票数 + large_penalty: 大惩罚值 + + Returns: + 选择的补丁索引，或 None（跳过） + """ + # 计算每个补丁的分数 + scores = [] + for i, (patch, judgments, dry_run_ok) in enumerate( + zip(patches, judgments_aggregated, dry_run_results) + ): + # 无效或干运行失败 → 重罚 + if not dry_run_ok or not judgments: + scores.append(-large_penalty) + continue + + # 计算分数 + yes_votes = sum(judgments) + if yes_votes == 0: + scores.append(-large_penalty) + continue + + # 基础分 = (Yes 票)^2 × 权重 + score = (yes_votes ** 2) * 5.0 + + # 指数级大小惩罚 + score -= np.exp(len(patch) / 10) - 1 + + scores.append(score) + + # 找到最高分 + max_score = max(scores) + if max_score <= 0: + return None # 跳过 + + # top 百分位过滤 + threshold = np.percentile(scores, 100 * (1 - top_percentile)) + if max_score < threshold: + return None + + # 选择最高分补丁 + best_idx = scores.index(max_score) + + # 检查是否显著优于第二名 + sorted_scores = sorted(scores, reverse=True) + if len(sorted_scores) > 1 and max_score < sorted_scores[1] * 1.5: + return None + + # 最小 Yes 票检查 + if sum(judgments_aggregated[best_idx]) < min_yes_votes: + return None + + return best_idx +``` + +--- + +## 性能优化 + +### 1. 并行处理 +- 使用 vLLM 的并行处理 +- 并发生成和验证候选补丁 + +### 2. 早期过滤 +- 无效或不可应用的补丁立即丢弃 +- 节省计算资源 + +--- + +## 经验教训 + +### ✅ 优势 + +1. **生成-过滤策略**: 信任 LLM 产生多个解决方案，然后应用严格逻辑过滤 +2. **指数大小惩罚**: 强制模型直接解决问题，避免冗余修改 +3. **多次验证**: 减少 LLM 幻觉，提高可靠性 + +### ❌ 局限性和改进方向 + +#### 1. **强制性测试阶段** (最关键) + +**问题**: 仅靠 LLM 验证不够客观 + +**解决方案** (来自前排方案): +- 要求 LLM 自动生成 F2P (Fail-to-Pass) 测试 +- 测试必须在原始代码上失败，在补丁后通过 +- 最可靠的 bug 复现和修复确认方式 + +#### 2. **更智能的选择阶段** + +改进方向: +- 优先分析 traceback（如 5th Place 的正则方法） +- 提供现有测试的上下文（如获胜方案的单元测试示例） +- 将补丁格式从 git diff 改为 SEARCH/REPLACE 中间格式 + +#### 3. **重试机制** + +- 当初始测试生成失败时实现重试 +- 可以使用更高温度设置增加多样性 + +#### 4. **增强评分系统** + +- 添加修改文件数量的惩罚 +- 优先考虑本地化更改 + +--- + +## 可复用模板 + +### Template 1: 多次验证 + +```python +def multi_attempt_verify( + patch: str, + context: str, + num_attempts: int = 3, + model: str = "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct" +) -> List[bool]: + """ + 多次验证补丁 + + Returns: + List of bool: 每个 Yes 票表示验证通过 + """ + judgments = [] + + for _ in range(num_attempts): + response = llm_call( + model=model, + messages=[{ + "role": "user", + "content": f"""请验证以下补丁是否正确修复了 bug： + +上下文： +{context} + +补丁： +{patch} + +请回答 "Yes" 或 "No"。""" + }] + ) + + judgment = "yes" in response.lower() + judgments.append(judgment) + + return judgments +``` + +### Template 2: 补丁评分 + +```python +def score_patch( + patch: str, + yes_votes: int, + base_weight: float = 5.0, + size_penalty_scale: float = 10.0 +) -> float: + """ + 计算补丁分数 + + Args: + patch: 补丁内容 + yes_votes: Yes 票数 + base_weight: 基础权重 + size_penalty_scale: 大小惩罚缩放 + + Returns: + 补丁分数 + """ + # 基础分 = (Yes 票)^2 × 权重 + score = (yes_votes ** 2) * base_weight + + # 指数级大小惩罚 + size_penalty = np.exp(len(patch) / size_penalty_scale) - 1 + score -= size_penalty + + return score +``` + +### Template 3: Select-Patch-Verify-Choose 完整流程 + +```python +async def spvc_pipeline( + bug_report: str, + code_tree: Dict[str, str], + model: str = "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct" +) -> Optional[str]: + """ + Select-Patch-Verify-Choose 完整流程 + + Returns: + 选择的补丁，或 None（跳过） + """ + # 1. Select + selections = await select_phase(bug_report, code_tree, model) + + # 2. Patch + patches = await patch_phase(selections, model) + + # 3. Verify + judgments_aggregated = [] + for patch in patches: + judgments = multi_attempt_verify(patch, bug_report, model=model) + judgments_aggregated.append(judgments) + + # 4. Choose + best_idx = choose_patch_string_optimized( + patches=patches, + judgments_aggregated=judgments_aggregated, + dry_run_results=[True] * len(patches) # 假设都通过干运行 + ) + + return patches[best_idx] if best_idx is not None else None +``` + +--- + +## 相关资源 + +### GitHub 仓库 +- **6th Place Solution**: https://github.com/quan16369/Kaggle-Konwinski-Prize-6th-Place-Solution- + +### Kaggle 竞赛 +- **竞赛主页**: https://www.kaggle.com/competitions/konwinski-prize +- **官方网站**: https://kprize.ai + +### 策略指南 +- **Strategy Guide**: https://github.com/raymyers/konwinski-prize-strategy-guide + +### 相关基准测试 +- **SWE-bench**: https://www.swebench.com/ + +--- + +## 总结 + +6th Place 的方案展示了如何在 **严格的规则约束** 下，通过 **生成-过滤策略** 和 **多次验证机制**，在 **高难度代码修复任务** 中获得优异成绩。 + +**核心要点**: +1. 质量 > 数量：宁愿跳过也不要错误修复 +2. 多次验证：减少 LLM 幻觉 +3. 指数惩罚：强制简洁解决方案 +4. 严格过滤：确保只有高置信度补丁被选择 + +**下一步改进**: +- 添加 F2P 测试阶段（最关键） +- 优化选择阶段的上下文提供 +- 实现重试机制 +- 增强评分系统 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025-comparison.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025-comparison.md new file mode 100644 index 0000000..df0ef11 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025-comparison.md @@ -0,0 +1,1337 @@ +# Konwinski Prize 2025 前排方案对比学习 + +> **竞赛**: Konwinski Prize 2025 - AI GitHub Issue Resolver +> +> **研究重点**: 1st Place vs 5th Place 技术方案对比 +> +> **更新日期**: 2026-01-25 + +--- + +## 目录 + +1. [竞赛概览](#竞赛概览) +2. [前排方案对比表](#前排方案对比表) +3. [1st Place 方案深度解析](#1st-place-方案深度解析) +4. [5th Place 方案深度解析](#5th-place-方案深度解析) +5. [核心技术对比](#核心技术对比) +6. [可复用代码模板](#可复用代码模板) +7. [关键经验教训](#关键经验教训) + +--- + +## 竞赛概览 + +### 竞赛基本信息 + +| 项目 | 内容 | +|------|------| +| **竞赛名称** | Konwinski Prize 2025 | +| **主办方** | Andy Konwinski (Databricks 联合创始人) | +| **总奖金** | $1,225,000+ | +| **最高奖金** | $1,000,000 (90% 成功率，尚未触发) | +| **Round 1 首奖** | $50,000 | +| **参与团队** | 616 个团队 | +| **竞赛时间** | 2024年12月 - 2025年7月 | + +### 任务定义 + +**目标**: 构建 AI Agent，自动修复 GitHub 真实项目中的 bug + +**挑战**: +- 测试集完全隐藏（提交后收集） +- 无数据泄露（contamination-free） +- 严格评分机制 +- 仅允许使用开源模型 + +### 评分机制 + +```python +# 评分公式（简化版） +score = num_correct - C * num_wrong + +# 其中 C 是错误修复的惩罚系数（通常较大） +# skip 仅有轻微惩罚 +``` + +**关键洞察**: +- 错误修复 → 重罚 +- 跳过 → 轻罚 +- **策略**: 宁可跳过，不要出错 + +--- + +## 前排方案对比表 + +### 排名和成绩 + +| 排名 | 参与者 | 成功率 | 核心策略 | 关键技术 | +|------|--------|--------|----------|----------| +| **1st** | Eduardo Rocha de Andrade | **7.5%** | Prompt Engineering + F2P Testing | • Fail-to-Pass 测试
    • 保守提交策略
    • 精心设计的 prompt | +| **5th** | Anonymous (Ambrosm?) | ~5% | Regex Traceback Analysis | • 正则提取 traceback
    • 精确定位错误
    • 上下文优化 | +| **6th** | quan16369 | 0.8% | Select-Patch-Verify-Choose | • 多次验证
    • 指数大小惩罚
    • 严格过滤 | + +### 核心差异概览 + +| 维度 | 1st Place | 5th Place | 6th Place | +|------|-----------|-----------|-----------| +| **测试验证** | ✅ F2P 测试（关键） | ✅ F2P 测试 | ❌ 仅 LLM 验证 | +| **错误定位** | Prompt Engineering | Regex Traceback | LLM Select | +| **补丁选择** | 保守策略 | 保守策略 | 规则评分 | +| **提交策略** | 仅高置信度 | 仅高置信度 | 相对宽松 | +| **上下文使用** | 全面的 issue 分析 | 精准的 traceback | 全代码树 | + +--- + +## 1st Place 方案深度解析 + +### 核心理念 + +> **"质量 > 数量，客观测试 > 主观判断"** + +### 架构设计 + +``` +┌─────────────────────────────────────────────────────────┐ +│ 1st Place 完整流程 │ +└─────────────────────────────────────────────────────────┘ + +输入: GitHub Issue + 代码库 + │ + ▼ +┌──────────────────┐ +│ 1. Issue 分析 │ • 提取关键信息 +│ │ • 理解问题本质 +└────────┬─────────┘ + │ + ▼ +┌──────────────────┐ +│ 2. F2P 测试生成 │ ⭐ 核心创新 +│ │ • 测试必须在原代码失败 +└────────┬─────────┘ • 测试必须在补丁后通过 + │ + ▼ +┌──────────────────┐ +│ 3. 补丁生成 │ • 基于测试指导 +│ │ • 多个候选方案 +└────────┬─────────┘ + │ + ▼ +┌──────────────────┐ +│ 4. F2P 测试验证 │ • 客观验证 +│ │ • 确保修复有效 +└────────┬─────────┘ + │ + ▼ +┌──────────────────┐ +│ 5. 保守决策 │ • 仅高置信度提交 +│ │ • 宁可跳过 +└──────────────────┘ +``` + +### 关键技术 1: F2P (Fail-to-Pass) 测试 + +**定义**: 生成在原始代码上失败、在修复后通过的测试用例 + +**实现流程**: + +```python +def generate_f2p_test(issue: str, code_context: str, model) -> str: + """ + 生成 Fail-to-Pass 测试 + + Args: + issue: GitHub issue 描述 + code_context: 相关代码上下文 + model: LLM 模型 + + Returns: + test_code: F2P 测试代码 + """ + prompt = f""" +你是一个测试工程师。根据以下 GitHub Issue，生成一个单元测试： + +GitHub Issue: +{issue} + +相关代码: +{code_context} + +要求： +1. 测试必须在当前（有 bug 的）代码上 FAIL +2. 测试必须在修复 bug 后 PASS +3. 测试应该最小化，专注于特定 bug +4. 使用 pytest 框架 + +返回完整的测试代码。 +""" + + test_code = model.generate(prompt) + return test_code + + +def validate_f2p_test( + test_code: str, + original_code: str, + patched_code: str +) -> bool: + """ + 验证 F2P 测试的有效性 + + Returns: + True 如果测试是有效的 F2P 测试 + """ + # 1. 在原始代码上运行测试（应该 FAIL） + original_result = run_test(test_code, original_code) + if original_result.status != "FAIL": + return False # 测试在原代码上没有失败！ + + # 2. 在补丁后代码上运行测试（应该 PASS） + patched_result = run_test(test_code, patched_code) + if patched_result.status != "PASS": + return False # 测试在补丁后没有通过！ + + return True +``` + +**F2P 测试的优势**: + +1. **客观验证**: 不依赖 LLM 主观判断 +2. **Bug 复现**: 确保 bug 真实存在 +3. **修复确认**: 确保补丁真正修复了问题 +4. **回归预防**: 防止补丁引入新问题 + +### 关键技术 2: 保守提交策略 + +```python +def should_submit_patch( + patch: str, + f2p_test_result: dict, + confidence_metrics: dict +) -> bool: + """ + 保守的提交决策 + + 只有在所有条件都满足时才提交 + """ + # 条件 1: F2P 测试必须通过 + if not f2p_test_result['valid_f2p']: + return False + + # 条件 2: 补丁必须成功应用 + if not f2p_test_result['applied_successfully']: + return False + + # 条件 3: 补丁大小必须合理 + if len(patch) > 500: # 字符数限制 + return False + + # 条件 4: 修改的文件数量有限 + if f2p_test_result['files_modified'] > 2: + return False + + # 条件 5: 高置信度 + if confidence_metrics['score'] < 0.9: + return False + + # 所有条件满足 → 提交 + return True +``` + +### 关键技术 3: Prompt Engineering + +**Issue 分析 Prompt**: + +```python +ISSUE_ANALYSIS_PROMPT = """ +你是一个资深的软件工程师和调试专家。 + +任务：分析以下 GitHub Issue，提取关键信息 + +GitHub Issue: +{issue} + +请提供： +1. 问题类型（bug/feature/性能/安全等） +2. 错误消息（如果有） +3. Traceback 信息（如果有） +4. 复现步骤 +5. 期望行为 +6. 相关文件或模块 +7. 可能的根本原因 + +以结构化的 JSON 格式返回。 +""" +``` + +**补丁生成 Prompt**: + +```python +PATCH_GENERATION_PROMPT = """ +你是一个代码修复专家。 + +任务：根据以下信息生成修复补丁 + +GitHub Issue: +{issue} + +F2P 测试: +{f2p_test} + +相关代码: +{code} + +要求： +1. 生成最小化的补丁 +2. 只修改必要的代码 +3. 确保补丁能让 F2P 测试通过 +4. 不要添加不必要的功能 +5. 使用 git diff 格式 + +返回补丁代码。 +""" +``` + +--- + +## 5th Place 方案深度解析 + +### 核心理念 + +> **"精确的错误定位 + 有效的上下文"** + +### 架构设计 + +``` +┌─────────────────────────────────────────────────────────┐ +│ 5th Place 完整流程 │ +└─────────────────────────────────────────────────────────┘ + +输入: GitHub Issue + 代码库 + │ + ▼ +┌──────────────────┐ +│ 1. Traceback │ ⭐ 核心创新 +│ 提取 │ • 正则表达式匹配 +└────────┬─────────┘ • 提取错误位置 + │ + ▼ +┌──────────────────┐ +│ 2. 精确定位 │ • 文件级别 +│ │ • 行级别 +└────────┬─────────┘ • 函数级别 + │ + ▼ +┌──────────────────┐ +│ 3. 上下文收集 │ • 仅相关代码 +│ │ • 减少噪音 +└────────┬─────────┘ + │ + ▼ +┌──────────────────┐ +│ 4. F2P 测试生成 │ • 基于定位结果 +└────────┬─────────┘ + │ + ▼ +┌──────────────────┐ +│ 5. 目标化补丁 │ • 精准修复 +│ │ • 最小化修改 +└────────┬─────────┘ + │ + ▼ +┌──────────────────┐ +│ 6. 测试验证 │ • F2P 验证 +└──────────────────┘ +``` + +### 关键技术: Regex Traceback 分析 + +**完整的 Traceback 提取器**: + +```python +import re +from typing import Dict, List, Optional, Tuple +from dataclasses import dataclass + + +@dataclass +class TracebackInfo: + """Traceback 信息结构""" + files: List[str] + lines: List[int] + functions: List[str] + error_types: List[str] + error_messages: List[str] + raw_traceback: str + + +class TracebackExtractor: + """使用正则表达式提取 Traceback 信息""" + + # Python Traceback 模式 + PATTERNS = { + 'traceback_header': r'Traceback \(most recent call last\):', + 'frame': r' File "([^"]+)", line (\d+), in (\w+)', + 'error': r'(\w*Error):\s*(.+)', + 'assertion': r'AssertionError:\s*(.+)', + 'exception_in': r'Exception in (\w+) (.+)', + } + + def __init__(self): + # 编译正则表达式 + self.compiled_patterns = { + name: re.compile(pattern) + for name, pattern in self.PATTERNS.items() + } + + def extract(self, issue_text: str) -> Optional[TracebackInfo]: + """ + 从 issue 文本中提取 traceback 信息 + + Args: + issue_text: GitHub issue 的完整文本 + + Returns: + TracebackInfo 对象，如果没有找到 traceback 则返回 None + """ + # 1. 检查是否有 traceback + if not self.compiled_patterns['traceback_header'].search(issue_text): + return None + + # 2. 提取帧信息 + frames = self.compiled_patterns['frame'].findall(issue_text) + files = [frame[0] for frame in frames] + lines = [int(frame[1]) for frame in frames] + functions = [frame[2] for frame in frames] + + # 3. 提取错误信息 + error_match = self.compiled_patterns['error'].search(issue_text) + if error_match: + error_types = [error_match.group(1)] + error_messages = [error_match.group(2)] + else: + # 尝试匹配 AssertionError + assertion_match = self.compiled_patterns['assertion'].search(issue_text) + if assertion_match: + error_types = ['AssertionError'] + error_messages = [assertion_match.group(1)] + else: + error_types = [] + error_messages = [] + + # 4. 提取原始 traceback 文本 + traceback_match = re.search( + r'(Traceback \(most recent call last\):.*?)(?=\n\n|\Z)', + issue_text, + flags=re.DOTALL + ) + raw_traceback = traceback_match.group(1) if traceback_match else "" + + return TracebackInfo( + files=files, + lines=lines, + functions=functions, + error_types=error_types, + error_messages=error_messages, + raw_traceback=raw_traceback + ) + + def prioritize_files( + self, + traceback: TracebackInfo, + all_files: List[str] + ) -> List[str]: + """ + 根据 traceback 优先排序文件 + + Args: + traceback: 提取的 traceback 信息 + all_files: 代码库中所有文件的列表 + + Returns: + 优先排序后的文件列表 + """ + prioritized = [] + + # 优先级 1: traceback 中直接提到的文件 + for tb_file in traceback.files: + # 标准化路径 + normalized = tb_file.replace('/', '.') + if normalized in all_files: + prioritized.append((normalized, 1.0)) + # 尝试部分匹配 + elif any(tb_file in f or f in tb_file for f in all_files): + match = next(f for f in all_files if tb_file in f or f in tb_file) + prioritized.append((match, 0.9)) + + # 优先级 2: 同目录下的文件 + if traceback.files: + tb_dir = '/'.join(traceback.files[0].split('/')[:-1]) + for f in all_files: + if f.startswith(tb_dir) and f not in [p[0] for p in prioritized]: + prioritized.append((f, 0.7)) + + # 优先级 3: 相关测试文件 + for f in all_files: + if 'test' in f.lower() and f not in [p[0] for p in prioritized]: + prioritized.append((f, 0.5)) + + # 按优先级排序 + prioritized.sort(key=lambda x: x[1], reverse=True) + + return [p[0] for p in prioritized] + + def get_context_lines( + self, + traceback: TracebackInfo, + file_content: str, + context_window: int = 10 + ) -> str: + """ + 获取错误行周围的上下文 + + Args: + traceback: Traceback 信息 + file_content: 文件内容 + context_window: 上下文行数 + + Returns: + 上下文代码字符串 + """ + if not traceback.lines: + return file_content[:500] # 默认返回前 500 字符 + + lines = file_content.split('\n') + error_line = traceback.lines[0] + + # 提取上下文 + start = max(0, error_line - context_window) + end = min(len(lines), error_line + context_window + 1) + + context_lines = lines[start:end] + + # 添加行号 + context_with_line_numbers = [ + f"{i+1:4d}: {line}" + for i, line in enumerate(context_lines, start=start) + ] + + # 标记错误行 + if error_line - start < len(context_with_line_numbers): + idx = error_line - start + context_with_line_numbers[idx] = f">>> {context_with_line_numbers[idx]}" + + return '\n'.join(context_with_line_numbers) +``` + +**使用示例**: + +```python +# 初始化 +extractor = TracebackExtractor() + +# 从 issue 中提取 traceback +issue_text = """ +When I run the model, I get this error: + +Traceback (most recent call last): + File "train.py", line 42, in train_loop + loss = model(batch) + File "model.py", line 156, in __call__ + outputs = self.layer(inputs) +TypeError: Layer.__call__() got an unexpected keyword argument 'training' + +This happens when I use the new layer type. +""" + +traceback = extractor.extract(issue_text) + +if traceback: + print(f"Error Type: {traceback.error_types}") + print(f"Error Message: {traceback.error_messages}") + print(f"Files: {traceback.files}") + print(f"Lines: {traceback.lines}") + print(f"Functions: {traceback.functions}") + + # 优先排序文件 + all_files = ['model.py', 'train.py', 'utils.py', 'test_model.py'] + prioritized = extractor.prioritize_files(traceback, all_files) + print(f"Prioritized files: {prioritized}") + + # 获取上下文 + model_code = read_file('model.py') + context = extractor.get_context_lines(traceback, model_code) + print(f"Context:\n{context}") +``` + +### 基于 Traceback 的补丁生成 + +```python +def generate_traceback_aware_patch( + issue: str, + traceback: TracebackInfo, + code_context: str, + model +) -> str: + """ + 基于 traceback 信息生成精准的补丁 + + Args: + issue: GitHub issue + traceback: 提取的 traceback 信息 + code_context: 错误行周围的代码上下文 + model: LLM 模型 + + Returns: + patch: 生成的补丁 + """ + prompt = f""" +你是一个代码修复专家。 + +Bug 报告: +{issue} + +错误位置信息: +- 文件: {traceback.files[0] if traceback.files else 'Unknown'} +- 行号: {traceback.lines[0] if traceback.lines else 'Unknown'} +- 函数: {traceback.functions[0] if traceback.functions else 'Unknown'} +- 错误类型: {traceback.error_types[0] if traceback.error_types else 'Unknown'} +- 错误消息: {traceback.error_messages[0] if traceback.error_messages else 'Unknown'} + +错误行周围的代码: +{code_context} + +任务： +1. 分析错误的根本原因 +2. 生成最小的修复补丁 +3. 只修改必要的代码 +4. 使用 git diff 格式 + +返回补丁代码。 +""" + + patch = model.generate(prompt) + return patch +``` + +--- + +## 核心技术对比 + +### 对比维度分析 + +| 技术维度 | 1st Place | 5th Place | 优势分析 | +|---------|-----------|-----------|----------| +| **错误定位** | Prompt Engineering + 全面分析 | Regex Traceback 提取 | 5th 更精确，1st 更全面 | +| **测试验证** | F2P 测试 | F2P 测试 | 两者都使用（关键） | +| **上下文管理** | 全面 issue 分析 | 精准 traceback 定位 | 5th 更高效 | +| **补丁生成** | 多候选 + 精心 prompt | 目标化 + 精准定位 | 5th 更聚焦 | +| **提交策略** | 极度保守 | 保守 | 1st 更保守 | +| **适用场景** | 复杂、多文件问题 | 明确 traceback 错误 | 各有优势 | + +### F2P 测试 vs Traceback 分析 + +#### F2P 测试（1st Place 核心优势） + +**优势**: +1. ✅ **客观验证**: 不依赖 LLM 主观判断 +2. ✅ **Bug 复现**: 确保问题真实存在 +3. ✅ **修复确认**: 确保补丁有效 +4. ✅ **通用性强**: 适用于所有类型的 bug + +**劣势**: +1. ❌ **生成困难**: 需要高质量的 prompt +2. ❌ **计算成本**: 需要运行测试 +3. ❌ **测试质量**: 可能生成不完整或错误的测试 + +**最佳适用场景**: +- 需要高置信度的场景 +- 没有 traceback 的 bug 报告 +- 功能性 bug（非错误消息） + +#### Traceback 分析（5th Place 核心优势） + +**优势**: +1. ✅ **精确定位**: 直接指向错误位置 +2. ✅ **高效**: 减少不必要的上下文 +3. ✅ **明确信息**: 错误类型和消息清晰 +4. ✅ **上下文优化**: 只关注相关代码 + +**劣势**: +1. ❌ **依赖 traceback**: 不是所有 bug 都有 +2. ❌ **正则脆弱**: 可能漏掉非标准格式 +3. ❌ **表面症状**: 可能不是根本原因 + +**最佳适用场景**: +- 有明确 traceback 的错误 +- 单文件或局部问题 +- 需要快速定位的场景 + +#### 组合策略（最优方案） + +```python +def combined_strategy(issue: str, codebase: dict) -> Optional[str]: + """ + 组合 F2P 测试和 Traceback 分析 + + 结合两者的优势 + """ + # 1. 尝试提取 traceback + traceback = extract_traceback(issue) + + # 2. 根据是否有 traceback 选择策略 + if traceback: + # 使用 traceback 精确定位 + relevant_files = traceback.prioritize_files(codebase.keys()) + context = get_traceback_context(traceback, codebase) + else: + # 使用全面的 issue 分析 + relevant_files = analyze_issue(issue, codebase) + context = get_full_context(issue, codebase) + + # 3. 生成 F2P 测试（两种情况都需要） + f2p_test = generate_f2p_test(issue, context) + + # 4. 生成补丁 + patch = generate_patch(issue, f2p_test, context) + + # 5. 验证 + if validate_f2p_test(f2p_test, patch): + return patch + else: + return None +``` + +--- + +## 可复用代码模板 + +### Template 1: 完整的 F2P 测试流程（1st Place 风格） + +```python +from typing import Optional, Dict, Any +import subprocess +import tempfile +import os + + +class F2PTestGenerator: + """Fail-to-Pass 测试生成器""" + + def __init__(self, model): + self.model = model + + def generate(self, issue: str, code_context: str) -> str: + """生成 F2P 测试""" + prompt = f""" +根据以下 GitHub Issue 生成一个单元测试： + +Issue: +{issue} + +相关代码: +{code_context} + +要求： +1. 测试必须在当前（有 bug 的）代码上 FAIL +2. 测试必须在修复 bug 后 PASS +3. 使用 pytest 框架 +4. 测试应该最小化且专注于特定 bug + +返回完整的测试代码。 +""" + return self.model.generate(prompt) + + def validate( + self, + test_code: str, + original_code: str, + patched_code: str + ) -> Dict[str, Any]: + """验证 F2P 测试的有效性""" + results = { + 'valid_f2p': False, + 'original_result': None, + 'patched_result': None, + 'error': None + } + + try: + # 1. 在原始代码上运行（应该 FAIL） + results['original_result'] = self._run_test( + test_code, original_code + ) + + if results['original_result']['status'] != 'FAIL': + results['error'] = "Test did not fail on original code" + return results + + # 2. 在补丁后代码上运行（应该 PASS） + results['patched_result'] = self._run_test( + test_code, patched_code + ) + + if results['patched_result']['status'] != 'PASS': + results['error'] = "Test did not pass on patched code" + return results + + # 3. 测试有效 + results['valid_f2p'] = True + return results + + except Exception as e: + results['error'] = str(e) + return results + + def _run_test(self, test_code: str, code: str) -> Dict[str, Any]: + """运行测试并返回结果""" + with tempfile.TemporaryDirectory() as tmpdir: + # 写入测试文件 + test_file = os.path.join(tmpdir, 'test_fix.py') + with open(test_file, 'w') as f: + f.write(test_code) + f.write('\n\n') + f.write(code) + + # 运行测试 + result = subprocess.run( + ['pytest', test_file, '-v'], + capture_output=True, + text=True, + timeout=10 + ) + + return { + 'status': 'PASS' if result.returncode == 0 else 'FAIL', + 'stdout': result.stdout, + 'stderr': result.stderr + } + + +# 使用示例 +def solve_issue_with_f2p( + issue: str, + codebase: Dict[str, str], + model +) -> Optional[str]: + """ + 使用 F2P 测试解决问题 + """ + # 1. 生成测试 + test_gen = F2PTestGenerator(model) + test_code = test_gen.generate(issue, codebase) + + # 2. 生成补丁 + patch = generate_patch(issue, test_code, codebase, model) + + # 3. 验证 + validation = test_gen.validate( + test_code, + codebase, + apply_patch(codebase, patch) + ) + + # 4. 返回结果 + if validation['valid_f2p']: + return patch + else: + return None +``` + +### Template 2: Traceback 分析器（5th Place 风格） + +```python +import re +from typing import Optional, List, Tuple +from dataclasses import dataclass + + +@dataclass +class TracebackInfo: + """Traceback 信息""" + files: List[str] + lines: List[int] + functions: List[str] + error_type: Optional[str] + error_message: Optional[str] + full_traceback: str + + +class TracebackAnalyzer: + """Traceback 分析器""" + + def __init__(self): + self.patterns = { + 'header': re.compile(r'Traceback \(most recent call last\):'), + 'frame': re.compile(r' File "([^"]+)", line (\d+), in (\w+)'), + 'error': re.compile(r'(\w*Error):\s*(.+)'), + } + + def extract(self, text: str) -> Optional[TracebackInfo]: + """从文本中提取 traceback""" + if not self.patterns['header'].search(text): + return None + + # 提取帧 + frames = self.patterns['frame'].findall(text) + + # 提取错误 + error_match = self.patterns['error'].search(text) + error_type = error_match.group(1) if error_match else None + error_message = error_match.group(2) if error_match else None + + # 提取完整 traceback + tb_match = re.search( + r'(Traceback \(most recent call last\):.*?)(?=\n\n|\Z)', + text, + flags=re.DOTALL + ) + full_traceback = tb_match.group(1) if tb_match else "" + + return TracebackInfo( + files=[f[0] for f in frames], + lines=[int(f[1]) for f in frames], + functions=[f[2] for f in frames], + error_type=error_type, + error_message=error_message, + full_traceback=full_traceback + ) + + def get_error_location(self, traceback: TracebackInfo) -> Tuple[str, int]: + """获取错误位置（文件，行号）""" + if traceback.files and traceback.lines: + return (traceback.files[0], traceback.lines[0]) + return (None, None) + + def get_context( + self, + traceback: TracebackInfo, + file_content: str, + window: int = 5 + ) -> str: + """获取错误行周围的上下文""" + if not traceback.lines: + return file_content[:500] + + lines = file_content.split('\n') + error_line = traceback.lines[0] + + start = max(0, error_line - window) + end = min(len(lines), error_line + window + 1) + + context = lines[start:end] + return '\n'.join( + f"{i+1:4d}: {line}" + for i, line in enumerate(context, start=start) + ) + + +# 使用示例 +def solve_issue_with_traceback( + issue: str, + codebase: Dict[str, str], + model +) -> Optional[str]: + """ + 使用 Traceback 分析解决问题 + """ + # 1. 提取 traceback + analyzer = TracebackAnalyzer() + traceback = analyzer.extract(issue) + + if not traceback: + # 回退到其他方法 + return solve_issue_without_traceback(issue, codebase, model) + + # 2. 获取错误位置 + file_path, line_no = analyzer.get_error_location(traceback) + + # 3. 获取上下文 + if file_path in codebase: + context = analyzer.get_context( + traceback, + codebase[file_path] + ) + else: + return None + + # 4. 生成补丁 + prompt = f""" +修复以下错误： + +Issue: {issue} + +错误位置: {file_path}:{line_no} +错误类型: {traceback.error_type} +错误消息: {traceback.error_message} + +上下文代码: +{context} + +生成最小化的修复补丁（git diff 格式）。 +""" + patch = model.generate(prompt) + + # 5. 验证（仍然需要 F2P 测试） + # ... + + return patch +``` + +### Template 3: 组合策略（最优方案） + +```python +class HybridIssueSolver: + """ + 组合 F2P 测试和 Traceback 分析的混合策略 + + 结合 1st Place 和 5th Place 的优势 + """ + + def __init__(self, model): + self.model = model + self.traceback_analyzer = TracebackAnalyzer() + self.f2p_generator = F2PTestGenerator(model) + + def solve( + self, + issue: str, + codebase: Dict[str, str] + ) -> Optional[str]: + """ + 主解决流程 + """ + # 1. 尝试提取 traceback + traceback = self.traceback_analyzer.extract(issue) + + # 2. 根据情况选择策略 + if traceback: + return self._solve_with_traceback(issue, traceback, codebase) + else: + return self._solve_with_f2p(issue, codebase) + + def _solve_with_traceback( + self, + issue: str, + traceback: TracebackInfo, + codebase: Dict[str, str] + ) -> Optional[str]: + """ + 使用 traceback 精准定位 + """ + # 1. 获取错误位置 + file_path, line_no = self.traceback_analyzer.get_error_location(traceback) + + # 2. 获取精准上下文 + if file_path and file_path in codebase: + context = self.traceback_analyzer.get_context( + traceback, + codebase[file_path] + ) + else: + return None + + # 3. 生成 F2P 测试（即使有 traceback 也要测试） + test_code = self.f2p_generator.generate(issue, context) + + # 4. 生成补丁 + patch = self._generate_traceback_aware_patch( + issue, traceback, context, test_code + ) + + # 5. 验证 + validation = self.f2p_generator.validate( + test_code, + codebase[file_path], + apply_patch(codebase[file_path], patch) + ) + + return patch if validation['valid_f2p'] else None + + def _solve_with_f2p( + self, + issue: str, + codebase: Dict[str, str] + ) -> Optional[str]: + """ + 使用纯 F2P 测试策略（1st Place 方法） + """ + # 1. 全面分析 issue + context = self._analyze_issue(issue, codebase) + + # 2. 生成 F2P 测试 + test_code = self.f2p_generator.generate(issue, context) + + # 3. 生成补丁 + patch = self._generate_patch(issue, test_code, context) + + # 4. 验证 + # ... (验证逻辑) + + return patch + + def _generate_traceback_aware_patch( + self, + issue: str, + traceback: TracebackInfo, + context: str, + test_code: str + ) -> str: + """生成基于 traceback 的精准补丁""" + prompt = f""" +修复以下错误： + +Issue: {issue} +错误类型: {traceback.error_type} +错误消息: {traceback.error_message} + +上下文: +{context} + +F2P 测试: +{test_code} + +生成最小化修复补丁（git diff 格式）。 +""" + return self.model.generate(prompt) + + def _generate_patch( + self, + issue: str, + test_code: str, + context: str + ) -> str: + """生成常规补丁""" + prompt = f""" +修复以下 bug： + +Issue: +{issue} + +测试用例: +{test_code} + +代码上下文: +{context} + +生成修复补丁（git diff 格式）。 +""" + return self.model.generate(prompt) +``` + +--- + +## 关键经验教训 + +### 从排名差异中学到的 + +#### 1. F2P 测试是成功的必要条件 + +**证据**: +- 1st Place: 使用 F2P → 7.5% +- 5th Place: 使用 F2P → ~5% +- 6th Place: 无 F2P → 0.8% + +**结论**: +> **没有 F2P 测试，不可能获得好成绩** + +#### 2. Traceback 分析提供显著优势 + +**分析**: +- 5th Place 的 traceback 分析使其在 6th Place 基础上提升了 ~4.2% +- 精准的上下文管理减少了 LLM 幻觉 +- 更高效的 token 使用 + +**建议**: +> **有 traceback 一定要用，没有也要尝试提取** + +#### 3. 保守策略是明智的 + +**证据**: +- 所有前排方案都采用保守提交策略 +- 错误修复的惩罚远大于跳过 + +**实践**: +```python +# 保守的阈值设置 +CONFIDENCE_THRESHOLD = 0.9 +MAX_PATCH_SIZE = 500 +MAX_FILES_MODIFIED = 2 + +def should_submit(patch, validation_result): + return ( + validation_result['valid_f2p'] and + len(patch) < MAX_PATCH_SIZE and + validation_result['confidence'] > CONFIDENCE_THRESHOLD + ) +``` + +### 实施建议 + +#### 优先级 1: 实现 F2P 测试 + +```python +# 最小化的 F2P 实现 +def minimal_f2p(issue, code, model): + # 1. 生成测试 + test = generate_test(issue, code, model) + + # 2. 验证测试 + if not test_fails_on_original(test, code): + return None # 测试无效 + + # 3. 生成补丁 + patch = generate_patch(issue, test, code, model) + + # 4. 验证补丁 + if not test_passes_on_patched(test, patch, code): + return None # 补丁无效 + + return patch +``` + +#### 优先级 2: 添加 Traceback 分析 + +```python +# 最小化的 Traceback 实现 +def minimal_traceback_analysis(issue): + import re + + # 提取文件和行号 + pattern = r'File "([^"]+)", line (\d+)' + matches = re.findall(pattern, issue) + + if matches: + return { + 'file': matches[0][0], + 'line': int(matches[0][1]), + 'has_traceback': True + } + + return {'has_traceback': False} +``` + +#### 优先级 3: 采用保守策略 + +```python +# 保守的提交决策 +def conservative_submit(patch, validation): + # 多重检查 + checks = [ + validation['valid_f2p'], + len(patch) < 500, + validation['confidence'] > 0.9, + validation['files_modified'] <= 2 + ] + + # 所有检查通过才提交 + return all(checks) +``` + +### 技术栈建议 + +#### 模型选择 + +| 任务 | 推荐模型 | 原因 | +|------|----------|------| +| 补丁生成 | Qwen2.5-Coder-32B | 代码生成能力强 | +| 测试生成 | Qwen2.5-Coder-32B | 理解测试逻辑 | +| 验证 | Qwen2.5-Coder-32B | 一致性好 | +| Traceback 分析 | 规则（不需要模型） | 精确且快速 | + +#### 性能优化 + +```python +# 并行处理 +from concurrent.futures import ThreadPoolExecutor + +def parallel_verify(patches, issue, model, num_workers=4): + """并行验证多个补丁""" + with ThreadPoolExecutor(max_workers=num_workers) as executor: + futures = [ + executor.submit(verify_patch, patch, issue, model) + for patch in patches + ] + results = [f.result() for f in futures] + return results +``` + +### 常见陷阱 + +#### ❌ 陷阱 1: 信任单次验证 + +```python +# 错误：单次验证 +if verify(patch) == "Yes": + submit(patch) # 可能是幻觉 + +# 正确：多次验证 +verifications = [verify(patch) for _ in range(5)] +if sum(v == "Yes" for v in verifications) >= 4: + submit(patch) +``` + +#### ❌ 陷阱 2: 忽略补丁大小 + +```python +# 错误：不考虑大小 +if is_valid_patch(patch): + submit(patch) # 可能提交巨大补丁 + +# 正确：考虑大小 +if is_valid_patch(patch) and len(patch) < 500: + submit(patch) +``` + +#### ❌ 陷阱 3: 没有测试就提交 + +```python +# 错误：没有测试 +if llm_says_good(patch): + submit(patch) + +# 正确：必须有测试 +if test_fails_on_original(test, code) and test_passes_on_patched(test, patch, code): + submit(patch) +``` + +--- + +## 总结 + +### 核心要点 + +1. **F2P 测试是关键**: 所有前排方案都使用 +2. **Traceback 分析提供优势**: 5th Place 的核心创新 +3. **保守策略获胜**: 质量远比数量重要 +4. **组合策略最优**: 结合两种方法的效果最好 + +### 实施路线图 + +**阶段 1: 基础** +- 实现 F2P 测试生成和验证 +- 实现保守提交策略 + +**阶段 2: 优化** +- 添加 Traceback 分析 +- 实现多次验证 +- 添加大小惩罚 + +**阶段 3: 精进** +- 优化 prompt +- 并行处理 +- 性能优化 + +### 最终建议 + +> **"从 6th Place 的基础架构开始，添加 5th Place 的 traceback 分析，最终实现 1st Place 的 F2P 测试和保守策略"** + +--- + +**文档版本**: 1.0 +**最后更新**: 2026-01-25 +**参考来源**: +- Kaggle Konwinski Prize 竞赛页面 +- 6th Place 开源代码: https://github.com/quan16369/Kaggle-Konwinski-Prize-6th-Place-Solution- +- 策略指南: https://github.com/raymyers/konwinski-prize-strategy-guide +- SWE-bench: https://www.swebench.com/ diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025.md new file mode 100644 index 0000000..fc02ce9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/konwinski-prize-2025.md @@ -0,0 +1,662 @@ +# Konwinski Prize 2025 - AI GitHub Issue Resolver Competition + +> **Competition URL**: https://www.kaggle.com/competitions/konwinski-prize +> +> **Official Website**: https://kprize.ai +> +> **Category**: Code Agent / AI Software Engineering +> +> **Tags**: `code-agent`, `LLM-agent`, `SWE-bench`, `GitHub-issues`, `automated-programming` + +--- + +## Competition Brief + +### Overview +The **Konwinski Prize** is a $1M competition founded by **Andy Konwinski** (co-founder of Databricks) that challenges teams to build an AI system capable of resolving **real GitHub issues**. The competition uses a contamination-free version of the SWE-bench benchmark with GitHub issues collected **after** submissions to prevent data leakage. + +### Prize Structure +- **Grand Prize**: $1,000,000 for achieving >90% success rate (unclaimed) +- **Round 1 First Place**: $50,000 +- **Total Prize Fund**: $1,225,000+ +- **Participation**: 616 teams in Round 1 + +### Key Challenge +- **Goal**: Build an AI agent that can resolve real GitHub issues +- **Evaluation**: Performed on a **contamination-free test set** collected after submission +- **Success Criterion**: >90% issue resolution rate +- **Timeline**: Round 1 submissions closed July 2025; next round TBD + +### Round 1 Results (July 2025) +| Rank | Participant | Score | Achievement | +|------|-------------|-------|-------------| +| 1st | Eduardo Rocha de Andrade | 7.5% (0.058242) | $50,000 prize | +| 2nd | camaro | ~6-7% | Public 2nd Place | +| 3rd | Anonymous | ~5-6% | Bronze Medal | +| 4th | Anonymous | ~5-6% | "Select-Patch-Verify-Test" | +| 5th | Anonymous | ~5% | Regex traceback analysis | +| 6th | quan16369 (Team of 2) | 0.8% | Gold Medal (3 correct, 2 wrong) | + +**Key Insight**: The winning score of **7.5%** highlights how extremely difficult real-world GitHub issue resolution is, even for state-of-the-art AI systems. + +### Technical Constraints +- **Open-Weight Models Only**: No closed models (GPT-4, Claude, etc.) allowed +- **No External API Calls**: Must run locally +- **Runtime Environment**: Limited computing resources +- **Test Set**: Hidden until evaluation, collected after submission freeze + +--- + +## Top Solutions Analysis + +### 1st Place: Eduardo Rocha de Andrade (7.5% success) + +**Approach Summary**: Prompt engineering + careful test case generation + +**Key Techniques**: +- Meticulous prompt engineering +- Automated test case generation (Fail-to-Pass tests) +- Careful patch validation +- Conservative submission strategy (only high-confidence fixes) + +**Why It Won**: +- Quality over quantity: Only submitted fixes with highest confidence +- Proper test validation to ensure patches actually work +- Avoided the heavy penalties for wrong fixes + +--- + +### 4th Place: "Select-Patch-Verify-Test" Pipeline + +**Architecture**: +``` +Select → Patch → Verify → Test → Choose +``` + +**Pipeline Steps**: + +1. **Select**: Analyze bug reports + code tree to identify relevant files +2. **Patch**: Generate candidate patches using LLM +3. **Verify**: Multi-attempt LLM verification (measure confidence) +4. **Test**: Generate F2P (Fail-to-Pass) tests + - Tests must fail on original code + - Tests must pass after patch application +5. **Choose**: Rule-based scoring with strict filtering + +**Key Innovation**: The **mandatory testing phase** was crucial for objective validation. + +--- + +### 5th Place: Regex Traceback Analysis + +**Key Strategy**: +- Use regex to extract traceback information from error messages +- Focus LLM attention on specific error locations +- More targeted patch generation +- Reduced context window usage + +**Effectiveness**: Improved localization of bugs, less hallucination. + +--- + +### 6th Place: Select-Patch-Verify-Choose (quan16369) + +**Performance**: +- Private LB: 0.823% (3 correct, 2 wrong, 115 skipped) +- Public LB: -0.0097% (1 correct, 1 wrong, 69 skipped) + +**Core Pipeline**: +```python +Select → Patch → Verify (Multi-attempt) → Choose (Logic) +``` + +**Key Techniques**: + +#### 1. Multi-Attempt Verification for Confidence Assessment +```python +# Verify each patch multiple times +VALIDATION_COPY_COUNT = 3 # or more + +# Only trust patches with high consensus +judgments_aggregated = [ + [], # Candidate 1: No consensus + [True, True, True], # Candidate 2: STRONG SIGNAL + [], # Candidate 3: No consensus + # ... etc +] +``` + +#### 2. Sophisticated Scoring Function +```python +def calculate_patch_score(patch, judgments): + # Heavy penalty if invalid or no Yes votes + if not is_valid(patch) or judgments.count(True) == 0: + return -LARGE_PENALTY + + # Base score = (Yes votes)² × weight + score = (judgments.count(True) ** 2) * 5.0 + + # EXPONENTIAL size penalty - forces concise solutions + score -= (np.exp(len(patch) / 10) - 1) + + return score +``` + +**Scoring Criteria**: +- ✅ Positive score +- ✅ Top percentile (e.g., top 1%) +- ✅ Significantly outperforms second-best +- ✅ Minimum "Yes" vote threshold +- ❌ Otherwise SKIP for safety + +#### 3. Size Penalty Strategy +- **Exponential penalty** for patch length +- Forces LLM to find minimal, precise solutions +- Prevents unnecessary changes that cause side effects + +**Why Only 6th Place**: +- No **objective testing phase** (unlike top 5) +- Relied only on LLM self-verification (hallucination risk) +- Missed the importance of F2P tests + +--- + +### Common Themes Across Top Solutions + +#### What Worked: +1. **Conservative Strategy**: Better to skip than be wrong + - Wrong fixes: Heavy penalty + - Skips: Small penalty + - **Insight**: Quality > Quantity + +2. **Multi-Attempt Verification** + - Don't trust single LLM judgment + - Aggregate multiple verification attempts + - Use consensus as confidence metric + +3. **Size Penalties** + - Exponential penalty for large patches + - Forces minimal, targeted fixes + - Reduces side effects + +4. **Test Case Generation** (Critical for top places) + - Generate Fail-to-Pass tests + - Must fail on original code + - Must pass after patching + - Objective validation (not subjective LLM judgment) + +#### What Didn't Work: +1. **Aggressive Fixing**: Trying to fix everything led to more wrong fixes +2. **Single Verification**: Trusting one LLM judgment caused hallucinations +3. **Large Patches**: More code = more chance of breaking something +4. **No Objective Tests**: Pure LLM verification is unreliable + +--- + +## Code Templates + +### Template 1: Select-Patch-Verify-Choose Pipeline + +```python +import numpy as np +from typing import List, Tuple + +class KonwinskiPrizeAgent: + def __init__(self, llm_client): + self.llm = llm_client + self.VALIDATION_COPY_COUNT = 3 + self.SIZE_PENALTY_WEIGHT = 0.1 + + def select_relevant_code(self, issue: str, code_tree: dict) -> List[str]: + """Select relevant files using LLM analysis""" + prompt = f""" + Analyze this GitHub issue and identify relevant files: + + Issue: {issue} + + Code Tree: + {self._format_code_tree(code_tree)} + + Return a list of relevant files with brief explanations. + """ + # Multiple selection attempts for diversity + selections = [] + for _ in range(3): + selection = self.llm.generate(prompt) + selections.append(selection) + return selections + + def generate_patches(self, issue: str, selected_code: str) -> List[str]: + """Generate multiple candidate patches""" + prompt = f""" + GitHub Issue: {issue} + + Relevant Code: + {selected_code} + + Generate 5 different git diff patches to fix this issue. + Each patch should be minimal and targeted. + """ + patches = self.llm.generate(prompt) + return self._parse_patches(patches) + + def verify_patch(self, issue: str, patch: str) -> List[bool]: + """Multi-attempt verification for confidence assessment""" + judgments = [] + + for _ in range(self.VALIDATION_COPY_COUNT): + prompt = f""" + Issue: {issue} + + Proposed Patch: + {patch} + + Does this patch correctly fix the issue? Answer Yes or No. + """ + response = self.llm.generate(prompt) + is_yes = "yes" in response.lower() + judgments.append(is_yes) + + return judgments + + def calculate_patch_score(self, patch: str, judgments: List[bool]) -> float: + """Calculate score with exponential size penalty""" + # Heavy penalty if invalid or no Yes votes + if judgments.count(True) == 0: + return -1000.0 + + # Base score = (Yes votes)² × weight + score = (judgments.count(True) ** 2) * 5.0 + + # Exponential size penalty + score -= (np.exp(len(patch) / 10) - 1) + + return score + + def choose_best_patch(self, patches: List[str], all_judgments: List[List[bool]]) -> str: + """Choose best patch using scoring function""" + scored_patches = [] + + for patch, judgments in zip(patches, all_judgments): + score = self.calculate_patch_score(patch, judgments) + scored_patches.append((patch, score, judgments)) + + # Sort by score + scored_patches.sort(key=lambda x: x[1], reverse=True) + + # Apply strict criteria + if not scored_patches: + return None + + best_patch, best_score, best_judgments = scored_patches[0] + + # Must meet all criteria + if best_score <= 0: + return None + + if len(scored_patches) > 1: + second_score = scored_patches[1][1] + if best_score - second_score < 10: # Must be significantly better + return None + + return best_patch + + def solve_issue(self, issue: str, code_tree: dict) -> str: + """Main pipeline: Select → Patch → Verify → Choose""" + # Step 1: Select relevant code + selections = self.select_relevant_code(issue, code_tree) + selected_code = selections[0] # Use best selection + + # Step 2: Generate patches + patches = self.generate_patches(issue, selected_code) + + # Step 3: Verify patches + all_judgments = [] + for patch in patches: + judgments = self.verify_patch(issue, patch) + all_judgments.append(judgments) + + # Step 4: Choose best patch + best_patch = self.choose_best_patch(patches, all_judgments) + + return best_patch # Returns None if no patch is good enough +``` + +### Template 2: With Test Case Generation (Top 5 Approach) + +```python +class TestValidatedAgent(KonwinskiPrizeAgent): + """Enhanced agent with Fail-to-Pass test generation""" + + def generate_f2p_test(self, issue: str, code: str) -> str: + """Generate a test that fails on original code""" + prompt = f""" + GitHub Issue: {issue} + + Original Code: + {code} + + Generate a unit test that: + 1. FAILS on the current (buggy) code + 2. PASSES when the bug is fixed + + The test should be minimal and focused on the specific bug. + """ + test_code = self.llm.generate(prompt) + return test_code + + def validate_patch_with_test(self, patch: str, test_code: str, original_code: str) -> bool: + """Objective validation: test must fail on original, pass on patched""" + # Apply patch to get patched code + patched_code = self._apply_patch(original_code, patch) + + # Run test on original code (should FAIL) + original_result = self._run_test(test_code, original_code) + if original_result != "FAIL": + return False # Test doesn't fail on buggy code! + + # Run test on patched code (should PASS) + patched_result = self._run_test(test_code, patched_code) + if patched_result != "PASS": + return False # Test doesn't pass on fixed code! + + return True + + def solve_issue_with_tests(self, issue: str, code_tree: dict) -> str: + """Pipeline with test validation""" + # Select + Patch as before + selections = self.select_relevant_code(issue, code_tree) + patches = self.generate_patches(issue, selections[0]) + + # Generate test + test_code = self.generate_f2p_test(issue, selections[0]) + + # Validate each patch with test + valid_patches = [] + for patch in patches: + if self.validate_patch_with_test(patch, test_code, selections[0]): + valid_patches.append(patch) + + # Use verification to choose among valid patches + if not valid_patches: + return None + + # Apply verification logic only to valid patches + all_judgments = [] + for patch in valid_patches: + judgments = self.verify_patch(issue, patch) + all_judgments.append(judgments) + + return self.choose_best_patch(valid_patches, all_judgments) +``` + +### Template 3: Traceback Analysis (5th Place Approach) + +```python +import re + +class TracebackAwareAgent(KonwinskiPrizeAgent): + """Agent that uses regex to extract traceback info""" + + def extract_traceback(self, issue: str) -> dict: + """Extract traceback information using regex""" + traceback_patterns = [ + r'File "([^"]+)", line (\d+), in (\w+)', + r'(\w+Error): (.+)', + r'Traceback \(most recent call last\):', + ] + + traceback_info = { + 'files': [], + 'lines': [], + 'functions': [], + 'error_types': [], + 'error_messages': [], + } + + for pattern in traceback_patterns: + matches = re.findall(pattern, issue) + # Parse matches into traceback_info + + return traceback_info + + def select_with_traceback(self, issue: str, code_tree: dict) -> List[str]: + """Use traceback to prioritize files""" + traceback_info = self.extract_traceback(issue) + + # Prioritize files mentioned in traceback + prioritized_files = [] + for file_path in traceback_info['files']: + if file_path in code_tree: + prioritized_files.append(file_path) + + # Add context from nearby files + for file_path in prioritized_files: + # Add sibling files, parent directories, etc. + + return prioritized_files + + def generate_targeted_patch(self, issue: str, traceback_info: dict, code: str) -> str: + """Generate patch focused on traceback location""" + prompt = f""" + Issue: {issue} + + Error Location: + - File: {traceback_info['files']} + - Line: {traceback_info['lines']} + - Function: {traceback_info['functions']} + + Error Type: {traceback_info['error_types'][0]} + Error Message: {traceback_info['error_messages'][0]} + + Code: + {code} + + Generate a minimal git diff patch to fix this specific error. + Focus on the exact location mentioned in the traceback. + """ + patch = self.llm.generate(prompt) + return patch +``` + +--- + +## Best Practices + +### 1. Conservative Strategy > Aggressive Fixing + +**Key Insight**: The evaluation heavily penalizes wrong fixes more than skips. + +```python +# Bad: Try to fix everything +if patch_score > 0: + submit(patch) # Might submit low-quality patches + +# Good: Only submit when very confident +if (patch_score > 0 and + patch_score > second_best_score * 2 and # Significantly better + min_yes_votes >= 3): # Strong consensus + submit(patch) +else: + skip() # Better safe than sorry +``` + +### 2. Multi-Attempt Verification is Essential + +**Key Insight**: Single LLM judgments are unreliable due to hallucination. + +```python +# Bad: Trust single verification +if verify(patch) == "Yes": + trust(patch) + +# Good: Aggregate multiple verifications +verifications = [verify(patch) for _ in range(5)] +yes_count = sum(1 for v in verifications if v == "Yes") +if yes_count >= 4: # Strong consensus + trust(patch) +``` + +### 3. Exponential Size Penalties Work + +**Key Insight**: Larger patches have exponentially higher risk of side effects. + +```python +def score_with_size_penalty(patch, base_score): + # Exponential penalty + penalty = np.exp(len(patch) / 10) - 1 + return base_score - penalty + +# This forces the LLM to find minimal solutions +# rather than rewriting entire files +``` + +### 4. Objective Testing > Subjective Verification + +**Key Insight**: LLM self-verification is subjective; tests are objective. + +```python +# Less reliable: Pure LLM verification +if llm_says_patch_is_good(patch): + submit(patch) + +# More reliable: Objective test validation +if test_fails_on_original(code) and test_passes_on_patched(code, patch): + submit(patch) +``` + +### 5. Traceback Analysis Improves Localization + +**Key Insight**: Error tracebacks tell you exactly where to look. + +```python +# Use regex to extract: +# - File paths +# - Line numbers +# - Function names +# - Error types + +# Focus LLM attention on these specific locations +# rather than analyzing entire codebase +``` + +### 6. Context Window Management + +**Key Insight**: Limited context means you must prioritize information. + +```python +# Bad: Send entire codebase +context = entire_repository # Too large! + +# Good: Send only relevant files +context = select_top_k_files(issue, code_tree, k=10) + +# Better: Send only relevant functions +context = select_top_k_functions(issue, code_tree, k=5) +``` + +### 7. Model Selection + +**Open-Weight Models** (allowed in competition): +- **Qwen2.5-Coder-32B-Instruct**: Good balance of capability and size +- **DeepSeek-Coder-V2**: Strong coding performance (may be too large) +- **CodeLlama-34B**: Reliable but older + +**Strategies**: +- Use smaller models for selection/verification +- Use larger models for patch generation +- Ensemble multiple models if compute allows + +--- + +## Lessons Learned + +### What Round 1 Revealed + +1. **Real-World Code is Much Harder Than Benchmarks** + - SWE-bench Verified: ~75% top score + - Konwinski Prize: 7.5% top score + - **Gap**: Contamination-free, recent issues are significantly harder + +2. **Objective Testing is Non-Negotiable** + - All top 5 solutions used test generation + - 6th place (no tests) dropped to 0.8% + - LLM verification alone is insufficient + +3. **Quality > Quantity** + - Best strategy: Fix few issues correctly + - Worst strategy: Fix many issues incorrectly + - **Insight**: Skip when uncertain + +4. **Current AI Limitations** + - Even best open models struggle with real issues + - 90% target remains far off + - Significant room for improvement + +### Future Directions + +1. **Better Test Generation** + - Automatic test case synthesis + - Edge case coverage + - Regression prevention + +2. **Improved Retrieval** + - Better code search + - Semantic similarity matching + - Issue-to-code mapping + +3. **Multi-Agent Systems** + - Specialized agents for different tasks + - Agent communication and consensus + - Hierarchical decision making + +4. **Better Models** + - Larger context windows + - Improved code understanding + - Better reasoning capabilities + +--- + +## Resources + +### Official Resources +- **Competition Page**: https://www.kaggle.com/competitions/konwinski-prize +- **Official Website**: https://kprize.ai +- **Strategy Guide**: https://github.com/raymyers/konwinski-prize-strategy-guide + +### Solution Writeups +- **1st Place**: Eduardo Rocha de Andrade (July 2025) +- **2nd Place**: camaro (Public 2nd Place) +- **3rd Place**: Anonymous +- **4th Place**: "Select-Patch-Verify-Test" +- **5th Place**: Regex traceback analysis +- **6th Place**: https://github.com/quan16369/Kaggle-Konwinski-Prize-6th-Place-Solution- + +### Related Benchmarks +- **SWE-bench**: https://www.swebench.com/ +- **SWE-bench Verified**: https://www.swebench.com/verified +- **SWE-agent**: https://github.com/princeton-nlp/SWE-agent + +### Technical Papers +- SWE-bench Technical Report +- "Dissecting the SWE-Bench Leaderboards" (2025) +- "SWE-RM: Execution-free reward model for SWE agents" +- "DeepSWE: Reinforcement learning for code agents" + +--- + +## Summary + +The **Konwinski Prize** is a groundbreaking competition that revealed the **significant gap** between AI performance on contaminated benchmarks and real-world GitHub issue resolution. With a winning score of only **7.5%**, the competition demonstrated that: + +1. **Current AI is far from 90% automated software engineering** +2. **Objective testing is essential** for reliable code generation +3. **Conservative strategies beat aggressive approaches** +4. **Real-world coding remains an enormous challenge** for AI systems + +The competition's focus on **open-weight models**, **contamination-free evaluation**, and **real GitHub issues** makes it a valuable benchmark for the field of AI software engineering. + +--- + +**Last Updated**: January 2026 +**Sources**: Kaggle competition page, solution writeups, GitHub repositories, and news articles diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/map-2024.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/map-2024.md new file mode 100644 index 0000000..d14749f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/nlp/map-2024.md @@ -0,0 +1,346 @@ +# MAP - Charting Student Math Misunderstandings (2024) +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### MAP - Charting Student Math Misunderstandings (2024) + +**竞赛背景：** +- **主办方**：The Learning Agency (TLA) +- **目标**：从学生回答中识别数学误解 +- **应用场景**：教育评估、学习进度跟踪 +- **社会意义**：大规模数学误解诊断，改进教学方法 + +**任务描述：** +从学生回答和题目文本中识别误解： +- **输入**：题目文本 + 学生回答（可能是文本、图像、混合） +- **输出**：Top 3 相关误解 +- **挑战**：回答可能是部分正确、完全错误、或包含多步推理 + +**数据集规模：** +- 训练集：1,850+ 个回答（来自多个来源） +- 误解类别：2,587 种类型 +- 答案类型：文本、图像、混合 + +**数据特点：** +1. **多模态输入**：文本、图像、混合数据 +2. **推理链依赖**：需要分析多步推理过程 +3. **部分正确答案**：答案可能包含正确和错误元素的混合 + +**评估指标：** +- **MAP@3**：平均精度 +- 需要考虑部分正确的情况 + +**竞赛约束：** +- 计算资源限制 +- 数据隐私保护 + +**最终排名：** +- 1st Place: Team MTH 101 (Raja Biswas) - Score >0.948 MAP@3 +- 2nd Place: - +- 3rd Place: - +- 总参赛队伍：1,850+ + +**技术趋势：** +- **多阶段推理**：分步骤处理复杂推理 +- **合成数据**：LLM 生成额外训练数据 +- **知识蒸馏**：大模型 → 小模型 + +**关键创新：** +- **MiRAGE 框架** (1st Place)：Retrieval-guided Multi-stage Reasoning and Ensemble Fusion +- **Shared-prefix attention** (1st Place)：FlexAttention masks for suffix classification +- **Multi-loss training** (2nd Place)：Soft labels + synthetic data +- **CoT distillation** (通用)：20B → 8B 知识蒸馏 + +**Note:** MAP 是 Eedi 竞赛的后续版本，扩展到更完整的学生回答分析 + +--- + +## Original Summaries + +### MAP - Charting Student Math Misunderstandings (2024) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/map-charting-student-math-misunderstandings) | [Case Study](https://the-learning-agency.com/the-cutting-ed/article/case-study-math-misconceptions-competition/) | [MiRAGE Paper](https://arxiv.org/html/2511.01182v1) +**Category:** NLP/LLM (教育 AI / 误解检测) +**Key Techniques:** +- **MiRAGE 框架**: Retrieval-guided Multi-stage Reasoning and Ensemble Fusion +- **Shared-prefix attention**: FlexAttention masks for suffix classification (1st Place) +- **Multi-loss training**: Soft labels + synthetic data (2nd Place) +- **Auxiliary tasks**: Correctness + reasoning error prediction (3rd Place) +- **CoT distillation**: 20B → 8B knowledge distillation +- **Ensemble fusion**: Weighted combination of retrieval + reranking +- **Label taxonomy**: 2,587 misconception types from Vanderbilt experts + +**Results:** Top score >0.948 MAP@3 (baseline 0.75), 1,850+ teams, 39,760+ entries + +**Note:** MAP 是 Eedi 竞赛的后续版本，扩展到完整的学生回答分析 + +#### 前排方案详细技术分析 + +**1st Place - Team MTH 101 (Raja Biswas) - MAP@3 >0.948** + +核心技巧： +- **Shared-prefix attention**：使用 FlexAttention masks 让每个 suffix 只关注共享前缀，避免候选标签之间的干扰 +- **Multi-stage reasoning pipeline**：检索 → CoT 推理 → 重排的三阶段框架 +- **Soft labels with multi-loss training**：结合硬标签和软标签减少标签模糊性的影响 +- **Large ranker ensemble**：72B + 32B ranker 模型集成 +- **Distractor prediction**：预测错误答案与误解的亲和度 + +实现细节： +- 使用 FlexAttention masks 实现共享前缀注意力机制 +- 每个 suffix 可以关注共享前缀（问题 + 回答 + 解释） +- 每个 suffix 之间相互独立，避免信息泄露 +- 使用每个 suffix 的最后一个 token 的特征进行分类 +- 最终 MAP@3 >0.948，获得 $20,000 奖金 + +**2nd Place - MAP@3 ~0.947** + +核心技巧： +- **Multi-loss training with soft labels**：使用软标签（soft labels）进行训练 +- **Synthetic data augmentation**：生成 80K 合成训练数据 +- **Ensemble of LLMs**：多个 LLM 的加权集成 +- **Auxiliary tasks**：同时训练多个辅助任务（正确性、推理错误类型） + +实现细节： +- 生成软标签：平均多个模型的预测 +- 多损失训练：结合 hard labels 和 soft labels +- 解决标签模糊性问题 +- 使用温度参数调整软标签分布 + +**3rd Place - monsaraida & Masaya - MAP@3 ~0.946** + +核心技巧： +- **Multi-stage inference**：分步骤处理复杂推理 +- **Auxiliary task training**：同时训练主任务和辅助任务 +- **Confidence-based routing**：基于置信度选择模型 +- **Large models on low-confidence samples**：对低置信度样本使用 72B 大模型 + +实现细节： +- 主任务：预测误解类型 +- 辅助任务 1：预测答案是否正确 +- 辅助任务 2：预测推理错误类型 +- 多任务学习提升整体性能 + +**6th Place - Manan Jhaveri - MAP@3 ~0.944** + +核心技巧： +- **Qwen-semble**：多个 Qwen 模型的集成 +- **Data-centric approach**：重视数据质量和处理 +- **Synthetic data generation**：LLM 生成额外训练数据 + +**8th Place - MAP@3 ~0.942** + +核心技巧： +- **Embedding + ensemble**：嵌入模型与 LLM 集成 +- **Deberta + Qwen**：结合不同架构的模型 + +**4th Place - (匿名团队) - MAP@3 ~0.945** + +核心技巧： +- **多阶段推理 pipeline**：检索 → 推理 → 验证三阶段 +- **集成多样性**：不同架构和大小的模型组合 +- **软标签融合**：从多个教师模型蒸馏软标签 +- **置信度阈值**：动态调整预测阈值 + +实现细节： +- 三阶段：BM25 检索 → LLM 推理 → 交叉验证 +- 集成：72B + 32B + 8B 模型组合 +- 软标签：温度 T=2.0 的教师蒸馏 +- 动态阈值：根据验证集最优阈值选择 + +**5th Place - (匿名团队) - MAP@3 ~0.944** + +核心技巧： +- **Cross-encoder 检索**：交叉编码器精确匹配 +- **Few-shot prompting**：少样本提示增强推理 +- **数据增强**：数学问题改写和变体生成 +- **知识蒸馏**：大模型 → 小模型压缩 + +实现细节： +- Cross-encoder：Question-Misconception 对联合编码 +- Few-shot：3-5 个示例的 in-context learning +- 数据增强：改写问题、交换选项顺序、生成变体 +- 蒸馏：72B → 14B 知识蒸馏 + +**7th Place - (匿名团队) - MAP@3 ~0.943** + +核心技巧： +- **混合检索系统**：稀疏 + 密集向量检索结合 +- **Learning to Rank**：学习排序模型优化检索 +- **领域适应**：从 Eedi 迁移学习到 MAP +- **主动学习**：选择最有价值的样本标注 + +实现细节： +- 混合检索：BM25（稀疏）+ DPR（密集） +- L2R：LambdaMART 或 RankNet 学习排序 +- 领域适应：Eedi 预训练权重初始化 +- 主动学习：不确定性采样选择标注样本 + +**9th Place - (匿名团队) - MAP@3 ~0.941** + +核心技巧： +- **检索增强生成 (RAG)**：检索相关示例作为上下文 +- **提示工程优化**：精心设计的提示模板 +- **多候选筛选**：生成多个候选，选择最优 +- **后处理规则**：基于约束规则的后处理 + +实现细节： +- RAG：检索 Top-10 相似问题作为上下文 +- 提示模板：包含问题、答案、示例的结构化提示 +- 多候选：生成 5-10 个候选，选择最高置信度 +- 后处理：误解层次关系、父子关系约束 + +**10th Place - (匿名团队) - MAP@3 ~0.940** + +核心技巧： +- **对比学习**：学习问题-误解的相似度表示 +- **难样本挖掘**：挖掘困难负样本提升模型 +- **集成策略**：多个检索器的集成 +- **查询扩展**：扩展查询提高召回率 + +实现细节： +- 对比学习：InfoNCE 损失学习嵌入表示 +- 难样本挖掘：选择与查询相似但不是正确误解的样本 +- 集成：多个检索器（DPR、ColBERT、ANCE）的投票 +- 查询扩展：使用同义词、上位词扩展查询 + +**11th-20th Place 总结** + +| 排名 | 核心技术 | 关键创新 | +|------|---------|---------| +| **11th** | 多模态特征 | 结合文本、数值、图像特征 | +| **12th** | 图神经网络 | 建模误解之间的关联 | +| **13th** | 集成学习 | Stacking 多层模型集成 | +| **14th** | 特征选择 | 自动选择最相关特征 | +| **15th** | 数据清洗 | 清洗低质量和噪声数据 | +| **16th** | 迁移学习 | 从通用 NLP 任务迁移 | +| **17th** | 元学习 | 少样本学习适应新误解 | +| **18th** | 自动提示 | 自动优化提示模板 | +| **19th** | 强化学习 | RL 优化预测策略 | +| **20th** | 神经架构搜索 | NAS 自动搜索最优架构 | + +**与 Eedi 的技术演进：** + +| 技术方面 | Eedi (2024年9月) | MAP (2024年) | +|---------|------------------|--------------| +| **任务** | 错误答案与误解的亲和度 | 学生解释中的误解 | +| **输入** | 问题 + 错误答案 | 问题 + 答案 + 解释 | +| **检索** | Embedding similarity | Embedding + CoT | +| **重排** | Pointwise/Listwise | Multi-stage reasoning | +| **数据增强** | Synthetic data (LLM生成) | Synthetic data (80K) | +| **核心创新** | Distractor prediction | Shared-prefix attention | + +**MiRAGE 框架详解：** +- **M**: Misconception detection（误解检测） +- **R**: Retrieval-guided（检索引导） +- **A**: Multi-stage reasoning（多阶段推理） +- **G**: Ensemble fusion（集成融合） +- **E**: Education（教育应用） + +**关键数据：** +- 标签空间：2,587 种误解类型 +- 数据来源：Eedi + NAEP 数学问题 +- 标注者：15 名受过培训的标注员 +- 学生群体：9-14 岁（4-8 年级） + +--- + +### MAP - Charting Student Math Misunderstandings + +**竞赛背景：** +- **主办方**：The Learning Agency + Eedi + Vanderbilt University +- **目标**：预测学生数学回答中的误解（Misconception） +- **特殊性质**：测试 AI 的**教育诊断能力**，帮助教师识别学生的错误思维模式 + +**竞赛演变：** +- **Eedi (2024年9月)**: "Mining Misconceptions in Mathematics" - 第一个竞赛，预测错误答案与误解的亲和度 +- **MAP (2024年)**: "Charting Student Math Misunderstandings" - 第二个竞赛，扩展到完整的学生回答分析 +- **相同获胜者**: Team MTH 101 (Raja Biswas) 赢得了两个竞赛 + +**竞赛规模（MAP）：** +- **数据来源**：Eedi + NAEP 数学问题 +- **标注者**：15 名受过培训的标注员（有数学辅导经验） +- **学生群体**：9-14 岁（4-8 年级） +- **总队伍数**：1,850+ teams +- **总提交数**：39,760+ entries +- **奖项池**：$55,000（第 1 名 $20,000） + +**任务格式对比：** + +| 竞赛 | 任务 | 输入 | 输出 | +|------|------|------|------| +| **Eedi** | 预测错误答案与误解的亲和度 | 问题 + 错误答案 | 误解类型 | +| **MAP** | 预测学生解释中的误解 | 问题 + 答案 + 解释 | Top 25 误解预测 | + +**任务格式：** +``` +[问题文本 + 学生选择答案 + 学生解释] + ↓ +预测误解类型（Top 25 预测） + ↓ +MAP@3 评估（前 3 个预测） +``` + +**评估指标：** +- **MAP@3**: Mean Average Precision at 3 + - 第 1 次预测正确：1.0 分 + - 第 2 次预测正确：0.5 分 + - 第 3 次预测正确：0.33 分 + - 未预测正确：0 分 +- **标签空间**：2,587 种误解类型 + +**关键洞察：** +1. **误解 vs 错误**：误解是系统性的、持续的，需要针对性干预 +2. **标签层次**：正确性 → 解释质量 → 误解类型 +3. **噪声标签**：多种子验证是处理噪声的关键 +4. **检索+重排**：先用 embedding 检索，再用 CoT 推理重排 +5. **集成融合**：加权融合多个模块提升鲁棒性 + +**前排方案总结（MAP Top 10+）：** + +| 排名 | 团队 | MAP@3 | 核心技术 | 模型 | +|------|------|-------|---------|------| +| **1st** | Team MTH 101 | >0.948 | Shared-prefix attention, FlexAttention | 72B ranker + 32B ranker | +| **2nd** | - | ~0.947 | Multi-loss training, soft labels, 80K synthetic | Ensemble of LLMs | +| **3rd** | monsaraida & Masaya | ~0.946 | Auxiliary tasks, multi-stage inference | 72B models on low-confidence | +| **6th** | Manan Jhaveri | ~0.944 | Qwen-semble, data-centric | Qwen ensemble | +| **8th** | - | ~0.942 | Embedding + ensemble | Deberta + Qwen | +| **15th** | - | ~0.938 | Embedding models, semantic grouping | Manual inspection | + +--- + +**前排方案总结（Eedi Top 12）：** + +| 排名 | 团队 | MAP@25 | 核心技术 | 模型 | +|------|------|--------|---------|------| +| **1st** | Team MTH 101 | ~0.637 | Co-occurrence stats, Claude 3.5 Sonnet context | 72B + 32B ranker | +| **2nd** | Kazuhito Yonekawa et al. | ~0.636 | Multi-stage retrieve-and-rank | Qwen2.5-72B | +| **3rd** | waseda-pochi | ~0.635 | Magic boost post-processing, unknown misconception correction | Qwen2.5-32B | +| **4th** | - | ~0.634 | CoT features, grouped synthetic data | Qwen2.5-32B | +| **5th** | ebi-ktr | ~0.633 | Bi-encoder, listwise reranking | Qwen2.5-32B | +| **6th** | - | ~0.632 | QLoRA fine-tuning, ensemble | Qwen2.5-14B | +| **7th (Private) / 2nd (Public)** | terekaerumasahmet | ~0.631 | Multi-loss, soft labels | Qwen2.5-32B | +| **8th** | - | ~0.630 | Multi-stage retrieval, listwise reranking | Qwen2.5-32B | +| **9th (Private) / 7th (Public)** | - | ~0.629 | QLoRA fine-tuning | Qwen2.5-14B | +| **10th** | - | ~0.628 | Synthetic data, knowledge distillation | Qwen2.5-32B | + +**Eedi vs MAP 技术对比：** + +| 技术方面 | Eedi (2024年9月) | MAP (2024年) | +|---------|------------------|--------------| +| **任务** | 错误答案与误解的亲和度 | 学生解释中的误解 | +| **输入** | 问题 + 错误答案 | 问题 + 答案 + 解释 | +| **输出** | Top 25 误解预测 | Top 25 误解预测 | +| **检索** | Embedding similarity | Embedding + CoT | +| **重排** | Pointwise/Listwise | Multi-stage reasoning | +| **数据增强** | Synthetic data (LLM生成) | Synthetic data (80K) | +| **后处理** | Unknown misconception correction | - | + +**核心创新 - MiRAGE 框架：** +- **M**: Misconception detection（误解检测） +- **R**: Retrieval-guided（检索引导） +- **A**: Multi-stage reasoning（多阶段推理） +- **G**: Ensemble fusion（集成融合） +- **E**: Education（教育应用） + +--- + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/tabular/amp-parkinsons-2021.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/tabular/amp-parkinsons-2021.md new file mode 100644 index 0000000..82b4f3b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/tabular/amp-parkinsons-2021.md @@ -0,0 +1,593 @@ +# AMP®-Parkinson's Disease Progression Prediction (2023) + +## Competition Brief + +**竞赛基本信息** +- **主办方**: AMP (Accelerating Medicines Partnership) +- **时间**: 2023年 +- **类型**: 表格数据/医疗预测 +- **数据规模**: 小样本数据集 +- **评价目标**: SMAPE (Symmetric Mean Absolute Percentage Error) + +**任务描述** +预测帕金森病患者的疾病进展情况。使用蛋白质和肽段数据（通过质谱测量脑脊液样本）来预测患者未来的 MDS-UPDRS 评分。 + +**数据特点** +- **蛋白质数据**: 227个蛋白质特征 +- **肽段数据**: 来自多个质谱实验 +- **时间序列**: 每个患者有多次访问记录 +- **样本量**: 相对较小（小样本竞赛） +- **目标变量**: MDS-UPDRS 评分的进展 + +**评价指标** +SMAPE (Symmetric Mean Absolute Percentage Error) +- 对称性平均绝对百分比误差 +- 范围 [0, 200]，越小越好 +- 对异常值相对鲁棒 + +--- + +## Top Solutions Analysis + +### 1st Place - Connecting Dotts (Dmitry Gordeev et al.) + +**核心策略** +- **模型组合**: LightGBM + Neural Network 的简单平均 +- **特征工程**: 精心设计的蛋白质和肽段聚合特征 +- **数据处理**: 针对神经网络的标准化和二值化 + +**关键技术细节** + +1. **特征工程** + - 蛋白质和肽段的聚合统计量（均值、中位数、标准差） + - 时间序列特征的构造 + - 蛋白质-肽段关系特征的提取 + +2. **模型架构** + - **LightGBM**: 梯度提升树模型 + - **Neural Network**: 深度学习模型 + - **集成策略**: 简单平均 + +3. **数据预处理** + - NN专用预处理: 特征缩放 + - 特征二值化处理 + - 缺失值处理策略 + +**代码要点** +```python +# 模型集成示例 +final_prediction = (lgb_pred + nn_pred) / 2 +``` + +### 2nd Place - No Luck, All Skill + +**核心策略** +- 发布时间: 2023年6月19日 +- 强调特征工程的重要性 +- 多模型集成策略 + +**关键特征** +- 详细的特征工程流程 +- 模型融合技术 +- 验证策略设计 + +### 3rd Place - Hajime Tamura + +**核心策略** +- 发布时间: 2023年5月19日 +- **分组策略**: 将数据分成两组分别优化 +- 简洁的解决方案（三个主要函数） + +**关键创新** +- 数据分组优化 +- 针对性模型训练 +- 简化流程提升效率 + +### 4th/5th Place - Ambrosm (#5: Find the Control Group) + +**核心策略** +- 发布时间: 2023年5月18日 +- **控制组识别**: 关键创新点 +- 利用对照组信息改进预测 + +**关键洞察** +- 识别并分离控制组样本 +- 针对不同组别使用不同策略 +- 提升模型区分度 + +### 9th Place - Makotu + +**核心策略** +- 发布时间: 2023年5月18日 +- 详细的特征工程和模型调优 + +### 13th Place - FNOA + +**技术要点** +- 中等排名的稳定方案 +- 实用的特征工程方法 + +### 43rd Place - Wojciech Victor Fulmyk (Top 3% Silver) + +**重要发现** +- **XGBoost 和 LightGBM 表现不佳** +- 强调传统树模型在这个数据集上的局限性 +- 探索其他模型方向 + +**技术要点** +```python +# 他们的发现表明传统 GBDT 可能不是最佳选择 +# 需要考虑其他模型或更复杂的特征工程 +``` + +### 89th Place - Giba (Non-Leaky Solution) + +**核心策略** +- 强调无数据泄露的干净方案 +- 可复现的验证策略 + +--- + +## Common Techniques Across Solutions + +### 1. Feature Engineering Patterns + +**蛋白质/肽段聚合特征** +```python +# 时间聚合 +protein_stats = train.groupby('patient_id')['protein'].agg([ + 'mean', 'median', 'std', 'min', 'max' +]) + +# 肽段聚合 +peptide_stats = train.groupby('patient_id')['peptide'].agg([ + 'mean', 'count', 'nunique' +]) +``` + +**时间序列特征** +- 访问间隔时间 +- 进展速度估计 +- 基线和随访差异 + +**蛋白质-肽段关系** +- 蛋白质包含的肽数量 +- 肽段来源的蛋白质信息 + +### 2. Model Selection Insights + +**成功模型** +- LightGBM (部分方案) +- Neural Networks / MLP +- 集成方法 + +**需要谨慎的模型** +- XGBoost (43rd方案指出效果不佳) +- 纯线性模型 +- 单一模型（推荐集成） + +### 3. Validation Strategies + +**关键原则** +- 避免患者级别的数据泄露 +- 时间基础的分割 +- 分组交叉验证 + +```python +from sklearn.model_selection import GroupKFold + +gkf = GroupKFold(n_splits=5) +for train_idx, val_idx in gkf.split(X, y, groups=patient_ids): + # 训练和验证 +``` + +### 4. Data Leakage Prevention + +**常见陷阱** +- 同一患者的多次访问分散在训练/验证集 +- 未来信息泄露到训练集 +- 蛋白质/肽段测试集信息泄露 + +**预防措施** +- 严格的患者级别分割 +- 时间有序分割 +- 仔细的特征构造审计 + +--- + +## Code Templates + +### Basic Feature Engineering + +```python +import pandas as pd +import numpy as np + +def create_protein_features(train_proteins, test_proteins): + """创建蛋白质聚合特征""" + def process(df): + stats = df.groupby('patient_id')['NPX'].agg([ + ('protein_mean', 'mean'), + ('protein_std', 'std'), + ('protein_min', 'min'), + ('protein_max', 'max') + ]).reset_index() + return stats + + train_stats = process(train_proteins) + test_stats = process(test_proteins) + + return train_stats, test_stats + +def create_peptide_features(train_peptides, test_peptides): + """创建肽段聚合特征""" + def process(df): + stats = df.groupby('patient_id')['PeptideAbundance'].agg([ + ('peptide_mean', 'mean'), + ('peptide_std', 'std'), + ('peptide_count', 'count') + ]).reset_index() + return stats + + train_stats = process(train_peptides) + test_stats = process(test_peptides) + + return train_stats, test_stats + +def create_time_features(train_clinical, test_clinical): + """创建时间序列特征""" + def process(df): + df = df.copy() + df['visit_month'] = df['visit_month'].astype(int) + df['pred_month'] = df['visit_month'] + df['updrs_test_month'] + + # 计算自基线以来的时间 + df['months_since_baseline'] = df.groupby('patient_id')['visit_month'].transform(lambda x: x - x.min()) + + return df + + return process(train_clinical), process(test_clinical) +``` + +### Model Training Template + +```python +import lightgbm as lgb +from sklearn.model_selection import GroupKFold +from sklearn.metrics import mean_absolute_error + +def smape(y_true, y_pred): + """SMAPE 评估指标""" + return 100 * np.mean(2 * np.abs(y_pred - y_true) / (np.abs(y_true) + np.abs(y_pred) + 1e-8)) + +def train_lightgbm(X_train, y_train, groups, params=None): + """训练 LightGBM 模型""" + if params is None: + params = { + 'objective': 'regression', + 'metric': 'mae', + 'learning_rate': 0.01, + 'num_leaves': 31, + 'max_depth': -1, + 'feature_fraction': 0.8, + 'bagging_fraction': 0.8, + 'bagging_freq': 5, + 'verbose': -1 + } + + gkf = GroupKFold(n_splits=5) + models = [] + scores = [] + + for train_idx, val_idx in gkf.split(X_train, y_train, groups=groups): + X_tr, X_val = X_train.iloc[train_idx], X_train.iloc[val_idx] + y_tr, y_val = y_train.iloc[train_idx], y_train.iloc[val_idx] + + train_data = lgb.Dataset(X_tr, label=y_tr) + val_data = lgb.Dataset(X_val, label=y_val, reference=train_data) + + model = lgb.train( + params, + train_data, + num_boost_round=10000, + valid_sets=[train_data, val_data], + callbacks=[lgb.early_stopping(100), lgb.log_evaluation(0)] + ) + + pred = model.predict(X_val) + score = smape(y_val, pred) + + models.append(model) + scores.append(score) + + print(f'Average SMAPE: {np.mean(scores):.2f}') + + return models, scores + +# 使用示例 +# models, scores = train_lightgbm(X_train, y_train, patient_ids) +``` + +### Neural Network Template + +```python +import tensorflow as tf +from sklearn.preprocessing import StandardScaler + +def create_nn_model(input_dim, hidden_units=[256, 128, 64]): + """创建神经网络模型""" + model = tf.keras.Sequential([ + tf.keras.layers.Input(shape=(input_dim,)), + ]) + + for units in hidden_units: + model.add(tf.keras.layers.Dense( + units, + activation='relu', + kernel_regularizer=tf.keras.regularizers.l2(0.01) + )) + model.add(tf.keras.layers.Dropout(0.3)) + model.add(tf.keras.layers.BatchNormalization()) + + model.add(tf.keras.layers.Dense(1, activation='linear')) + + model.compile( + optimizer=tf.keras.optimizers.Adam(learning_rate=0.001), + loss='mae', + metrics=['mae'] + ) + + return model + +def train_nn(X_train, y_train, groups, epochs=100, batch_size=32): + """训练神经网络""" + # 标准化 + scaler = StandardScaler() + X_train_scaled = scaler.fit_transform(X_train) + + gkf = GroupKFold(n_splits=5) + models = [] + scores = [] + + for train_idx, val_idx in gkf.split(X_train_scaled, y_train, groups=groups): + X_tr, X_val = X_train_scaled[train_idx], X_train_scaled[val_idx] + y_tr, y_val = y_train.iloc[train_idx], y_train.iloc[val_idx] + + model = create_nn_model(X_train.shape[1]) + + early_stop = tf.keras.callbacks.EarlyStopping( + monitor='val_loss', + patience=10, + restore_best_weights=True + ) + + history = model.fit( + X_tr, y_tr, + validation_data=(X_val, y_val), + epochs=epochs, + batch_size=batch_size, + callbacks=[early_stop], + verbose=0 + ) + + pred = model.predict(X_val).flatten() + score = smape(y_val, pred) + + models.append((model, scaler)) + scores.append(score) + + print(f'Average SMAPE: {np.mean(scores):.2f}') + + return models, scores +``` + +### Ensemble Template + +```python +def ensemble_predictions(lgb_models, nn_models, X_test): + """集成多个模型的预测""" + # LightGBM 预测 + lgb_preds = np.mean([model.predict(X_test) for model in lgb_models], axis=0) + + # NN 预测（需要标准化） + _, scaler = nn_models[0] + X_test_scaled = scaler.transform(X_test) + nn_preds = np.mean([ + model.predict(X_test_scaled).flatten() + for model, _ in nn_models + ], axis=0) + + # 简单平均 + final_pred = (lgb_preds + nn_preds) / 2 + + return final_pred +``` + +--- + +## Best Practices + +### 1. Data Understanding + +**蛋白质数据特性** +- 227个蛋白质可能来自不同通路 +- 部分蛋白质可能高度相关 +- 需要探索蛋白质-疾病关系 + +**肽段数据特性** +- 肽数量远大于蛋白质数 +- 多个肽段可能来自同一蛋白质 +- 肽段丰度需要归一化 + +**临床数据特性** +- MDS-UPDRS 评分范围 0-260 +- 不同子评分（第一部分到第四部分） +- 访问时间间隔不均匀 + +### 2. Feature Engineering Guidelines + +**DOs** +- ✅ 创建患者级别的聚合特征 +- ✅ 利用时间序列信息 +- ✅ 探索蛋白质-肽段关系 +- ✅ 考虑蛋白质生物学意义 +- ✅ 使用领域知识构造特征 + +**DON'Ts** +- ❌ 在测试集上计算统计量 +- ❌ 混合不同患者的未来信息 +- ❌ 忽略数据的时间顺序 +- ❌ 过度使用目标编码（容易泄露） + +### 3. Model Selection Strategy + +**推荐流程** +1. 从简单模型开始（线性模型、决策树） +2. 尝试 LightGBM（部分方案有效） +3. 探索神经网络（1st方案使用） +4. 集成多个模型 +5. 针对性调整超参数 + +**模型选择考虑** +- 数据量小 → 简单模型或强正则化 +- 特征多 → 特征选择或降维 +- 时序特性 → 考虑时间序列模型 +- 集成收益 → 尝试模型融合 + +### 4. Validation Strategy + +**推荐方法** +```python +# 患者级别的 Group K-Fold +from sklearn.model_selection import GroupKFold + +gkf = GroupKFold(n_splits=5) +for fold, (train_idx, val_idx) in enumerate(gkf.split(X, y, groups=patient_ids)): + print(f'Fold {fold + 1}') + # 训练和验证 +``` + +**时间序列分割** +```python +from sklearn.model_selection import TimeSeriesSplit + +tscv = TimeSeriesSplit(n_splits=5) +for fold, (train_idx, val_idx) in enumerate(tscv.split(X)): + # 确保验证集在时间上晚于训练集 +``` + +### 5. Common Pitfalls + +**数据泄露** +- ❌ 将同一患者的多次访问分散到训练和验证集 +- ❌ 在分割前计算全局统计量 +- ❌ 使用未来信息预测过去 + +**过拟合** +- ❌ 特征过多而样本过少 +- ❌ 过度调参导致验证集泄露 +- ❌ 复杂模型在小数据集上 + +**评估偏差** +- ❌ 使用错误的评估指标 +- ❌ 忽略 SMAPE 的对称性 +- ❌ 不关注预测的分布特性 + +### 6. Domain Knowledge Integration + +**帕金森病相关** +- MDS-UPDRS 评分的临床意义 +- 蛋白质标志物的生物学作用 +- 疾病进展的非线性特性 + +**蛋白质组学** +- 质谱数据的技术变异 +- 蛋白质-肽段的定量关系 +- 缺失值的含义 + +### 7. Hyperparameter Tuning + +**LightGBM 关键参数** +```python +params = { + 'learning_rate': 0.01, # 降低学习率 + 'num_leaves': 31, # 控制复杂度 + 'max_depth': -1, # 不限制深度 + 'min_data_in_leaf': 20, # 小数据集增大此值 + 'feature_fraction': 0.8, # 特征采样 + 'bagging_fraction': 0.8, # 数据采样 + 'bagging_freq': 5, + 'lambda_l1': 0.1, # L1 正则化 + 'lambda_l2': 0.1, # L2 正则化 +} +``` + +**神经网络关键参数** +```python +# 小数据集推荐 +hidden_units = [128, 64, 32] # 减少层数和单元数 +dropout_rate = 0.3 # 增加 dropout +l2_reg = 0.01 # L2 正则化 +learning_rate = 0.001 # 适中学习率 +batch_size = 32 # 小批量 +``` + +--- + +## Key Takeaways + +1. **小样本竞赛特点** + - 特征工程比模型复杂度更重要 + - 避免过拟合是关键 + - 简单模型集成可能优于复杂单模型 + +2. **医疗数据特殊性** + - 需要理解领域知识 + - 数据泄露风险更高 + - 评估指标的临床意义 + +3. **成功的共同点** + - 仔细的特征工程 + - 严格的验证策略 + - 模型集成 + - 避免数据泄露 + +4. **需要注意的陷阱** + - XGBoost/LightGBM 不是万能的（43rd方案发现） + - 数据泄露容易但难以发现 + - 小样本的过拟合风险 + +5. **推荐的学习路径** + - 从 1st, 2nd, 3rd 方案学习顶级思路 + - 从 5th, 9th 方案学习实用技巧 + - 从 43rd 方案学习失败经验 + - 综合多个方案形成自己的方法 + +--- + +## Resources + +### Official Writeups +- [1st Place Solution - Connecting Dotts](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/connecting-dotts-1st-place-solution) +- [2nd Place Solution - No Luck, All Skill](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/no-luck-all-skill-2nd-place-solution) +- [3rd Place Solution - Hajime Tamura](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/hajime-tamura-3rd-place-solution) +- [5th Place Solution - Ambrosm](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/ambrosm-5-find-the-control-group) +- [9th Place Solution - Makotu](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/makotu-9th-place-solution) +- [13th Place Solution - FNOA](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/fnoa-13th-place-solution) +- [43rd Place Solution - Wojciech Victor Fulmyk](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/wojciech-victor-fulmyk-43rd-top-3-silver-medal-sol) +- [89th Place Solution - Giba (Non-Leaky)](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/writeups/giba-top-89-non-leaky-solution) + +### External Resources +- [H2O.ai Blog: Navigating the Parkinson's Disease Prediction Challenge with AI](https://h2o.ai/blog/2023/winners-insight-navigating-the-parkinsons-disease-prediction-challenge-with-ai/) +- [中文复现: 小样本比赛也能有稳定区分度](https://zhuanlan.zhihu.com/p/669527953) + +### Competition Pages +- [Main Competition Page](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction) +- [Data Description](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction/data) +- [Discussion Forum](https://www.kaggle.com/c/amp-parkinsons-disease-progression-prediction/discussion) + +### Code Notebooks +- [LightGBM Starter with Added Features](https://www.kaggle.com/code/sijovm/lightgbm-starter-with-added-features) +- [XGB Baseline with Added Features](https://www.kaggle.com/code/sijovm/xgb-baseline-with-added-features) +- [AMP® - PDPP EDA + TF Model](https://www.kaggle.com/code/callmewenhao/amp-pdpp-eda-tf-model) +- [AMP® - PDPP EDA](https://www.kaggle.com/code/gunesevitan/amp-pdpp-eda) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-2023.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-2023.md new file mode 100644 index 0000000..003a556 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-2023.md @@ -0,0 +1,1860 @@ +# BirdCLEF 2023 +> Last updated: 2026-01-25 +> Source count: 10+ +--- + +### BirdCLEF 2023 - Bird Sound Identification (2023) + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology, LifeCLEF +- **目标**：识别东非鸟类叫声，促进鸟类保护和生态监测 +- **应用场景**：自动化生物声学监测，替代人工识别 +- **社会意义**：大规模鸟类种群监测，生物多样性保护 +- **竞赛时间**：2023 年 3-5 月 +- **参赛队伍**：1,189 支团队 + +**任务描述：** +从肯尼亚 soundscape 音频中分类 264 种鸟类叫声： +- **多标签分类**：一个音频可能包含多种鸟类 +- **评估指标**：**Macro-averaged ROC-AUC**（所有类别的平均） +- 需要预测所有 264 个类别的概率 +- 提交格式：row_id × 264物种的概率矩阵 + +**数据集规模：** +- 训练数据：~20,000 个标注样本（5 秒片段） +- 测试数据：未标注的 soundscape 音频（需 5 秒滑动窗口预测） +- 音频长度：随机长度（5 秒到数分钟） +- 采样率：通常为 32 kHz +- 物种数量：264 种东非鸟类 + +**数据特点：** +1. **类别不平衡**：某些鸟类样本数 < 10，某些 > 1000 +2. **混合叫声**：一个音频可能包含多种鸟类 +3. **背景噪声**：风声、雨声、人声、昆虫声等环境噪声 +4. **未标注数据**：大量未标注 soundscape 可用于伪标签 +5. **领域偏移**：训练数据（哥伦比亚）与测试数据（肯尼亚）存在分布差异 + +**竞赛约束：** +- **推理限制**：仅 CPU，推理时间限制 +- 需要优化推理速度，不能使用太大模型 +- 提交文件大小限制 + +**前排方案排名：** +| 排名 | 团队/个人 | Private LB | 关键技术 | +|------|----------|------------|----------| +| **1st** | Volodymyr Sydorskyi | **0.76392** | Correct Data is All You Need - 数据清洗 + 外部数据 + 模型集成 | +| **2nd** | Griffith | ~0.75+ | SED + CNN with 7 models ensemble | +| **3rd** | ADSR | ~0.75 | SED with attention on Mel frequency bands | +| **4th** | ATFujita | 0.74424 | Knowledge Distillation Is All You Need - 知识蒸馏 + Xeno-Canto | +| **5th** | Yevhenii Maslov | ~0.74 | 外部数据 + 预训练 + 集成 | + +**技术演进（与后续版本对比）：** +| 技术点 | BirdCLEF 2023 | BirdCLEF 2024 | BirdCLEF+ 2025 | +|--------|---------------|---------------|-----------------| +| **物种数量** | 264 种 | 182 种 | 206 种（多分类群）| +| **外部数据** | Xeno-Canto 重要 | 不用外部数据更优 | Xeno-Canto 预训练重要 | +| **模型架构** | EfficientNetV2 + SED | EfficientNet B0 + RegNetY | EfficientNet + ViT | +| **损失函数** | BCE + FocalLoss | CE Loss | BCE Loss | +| **伪标签** | 高低阈值筛选 | Google Classifier 预标注 | Noisy Student | +| **推理优化** | PyTorch | OpenVINO | OpenVINO | + +--- + +## Competition Brief（竞赛简介） + +### 竞赛概述 + +BirdCLEF 2023 是 Kaggle 上举办的鸟类声音识别竞赛，目标是从东非肯尼亚的 soundscape 音频中自动识别鸟类物种。该竞赛是 BirdCLEF 系列的 2023 年版本，属于时序音频分类任务。 + +### 关键挑战 + +1. **长尾分布**：264 个物种的样本数量极不均衡 +2. **领域偏移**：训练数据与测试数据来自不同地区 +3. **背景噪声**：实际环境中的各种噪声干扰 +4. **弱监督学习**：大量未标注 soundscape 数据需要利用 +5. **计算限制**：CPU 推理限制，需要优化推理速度 + +### 评估机制 + +- **指标**：Macro-averaged ROC-AUC +- **评估方式**：每个类别独立计算 AUC，然后取平均 +- **提交格式**：CSV 文件，包含 row_id 和 264 个物种的概率列 +- **后处理**：允许基于时间和空间一致性的后处理 + +--- + +## 前排方案详细技术分析 + +### 1st Place - Volodymyr Sydorskyi (Volodymyr) + +**最终成绩**：0.76392（Private LB） + +**核心策略**：Correct Data is All You Need + +**关键技术**： + +1. **数据清洗和质量控制** + - 严格的音频质量筛选 + - 基于信噪比的过滤 + - 去除低质量标注样本 + - 时间戳验证和清洗 + +2. **外部数据策略** + - Xeno-Canto 数据集成 + - 跨年度数据利用（2021/2022 竞赛数据） + - 领域自适应技术 + - 数据重采样策略 + +3. **模型架构** + - EfficientNetV2 系列作为 backbone + - SED (Sound Event Detection) 框架 + - 多尺度特征提取 + - 注意力机制集成 + +4. **训练策略** + - 两阶段训练：预训练 + 微调 + - Focal Loss 处理类别不平衡 + - 混合精度训练 + - 梯度累积 + +5. **集成策略** + - 多模型集成（不同 backbone 和配置） + - Checkpoint averaging + - 时序平滑后处理 + - 基于物种出现时间的后处理 + +**实现细节**： +- 使用 EfficientNetV2-s 和 EfficientNetV2-m +- 7+ 模型集成 +- Mel-spectrogram 参数：n_mels=128, fmin=64, fmax=16000 +- 数据增强：SpecAugment + MixUp +- 推理优化：ONNX + 多线程 + +**代码仓库**： +- GitHub: [VSydorskyy/BirdCLEF_2023_1st_place](https://github.com/VSydorskyy/BirdCLEF_2023_1st_place) +- Kaggle Writeup: [1st place solution: Correct Data is All You Need](https://www.kaggle.com/competitions/birdclef-2023/writeups/volodymyr-1st-place-solution-correct-data-is-all-y) + +--- + +### 2nd Place - Griffith + +**最终成绩**：~0.75+（Private LB） + +**核心策略**：SED + CNN with 7 models ensemble + +**关键技术**： + +1. **SED (Sound Event Detection) 框架** + - 基于 EfficientNetV2-s 的 SED 模型 + - 强时间建模能力 + - 音频事件检测与分类结合 + - 时序一致性约束 + +2. **7 模型集成策略** + - 不同 backbone：EfficientNetV2-s, ResNet, ConvNeXt + - 不同输入尺寸和配置 + - 不同 Mel 参数组合 + - 加权集成代替简单平均 + +3. **数据增强** + - SpecAugment（时间/频率掩码） + - MixUp 数据混合 + - 颜色噪声注入 + - 音频速度和音调变化 + +4. **损失函数** + - BCE Loss（Binary Cross Entropy） + - Focal Loss 处理类别不平衡 + - Label Smoothing + - 辅助损失函数 + +**实现细节**： +- EfficientNetV2-s backbone +- SED 框架 + 自定义 CNN +- 7 个模型集成 +- Mel 参数：n_mels=128-256 不同配置 +- 数据增强：SpecAugment + MixUp + 颜色噪声 +- 推理优化：模型并行 + 批处理 + +**代码仓库**： +- GitHub: [LIHANG-HONG/birdclef2023-2nd-place-solution](https://github.com/LIHANG-HONG/birdclef2023-2nd-place-solution) +- Kaggle Writeup: [2nd place solution: SED + CNN with 7 models ensemble](https://www.kaggle.com/competitions/birdclef-2023/writeups/griffith-2nd-place-solution-sed-cnn-with-7-models-) + +--- + +### 3rd Place - ADSR + +**最终成绩**：~0.75（Private LB） + +**核心策略**：SED with attention on Mel frequency bands + +**关键技术**： + +1. **Mel 频域注意力机制** + - 在 Mel 频率维度上添加注意力 + - 自适应频率加权 + - 频带重要性学习 + - 多尺度频谱分析 + +2. **改进的 SED 框架** + - CNN + RNN 混合架构 + - 双向 LSTM 时序建模 + - CRF 层优化时序一致性 + - 多任务学习 + +3. **特征工程** + - 多尺度 Mel-spectrogram + - MFCC 特征 + - 频谱对比度增强 + - 时频域联合分析 + +4. **训练策略** + - 课程学习（从简单到困难） + - 难样本挖掘 + - 在线难样本挖掘（OHEM） + - 渐进式训练 + +**实现细节**： +- 改进的 SED 架构 +- Mel 频域注意力机制 +- 双向 LSTM 时序建模 +- 多任务学习框架 +- 课程学习策略 + +**代码仓库**： +- Kaggle Writeup: [3rd place solution: SED with attention on Mel frequency bands](https://www.kaggle.com/competitions/birdclef-2023/writeups/adsr-3rd-place-solution-sed-with-attention-on-mel-) + +--- + +### 4th Place - ATFujita + +**最终成绩**：0.74424（Private LB） + +**核心策略**：Knowledge Distillation Is All You Need + +**关键技术**： + +1. **知识蒸馏（Knowledge Distillation）** + - 使用 Kaggle Models 的 bird-vocalization-classifier 作为教师模型 + - 预计算教师模型预测 + - 蒸馏损失：KL 散度 + 学生损失 + - 温度参数调优 + +2. **Xeno-Canto 数据集成** + - 收集额外 Xeno-Canto 数据 + - 数据过滤和质量控制 + - 领域自适应 + - 数据重采样 + +3. **预训练策略** + - 在 Xeno-Canto 上预训练 + - 在竞赛数据上微调 + - 渐进式解冻 + - 学习率调度 + +4. **集成策略** + - 4 个模型集成 + - 不同 backbone + - Checkpoint averaging + - 时序平滑 + +**实现细节**： +- BaseModel + Knowledge Distillation +- 4 个模型集成 +- Xeno-Canto 预训练 +- Mel 参数：n_mels=128, fmin=64, fmax=16000 +- 数据增强：标准 SpecAugment +- 推理优化：模型量化 + +**代码仓库**： +- GitHub: [AtsunoriFujita/BirdCLEF-2023-Identify-bird-calls-in-soundscapes](https://github.com/AtsunoriFujita/BirdCLEF-2023-Identify-bird-calls-in-soundscapes) +- Kaggle Writeup: [4th Place Solution: Knowledge Distillation Is All You Need](https://www.kaggle.com/competitions/birdclef-2023/writeups/atfujita-4th-place-solution-knowledge-distillation) + +**关键创新**： +- 使用预训练的 bird-vocalization-classifier 作为教师模型 +- 蒸馏损失与标准损失的加权组合 +- 高效的伪标签生成 +- 领域自适应技术 + +--- + +### 5th Place - Yevhenii Maslov + +**最终成绩**：~0.74（Private LB） + +**核心策略**：外部数据 + 预训练 + 集成 + +**关键技术**： + +1. **外部数据利用** + - 2023/2022/2021 竞赛数据 + - Xeno-Canto 数据（2023 物种） + - 数据过滤和清洗 + - 数据平衡策略 + +2. **预训练和微调** + - 在外部数据上预训练 + - 在竞赛数据上微调 + - 分层学习率 + - 渐进式训练 + +3. **模型架构** + - EfficientNetV2 系列 + - SED 框架 + - 注意力机制 + - 多尺度特征融合 + +4. **推理优化** + - 模型量化（INT8） + - 多线程推理 + - 批处理优化 + - ONNX 导出 + +**实现细节**： +- EfficientNetV2 backbone +- SED 框架 +- 外部数据预训练 +- 5+ 模型集成 +- Mel 参数：标准配置 +- 推理优化：量化 + 多线程 + +**代码仓库**： +- GitHub: [yevmaslov](https://github.com/yevmaslov) +- Kaggle Writeup: [5th place solution](https://www.kaggle.com/competitions/birdclef-2023/writeups/yevhenii-maslov-5th-place-solution) + +--- + +### 8th Place - FURU-NAG + +**最终成绩**：~0.73（Private LB） + +**核心策略**：Implementing Multimodal Data Augmentation Methods + +**关键技术**： + +1. **多模态数据增强** + - 波形级增强：音调变化、时间拉伸、噪声注入 + - 频谱级增强：SpecAugment、频率掩码、时间掩码 + - 混合增强：MixUp、CutMix + - 自适应增强策略 + +2. **防止过拟合** + - 现实音频组合 + - 增强强度调度 + - 在线增强 + - 增强多样性 + +3. **预处理管道** + - 音频质量检查 + - 噪声过滤 + - 音频归一化 + - 特征标准化 + +**实现细节**： +- 多模态数据增强管道 +- 防止过拟合的策略 +- 现实音频组合 +- 自适应增强 + +**代码仓库**： +- Kaggle Writeup: [8th Place Solution: Implementing Multimodal Data Augmentation Methods](https://www.kaggle.com/competitions/birdclef-2023/writeups/furu-nag-8th-place-solution-implementing-multimoda) + +--- + +### 18th Place - SED with Attention + +**核心策略**：SED with attention + +**关键技术**： + +1. **注意力机制** + - 时间注意力 + - 频率注意力 + - 自注意力 + - 交叉注意力 + +2. **SED 框架改进** + - 改进的时序建模 + - 多尺度特征提取 + - 注意力加权 + - 残差连接 + +**代码仓库**： +- Kaggle Writeup: [18th place solution: SED with attention](https://www.kaggle.com/competitions/birdclef-2023/writeups/18th-place-solution-sed-with-attention) + +--- + +## Code Templates（代码模板） + +### 1. Mel-Spectrogram 特征提取 + +```python +import torch +import torchaudio +import torch.nn as nn +import numpy as np +import librosa + +class MelSpectrogramExtractor: + """BirdCLEF 2023 统一 Mel-Spectrogram 提取器""" + + def __init__( + self, + sample_rate: int = 32000, + n_mels: int = 128, + n_fft: int = 2048, + hop_length: int = 512, + fmin: float = 64.0, + fmax: float = 16000.0, + power: float = 2.0, + normalize: bool = True, + ): + self.sample_rate = sample_rate + self.n_mels = n_mels + self.n_fft = n_fft + self.hop_length = hop_length + self.fmin = fmin + self.fmax = fmax + + # 使用 torchaudio 的 MelSpectrogram + self.mel_transform = torchaudio.transforms.MelSpectrogram( + sample_rate=sample_rate, + n_fft=n_fft, + hop_length=hop_length, + n_mels=n_mels, + f_min=fmin, + f_max=fmax, + power=power, + normalized=normalize, + ) + + def extract(self, waveform: torch.Tensor) -> torch.Tensor: + """ + 提取 mel-spectrogram + + Args: + waveform: (num_samples,) 或 (batch, num_samples) + + Returns: + mel_spec: (n_mels, time) 或 (batch, n_mels, time) + """ + if waveform.dim() == 1: + waveform = waveform.unsqueeze(0) + + mel_spec = self.mel_transform(waveform) + + # 转换为对数尺度 + mel_spec = torch.log(mel_spec + 1e-9) + + return mel_spec + + def extract_fixed_length( + self, waveform: torch.Tensor, target_length: int + ) -> torch.Tensor: + """ + 提取固定长度的 mel-spectrogram（用于 5 秒音频） + + Args: + waveform: (num_samples,) + target_length: 目标时间维度 + + Returns: + mel_spec: (n_mels, target_length) + """ + mel_spec = self.extract(waveform).squeeze(0) + + # 调整到固定长度 + if mel_spec.shape[1] < target_length: + # 填充 + pad_length = target_length - mel_spec.shape[1] + mel_spec = nn.functional.pad(mel_spec, (0, pad_length)) + else: + # 裁剪（从中心） + start = (mel_spec.shape[1] - target_length) // 2 + mel_spec = mel_spec[:, start:start + target_length] + + return mel_spec + + +# 常用配置（前排方案） +CONFIGS = { + "config_128": { # EfficientNetV2-s 标准 + "n_mels": 128, + "n_fft": 2048, + "hop_length": 512, + "fmin": 64.0, + "fmax": 16000.0, + }, + "config_256": { # 高分辨率 + "n_mels": 256, + "n_fft": 4096, + "hop_length": 1024, + "fmin": 64.0, + "fmax": 16000.0, + }, +} + +# 使用示例 +extractor = MelSpectrogramExtractor(**CONFIGS["config_128"]) +waveform, sr = torchaudio.load("audio.wav") +if sr != 32000: + waveform = torchaudio.transforms.Resample(sr, 32000)(waveform) +mel_spec = extractor.extract_fixed_length(waveform.squeeze(0), target_length=313) # 5秒 -> 313帧 +``` + +### 2. SED 模型架构（2nd Place 风格） + +```python +import torch +import torch.nn as nn +import timm + +class SEDModel(nn.Module): + """ + Sound Event Detection 模型 + 基于 2nd Place Griffith 的方案 + """ + + def __init__( + self, + model_name: str = "tf_efficientnetv2_s", + num_classes: int = 264, + pretrained: bool = True, + in_channels: int = 1, + rnn_layers: int = 1, + rnn_hidden: int = 128, + ): + super().__init__() + + # Backbone（EfficientNetV2） + self.backbone = timm.create_model( + model_name, + pretrained=pretrained, + in_chans=in_channels, + num_classes=0, # 移除分类头 + global_pool="", # 移除全局池化 + ) + + # 获取 backbone 特征维度 + backbone_features = self.backbone.num_features + + # RNN 层（时序建模） + self.rnn = nn.LSTM( + input_size=backbone_features, + hidden_size=rnn_hidden, + num_layers=rnn_layers, + batch_first=True, + bidirectional=True, + ) + + # 分类头 + self.classifier = nn.Sequential( + nn.Linear(rnn_hidden * 2, rnn_hidden), + nn.ReLU(), + nn.Dropout(0.3), + nn.Linear(rnn_hidden, num_classes), + ) + + def forward(self, x, return_segmentwise=False): + """ + Args: + x: (batch, channels, n_mels, time) + return_segmentwise: 是否返回分段预测 + + Returns: + logits: (batch, num_classes) 或 (batch, time, num_classes) + """ + batch_size = x.size(0) + + # Backbone 特征提取 + # (batch, channels, n_mels, time) -> (batch, features, time') + features = self.backbone(x) + + # 转置为 (batch, time', features) + features = features.permute(0, 2, 1) + + # RNN 时序建模 + # (batch, time', features) -> (batch, time', rnn_hidden * 2) + rnn_out, _ = self.rnn(features) + + if return_segmentwise: + # 分段预测（每个时间步） + segmentwise_logits = self.classifier(rnn_out) + return segmentwise_logits + else: + # 全局预测（时间平均池化） + global_features = rnn_out.mean(dim=1) # (batch, rnn_hidden * 2) + logits = self.classifier(global_features) + return logits + + +# 使用示例 +model = SEDModel( + model_name="tf_efficientnetv2_s", + num_classes=264, + pretrained=True, + in_channels=1, + rnn_layers=1, + rnn_hidden=128, +) + +# 前向传播 +mel_spec = torch.randn(4, 1, 128, 313) # (batch, channels, n_mels, time) +logits = model(mel_spec) # (batch, 264) +segmentwise_logits = model(mel_spec, return_segmentwise=True) # (batch, time, 264) +``` + +### 3. 带 Mel 频域注意力的 SED 模型（3rd Place 风格） + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F +import timm + +class MelFrequencyAttention(nn.Module): + """Mel 频域注意力机制（3rd Place ADSR）""" + + def __init__(self, n_mels: int, reduction: int = 8): + super().__init__() + self.avg_pool = nn.AdaptiveAvgPool2d(1) + self.max_pool = nn.AdaptiveMaxPool2d(1) + + self.fc = nn.Sequential( + nn.Linear(n_mels, n_mels // reduction, bias=False), + nn.ReLU(inplace=True), + nn.Linear(n_mels // reduction, n_mels, bias=False), + ) + self.sigmoid = nn.Sigmoid() + + def forward(self, x): + """ + Args: + x: (batch, channels, n_mels, time) + + Returns: + attention: (batch, channels, n_mels, 1) + """ + # 全局平均池化和最大池化 + avg_out = self.avg_pool(x).squeeze(-1).squeeze(-1) # (batch, channels) + max_out = self.max_pool(x).squeeze(-1).squeeze(-1) # (batch, channels) + + # 通过 FC 层 + avg_out = self.fc(avg_out) + max_out = self.fc(max_out) + + # 合并并应用 sigmoid + attention = self.sigmoid(avg_out + max_out) + attention = attention.unsqueeze(-1).unsqueeze(-1) # (batch, channels, n_mels, 1) + + return attention + + +class SEDWithMelAttention(nn.Module): + """带 Mel 频域注意力的 SED 模型""" + + def __init__( + self, + model_name: str = "tf_efficientnetv2_s", + num_classes: int = 264, + pretrained: bool = True, + n_mels: int = 128, + rnn_hidden: int = 128, + ): + super().__init__() + + # Backbone + self.backbone = timm.create_model( + model_name, + pretrained=pretrained, + in_chans=1, + num_classes=0, + global_pool="", + ) + + backbone_features = self.backbone.num_features + + # Mel 频域注意力 + self.mel_attention = MelFrequencyAttention(n_mels=n_mels) + + # RNN 层 + self.rnn = nn.LSTM( + input_size=backbone_features, + hidden_size=rnn_hidden, + num_layers=1, + batch_first=True, + bidirectional=True, + ) + + # 分类头 + self.classifier = nn.Sequential( + nn.Linear(rnn_hidden * 2, rnn_hidden), + nn.ReLU(), + nn.Dropout(0.3), + nn.Linear(rnn_hidden, num_classes), + ) + + def forward(self, x, return_segmentwise=False): + """ + Args: + x: (batch, 1, n_mels, time) + + Returns: + logits: (batch, num_classes) + """ + # Backbone 特征 + features = self.backbone(x) # (batch, features, time') + + # 应用 Mel 频域注意力 + mel_att = self.mel_attention(features) # (batch, features, n_mels, 1) + features = features * mel_att + + # 转置 + features = features.permute(0, 2, 1) # (batch, time', features) + + # RNN + rnn_out, _ = self.rnn(features) + + if return_segmentwise: + segmentwise_logits = self.classifier(rnn_out) + return segmentwise_logits + else: + global_features = rnn_out.mean(dim=1) + logits = self.classifier(global_features) + return logits + + +# 使用示例 +model = SEDWithMelAttention( + model_name="tf_efficientnetv2_s", + num_classes=264, + pretrained=True, + n_mels=128, + rnn_hidden=128, +) +``` + +### 4. 数据增强（8th Place 风格） + +```python +import torch +import torchaudio +import numpy as np + +class AudioAugmentation: + """多模态音频增强（8th Place FURU-NAG）""" + + def __init__( + self, + sample_rate: int = 32000, + apply_prob: float = 0.5, + ): + self.sample_rate = sample_rate + self.apply_prob = apply_prob + + def __call__(self, waveform: torch.Tensor) -> torch.Tensor: + """应用随机增强""" + if torch.rand(1).item() > self.apply_prob: + return waveform + + # 随机选择增强方法 + augmentations = [ + self._pitch_shift, + self._time_stretch, + self._add_noise, + self._gain, + ] + + np.random.shuffle(augmentations) + + # 应用 1-2 种增强 + num_augment = np.random.randint(1, 3) + for aug in augmentations[:num_augment]: + waveform = aug(waveform) + + return waveform + + def _pitch_shift(self, waveform: torch.Tensor) -> torch.Tensor: + """音调变化""" + if torch.rand(1).item() > 0.5: + return waveform + + n_steps = np.random.uniform(-2, 2) # 半音 + waveform_np = waveform.numpy() + + # 使用 librosa 进行音调变化 + shifted = librosa.effects.pitch_shift( + waveform_np, + sr=self.sample_rate, + n_steps=n_steps, + ) + + return torch.from_numpy(shifted).float() + + def _time_stretch(self, waveform: torch.Tensor) -> torch.Tensor: + """时间拉伸""" + if torch.rand(1).item() > 0.5: + return waveform + + rate = np.random.uniform(0.8, 1.2) + waveform_np = waveform.numpy() + + # 使用 librosa 进行时间拉伸 + stretched = librosa.effects.time_stretch( + waveform_np, + rate=rate, + ) + + return torch.from_numpy(stretched).float() + + def _add_noise(self, waveform: torch.Tensor) -> torch.Tensor: + """添加噪声""" + if torch.rand(1).item() > 0.5: + return waveform + + snr = np.random.uniform(10, 30) # 信噪比 + noise = torch.randn_like(waveform) + + # 计算噪声功率 + signal_power = waveform.mean() ** 2 + noise_power = noise.mean() ** 2 + + # 调整噪声功率 + noise = noise * torch.sqrt(signal_power / (noise_power * (10 ** (snr / 10)))) + + return waveform + noise + + def _gain(self, waveform: torch.Tensor) -> torch.Tensor: + """增益调整""" + if torch.rand(1).item() > 0.5: + return waveform + + gain = np.random.uniform(0.8, 1.2) + return waveform * gain + + +class SpecAugment: + """SpecAugment 增强（频谱增强）""" + + def __init__( + self, + time_mask_param: int = 50, + freq_mask_param: int = 16, + num_time_masks: int = 2, + num_freq_masks: int = 2, + apply_prob: float = 0.5, + ): + self.time_mask_param = time_mask_param + self.freq_mask_param = freq_mask_param + self.num_time_masks = num_time_masks + self.num_freq_masks = num_freq_masks + self.apply_prob = apply_prob + + def __call__(self, spec: torch.Tensor) -> torch.Tensor: + """ + Args: + spec: (channels, n_mels, time) + + Returns: + augmented_spec: (channels, n_mels, time) + """ + if torch.rand(1).item() > self.apply_prob: + return spec + + # 时间掩码 + for _ in range(self.num_time_masks): + t = np.random.randint(0, self.time_mask_param) + t0 = np.random.randint(0, max(1, spec.size(-1) - t)) + spec[:, :, t0:t0 + t] = 0 + + # 频率掩码 + for _ in range(self.num_freq_masks): + f = np.random.randint(0, self.freq_mask_param) + f0 = np.random.randint(0, max(1, spec.size(-2) - f)) + spec[:, f0:f0 + f, :] = 0 + + return spec + + +class MixUp: + """MixUp 数据增强""" + + def __init__(self, alpha: float = 0.5, apply_prob: float = 0.5): + self.alpha = alpha + self.apply_prob = apply_prob + + def __call__( + self, + mel_spec: torch.Tensor, + labels: torch.Tensor, + ) -> tuple[torch.Tensor, torch.Tensor]: + """ + Args: + mel_spec: (batch, channels, n_mels, time) + labels: (batch, num_classes) + + Returns: + mixed_mel, mixed_labels + """ + if torch.rand(1).item() > self.apply_prob: + return mel_spec, labels + + batch_size = mel_spec.size(0) + + # 生成混合权重 + lam = np.random.beta(self.alpha, self.alpha) + + # 随机排列 + index = torch.randperm(batch_size) + + # 混合特征和标签 + mixed_mel = lam * mel_spec + (1 - lam) * mel_spec[index] + mixed_labels = lam * labels + (1 - lam) * labels[index] + + return mixed_mel, mixed_labels + + +# 使用示例 +audio_aug = AudioAugmentation(sample_rate=32000, apply_prob=0.8) +spec_aug = SpecAugment( + time_mask_param=50, + freq_mask_param=16, + num_time_masks=2, + num_freq_masks=2, + apply_prob=0.8, +) +mixup = MixUp(alpha=0.5, apply_prob=0.5) + +# 音频增强 +waveform = torchaudio.load("audio.wav")[0] +augmented_waveform = audio_aug(waveform) + +# 频谱增强 +mel_spec = torch.randn(4, 1, 128, 313) +augmented_spec = spec_aug(mel_spec) + +# MixUp +labels = torch.randint(0, 2, (4, 264)).float() +mixed_spec, mixed_labels = mixup(mel_spec, labels) +``` + +### 5. 损失函数 + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class FocalLoss(nn.Module): + """Focal Loss（处理类别不平衡）""" + + def __init__( + self, + alpha: float = 0.25, + gamma: float = 2.0, + reduction: str = "mean", + ): + super().__init__() + self.alpha = alpha + self.gamma = gamma + self.reduction = reduction + + def forward(self, inputs: torch.Tensor, targets: torch.Tensor) -> torch.Tensor: + """ + Args: + inputs: (batch, num_classes) - logits + targets: (batch, num_classes) - one-hot or multi-hot labels + + Returns: + loss + """ + bce_loss = F.binary_cross_entropy_with_logits( + inputs, targets, reduction="none" + ) + + pt = torch.exp(-bce_loss) + focal_loss = self.alpha * (1 - pt) ** self.gamma * bce_loss + + if self.reduction == "mean": + return focal_loss.mean() + elif self.reduction == "sum": + return focal_loss.sum() + else: + return focal_loss + + +class CombinedLoss(nn.Module): + """组合损失（BCE + Focal Loss）""" + + def __init__( + self, + bce_weight: float = 0.5, + focal_weight: float = 0.5, + focal_alpha: float = 0.25, + focal_gamma: float = 2.0, + label_smoothing: float = 0.0, + ): + super().__init__() + self.bce_weight = bce_weight + self.focal_weight = focal_weight + + self.focal_loss = FocalLoss( + alpha=focal_alpha, + gamma=focal_gamma, + ) + + self.label_smoothing = label_smoothing + + def forward( + self, + inputs: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + inputs: (batch, num_classes) - logits + targets: (batch, num_classes) - multi-hot labels + + Returns: + loss + """ + # Label smoothing + if self.label_smoothing > 0: + targets = targets * (1 - self.label_smoothing) + \ + self.label_smoothing / targets.size(-1) + + # BCE Loss + bce_loss = F.binary_cross_entropy_with_logits(inputs, targets) + + # Focal Loss + focal_loss = self.focal_loss(inputs, targets) + + # 组合 + loss = self.bce_weight * bce_loss + self.focal_weight * focal_loss + + return loss + + +class KnowledgeDistillationLoss(nn.Module): + """知识蒸馏损失（4th Place）""" + + def __init__( + self, + temperature: float = 4.0, + alpha: float = 0.7, # 蒸馏损失权重 + ): + super().__init__() + self.temperature = temperature + self.alpha = alpha + + def forward( + self, + student_logits: torch.Tensor, + teacher_logits: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + student_logits: (batch, num_classes) - 学生模型预测 + teacher_logits: (batch, num_classes) - 教师模型预测（预计算） + targets: (batch, num_classes) - 真实标签 + + Returns: + loss + """ + # 蒸馏损失（KL 散度） + T = self.temperature + + # Soft targets + soft_teacher = F.softmax(teacher_logits / T, dim=-1) + soft_student = F.log_softmax(student_logits / T, dim=-1) + + distillation_loss = F.kl_div( + soft_student, + soft_teacher, + reduction="batchmean", + ) * (T ** 2) + + # 学生损失（标准 BCE） + student_loss = F.binary_cross_entropy_with_logits( + student_logits, + targets, + ) + + # 组合 + loss = self.alpha * distillation_loss + (1 - self.alpha) * student_loss + + return loss + + +# 使用示例 +criterion = CombinedLoss( + bce_weight=0.5, + focal_weight=0.5, + focal_alpha=0.25, + focal_gamma=2.0, + label_smoothing=0.1, +) + +logits = torch.randn(4, 264) +targets = torch.randint(0, 2, (4, 264)).float() + +loss = criterion(logits, targets) +print(f"Combined Loss: {loss.item()}") + +# 知识蒸馏 +kd_criterion = KnowledgeDistillationLoss( + temperature=4.0, + alpha=0.7, +) + +student_logits = torch.randn(4, 264) +teacher_logits = torch.randn(4, 264) # 预计算的教师预测 + +kd_loss = kd_criterion(student_logits, teacher_logits, targets) +print(f"KD Loss: {kd_loss.item()}") +``` + +--- + +## Best Practices（最佳实践） + +### 1. 数据处理最佳实践 + +#### 1.1 音频质量筛选（1st Place） + +```python +import librosa +import numpy as np + +def calculate_snr(audio: np.ndarray, sample_rate: int) -> float: + """计算信噪比（SNR）""" + # 使用能量计算 SNR + frame_length = 2048 + frames = librosa.util.frame(audio, frame_length=frame_length, hop_length=512) + + # 计算每帧能量 + energies = np.mean(frames ** 2, axis=0) + + # 信号能量：高能量帧 + signal_energy = np.percentile(energies, 90) + # 噪声能量：低能量帧 + noise_energy = np.percentile(energies, 10) + + snr = 10 * np.log10(signal_energy / (noise_energy + 1e-9)) + return snr + +def filter_audio_by_quality( + audio_path: str, + min_snr: float = 10.0, + max_duration: float = 60.0, +) -> bool: + """根据质量筛选音频""" + try: + audio, sr = librosa.load(audio_path, sr=32000) + + # 检查 SNR + snr = calculate_snr(audio, sr) + if snr < min_snr: + return False + + # 检查时长 + duration = len(audio) / sr + if duration > max_duration: + return False + + # 检查是否静音 + rms = librosa.feature.rms(y=audio)[0] + if np.mean(rms) < 0.01: + return False + + return True + + except Exception as e: + print(f"Error loading {audio_path}: {e}") + return False + + +# 使用示例 +is_good_quality = filter_audio_by_quality("audio.wav", min_snr=10.0) +``` + +#### 1.2 外部数据集成（4th/5th Place） + +```python +from pathlib import Path +import pandas as pd + +def load_external_data( + data_dir: str, + species_list: list[str], + min_samples_per_species: int = 5, +) -> pd.DataFrame: + """加载外部数据（Xeno-Canto）""" + data_dir = Path(data_dir) + + all_records = [] + + for species in species_list: + species_dir = data_dir / species + if not species_dir.exists(): + continue + + audio_files = list(species_dir.glob("*.wav")) + \ + list(species_dir.glob("*.mp3")) + + # 过滤样本数少的物种 + if len(audio_files) < min_samples_per_species: + continue + + for audio_file in audio_files: + all_records.append({ + "filename": str(audio_file), + "species": species, + "source": "xeno_canto", + }) + + return pd.DataFrame(all_records) + + +# 使用示例 +species_list = ["bird_a", "bird_b", "bird_c"] +external_df = load_external_data( + "data/xeno_canto", + species_list, + min_samples_per_species=5, +) +``` + +### 2. 训练策略最佳实践 + +#### 2.1 两阶段训练（1st/4th Place） + +```python +import torch +import torch.nn as nn +from torch.utils.data import DataLoader + +def two_stage_training( + model: nn.Module, + train_loader_external: DataLoader, + train_loader_competition: DataLoader, + val_loader: DataLoader, + num_epochs_stage1: int = 10, + num_epochs_stage2: int = 20, + lr_stage1: float = 1e-3, + lr_stage2: float = 1e-4, +): + """两阶段训练：外部数据预训练 + 竞赛数据微调""" + + # Stage 1: 在外部数据上预训练 + print("Stage 1: Pre-training on external data") + optimizer = torch.optim.AdamW(model.parameters(), lr=lr_stage1) + criterion = nn.BCEWithLogitsLoss() + + for epoch in range(num_epochs_stage1): + model.train() + for batch in train_loader_external: + mel_spec = batch["mel_spec"].cuda() + labels = batch["labels"].cuda() + + # 前向传播 + logits = model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + # 验证 + val_loss = validate(model, val_loader, criterion) + print(f"Epoch {epoch+1}/{num_epochs_stage1}, Val Loss: {val_loss:.4f}") + + # Stage 2: 在竞赛数据上微调 + print("Stage 2: Fine-tuning on competition data") + optimizer = torch.optim.AdamW(model.parameters(), lr=lr_stage2) + + for epoch in range(num_epochs_stage2): + model.train() + for batch in train_loader_competition: + mel_spec = batch["mel_spec"].cuda() + labels = batch["labels"].cuda() + + # 前向传播 + logits = model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + # 验证 + val_loss = validate(model, val_loader, criterion) + print(f"Epoch {epoch+1}/{num_epochs_stage2}, Val Loss: {val_loss:.4f}") + + return model + + +def validate(model: nn.Module, val_loader: DataLoader, criterion: nn.Module): + """验证""" + model.eval() + total_loss = 0 + + with torch.no_grad(): + for batch in val_loader: + mel_spec = batch["mel_spec"].cuda() + labels = batch["labels"].cuda() + + logits = model(mel_spec) + loss = criterion(logits, labels) + + total_loss += loss.item() + + return total_loss / len(val_loader) +``` + +#### 2.2 Checkpoint Averaging（2nd/4th Place） + +```python +import torch +from pathlib import Path + +def average_checkpoints( + checkpoint_paths: list[str], + output_path: str, +): + """平均多个 checkpoint""" + # 加载所有 checkpoint + checkpoints = [] + for path in checkpoint_paths: + ckpt = torch.load(path, map_location="cpu") + checkpoints.append(ckpt) + + # 获取第一个 checkpoint 的结构 + avg_state_dict = checkpoints[0]["model_state_dict"].copy() + + # 计算平均 + for key in avg_state_dict.keys(): + tensors = [ckpt["model_state_dict"][key] for ckpt in checkpoints] + avg_state_dict[key] = torch.stack(tensors).mean(dim=0) + + # 保存 + torch.save({ + "model_state_dict": avg_state_dict, + "epoch": sum([ckpt["epoch"] for ckpt in checkpoints]) // len(checkpoints), + }, output_path) + + print(f"Averaged checkpoint saved to {output_path}") + + +# 使用示例 +checkpoint_dir = Path("checkpoints") +checkpoint_paths = [ + str(checkpoint_dir / "model_epoch_13.pt"), + str(checkpoint_dir / "model_epoch_15.pt"), + str(checkpoint_dir / "model_epoch_17.pt"), + str(checkpoint_dir / "model_epoch_19.pt"), + str(checkpoint_dir / "model_epoch_20.pt"), +] + +average_checkpoints( + checkpoint_paths, + "checkpoints/model_averaged.pt", +) +``` + +### 3. 推理优化最佳实践 + +#### 3.1 模型量化（5th Place） + +```python +import torch +import torch.nn as nn + +def quantize_model( + model: nn.Module, + calibration_loader: DataLoader, +): + """量化模型到 INT8""" + # 动态量化 + quantized_model = torch.quantization.quantize_dynamic( + model, + {nn.Linear, nn.Conv2d}, + dtype=torch.qint8, + ) + + # 校准（静态量化需要） + # quantized_model.eval() + # with torch.no_grad(): + # for batch in calibration_loader: + # _ = quantized_model(batch["mel_spec"]) + + return quantized_model + + +# 使用示例 +quantized_model = quantize_model(model, val_loader) +torch.save(quantized_model.state_dict(), "model_quantized.pt") +``` + +#### 3.2 ONNX 导出和优化 + +```python +import torch +import torch.onnx +import onnxruntime as ort + +def export_to_onnx( + model: nn.Module, + output_path: str, + input_shape: tuple = (1, 1, 128, 313), + opset_version: int = 13, +): + """导出模型到 ONNX""" + model.eval() + + # 创建示例输入 + dummy_input = torch.randn(*input_shape) + + # 导出 + torch.onnx.export( + model, + dummy_input, + output_path, + opset_version=opset_version, + input_names=["mel_spec"], + output_names=["logits"], + dynamic_axes={ + "mel_spec": {0: "batch_size"}, + "logits": {0: "batch_size"}, + }, + ) + + print(f"Model exported to {output_path}") + + # 优化 ONNX 模型 + sess_options = ort.SessionOptions() + sess_options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL + + session = ort.InferenceSession( + output_path, + sess_options, + providers=["CPUExecutionProvider"], + ) + + return session + + +# 使用示例 +onnx_session = export_to_onnx( + model, + "model.onnx", + input_shape=(1, 1, 128, 313), +) + +# ONNX 推理 +def predict_onnx(session: ort.InferenceSession, mel_spec: np.ndarray): + """使用 ONNX Runtime 推理""" + inputs = {session.get_inputs()[0].name: mel_spec} + outputs = session.run(None, inputs) + + return outputs[0] + + +# 批量推理 +def batch_predict_onnx( + session: ort.InferenceSession, + mel_specs: np.ndarray, + batch_size: int = 32, +): + """批量推理""" + predictions = [] + + for i in range(0, len(mel_specs), batch_size): + batch = mel_specs[i:i+batch_size] + batch_pred = predict_onnx(session, batch) + predictions.append(batch_pred) + + return np.concatenate(predictions, axis=0) +``` + +### 4. 集成策略最佳实践 + +#### 4.1 加权集成（2nd Place） + +```python +import numpy as np +from scipy.optimize import minimize + +def find_optimal_weights( + predictions: np.ndarray, + targets: np.ndarray, +) -> np.ndarray: + """ + 找到最优集成权重 + + Args: + predictions: (num_models, num_samples, num_classes) + targets: (num_samples, num_classes) + + Returns: + weights: (num_models,) + """ + num_models = predictions.shape[0] + + def objective(weights): + # 加权平均 + weighted_pred = np.average(predictions, axis=0, weights=weights) + # 计算 AUC（简化版） + auc = compute_auc(weighted_pred, targets) + return -auc # 最小化负 AUC + + # 约束：权重和为 1 + constraints = {"type": "eq", "fun": lambda w: np.sum(w) - 1} + bounds = [(0, 1) for _ in range(num_models)] + + # 初始权重：平均 + initial_weights = np.ones(num_models) / num_models + + # 优化 + result = minimize( + objective, + initial_weights, + method="SLSQP", + bounds=bounds, + constraints=constraints, + ) + + return result.x + + +def compute_auc(predictions: np.ndarray, targets: np.ndarray) -> float: + """计算 AUC（简化版）""" + from sklearn.metrics import roc_auc_score + return roc_auc_score(targets, predictions, average="macro") + + +# 使用示例 +# predictions: (num_models, num_samples, num_classes) +predictions = np.random.rand(5, 1000, 264) +targets = np.random.randint(0, 2, (1000, 264)) + +optimal_weights = find_optimal_weights(predictions, targets) +print(f"Optimal weights: {optimal_weights}") + +# 加权集成 +final_predictions = np.average(predictions, axis=0, weights=optimal_weights) +``` + +#### 4.2 Min/Max Ensemble（1st Place 风格） + +```python +import numpy as np + +def min_ensemble(predictions: np.ndarray) -> np.ndarray: + """ + Min 集成（降低不确定预测） + + Args: + predictions: (num_models, num_samples, num_classes) + + Returns: + ensemble: (num_samples, num_classes) + """ + return np.min(predictions, axis=0) + + +def max_ensemble(predictions: np.ndarray) -> np.ndarray: + """ + Max 集成（增强高置信预测） + + Args: + predictions: (num_models, num_samples, num_classes) + + Returns: + ensemble: (num_samples, num_classes) + """ + return np.max(predictions, axis=0) + + +def rank_ensemble( + predictions: np.ndarray, + method: str = "geometric", +) -> np.ndarray: + """ + Rank 集成（基于排名的集成） + + Args: + predictions: (num_models, num_samples, num_classes) + method: "geometric" or "arithmetic" + + Returns: + ensemble: (num_samples, num_classes) + """ + # 计算排名 + ranks = np.zeros_like(predictions) + for i in range(predictions.shape[0]): + ranks[i] = scipy.stats.rankdata(predictions[i], axis=-1) + + # 平均排名 + if method == "geometric": + avg_ranks = np.exp(np.mean(np.log(ranks + 1), axis=0)) - 1 + else: # arithmetic + avg_ranks = np.mean(ranks, axis=0) + + # 将排名转回概率 + ensemble = avg_ranks / avg_ranks.sum(axis=-1, keepdims=True) + + return ensemble + + +# 使用示例 +predictions = np.random.rand(5, 1000, 264) + +min_pred = min_ensemble(predictions) +max_pred = max_ensemble(predictions) +rank_pred = rank_ensemble(predictions, method="geometric") +``` + +### 5. 后处理最佳实践 + +#### 5.1 时序平滑（2nd/3rd Place） + +```python +import numpy as np +from scipy.ndimage import gaussian_filter1d + +def temporal_smoothing( + predictions: np.ndarray, + sigma: float = 1.0, +) -> np.ndarray: + """ + 时序平滑（高斯滤波） + + Args: + predictions: (num_samples, num_classes) - 按时间排序 + sigma: 高斯核标准差 + + Returns: + smoothed: (num_samples, num_classes) + """ + smoothed = np.zeros_like(predictions) + + for i in range(predictions.shape[1]): + smoothed[:, i] = gaussian_filter1d(predictions[:, i], sigma=sigma) + + return smoothed + + +def neighbor_window_smoothing( + predictions: np.ndarray, + window_size: int = 5, + neighbor_weight: float = 0.5, +) -> np.ndarray: + """ + 邻居窗口平滑（2nd Place 风格） + + Args: + predictions: (num_samples, num_classes) + window_size: 窗口大小（奇数） + neighbor_weight: 邻居权重 + + Returns: + smoothed: (num_samples, num_classes) + """ + half_window = window_size // 2 + smoothed = np.zeros_like(predictions) + + for i in range(len(predictions)): + # 获取邻居窗口 + start = max(0, i - half_window) + end = min(len(predictions), i + half_window + 1) + + window = predictions[start:end] + + # 中心样本权重为 1，邻居权重为 neighbor_weight + weights = np.ones(len(window)) + weights[weights == 1] = neighbor_weight + weights[len(window) // 2] = 1.0 + + # 加权平均 + smoothed[i] = np.average(window, axis=0, weights=weights) + + return smoothed + + +# 使用示例 +predictions = np.random.rand(100, 264) # 100 个时间步 + +smoothed_gaussian = temporal_smoothing(predictions, sigma=1.5) +smoothed_neighbor = neighbor_window_smoothing( + predictions, + window_size=5, + neighbor_weight=0.5, +) +``` + +#### 5.2 基于物种时间的后处理 + +```python +import numpy as np +import pandas as pd + +def species_time_filtering( + predictions: pd.DataFrame, + time_info: pd.DataFrame, + species_activity: dict, +) -> pd.DataFrame: + """ + 基于物种活动时间的后处理 + + Args: + predictions: (num_samples, num_species) - 包含 species columns + time_info: (num_samples,) - 包含 "time" column + species_activity: {species: {active_hours: [start, end]}} + + Returns: + filtered_predictions + """ + filtered = predictions.copy() + + for species, activity in species_activity.items(): + if species not in predictions.columns: + continue + + active_hours = activity["active_hours"] # [start, end] + + # 获取小时 + hours = pd.to_datetime(time_info["time"]).dt.hour + + # 在非活跃时间降低预测 + mask = (hours < active_hours[0]) | (hours > active_hours[1]) + filtered.loc[mask, species] *= 0.5 + + return filtered + + +# 使用示例 +predictions_df = pd.DataFrame({ + "bird_a": np.random.rand(100), + "bird_b": np.random.rand(100), +}) + +time_info_df = pd.DataFrame({ + "time": pd.date_range("2023-01-01 00:00", periods=100, freq="5min"), +}) + +species_activity = { + "bird_a": {"active_hours": [6, 18]}, # 6:00-18:00 活跃 + "bird_b": {"active_hours": [18, 6]}, # 夜间活跃 +} + +filtered_predictions = species_time_filtering( + predictions_df, + time_info_df, + species_activity, +) +``` + +--- + +## 关键技术创新总结 + +### BirdCLEF 2023 vs 2024 vs 2025 对比 + +| 维度 | BirdCLEF 2023 | BirdCLEF 2024 | BirdCLEF+ 2025 | +|------|---------------|---------------|----------------| +| **物种数量** | 264 种 | 182 种 | 206 种（多分类群）| +| **评估指标** | Macro AUC-ROC | AUC-ROC | Multi-Label AUC-ROC | +| **外部数据** | Xeno-Canto 重要 | 不用外部数据 | Xeno-Canto 预训练重要 | +| **模型架构** | EfficientNetV2 + SED | EfficientNet B0 + RegNetY | EfficientNet + ViT | +| **损失函数** | BCE + FocalLoss | CE Loss | BCE Loss | +| **伪标签** | 高低阈值筛选 | Google Classifier 预标注 | Noisy Student | +| **推理优化** | PyTorch | OpenVINO | OpenVINO | +| **关键创新** | 数据清洗 + 知识蒸馏 | Statistics T 过滤 | 自蒸馏 + 幂次变换 | + +### BirdCLEF 2023 独特创新 + +1. **数据清洗（1st Place）** + - 严格的音频质量筛选 + - 基于信噪比的过滤 + - 时间戳验证 + +2. **知识蒸馏（4th Place）** + - 使用预训练 bird-vocalization-classifier + - 蒸馏损失 + 学生损失 + - 温度参数调优 + +3. **Mel 频域注意力（3rd Place）** + - 自适应频率加权 + - 多尺度频谱分析 + - 频带重要性学习 + +4. **多模态增强（8th Place）** + - 波形级增强 + - 频谱级增强 + - 现实音频组合 + +--- + +## 参考资料 + +### Kaggle Writeups + +1. **[1st place solution: Correct Data is All You Need](https://www.kaggle.com/competitions/birdclef-2023/writeups/volodymyr-1st-place-solution-correct-data-is-all-y)** - Volodymyr Sydorskyi +2. **[2nd place solution: SED + CNN with 7 models ensemble](https://www.kaggle.com/competitions/birdclef-2023/writeups/griffith-2nd-place-solution-sed-cnn-with-7-models-)** - Griffith +3. **[3rd place solution: SED with attention on Mel frequency bands](https://www.kaggle.com/competitions/birdclef-2023/writeups/adsr-3rd-place-solution-sed-with-attention-on-mel-)** - ADSR +4. **[4th Place Solution: Knowledge Distillation Is All You Need](https://www.kaggle.com/competitions/birdclef-2023/writeups/atfujita-4th-place-solution-knowledge-distillation)** - ATFujita +5. **[5th place solution](https://www.kaggle.com/competitions/birdclef-2023/writeups/yevhenii-maslov-5th-place-solution)** - Yevhenii Maslov +6. **[8th Place Solution: Implementing Multimodal Data Augmentation Methods](https://www.kaggle.com/competitions/birdclef-2023/writeups/furu-nag-8th-place-solution-implementing-multimoda)** - FURU-NAG +7. **[18th place solution: SED with attention](https://www.kaggle.com/competitions/birdclef-2023/writeups/18th-place-solution-sed-with-attention)** + +### GitHub Repositories + +1. **[VSydorskyy/BirdCLEF_2023_1st_place](https://github.com/VSydorskyy/BirdCLEF_2023_1st_place)** - 1st Place 代码 +2. **[LIHANG-HONG/birdclef2023-2nd-place-solution](https://github.com/LIHANG-HONG/birdclef2023-2nd-place-solution)** - 2nd Place 代码 +3. **[AtsunoriFujita/BirdCLEF-2023-Identify-bird-calls-in-soundscapes](https://github.com/AtsunoriFujita/BirdCLEF-2023-Identify-bird-calls-in-soundscapes)** - 4th Place 代码 +4. **[yevmaslov](https://github.com/yevmaslov)** - 5th Place 代码 + +### 学术论文 + +1. **[Overview of BirdCLEF 2023: Automated Bird Species Identification in Eastern Africa](https://hal.science/hal-05182512/document)** - 竞赛概述 +2. **[Acoustic Bird Species Recognition at BirdCLEF 2023](https://ceur-ws.org/Vol-3497/paper-172.pdf)** - 2nd Place 学术论文 +3. **[Bird Species Recognition using Convolutional Neural Networks with Attention on Frequency Bands](https://www.researchgate.net/publication/389264675_Bird_Species_Recognition_using_Convolutional_Neural_Networks_with_Attention_on_Frequency_Bands)** + +### 技术博客 + +1. **[(Kaggle) BirdCLEF 2023 - 24th (top 2%) place solution](https://kozistr.tech/2023-05-26-birdcelf-2023/)** - 24th Place 详细方案 +2. **[763rd Place Solution for the BirdCLEF 2023 Competition](https://www.kaggle.com/competitions/birdclef-2023/discussion/451041)** - 讨论帖 + +### 其他资源 + +1. **[Leaderboard - BirdCLEF 2023](https://www.kaggle.com/competitions/birdclef-2023/leaderboard)** - 最终排行榜 +2. **[BirdCLEF 2023 Competition Page](https://www.kaggle.com/competitions/birdclef-2023)** - 竞赛主页 +3. **[Xeno-canto Extended Metadata for BirdCLEF2023](https://www.kaggle.com/datasets/mariotsaberlin/xeno-canto-extended-metadata-for-birdclef2023)** - Xeno-Canto 扩展数据集 + +--- + +## 总结 + +BirdCLEF 2023 是一个专注于东非鸟类声音识别的竞赛，其关键特点包括： + +1. **数据质量是关键**（1st Place）：严格的音频质量筛选比模型架构更重要 +2. **外部数据的战略使用**：Xeno-Canto 数据的合理集成和领域自适应 +3. **SED 框架的普及**：前排方案大多采用 SED（Sound Event Detection）框架 +4. **知识蒸馏的应用**（4th Place）：使用预训练模型作为教师提升性能 +5. **注意力机制的优化**（3rd Place）：Mel 频域注意力机制提升特征提取 +6. **多模态数据增强**（8th Place）：波形级和频谱级的联合增强 + +**与后续版本的主要区别**： +- BirdCLEF 2023 更依赖外部数据（Xeno-Canto） +- BirdCLEF 2024 强调不使用外部数据，关注数据清洗 +- BirdCLEF+ 2025 扩展到多分类群（鸟类、两栖、哺乳、昆虫） + +**技术演进趋势**： +- 从 EfficientNetV2 → EfficientNet B0/RegNetY +- 从 BCE+Focal Loss → CE Loss → BCE Loss +- 从伪标签高低阈值 → Google Classifier 预标注 → Noisy Student +- 从 PyTorch 推理 → OpenVINO 优化 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-2024.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-2024.md new file mode 100644 index 0000000..69305fc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-2024.md @@ -0,0 +1,4984 @@ +# BirdCLEF 2024 +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### BirdCLEF 2024 - Bird Sound Identification (2024) + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology (康奈尔大学鸟类学实验室) +- **目标**：识别鸟类声音，促进鸟类保护和生态监测 +- **应用场景**：自动化生物声学监测，替代人工识别 +- **社会意义**：大规模鸟类种群监测，生物多样性保护 + +**任务描述：** +从音频片段中分类 182 种鸟类叫声： +- 多标签分类（一个音频可能包含多种鸟类） +- 评估指标：**AUC-ROC**（所有类别的平均） +- 需要预测所有 182 个类别的概率 + +**数据集规模：** +- 训练数据：~240,000 个标注样本 +- 测试数据：未标注的 soundscape 音频 +- 音频长度：随机长度（5 秒到数分钟） +- 采样率：通常为 32 kHz 或 44.1 kHz + +**数据特点：** +1. **类别不平衡**：某些鸟类样本数 < 10，某些 > 1000 +2. **混合叫声**：一个音频可能包含多种鸟类 +3. **背景噪声**：风声、雨声、人声等环境噪声 +4. **未标注数据**：大量未标注 soundscape 可用于伪标签 + +**评估指标：** +- **AUC-ROC**：每个类别单独计算，然后取平均 +- 需要预测所有 182 个类别的概率 +- 对正负样本不平衡较为鲁棒 + +**竞赛约束：** +- **推理限制**：仅 CPU，最多 120 分钟 +- 这是 BirdCLEF 2024 最关键的约束 +- 需要优化推理速度，不能使用太大模型 + +**前排方案排名：** +| 排名 | 团队 | Private LB | Public LB | 关键技术 | +|------|------|------------|-----------|----------| +| **1st** | Team Kefir | **0.690** | **0.729** | Statistics T 过滤, Google Classifier 预标注, Min() Ensemble | +| **2nd** | ADSR | 0.685 | 0.733 | 伪标签迭代训练, Checkpoint Soup, 邻居窗口后处理 | +| **3rd** | NVBird | 0.68+ | 0.72+ | EfficientViT 快速推理, 两级模型架构 | +| **4th** | - | ~0.68 | ~0.72 | 邻居窗口 0.5 倍后处理 | +| **5th+** | - | ~0.67 | ~0.71 | 各种集成策略 | + +**技术演进（与 BirdCLEF 2023 对比）：** +| 技术点 | BirdCLEF 2023 | BirdCLEF 2024 | +|--------|---------------|---------------| +| **模型架构** | EfficientNetV2 + SED | EfficientNet B0 + RegNetY | +| **数据策略** | Xeno-Canto 外部数据重要 | 只使用 2024 数据更优 | +| **损失函数** | BCE + FocalLoss | CE Loss（训练用 softmax，推理用 sigmoid）| +| **伪标签** | 高低阈值筛选 | Google Classifier 预标注 + 小系数 | +| **推理优化** | ONNX | OpenVINO | +| **集成策略** | 简单平均 | Min() ensemble 降低不确定预测 | + +#### 前排方案详细技术分析 + +**1st Place - Team Kefir (vkop, great_alex, etc.)** + +核心技巧： +- **Statistics T 噪声过滤**：T = std + var + rms + pwr，使用 0.8 分位数过滤噪声数据 +- **Google Bird Classifier 预标注**：使用 Google 模型过滤低质量数据，添加伪标签（系数 0.05） +- **CE Loss + Sigmoid 推理**：训练用 CE Loss + Softmax（多分类），推理用 Sigmoid（多标签） +- **Min() Ensemble**：降低不确定预测，比简单平均更稳定 +- **OpenVINO 推理优化**：固定输入大小，加速推理 +- **只使用 2024 数据**：不使用外部数据更优 + +实现细节： +- 使用 efficientnet_b0_ns 和 regnety_008 架构 +- 6 模型集成：mean[3 efficientnet, 3 regnety] +- 训练时使用 CE Loss + Softmax，推理时使用 Sigmoid +- 最终 Private LB：0.690，Public LB：0.729 + +**2nd Place - ADSR** + +核心技巧： +- **伪标签迭代训练**：3 次迭代循环，集成自我改进 +- **Checkpoint Soup**：平均 13-50 epoch checkpoint，代替 early stopping +- **邻居窗口后处理**：相邻窗口 0.5 倍权重 +- **数据增强**：局部和全局时间/频率拉伸 +- **只用前 5 秒数据**：后续信息贡献小 + +实现细节： +- EfficientNet B0 backbone +- 不同 Mel 参数、数据子集、图像大小实现模型多样性 +- 模型间伪标签概率：25-45% +- 最终 Private LB：0.685，Public LB：0.733 + +**3rd Place - NVBird (Theo Viel)** + +核心技巧： +- **EfficientViT 快速推理**：b0/b1/m3 变体，ONNX 优化 +- **两级模型架构**：第一级（CNN + EfficientViT）→ 第二级（EfficientViT-b0 + MNASNet-100） +- **添加性 Mixup**：两段音频混合，标签取 max +- **5 fold 40 分钟推理**：ONNX 加速 + +实现细节： +- 第一级：多种 CNN（efficientnets, mobilenets, tinynets, mnasnets）和 EfficientViT +- 第二级：EfficientViT-b0 + MNASNet-100，使用伪标签训练 +- 推理时间：5 fold 40 分钟 +- 最终 Private LB：0.68+，Public LB：0.72+ + +--- + +### BirdCLEF 2024 关键创新 + +1. **Statistics T 噪声过滤（1st Place）** + ```python + # T = std + var + rms + pwr + # 使用 0.8 分位数过滤噪声数据 + T = std + var + rms + pwr + threshold = np.quantile(T, 0.8) + clean_data = data[T < threshold] + ``` + +2. **Google Bird Classifier 预标注（1st Place）** + - 使用 Google 模型过滤低质量数据 + - 如果 Google 预测与 primary label 不匹配，丢弃该 chunk + - 如果与 secondary label 匹配，替换 primary label + - 添加 Google 预测作为伪标签（系数 0.05） + +3. **CE Loss + Sigmoid 推理（1st Place）** + - 训练：CE Loss + Softmax（多分类问题） + - 推理：Sigmoid（多标签预测） + - 原因：数据大多只有 1-2 个标签，可视为多分类 + +4. **Min() Ensemble（1st Place）** + ```python + # 降低不确定预测 + predictions = np.min([model1_pred, model2_pred, model3_pred], axis=0) + ``` + +5. **伪标签迭代训练（2nd Place）** + - 3 次迭代循环 + - 每次用新集成生成伪标签 + - 25-45% 概率添加伪标签数据 + +6. **Checkpoint Soup（2nd Place）** + - 平均 13-50 epoch 的 checkpoint + - 代替 early stopping + +**与 BirdCLEF+ 2025 的差异：** +| 维度 | BirdCLEF 2024 | BirdCLEF+ 2025 | +|------|---------------|----------------| +| **物种数量** | 182 种鸟类 | 206 种（鸟类+两栖+哺乳+昆虫）| +| **评估指标** | AUC-ROC | Multi-Label AUC-ROC | +| **推理限制** | 120 分钟 CPU | 90 分钟 CPU | +| **数据策略** | 不用外部数据 | Xeno-Canto 预训练重要 | +| **关键创新** | Statistics T 过滤 | Noisy Student + 自蒸馏 | + +**参考资料：** +- [1st Place Writeup](https://www.kaggle.com/competitions/birdclef-2024/writeups/team-kefir-1st-place-solution) +- [2nd Place Solution (Japanese)](https://zenn.dev/yuto_mo/articles/85eee84a753159) +- [3rd Place GitHub](https://github.com/TheoViel/kaggle_birdclef2024) +- [1st Place Explanation (Japanese)](https://zenn.dev/yuto_mo/articles/ad43c630729073) + +**4th Place - Team** + +核心技巧： +- **邻居窗口 0.5 倍后处理**：相邻窗口 0.5 倍权重平滑 +- **多模型集成**：不同 backbone 和参数组合 +- **数据增强优化**：SpecAugment 参数调优 +- **推理加速**：ONNX + OpenVINO 优化 + +实现细节： +- 后处理：相邻窗口权重 0.5，中心窗口权重 1.0 +- 模型：EfficientNet B0/B1 + RegNet Y +- 最终 Private LB：~0.68，Public LB：~0.72 + +**5th Place - HiddenLayer** + +核心技巧： +- **两级训练策略**：第一阶段全数据，第二阶段高质量数据 +- **高质量样本筛选**：基于置信度和预测一致性 +- **Mel 频谱图优化**：n_mels=128, fmin=64, fmax=16000 +- **集成多样性**：不同随机种子和初始化 + +实现细节： +- 两级训练：Stage 1 全数据，Stage 2 筛选高置信度样本 +- 筛选条件：预测置信度 >0.7，多模型预测一致 +- Mel 参数：128 Mel bins, 10ms hop length +- 最终 Private LB：~0.677 + +**6th Place - BirdWhisperer** + +核心技巧： +- **Whisper 架构改编**：音频编码器 + 解码器结构 +- **时间掩码增强**：SpecAugment 时间掩码变体 +- **标签平滑**：防止过拟合 +- **学习率预热**：前 5 epoch warmup + +实现细节： +- Whisper改编：使用音频编码器，忽略解码器 +- 时间掩码：随机掩码 10-30% 连续时间步 +- 标签平滑：ε=0.1 +- 学习率预热：linear warmup，peak lr=1e-3 +- 最终 Private LB：~0.676 + +**7th Place - AudioZenith** + +核心技巧： +- **频域数据增强**：频率掩码、频率混合 +- **多尺度 Mel 频谱**：64/128/256 Mel bins 多尺度 +- **模型集成**：加权平均代替简单平均 +- **后处理优化**：基于物种出现时间的后处理 + +实现细节： +- 频域增强：随机屏蔽 5-15% 频带 +- 多尺度：并行训练不同 Mel 参数模型 +- 加权集成：基于验证集性能学习权重 +- 后处理：考虑物种日活动时间模式 +- 最终 Private LB：~0.675 + +**8th Place - SpecDroid** + +核心技巧： +- **Spectrogram 数据增强**：时间/频率 masking + mixup +- **ResNeSt 架构**：Split-Attention 机制 +- **Focal Loss**：处理类别不平衡 +- **TTA（测试时增强）**：多次预测平均 + +实现细节： +- ResNeSt：26-9t layers, Split-Attention blocks +- Focal Loss：γ=2.0, α=0.25 +- TTA：5 次不同增强预测平均 +- 最终 Private LB：~0.674 + +**9th Place - MelMaster** + +核心技巧： +- **自适应 Mel 频谱**：根据音频长度动态调整参数 +- **全局平均池化**：替换全连接层减少参数 +- **混合精度训练**：FP16+FP32 混合精度 +- **梯度累积**：模拟大 batch size + +实现细节： +- 自适应 Mel：短音频 n_mels=256，长音频 n_mels=128 +- GAP：全局平均池化 + 单层分类器 +- 混合精度：AMP 自动损失缩放 +- 梯度累积：accumulation_steps=4 +- 最终 Private LB：~0.673 + +**10th Place - SoundScape** + +核心技巧： +- **背景噪声去除**：基于能量的噪声门限 +- **音频切片策略**：智能选择包含鸟叫的片段 +- **轻量级模型**：MobileNetV3 快速推理 +- **知识蒸馏**：从大模型蒸馏到小模型 + +实现细节： +- 噪声门限：能量阈值 -60dB，去除静音片段 +- 音频切片：选择能量 >阈值的 5 秒片段 +- MobileNetV3：small 变体，onnx 优化 +- 知识蒸馏：EfficientNet-B0 → MobileNetV3，3:1 压缩 +- 最终 Private LB：~0.672 + +--- + +### BirdCLEF+ 2025 - Multi-Taxonomic Sound Identification (2025) + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology, LifeCLEF, Chemnitz University of Technology +- **目标**：通过声学特征识别研究不足的物种（鸟类、两栖、哺乳、昆虫） +- **应用场景**：生物多样性监测、生态恢复项目评估、被动声学监测（PAM） +- **社会意义**：自动化物种识别，支持保护行动的调整和优化 + +**任务描述：** +从连续音频数据中识别 206 个物种的声音： +- **鸟类**：主要分类群 +- **两栖动物**：青蛙和蟾蜍 +- **哺乳动物**：各种哺乳动物声音 +- **昆虫**：昆虫鸣声 + +**数据集规模：** +- 训练音频：~20,000 个标注文件（5 秒片段） +- 训练音景：未标注的连续音频（train_soundscapes） +- 测试音频：~200 个连续音频文件（需 5 秒滑动窗口预测） +- 物种数量：206 个物种 + +**数据特点：** +1. **多分类群**：涵盖鸟类、两栖、哺乳、昆虫四大类 +2. **未标注数据丰富**：大量未标注的 soundscape 数据可用于半监督学习 +3. **长尾分布**：稀有物种样本极少（某些物种 <10 个样本） +4. **领域偏移**：训练数据（哥伦比亚）与测试数据存在分布差异 +5. **背景噪声**：包含人声、环境噪声等干扰 + +**评估指标：** +- **宏平均 ROC-AUC**：跳过没有真实正标签的类别 +- 每个物种独立计算 AUC，然后宏平均 +- 对每个 row_id（5 秒窗口），预测各物种存在概率 + +**竞赛约束：** +- **90 分钟 CPU 推理限制**：这是最关键的约束 +- 提交格式：row_id × 206物种的概率矩阵 +- 需要高效推理（ONNX、OpenVINO 等） + +**最终排名：** +- 1st Place: Nikita Babych - Private LB **0.927** +- 2nd Place: Volodymyr Vialactea - Private LB ~0.926 +- 3rd Place: Team - Private LB ~0.925 +- 总参赛队伍：~2,000+ 支 + +**技术趋势：** +- **半监督学习**：伪标签技术被所有前排方案使用 +- **SED 模型**：Sound Event Detection 架构成为主流 +- **数据增强**：MixUp、Sumix、SpecAugment 广泛应用 +- **模型集成**：5-20 个模型的集成是常态 +- **领域适应**：针对训练-测试分布差异的各种处理策略 + +**关键创新：** +- **多迭代 Noisy Student** (1st Place)：MixUp + 幂次变换伪标签 +- **Soft AUC Loss** (4th Place)：支持软标签的 AUC 损失函数 +- **自蒸馏技术** (5th Place)：迭代丰富次要标签 +- **Silero VAD 预处理** (5th Place)：去除人声干扰 +- **滑动窗口推理** (1st Place)：帧预测平均，避免数据丢弃 + +**前排方案总结（Top 14）：** + +| 排名 | 团队/作者 | 核心技术 | 模型 | 关键创新 | +|------|----------|---------|------|----------| +| **1st** | Nikita Babych | Multi-Iterative Noisy Student + MixUp | SED模型 | 幂次变换伪标签 + 滑动窗口推理 | +| **2nd** | Volodymyr Vialactea | Pseudo-labeling + 预训练 | tf_efficientnetv2_s + eca_nfnet_l0 | Xeno-Canto 预训练 + 5秒片段 | +| **3rd** | - | 20 模型集成（10 CNN + 10 SED） | 多种 backbone | BirdCLEF 2023+2025 数据合并 | +| **4th** | dylan.liu | Soft AUC Loss + 半监督 | EfficientNet 系列 | 自定义 soft AUC 损失函数 | +| **5th** | Noir | Self-Distillation | EfficientNet 系列 | Silero VAD + 三阶段自蒸馏 | +| **6th** | - | SED + 自定义 AttBlockV2 | tf_efficientnet_b3 | segmentwise_logit 伪标签 | +| **7th** | - | 伪标签迭代训练 | 多种 CNN | BirdNET 提取音频片段 | +| **8th** | - | 硬 Mixup + 双向蒸馏 | SED + CNN | 在线伪标签 + 帧级监督 | +| **9th** | - | 两阶段策略 | SED + CNN | RMS 采样 + FocalBCE | +| **10th** | lhwcv | 领域适应 + 改进损失 | 多模型 | 高低阈值筛选 + 负样本惩罚 | +| **11th** | - | CE Loss + 熵值筛选 | tf_efficientnetv2_b3/s | 206→316 类扩展 | +| **12th** | - | Checkpoint Soups + EMA | 12 个 SED 模型 | OpenVINO 推理加速 | +| **13th** | H.K.Z. | 领域偏移处理 | seresnext26t + v2_b3 | Sumix + 罕见物种模型 | +| **14th** | - | 知识蒸馏 | tf_efficientnetv2_m | 块级伪标签 + 加权蒸馏 | + +#### 前排方案详细技术分析 + +**1st Place - Multi-Iterative Noisy Student (Nikita Babych)** + +核心技巧： +- **多迭代 Noisy Student 自训练**：MixUp + 幂次变换伪标签，固定混合权重 0.5 +- **SED 帧预测推理**：相邻音频块的帧预测平均（1D 滑动窗口），避免丢弃有价值数据 +- **幂次变换伪标签**：直接温度缩放会提高噪声概率，幂次变换可防止噪声放大 +- **Xeno-Canto 扩展数据**：针对两栖类和昆虫类标签组训练单独模型 + +实现细节： +- 使用 20 秒音频块处理 +- 伪标签采样器根据每个 soundscape 标签最大值之和分配权重 +- 推理通过平均相邻块重叠的帧预测，然后平滑和 delta shift + +**2nd Place - Pseudo-labeling + 预训练 (Volodymyr Vialactea)** + +核心技巧： +- **Xeno-Canto 预训练**：下载外部数据并清洗，过滤当年比赛物种避免数据泄漏 +- **5 秒随机片段**：尝试多种采样方法减少误报 +- **预训练模型微调**：AUC 从 0.83-0.84 跳升至 0.86-0.87 +- **多种验证策略**：确保每个类至少有一个样本 +- **平衡采样策略**：平衡、平方和上采样等多种策略 + +实现细节： +- 使用 tf_efficientnetv2_s 和 eca_nfnet_l0 作为骨干网络 +- Spec → 2D CNN 方法 +- 保留 RandomFiltering 和 SpecAug 设置 + +**3rd Place - 20 模型集成 (Team)** + +核心技巧： +- **BirdCLEF 2023+2025 数据合并**：结合历年数据扩充训练集 +- **20 模型集成**：10 CNN + 10 SED 模型 +- **两组 Mel 参数**：n_mels=128 和 96 探索不同频谱分辨率 +- **随机抽样代替前 5 秒**：基于 RMS 的抽样方法 +- **人声作为背景噪声**：提高环境适应性 + +实现细节： +- 使用多种 backbone：tf_efficientnet、mnasnet 等 +- CutMix、MixUp、Sumix 数据增强 +- Focal BCE 损失函数处理类别不平衡 +- 所有模型导出为 ONNX 格式 + +**4th Place - Soft AUC Loss (dylan.liu)** + +核心技巧： +- **Soft AUC 损失函数**：支持软标签，解决 AUC 损失不支持软标签问题 +- **半监督学习**：10 个 SED 模型对前 10 秒音频生成伪标签 +- **音频混合增强**：两段音频混合，标签取最大值 + +实现细节： +- Soft AUC 损失使 LB 从 0.850 提升到 0.901 +- 使用 EfficientNet 和 EfficientNetV2 系列 +- 10 个使用 EfficientNet 系列模型训练的 SED 模型 + +**5th Place - Self-Distillation (Noir)** + +核心技巧： +- **Silero VAD 数据清洗**：检测并去除包含人声的音频片段 +- **自蒸馏技术**：迭代将模型预测作为新标签丰富次要标签 +- **三阶段训练**： + 1. 初始训练 + 2. 仅使用 train_audio 自蒸馏 + 3. 结合 train_audio 和 train_soundscapes 自蒸馏 + +实现细节： +- 样本量 <30 的类别手动筛选 +- 清洗后文件使用前 60 秒，其他文件使用前 30 秒 +- 样本量 <20 的类别复制以平衡数据集 + +**6th Place - SED + AttBlockV2** + +核心技巧： +- **自定义 AttBlockV2**：通过 softmax 和 tanh 归一化，默认使用 sigmoid +- **segmentwise_logit 伪标签**：clipwise_output 值过小，使用 segmentwise_logit 生成伪标签 +- **伪标签迭代**：多轮训练，每轮使用多模型的 segmentwise_logit 输出 + +实现细节： +- 使用 tf_efficientnet_b3.ns_jft_in1k 和 tf_efficientnetv2_b3.in21k +- nn.BCEWithLogitsLoss 对 clipwise_output 和 segmentwise_logit 进行训练 + +**7th Place - BirdNET 片段提取** + +核心技巧： +- **BirdNET 提取音频片段**：对 train_soundscapes 推断，提取置信度 >0.1 的片段 +- **50% 伪标签概率**：训练期间随机从 soundscape 采样，50% 概率使用伪标签 +- **模型融合限制**：3 个模型足够，过多会损害分数 + +实现细节： +- 伪标签需归一化：`labels = labels - np.min(labels)` +- 使用原始信号模型和简单 CNN 增加集成多样性 + +**8th Place - 硬 Mixup + 双向蒸馏** + +核心技巧： +- **硬 Mixup**：数据混合后，损失为混合标签的损失 +- **在线伪标签**：训练过程中在线生成伪标签（片段级和帧级） +- **双向知识蒸馏**：不同模型相互学习 +- **MLD 知识蒸馏**：按 2023 年方案进行 + +实现细节： +- 伪标签阈值选择 0.4，平衡假阴性和假阳性 +- 两个 SED 模型 + 一个 CNN 模型 + +**9th Place - 两阶段策略** + +核心技巧： +- **RMS 采样**：基于信号能量的采样方法，比随机采样更有效 +- **去除 50% 人声**：完全去除会影响性能 +- **两阶段模型**： + 1. SED + CNN 模型（FocalBCE 和 CE+BCE） + 2. 伪标签再训练（提升 0.02+） + +实现细节： +- TTA：10 秒片段和 2 秒窗口长度 +- 原始信号：PitchShift、Shift、Sumix +- Mel-Spectrogram：Mixup2、Time masking、FilterAugment、FrequencyMasking、PinkNoise + +**10th Place - 领域适应 + 改进损失 (lhwcv)** + +核心技巧： +- **高低阈值筛选**：从 stage1 模型生成软标签，筛选可信正负样本 +- **负样本惩罚策略**：对置信度较低的正样本也进行惩罚 +- **多分辨率 Mel 参数**：384x160、384x256、320x192、320x160 等 + +实现细节： +- SED + CE loss 基线 +- 平滑核预测平滑，alpha 值根据参考频率动态调整 + +**11th Place - CE Loss + 类扩展** + +核心技巧： +- **类别扩展**：从 206 类扩展至 316 类 +- **熵值筛选**：选择高质量伪标签 +- **CE Loss 替代 BCE**：性能从 0.83 提升至 0.88 + +实现细节： +- 最大样本 500，<10 样本类别上采样 +- 集成 5 个 v2b3 + 1 个 v2s 模型 + +**12th Place - Checkpoint Soups + EMA** + +核心技巧： +- **Checkpoint Soups**：平均第 30-50 epoch 权重，缓解稀有类宏 AUC 不稳定 +- **EMA（指数移动平均）**：衰减系数 0.999 +- **少数类子集训练**：冻结所有类预训练主干，仅对少数类 SED 头训练 + +实现细节： +- 12 个 OpenVINO 转换的 SED 模型 +- 加权移动平均 + 文件级平均概率后处理（提升 0.07-0.08） +- 三种不同管道类型集成 + +**13th Place - 领域偏移处理 (H.K.Z.)** + +核心技巧： +- **Sumix 替代 Mixup**：在原始音频信号上应用 +- **移除人声**：减少训练-测试分布差异 +- **罕见物种模型**：训练特定罕见物种模型，显著提升分数 + +实现细节： +- 基于 2023 年第二名代码训练基础 SED 模型 +- 四个步骤：基础模型、伪标签增强、模型集成、罕见物种模型 + +**14th Place - 知识蒸馏** + +核心技巧： +- **块级伪标签**：来自教师模型的 10 秒块级伪标签 +- **加权蒸馏**：全音频平均伪标签（0.3）+ 块级伪标签（0.7） +- **多轮蒸馏**：每轮基于 LB 改进选择最佳教师模型 + +实现细节： +- 仅使用 tf_efficientnetv2_m.in21k +- 邻近剪辑平滑：权重 0.1、0.8、0.1 +- OpenVINO 加速推理 + +--- + +## Original Summaries + +### BirdCLEF 2024 - Bird Sound Identification (2024) - 2026-01-23 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/birdclef-2024) +**Category:** Time Series (音频分类 / 生物声学) +**Summary:** 182 种鸟类叫声多标签分类竞赛。数据包含 240,000+ 标注样本和未标注 soundscape。AUC-ROC 评估，CPU 120 分钟推理限制。**1st Place: Team Kefir** (vkop, great_alex, etc.)，Private LB 0.690。 + +**Key Techniques:** +- **Statistics T 噪声过滤**: T = std + var + rms + pwr，0.8 分位数过滤 +- **Google Bird Classifier 预标注**: 过滤低质量数据 + 伪标签生成（系数 0.05） +- **CE Loss + Sigmoid 推理**: 训练用 softmax（多分类），推理用 sigmoid（多标签） +- **Min() Ensemble**: 降低不确定预测，比简单平均更稳定 +- **伪标签迭代训练** (2nd Place): 3 次迭代循环，集成自我改进 +- **Checkpoint Soup** (2nd Place): 平均 13-50 epoch checkpoint 代替 early stopping +- **EfficientViT 快速推理** (3rd Place): ONNX 优化，5 fold 40 分钟 + +**Results:** 1st place (Private LB: 0.690, Public LB: 0.729, 2935 teams) + +**Resources:** +- [1st Place Writeup](https://www.kaggle.com/competitions/birdclef-2024/writeups/team-kefir-1st-place-solution) +- [2nd Place Solution (Japanese)](https://zenn.dev/yuto_mo/articles/85eee84a753159) +- [3rd Place GitHub](https://github.com/TheoViel/kaggle_birdclef2024) +- [1st Place Explanation (Japanese)](https://zenn.dev/yuto_mo/articles/ad43c630729073) + +### BirdCLEF+ 2025 - Multi-Taxonomic Sound Identification (2025) - 2026-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/birdclef-2025) | [知乎 14个高分方案](https://zhuanlan.zhihu.com/p/1920582942931019095) +**Category:** Time Series (音频分类 / 生物声学) +**Summary:** 多分类群声音识别竞赛。数据包含 206 个物种（鸟类、两栖、哺乳、昆虫），需从连续音频中识别物种。**1st Place: Nikita Babych**，Private LB 0.927。 + +**Key Techniques:** +- **Noisy Student 自训练**: 多迭代半监督学习，MixUp 混合伪标签与训练数据 +- **自蒸馏 (Self-Distillation)**: 模型预测作为新标签迭代训练 +- **SED (Sound Event Detection)**: 帧级预测 + 滑动窗口推理 +- **伪标签技术**: 利用未标注 train_soundscapes 数据 +- **领域适应**: 解决训练-测试分布差异 +- **Soft AUC Loss**: 支持软标签的 AUC 损失函数 +- **Silero VAD**: 去除人声干扰 + +**Results:** 1st place (Private LB: 0.927, ~2000 teams) + +**Resources:** +- [1st Place Solution (Kaggle)](https://www.kaggle.com/competitions/birdclef-2025/discussion/583577) +- [2nd Place Solution](https://www.kaggle.com/competitions/birdclef-2025/discussion/583699) +- [5th Place Solution](https://www.kaggle.com/competitions/birdclef-2025/discussion/583312) +- [Chinese Summary - 14 Solutions](https://zhuanlan.zhihu.com/p/1920582942931019095) + +--- + +## Code Templates + +### Statistics T 噪声过滤（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 的噪声过滤技巧，使用信号统计量过滤低质量数据： + +```python +import numpy as np +import librosa + +class StatisticsTNoiseFilter: + """ + Statistics T 噪声过滤 + 参考：BirdCLEF 2024 1st Place Solution + """ + + def __init__(self, quantile: float = 0.8): + self.quantile = quantile + + def compute_statistics(self, audio: np.ndarray, sample_rate: int) -> dict: + """计算音频统计量""" + # RMS (Root Mean Square) + rms = librosa.feature.rms(y=audio)[0] + + # 零交叉率 (Zero Crossing Rate) + zcr = librosa.feature.zero_crossing_rate(audio)[0] + + # 标准差 + std = np.std(audio) + + # 方差 + var = np.var(audio) + + # 功率 + pwr = np.mean(audio ** 2) + + return { + 'std': std, + 'var': var, + 'rms': np.mean(rms), + 'pwr': pwr, + 'zcr': np.mean(zcr), + } + + def compute_T(self, stats: dict) -> float: + """计算统计量 T""" + T = ( + stats['std'] + + stats['var'] + + stats['rms'] + + stats['pwr'] + ) + return T + + def filter_audio( + self, + audio_paths: list[str], + sample_rate: int = 32000 + ) -> list[str]: + """ + 过滤噪声音频 + + Args: + audio_paths: 音频文件路径列表 + sample_rate: 采样率 + + Returns: + filtered_paths: 过滤后的音频路径列表 + """ + T_values = [] + + # 计算所有音频的 T 值 + for path in audio_paths: + audio, _ = librosa.load(path, sr=sample_rate) + stats = self.compute_statistics(audio, sample_rate) + T = self.compute_T(stats) + T_values.append(T) + + # 使用分位数过滤 + threshold = np.quantile(T_values, self.quantile) + + # 只保留 T 值低于阈值的音频（噪声较小） + filtered_paths = [ + path for path, T in zip(audio_paths, T_values) + if T < threshold + ] + + print(f"过滤前: {len(audio_paths)} 过滤后: {len(filtered_paths)}") + return filtered_paths +``` + +### Google Bird Classifier 预标注（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 使用 Google Bird Vocalization Classifier 进行数据过滤和预标注： + +```python +import numpy as np +import pandas as pd +from typing import Optional + +class GoogleClassifierPreLabeler: + """ + Google Bird Classifier 预标注 + 参考：BirdCLEF 2024 1st Place Solution + """ + + def __init__(self, model, pseudo_label_coeff: float = 0.05): + """ + Args: + model: Google Bird Vocalization Classifier + pseudo_label_coeff: 伪标签系数 + """ + self.model = model + self.pseudo_label_coeff = pseudo_label_coeff + + def predict(self, audio_chunk: np.ndarray) -> dict: + """使用 Google 模型预测""" + # 假设 model 返回 {class_name: probability} + predictions = self.model.predict(audio_chunk) + return predictions + + def filter_and_relabel( + self, + audio_path: str, + primary_label: str, + secondary_labels: Optional[list[str]] = None + ) -> Optional[dict]: + """ + 过滤低质量数据并重新标注 + + Args: + audio_path: 音频路径 + primary_label: 主要标签 + secondary_labels: 次要标签 + + Returns: + filtered_label: 过滤后的标签字典，None 表示应丢弃 + """ + # 获取 Google 预测 + predictions = self.predict(audio_path) + max_class = max(predictions, key=predictions.get) + max_prob = predictions[max_class] + + # 过滤：如果最大预测与 primary label 不匹配，丢弃 + if max_class != primary_label: + # 检查是否与 secondary label 匹配 + if secondary_labels and max_class in secondary_labels: + # 替换 primary label + primary_label = max_class + else: + # 丢弃该 chunk + return None + + # 构建标签向量 + num_classes = len(predictions) + label_vector = np.zeros(num_classes) + + # Primary label 权重 0.5 + label_vector[primary_label] = 0.5 + + # Secondary labels 分配剩余 0.5 + if secondary_labels: + for sec_label in secondary_labels: + label_vector[sec_label] += 0.5 / len(secondary_labels) + + # 添加 Google 预测作为伪标签 + for class_name, prob in predictions.items(): + label_vector[class_name] += self.pseudo_label_coeff * prob + + return {'label_vector': label_vector, 'primary': primary_label} + + def relabel_soundscape(self, audio_path: str) -> np.ndarray: + """为 soundscape 生成伪标签""" + predictions = self.predict(audio_path) + return np.array([predictions.get(cls, 0) for cls in range(self.num_classes)]) +``` + +### CE Loss + Sigmoid 推理（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 的创新：训练用 CE Loss + Softmax，推理用 Sigmoid： + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class CESigmoidTrainer: + """ + CE Loss 训练 + Sigmoid 推理 + 参考：BirdCLEF 2024 1st Place Solution + + 核心思想： + - 训练时用 CE Loss + Softmax（多分类问题） + - 推理时用 Sigmoid（多标签预测） + - 原因：数据大多只有 1-2 个标签，可视为多分类 + """ + + def __init__(self, model: nn.Module, num_classes: int): + self.model = model + self.num_classes = num_classes + self.criterion = nn.CrossEntropyLoss() + + def train_step(self, batch: dict) -> torch.Tensor: + """ + 训练步骤：使用 CE Loss + Softmax + + Args: + batch: 包含 'mel_spec' 和 'labels' + + Returns: + loss: CE Loss + """ + mel_spec = batch['mel_spec'] # (B, C, H, W) + labels = batch['labels'] # (B, num_classes) + + # 前向传播 + logits = self.model(mel_spec) # (B, num_classes) + + # 对于多标签数据，取最大标签作为训练目标 + # （因为 CE Loss 是多分类损失） + target_labels = torch.argmax(labels, dim=1) # (B,) + + # CE Loss + Softmax + loss = self.criterion(logits, target_labels) + + return loss + + @torch.no_grad() + def predict(self, mel_spec: torch.Tensor) -> torch.Tensor: + """ + 推理步骤：使用 Sigmoid + + Args: + mel_spec: (B, C, H, W) + + Returns: + probabilities: (B, num_classes), Sigmoid 概率 + """ + logits = self.model(mel_spec) # (B, num_classes) + + # 推理时使用 Sigmoid（多标签预测） + probabilities = torch.sigmoid(logits) + + return probabilities + + def fit(self, train_loader, val_loader, num_epochs: int, lr: float = 1e-3): + """训练循环""" + optimizer = torch.optim.AdamW(self.model.parameters(), lr=lr) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=num_epochs + ) + + for epoch in range(num_epochs): + # 训练 + self.model.train() + train_loss = 0 + for batch in train_loader: + loss = self.train_step(batch) + loss.backward() + optimizer.step() + optimizer.zero_grad() + train_loss += loss.item() + + # 验证（用 Sigmoid） + self.model.eval() + val_preds = [] + val_labels = [] + for batch in val_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + probs = self.predict(mel_spec) + val_preds.append(probs.cpu().numpy()) + val_labels.append(labels.cpu().numpy()) + + # 计算验证指标 + val_preds = np.concatenate(val_preds) + val_labels = np.concatenate(val_labels) + val_auc = self.compute_auc(val_labels, val_preds) + + print(f"Epoch {epoch}: Train Loss={train_loss/len(train_loader):.4f}, Val AUC={val_auc:.4f}") + scheduler.step() +``` + +### Min() Ensemble（BirdCLEF 2024 - 1st Place） + +1st Place Team Kefir 的 Min() Ensemble，降低不确定预测： + +```python +import numpy as np +import torch + +class MinEnsemble: + """ + Min() Ensemble + 参考：BirdCLEF 2024 1st Place Solution + + 核心思想： + - 使用 min() 而不是 mean() 聚合模型预测 + - 降低不确定预测，提高稳定性 + """ + + def __init__(self, models: list[nn.Module]): + self.models = models + + @torch.no_grad() + def predict_min(self, mel_spec: torch.Tensor) -> np.ndarray: + """ + 使用 Min() 聚合预测 + + Args: + mel_spec: (B, C, H, W) + + Returns: + predictions: (B, num_classes), min() 聚合后的概率 + """ + predictions = [] + + # 获取所有模型的预测 + for model in self.models: + model.eval() + logits = model(mel_spec) + probs = torch.sigmoid(logits) # Sigmoid + predictions.append(probs.cpu().numpy()) + + # Stack: (num_models, B, num_classes) + predictions = np.stack(predictions, axis=0) + + # Min() 聚合 + min_predictions = np.min(predictions, axis=0) + + return min_predictions + + def predict_mean(self, mel_spec: torch.Tensor) -> np.ndarray: + """传统 Mean() 聚合（对比用）""" + predictions = [] + + for model in self.models: + model.eval() + logits = model(mel_spec) + probs = torch.sigmoid(logits) + predictions.append(probs.cpu().numpy()) + + predictions = np.stack(predictions, axis=0) + mean_predictions = np.mean(predictions, axis=0) + + return mean_predictions + +# 使用示例 +# min_ensemble = MinEnsemble([model1, model2, model3, model4, model5]) +# predictions = min_ensemble.predict_min(test_mel_spec) +``` + +### Checkpoint Soup（BirdCLEF 2024 - 2nd Place） + +2nd Place ADSR 的 Checkpoint Soup 技巧： + +```python +import torch +import torch.nn as nn +from typing import list + +class CheckpointSoup: + """ + Checkpoint Soup + 参考：BirdCLEF 2024 2nd Place Solution + + 核心思想： + - 平均多个 epoch 的 checkpoint 权重 + - 代替 early stopping + - 通常更稳定 + """ + + def __init__(self, model: nn.Module, metrics: list[str] = ['auc', 'lrap', 'f1']): + self.model = model + self.metrics = metrics + self.checkpoints = [] # 存储 (epoch, state_dict, scores) + + def add_checkpoint(self, epoch: int, state_dict: dict, scores: dict): + """ + 添加 checkpoint + + Args: + epoch: epoch 编号 + state_dict: 模型权重 + scores: 验证指标 {metric_name: score} + """ + # 检查是否有任意指标改进 + should_save = False + for metric in self.metrics: + if epoch == 0: + should_save = True + break + best_score = max([ckpt[2].get(metric, 0) for ckpt in self.checkpoints]) + if scores.get(metric, 0) >= best_score: + should_save = True + break + + if should_save: + self.checkpoints.append((epoch, state_dict.copy(), scores)) + print(f"Checkpoint {epoch} saved: {scores}") + + def make_soup(self) -> dict: + """ + 制作 Checkpoint Soup + + Returns: + soup_state_dict: 平均后的权重 + """ + if not self.checkpoints: + raise ValueError("No checkpoints to average") + + # 初始化 soup + soup_state_dict = self.checkpoints[0][1].copy() + + # 累加所有 checkpoint + for _, ckpt, _ in self.checkpoints[1:]: + for key in soup_state_dict.keys(): + if key in ckpt: + soup_state_dict[key] += ckpt[key] + + # 平均 + num_checkpoints = len(self.checkpoints) + for key in soup_state_dict.keys(): + soup_state_dict[key] /= num_checkpoints + + print(f"Soup made from {num_checkpoints} checkpoints (epochs: {[ckpt[0] for ckpt in self.checkpoints]})") + return soup_state_dict + + def load_soup(self, model: nn.Module): + """加载 soup 到模型""" + soup = self.make_soup() + model.load_state_dict(soup) + return model + +# 使用示例 +# checkpoint_soup = CheckpointSoup(model, metrics=['auc', 'lrap', 'f1']) +# +# # 训练循环中 +# for epoch in range(num_epochs): +# train(...) +# scores = validate(...) +# checkpoint_soup.add_checkpoint(epoch, model.state_dict(), scores) +# +# # 训练结束后 +# final_model = checkpoint_soup.load_soup(model) +``` + +### 伪标签迭代训练（BirdCLEF 2024 - 2nd Place） + +2nd Place ADSR 的伪标签迭代训练循环： + +```python +import numpy as np +import torch +from typing import list + +class IterativePseudoLabeling: + """ + 伪标签迭代训练 + 参考：BirdCLEF 2024 2nd Place Solution + + 核心思想： + - 用当前集成生成伪标签 + - 用伪标签训练新模型 + - 新模型加入集成，重复循环 + """ + + def __init__( + self, + base_model_class, + pseudo_label_chance: float = 0.35, + amp_exp_min: float = -0.5, + amp_exp_max: float = 0.1, + num_iterations: int = 3, + ): + self.base_model_class = base_model_class + self.pseudo_label_chance = pseudo_label_chance + self.amp_exp_min = amp_exp_min + self.amp_exp_max = amp_exp_max + self.num_iterations = num_iterations + self.ensemble_models = [] + + def generate_pseudo_labels( + self, + unlabeled_audio_paths: list[str], + unlabeled_soundscapes: list[str] + ) -> list[dict]: + """ + 生成伪标签 + + Args: + unlabeled_audio_paths: 未标注音频路径 + unlabeled_soundscapes: 未标注 soundscape 路径 + + Returns: + pseudo_samples: [{audio_path, label_vector}, ...] + """ + pseudo_samples = [] + + for audio_path in unlabeled_soundscapes: + # 用集成模型预测 + predictions = [] + for model in self.ensemble_models: + pred = self.predict_with_model(model, audio_path) + predictions.append(pred) + + # 平均预测 + avg_pred = np.mean(predictions, axis=0) + pseudo_samples.append({ + 'audio_path': audio_path, + 'label_vector': avg_pred + }) + + return pseudo_samples + + def mix_pseudo_labels( + self, + train_sample: dict, + pseudo_sample: dict, + ) -> tuple[torch.Tensor, torch.Tensor]: + """ + 混合训练样本和伪标签样本 + + Args: + train_sample: 训练样本 {audio, label_vector} + pseudo_sample: 伪标签样本 {audio, label_vector} + + Returns: + mixed_audio: 混合后的音频 + mixed_label: 混合后的标签 + """ + train_audio = train_sample['audio'] + train_label = train_sample['label_vector'] + pseudo_audio = pseudo_sample['audio'] + pseudo_label = pseudo_sample['label_vector'] + + # 随机幅度系数 + amp_factor = 10 ** np.random.uniform(self.amp_exp_min, self.amp_exp_max) + + # 混合音频 + mixed_audio = train_audio * amp_factor + pseudo_audio * amp_factor + + # 混合标签（取 max） + mixed_label = np.maximum(train_label, pseudo_label) + + return mixed_audio, mixed_label + + def train_with_pseudo_labels( + self, + train_data: list[dict], + pseudo_samples: list[dict], + num_epochs: int = 50, + ): + """使用伪标签训练新模型""" + model = self.base_model_class() + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3) + criterion = torch.nn.BCEWithLogitsLoss() + + for epoch in range(num_epochs): + for train_sample in train_data: + # 随机决定是否添加伪标签 + if np.random.random() < self.pseudo_label_chance: + # 随机选择一个伪标签样本 + pseudo_sample = np.random.choice(pseudo_samples) + audio, label = self.mix_pseudo_labels(train_sample, pseudo_sample) + else: + audio = train_sample['audio'] + label = train_sample['label_vector'] + + # 训练步骤 + loss = self.train_step(model, audio, label, criterion) + loss.backward() + optimizer.step() + optimizer.zero_grad() + + return model + + def fit(self, train_data, unlabeled_soundscapes): + """完整的迭代训练循环""" + for iteration in range(self.num_iterations): + print(f"\n=== Iteration {iteration + 1}/{self.num_iterations} ===") + + # 生成伪标签 + pseudo_samples = self.generate_pseudo_labels(train_data, unlabeled_soundscapes) + print(f"Generated {len(pseudo_samples)} pseudo labels") + + # 训练新模型 + new_model = self.train_with_pseudo_labels(train_data, pseudo_samples) + self.ensemble_models.append(new_model) + + # 评估集成性能 + ensemble_score = self.evaluate_ensemble() + print(f"Ensemble score: {ensemble_score:.4f}") + + return self.ensemble_models +``` + +### 音频分类竞赛的最佳实践（BirdCLEF 2024） + +**与 BirdCLEF+ 2025 的主要差异：** +| 维度 | BirdCLEF 2024 | BirdCLEF+ 2025 | +|------|---------------|----------------| +| **物种数量** | 182 种鸟类 | 206 种（多分类群） | +| **推理限制** | 120 分钟 CPU | 90 分钟 CPU | +| **数据策略** | 不用外部数据更优 | Xeno-Canto 预训练重要 | +| **关键创新** | Statistics T 过滤 | Noisy Student + 自蒸馏 | +| **损失函数** | CE Loss（训练）+ Sigmoid（推理） | BCE + FocalLoss | + +#### BirdCLEF 2024 前排方案共性技术 + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **只用前 5 秒** | 1st, 2nd | 后续信息贡献小，节省计算 | +| **伪标签** | 1st, 2nd, 3rd | 利用未标注 soundscape | +| **Ensemble** | 所有前排 | 5-20 模型集成 | +| **OpenVINO/ONNX** | 1st, 3rd | CPU 推理加速必需 | +| **小模型** | 所有前排 | B0/ViT-b0 级别，控制推理时间 | + +#### BirdCLEF 2024 独特技术（与 2025 不同） + +**1. Statistics T 噪声过滤（1st Place）** +```python +# T = std + var + rms + pwr +# 使用 0.8 分位数过滤噪声音频 +T = std + var + rms + pwr +threshold = np.quantile(T, 0.8) +clean_data = data[T < threshold] +``` + +**2. CE Loss + Sigmoid 推理（1st Place）** +- 训练：CE Loss + Softmax（多分类问题） +- 推理：Sigmoid（多标签预测） +- 原因：数据大多只有 1-2 个标签，可视为多分类 +- **注意**：这与 BirdCLEF+ 2025 不同，2025 使用 BCE + FocalLoss + +**3. Min() Ensemble（1st Place）** +```python +# 降低不确定预测，比 mean() 更稳定 +predictions = np.min([model1_pred, model2_pred, model3_pred], axis=0) +``` + +**4. Google Bird Classifier 预标注（1st Place）** +- 使用 Google 模型过滤低质量数据 +- 如果预测与 primary label 不匹配，丢弃 +- 添加 Google 预测作为伪标签（系数 0.05） + +**5. Checkpoint Soup（2nd Place）** +- 平均 13-50 epoch 的 checkpoint +- 代替 early stopping +- 比单 checkpoint 更稳定 + +**6. 伪标签迭代训练（2nd Place）** +- 3 次迭代循环 +- 每次用新集成生成伪标签 +- 25-45% 概率添加伪标签数据 + +#### BirdCLEF 2024 推理优化（120 分钟限制） + +**前排方案的优化策略：** + +| 技术 | 说明 | 排名 | +|------|------|------| +| **OpenVINO 编译** | 固定输入大小，加速推理 | 1st | +| **并行 Mel 计算** | joblib 并行预处理 | 1st, 2nd | +| **RAM 缓存** | 预计算所有 mel spec 存入内存 | 1st | +| **小图像尺寸** | 64x64, 128x128 等 | 2nd | +| **ONNX 优化** | 5 fold 40 分钟 | 3rd | + +#### BirdCLEF 2024 数据处理最佳实践 + +**数据过滤：** +| 问题 | 解决方案 | +|------|----------| +| **噪声数据** | Statistics T 过滤（0.8 分位数） | +| **低质量标注** | Google Classifier 过滤 | +| **重复数据** | 去重处理 | + +**数据增强（2nd Place）：** +```python +# 局部和全局时间/频率拉伸 +# 通过调整图像大小实现 +augmented = resize(mel_spec, (new_height, new_width)) +``` + +#### BirdCLEF 2024 vs 2025：为何策略不同？ + +| 方面 | BirdCLEF 2024 | BirdCLEF+ 2025 | 原因 | +|------|---------------|----------------|------| +| **外部数据** | 不用更优 | Xeno-Canto 关键 | 2024 数据质量高，2025 需要预训练 | +| **损失函数** | CE Loss | BCE + Focal | 2024 数据大多 1-2 标签，2025 更复杂 | +| **集成策略** | Min() | Mean() | 2024 用 Sigmoid 噪声大，Min 更稳定 | + +#### BirdCLEF 2024 常见陷阱 + +| 陷阱 | 说明 | 解决方案 | +|------|------|----------| +| **使用外部数据** | Xeno-Canto 反而降低分数 | 只用 2024 数据 | +| **BCE Loss** | 比 CE Loss 效果差 | CE Loss + Sigmoid 推理 | +| **Mean Ensemble** | 对 Sigmoid 输出不稳定 | Min() Ensemble | +| **忽略 Statistics T** | fold0 优于其他 fold | 用统计量过滤噪声 | +| **太大模型** | 推理超时 | B0/RegNetY 级别 | + +### 音频分类竞赛的最佳实践（BirdCLEF+ 2025） + +与通用时间序列分类不同，音频分类（生物声学）有特殊的挑战和技术： + +| 方面 | 通用时序分类 | 音频分类（生物声学） | +|------|-------------|---------------------| +| **特征表示** | 原始信号/统计特征 | Mel-Spectrogram（时频表示） | +| **模型架构** | 1D-CNN/RNN/Transformer | SED 模型（2D-CNN + Attention） | +| **数据特点** | 通常标注完整 | 大量未标注数据（半监督学习关键） | +| **类别分布** | 相对均衡 | 极端长尾（稀有物种 <10 样本） | +| **推理约束** | 通常无特殊限制 | 严格时间限制（90分钟CPU） | +| **评估指标** | Accuracy/F1/ MSE | 宏平均 AUC（每个类独立） | + +#### BirdCLEF+ 2025 前排方案共性技术 + +**"银弹" - 所有前排方案共同使用：** + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **伪标签技术** | 1st-14th | 利用未标注 train_soundscapes 数据 | +| **Mel-Spectrogram** | 1st-14th | 将音频转换为图像表示 | +| **SED 模型架构** | 1st-14th | 帧级 + 片级预测 | +| **模型集成** | 1st-14th | 5-20 个模型集成 | +| **SpecAugment** | 1st-14th | 时间/频率掩码增强 | +| **EfficientNet 系列** | 多数 | tf_efficientnetv2_s/b3/m 作为 backbone | + +#### Mel-Spectrogram 配置最佳实践 + +前排方案使用的配置总结： + +| 配置 | n_mels | n_fft | hop_length | 使用场景 | +|------|--------|-------|-------------|----------| +| **标准配置** | 128 | 2048 | 512 | tf_efficientnetv2 系列（最常用） | +| **轻量配置** | 96 | 2048 | 512 | 轻量级模型，推理加速 | +| **高分辨率** | 256 | 4096 | 1024 | 高精度要求 | + +**频率范围设置（关键）：** +```python +# 鸟类声音频率范围 +FMIN = 0.0 # 最低频率（有些方案用 50Hz 过滤低频噪声） +FMAX = 16000.0 # 最高频率（32kHz 采样率的一半） + +# 稀有物种可能需要调整 +FMIN_RARE = 100.0 # 过滤低频环境噪声 +FMAX_RARE = 15000.0 # 避免高频噪声 +``` + +#### 半监督学习最佳实践（伪标签） + +**伪标签生成流程（前排方案共识）：** + +``` +阶段 1: 基础模型训练 + └── 使用 train_audio（有标签）训练 SED 模型 + +阶段 2: 伪标签生成 + ├── 对 train_soundscapes 进行推理 + ├── 应用高低阈值筛选 + │ ├── 高阈值（≥0.7）: 正样本 + │ └── 低阈值（≤0.3）: 负样本 + └── 幂次变换减少噪声（1st Place 创新） + +阶段 3: 混合训练 + ├── 50% train_audio + 50% 伪标签数据 + ├── MixUp 增强混合数据 + └── 迭代 2-3 次 +``` + +**关键参数（前排方案范围）：** +| 参数 | 范围 | 推荐值 | 说明 | +|------|------|--------|------| +| **高阈值** | 0.6-0.8 | 0.7 | 正样本置信度阈值 | +| **低阈值** | 0.2-0.4 | 0.3 | 负样本置信度阈值 | +| **幂次变换** | 1.2-2.0 | 1.5 | 减少伪标签噪声 | +| **混合比例** | 30%-50% | 50% | 伪标签数据占比 | + +**伪标签质量检查（10th Place 方法）：** +```python +# 高低阈值筛选 +high_threshold = 0.7 +low_threshold = 0.3 + +# 正样本：高置信度 +positive_mask = probs >= high_threshold + +# 负样本：低置信度 +negative_mask = probs <= low_threshold + +# 中等置信度：不使用（可能是噪声） +uncertain_mask = (probs > low_threshold) & (probs < high_threshold) + +# 只使用正负样本 +valid_mask = positive_mask | negative_mask +``` + +#### 推理优化最佳实践（90 分钟约束） + +BirdCLEF+ 2025 最关键的约束是 90 分钟 CPU 推理限制。前排方案的优化策略： + +**模型优化：** +| 技术 | 使用排名 | 加速比 | 说明 | +|------|---------|--------|------| +| **ONNX 导出** | 3rd, 12th, 14th | 2-3x | 标准化推理格式 | +| **OpenVINO** | 12th | 3-5x | Intel 优化，CPU 最优 | +| **模型量化** | 部分方案 | 1.5-2x | INT8 量化（可能损失精度） | +| **Batch 推理** | 所有方案 | 2-4x | 批量推理提高利用率 | + +**Mel-Spectrogram 预计算：** +```python +# 推理阶段预先计算所有 mel-spectrogram +# 避免 GPU-CPU 数据传输开销 + +def precompute_mel_spectrograms(audio_files, cache_dir="cache/mel"): + """预计算并缓存 mel-spectrogram""" + os.makedirs(cache_dir, exist_ok=True) + + for audio_file in tqdm(audio_files): + cache_path = os.path.join(cache_dir, f"{Path(audio_file).stem}.npy") + + if not os.path.exists(cache_path): + # 计算 mel-spectrogram + waveform, sr = torchaudio.load(audio_file) + mel_spec = extract_mel_spectrogram(waveform, sr) + + # 缓存 + np.save(cache_path, mel_spec.numpy()) +``` + +**滑动窗口优化（1st Place 创新）：** +```python +# 使用相邻窗口预测的平均值 +# 避免重复计算，提高推理效率 + +def sliding_window_inference_optimized(model, audio_path): + """优化的滑动窗口推理""" + waveform, sr = torchaudio.load(audio_path) + + # 一次性提取所有窗口的 mel-spectrogram + # 避免重复计算 + all_windows = extract_all_windows(waveform, sr) + + # Batch 推理 + with torch.no_grad(): + predictions = model(all_windows) # (num_windows, num_classes) + + # 相邻窗口平均（1st Place 创新） + smoothed_predictions = smooth_adjacent_windows(predictions) + + return smoothed_predictions +``` + +**前后处理优化：** +| 技术 | 说明 | +|------|------| +| **NumPy 向量化** | 避免循环，使用 NumPy 内置函数 | +| **多进程推理** | 并行处理多个音频文件 | +| **结果缓存** | 避免重复计算 | +| **精简后处理** | 简单平滑即可，避免复杂操作 | + +#### 长尾分布处理最佳实践 + +BirdCLEF+ 2025 数据集存在极端长尾分布（某些物种 <10 样本）： + +**前排方案的处理策略：** + +| 策略 | 使用排名 | 说明 | +|------|---------|------| +| **过采样** | 多数 | 复制稀有类样本至 20-50 | +| **损失加权** | 部分方案 | 稀有类更高权重 | +| **Focal Loss** | 9th Place | 自动处理难样本 | +| **分开训练** | 7th, 13th | 稀有类单独训练模型 | +| **数据增强** | 所有方案 | MixUp/SpecAugment 增加多样性 | + +**稀有物种模型训练（13th Place 策略）：** +```python +# 识别稀有物种（样本数 < 30） +rare_species = [species for species in all_species + if get_sample_count(species) < 30] + +# 训练稀有物种专用模型 +rare_model = create_model(num_classes=len(rare_species)) +rare_model.train_on(rare_species_data) + +# 集成时加入稀有模型预测 +final_prediction = 0.7 * general_model + 0.3 * rare_model +``` + +#### 模型集成最佳实践 + +前排方案的集成策略总结： + +**集成规模：** +| 排名 | 模型数量 | 架构多样性 | 说明 | +|------|---------|-----------|------| +| **1st** | ~10 | 多迭代 Noisy Student | 同一模型不同迭代 | +| **2nd** | ~5-8 | 不同 backbone | tf_efficientnetv2_s + eca_nfnet_l0 | +| **3rd** | 20 | 10 CNN + 10 SED | 最大规模集成 | +| **5th** | ~5-10 | EfficientNet 系列 | 自蒸馏不同阶段 | + +**集成方法：** +```python +# 简单平均（最常用） +predictions = np.mean([model1_pred, model2_pred, model3_pred], axis=0) + +# 加权平均（需要验证集调优） +weights = [0.3, 0.3, 0.4] +predictions = np.average([model1_pred, model2_pred, model3_pred], + axis=0, weights=weights) + +# Min-max 缩放后平均（7th Place） +for i in range(len(predictions)): + pred_min = predictions[i].min() + pred_max = predictions[i].max() + predictions[i] = (predictions[i] - pred_min) / (pred_max - pred_min) + +predictions = np.mean(predictions, axis=0) +``` + +**集成多样性（关键）：** +| 维度 | 多样性来源 | 说明 | +|------|-----------|------| +| **架构** | 不同 backbone | EfficientNetV2 vs NFNet | +| **数据** | 不同训练数据 | 原始 vs 伪标签 vs Xeno-Canto | +| **阶段** | 不同训练阶段 | Checkpoint Soups (12th Place) | +| **配置** | 不同 mel 参数 | n_mels=128 vs 96 | +| **随机性** | 不同随机种子 | 数据增强和初始化差异 | + +#### 常见陷阱和注意事项 + +基于前排方案经验： + +| 陷阱 | 说明 | 解决方案 | +|------|------|---------| +| **过拟合验证集** | LB 和 CV 分数差距大 | 更保守的集成，减少后处理 | +| **伪标签噪声累积** | 多次迭代后性能下降 | 幂次变换 + 高低阈值筛选 | +| **稀有物种检测失败** | 长尾类预测全为 0 | 单独训练稀有模型 + Focal Loss | +| **推理超时** | 90 分钟不够 | ONNX/OpenVINO + Batch 推理 | +| **人声干扰** | 背景人声导致误检 | Silero VAD 去除人声片段 | +| **测试集分布偏移** | 训练/测试环境差异 | 领域适应技术（13th Place） | + +--- + +--- + +## Google Brain - Ventilator Pressure Prediction (2021) + +### Competition Brief (竞赛简介) + +**竞赛背景：** +- **主办方**：Google Brain +- **目标**：预测机械呼吸机气道压力（时序回归任务） +- **应用场景**：自动化机械通气控制，辅助重症监护治疗 +- **社会意义**：减少医护人员手动调整呼吸机的工作量，提高治疗精度 + +**任务描述：** +从呼吸机的控制信号和肺部属性中，预测气道压力： +- **输入**：时间序列控制信号（u_in, u_out）+ 肺部属性（R, C） +- **输出**：每个时间步的气道压力（连续值） +- **约束**：测试集中 66% 的数据由 PID 控制器生成 + +**数据集规模：** +- 训练样本：6,036,000 条时间步 +- 测试样本：4,024,000 条时间步 +- 呼吸次数：约 75,450 次呼吸（训练）+ 40,240 次呼吸（测试） +- 患者数量：数千个不同患者的肺部特征 + +**数据特点：** +1. **PID 控制模式**：测试集中 2/3 的数据遵循 PID 控制规律 +2. **双重输入**：控制信号（u_in 连续，u_out 二值）+ 肺部属性（R 电阻，C 顺应性） +3. **时间步长**：80 步/次呼吸，不同患者呼吸模式不同 +4. **物理约束**：压力变化需遵循呼吸力学规律 + +**评估指标：** +- **MAE (Mean Absolute Error)**：平均绝对误差 +- 目标：最小化预测压力与真实压力的绝对差异 + +**竞赛约束：** +- 代码提交：Kaggle Notebooks 环境 +- 推理时间：无严格限制，但需考虑实用性 +- 模型大小：需平衡精度和推理速度 + +**最终排名：** +- 1st Place: group16 (Gilles Vandewiele et al.) - MAE ~0.104 +- 2nd Place: ambrosm - MAE ~0.105 +- 3rd Place: Upstage - MAE ~0.106 +- 总参赛队伍：2,605 支 + +**技术趋势：** +- **PID 逆向建模**：前排方案的核心创新 +- **多任务学习**：同时预测压力和压力变化 +- **LSTM/Transformer 混合**：结合时序建模和注意力机制 +- **集成策略**：3-10 个模型集成 + +**关键创新：** +- **PID Controller Matching**：利用 PID 控制规律直接拟合（1st, 2nd, 4th Place） +- **Delta Pressure 辅助任务**：预测压力差提升主任务（6th, 14th, 20th Place） +- **物理约束嵌入**：将呼吸力学知识融入模型（3rd Place） + +**后续影响：** +- 推动了医疗时序预测的发展 +- PID 逆向建模成为经典技巧 +- 多篇研究论文引用该比赛方法 + +--- + +### Original Summaries (原始总结) + +**前排方案概述：** + +1. **PID 控制器逆向流派（1st, 2nd, 4th Place）** + - 利用测试集中 66% 数据遵循 PID 控制的规律 + - 通过逆向 PID 公式直接预测压力 + - 无需深度学习即可获得极好结果 + +2. **深度学习流派（3rd, 6th, 14th Place）** + - 使用 LSTM/Transformer 建模时序依赖 + - 多任务学习预测压力和压力差 + - 不依赖 PID 规律，更通用 + +3. **混合流派（16th, 20th Place）** + - 结合 PID 匹配和深度学习 + - 使用辅助任务提升性能 + - 中间排名的务实策略 + +--- + +### 前排方案详细技术分析 + +#### 1st Place - group16 (Gilles Vandewiele et al.) + +**核心技巧：** +- **PID Controller Matching**：核心创新，拟合测试集 PID 控制规律 +- **LSTM + CNN + Transformer 混合架构**：深度学习部分 +- **两阶段预测**：先用 PID 匹配 66% 数据，再用 DL 预测剩余 34% +- **模型集成**：多个模型组合提升稳定性 + +**实现细节：** +- **PID 逆向公式**： + - 从 u_in 信号逆向推导目标压力 + - 拟合 PID 参数：Kp, Ki, Kd + - 对于 PID 控制的呼吸，MAE 可达到 0.05-0.08 + +- **深度学习模型**： + ```python + # LSTM + CNN + Transformer 混合架构 + class VentilatorModel(nn.Module): + def __init__(self): + self.cnn = CNN1D(input_dim=5) # u_in, u_out, R, C, time_step + self.lstm = LSTM(hidden_dim=256, num_layers=2) + self.transformer = TransformerEncoder(num_layers=2, nhead=8) + self.fc = Linear(256, 1) # 预测压力 + + def forward(self, x): + # CNN 提取局部特征 + x = self.cnn(x) + # LSTM 建模时序依赖 + x = self.lstm(x) + # Transformer 捕获长距离依赖 + x = self.transformer(x) + # 预测压力 + return self.fc(x) + ``` + +- **两阶段策略**： + 1. 识别测试集中哪些呼吸由 PID 控制（约 66%） + 2. 对 PID 呼吸使用逆向公式 + 3. 对非 PID 呼吸使用深度学习模型 + 4. 最终集成两种预测 + +- **特征工程**： + - 原始特征：u_in, u_out, R, C, time_step + - 衍生特征：u_in 的累积和、差分、滚动统计 + - 位置编码：sin/cos 位置嵌入 + - 肺部属性编码：R 和 C 的 embedding + +- **训练策略**： + - 损失函数：MAE + delta_pressure_MAE（多任务） + - 优化器：AdamW (lr=1e-3, weight_decay=0.01) + - 学习率调度：CosineAnnealingWarmRestarts + - 早停：CV 15 epochs 无改善则停止 + +- **最终 MAE**：约 0.104 + +**代码仓库**：[GillesVandewiele/google-brain-ventilator](https://github.com/GillesVandewiele/google-brain-ventilator) + +--- + +#### 2nd Place - ambrosm + +**核心技巧：** +- **The Inverse of a PID Controller**：纯粹的 PID 逆向方法 +- **无需深度学习**：完全基于物理规律 +- **数学拟合**：优化 PID 参数最小化误差 + +**实现细节：** +- **PID 逆向公式**： + ```python + def pid_inverse(u_in, u_out, R, C): + """ + PID 控制器的逆向函数 + 从控制信号 u_in 推导目标压力 + + PID 公式：u_in = Kp * e + Ki * ∫e dt + Kd * de/dt + 逆向：从 u_in 拟合目标压力 + """ + # 对每个呼吸单独拟合 + pressures = [] + + for breath_id in unique_breaths: + u_in_breath = u_in[breath_id] + u_out_breath = u_out[breath_id] + + # 拟合 PID 参数 + # 目标：最小化 u_in_pred - u_in_actual + Kp, Ki, Kd = fit_pid_parameters(u_in_breath, u_out_breath) + + # 逆向计算压力 + pressure = inverse_pid(u_in_breath, Kp, Ki, Kd, R, C) + pressures.append(pressure) + + return pressures + ``` + +- **参数优化**： + - 使用 Scipy.optimize.minimize 优化 PID 参数 + - 约束：Kp, Ki, Kd > 0 + - 损失：MSE between u_in_pred 和 u_in_actual + +- **最终 MAE**：约 0.105 + +**技术特点**： +- 最简洁的前排方案 +- 无需训练模型 +- 推理速度极快 +- 但仅适用于 PID 控制的呼吸 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/ambrosm-2-solution-the-inverse-of-a-pid-controller) + +--- + +#### 3rd Place - Upstage + +**核心技巧：** +- **Single Model without PID**：唯一不使用 PID 的前排方案 +- **多任务损失**：同时预测压力和压力变化 +- **数据增强**：时间扭曲、幅值缩放 +- **物理约束损失**：加入呼吸力学先验 + +**实现细节：** +- **模型架构**： + ```python + class UpstageModel(nn.Module): + def __init__(self): + self.embedding = Embedding(num_r_values * num_c_values, 64) + self.lstm1 = LSTM(input_dim=64+3, hidden_dim=256, num_layers=2, bidirectional=True) + self.lstm2 = LSTM(input_dim=512, hidden_dim=128, num_layers=1) + self.fc_pressure = Linear(128, 1) + self.fc_delta = Linear(128, 1) # 辅助任务 + + def forward(self, u_in, u_out, R, C): + # 肺部属性嵌入 + rc_embed = self.embedding(R * 100 + C) + + # 拼接输入 + x = torch.cat([u_in, u_out, rc_embed], dim=-1) + + # LSTM 建模 + x = self.lstm1(x) + x = self.lstm2(x) + + # 多任务预测 + pressure = self.fc_pressure(x) + delta = self.fc_delta(x) + + return pressure, delta + ``` + +- **多任务损失**： + ```python + def loss_function(pressure_pred, delta_pred, pressure_true): + # 主任务：压力预测 + loss_pressure = F.l1_loss(pressure_pred, pressure_true) + + # 辅助任务：压力差预测 + delta_true = pressure_true[:, 1:] - pressure_true[:, :-1] + loss_delta = F.l1_loss(delta_pred[:, :-1], delta_true) + + # 加权组合 + return loss_pressure + 0.3 * loss_delta + ``` + +- **数据增强**： + - 时间扭曲：随机拉伸/压缩时间轴 + - 幅值缩放：u_in 乘以 0.8-1.2 随机因子 + - 噪声注入：加入高斯噪声 + +- **物理约束**： + - 压力变化率约束：|dP/dt| < threshold + - 压力范围约束：0 < P < 60 cmH2O + +- **最终 MAE**：0.0975（不含 PID 后处理） + +**技术特点**： +- 最通用的前排方案 +- 不依赖 PID 规律 +- 可应用于新数据分布 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/upstage-making-ai-beneficial-3rd-place-single-mode) + +--- + +#### 4th Place - Jun Koda + +**核心技巧：** +- **Hacking the PID Control**：深入分析 PID 控制规律 +- **线性关系发现**：u_in 与目标压力线性相关 +- **分段处理**：对不同阶段使用不同策略 + +**实现细节：** +- **核心发现**： + ```python + # 吸气阶段（u_out = 0） + # u_in 与目标 pressure 呈线性关系 + u_in = α * pressure_target + β + + # 呼气阶段（u_out = 1） + # 压力按指数衰减 + pressure = pressure_peak * exp(-t / τ) + + # 其中 τ = R * C（时间常数） + ``` + +- **逆向求解**： + ```python + def predict_pressure(u_in, u_out, R, C): + pressures = [] + + for t in range(len(u_in)): + if u_out[t] == 0: # 吸气 + # 线性关系 + pressure[t] = (u_in[t] - β) / α + else: # 呼气 + # 指数衰减 + pressure[t] = pressure_peak * exp(-t / (R * C)) + + return pressures + ``` + +- **参数拟合**： + - α, β 通过线性回归拟合 + - τ 通过非线性优化拟合 + - 不同 R, C 组合使用不同参数 + +- **最终 MAE**：约 0.106 + +**技术特点**： +- 深入理解 PID 控制原理 +- 利用物理规律简化问题 +- 计算效率极高 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/jun-koda-4th-place-solution-hacking-the-pid-contro) + +--- + +#### 6th Place - 0-0ggg + +**核心技巧：** +- **Single Multi-task LSTM**：单模型多任务学习 +- **Delta Pressure 预测**：辅助任务提升主任务 +- **特征工程**：丰富的时序特征 + +**实现细节：** +- **模型架构**： + ```python + class MultiTaskLSTM(nn.Module): + def __init__(self, input_dim=5, hidden_dim=128): + super().__init__() + self.lstm = LSTM(input_dim, hidden_dim, num_layers=2, dropout=0.2) + self.fc_pressure = Linear(hidden_dim, 1) + self.fc_delta = Linear(hidden_dim, 1) + + def forward(self, x): + # LSTM 编码 + x, _ = self.lstm(x) + + # 多任务预测 + pressure = self.fc_pressure(x) + delta = self.fc_delta(x) + + return pressure, delta + ``` + +- **特征工程**： + - 原始特征：u_in, u_out, R, C + - 时序特征：u_in 的 lag-1, lag-2, lag-3 + - 统计特征：rolling mean, rolling std + - 交互特征：u_in * R, u_in * C + - 时间特征：sin/cos 时间编码 + +- **多任务训练**： + ```python + def train_step(model, batch): + pressure_pred, delta_pred = model(batch) + + # 主任务损失 + loss_pressure = mae_loss(pressure_pred, batch.pressure) + + # 辅助任务损失 + delta_true = batch.pressure[:, 1:] - batch.pressure[:, :-1] + loss_delta = mae_loss(delta_pred[:, :-1], delta_true) + + # 总损失 + loss = loss_pressure + 0.2 * loss_delta + return loss + ``` + +- **最终 MAE**：约 0.108 + +**技术特点**： +- 简洁有效的架构 +- 多任务学习提升性能 +- CV/LB 一致性好 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/0-0ggg-6th-place-solution-single-multi-task-lstm) + +--- + +#### 14th Place - pksha (Team "no pressure") + +**核心技巧：** +- **Multitask LSTM**：同时预测压力和压力变化 +- **Delta Pressure 辅助任务**：关键创新 +- **集成策略**：多模型融合 + +**实现细节：** +- **多任务设计**： + ```python + class MultitaskLSTM(nn.Module): + def __init__(self): + self.lstm = LSTM(input_dim=6, hidden_dim=128, num_layers=2, bidirectional=True) + self.fc1 = Linear(256, 64) + self.fc_pressure = Linear(64, 1) + self.fc_delta = Linear(64, 1) + + def forward(self, x): + x, _ = self.lstm(x) + x = F.relu(self.fc1(x)) + pressure = self.fc_pressure(x) + delta = self.fc_delta(x) + return pressure, delta + ``` + +- **辅助任务价值**： + - 预测 delta pressure：P[t] - P[t-1] + - 帮助模型学习压力变化趋势 + - CV/LB 提升 +0.01 ~ +0.015 + +- **最终 MAE**：约 0.112 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/pksha-no-pressure-14th-place-solution-multitask-ls) + +--- + +#### 16th Place - player2-has-flatlined + +**核心技巧：** +- **Journey Writeup**：详细的开发历程 +- **渐进优化**：从 baseline 到最终方案 +- **务实策略**：平衡效果和复杂度 + +**实现细节：** +- **开发历程**： + 1. Baseline LSTM：MAE ~0.15 + 2. 加入特征工程：MAE ~0.13 + 3. 多任务学习：MAE ~0.115 + 4. 模型集成：MAE ~0.113 + +- **关键改进**： + - 丰富特征工程 + - 多任务学习（delta pressure） + - 交叉验证策略优化 + - 简单平均集成 + +- **最终 MAE**：约 0.113 + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/player2-has-flatlined-16th-place-journey-writeup-n) + +--- + +#### 20th Place - hyeongchan-nikita / kozistr + +**核心技巧：** +- **Model & Multi-task Learning**：深度学习 + 多任务 +- **Delta Pressure Auxiliary Loss**：核心技术 +- **Top 1% 铜牌边界**：进入前 1% 的方案 + +**实现细节（kozistr）：** +- **多任务损失**： + ```python + def multi_task_loss(pressure_pred, delta_pred, pressure_true): + # 主任务 + loss_pressure = F.l1_loss(pressure_pred, pressure_true) + + # 辅助任务：delta pressure + delta_true = torch.diff(pressure_true, dim=1) + loss_delta = F.l1_loss(delta_pred[:, :-1], delta_true) + + return loss_pressure + 0.15 * loss_delta + ``` + +- **模型架构**： + - LSTM（2 层，128 隐藏单元） + - 特征：u_in, u_out, R, C + 统计特征 + - Dropout：0.3 + +- **最终 MAE**：约 0.116（Top 1% 边界） + +**技术特点**： +- 最简单的前排方案之一 +- 证明了多任务学习的有效性 +- CV/LB 提升 +0.01 ~ +0.015 + +**参考文章**：[Blog Post](https://kozistr.tech/2021-11-03-ventilator-pressure-prediction/) + +**Writeup**：[Kaggle Writeup](https://www.kaggle.com/competitions/ventilator-pressure-prediction/writeups/hyeongchan-nikita-20th-place-solution-model-multi-) + +--- + +### Code Templates (代码模板) + +#### PID Controller Matching (1st Place 核心技巧) + +```python +import numpy as np +from scipy.optimize import minimize + +def fit_pid_parameters(u_in, u_out, initial_pressure=0): + """ + 拟合 PID 控制器参数 + + Args: + u_in: 控制信号 (array) + u_out: 吸气/呼气标志 (array) + initial_pressure: 初始压力 + + Returns: + Kp, Ki, Kd: PID 参数 + """ + + def pid_loss(params, u_in, u_out): + Kp, Ki, Kd = params + + # 模拟 PID 控制器 + pressure_pred = simulate_pid(u_in, u_out, Kp, Ki, Kd, initial_pressure) + + # 计算误差（逆向：从 u_in 预测 pressure 的误差） + error = np.mean((u_in - target_from_pressure(pressure_pred)) ** 2) + return error + + # 初始参数 + x0 = [1.0, 0.1, 0.5] + + # 约束：参数必须为正 + bounds = [(0, None), (0, None), (0, None)] + + # 优化 + result = minimize(pid_loss, x0, args=(u_in, u_out), bounds=bounds) + + return result.x + +def simulate_pid(u_in, u_out, Kp, Ki, Kd, initial_pressure): + """ + PID 控制器模拟 + + Args: + u_in: 控制信号 + u_out: 吸气/呼气标志 + Kp, Ki, Kd: PID 参数 + initial_pressure: 初始压力 + + Returns: + pressure: 预测的压力序列 + """ + n_steps = len(u_in) + pressure = np.zeros(n_steps) + pressure[0] = initial_pressure + + integral = 0 + prev_error = 0 + + for t in range(1, n_steps): + # 设定值（目标压力） + setpoint = pressure[t-1] # 维持当前压力 + + # 过程变量（当前压力） + pv = pressure[t-1] + + # 误差 + error = setpoint - pv + + # 积分项 + integral += error + + # 微分项 + derivative = error - prev_error + prev_error = error + + # PID 输出 + output = Kp * error + Ki * integral + Kd * derivative + + # 肺部响应（一阶系统） + # dP/dt = (u_in - P) / (R * C) + R, C = get_rc_params(t) # 获取 R, C 参数 + tau = R * C # 时间常数 + + pressure[t] = pressure[t-1] + (output - pressure[t-1]) / tau + + # 呼气阶段处理 + if u_out[t] == 1: + pressure[t] = pressure[t] * 0.9 # 衰减 + + return pressure + +def predict_pressure_pid(u_in, u_out, R, C): + """ + 使用 PID 逆向方法预测压力 + + Args: + u_in: 控制信号 + u_out: 吸气/呼气标志 + R: 肺部电阻 + C: 肺部顺应性 + + Returns: + pressure: 预测压力 + """ + # 按呼吸分组 + breath_ids = get_breath_ids(u_out) + + pressures = [] + + for breath_id in breath_ids: + u_in_breath = u_in[breath_id] + u_out_breath = u_out[breath_id] + + # 拟合 PID 参数 + Kp, Ki, Kd = fit_pid_parameters(u_in_breath, u_out_breath) + + # 逆向预测压力 + pressure_breath = inverse_pid(u_in_breath, u_out_breath, Kp, Ki, Kd, R, C) + pressures.extend(pressure_breath) + + return np.array(pressures) + +def inverse_pid(u_in, u_out, Kp, Ki, Kd, R, C): + """ + PID 逆向：从 u_in 推导压力 + + 简化版本：假设比例控制主导 + u_in ≈ Kp * (target - current) + => target ≈ u_in / Kp + current + """ + n_steps = len(u_in) + pressure = np.zeros(n_steps) + + pressure[0] = 5 # 初始压力 + + for t in range(1, n_steps): + if u_out[t] == 0: # 吸气 + # 比例控制 + pressure[t] = pressure[t-1] + u_in[t] / Kp + else: # 呼气 + # 指数衰减 + tau = R * C + pressure[t] = pressure[t-1] * np.exp(-1 / tau) + + return pressure +``` + +#### Multi-task LSTM (6th, 14th, 20th Place 技巧) + +```python +import torch +import torch.nn as nn + +class MultiTaskVentilatorLSTM(nn.Module): + """多任务 LSTM 模型""" + + def __init__(self, input_dim=5, hidden_dim=128, num_layers=2, dropout=0.2): + super().__init__() + + # LSTM 层 + self.lstm = nn.LSTM( + input_size=input_dim, + hidden_size=hidden_dim, + num_layers=num_layers, + dropout=dropout, + batch_first=True, + bidirectional=True + ) + + # 全连接层 + self.fc1 = nn.Linear(hidden_dim * 2, 64) + self.dropout = nn.Dropout(dropout) + + # 多任务输出 + self.fc_pressure = nn.Linear(64, 1) # 主任务：压力预测 + self.fc_delta = nn.Linear(64, 1) # 辅助任务：压力差预测 + + def forward(self, x): + # LSTM 编码 + lstm_out, _ = self.lstm(x) # (batch, seq, hidden*2) + + # 全连接 + out = F.relu(self.fc1(lstm_out)) + out = self.dropout(out) + + # 多任务预测 + pressure = self.fc_pressure(out).squeeze(-1) # (batch, seq) + delta = self.fc_delta(out).squeeze(-1) # (batch, seq) + + return pressure, delta + +def multi_task_loss(pressure_pred, delta_pred, pressure_true, delta_weight=0.2): + """ + 多任务损失函数 + + Args: + pressure_pred: 压力预测 (batch, seq) + delta_pred: 压力差预测 (batch, seq) + pressure_true: 真实压力 (batch, seq) + delta_weight: 辅助任务权重 + + Returns: + total_loss: 总损失 + """ + # 主任务：压力预测 MAE + loss_pressure = F.l1_loss(pressure_pred, pressure_true) + + # 辅助任务：压力差预测 MAE + # 计算真实压力差 + delta_true = pressure_true[:, 1:] - pressure_true[:, :-1] + delta_pred_trimmed = delta_pred[:, 1:] + + loss_delta = F.l1_loss(delta_pred_trimmed, delta_true) + + # 加权组合 + total_loss = loss_pressure + delta_weight * loss_delta + + return total_loss + +# 训练循环 +def train_model(model, train_loader, val_loader, num_epochs=30, lr=1e-3): + optimizer = torch.optim.AdamW(model.parameters(), lr=lr, weight_decay=0.01) + scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( + optimizer, T_0=10, T_mult=2 + ) + + best_val_loss = float('inf') + patience = 5 + patience_counter = 0 + + for epoch in range(num_epochs): + # 训练 + model.train() + train_loss = 0 + + for batch in train_loader: + x = batch['features'] # (batch, seq, 5) + y = batch['pressure'] # (batch, seq) + + optimizer.zero_grad() + + # 前向传播 + pressure_pred, delta_pred = model(x) + + # 计算损失 + loss = multi_task_loss(pressure_pred, delta_pred, y) + + # 反向传播 + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证 + model.eval() + val_loss = 0 + + with torch.no_grad(): + for batch in val_loader: + x = batch['features'] + y = batch['pressure'] + + pressure_pred, delta_pred = model(x) + loss = multi_task_loss(pressure_pred, delta_pred, y) + val_loss += loss.item() + + # 学习率调度 + scheduler.step() + + # 早停 + if val_loss < best_val_loss: + best_val_loss = val_loss + patience_counter = 0 + # 保存最佳模型 + torch.save(model.state_dict(), 'best_model.pth') + else: + patience_counter += 1 + if patience_counter >= patience: + print(f'Early stopping at epoch {epoch}') + break + + print(f'Epoch {epoch}: Train Loss={train_loss/len(train_loader):.4f}, ' + f'Val Loss={val_loss/len(val_loader):.4f}') + + # 加载最佳模型 + model.load_state_dict(torch.load('best_model.pth')) + return model +``` + +#### 特征工程模板 + +```python +import numpy as np +import pandas as pd + +def create_features(df): + """ + 创建时序特征 + + Args: + df: 原始数据，包含列： + - u_in: 控制信号 + - u_out: 吸气/呼气标志 + - R: 肺部电阻 + - C: 肺部顺应性 + - breath_id: 呼吸ID + + Returns: + features: 特征 DataFrame + """ + df = df.copy() + + # 1. 基础特征 + features = df[['u_in', 'u_out', 'R', 'C']].copy() + + # 2. 时序特征：滞后 + for lag in [1, 2, 3]: + features[f'u_in_lag{lag}'] = df['u_in'].shift(lag) + + # 3. 时序特征：差分 + features['u_in_diff1'] = df['u_in'].diff() + features['u_in_diff2'] = df['u_in'].diff(2) + + # 4. 统计特征：滚动窗口 + for window in [5, 10]: + features[f'u_in_rolling_mean_{window}'] = df['u_in'].rolling(window).mean() + features[f'u_in_rolling_std_{window}'] = df['u_in'].rolling(window).std() + features[f'u_in_rolling_max_{window}'] = df['u_in'].rolling(window).max() + features[f'u_in_rolling_min_{window}'] = df['u_in'].rolling(window).min() + + # 5. 累积特征 + features['u_in_cumsum'] = df['u_in'].cumsum() + features['u_in_cummax'] = df['u_in'].cummax() + + # 6. 交互特征 + features['u_in_R'] = df['u_in'] * df['R'] + features['u_in_C'] = df['u_in'] * df['C'] + features['R_C'] = df['R'] * df['C'] # 时间常数 + + # 7. 时间特征（位置编码） + features['time_step'] = np.arange(len(df)) + features['time_sin'] = np.sin(2 * np.pi * features['time_step'] / 80) + features['time_cos'] = np.cos(2 * np.pi * features['time_step'] / 80) + + # 8. 呼吸级别特征 + breath_groups = df.groupby('breath_id') + + features['u_in_breath_mean'] = breath_groups['u_in'].transform('mean') + features['u_in_breath_max'] = breath_groups['u_in'].transform('max') + features['u_in_breath_std'] = breath_groups['u_in'].transform('std') + + # 9. 阶段特征 + features['u_out_lag1'] = df['u_out'].shift(1) + features['inhale_start'] = (features['u_out_lag1'] == 1) & (df['u_out'] == 0) + features['exhale_start'] = (features['u_out_lag1'] == 0) & (df['u_out'] == 1) + + # 10. 填充缺失值 + features = features.fillna(method='bfill').fillna(0) + + return features + +# 使用示例 +# df = pd.read_csv('train.csv') +# features = create_features(df) +# print(features.shape) +``` + +--- + +### Best Practices (最佳实践) + +#### PID 控制器逆向策略 + +**适用场景：** +- 测试集存在已知控制规律（如 PID） +- 控制信号与目标存在可逆向的关系 + +**实现步骤：** +1. **分析控制规律**： + - 绘制 u_in 与 pressure 的关系图 + - 识别线性/非线性关系 + - 分析不同阶段（吸气/呼气）的规律 + +2. **拟合逆向函数**： + - 使用优化方法拟合参数 + - 添加物理约束（如参数 > 0） + - 分组拟合（不同 R, C 组合） + +3. **混合策略**： + - 对 PID 控制样本使用逆向方法 + - 对非 PID 样本使用深度学习 + - 加权融合两种预测 + +**注意事项：** +| 问题 | 解决方案 | +|------|---------| +| 非线性关系 | 分段线性或使用非线性优化 | +| 参数不稳定 | 正则化或参数约束 | +| 部分样本不符合 PID | 使用残差模型校正 | + +#### 多任务学习策略 + +**辅助任务选择：** +- **Delta Pressure**：预测 P[t] - P[t-1]（最常用） +- **压力分类**：同时预测压力范围（辅助回归） +- **阶段预测**：预测吸气/呼气阶段（多任务） + +**损失权重调优：** +```python +# 网格搜索最佳权重 +for delta_weight in [0.1, 0.15, 0.2, 0.25, 0.3]: + loss = multi_task_loss(pressure_pred, delta_pred, pressure_true, delta_weight) + # 验证集评估 + val_mae = evaluate(val_loader, delta_weight) + print(f'delta_weight={delta_weight}: val_mae={val_mae:.4f}') +``` + +**最佳实践：** +| 技巧 | 说明 | +|------|------| +| 渐进式训练 | 先训练主任务，再加入辅助任务 | +| 权重衰减 | 逐渐降低辅助任务权重 | +| 多个辅助任务 | 可组合多个辅助任务 | +| 早停基于主任务 | 验证集只看主任务性能 | + +#### 交叉验证策略 + +**Group K-Fold：** +```python +from sklearn.model_selection import GroupKFold + +# 确保同一 breath 的样本不分散 +gkf = GroupKFold(n_splits=5) + +for fold, (train_idx, val_idx) in enumerate(gkf.split(X, y, groups=df['breath_id'])): + print(f'Fold {fold}: Train={len(train_idx)}, Val={len(val_idx)}') + + X_train, X_val = X[train_idx], X[val_idx] + y_train, y_val = y[train_idx], y[val_idx] + + # 训练模型 + model = train_model(X_train, y_train) +``` + +**时间序列分割：** +```python +from sklearn.model_selection import TimeSeriesSplit + +# 按时间顺序分割 +tscv = TimeSeriesSplit(n_splits=5) + +for fold, (train_idx, val_idx) in enumerate(tscv.split(X)): + # 训练集在验证集之前 + X_train, X_val = X[train_idx], X[val_idx] + y_train, y_val = y[train_idx], y[val_idx] +``` + +#### 模型集成策略 + +**集成方法：** +| 方法 | 使用排名 | 说明 | +|------|---------|------| +| **简单平均** | 所有排名 | 最常用，稳定可靠 | +| **加权平均** | 部分排名 | 需要验证集调优权重 | +| **Stacking** | 高排名 | 用元模型学习组合 | +| **不同架构** | 1st, 3rd | LSTM + Transformer + CNN | + +**集成代码：** +```python +def ensemble_predictions(predictions_list, weights=None): + """ + 集成多个模型的预测 + + Args: + predictions_list: 预测列表 [(n_samples, n_steps), ...] + weights: 权重列表，None 表示简单平均 + + Returns: + ensemble_pred: 集成预测 + """ + if weights is None: + # 简单平均 + ensemble_pred = np.mean(predictions_list, axis=0) + else: + # 加权平均 + ensemble_pred = np.average(predictions_list, axis=0, weights=weights) + + return ensemble_pred + +# 使用示例 +# pred1 = model1.predict(X_val) +# pred2 = model2.predict(X_val) +# pred3 = model3.predict(X_val) +# +# # 简单平均 +# ensemble = ensemble_predictions([pred1, pred2, pred3]) +# +# # 加权平均 +# weights = [0.3, 0.3, 0.4] +# ensemble = ensemble_predictions([pred1, pred2, pred3], weights) +``` + +#### 常见陷阱和注意事项 + +| 陷阱 | 说明 | 解决方案 | +|------|------|---------| +| **过拟合 PID 规律** | 模型只对 PID 样本有效 | 加入真实呼吸样本训练 | +| **数据泄露** | 使用未来信息 | 严格按时间切分 | +| **多任务权重不当** | 辅助任务干扰主任务 | 调优权重或渐进训练 | +| **集成过拟合** | 集成太多模型 | 3-5 个模型即可 | +| **特征工程过度** | 特征比样本还多 | 特征选择和降维 | +| **验证集策略错误** | 同一 breath 分散到训练和验证 | Group K-Fold | + +--- + +## Metadata + +| Source | Date | Tags | +|--------|------|------| +| [HMS - Harmful Brain Activity Classification](https://www.kaggle.com/competitions/hms-harmful-brain-activity-classification) | 2025-01-22 | EEG, 分类, CWT, Entmax, 2-Stage Training, KL-Divergence | +| [Child Mind Institute - Detect Sleep States](https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states) | 2025-01-22 | 睡眠检测, 事件检测, 两阶段建模, 后处理优化, 多tolerance AP | +| [Child Mind Institute - Detect Behavior with Sensor Data](https://www.kaggle.com/competitions/cmi-detect-behavior-with-sensor-data) | 2025-01-22 | 多模态时序, IMU+TOF+THM, 行为识别, 阶段感知Attention, 匈牙利算法 | +| [BirdCLEF 2024](https://www.kaggle.com/competitions/birdclef-2024) | 2026-01-23 | 音频分类, 生物声学, Statistics T过滤, Google Classifier预标注, CE Loss, Sigmoid推理, Min Ensemble, Checkpoint Soup, 伪标签迭代, 120分钟推理限制 | +| [BirdCLEF+ 2025](https://www.kaggle.com/competitions/birdclef-2025) | 2026-01-22 | 音频分类, 生物声学, Noisy Student, 自蒸馏, SED模型, 伪标签, Mel-Spectrogram, Soft AUC Loss, 90分钟推理限制 | +| [Google Brain - Ventilator Pressure Prediction](https://www.kaggle.com/c/ventilator-pressure-prediction) | 2026-01-23 | 时序回归, PID逆向, 多任务学习, Delta Pressure, LSTM+Transformer, MAE, 2,605队伍 | +| [Cornell Birdcall Identification (BirdCLEF 2020)](https://www.kaggle.com/competitions/birdsong-recognition) | 2026-01-23 | 音频分类, 生物声学, ResNeSt, Attention Pooling, Mel-Spectrogram, Weak Supervision, GAN伪标签, Ensemble, F1-Score, 1,390队伍 | +| [BirdCLEF 2021 - Birdcall Identification](https://www.kaggle.com/competitions/birdclef-2021) | 2026-01-23 | 音频分类, 生物声学, PANNs, 弱监督, Mixup, SpecAugment, Attention Mechanism, F1-Score, 1,700队伍 | +| [BirdCLEF 2022 - Endangered Bird Sounds](https://www.kaggle.com/competitions/birdclef-2022) | 2026-01-23 | 音频分类, 濒危物种, BirdNet, Perch, SED, 多尺度输入, AND规则, Framewise预测, F1-Score, 1,600队伍 | +| [Rainforest Connection Species Audio Detection 2021](https://www.kaggle.com/competitions/rfcx-species-audio-detection) | 2026-01-23 | 音频检测, 生物声学, LWLRAP, Mel-Spectrogram as Image, ResNeSt, EfficientNet, ImageNet预训练, 2,200队伍 | +| [AMP®-Parkinson's Disease Progression Prediction](https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction) | 2026-01-23 | 表格时序回归, 蛋白质数据, Gradient Boosting, SMAPE, XGBoost/LightGBM, 2,500队伍 | + +--- + +## Cornell Birdcall Identification (BirdCLEF 2020) + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology +- **目标**：识别音频录音中的鸟类叫声（多标签音频分类） +- **应用场景**：鸟类种群监测，生物声学研究，生态系统保护 +- **数据集规模**： + - 训练音频：2,000+ 段录音，涵盖 264 种鸟类 + - 测试音频：约 200 段连续录音（soundscape） + - 采样率： varied (通常 44.1kHz 或 48kHz) +- **评估指标**：micro-averaged F1-score（需要预测鸟类在 5 秒时间窗口内的出现） +- **最终排名**： + - 1st Place: Ryan Wong - F1 ~0.71 + - 2nd Place: niw + - 3rd Place: TheoViel + - 总参赛队伍：1,390 支 + +### 前排方案详细技术分析 + +#### 1st Place - ResNeSt + Attention Pooling + Large Ensemble (Ryan Wong) + +核心技巧： +- **ResNeSt Split-Attention Network**：使用 ResNeSt-50 作为主干网络 +- **Attention Pooling**：替代传统的全局平均池化 +- **Large Voting Ensemble**：13 模型投票集成，需要至少 4 票 +- **Mel-Spectrogram Preprocessing**：对数 Mel 频谱特征 +- **数据增强**：粉红噪声、高斯噪声、音量调整 +- **Multi-Scale Training**：不同音频片段长度 + +实现细节： +- **音频预处理**： + - 重采样到 32kHz 或 44.1kHz + - 使用短时傅里叶变换（STFT）计算 Mel-spectrogram + - 对数尺度转换：log(1 + mel) + - 时间维度：5 秒窗口 +- **模型架构**： + - ResNeSt-50 (Split-Attention variants of ResNet) + - 在 ImageNet 上预训练 + - 替换最后的全连接层为 Attention Pooling + - 输出层：264 类二分类（多标签） +- **Attention Pooling 实现**： + ```python + class AttentionPooling(nn.Module): + def __init__(self, input_dim, hidden_dim=128): + super().__init__() + self.attention = nn.Sequential( + nn.Linear(input_dim, hidden_dim), + nn.Tanh(), + nn.Linear(hidden_dim, 1) + ) + + def forward(self, x): + # x: (batch, time, features) + weights = F.softmax(self.attention(x), dim=1) + return (x * weights).sum(dim=1) + ``` +- **集成策略**： + - 13 个模型的投票集成 + - 每个预测需要至少 4 票才认为鸟类存在 + - 基于 LB 分数选择模型 + - 不同 checkpoint 和数据增强配置 +- **数据增强**： + - Mixup（混合增强） + - 背景噪声添加 + - 音高变换（pitch shifting） + - 时间拉伸（time stretching） +- **训练配置**： + - Loss：Binary Cross-Entropy + - Optimizer：AdamW + - Learning Rate：1e-3（带 cosine annealing） + - Batch Size：32 + - Epochs：~30 + +#### 2nd Place - Efficient Ensemble with Strong Data Augmentation (niw) + +核心技巧： +- **ResNet50-based Models**：多个 ResNet50 变体 +- **Aggressive Data Augmentation**：激进的音频增强 +- **Spectral Features**：多种频谱特征组合 +- **Prediction Thresholding**：预测阈值优化 +- **Cross-Validation Ensemble**：交叉验证集成 + +实现细节： +- **特征工程**： + - Mel-spectrogram（128 Mel bins） + - MFCC（Mel-Frequency Cepstral Coefficients） + - Chroma features + - Spectral contrast +- **模型变体**： + - ResNet50（预训练） + - EfficientNet-B0 + - DenseNet-121 +- **增强策略**： + - 时间遮罩（SpecAugment Time Masking） + - 频率遮罩（Frequency Masking） + - 添加背景噪声 + - 音量随机化 +- **后处理**： + - 类别特定的阈值优化 + - 时间平滑（temporal smoothing） + - 最小持续时间过滤 + +#### 3rd Place - Simple yet Effective Approach (TheoViel) + +核心技巧： +- **Pre-trained ResNeSt**：使用预训练的 ResNeSt 模型 +- **Mel-Spectrogram Input**：标准 Mel 频谱 +- **Strong Baseline**：简洁但强大的基线模型 +- **Moderate Ensemble**：中等规模集成 +- **Careful Validation**：仔细的验证策略 + +实现细节： +- **音频处理**： + - 重采样到 44.1kHz + - 5 秒固定窗口 + - 128 Mel bins + - 对数幅度压缩 +- **模型架构**： + - ResNeSt50（预训练） + - Global Average Pooling + - Sigmoid 激活 +- **训练策略**： + - 5-fold 交叉验证 + - Early stopping + - Learning rate scheduling +- **集成方法**： + - 5-7 个模型的平均 + - 不同随机种子 + +#### 4th Place - Logmels Spectral Features (dimabert & ususani) + +核心技巧： +- **Logmels Features**：对数 Mel 频谱作为主要特征 +- **Audio Normalization**：音频标准化处理 +- **32kHz Resampling**：统一采样率 +- **CNN Ensemble**：多个 CNN 模型集成 + +实现细节： +- **音频预处理**： + - 重采样到 32,000 Hz + - 音频归一化（RMS normalization） + - 固定长度窗口 +- **特征提取**： + - Logmels（对数 Mel-spectrogram） + - 128 Mel bins + - 时间帧数：约 500 帧/5秒 +- **模型选择**： + - ResNet50 + - ResNeSt50 + - EfficientNet +- **Loss Function**： + - Binary Cross-Entropy + - Label Smoothing + +#### 5th Place - Dual Approach with Different Architectures (Kramarenko Vladislav) + +核心技巧： +- **Multiple Approaches**：尝试了两种不同的方法 +- **Different CNN Architectures**：不同的 CNN 架构 +- **Feature Engineering**：特征工程优化 +- **Prediction Blending**：预测结果混合 + +实现细节： +- **方法 1**：ResNet50 + Mel-spectrogram +- **方法 2**：Custom CNN + MFCC features +- **最终集成**：两种方法的加权平均 + +#### 6th Place - Sound Event Detection with Attention (Deep) + +核心技巧： +- **SED Framework**：声音事件检测框架 +- **ResNeSt50 Encoder**：ResNeSt50 编码器 +- **Attention Mechanism**：注意力机制 +- **Strong Augmentation**：强数据增强 +- **Post-processing**：后处理优化 + +实现细节： +- **模型架构**： + - ResNeSt50 作为特征提取器 + - Temporal Attention Module + - Multi-head Attention +- **训练技巧**： + - Mixup augmentation + - CutMix + - SpecAugment + +#### 7th Place - Three Geese and a GAN (CPJKU) + +核心技巧： +- **Weak Supervision**：弱监督学习 +- **Generative Augmentation**：使用 GAN 生成增强数据 +- **Pseudo-labeling**：伪标签策略 +- **Strong Single Model**：强大的单模型 +- **Note**：该方案可修改后达到 1-2 名成绩 + +实现细节： +- **GAN-based Augmentation**： + - 使用生成对抗网络生成合成音频 + - 增加稀有鸟类的样本 + - 条件 GAN（conditional GAN） +- **弱监督策略**： + - 利用未标注数据 + - 自训练（self-training） + - 伪标签迭代优化 +- **模型架构**： + - Modified ResNet + - Attention pooling + - Multi-task learning +- **训练流程**： + - Stage 1: 在标注数据上训练 + - Stage 2: 生成伪标签 + - Stage 3: 在标注+伪标签数据上微调 + +#### 17th Place - File-level Post-processing + +核心技巧： +- **File-level Aggregation**：文件级别聚合 +- **Temporal Smoothing**：时间平滑 +- **Threshold Optimization**：阈值优化 +- **Ensemble Diversification**：集成多样化 + +实现细节： +- **后处理策略**： + - 同一文件内的预测平滑 + - 移除短于阈值的检测 + - 类别特定的阈值 +- **集成方法**： + - 多个 checkpoint 平均 + - 不同架构的集成 + +### 代码模板 + +#### Mel-Spectrogram 特征提取 +```python +import torch +import torch.nn as nn +import torchaudio +import numpy as np + +class MelSpectrogramExtractor: + def __init__(self, sample_rate=32000, n_mels=128, n_fft=2048, hop_length=512): + self.sample_rate = sample_rate + self.n_mels = n_mels + self.n_fft = n_fft + self.hop_length = hop_length + + # Mel-spectrogram transform + self.mel_transform = torchaudio.transforms.MelSpectrogram( + sample_rate=sample_rate, + n_fft=n_fft, + hop_length=hop_length, + n_mels=n_mels, + f_min=0, + f_max=16000 + ) + + # Amplitude to dB + self.amplitude_to_db = torchaudio.transforms.AmplitudeToDB() + + def extract(self, waveform): + """提取 Mel-spectrogram 特征""" + # Compute mel-spectrogram + mel_spec = self.mel_transform(waveform) + + # Convert to dB scale + mel_spec_db = self.amplitude_to_db(mel_spec) + + # Normalize to [0, 1] + mel_spec_norm = (mel_spec_db - mel_spec_db.min()) / (mel_spec_db.max() - mel_spec_db.min() + 1e-8) + + return mel_spec_norm + +# 使用示例 +extractor = MelSpectrogramExtractor(sample_rate=32000, n_mels=128) +waveform, sr = torchaudio.load("bird_audio.wav") +if sr != 32000: + resampler = torchaudio.transforms.Resample(sr, 32000) + waveform = resampler(waveform) +mel_spec = extractor.extract(waveform) +``` + +#### ResNeSt + Attention Pooling 模型 +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class AttentionPooling2d(nn.Module): + """2D Attention Pooling for spectrograms""" + def __init__(self, in_channels, hidden_dim=128): + super().__init__() + self.attention = nn.Sequential( + nn.Conv2d(in_channels, hidden_dim, kernel_size=1), + nn.BatchNorm2d(hidden_dim), + nn.Tanh(), + nn.Conv2d(hidden_dim, 1, kernel_size=1) + ) + + def forward(self, x): + # x: (batch, channels, time, freq) + attn_weights = F.softmax(self.attention(x), dim=(2, 3)) + return (x * attn_weights).sum(dim=(2, 3)) + +class BirdcallClassifier(nn.Module): + def __init__(self, num_classes=264, pretrained=True): + super().__init__() + + # ResNeSt backbone (需要安装 resnest 库) + from resnest.torch import resnest50 + + self.backbone = resnest50(pretrained=pretrained) + + # 替换最后的全连接层 + self.backbone.fc = nn.Identity() + + # Attention pooling + self.attention_pool = AttentionPooling2d(2048, hidden_dim=128) + + # Classifier head + self.classifier = nn.Sequential( + nn.Dropout(0.3), + nn.Linear(2048, 512), + nn.ReLU(), + nn.Dropout(0.2), + nn.Linear(512, num_classes) + ) + + def forward(self, x): + # x: (batch, channels, time, freq) - Mel-spectrogram + features = self.backbone(x) # (batch, 2048, H, W) + pooled = self.attention_pool(features) # (batch, 2048) + logits = self.classifier(pooled) # (batch, num_classes) + return logits + +# 使用示例 +model = BirdcallClassifier(num_classes=264, pretrained=True) +mel_spec_batch = torch.randn(8, 3, 224, 512) # (batch, channels, freq, time) +logits = model(mel_spec_batch) +probs = torch.sigmoid(logits) # Multi-label prediction +``` + +#### 数据增强 +```python +import torch +import torchaudio +import random + +class BirdcallAugmentation: + def __init__(self, sample_rate=32000): + self.sample_rate = sample_rate + + def add_noise(self, waveform, noise_level=0.005): + """添加高斯噪声""" + noise = torch.randn_like(waveform) * noise_level + return waveform + noise + + def add_pink_noise(self, waveform, alpha=1): + """添加粉红噪声（1/f 噪声）""" + # 简化的粉红噪声生成 + white_noise = torch.randn_like(waveform) + # 在频域应用 1/f 滤波 + freq_noise = torch.fft.rfft(white_noise) + freqs = torch.fft.rfftfreq(waveform.shape[-1], 1/self.sample_rate) + pink_filter = 1 / (freqs[1:] + 1e-8) ** alpha + freq_noise[:, 1:] *= pink_filter + pink_noise = torch.fft.irfft(freq_noise, n=waveform.shape[-1]) + return waveform + pink_noise * 0.01 + + def time_mask(self, mel_spec, max_mask_pct=0.1): + """时间遮罩（SpecAugment）""" + batch, channels, time, freq = mel_spec.shape + mask_len = int(time * max_mask_pct) + t = random.randint(0, mask_len) + t0 = random.randint(0, time - t) + mel_spec[:, :, t0:t0+t, :] = 0 + return mel_spec + + def freq_mask(self, mel_spec, max_mask_pct=0.1): + """频率遮罩""" + batch, channels, time, freq = mel_spec.shape + mask_len = int(freq * max_mask_pct) + f = random.randint(0, mask_len) + f0 = random.randint(0, freq - f) + mel_spec[:, :, :, f0:f0+f] = 0 + return mel_spec + + def pitch_shift(self, waveform, shift=2.0): + """音高变换""" + # 简化实现：使用 resampling + # 实际应用中可用更高级的库如 pydub 或 librosa + n_steps = int(shift * 10) + resampler = torchaudio.transforms.Resample( + self.sample_rate, + int(self.sample_rate * (1 + shift * 0.1)) + ) + return resampler(waveform) + + def gain(self, waveform, min_gain=0.5, max_gain=1.5): + """音量调整""" + gain = random.uniform(min_gain, max_gain) + return waveform * gain + +# 使用示例 +augmentation = BirdcallAugmentation(sample_rate=32000) +waveform, sr = torchaudio.load("bird_audio.wav") + +# 应用增强 +waveform_aug = augmentation.add_noise(waveform) +waveform_aug = augmentation.gain(waveform_aug) +``` + +#### 训练循环 +```python +import torch +import torch.nn as nn +from torch.utils.data import DataLoader + +def train_epoch(model, dataloader, criterion, optimizer, device, augmentation=None): + model.train() + total_loss = 0 + + for batch in dataloader: + waveforms, labels = batch + waveforms = waveforms.to(device) + labels = labels.to(device) + + # 数据增强（训练时） + if augmentation is not None: + # 在 Mel-spectrogram 上应用增强 + pass + + # 前向传播 + logits = model(waveforms) + loss = criterion(logits, labels.float()) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + total_loss += loss.item() + + return total_loss / len(dataloader) + +def train_model(model, train_loader, val_loader, num_epochs=30, device='cuda'): + criterion = nn.BCEWithLogitsLoss() + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3, weight_decay=1e-4) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_epochs) + + best_val_score = 0 + + for epoch in range(num_epochs): + # 训练 + train_loss = train_epoch(model, train_loader, criterion, optimizer, device) + + # 验证 + val_score, val_loss = validate(model, val_loader, criterion, device) + + # 学习率调度 + scheduler.step() + + print(f"Epoch {epoch+1}/{num_epochs}") + print(f"Train Loss: {train_loss:.4f}") + print(f"Val Loss: {val_loss:.4f}") + print(f"Val F1: {val_score:.4f}") + + # 保存最佳模型 + if val_score > best_val_score: + best_val_score = val_score + torch.save(model.state_dict(), 'best_model.pth') + + return model +``` + +#### 集成与后处理 +```python +import numpy as np +import pandas as pd + +class EnsemblePredictor: + def __init__(self, models, threshold=0.5, min_votes=4): + """ + Args: + models: 模型列表 + threshold: 二值化阈值 + min_votes: 最小投票数（如 1st place 用 4 票） + """ + self.models = models + self.threshold = threshold + self.min_votes = min_votes + + def predict(self, mel_spec_batch): + """集成预测""" + all_predictions = [] + + for model in self.models: + model.eval() + with torch.no_grad(): + logits = model(mel_spec_batch) + probs = torch.sigmoid(logits) + binary = (probs > self.threshold).float() + all_predictions.append(binary.cpu().numpy()) + + # 投票集成 + all_predictions = np.array(all_predictions) # (n_models, batch, num_classes) + votes = all_predictions.sum(axis=0) # (batch, num_classes) + + # 需要至少 min_votes 票 + final_pred = (votes >= self.min_votes).astype(int) + + return final_pred + +def temporal_post_process(predictions, window_size=3, min_duration=3): + """ + 时间后处理 + + Args: + predictions: (time_steps, num_classes) 二值预测 + window_size: 平滑窗口大小 + min_duration: 最小持续时间（时间步） + """ + smoothed = predictions.copy() + + # 时间平滑（多数投票） + for i in range(predictions.shape[0]): + start = max(0, i - window_size // 2) + end = min(predictions.shape[0], i + window_size // 2 + 1) + window = predictions[start:end] + smoothed[i] = (window.sum(axis=0) > window_size // 2).astype(int) + + # 移除短于阈值的检测 + final = smoothed.copy() + for c in range(predictions.shape[1]): + col = smoothed[:, c] + # 找连续段 + changes = np.diff(col, prepend=0, append=0) + starts = np.where(changes == 1)[0] + ends = np.where(changes == -1)[0] + + for s, e in zip(starts, ends): + if e - s < min_duration: + final[s:e, c] = 0 + + return final + +def create_submission(predictions, audio_ids, bird_species): + """ + 创建提交文件 + + Args: + predictions: (n_samples, num_classes) 二值预测 + audio_ids: 音频文件 ID 列表 + bird_species: 鸟类名称列表 + """ + rows = [] + for audio_id, pred in zip(audio_ids, predictions): + active_birds = [bird_species[i] for i, p in enumerate(pred) if p == 1] + if active_birds: + rows.append({ + 'row_id': f"{audio_id}", + 'birds': ' '.join(active_birds) + }) + else: + rows.append({ + 'row_id': f"{audio_id}", + 'birds': 'nocall' + }) + + submission = pd.DataFrame(rows) + return submission +``` + +### 最佳实践 + +1. **音频预处理标准化**： + - 统一采样率（32kHz 或 44.1kHz） + - 使用高质量的 Mel-spectrogram 参数（n_fft=2048, hop_length=512, n_mels=128） + - 对数幅度压缩（log 或 dB 转换） + +2. **模型选择**： + - ResNeSt 表现最佳（split-attention 机制） + - 在 ImageNet 上预训练的模型迁移效果好 + - Attention Pooling 优于 Global Average Pooling + +3. **数据增强策略**： + - SpecAugment（时间/频率遮罩）是必需的 + - Mixup 有助于提高泛化能力 + - 添加背景噪声提高鲁棒性 + - GAN 生成增强数据可以提升稀有类别性能 + +4. **集成方法**： + - 投票集成优于平均集成 + - 设置最小投票数阈值（如 4 票）可减少误报 + - 使用不同 checkpoint 和随机种子增加多样性 + +5. **后处理优化**： + - 时间平滑可以减少闪烁 + - 移除短于阈值的检测 + - 类别特定的阈值优化 + +6. **验证策略**： + - 使用 5-fold 交叉验证 + - 仔细设计验证集以反映测试集分布 + - 监控 micro-F1 分数 + +7. **训练技巧**： + - 使用 AdamW 优化器 + - Cosine annealing 学习率调度 + - Binary Cross-Entropy Loss + - Label smoothing 有助于正则化 + +8. **常见陷阱**： + - 避免过度拟合训练集的音频特征 + - 注意类别不平衡问题 + - 验证集和测试集可能有不同的分布 + - 推理时间限制（如果有）需要考虑模型效率 + +--- + +## BirdCLEF 2021 - Birdcall Identification + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology + LifeCLEF +- **目标**：识别音频录音中的鸟类叫声（弱监督多标签音频分类） +- **应用场景**：鸟类种群监测，生物声学研究，生态系统保护 +- **数据集规模**： + - 训练音频：约 3,900 段录音，涵盖 397 种鸟类 + - 测试音频：约 2,600 段连续录音（soundscape） + - 弱监督标注：只有音频级别的标签，无时间戳 +- **评估指标**：micro-averaged F1-score +- **最终排名**： + - 1st Place: DR (kami634) - 弱监督方案 + - 2nd Place: Christof Henkel + - 3rd Place: shiro + - 总参赛队伍：约 1,700+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Weak Supervision with PANNs (DR) + +核心技巧： +- **Pre-trained Audio Neural Networks (PANNs)**：使用预训练的音频神经网络 +- **Weak Supervision Strategy**：弱监督学习策略 +- **Attention Mechanisms**：自注意力机制用于音频分类 +- **Spectrogram-based Features**：基于频谱图的特征 +- **Model Ensemble**：多模型集成 +- **Post-processing**：后处理优化 + +实现细节： +- **基础模型**： + - 使用预训练的 PANNs (Pre-trained Audio Neural Networks) + - 包括 CNN14, CNN10, ResNet38 等架构 + - 在 AudioSet 上预训练 + - 迁移学习到鸟类叫声分类 +- **特征提取**： + - Mel-spectrogram（64/128 Mel bins） + - 对数幅度压缩 + - 多尺度时间窗口 +- **弱监督策略**： + - 仅使用音频级别的标签（无时间戳） + - 通过注意力机制定位关键区域 + - 多实例学习（Multiple Instance Learning） +- **模型架构**： + - CNN-based 特征提取器 + - Self-Attention 层 + - Global Pooling + 分类器 +- **集成方法**： + - 多个 PANNs 模型集成 + - 不同架构和预训练权重 + - 投票或平均策略 +- **数据增强**： + - Mixup + - SpecAugment + - 背景噪声添加 +- **后处理**： + - 时间平滑 + - 阈值优化 + - 类别特定的后处理 + +#### 2nd Place - New Baseline with Strong Augmentation (Christof Henkel) + +核心技巧： +- **New Baseline Architecture**：新颖的基线架构 +- **Mixup Augmentation**：Mixup 数据增强 +- **Background Noise Addition**：背景噪声添加 +- **Pseudo-labeling**：伪标签策略 +- **5-second Segment Inference**：5秒片段推理 +- **Strong Single Model**：强大的单模型 + +实现细节： +- **模型选择**： + - ResNet50 / ResNeSt50 + - EfficientNet variants + - DenseNet-based models +- **音频预处理**： + - 重采样到 32kHz + - Mel-spectrogram 提取 + - 标准化处理 +- **增强策略**： + - Mixup（强制使用） + - 时间遮罩（Time Masking） + - 频率遮罩（Frequency Masking） + - 背景噪声混合 +- **伪标签**： + - 使用训练好的模型预测未标注数据 + - 高置信度预测作为伪标签 + - 迭代训练 +- **训练配置**： + - Binary Cross-Entropy Loss + - AdamW 优化器 + - Cosine 学习率衰减 + - 5-fold 交叉验证 +- **推理策略**： + - 5秒滑动窗口 + - 窗口间有重叠 + - 多个窗口预测聚合 + +#### 3rd Place - Ensemble with Multiple Approaches (shiro) + +核心技巧： +- **Multiple Model Families**：多族模型集成 +- **Spectral Feature Engineering**：频谱特征工程 +- **Cross-Validation Strategy**：交叉验证策略 +- **Post-processing Pipeline**：后处理流程 +- **Attention-based Models**：基于注意力的模型 + +实现细节： +- **模型选择**： + - ResNet variants + - DenseNet variants + - EfficientNet variants + - Custom CNN architectures +- **特征多样性**： + - 不同 Mel-spectrogram 参数 + - MFCC features + - Chroma features + - Spectral contrast +- **训练策略**： + - 5-fold 交叉验证 + - Early stopping + - Learning rate scheduling +- **集成方法**： + - 加权平均 + - 基于验证集权重优化 + - 不同 checkpoint 集成 + +#### 4th Place - Third Time's The Charm (tattaka) + +核心技巧： +- **Iterative Improvement**：迭代改进策略 +- **Strong Data Augmentation**：强数据增强 +- **Spectrogram Preprocessing**：频谱预处理优化 +- **Model Architecture Search**：模型架构搜索 +- **Ensemble Optimization**：集成优化 + +实现细节： +- **音频处理**： + - 高质量 Mel-spectrogram 参数调优 + - 多种时间窗口长度 + - 频率范围选择 +- **模型架构**： + - ResNet50 + - ResNeSt50 + - DenseNet-121 +- **增强组合**： + - SpecAugment（多种参数） + - Mixup + CutMix + - 噪声增强 + - 音高变换 +- **训练技巧**： + - 渐进式训练 + - 迭代优化 + - A/B 测试不同策略 + +#### 5th Place - Dual Approach Blending (Kramarenko Vladislav) + +核心技巧： +- **Multiple Approaches**：多种方法尝试 +- **Different Feature Sets**：不同特征集 +- **Blending Strategy**：混合策略 +- **Spectral Analysis**：频谱分析 + +实现细节： +- **方法 1**：CNN + Mel-spectrogram +- **方法 2**：Gradient Boosting + 手工特征 +- **最终集成**：两种方法加权混合 + +#### 6th-10th Place 概述 + +**常见技术**： +- PANNs 预训练模型广泛使用 +- SpecAugment 成为标准增强 +- Mixup 几乎所有前排方案使用 +- 5-fold 交叉验证是标准配置 +- Mel-spectrogram 是主流特征 + +**关键技术点**： +- **弱监督处理**：使用注意力机制定位音频中的鸟类叫声 +- **数据增强**：SpecAugment + Mixup + 背景噪声 +- **模型集成**：多架构、多 checkpoint 集成 +- **后处理**：时间平滑、阈值优化、类别特定处理 + +### 代码模板 + +#### PANNs 模型加载和使用 +```python +import torch +import torch.nn as nn +# 需要安装: pip install torchlibrosa +from torchlibrosa.stft import Spectrogram, LogmelFilterBank + +class PANNsCNN14(nn.Module): + """ + 基于 PANNs CNN14 的模型 + 参考: https://github.com/qiuqiangkong/audioset_tagging_cnn + """ + def __init__(self, sample_rate=32000, window_size=512, hop_size=320, + mel_bins=64, fmin=50, fmax=14000, num_classes=397): + super().__init__() + + window = 'hann' + center = True + pad_mode = 'reflect' + ref = 1.0 + amin = 1e-10 + top_db = None + + # Spectrogram extractor + self.spectrogram_extractor = Spectrogram( + n_fft=window_size, + hop_length=hop_size, + win_length=window_size, + window=window, + center=center, + pad_mode=pad_mode, + freeze_parameters=True) + + # Logmel feature extractor + self.logmel_extractor = LogmelFilterBank( + sr=sample_rate, + n_fft=window_size, + n_mels=mel_bins, + fmin=fmin, + fmax=fmax, + ref=ref, + amin=amin, + top_db=top_db, + freeze_parameters=True) + + # SpecAugment (训练时使用) + self.spec_augment = SpecAugmentation( + time_drop_width=64, + time_stripes_num=2, + freq_drop_width=8, + freq_stripes_num=2) + + # CNN14 backbone + self.bn0 = nn.BatchNorm2d(mel_bins) + + self.conv_block1 = ConvBlock(in_channels=1, out_channels=64) + self.conv_block2 = ConvBlock(in_channels=64, out_channels=128) + self.conv_block3 = ConvBlock(in_channels=128, out_channels=256) + self.conv_block4 = ConvBlock(in_channels=256, out_channels=512) + self.conv_block5 = ConvBlock(in_channels=512, out_channels=1024) + self.conv_block6 = ConvBlock(in_channels=1024, out_channels=2048) + + self.fc1 = nn.Linear(2048, 2048, bias=True) + self.fc_audioset = nn.Linear(2048, num_classes, bias=True) + + self.init_weight() + + def init_weight(self): + init_bn(self.bn0) + init_layer(self.fc1) + init_layer(self.fc_audioset) + + def forward(self, input, mixup_lambda=None, device='cuda'): + """ + Args: + input: (batch_size, time_samples) + Returns: + output: (batch_size, num_classes) + """ + # Spectrogram + x = self.spectrogram_extractor(input) # (batch, 1, time, freq) + x = self.logmel_extractor(x) # (batch, 1, time, mel_bins) + + # BN + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + + # SpecAugment (仅训练时) + if self.training: + x = self.spec_augment(x) + + # CNN blocks + x = self.conv_block1(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block2(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block3(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block4(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block5(x, pool_size=(2, 2), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + x = self.conv_block6(x, pool_size=(1, 1), pool_type='avg') + x = F.dropout(x, p=0.2, training=self.training) + + # Global pooling + x = torch.mean(x, dim=3) # (batch, channels, time) + + (x1, _) = torch.max(x, dim=2) # (batch, channels) + x2 = torch.mean(x, dim=2) # (batch, channels) + x = x1 + x2 # (batch, channels) + + x = F.dropout(x, p=0.5, training=self.training) + x = F.relu_(self.fc1(x)) + embedding = F.dropout(x, p=0.5, training=self.training) + clipwise_output = torch.sigmoid(self.fc_audioset(x)) + + return clipwise_output + + def load_from_pretrained(self, pretrained_path): + """加载预训练权重""" + checkpoint = torch.load(pretrained_path, map_location='cpu') + model_state = self.state_dict() + pretrained_state = checkpoint['model'] + + # 过滤不匹配的键 + pretrained_state = {k: v for k, v in pretrained_state.items() + if k in model_state and v.shape == model_state[k].shape} + + model_state.update(pretrained_state) + self.load_state_dict(model_state) + print(f"Loaded pretrained weights from {pretrained_path}") + +class ConvBlock(nn.Module): + def __init__(self, in_channels, out_channels): + super().__init__() + + self.conv1 = nn.Conv2d(in_channels=in_channels, + out_channels=out_channels, + kernel_size=(3, 3), stride=(1, 1), + padding=(1, 1), bias=False) + self.conv2 = nn.Conv2d(in_channels=out_channels, + out_channels=out_channels, + kernel_size=(3, 3), stride=(1, 1), + padding=(1, 1), bias=False) + self.bn1 = nn.BatchNorm2d(out_channels) + self.bn2 = nn.BatchNorm2d(out_channels) + + self.init_weight() + + def init_weight(self): + init_bn(self.bn1) + init_bn(self.bn2) + init_layer(self.conv1) + init_layer(self.conv2) + + def forward(self, input, pool_size=(2, 2), pool_type='avg'): + x = input + x = F.relu_(self.bn1(self.conv1(x))) + x = F.relu_(self.bn2(self.conv2(x))) + if pool_type == 'max': + x = F.max_pool2d(x, kernel_size=pool_size) + elif pool_type == 'avg': + x = F.avg_pool2d(x, kernel_size=pool_size) + elif pool_type == 'avg+max': + x1 = F.avg_pool2d(x, kernel_size=pool_size) + x2 = F.max_pool2d(x, kernel_size=pool_size) + x = x1 + x2 + else: + raise ValueError(f'Unknown pool type: {pool_type}') + return x + +class SpecAugmentation(nn.Module): + def __init__(self, time_drop_width, time_stripes_num, + freq_drop_width, freq_stripes_num): + super().__init__() + self.time_drop_width = time_drop_width + self.time_stripes_num = time_stripes_num + self.freq_drop_width = freq_drop_width + self.freq_stripes_num = freq_stripes_num + + def forward(self, x): + """x: (batch, channels, time, freq)""" + self._mask_along_axis(x, self.time_drop_width, + self.time_stripes_num, axis=2) + self._mask_along_axis(x, self.freq_drop_width, + self.freq_stripes_num, axis=3) + return x + + def _mask_along_axis(self, x, drop_width, stripes_num, axis): + """沿指定轴遮罩""" + for _ in range(stripes_num): + drop_width = int(drop_width) if isinstance(drop_width, int) else \ + int(drop_width * x.shape[axis]) + drop_start = int(torch.rand(1).item() * (x.shape[axis] - drop_width)) + + if axis == 2: # time axis + x[:, :, drop_start:drop_start + drop_width, :] = 0 + elif axis == 3: # freq axis + x[:, :, :, drop_start:drop_start + drop_width] = 0 + return x + +def init_layer(layer): + """Initialize a Linear or Convolutional layer.""" + nn.init.xavier_uniform_(layer.weight) + if hasattr(layer, 'bias'): + if layer.bias is not None: + layer.bias.data.fill_(0.) + +def init_bn(bn): + """Initialize a Batchnorm layer.""" + bn.bias.data.fill_(0.) + bn.weight.data.fill_(1.) + +# 使用示例 +model = PANNsCNN14( + sample_rate=32000, + window_size=512, + hop_size=320, + mel_bins=64, + num_classes=397 +) + +# 加载预训练权重（可选） +# model.load_from_pretrained('path/to/pretrained/CNN14.pth') + +waveform = torch.randn(4, 32000 * 5) # (batch, 5 seconds at 32kHz) +with torch.no_grad(): + output = model(waveform) +print(output.shape) # (4, 397) +``` + +#### Mixup 数据增强 +```python +import torch +import numpy as np + +def mixup_data(x, y, alpha=0.2): + """ + Mixup 数据增强 + + Args: + x: 输入数据 (batch_size, ...) + y: 标签 (batch_size, num_classes) + alpha: Beta 分布参数 + + Returns: + mixed_x: 混合后的输入 + y_a, y_b: 两个样本的标签 + lam: 混合系数 + """ + if alpha > 0: + lam = np.random.beta(alpha, alpha) + else: + lam = 1 + + batch_size = x.size(0) + index = torch.randperm(batch_size).to(x.device) + + mixed_x = lam * x + (1 - lam) * x[index, :] + y_a, y_b = y, y[index] + + return mixed_x, y_a, y_b, lam + +def mixup_criterion(criterion, pred, y_a, y_b, lam): + """Mixup 损失函数""" + return lam * criterion(pred, y_a) + (1 - lam) * criterion(pred, y_b) + +# 使用示例 +criterion = nn.BCEWithLogitsLoss() + +for batch_idx, (waveforms, labels) in enumerate(train_loader): + waveforms = waveforms.to(device) + labels = labels.to(device) + + # 应用 Mixup + waveforms_mixed, labels_a, labels_b, lam = mixup_data( + waveforms, labels, alpha=0.2 + ) + + # 前向传播 + outputs = model(waveforms_mixed) + + # 计算 Mixup 损失 + loss = mixup_criterion(criterion, outputs, labels_a, labels_b, lam) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() +``` + +#### 弱监督训练（音频级别标签） +```python +import torch +import torch.nn as nn +from torch.utils.data import Dataset + +class BirdcallWeakDataset(Dataset): + """ + 弱监督数据集：只有音频级别标签，无时间戳 + """ + def __init__(self, audio_files, labels, audio_transforms=None, + duration=5, sample_rate=32000): + self.audio_files = audio_files + self.labels = labels # Multi-hot labels: (num_samples, num_classes) + self.audio_transforms = audio_transforms + self.duration = duration + self.sample_rate = sample_rate + + def __len__(self): + return len(self.audio_files) + + def __getitem__(self, idx): + # 加载音频 + waveform, sr = torchaudio.load(self.audio_files[idx]) + + # 重采样 + if sr != self.sample_rate: + resampler = torchaudio.transforms.Resample(sr, self.sample_rate) + waveform = resampler(waveform) + + # 固定长度（裁剪或填充） + target_length = self.duration * self.sample_rate + if waveform.shape[1] > target_length: + # 随机裁剪 + start = torch.randint(0, waveform.shape[1] - target_length, (1,)).item() + waveform = waveform[:, start:start + target_length] + elif waveform.shape[1] < target_length: + # 填充 + padding = target_length - waveform.shape[1] + waveform = torch.nn.functional.pad(waveform, (0, padding)) + + # 获取标签（音频级别，多标签） + label = self.labels[idx] + + # 数据增强 + if self.audio_transforms is not None: + waveform = self.audio_transforms(waveform) + + return waveform, label + +class AttentionPooling(nn.Module): + """ + 注意力池化：用于弱监督学习，自动定位重要区域 + """ + def __init__(self, input_dim, hidden_dim=128): + super().__init__() + self.attention = nn.Sequential( + nn.Linear(input_dim, hidden_dim), + nn.Tanh(), + nn.Linear(hidden_dim, 1) + ) + + def forward(self, x): + """ + Args: + x: (batch, time_steps, features) + + Returns: + pooled: (batch, features) + weights: (batch, time_steps) - 可视化注意力 + """ + attn_weights = F.softmax(self.attention(x), dim=1) + pooled = (x * attn_weights).sum(dim=1) + return pooled, attn_weights + +class WeaklySupervisedBirdcallModel(nn.Module): + """ + 弱监督鸟类叫声分类模型 + """ + def __init__(self, num_classes=397, pretrained=True): + super().__init__() + + # 使用预训练的 PANNs CNN14 作为特征提取器 + self.backbone = PANNsCNN14(num_classes=num_classes, pretrained=pretrained) + + # 移除最后的分类层 + self.backbone.fc_audioset = nn.Identity() + + # 注意力池化 + feature_dim = 2048 # CNN14 的输出维度 + self.attention_pool = AttentionPooling(feature_dim, hidden_dim=128) + + # 分类器 + self.classifier = nn.Sequential( + nn.Dropout(0.3), + nn.Linear(feature_dim, 512), + nn.ReLU(), + nn.Dropout(0.2), + nn.Linear(512, num_classes) + ) + + def forward(self, x, return_attention=False): + """ + Args: + x: (batch, time_samples) + return_attention: 是否返回注意力权重用于可视化 + + Returns: + logits: (batch, num_classes) + attention_weights (optional): (batch, time_steps) + """ + # 提取特征（修改 backbone 以返回时间维度特征） + features = self.extract_features(x) # (batch, time_steps, feature_dim) + + # 注意力池化 + pooled, attn_weights = self.attention_pool(features) + + # 分类 + logits = self.classifier(pooled) + + if return_attention: + return logits, attn_weights + return logits + + def extract_features(self, x): + """ + 从 backbone 提取时间维度特征 + 这是一个简化版本，实际使用时需要修改 PANNsCNN14 + """ + # 简化实现：直接使用全局特征 + with torch.no_grad(): + features = self.backbone.fc1( + torch.mean(self.backbone.bn0( + self.backbone.logmel_extractor( + self.backbone.spectrogram_extractor(x) + ).transpose(1, 3) + ), dim=3) + ) + # 添加时间维度 + return features.unsqueeze(1) # (batch, 1, feature_dim) + +# 训练循环 +def train_weakly_supervised(model, dataloader, criterion, optimizer, device, use_mixup=True): + model.train() + + for waveforms, labels in dataloader: + waveforms = waveforms.to(device) + labels = labels.to(device).float() + + # Mixup 增强 + if use_mixup and np.random.rand() < 0.5: + waveforms, labels_a, labels_b, lam = mixup_data(waveforms, labels, alpha=0.2) + + # 前向传播 + logits = model(waveforms) + + # 计算损失 + if use_mixup and np.random.rand() < 0.5: + loss = mixup_criterion(criterion, logits, labels_a, labels_b, lam) + else: + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + +# 可视化注意力（用于理解模型关注的区域） +def visualize_attention(model, waveform, bird_name): + """可视化注意力权重，了解模型关注的音频区域""" + model.eval() + with torch.no_grad(): + logits, attention = model(waveform.unsqueeze(0), return_attention=True) + + # attention: (1, time_steps) + attention = attention.squeeze(0).cpu().numpy() + + import matplotlib.pyplot as plt + fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 6)) + + # 音频波形 + ax1.plot(waveform.cpu().numpy().T) + ax1.set_title(f'Audio Waveform - {bird_name}') + ax1.set_xlabel('Time') + ax1.set_ylabel('Amplitude') + + # 注意力权重 + ax2.plot(attention) + ax2.set_title('Attention Weights') + ax2.set_xlabel('Time Step') + ax2.set_ylabel('Attention Weight') + + plt.tight_layout() + plt.savefig('attention_visualization.png') + plt.close() +``` + +#### 5秒滑动窗口推理 +```python +import torch +import numpy as np + +def predict_with_sliding_window(model, audio_path, window_size=5, + hop_size=2.5, sample_rate=32000, + device='cuda'): + """ + 使用滑动窗口进行推理 + + Args: + model: 训练好的模型 + audio_path: 音频文件路径 + window_size: 窗口大小（秒） + hop_size: 跳跃大小（秒） + sample_rate: 采样率 + device: 设备 + + Returns: + predictions: (num_windows, num_classes) + timestamps: 窗口时间戳 + """ + model.eval() + + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + if sr != sample_rate: + resampler = torchaudio.transforms.Resample(sr, sample_rate) + waveform = resampler(waveform) + + waveform = waveform.mean(dim=0, keepdim=True) # 转为单声道 + + # 计算窗口参数 + window_samples = int(window_size * sample_rate) + hop_samples = int(hop_size * sample_rate) + + predictions = [] + timestamps = [] + + # 滑动窗口 + with torch.no_grad(): + for start in range(0, waveform.shape[1] - window_samples + 1, hop_samples): + end = start + window_samples + window = waveform[:, start:end].to(device) + + # 预测 + logits = model(window) + probs = torch.sigmoid(logits).cpu().numpy() + + predictions.append(probs[0]) + timestamps.append(start / sample_rate) + + predictions = np.array(predictions) + timestamps = np.array(timestamps) + + return predictions, timestamps + +def aggregate_predictions(predictions, threshold=0.5, min_duration=3): + """ + 聚合滑动窗口预测 + + Args: + predictions: (num_windows, num_classes) + threshold: 二值化阈值 + min_duration: 最小持续时间（窗口数） + + Returns: + final_pred: (num_windows, num_classes) 二值预测 + """ + binary_pred = (predictions > threshold).astype(int) + + # 时间平滑 + final_pred = binary_pred.copy() + for c in range(binary_pred.shape[1]): + col = binary_pred[:, c] + + # 移除短于阈值的检测 + changes = np.diff(col, prepend=0, append=0) + starts = np.where(changes == 1)[0] + ends = np.where(changes == -1)[0] + + for s, e in zip(starts, ends): + if e - s < min_duration: + final_pred[s:e, c] = 0 + + return final_pred + +def create_birdclef_submission(predictions, timestamps, audio_id, + bird_species, threshold=0.5): + """ + 创建 BirdCLEF 格式的提交文件 + + Args: + predictions: (num_windows, num_classes) 概率预测 + timestamps: (num_windows,) 时间戳 + audio_id: 音频文件 ID + bird_species: 鸟类名称列表 + threshold: 二值化阈值 + + Returns: + rows: 提交文件的行列表 + """ + rows = [] + + for i, (pred, ts) in enumerate(zip(predictions, timestamps)): + # 获取活跃的鸟类 + active_birds = [] + for j, p in enumerate(pred): + if p > threshold: + active_birds.append(bird_species[j]) + + # 创建 row_id + row_id = f"{audio_id}_{ts:.1f}" + + if active_birds: + rows.append({ + 'row_id': row_id, + 'birds': ' '.join(active_birds) + }) + else: + rows.append({ + 'row_id': row_id, + 'birds': 'nocall' + }) + + return rows + +# 使用示例 +model = WeaklySupervisedBirdcallModel(num_classes=397) +model = model.to(device) +model.load_state_dict(torch.load('best_model.pth')) + +audio_path = 'test_soundscape.wav' +predictions, timestamps = predict_with_sliding_window( + model, audio_path, window_size=5, hop_size=2.5, device=device +) + +# 聚合预测 +final_pred = aggregate_predictions(predictions, threshold=0.5, min_duration=3) + +# 创建提交 +bird_species = [...] # 397 个鸟类名称列表 +rows = create_birdclef_submission( + predictions, timestamps, 'soundscape_01', bird_species, threshold=0.5 +) + +import pandas as pd +submission = pd.DataFrame(rows) +submission.to_csv('submission.csv', index=False) +``` + +### 最佳实践 + +1. **弱监督学习策略**： + - 使用注意力机制定位音频中的关键区域 + - 多实例学习（MIL）框架处理音频级别标签 + - 时序池化（Temporal Pooling）聚合时间维度信息 + +2. **预训练模型利用**： + - PANNs（AudioSet 预训练）是最流行的起点 + - CNN14/CNN10 提供强大的基线特征 + - 迁移学习显著提升性能 + +3. **数据增强组合**： + - SpecAugment（时间+频率遮罩）必需 + - Mixup 是 BirdCLEF 2021 的关键技巧 + - 背景噪声添加提高鲁棒性 + - 组合多种增强效果最佳 + +4. **训练技巧**： + - 5-fold 交叉验证标准配置 + - AdamW + Cosine 学习率 + - Binary Cross-Entropy Loss + - Label Smoothing 有助于正则化 + - 渐进式训练策略 + +5. **推理策略**： + - 5秒滑动窗口（与标注一致） + - 窗口间有重叠（2.5秒跳跃） + - 时间平滑减少闪烁 + - 移除短于阈值的检测 + +6. **集成方法**： + - 多架构集成（ResNet, DenseNet, EfficientNet） + - 多 checkpoint 集成 + - 不同增强配置增加多样性 + - 加权平均或投票集成 + +7. **后处理优化**： + - 类别特定的阈值优化 + - 时间平滑（移动平均或中值滤波） + - 最小持续时间过滤 + - 基于验证集优化阈值 + +8. **常见陷阱**： + - 忽略弱监督的特殊性（无时间戳） + - 过度依赖单一模型 + - 验证集和测试集分布不同 + - 忘记时间平滑导致预测不稳定 + - 阈值选择不当影响 F1 分数 + +--- + +## BirdCLEF 2022 - Endangered Bird Sounds Classification + +**竞赛背景：** +- **主办方**：Cornell Lab of Ornithology + LifeCLEF +- **目标**：识别夏威夷濒危鸟类的叫声（多标签音频分类） +- **应用场景**：濒危物种保护，生态系统监测 +- **数据集规模**： + - 训练音频：约 8,700 段标注录音，涵盖 152 种鸟类（主要是夏威夷物种） + - 测试音频：约 1,300 段连续录音（soundscape） + - 短片段标注：部分音频有 5 秒级别的短片段标注 + - 背景噪声：包含雨声、风声、昆虫声等复杂环境音 +- **评估指标**：micro-averaged F1-score +- **最终排名**： + - 1st Place: kdl - "It's not all BirdNet" + - 2nd Place: Leon Shangguan + - 3rd Place: uemu-slime + - 总参赛队伍：约 1,600+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Beyond BirdNet (kdl) + +核心技巧： +- **BirdNet + Perch Architecture**：结合 BirdNet 和 Perch 模型 +- **SED Framework**：声音事件检测框架 +- **Multi-scale Input**：短片段（5秒）和长片段（10秒+） +- **AND Rule**：短片段和长片段预测的 AND 逻辑 +- **Model Ensemble**：多架构集成 +- **External Data**：使用 BirdCLEF 2021 数据增强 + +实现细节： +- **模型架构组合**： + - BirdNet（预训练鸟类分类模型） + - Perch（预训练模型，类似 BirdNET-lite） + - 自训练 CNN 模型（ResNet50/ResNeSt50） + - SED 模型（framewise 输出） +- **多尺度策略**： + - 短片段（5秒）：精确分类 + - 长片段（10-15秒）：提高召回率 + - AND 规则：短片段 AND 长片段都预测为正才认为存在 +- **SED 实现**： + - 使用 framewise 输出 + - max(framewise, dim=time) 聚合 + - 时间注意力机制 +- **集成方法**： + - 多个模型集成（10+ 模型） + - 不同预训练权重 + - 不同输入长度 + - TTA（Test Time Augmentation） +- **外部数据**： + - BirdCLEF 2021 数据迁移学习 + - 额外鸟类音频数据 +- **后处理**： + - 时间平滑 + - 最小持续时间过滤 + - 类别特定阈值 + +#### 2nd Place - SED + CNN with 7 Models Ensemble (Leon Shangguan) + +核心技巧： +- **SED Framework**：声音事件检测框架 +- **10-second Chunks**：10秒片段处理 +- **Centered 5-second CNN**：中心 5 秒 CNN 预测 +- **Max Framewise Pooling**：framewise 最大值池化 +- **7 Models Ensemble**：7 模型集成 +- **TTA with 2s Shifts**：2秒偏移的测试时增强 + +实现细节： +- **SED 模型**： + - 使用 10 秒音频片段 + - 输出 framewise 预测 + - max(framewise, dim=time) 聚合 + - ResNet50/ResNeSt50 backbone +- **CNN 模型**： + - 仅对中心 5 秒进行预测 + - 减少计算量 + - Mel-spectrogram 输入 +- **集成策略**： + - 7 个模型集成 + - 不同架构和配置 + - 加权平均 +- **TTA**： + - 2 秒偏移的多个预测 + - 预测平均 +- **数据增强**： + - SpecAugment + - Mixup + - 背景噪声 + +#### 3rd Place - 18 Checkpoints Ensemble (uemu-slime) + +核心技巧： +- **18 Checkpoints Ensemble**：18 个模型检查点集成 +- **Multiple CNN Architectures**：多种 CNN 架构 +- **Different Folds**：不同折的训练 +- **Perch + BirdNet**：使用预训练模型 +- **Strong Data Augmentation**：强数据增强 + +实现细节： +- **模型架构**： + - ResNet50 + - ResNeSt50 + - EfficientNet-B0/B3 + - Perch（预训练） + - BirdNet（预训练） +- **训练策略**： + - 每个架构在 5-fold 上训练 + - 选择最佳 checkpoint + - 共 18 个模型 +- **集成方法**： + - 简单平均 + - 所有模型等权重 +- **增强组合**： + - SpecAugment + - Mixup + - 背景噪声 + - 时间遮罩/频率遮罩 + +#### 4th Place - CNN-based Ensemble (Kramarenko Vladislav) + +核心技巧： +- **CNN Ensemble**：CNN 模型集成 +- **Mel-Spectrogram Features**：Mel 频谱特征 +- **Multiple Backbones**：多种主干网络 +- **Cross-Validation**：交叉验证 + +实现细节： +- **模型选择**： + - ResNet50 + - ResNeSt50 + - DenseNet-121 +- **特征工程**： + - Mel-spectrogram + - 不同参数配置 +- **训练**： + - 5-fold 交叉验证 + - Early stopping + +#### 5th Place - Reimplementation of 2021 2nd Place (common-kestrel) + +核心技巧： +- **9 Models Ensemble**：9 模型集成 +- **BirdCLEF 2021 Baseline**：重实现 2021 年 2nd place 方案 +- **4x Backbones**：4 种主干网络 +- **Different Seeds and Folds**：不同随机种子和折 + +实现细节： +- **主干网络**： + - ResNet50 + - ResNeSt50 + - EfficientNet-B0 + - DenseNet-121 +- **配置多样性**： + - 不同随机种子 + - 不同 fold + - 不同数据增强参数 +- **集成方法**： + - 平均集成 + - 9 个模型 + +#### 6th-10th Place 概述 + +**常见技术**： +- BirdNet 预训练模型广泛使用 +- Perch 模型（类似 BirdNET-lite） +- SED（Sound Event Detection）框架 +- 多尺度输入（5秒 + 10-15秒） +- SpecAugment + Mixup 标准配置 + +**关键技术点**： +- **短片段长片段结合**：AND 规则减少误报 +- **Framewise 预测**：SED 模型的 framewise 输出 +- **外部数据利用**：BirdCLEF 2021 数据迁移学习 +- **模型集成**：10-20 个模型集成是常态 +- **后处理**：时间平滑、最小持续时间过滤 + +### 代码模板 + +#### SED 模型（Framewise 输出） +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SEDModel(nn.Module): + """ + 声音事件检测模型 - 输出 framewise 预测 + + 用于 BirdCLEF 2022 风格的音频分类 + """ + def __init__(self, num_classes=152, backbone='resnet50', + sample_rate=32000, window_size=5, hop_size=512): + super().__init__() + + self.num_classes = num_classes + self.window_size = window_size + self.sample_rate = sample_rate + + # Mel-spectrogram 提取器 + self.mel_extractor = MelSpectrogramExtractor( + sample_rate=sample_rate, + n_mels=128, + n_fft=2048, + hop_length=hop_size + ) + + # Backbone（简化版本） + if backbone == 'resnet50': + import torchvision.models as models + self.backbone = models.resnet50(pretrained=True) + # 修改第一层接受 1 通道输入（mel-spectrogram） + self.backbone.conv1 = nn.Conv2d( + 1, 64, kernel_size=7, stride=2, padding=3, bias=False + ) + feature_dim = 2048 + elif backbone == 'resnest50': + # 使用 ResNeSt50 + feature_dim = 2048 + + # 移除最后的全连接层 + self.backbone.fc = nn.Identity() + + # Framewise 分类头 + self.fc = nn.Linear(feature_dim, num_classes) + + def forward(self, waveform, return_frames=False): + """ + Args: + waveform: (batch, time_samples) + return_frames: 是否返回 framewise 预测 + + Returns: + output: (batch, num_classes) 或 (batch, time_frames, num_classes) + """ + batch_size = waveform.shape[0] + + # 提取 Mel-spectrogram + mel_spec = self.mel_extractor.extract(waveform) # (batch, 1, mel_bins, time_frames) + + # 通过 backbone（保留时间维度） + # 简化版本：实际需要修改 backbone 以保留时间维度 + features = self.extract_features_with_time(mel_spec) # (batch, time_frames, feature_dim) + + # Framewise 预测 + framewise_output = self.fc(features) # (batch, time_frames, num_classes) + + if return_frames: + return framewise_output + + # 聚合（max pooling over time） + output, _ = torch.max(framewise_output, dim=1) # (batch, num_classes) + + return output + + def extract_features_with_time(self, mel_spec): + """ + 提取特征并保留时间维度 + + 这是一个简化版本，实际使用时需要修改 backbone + """ + # 将时间维度视为 batch 维度处理 + batch, channels, mel_bins, time_frames = mel_spec.shape + + # Reshape: (batch * time_frames, channels, mel_bins, 1) + mel_spec_reshaped = mel_spec.permute(0, 3, 1, 2).reshape( + batch * time_frames, channels, mel_bins, 1 + ) + + # 通过 backbone（需要对输入维度进行调整） + # 这里简化为直接使用全局特征 + features = self.backbone(mel_spec_reshaped) # (batch * time_frames, feature_dim) + + # Reshape 回 (batch, time_frames, feature_dim) + features = features.reshape(batch, time_frames, -1) + + return features + +class MultiScaleSEDModel(nn.Module): + """ + 多尺度 SED 模型 + + 结合短片段（5秒）和长片段（10秒）预测 + """ + def __init__(self, num_classes=152, short_duration=5, long_duration=10): + super().__init__() + + self.num_classes = num_classes + + # 短片段模型（5秒） + self.short_model = SEDModel( + num_classes=num_classes, + window_size=short_duration + ) + + # 长片段模型（10秒） + self.long_model = SEDModel( + num_classes=num_classes, + window_size=long_duration + ) + + def forward(self, waveform_short, waveform_long, use_and_rule=True): + """ + Args: + waveform_short: 5秒音频 (batch, 5 * sample_rate) + waveform_long: 10秒音频 (batch, 10 * sample_rate) + use_and_rule: 是否使用 AND 规则 + + Returns: + output: (batch, num_classes) + """ + # 短片段预测 + output_short = self.short_model(waveform_short) # (batch, num_classes) + prob_short = torch.sigmoid(output_short) + + # 长片段预测 + output_long = self.long_model(waveform_long) # (batch, num_classes) + prob_long = torch.sigmoid(output_long) + + if use_and_rule: + # AND 规则：两者都为正才认为存在 + prob_final = prob_short * prob_long + else: + # OR 规则：任一为正就认为存在 + prob_final = torch.clamp(prob_short + prob_long, 0, 1) + + return prob_final + +# 使用示例 +model = MultiScaleSEDModel(num_classes=152, short_duration=5, long_duration=10) + +# 短片段和长片段 +waveform_short = torch.randn(4, 5 * 32000) # 4 samples, 5 seconds +waveform_long = torch.randn(4, 10 * 32000) # 4 samples, 10 seconds + +# 预测 +with torch.no_grad(): + prob = model(waveform_short, waveform_long, use_and_rule=True) +print(prob.shape) # (4, 152) +``` + +#### TTA（Test Time Augmentation） +```python +import torch +import numpy as np + +def predict_with_tta(model, audio_path, window_size=5, tta_shifts=[0, 1, 2], + sample_rate=32000, device='cuda'): + """ + 使用 TTA 进行推理 + + Args: + model: 训练好的模型 + audio_path: 音频文件路径 + window_size: 窗口大小（秒） + tta_shifts: TTA 偏移量（秒） + sample_rate: 采样率 + device: 设备 + + Returns: + predictions: (num_windows, num_classes) TTA 平均后的预测 + """ + model.eval() + + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + if sr != sample_rate: + resampler = torchaudio.transforms.Resample(sr, sample_rate) + waveform = resampler(waveform) + + waveform = waveform.mean(dim=0, keepdim=True) # 单声道 + + window_samples = int(window_size * sample_rate) + + # 存储所有 TTA 预测 + all_tta_predictions = [] + + for shift in tta_shifts: + shift_samples = int(shift * sample_rate) + + # 计算起始位置 + start_positions = list(range(shift_samples, waveform.shape[1] - window_samples + 1, + int(window_size * sample_rate))) + + predictions = [] + + with torch.no_grad(): + for start in start_positions: + end = start + window_samples + window = waveform[:, start:end].to(device) + + # 预测 + logits = model(window) + probs = torch.sigmoid(logits).cpu().numpy() + predictions.append(probs[0]) + + predictions = np.array(predictions) + all_tta_predictions.append(predictions) + + # TTA 平均 + all_tta_predictions = np.array(all_tta_predictions) # (num_shifts, num_windows, num_classes) + + # 对齐并平均 + avg_predictions = np.mean(all_tta_predictions, axis=0) + + return avg_predictions + +# 使用示例 +model = SEDModel(num_classes=152) +model = model.to(device) +model.load_state_dict(torch.load('best_model.pth')) + +audio_path = 'test_soundscape.wav' +predictions = predict_with_tta( + model, audio_path, window_size=5, tta_shifts=[0, 1, 2], device=device +) + +# 二值化 +threshold = 0.5 +binary_pred = (predictions > threshold).astype(int) +``` + +#### AND 规则后处理 +```python +import numpy as np + +def and_rule_post_process(short_pred, long_pred, threshold=0.5): + """ + AND 规则后处理 + + Args: + short_pred: 短片段预测 (num_windows_short, num_classes) + long_pred: 长片段预测 (num_windows_long, num_classes) + threshold: 二值化阈值 + + Returns: + final_pred: AND 规则后的预测 (num_windows_short, num_classes) + """ + # 二值化 + binary_short = (short_pred > threshold).astype(int) + binary_long = (long_pred > threshold).astype(int) + + # 长片段预测需要对应到短片段的时间位置 + # 假设长片段是短片段的两倍长度 + scale_factor = len(short_pred) / len(long_pred) + + final_pred = np.zeros_like(binary_short) + + for i in range(len(short_pred)): + # 找到对应的长片段索引 + long_idx = int(i / scale_factor) + + if long_idx < len(binary_long): + # AND 规则：两者都为 1 才认为存在 + final_pred[i] = binary_short[i] & binary_long[long_idx] + else: + # 没有对应的长片段预测，使用短片段预测 + final_pred[i] = binary_short[i] + + return final_pred + +# 使用示例 +# 短片段预测（5秒窗口） +short_pred = np.random.rand(100, 152) # 100 个窗口，152 个类别 + +# 长片段预测（10秒窗口） +long_pred = np.random.rand(50, 152) # 50 个窗口 + +# 应用 AND 规则 +final_pred = and_rule_post_process(short_pred, long_pred, threshold=0.5) +``` + +#### 模型集成 +```python +import torch +import numpy as np + +class EnsembleModel: + """ + 模型集成类 + """ + def __init__(self, models, weights=None, device='cuda'): + """ + Args: + models: 模型列表 + weights: 模型权重（可选），默认平均 + device: 设备 + """ + self.models = models + self.device = device + + if weights is None: + # 默认等权重 + self.weights = [1.0 / len(models)] * len(models) + else: + # 归一化权重 + total = sum(weights) + self.weights = [w / total for w in weights] + + # 将模型移到设备并设置为评估模式 + for model in self.models: + model.to(device) + model.eval() + + def predict(self, waveform): + """ + 集成预测 + + Args: + waveform: 输入音频 (batch, time_samples) + + Returns: + ensemble_pred: 集成后的预测 (batch, num_classes) + """ + all_predictions = [] + + with torch.no_grad(): + for model in self.models: + logits = model(waveform) + probs = torch.sigmoid(logits).cpu().numpy() + all_predictions.append(probs) + + all_predictions = np.array(all_predictions) # (num_models, batch, num_classes) + + # 加权平均 + ensemble_pred = np.zeros_like(all_predictions[0]) + for i, pred in enumerate(all_predictions): + ensemble_pred += self.weights[i] * pred + + return ensemble_pred + + def predict_from_files(self, model_paths, ModelClass, model_kwargs, waveform): + """ + 从文件加载模型并预测 + + Args: + model_paths: 模型文件路径列表 + ModelClass: 模型类 + model_kwargs: 模型初始化参数 + waveform: 输入音频 + + Returns: + ensemble_pred: 集成后的预测 + """ + all_predictions = [] + + for path in model_paths: + # 加载模型 + model = ModelClass(**model_kwargs) + model.load_state_dict(torch.load(path)) + model.to(self.device) + model.eval() + + # 预测 + with torch.no_grad(): + logits = model(waveform) + probs = torch.sigmoid(logits).cpu().numpy() + all_predictions.append(probs) + + all_predictions = np.array(all_predictions) + + # 加权平均 + ensemble_pred = np.zeros_like(all_predictions[0]) + for i, pred in enumerate(all_predictions): + ensemble_pred += self.weights[i] * pred + + return ensemble_pred + +# 使用示例 +# 假设有 7 个模型 +models = [ + SEDModel(num_classes=152, backbone='resnet50'), + SEDModel(num_classes=152, backbone='resnest50'), + SEDModel(num_classes=152, backbone='efficientnet_b0'), + # ... 更多模型 +] + +# 加载权重 +for i, model in enumerate(models): + model.load_state_dict(torch.load(f'model_{i}.pth')) + +# 创建集成 +ensemble = EnsembleModel(models, weights=None, device=device) + +# 预测 +waveform = torch.randn(4, 5 * 32000).to(device) +predictions = ensemble.predict(waveform) +print(predictions.shape) # (4, 152) +``` + +#### BirdNet/Perch 模型使用 +```python +""" +BirdNet 和 Perch 是预训练的鸟类音频分类模型 + +使用前需要： +1. 安装 birdnetlib 或 perch 库 +2. 下载预训练权重 + +这里提供一个简化接口示例 +""" + +class BirdNetModel(nn.Module): + """ + BirdNet 模型包装器 + + 实际使用时需要从官方仓库获取模型 + 参考: https://github.com/BirdVox/birdnet-library + """ + def __init__(self, num_classes=152, pretrained_path=None): + super().__init__() + + # 这里应该是 BirdNet 的实际架构 + # 简化版本：使用 ResNet50 + import torchvision.models as models + self.backbone = models.resnet50(pretrained=True) + + # 修改第一层接受 mel-spectrogram + self.backbone.conv1 = nn.Conv2d( + 1, 64, kernel_size=7, stride=2, padding=3, bias=False + ) + + feature_dim = 2048 + + # 分类头 + self.classifier = nn.Sequential( + nn.Dropout(0.5), + nn.Linear(feature_dim, num_classes) + ) + + # 加载预训练权重 + if pretrained_path is not None: + self.load_pretrained(pretrained_path) + + def load_pretrained(self, path): + """加载预训练权重""" + state_dict = torch.load(path, map_location='cpu') + + # 过滤不兼容的键 + model_state = self.state_dict() + pretrained_state = { + k: v for k, v in state_dict.items() + if k in model_state and v.shape == model_state[k].shape + } + + model_state.update(pretrained_state) + self.load_state_dict(model_state) + print(f"Loaded pretrained weights from {path}") + + def forward(self, mel_spec): + """ + Args: + mel_spec: (batch, 1, mel_bins, time_frames) + + Returns: + logits: (batch, num_classes) + """ + features = self.backbone(mel_spec) + logits = self.classifier(features) + return logits + +# 使用示例（需要实际的预训练权重） +# model = BirdNetModel(num_classes=152, pretrained_path='birdnet.pth') +# model.eval() +# with torch.no_grad(): +# logits = model(mel_spec) +# probs = torch.sigmoid(logits) +``` + +### 最佳实践 + +1. **多尺度策略**： + - 短片段（5秒）用于精确分类 + - 长片段（10-15秒）提高召回率 + - AND 规则减少误报（两个都为正才认为存在） + - OR 规则提高召回（任一为正就认为存在） + +2. **SED 框架**： + - Framewise 输出提供时间分辨率 + - Max pooling over time 聚合 + - 注意力权重加权 + +3. **模型集成**： + - 10-20 个模型集成是常态 + - 不同架构（ResNet, ResNeSt, EfficientNet） + - 不同训练配置（fold, seed, 数据增强） + - 加权平均或投票 + +4. **预训练模型利用**： + - BirdNet：强大的鸟类分类预训练模型 + - Perch：轻量级版本（BirdNET-lite） + - 迁移学习显著提升性能 + - 在目标任务上微调 + +5. **外部数据**： + - BirdCLEF 2021 数据 + - 其他鸟类音频数据集 + - 预训练模型在大规模数据上训练 + +6. **TTA（Test Time Augmentation）**： + - 时间偏移（1-2秒） + - 多个预测平均 + - 提高稳定性 + +7. **后处理**： + - 时间平滑 + - 最小持续时间过滤 + - 类别特定阈值 + - AND 规则结合短长片段 + +8. **常见陷阱**： + - 忽视短片段和长片段的互补性 + - 过度依赖单一模型或架构 + - 集成权重未优化 + - 忘记使用 TTA + - AND/OR 规则选择不当 + +--- + +## Rainforest Connection Species Audio Detection 2021 + +**竞赛背景：** +- **主办方**：Rainforest Connection (RFCx) +- **目标**：检测热带雨林录音中的鸟类和蛙类叫声（多标签音频检测） +- **应用场景**：生物多样性监测，生态系统保护，濒危物种追踪 +- **数据集规模**： + - 训练音频：约 2,000 段标注录音 + - 测试音频：约 200 段连续录音（soundscape） + - 物种数量：24 种鸟类和蛙类 + - 采样率：48 kHz +- **评估指标**：LWLRAP (Label-Weighted Label-Ranking Average Precision) +- **最终排名**： + - 1st Place: watercooled + - 7th Place: Beluga & Peter + - 11th Place: cpmp + - 13th Place: Ryan Epp + - 总参赛队伍：约 2,200+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Image Classification Approach (watercooled) + +核心技巧： +- **Mel-Spectrogram as Images**：将 Mel 频谱视为图像 +- **Pretrained Image Models**：使用预训练图像分类模型 +- **Ensemble**：多模型集成 +- **Temporal Pooling**：时间池化策略 +- **Data Augmentation**：图像和音频增强 +- **Post-processing**：后处理优化 + +实现细节： +- **模型架构**： + - ResNet50/ResNeSt50（ImageNet 预训练） + - EfficientNet-B3 + - 修改第一层接受单通道输入（Mel-spectrogram） +- **特征提取**： + - Mel-spectrogram（128 Mel bins） + - 对数幅度压缩 + - 时间维度：5 秒窗口 +- **集成方法**： + - 多个模型集成 + - 不同 checkpoint + - 加权平均 +- **后处理**： + - 时间平滑 + - 阈值优化 + - 最小持续时间过滤 + +#### 7th Place - Strong Baseline with Ensemble (Beluga & Peter) + +核心技巧： +- **ResNeSt50 Architecture**：ResNeSt-50 主干网络 +- **Mel-Spectrogram Features**：Mel 频谱特征 +- **5-fold Cross-Validation**：5 折交叉验证 +- **Model Ensemble**：模型集成 +- **Strong Data Augmentation**：强数据增强 + +实现细节： +- **模型选择**： + - ResNeSt50（预训练） + - EfficientNet-B3 + - DenseNet-121 +- **增强策略**： + - SpecAugment + - Mixup + - 背景噪声 + - 时间遮罩/频率遮罩 + +#### 11th Place - The 0.931 Magic Explained (cpmp) + +核心技巧： +- **Image Classification Approach**：图像分类方法 +- **High-Performance Architecture**：高性能架构 +- **Optimized Preprocessing**：优化的预处理 +- **LWLRAP-specific Optimization**：针对 LWLRAP 指标优化 + +实现细节： +- **关键发现**： + - 优化的 Mel-spectrogram 参数 + - 特定的数据增强组合 + - 后处理技巧达到 0.931 分数 + +#### 13th Place - Mean Co-Teachers and Noisy Students (Ryan Epp) + +核心技巧： +- **Mean Teacher**：均值教师模型 +- **Co-Teaching**：协同教学 +- **Noisy Student**：噪声学生策略 +- **Semi-Supervised Learning**：半监督学习 +- **Pseudo-labeling**：伪标签 + +实现细节： +- **半监督策略**： + - 使用未标注数据 + - 伪标签迭代优化 + - Mean Teacher 平滑预测 + +### 关键技术点 + +1. **Mel-Spectrogram 作为图像**： + - 将音频转换为 Mel-spectrogram + - 使用图像分类模型（ResNet, EfficientNet） + - 修改第一层接受单通道输入 + +2. **LWLRAP 指标**： + - Label-Weighted Label-Ranking Average Precision + - 需要优化预测的排序 + - 类别权重不平衡 + +3. **数据增强**： + - SpecAugment（时间/频率遮罩） + - Mixup + - 背景噪声 + +4. **模型集成**： + - 多架构集成 + - 不同 checkpoint + - 加权平均 + +5. **后处理**： + - 时间平滑 + - 阈值优化 + - 最小持续时间过滤 + +--- + +## AMP®-Parkinson's Disease Progression Prediction 2023 + +**注意**：此比赛主要使用蛋白质/多肽测量数据，属于**表格数据时序回归**任务，非传统的一维信号处理（如音频、EEG 等）。 + +**竞赛背景：** +- **主办方**：AMP (Accelerating Medicines Partnership) +- **目标**：预测帕金森病患者的 MDS-UPDRS 评分变化（时序回归） +- **应用场景**：帕金森病进展监测，药物效果评估 +- **数据集规模**： + - 患者数量：约 1,000+ 患者 + - 蛋白质/多肽测量：数百种蛋白质特征 + - 时间点：多个月份的访视数据 + - 访视记录：蛋白丰度数据 + 蛋白肽数据 +- **评估指标**：SMAPE (Symmetric Mean Absolute Percentage Error) +- **最终排名**： + - 1st Place: Connecting Dotts + - 2nd Place: No Luck All Skill + - 3rd Place: Hajime Tamura + - 总参赛队伍：约 2,500+ 支 + +### 前排方案详细技术分析 + +#### 1st Place - Feature Engineering + Gradient Boosting (Connecting Dotts) + +核心技巧： +- **Protein/Peptide Feature Engineering**：蛋白质/多肽特征工程 +- **Gradient Boosting Models**：梯度提升模型 +- **Ensemble**：多模型集成 +- **Cross-Validation**：交叉验证 +- **Clincal Knowledge Integration**：临床知识整合 + +实现细节： +- **特征工程**： + - 蛋白质丰度统计特征 + - 时间变化特征 + - 蛋白质-蛋白质交互特征 + - 临床协变量整合 +- **模型选择**： + - XGBoost/LightGBM + - CatBoost + - 多个模型集成 +- **训练策略**： + - 5-fold 交叉验证 + - 特征选择 + - 超参数优化 + +#### 2nd Place - Strong Feature Engineering (No Luck All Skill) + +核心技巧： +- **Advanced Feature Engineering**：高级特征工程 +- **Protein Network Features**：蛋白质网络特征 +- **Time-Series Features**：时序特征 +- **Model Ensemble**：模型集成 + +实现细节： +- **特征类型**： + - 蛋白质丰度基线 + - 时间变化趋势 + - 蛋白质-蛋白质相关性 + - 临床协变量 + +#### 3rd Place - Robust Modeling Approach (Hajime Tamura) + +核心技巧： +- **Robust Feature Selection**：稳健特征选择 +- **Gradient Boosting**：梯度提升 +- **Ensemble Strategy**：集成策略 + +实现细节： +- **特征选择**： + - 基于重要性的特征选择 + - 多重共线性处理 +- **模型**： + - XGBoost/LightGBM + - 简单平均集成 + +### 关键技术点 + +1. **蛋白质数据特征**： + - 蛋白质丰度（protein abundance） + - 肽段数据（peptide data） + - 时间序列变化 + - 临床协变量 + +2. **特征工程**： + - 基线特征 + - 时间变化特征 + - 交互特征 + - 统计特征 + +3. **模型选择**： + - Gradient Boosting (XGBoost, LightGBM, CatBoost) + - 集成多个模型 + +4. **评估指标**： + - SMAPE (Symmetric MAPE) + - 需要处理零值和异常值 + +5. **验证策略**： + - 按患者划分的交叉验证 + - 时间序列分割 + - 防止数据泄露 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-plus-2025.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-plus-2025.md new file mode 100644 index 0000000..b25b5b1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/birdclef-plus-2025.md @@ -0,0 +1,2312 @@ +# BirdCLEF\+ 2025 +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### Mel-Spectrogram 特征提取（BirdCLEF+ 2025） + +基于前排方案，统一的 mel-spectrogram 提取流程： + +```python +import torch +import torchaudio +import torch.nn as nn +import numpy as np + +class MelSpectrogramExtractor: + """统一的 Mel-Spectrogram 提取器""" + + def __init__( + self, + sample_rate: int = 32000, + n_mels: int = 128, + n_fft: int = 2048, + hop_length: int = 512, + fmin: float = 0.0, + fmax: float = 16000.0, + power: float = 2.0, + normalize: bool = True, + ): + self.sample_rate = sample_rate + self.n_mels = n_mels + self.n_fft = n_fft + self.hop_length = hop_length + self.fmin = fmin + self.fmax = fmax + + # 使用 torchaudio 的 MelSpectrogram + self.mel_transform = torchaudio.transforms.MelSpectrogram( + sample_rate=sample_rate, + n_fft=n_fft, + hop_length=hop_length, + n_mels=n_mels, + f_min=fmin, + f_max=fmax, + power=power, + normalized=normalize, + ) + + def extract(self, waveform: torch.Tensor) -> torch.Tensor: + """ + 提取 mel-spectrogram + + Args: + waveform: (num_samples,) 或 (batch, num_samples) + + Returns: + mel_spec: (n_mels, time) 或 (batch, n_mels, time) + """ + if waveform.dim() == 1: + waveform = waveform.unsqueeze(0) + + mel_spec = self.mel_transform(waveform) + + # 转换为对数尺度 + mel_spec = torch.log(mel_spec + 1e-9) + + return mel_spec + + def extract_fixed_length( + self, waveform: torch.Tensor, target_length: int + ) -> torch.Tensor: + """ + 提取固定长度的 mel-spectrogram（用于 5 秒音频） + + Args: + waveform: (num_samples,) + target_length: 目标时间维度 + + Returns: + mel_spec: (n_mels, target_length) + """ + mel_spec = self.extract(waveform).squeeze(0) + + # 调整到固定长度 + if mel_spec.shape[1] < target_length: + # 填充 + pad_length = target_length - mel_spec.shape[1] + mel_spec = nn.functional.pad(mel_spec, (0, pad_length)) + else: + # 裁剪（从中心） + start = (mel_spec.shape[1] - target_length) // 2 + mel_spec = mel_spec[:, start:start + target_length] + + return mel_spec + + +# 常用配置（前排方案） +CONFIGS = { + "config_128": { # tf_efficientnet 系列 + "n_mels": 128, + "n_fft": 2048, + "hop_length": 512, + "fmin": 0.0, + "fmax": 16000.0, + }, + "config_96": { # 轻量级模型 + "n_mels": 96, + "n_fft": 2048, + "hop_length": 512, + "fmin": 0.0, + "fmax": 16000.0, + }, + "config_256": { # 高分辨率 + "n_mels": 256, + "n_fft": 4096, + "hop_length": 1024, + "fmin": 0.0, + "fmax": 16000.0, + }, +} + +# 使用示例 +extractor = MelSpectrogramExtractor(**CONFIGS["config_128"]) +waveform, sr = torchaudio.load("audio.wav") +mel_spec = extractor.extract_fixed_length(waveform.squeeze(0), target_length=313) # 5秒 -> 313帧 +``` + +### 伪标签生成（BirdCLEF+ 2025） + +```python +import torch +import torch.nn as nn +import numpy as np +from pathlib import Path + +class PseudoLabelGenerator: + """伪标签生成器 - 基于前排方案""" + + def __init__( + self, + model: nn.Module, + threshold: float = 0.4, + use_segmentwise: bool = True, + power_transform: float = 1.0, + ): + """ + Args: + model: 训练好的模型 + threshold: 置信度阈值（前排方案使用 0.3-0.5） + use_segmentwise: 是否使用 segmentwise_logit（更细粒度） + power_transform: 幂次变换参数（1st Place 使用） + """ + self.model = model + self.model.eval() + self.threshold = threshold + self.use_segmentwise = use_segmentwise + self.power_transform = power_transform + + @torch.no_grad() + def generate_pseudo_labels( + self, + audio_path: str, + segment_duration: int = 5, + overlap: float = 0.5, + ) -> list[dict]: + """ + 生成伪标签 + + Returns: + List of {"start": float, "end": float, "labels": np.ndarray} + """ + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + + # 分段处理 + samples_per_segment = int(segment_duration * sr) + hop_length = int(samples_per_segment * (1 - overlap)) + + pseudo_labels = [] + + for start_idx in range(0, len(waveform) - samples_per_segment, hop_length): + end_idx = start_idx + samples_per_segment + segment = waveform[:, start_idx:end_idx] + + # 提取特征 + mel_spec = self.extract_mel(segment) + + # 模型预测 + if self.use_segmentwise: + # segmentwise_logit: 更细粒度的预测 + logits = self.model(mel_spec, return_segmentwise=True) + # 时间维度平均 + logits = logits.mean(dim=1) # (batch, num_classes) + else: + logits = self.model(mel_spec) + + # Sigmoid 激活 + probs = torch.sigmoid(logits).squeeze(0).cpu().numpy() + + # 幂次变换（1st Place 创新） + if self.power_transform != 1.0: + probs = np.power(probs, self.power_transform) + + # 高低阈值筛选（10th Place 方法） + mask = self._apply_threshold(probs) + + if mask.sum() > 0: + pseudo_labels.append({ + "start": start_idx / sr, + "end": end_idx / sr, + "labels": probs, + "mask": mask, + }) + + return pseudo_labels + + def _apply_threshold(self, probs: np.ndarray) -> np.ndarray: + """应用高低阈值筛选""" + # 高阈值：正样本 + high_threshold = 0.7 + # 低阈值：负样本 + low_threshold = 0.3 + + mask = np.zeros_like(probs, dtype=bool) + mask[probs >= high_threshold] = True # 高置信度正样本 + mask[probs <= low_threshold] = True # 低置信度负样本 + + return mask + + def extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram（简化版本）""" + # 实际使用中应该与训练时的提取器一致 + pass + + +# 使用示例（前排方案风格） +generator = PseudoLabelGenerator( + model=model, + threshold=0.4, + use_segmentwise=True, # 6th Place 关键 + power_transform=1.5, # 1st Place 幂次变换 +) + +pseudo_labels = generator.generate_pseudo_labels("train_soundscape_01.wav") +``` + +### MixUp 数据增强（BirdCLEF+ 2025） + +```python +import torch +import torch.nn as nn +import numpy as np + +class AudioMixUp: + """音频 MixUp 增强 - 前排方案风格""" + + def __init__( + self, + alpha: float = 0.5, + mixup_type: str = "hard", # "hard" 或 "soft" + probability: float = 0.5, + ): + """ + Args: + alpha: Beta 分布参数 + mixup_type: + - "soft": 标准混合标签（MixUp） + - "hard": 硬混合标签（8th Place 创新） + probability: 应用 MixUp 的概率 + """ + self.alpha = alpha + self.mixup_type = mixup_type + self.probability = probability + + def __call__( + self, + batch: dict, + ) -> dict: + """ + 应用 MixUp + + Args: + batch: {"mel": (B, C, H, W), "labels": (B, num_classes)} + + Returns: + Mixed batch + """ + if torch.rand(1).item() > self.probability: + return batch + + mel = batch["mel"] + labels = batch["labels"] + + batch_size = mel.size(0) + + # 生成混合权重 + lam = np.random.beta(self.alpha, self.alpha) + + # 随机排列 + index = torch.randperm(batch_size) + + # 混合特征 + mixed_mel = lam * mel + (1 - lam) * mel[index] + + # 混合标签 + if self.mixup_type == "soft": + # 标准 MixUp: 软标签混合 + mixed_labels = lam * labels + (1 - lam) * labels[index] + elif self.mixup_type == "hard": + # 硬 MixUp (8th Place): 混合标签的最大值 + mixed_labels = torch.maximum(labels, labels[index]) + else: + raise ValueError(f"Unknown mixup_type: {self.mixup_type}") + + return { + "mel": mixed_mel, + "labels": mixed_labels, + "lam": lam, # 可能用于损失调整 + } + + +# Sumix 增强（13th Place 使用） +class Sumix: + """Sumix: 原始信号上的 MixUp""" + + def __init__(self, alpha: float = 0.5, probability: float = 1.0): + self.alpha = alpha + self.probability = probability + + def __call__( + self, + waveform: torch.Tensor, + labels: torch.Tensor, + ) -> tuple[torch.Tensor, torch.Tensor]: + """ + 在原始波形上应用 Sumix + + Args: + waveform: (batch, num_samples) + labels: (batch, num_classes) + + Returns: + Mixed waveform and labels + """ + if torch.rand(1).item() > self.probability: + return waveform, labels + + batch_size = waveform.size(0) + lam = np.random.beta(self.alpha, self.alpha) + index = torch.randperm(batch_size) + + # 混合波形 + mixed_waveform = lam * waveform + (1 - lam) * waveform[index] + + # 混合标签（最大值） + mixed_labels = torch.maximum(labels, labels[index]) + + return mixed_waveform, mixed_labels + + +# 使用示例 +mixup = AudioMixUp(alpha=0.5, mixup_type="hard", probability=0.5) +sumix = Sumix(alpha=0.5, probability=1.0) + +# 训练循环中 +for batch in dataloader: + # Sumix 在原始波形 + waveform, labels = sumix(batch["waveform"], batch["labels"]) + + # 提取 mel-spectrogram + mel = extract_mel(waveform) + + # MixUp 在 mel-spectrogram + batch = mixup({"mel": mel, "labels": labels}) +``` + +### Soft AUC Loss（BirdCLEF+ 2025 - 4th Place） + +支持软标签的 AUC 损失函数： + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SoftAUCLoss(nn.Module): + """ + Soft AUC Loss - 4th Place 创新 + + 支持 soft labels，适用于知识蒸馏和半监督学习 + """ + + def __init__(self, reduction: str = "mean"): + super().__init__() + self.reduction = reduction + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) - 原始 logits + targets: (batch, num_classes) - 软标签 [0, 1] + + Returns: + AUC loss + """ + # Sigmoid 激活 + probs = torch.sigmoid(predictions) + + # 计算 AUC loss + # 对每个类别独立计算 + num_classes = predictions.size(1) + losses = [] + + for c in range(num_classes): + # 当前类别的预测和目标 + prob_c = probs[:, c] + target_c = targets[:, c] + + # 按目标值排序（软标签） + sorted_indices = torch.argsort(target_c, descending=True) + + # 计算正负样本的得分差异 + # 对于软标签，我们需要加权处理 + positive_scores = prob_c[sorted_indices[:len(sorted_indices)//2]] + negative_scores = prob_c[sorted_indices[len(sorted_indices)//2:]] + + # AUC 近似：正样本得分应该高于负样本 + # 使用 sigmoid 差异 + diff = positive_scores.unsqueeze(1) - negative_scores.unsqueeze(0) + loss_c = torch.sigmoid(-diff).mean() + + losses.append(loss_c) + + losses = torch.stack(losses) + + if self.reduction == "mean": + return losses.mean() + elif self.reduction == "sum": + return losses.sum() + else: + return losses + + +# 改进的 AUC Loss（更稳定） +class ImprovedAUCLoss(nn.Module): + """ + 改进的 AUC Loss - 更稳定且支持软标签 + """ + + def __init__(self, margin: float = 1.0): + super().__init__() + self.margin = margin + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) + targets: (batch, num_classes) - 软标签 + """ + probs = torch.sigmoid(predictions) + num_classes = predictions.size(1) + + losses = [] + for c in range(num_classes): + prob_c = probs[:, c] + target_c = targets[:, c] + + # 计算成对损失 + # 对于每个样本对 (i, j): + # 如果 target_i > target_j，则希望 prob_i > prob_j + n = prob_c.size(0) + if n < 2: + continue + + # 创建样本对矩阵 + target_diff = target_c.unsqueeze(1) - target_c.unsqueeze(0) + prob_diff = prob_c.unsqueeze(1) - prob_c.unsqueeze(0) + + # 只考虑 target_i > target_j 的对 + mask = target_diff > 0 + + if mask.sum() > 0: + # Hinge loss: max(0, margin - (prob_i - prob_j)) + loss_c = F.relu(self.margin - prob_diff)[mask].mean() + losses.append(loss_c) + + if len(losses) == 0: + return torch.tensor(0.0, device=predictions.device) + + return torch.stack(losses).mean() + + +# 使用示例 +criterion = SoftAUCLoss(reduction="mean") + +# 训练循环 +for batch in dataloader: + predictions = model(batch["mel"]) + + # 支持软标签 + loss = criterion(predictions, batch["labels"]) + + loss.backward() + optimizer.step() +``` + +### 滑动窗口推理（BirdCLEF+ 2025 - 1st Place） + +```python +import torch +import torch.nn as nn +from scipy.ndimage import gaussian_filter1d + +class SlidingWindowInference: + """ + 滑动窗口推理 - 1st Place 创新 + + 使用帧预测的平均值，而不是仅使用中心窗口的最大值 + """ + + def __init__( + self, + model: nn.Module, + window_size: int = 5, # 秒 + hop_size: int = 5, # 秒（步长） + sample_rate: int = 32000, + smoothing_sigma: float = 1.0, + ): + self.model = model + self.model.eval() + self.window_size = window_size + self.hop_size = hop_size + self.sample_rate = sample_rate + self.smoothing_sigma = smoothing_sigma + + @torch.no_grad() + def predict( + self, + audio_path: str, + ) -> dict[str, float]: + """ + 对整个音频进行预测，返回 5 秒窗口的预测 + + Returns: + Dict of {row_id: {species_id: probability}} + """ + # 加载音频 + waveform, sr = torchaudio.load(audio_path) + + # 计算窗口参数 + samples_per_window = int(self.window_size * sr) + samples_per_hop = int(self.hop_size * sr) + + # 存储所有帧预测 + all_frame_predictions = [] + + # 滑动窗口 + window_id = 0 + for start_idx in range(0, len(waveform) - samples_per_window, samples_per_hop): + end_idx = start_idx + samples_per_window + window = waveform[:, start_idx:end_idx] + + # 提取特征 + mel_spec = self.extract_mel(window) + + # 模型预测 + frame_output = self.model(mel_spec) + + # 如果是 SED 模型，可能有 clipwise 和 segmentwise 输出 + if isinstance(frame_output, dict): + frame_pred = frame_output["clipwise_output"] + else: + frame_pred = frame_output + + all_frame_predictions.append(frame_pred.cpu().numpy()) + + window_id += 1 + + # 转换为 numpy array + all_frame_predictions = np.array(all_frame_predictions) # (num_windows, num_classes) + + # 1st Place 创新: 相邻窗口帧预测平均 + # 这是一种 1D 滑动窗口分割，类似于大图像的 2D 滑动窗口分割 + smoothed_predictions = self._smooth_predictions(all_frame_predictions) + + # 生成最终预测 + predictions = {} + for window_id in range(len(smoothed_predictions)): + row_id = f"soundscape_{window_id}_{self.window_size}" + predictions[row_id] = { + f"species_{i}": float(prob) + for i, prob in enumerate(smoothed_predictions[window_id]) + } + + return predictions + + def _smooth_predictions( + self, + predictions: np.ndarray, + ) -> np.ndarray: + """ + 平滑预测 - 使用高斯滤波和时间平均 + + Args: + predictions: (num_windows, num_classes) + + Returns: + Smoothed predictions + """ + # 1. 时间维度高斯平滑 + if self.smoothing_sigma > 0: + smoothed = gaussian_filter1d( + predictions, + sigma=self.smoothing_sigma, + axis=0, + mode="nearest", + ) + else: + smoothed = predictions + + # 2. 相邻窗口平均（1st Place 创新） + # 使用相邻 3 个窗口的平均 + kernel_size = 3 + if len(smoothed) >= kernel_size: + # Padding + padded = np.pad( + smoothed, + ((kernel_size // 2, kernel_size // 2), (0, 0)), + mode="edge", + ) + + # 一维卷积平均 + kernel = np.ones(kernel_size) / kernel_size + averaged = np.zeros_like(smoothed) + + for c in range(smoothed.shape[1]): + averaged[:, c] = np.convolve( + padded[:, c], + kernel, + mode="valid", + ) + + return averaged + else: + return smoothed + + def extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram""" + # 实际使用中应该与训练时的提取器一致 + pass + + +# 使用示例 +inference = SlidingWindowInference( + model=model, + window_size=5, + hop_size=5, + smoothing_sigma=1.0, +) + +predictions = inference.predict("test_soundscape_01.wav") + +# 后处理（可选） +# - Delta shift: 调整低置信度类别的概率 +# - Min-max 缩放 +# - 频率范围调整 +``` + +### SED 模型架构（BirdCLEF+ 2025 标准） + +前排方案广泛使用的 SED (Sound Event Detection) 模型架构： + +```python +import torch +import torch.nn as nn +import timm + +class SEDModel(nn.Module): + """ + Sound Event Detection 模型 + + 参考 BirdCLEF 2023 2nd Place 和 BirdCLEF+ 2025 前排方案 + """ + + def __init__( + self, + backbone: str = "tf_efficientnetv2_s.in21k", + num_classes: int = 206, + in_channels: int = 1, + pretrained: bool = True, + ): + super().__init__() + + self.num_classes = num_classes + + # 使用 timm 的 EfficientNet 作为 backbone + self.backbone = timm.create_model( + backbone, + pretrained=pretrained, + in_chans=in_channels, + num_classes=0, # 移除分类头 + ) + + # 获取 backbone 输出特征维度 + self.features_dim = self.backbone.num_features + + # 自定义注意力块 (6th Place AttBlockV2) + self.att_block = AttBlockV2( + self.features_dim, + num_classes, + activation="sigmoid", + ) + + def forward(self, x, return_segmentwise=False): + """ + Args: + x: (batch, in_channels, n_mels, time) + return_segmentwise: 是否返回 segmentwise_logit + + Returns: + 如果 return_segmentwise=False: + clipwise_output: (batch, num_classes) + 如果 return_segmentwise=True: + dict with: + clipwise_output: (batch, num_classes) + segmentwise_output: (batch, num_classes, time_frames) + """ + # Backbone 特征提取 + features = self.backbone(x) # (batch, features_dim, time_frames) + + # 全局池化 + pooled_features = features.mean(dim=[2]) # (batch, features_dim) + + # 片级预测 + clipwise_output = self.att_block(pooled_features) # (batch, num_classes) + + if not return_segmentwise: + return clipwise_output + + # 帧级预测（用于伪标签生成） + segmentwise_output = self.att_block(features) # (batch, num_classes, time_frames) + + return { + "clipwise_output": clipwise_output, + "segmentwise_output": segmentwise_output, + } + + +class AttBlockV2(nn.Module): + """ + 自定义注意力块 - 6th Place 创新 + + 使用 softmax 和 tanh 进行归一化，结合非线性变换 + """ + + def __init__( + self, + in_features: int, + out_features: int, + activation: str = "sigmoid", + ): + super().__init__() + + self.activation = activation + self.att = nn.Conv1d(in_features, out_features, kernel_size=1) + self.cla = nn.Conv1d(in_features, out_features, kernel_size=1) + + # 初始化权重（6th Place 关键） + self.apply(self._init_weights) + + def _init_weights(self, m): + if isinstance(m, nn.Conv1d): + nn.init.kaiming_normal_(m.weight, mode="fan_out", nonlinearity="relu") + if m.bias is not None: + nn.init.constant_(m.bias, 0) + + def forward(self, x): + """ + Args: + x: (batch, in_features, time_frames) 或 (batch, in_features) + + Returns: + output: (batch, out_features) 或 (batch, out_features, time_frames) + """ + if x.dim() == 2: + # 全局池化特征 + x = x.unsqueeze(-1) # (batch, in_features, 1) + + # 注意力权重 + att = self.att(x) + att = torch.softmax(att, dim=1) # 时间维度归一化 + + # 分类特征 + cla = self.cla(x) + + # 加权求和 + output = torch.clamp(torch.clamp((cla * att).sum(dim=-1), min=1e-7, max=1-1e-7), min=1e-7) + + # 激活函数 + if self.activation == "sigmoid": + output = torch.sigmoid(output) + elif self.activation == "none": + pass + else: + raise ValueError(f"Unknown activation: {self.activation}") + + return output.squeeze(-1) if output.size(-1) == 1 else output + + +# 常用 backbone 配置（前排方案） +BACKBONES = { + "tf_efficientnetv2_s.in21k": { + "features_dim": 1280, + "description": "2nd Place 使用，平衡性能和速度", + }, + "tf_efficientnetv2_b3.in21k": { + "features_dim": 1536, + "description": "6th Place 使用，更强性能", + }, + "tf_efficientnetv2_m.in21k": { + "features_dim": 2048, + "description": "14th Place 使用，更高精度", + }, + "eca_nfnet_l0": { + "features_dim": 2304, + "description": "2nd Place 使用，增加多样性", + }, +} + +# 使用示例 +model = SEDModel( + backbone="tf_efficientnetv2_s.in21k", + num_classes=206, + in_channels=1, + pretrained=True, +) + +# 训练时：片级预测 +clipwise_output = model(mel_spec) +loss = criterion(clipwise_output, labels) + +# 伪标签生成时：帧级预测 +output = model(mel_spec, return_segmentwise=True) +segmentwise_logits = output["segmentwise_output"] # (batch, 206, time_frames) +segmentwise_probs = torch.sigmoid(segmentwise_logits) +# 时间维度平均得到更稳定的伪标签 +avg_segmentwise_probs = segmentwise_probs.mean(dim=-1) # (batch, 206) +``` + +### 前排方案详细技术分析 + +#### 2nd Place - Xeno-Canto 预训练详细流程 + +**作者**: Volodymyr Vialactea +**核心创新**: 使用外部数据预训练 + 5秒音频片段训练 + +**完整流程：** + +```python +import torch +import torchaudio +import pandas as pd +from pathlib import Path + +class XenoCantoPretraining: + """ + 2nd Place 方案：Xeno-Canto 预训练流程 + + 关键点： + 1. 下载额外的 Xeno-Canto 数据 + 2. 数据清洗和预处理 + 3. 预训练 + 4. 在主数据集上微调 + """ + + def __init__( + self, + species_list: list, + target_sample_rate: int = 32000, + segment_duration: int = 5, + ): + self.species_list = species_list + self.target_sample_rate = target_sample_rate + self.segment_duration = segment_duration + + def download_xeno_canto_data(self, output_dir: str = "data/xeno_canto"): + """ + 步骤 1: 从 Xeno-Canto 下载数据 + + 注意事项： + - 过滤掉当年比赛中的物种（避免数据泄漏） + - 只下载高质量录音（评分 ≥ 3.0） + - 限制每个物种的下载量（避免数据不平衡） + """ + # 使用 xeno-canto-api 或手动下载 + # 这里提供框架代码 + + xc_species = [s for s in self.species_list if self._should_download(s)] + + for species in xc_species: + # 调用 Xeno-Canto API + # 下载音频文件 + # 保存到 output_dir/species_name/ + pass + + def _should_download(self, species: str) -> bool: + """检查物种是否应该下载（避免数据泄漏）""" + # 过滤比赛数据集中的物种 + competition_species = set(self._get_competition_species()) + return species not in competition_species + + def preprocess_xeno_canto(self, audio_dir: str): + """ + 步骤 2: 数据清洗和预处理 + + 2nd Place 的关键步骤： + 1. 去除人声（如果可能） + 2. 统一采样率到 32kHz + 3. 音频归一化 + 4. 质量检查（SNR、时长等） + """ + audio_files = list(Path(audio_dir).rglob("*.mp3")) + + cleaned_data = [] + + for audio_file in audio_files: + # 加载音频 + waveform, sr = torchaudio.load(audio_file) + + # 重采样到 32kHz + if sr != self.target_sample_rate: + resampler = torchaudio.transforms.Resample(sr, self.target_sample_rate) + waveform = resampler(waveform) + + # 质量检查 + if self._check_quality(waveform): + # 提取 5 秒片段 + segments = self._extract_segments(waveform) + + for segment in segments: + cleaned_data.append({ + "file_path": str(audio_file), + "species": audio_file.parent.name, + "waveform": segment, + }) + + return cleaned_data + + def _check_quality(self, waveform: torch.Tensor) -> bool: + """质量检查""" + # 检查 1: 时长至少 5 秒 + if waveform.shape[1] < self.target_sample_rate * self.segment_duration: + return False + + # 检查 2: SNR（信噪比） + # snr = self._calculate_snr(waveform) + # if snr < 10: # 最低 10dB + # return False + + # 检查 3: 削波检测 + if torch.abs(waveform).max() > 0.99: + return False + + return True + + def _extract_segments(self, waveform: torch.Tensor) -> list: + """ + 提取 5 秒音频片段 + + 2nd Place 使用了多种采样策略： + 1. 随机采样 + 2. 基于能量的采样（RMS） + 3. 重叠采样 + """ + segment_samples = self.segment_duration * self.target_sample_rate + + if waveform.shape[1] <= segment_samples: + # 填充到 5 秒 + padding = segment_samples - waveform.shape[1] + waveform = torch.nn.functional.pad(waveform, (0, padding)) + return [waveform] + + # 方法 1: 随机采样 + # 2nd Place 尝试了多种方法，最终发现随机采样效果最好 + + # 方法 2: 基于能量的采样（RMS） + # 计算每个 5 秒窗口的 RMS 能量 + # 选择能量最高的窗口 + + # 方法 3: 重叠采样 + # 滑动窗口，hop_size = 2.5 秒 + + # 这里实现随机采样 + max_start = waveform.shape[1] - segment_samples + start_idx = torch.randint(0, max_start, (1,)).item() + + segment = waveform[:, start_idx:start_idx + segment_samples] + return [segment] + + def pretrain(self, xc_data, model, save_path: str = "checkpoints/pretrained.pth"): + """ + 步骤 3: 预训练 + + 2nd Place 的预训练策略： + - 使用 Xeno-Canto 数据训练 + - BCE Loss + - SpecAugment 增强 + - 50-100 epochs + """ + # 创建 dataloader + train_loader = self._create_dataloader(xc_data) + + # 优化器 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3) + + # 学习率调度器 + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=50, eta_min=1e-6 + ) + + # 损失函数 + criterion = nn.BCEWithLogitsLoss() + + # 训练循环 + model.train() + for epoch in range(50): # 50 epochs + for batch in train_loader: + mel_spec = self._extract_mel(batch["waveform"]) + labels = batch["labels"] + + # 前向传播 + logits = model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + scheduler.step() + + print(f"Epoch {epoch+1}/50, Loss: {loss.item():.4f}") + + # 保存预训练模型 + torch.save(model.state_dict(), save_path) + print(f"Pretrained model saved to {save_path}") + + def finetune(self, model, train_data, val_data, pretrained_path: str): + """ + 步骤 4: 微调 + + 2nd Place 的微调策略： + - 加载预训练权重 + - 使用更小的学习率 + - 选择最佳 checkpoint（不是最后一个） + - 关键：AUC 从 0.83-0.84 跳升至 0.86-0.87 + """ + # 加载预训练权重 + model.load_state_dict(torch.load(pretrained_path)) + + # 优化器（更小的学习率） + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-4) + + # 学习率调度器 + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=30, eta_min=1e-7 + ) + + # 损失函数 + criterion = nn.BCEWithLogitsLoss() + + best_val_score = 0 + best_epoch = 0 + + # 微调循环 + model.train() + for epoch in range(30): # 30 epochs + # 训练 + for batch in train_data: + mel_spec = self._extract_mel(batch["waveform"]) + labels = batch["labels"] + + logits = model(mel_spec) + loss = criterion(logits, labels) + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + # 验证 + val_score = self._validate(model, val_data) + + print(f"Epoch {epoch+1}/30, Val AUC: {val_score:.4f}") + + # 保存最佳模型 + if val_score > best_val_score: + best_val_score = val_score + best_epoch = epoch + torch.save(model.state_dict(), f"checkpoints/best_finetuned_epoch{epoch}.pth") + + scheduler.step() + + print(f"Best epoch: {best_epoch}, Best Val AUC: {best_val_score:.4f}") + + def _extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram（应该与训练时一致）""" + # 实现 mel-spectrogram 提取 + pass + + def _create_dataloader(self, data): + """创建 dataloader""" + pass + + def _validate(self, model, val_data): + """验证""" + pass + + def _get_competition_species(self) -> list: + """获取竞赛数据集中的物种（避免数据泄漏）""" + pass + + def _calculate_snr(self, waveform: torch.Tensor) -> float: + """计算 SNR""" + pass + + +# 2nd Place 关键技术总结 +""" +关键发现（来自 2nd Place writeup）： + +1. **预训练效果显著**： + - 无预训练：AUC 0.83-0.84 + - 有预训练：AUC 0.86-0.87 + - 提升：+0.02-0.03 AUC + +2. **Checkpoint 选择很重要**： + - 不是最后一个 epoch 最好 + - 需要验证集选择最佳 checkpoint + - 通常在 epoch 10-20 之间 + +3. **采样策略**： + - 随机采样效果最好 + - 基于能量的采样没有明显优势 + - 5 秒片段是最佳长度 + +4. **数据增强**： + - SpecAugment 必须保留 + - RandomFiltering 有效 + - 即使关闭略微提高 CV，但保留确保 LB 稳定性 +""" +``` + +#### 5th Place - Self-Distillation 详细实现 + +**作者**: Noir +**核心创新**: 三阶段自蒸馏 + Silero VAD 数据清洗 + +**完整流程：** + +```python +import torch +import torch.nn as nn +import numpy as np + +class SelfDistillationTrainer: + """ + 5th Place 方案：Self-Distillation 三阶段训练 + + 核心思想： + 1. 使用 Silero VAD 去除人声 + 2. 三阶段自蒸馏训练 + 3. 迭代丰富次要标签 + """ + + def __init__( + self, + model: nn.Module, + num_classes: int = 206, + ): + self.model = model + self.num_classes = num_classes + + def stage1_initial_training(self, train_loader, val_loader, epochs=30): + """ + 阶段 1: 初始训练 + + 使用清洗后的训练音频（train_audio）进行初始训练 + """ + print("=== Stage 1: Initial Training ===") + + optimizer = torch.optim.AdamW(self.model.parameters(), lr=1e-3) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-6 + ) + criterion = nn.BCEWithLogitsLoss() + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + for batch in train_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + # 前向传播 + logits = self.model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证 + val_loss = self._validate(self.model, val_loader, criterion) + + # 学习率更新 + scheduler.step() + + print(f"Epoch {epoch+1}/{epochs}, Train Loss: {train_loss/len(train_loader):.4f}, " + f"Val Loss: {val_loss:.4f}") + + # 保存最佳模型 + if val_loss < best_val_loss: + best_val_loss = val_loss + torch.save(self.model.state_dict(), "checkpoints/stage1_best.pth") + + print(f"Stage 1 complete. Best Val Loss: {best_val_loss:.4f}") + + # 加载最佳模型用于下一阶段 + self.model.load_state_dict(torch.load("checkpoints/stage1_best.pth")) + + def stage2_self_distillation_train_audio( + self, + train_loader, + epochs=20, + temperature=3.0, + alpha=0.7, + ): + """ + 阶段 2: 使用 train_audio 的自蒸馏 + + 使用 stage 1 模型的预测作为软标签进行蒸馏 + """ + print("=== Stage 2: Self-Distillation on train_audio ===") + + # stage 1 模型作为教师 + teacher_model = type(self.model)( + backbone=self.model.backbone, + num_classes=self.num_classes, + ) + teacher_model.load_state_dict(torch.load("checkpoints/stage1_best.pth")) + teacher_model.eval() + + # 学生模型（可以重置权重或继续训练） + # 5th Place 选择继续训练 + + optimizer = torch.optim.AdamW(self.model.parameters(), lr=5e-4) # 更小的学习率 + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-7 + ) + + # 蒸馏损失 + distillation_criterion = nn.KLDivLoss(reduction="batchmean") + bce_criterion = nn.BCEWithLogitsLoss() + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + for batch in train_loader: + mel_spec = batch['mel_spec'] + hard_labels = batch['labels'] + + with torch.no_grad(): + # 教师模型预测（软标签） + teacher_logits = teacher_model(mel_spec) + teacher_probs = torch.sigmoid(teacher_logits / temperature) + + # 学生模型预测 + student_logits = self.model(mel_spec) + student_log_probs = torch.log_softmax(student_logits / temperature, dim=-1) + + # 蒸馏损失 + distill_loss = distillation_criterion(student_log_probs, teacher_probs) + + # 硬标签损失 + bce_loss = bce_criterion(student_logits, hard_labels) + + # 组合损失 + loss = alpha * (temperature ** 2) * distill_loss + (1 - alpha) * bce_loss + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证 + val_loss = self._validate(self.model, train_loader, bce_criterion) # 用训练集验证 + + scheduler.step() + + print(f"Epoch {epoch+1}/{epochs}, Train Loss: {train_loss/len(train_loader):.4f}, " + f"Val Loss: {val_loss:.4f}") + + if val_loss < best_val_loss: + best_val_loss = val_loss + torch.save(self.model.state_dict(), "checkpoints/stage2_best.pth") + + print(f"Stage 2 complete. Best Val Loss: {best_val_loss:.4f}") + + self.model.load_state_dict(torch.load("checkpoints/stage2_best.pth")) + + def stage3_self_distillation_soundscape( + self, + train_audio_loader, + soundscape_files, + epochs=20, + temperature=3.0, + alpha=0.5, # 更重视伪标签 + ): + """ + 阶段 3: 结合 train_audio 和 train_soundscapes 的自蒸馏 + + 关键创新：丰富次要标签 + - 许多音频包含未标注的鸟叫声 + - 通过自蒸馏发现这些次要标签 + """ + print("=== Stage 3: Self-Distillation with soundscape ===") + + # stage 2 模型作为教师 + teacher_model = type(self.model)( + backbone=self.model.backbone, + num_classes=self.num_classes, + ) + teacher_model.load_state_dict(torch.load("checkpoints/stage2_best.pth")) + teacher_model.eval() + + optimizer = torch.optim.AdamW(self.model.parameters(), lr=3e-4) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-7 + ) + + distillation_criterion = nn.KLDivLoss(reduction="batchmean") + bce_criterion = nn.BCEWithLogitsLoss() + + # 生成 soundscape 的伪标签 + soundscape_pseudo_labels = self._generate_pseudo_labels( + teacher_model, soundscape_files + ) + + # 合并 train_audio 和 soundscape 数据 + # 50% train_audio + 50% soundscape + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + # 训练 train_audio（带硬标签） + for batch in train_audio_loader: + if np.random.rand() > 0.5: + continue # 50% 概率使用 train_audio + + mel_spec = batch['mel_spec'] + hard_labels = batch['labels'] + + with torch.no_grad(): + teacher_logits = teacher_model(mel_spec) + teacher_probs = torch.sigmoid(teacher_logits / temperature) + + student_logits = self.model(mel_spec) + student_log_probs = torch.log_softmax(student_logits / temperature, dim=-1) + + distill_loss = distillation_criterion(student_log_probs, teacher_probs) + bce_loss = bce_criterion(student_logits, hard_labels) + loss = alpha * (temperature ** 2) * distill_loss + (1 - alpha) * bce_loss + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 训练 soundscape（伪标签） + for batch in soundscape_pseudo_labels: + if np.random.rand() <= 0.5: + continue # 50% 概率使用 soundscape + + mel_spec = batch['mel_spec'] + pseudo_labels = batch['labels'] # 软标签 + + with torch.no_grad(): + teacher_logits = teacher_model(mel_spec) + teacher_probs = torch.sigmoid(teacher_logits / temperature) + + student_logits = self.model(mel_spec) + student_log_probs = torch.log_softmax(student_logits / temperature, dim=-1) + + # 只使用蒸馏损失（没有硬标签） + distill_loss = distillation_criterion(student_log_probs, teacher_probs) + + optimizer.zero_grad() + distill_loss.backward() + optimizer.step() + + train_loss += distill_loss.item() + + scheduler.step() + + print(f"Epoch {epoch+1}/{epochs}, Train Loss: {train_loss:.4f}") + + # 保存检查点 + if epoch % 5 == 0: + torch.save(self.model.state_dict(), f"checkpoints/stage3_epoch{epoch}.pth") + + print("Stage 3 complete") + + def _generate_pseudo_labels( + self, + model: nn.Module, + audio_files: list, + ) -> list: + """ + 生成 soundscape 的伪标签 + + 关键：丰富次要标签 + - 使用帧级预测（segmentwise） + - 时间维度平均 + """ + model.eval() + pseudo_labels = [] + + with torch.no_grad(): + for audio_file in audio_files: + # 加载音频 + waveform, sr = torchaudio.load(audio_file) + + # 分段处理（5秒窗口） + segments = self._split_audio(waveform, sr) + + for segment in segments: + mel_spec = self._extract_mel(segment) + + # 获取帧级预测 + output = model(mel_spec, return_segmentwise=True) + segmentwise_logits = output["segmentwise_output"] # (1, 206, time) + segmentwise_probs = torch.sigmoid(segmentwise_logits) + + # 时间维度平均（关键：丰富次要标签） + avg_probs = segmentwise_probs.mean(dim=-1).squeeze(0) # (206,) + + pseudo_labels.append({ + "mel_spec": mel_spec, + "labels": avg_probs, + }) + + return pseudo_labels + + def _split_audio(self, waveform: torch.Tensor, sr: int) -> list: + """分段处理音频""" + segment_samples = 5 * sr + segments = [] + + for i in range(0, waveform.shape[1], segment_samples): + segment = waveform[:, i:i+segment_samples] + if segment.shape[1] == segment_samples: + segments.append(segment) + else: + # 填充 + padding = segment_samples - segment.shape[1] + segment = torch.nn.functional.pad(segment, (0, padding)) + segments.append(segment) + + return segments + + def _extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram""" + pass + + def _validate(self, model, val_loader, criterion): + """验证""" + model.eval() + total_loss = 0 + + with torch.no_grad(): + for batch in val_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + logits = model(mel_spec) + loss = criterion(logits, labels) + total_loss += loss.item() + + return total_loss / len(val_loader) + + +class SileroVADDataCleaner: + """ + Silero VAD 数据清洗 + + 5th Place 使用 Silero VAD 检测并去除人声片段 + """ + + def __init__(self): + # 加载 Silero VAD 模型 + self.model, utils = torch.hub.load( + repo_or_dir='snakers4/silero-vad', + model='silero_vad', + force_reload=False, + onnx=False + ) + self.model.eval() + + def clean_audio(self, audio_path: str, output_path: str): + """ + 去除包含人声的音频片段 + + Returns: + 清洗后的音频（去除人声部分） + """ + waveform, sr = torchaudio.load(audio_path) + + # 转换为单声道 + if waveform.shape[0] > 1: + waveform = waveform.mean(dim=0, keepdim=True) + + # 重采样到 16kHz（Silero VAD 要求） + if sr != 16000: + resampler = torchaudio.transforms.Resample(sr, 16000) + waveform = resampler(waveform) + sr = 16000 + + # VAD 检测 + speech_chunks = self._detect_speech(waveform, sr) + + # 如果检测到人声，去除这些片段 + if speech_chunks: + cleaned_waveform = self._remove_speech_chunks(waveform, speech_chunks) + else: + cleaned_waveform = waveform + + # 保存清洗后的音频 + torchaudio.save(output_path, cleaned_waveform, sr) + + return cleaned_waveform + + def _detect_speech(self, waveform: torch.Tensor, sr: int) -> list: + """ + 检测人声片段 + + Returns: + List of (start_ms, end_ms) tuples + """ + # 获取语音概率 + speech_probs = [] + window_size = 512 # 32ms at 16kHz + + for i in range(0, waveform.shape[1], window_size): + chunk = waveform[:, i:i+window_size] + if chunk.shape[1] < window_size: + continue + + with torch.no_grad(): + speech_prob = self.model(chunk, sr).item() + speech_probs.append(speech_prob) + + # 阈值检测（人声概率 > 0.5） + speech_chunks = [] + in_speech = False + start_idx = 0 + + for i, prob in enumerate(speech_probs): + if prob > 0.5 and not in_speech: + in_speech = True + start_idx = i * window_size + elif prob <= 0.5 and in_speech: + in_speech = False + end_idx = i * window_size + speech_chunks.append((start_idx, end_idx)) + + # 转换为毫秒 + speech_chunks_ms = [(s * 1000 / sr, e * 1000 / sr) for s, e in speech_chunks] + + return speech_chunks_ms + + def _remove_speech_chunks( + self, + waveform: torch.Tensor, + speech_chunks: list, + ) -> torch.Tensor: + """去除人声片段""" + sr = 16000 + + # 将时间转换为样本索引 + speech_ranges = [(int(s * sr / 1000), int(e * sr / 1000)) for s, e in speech_chunks] + + # 创建掩码（True 表示保留） + mask = torch.ones(waveform.shape[1], dtype=torch.bool) + + for start, end in speech_ranges: + mask[start:end] = False + + # 应用掩码 + cleaned_waveform = waveform[:, mask] + + return cleaned_waveform + + +# 5th Place 关键技术总结 +""" +关键发现（来自 5th Place writeup）： + +1. **Silero VAD 有效**： + - 去除人声减少误检 + - 清洗后数据质量提升 + +2. **三阶段自蒸馏**： + - Stage 1: 基础训练 + - Stage 2: train_audio 自蒸馏 + - Stage 3: 加入 soundscape 伪标签 + - 每个阶段都带来提升 + +3. **丰富次要标签**： + - 许多音频包含未标注的鸟叫声 + - 使用帧级预测和时间平均 + - 迭代训练发现更多标签 + +4. **数据平衡重要**： + - 样本 <20 的类别复制到 20 + - 样本 <30 的类别手动筛选 + - 使用前 30/60 秒数据 +""" +``` + +#### 1st Place - Multi-Iterative Noisy Student 详细流程 + +**作者**: Nikita Babych +**核心创新**: 多迭代 Noisy Student + MixUp + 幂次变换 + +**完整流程：** + +```python +import torch +import torch.nn as nn +import numpy as np + +class MultiIterativeNoisyStudent: + """ + 1st Place 方案：多迭代 Noisy Student 自训练 + + 核心创新： + 1. 多迭代自训练，每次使用 MixUp + 2. 伪标签幂次变换减少噪声 + 3. 滑动窗口推理，帧预测平均 + """ + + def __init__( + self, + model: nn.Module, + num_classes: int = 206, + num_iterations: int = 3, + ): + self.model = model + self.num_classes = num_classes + self.num_iterations = num_iterations + + # 1st Place 关键参数 + self.mixup_alpha = 0.5 + self.power_transform = 1.5 # 幂次变换参数（减少伪标签噪声） + + def train_iteration( + self, + train_audio_loader, + train_soundscape_files, + iteration: int, + epochs=30, + ): + """ + 执行一次 Noisy Student 迭代 + + Args: + iteration: 当前迭代编号（0, 1, 2, ...） + """ + print(f"=== Noisy Student Iteration {iteration + 1} ===") + + # 准备数据 + # 50% train_audio + 50% 伪标签 soundscape + if iteration == 0: + # 第一次迭代：只使用 train_audio + train_loader = train_audio_loader + else: + # 后续迭代：混合 train_audio 和伪标签 + train_loader = self._prepare_mixed_data( + train_audio_loader, + train_soundscape_files, + iteration, + ) + + # 优化器 + optimizer = torch.optim.AdamW(self.model.parameters(), lr=1e-3) + scheduler = torch.optim.lr_scheduler.CosineAnnealingLR( + optimizer, T_max=epochs, eta_min=1e-6 + ) + criterion = nn.BCEWithLogitsLoss() + + best_val_loss = float('inf') + + for epoch in range(epochs): + self.model.train() + train_loss = 0 + + for batch in train_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + # MixUp 数据增强（1st Place 关键） + if np.random.rand() < 0.5: # 50% 概率应用 MixUp + mel_spec, labels = self._apply_mixup(mel_spec, labels) + + # 前向传播 + logits = self.model(mel_spec) + loss = criterion(logits, labels) + + # 反向传播 + optimizer.zero_grad() + loss.backward() + optimizer.step() + + train_loss += loss.item() + + # 验证（使用训练集的一个子集） + val_loss = self._quick_validate(train_audio_loader, criterion) + + scheduler.step() + + print(f"Iteration {iteration+1}, Epoch {epoch+1}/{epochs}, " + f"Train Loss: {train_loss/len(train_loader):.4f}, " + f"Val Loss: {val_loss:.4f}") + + if val_loss < best_val_loss: + best_val_loss = val_loss + torch.save(self.model.state_dict(), + f"checkpoints/noisy_student_iter{iteration}_best.pth") + + print(f"Iteration {iteration+1} complete. Best Val Loss: {best_val_loss:.4f}") + + def _prepare_mixed_data( + self, + train_audio_loader, + soundscape_files, + iteration: int, + ): + """ + 准备混合数据：train_audio + 伪标签 soundscape + + 关键：幂次变换减少伪标签噪声（1st Place 创新） + """ + # 生成伪标签 + pseudo_labels = self._generate_pseudo_labels_power_transform( + soundscape_files, + self.power_transform, + ) + + # 创建混合 dataloader + mixed_data = [] + + # 添加 train_audio + for batch in train_audio_loader: + mixed_data.append(batch) + + # 添加伪标签 soundscape + for item in pseudo_labels: + mixed_data.append(item) + + # 打乱顺序 + np.random.shuffle(mixed_data) + + return mixed_data + + def _generate_pseudo_labels_power_transform( + self, + audio_files: list, + power: float = 1.5, + ) -> list: + """ + 生成伪标签并应用幂次变换 + + 1st Place 关键创新：幂次变换减少噪声 + + 原理： + - 直接对概率进行温度缩放会提高噪声的概率 + - 通过幂次变换，防止噪声的放大，并保留重要的标签信号 + """ + self.model.eval() + pseudo_labels = [] + + with torch.no_grad(): + for audio_file in audio_files: + waveform, sr = torchaudio.load(audio_file) + + # 分段处理（5秒窗口） + segments = self._split_audio(waveform, sr) + + for segment in segments: + mel_spec = self._extract_mel(segment) + + # 获取预测 + logits = self.model(mel_spec) + probs = torch.sigmoid(logits).squeeze(0).cpu().numpy() # (206,) + + # 幂次变换（1st Place 创新） + # power > 1: 压缩低概率，扩展高概率 + # power < 1: 扩展低概率，压缩高概率 + probs_transformed = np.power(probs, power) + + pseudo_labels.append({ + "mel_spec": mel_spec, + "labels": torch.tensor(probs_transformed, dtype=torch.float32), + }) + + return pseudo_labels + + def _apply_mixup( + self, + mel_spec: torch.Tensor, + labels: torch.Tensor, + ) -> tuple: + """ + MixUp 数据增强 + + 1st Place 关键：使用固定混合权重 0.5 + """ + batch_size = mel_spec.size(0) + + # 生成混合权重 + lam = np.random.beta(self.mixup_alpha, self.mixup_alpha) + # 1st Place 发现固定权重 0.5 效果更好 + # lam = 0.5 + + # 随机排列 + index = torch.randperm(batch_size) + + # 混合特征 + mixed_mel = lam * mel_spec + (1 - lam) * mel_spec[index] + + # 混合标签（取最大值） + mixed_labels = torch.maximum(labels, labels[index]) + + return mixed_mel, mixed_labels + + def _split_audio(self, waveform: torch.Tensor, sr: int) -> list: + """分段处理音频""" + segment_samples = 5 * sr + segments = [] + + for i in range(0, waveform.shape[1], segment_samples): + segment = waveform[:, i:i+segment_samples] + if segment.shape[1] == segment_samples: + segments.append(segment) + else: + padding = segment_samples - segment.shape[1] + segment = torch.nn.functional.pad(segment, (0, padding)) + segments.append(segment) + + return segments + + def _extract_mel(self, waveform: torch.Tensor) -> torch.Tensor: + """提取 mel-spectrogram""" + pass + + def _quick_validate(self, val_loader, criterion): + """快速验证""" + self.model.eval() + total_loss = 0 + count = 0 + + with torch.no_grad(): + for i, batch in enumerate(val_loader): + if i >= 10: # 只验证前 10 个 batch + break + + mel_spec = batch['mel_spec'] + labels = batch['labels'] + + logits = self.model(mel_spec) + loss = criterion(logits, labels) + total_loss += loss.item() + count += 1 + + return total_loss / max(count, 1) + + +# 1st Place 关键技术总结 +""" +关键发现（来自 1st Place writeup）： + +1. **多迭代 Noisy Student 有效**： + - 每次迭代都带来提升 + - 3 次迭代是最优的 + - 更多迭代可能导致噪声累积 + +2. **幂次变换是关键**： + - 直接使用伪标签：性能提升有限 + - 幂次变换（power=1.5）：显著提升 + - 防止噪声放大，保留信号 + +3. **MixUp 策略**： + - 固定权重 0.5 比随机权重更稳定 + - 迫使模型学习更鲁棒的特征 + - 减少过拟合 + +4. **滑动窗口推理**： + - 使用帧预测的平均值 + - 避免丢弃有价值的预测数据 + - 类似图像的 2D 滑动窗口分割 +""" + + +# 1st Place 完整训练流程示例 +def train_noisy_student_full_pipeline(): + """ + 完整的 Noisy Student 训练流程 + """ + # 初始化 + model = SEDModel(num_classes=206) + trainer = MultiIterativeNoisyStudent(model, num_iterations=3) + + # 准备数据 + train_audio_loader = ... # 训练音频 loader + soundscape_files = ... # soundscape 文件列表 + + # 迭代 0: 只使用 train_audio + print("=== Iteration 0: Training on train_audio only ===") + trainer.train_iteration(train_audio_loader, soundscape_files, iteration=0, epochs=30) + + # 迭代 1: 加入伪标签 soundscape + print("=== Iteration 1: Adding pseudo-labeled soundscape ===") + trainer.train_iteration(train_audio_loader, soundscape_files, iteration=1, epochs=30) + + # 迭代 2: 使用新的伪标签 + print("=== Iteration 2: Refreshing pseudo labels ===") + trainer.train_iteration(train_audio_loader, soundscape_files, iteration=2, epochs=30) + + # 最终集成：使用不同迭代的模型 + model_iter0 = SEDModel(num_classes=206) + model_iter0.load_state_dict(torch.load("checkpoints/noisy_student_iter0_best.pth")) + + model_iter1 = SEDModel(num_classes=206) + model_iter1.load_state_dict(torch.load("checkpoints/noisy_student_iter1_best.pth")) + + model_iter2 = SEDModel(num_classes=206) + model_iter2.load_state_dict(torch.load("checkpoints/noisy_student_iter2_best.pth")) + + # 集成预测 + def ensemble_predict(mel_spec): + pred0 = torch.sigmoid(model_iter0(mel_spec)) + pred1 = torch.sigmoid(model_iter1(mel_spec)) + pred2 = torch.sigmoid(model_iter2(mel_spec)) + + # 简单平均 + ensemble_pred = (pred0 + pred1 + pred2) / 3 + return ensemble_pred + + return ensemble_predict +``` + +#### 4th Place - Soft AUC Loss 详细分析 + +**作者**: dylan.liu +**核心创新**: 支持软标签的 AUC 损失函数 + +**问题背景：** +- 标准 AUC 损失函数不支持软标签（适用于知识蒸馏和半监督学习） +- 4th Place 通过自定义 soft AUC loss 解决这个问题 +- 效果：从 11 名跃升至 4 名（LB 从 0.850 → 0.901） + +```python +import torch +import torch.nn as nn +import torch.nn.functional as F + +class SoftAUCLoss_v4(nn.Module): + """ + 4th Place Soft AUC Loss 实现 + + 参考：4th Place writeup + 效果：LB 从 0.850 → 0.901（显著提升） + + 核心思想： + 1. 支持 soft labels（适用于知识蒸馏和半监督学习） + 2. 通过正负样本对的排序关系优化 AUC + 3. 减少 overfitting + """ + + def __init__( + self, + margin: float = 1.0, + reduction: str = "mean", + ): + super().__init__() + self.margin = margin + self.reduction = reduction + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) - 原始 logits + targets: (batch, num_classes) - 软标签 [0, 1] + + Returns: + AUC loss + """ + probs = torch.sigmoid(predictions) + num_classes = predictions.size(1) + losses = [] + + for c in range(num_classes): + prob_c = probs[:, c] # (batch,) + target_c = targets[:, c] # (batch,) + + # 计算所有样本对的差异 + # 对于软标签，我们需要加权处理 + + # 创建样本对矩阵 + # target_diff > 0 表示 target_i > target_j + target_diff = target_c.unsqueeze(1) - target_c.unsqueeze(0) # (batch, batch) + prob_diff = prob_c.unsqueeze(1) - prob_c.unsqueeze(0) # (batch, batch) + + # 只考虑 target_i > target_j 的对 + # 即正样本（高 target）应该有更高的预测概率 + mask = target_diff > 0 + + if mask.sum() > 0: + # Hinge loss: max(0, margin - (prob_i - prob_j)) + # 理想情况：prob_i > prob_j（正样本预测高于负样本） + # margin - (prob_i - prob_j) 应该 <= 0 + # 如果 > 0，说明违反了排序关系 + + loss_c = F.relu(self.margin - prob_diff)[mask].mean() + + # 4th Place 发现加权版本更有效 + # 使用 target_diff 作为权重 + # weight = target_diff[mask] + # weighted_loss = F.relu(self.margin - prob_diff)[mask] * weight + # loss_c = weighted_loss.sum() / weight.sum() + + losses.append(loss_c) + + if len(losses) == 0: + return torch.tensor(0.0, device=predictions.device, requires_grad=True) + + losses = torch.stack(losses) + + if self.reduction == "mean": + return losses.mean() + elif self.reduction == "sum": + return losses.sum() + else: + return losses + + +class SoftAUCLoss_Advanced(nn.Module): + """ + 改进的 Soft AUC Loss + + 结合 4th Place 的发现和其他优化： + 1. 温度缩放 + 2. 自适应 margin + 3. 类别加权 + """ + + def __init__( + self, + margin: float = 1.0, + temperature: float = 1.0, + use_class_weighting: bool = True, + ): + super().__init__() + self.margin = margin + self.temperature = temperature + self.use_class_weighting = use_class_weighting + + def forward( + self, + predictions: torch.Tensor, + targets: torch.Tensor, + ) -> torch.Tensor: + """ + Args: + predictions: (batch, num_classes) + targets: (batch, num_classes) - 软标签 + """ + # 温度缩放 + probs = torch.sigmoid(predictions / self.temperature) + num_classes = predictions.size(1) + + losses = [] + + for c in range(num_classes): + prob_c = probs[:, c] + target_c = targets[:, c] + + # 样本对矩阵 + target_diff = target_c.unsqueeze(1) - target_c.unsqueeze(0) + prob_diff = prob_c.unsqueeze(1) - prob_c.unsqueeze(0) + + # mask: target_i > target_j + mask = target_diff > 0 + + if mask.sum() > 0: + # Hinge loss + base_loss = F.relu(self.margin - prob_diff)[mask] + + # 可选：使用 target_diff 作为权重 + # 这给予高 target 差异的样本对更高权重 + weights = target_diff[mask] + weighted_loss = base_loss * weights + + loss_c = weighted_loss.sum() / weights.sum() + + # 可选：类别权重（处理长尾分布） + if self.use_class_weighting: + # 稀有类别更高权重 + class_weight = self._get_class_weight(c, num_classes) + loss_c = loss_c * class_weight + + losses.append(loss_c) + + if len(losses) == 0: + return torch.tensor(0.0, device=predictions.device, requires_grad=True) + + return torch.stack(losses).mean() + + def _get_class_weight(self, class_idx: int, num_classes: int) -> float: + """ + 计算类别权重（处理长尾分布） + + 简单版本：可以基于样本频率 + """ + # 这里使用简单策略：可以替换为实际的类别频率 + #稀有类获得更高权重 + return 1.0 # 可以自定义 + + +# 4th Place 关键发现总结 +""" +关键发现（来自 4th Place writeup）： + +1. **Soft AUC Loss 显著提升性能**： + - LB 从 0.850 → 0.901 + - 排名从 11 名 → 4 名 + - +0.05 AUC 提升是巨大的 + +2. **为什么 Soft AUC Loss 有效**： + - 标准 AUC loss 只支持硬标签（0 或 1） + - Soft AUC Loss 支持软标签（0 到 1 之间） + - 适用于知识蒸馏和半监督学习 + - 减少 overfitting + +3. **实现细节**： + - 使用样本对的排序关系 + - Hinge loss: max(0, margin - (prob_i - prob_j)) + - 只考虑 target_i > target_j 的对 + - margin 通常设为 1.0 + +4. **适用场景**： + - 半监督学习（伪标签） + - 知识蒸馏（软标签） + - 长尾分布（稀有类别） + - 标签噪声（软标签更鲁棒） + +5. **与其他损失函数对比**： + - BCE Loss: 简单但易过拟合 + - Focal Loss: 处理类别不平衡，但不优化 AUC + - Soft AUC Loss: 直接优化 AUC，支持软标签 +""" + + +# 使用示例 +def train_with_soft_auc_loss(): + """使用 Soft AUC Loss 训练""" + + model = SEDModel(num_classes=206) + + # 标准训练：BCE Loss + criterion_bce = nn.BCEWithLogitsLoss() + + # 半监督训练：Soft AUC Loss + criterion_soft_auc = SoftAUCLoss_v4(margin=1.0) + + # 优化器 + optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3) + + # 训练循环 + for epoch in range(30): + model.train() + + for batch in train_loader: + mel_spec = batch['mel_spec'] + labels = batch['labels'] # 可能是软标签 + + # 选择损失函数 + if batch.get('is_pseudo', False): # 伪标签数据 + # 使用 Soft AUC Loss + loss = criterion_soft_auc(model(mel_spec), labels) + else: # 真实标签 + # 可以使用 BCE Loss 或 Soft AUC Loss + loss = criterion_bce(model(mel_spec), labels) + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + print(f"Epoch {epoch+1}/30, Loss: {loss.item():.4f}") +``` + +--- + +## Best Practices + +### 时间序列分类竞赛策略 + +| 策略 | 何时使用 | 说明 | +|------|---------|------| +| **CWT over STFT** | 非平稳信号 | CWT提供更好的时间-频率局部化 | +| **Entmax over Softmax** | 标签稀疏时 | Entmax产生更稀疏的输出 | +| **非负线性回归集成** | 多模型集成时 | 即使过拟合也能保持相关性 | +| **2-Stage Training** | 标签质量不均时 | Stage1全数据，Stage2高质量样本 | +| **Group K-Fold** | 有重复样本时 | 确保同一patient/EEG不分散 | +| **仅用高质量样本** | 评估时 | 使用votes≥10的样本建立验证集 | + +### 时频分析方法对比 + +| 方法 | 优点 | 缺点 | 适用场景 | +|------|------|------|---------| +| **STFT** | 简单，易实现 | 固定窗口，时频分辨率权衡 | 平稳信号 | +| **CWT** | 多分辨率分析，捕捉局部特征 | 需要选择小波函数 | 非平稳信号，EEG | +| **Superlet** | 最高时频分辨率 | 计算成本高 | 复杂脑波模式 | + +### 频率配置经验 + +| 配置 | 范围 | 说明 | +|------|------|------| +| **标准CWT** | 0.5-20 Hz | Kaggle提供的spectrogram默认范围 | +| **扩展CWT** | 0.5-40 Hz | 更好的结果 (suguuuuu) | +| **带通滤波** | 0.5-40 Hz | 高频噪声增加'other'投票 | + +### 数据增强策略 + +**时间序列 (1D):** +- 随机时间偏移 (±5秒) +- 随机带通滤波 (不同频率范围) +- 通道翻转 (水平/垂直) +- 幅值缩放 + +**Scalogram/Spectrogram (2D):** +- XYMasking (随机遮挡) +- Mixup +- 时间方向翻转 + +### Backbone选择 + +**时间序列 (1D):** +- 1D CNN + GRU +- Transformer (Time-series Transformer) +- LSTM/GRU + +**Scalogram (2D):** +- SwinV2: swinv2_tiny_window16 (最佳: CV 0.2229) +- MaxVIT: maxvit_base_tf_512 +- ConvNeXt: convnextv2_atto + +### 标签处理技巧 + +| 技巧 | 效果 | +|------|------| +| 标签平滑 (加0.02 offset) | 使低投票数标签获得更强正则化 | +| 仅用votes≥10评估 | CV/LB相关性接近1:1 | +| 投票数归一化 | 多专家投票转换为分布 | + +### 常见误区 + +| 误区 | 正确做法 | +|------|---------| +| STFT不够好就放弃时频分析 | 尝试CWT或Superlet | +| Softmax输出不够稀疏 | 使用Entmax | +| 集成权重手动调参 | 使用非负线性回归 | +| 用全部样本验证 | 仅用高质量样本 (votes≥10) | +| 忽略Group K-Fold | 防止同一patient的数据泄露 | + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/detect-behavior-sensor-2025.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/detect-behavior-sensor-2025.md new file mode 100644 index 0000000..174a84f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/detect-behavior-sensor-2025.md @@ -0,0 +1,1740 @@ +# CMI - Detect Behavior with Sensor Data (2025) +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### CMI - Detect Behavior with Sensor Data (2025) + +**竞赛背景：** +- **主办方**：Child Mind Institute +- **目标**：从腕部可穿戴设备传感器数据中识别身体聚焦重复行为 +- **应用场景**：BFRBs（Body-Focused Repetitive Behaviors）监测，如拔头发、抠皮肤等行为识别 +- **社会意义**：自动化行为识别，助力心理健康监测和早期干预 + +**任务描述：** +从多模态传感器数据中分类 18 种手势行为： +- **BFRB 类行为**（目标类）：拔头发、捏皮肤、挠皮肤等 +- **非 BFRB 类行为**（非目标类）：喝水、挥手、调整眼镜等 + +**数据集规模：** +- 总样本数：8,151 个序列（sequence_id） +- 参试者：81 人（subject） +- 数据点：每个序列最多 700 步（sequence_counter） +- 特征：341 列（IMU + THM + TOF） + +**数据特点：** +1. **多模态传感器**： + - **IMU**（惯性测量单元）：加速度、旋转四元数 + - **THM**（热电堆）：5 个温度传感器 + - **TOF**（飞行时间）：5 个距离传感器（8×8 像素阵列） +2. **数据缺失严重**：TOF 约 60% 缺失（标记为 -1），THM 约 3-4% 缺失 +3. **三阶段结构**：Transition（过渡）→ Pause（停顿）→ Gesture（动作） +4. **个体差异大**：不同 subject 的行为模式差异明显 + +**评估指标：** +- **多类别分类准确率**：18 个手势类别的分类准确率 +- **F1-Score**：综合考虑精确率和召回率 + +**竞赛约束：** +- 隐藏测试集约 50% 序列仅包含 IMU 数据（THM/TOF 完全缺失） +- 需要处理传感器数据缺失的情况 +- 个体约束：每个 subject 的特定手势在每个 orientation 下只出现一次 + +**最终排名：** +- 1st Place: Devin | Ogurtsov | zyz - Private LB: **待补充** +- 2nd Place: cucutzik - Private LB: ~ +- 3rd Place: Team RIST - Private LB: ~ +- 总参赛队伍：2,657 支 + +**技术趋势：** +- **多模态融合**：IMU + THM + TOF 特征融合 +- **缺失数据处理**：针对 TOF 缺失的特殊处理策略 +- **个体约束利用**：利用 subject × gesture × orientation 的唯一性约束 +- **数据增强**：mixup, cutmix, timeshift, rotation +- **后处理优化**：匈牙利算法全局最优标签分配 + +**关键创新：** +- **TOF 图像化处理** (1st Place)：2×2 正方形 9 个区域平均 +- **四元数 6D 表现** (2nd Place)：避免四元数不连续性 +- **阶段感知 Attention** (2nd Place)：分阶段（Transition/Pause/Gesture）应用不同 attention +- **时序转图像** (7th Place)：时序数据转换为图像，使用 2D-CNN +- **双向 Mamba** (13th Place)：长期时序依赖建模 + +**后续影响：** +- 推动多模态传感器数据融合技术发展 +- 为可穿戴设备行为识别提供参考方案 +- 缺失数据处理策略被后续竞赛借鉴 + +#### 前排方案详细技术分析 + +**1st Place - Devin | Ogurtsov | zyz** + +核心技巧： +- **TOF 图像化处理**：2×2 正方形 9 个区域平均，将 8×8 像素阵列降维 +- **多模态特征融合**：IMU + THM + TOF 三种传感器特征融合 +- **匈牙利算法后处理**：全局最优标签分配，利用 subject×gesture×orientation 唯一性约束 +- **缺失数据处理**：针对 TOF 60% 缺失（标记为 -1）的特殊处理 +- **阶段感知 Attention**：分阶段（Transition/Pause/Gesture）应用不同 attention 机制 + +实现细节： +- IMU：加速度、旋转四元数（6D 连续表示避免不连续性） +- THM：5 个温度传感器，线性插值填充缺失值 +- TOF：8×8 像素阵列 → 2×2 正方形 9 区域平均 +- 模型：Transformer + Attention，处理可变长度序列 +- 后处理：匈牙利算法确保每个 subject×gesture×orientation 只有一个预测 + +**2nd Place - cucutzik** + +核心技巧： +- **四元数 6D 表现**：使用 (x, y, z, qx, qy, qz) 六维连续表示，避免四元数不连续性 +- **阶段感知 Attention**：不同阶段（Transition/Pause/Gesture）使用不同的 attention 权重 +- **多模态 late fusion**：分别处理各模态，在决策层融合 +- **数据增强**：mixup, cutmix, timeshift, rotation + +实现细节： +- 四元数转换：quaternion → six-dimensional continuous representation +- 阶段识别：单独的分类器识别 Transition/Pause/Gesture 阶段 +- 模型架构：GRU + Attention，处理多模态时序数据 +- 融合策略：late fusion，加权组合各模态预测 + +**3rd Place - Team RIST** + +核心技巧： +- **时序转图像**：将时序数据转换为图像，使用 2D-CNN 处理 +- **特征工程**：提取统计特征、频域特征、时域特征 +- **集成学习**：多模型集成，提高鲁棒性 +- **数据增强**：时间平移、旋转、缩放等增强技术 + +实现细节： +- 时序转图像：将时间序列转换为 2D 图像（如 Gramian Angular Field） +- 特征提取：统计特征（均值、方差、峰度等）+ 频域特征（FFT） +- 模型：ResNet-2D 处理转换后的图像 +- 集成：5-10 个不同配置的模型集成 + +**4th Place - Rotter (Rotem D**) + +核心技巧： +- **Transformer 架构**：自注意力机制捕获长期时序依赖 +- **多传感器融合**：早期融合所有传感器数据 +- **位置编码**：学习序列中时间步的位置信息 +- **层归一化**：稳定训练过程 + +实现细节： +- Transformer：4 层，4 头注意力，d_model=128 +- 多传感器融合：IMU + THM + TOF 拼接为输入 +- 位置编码：可学习的位置嵌入 +- 最终 Private LB：待补充 + +**5th Place - SOK (Soichi** + +核心技巧： +- **双向 Mamba**：新型状态空间模型，处理长序列 +- **TOF 缺失掩码**：学习识别和忽略 TOF 缺失 +- **传感器选择**：动态选择最相关的传感器 +- **时序池化**：全局平均池化聚合时序特征 + +实现细节： +- 双向 Mamba：2 层，状态维度 64 +- TOF 掩码：-1 值掩码处理，模型学习忽略 +- 传感器选择：注意力机制学习传感器权重 +- 最终 Private LB：待补充 + +**6th Place - Alina (Alina G** + +核心技巧： +- **残差网络**：ResNet 架构处理时序数据 +- **特征融合**：早期和中期融合结合 +- **数据增强**：时间扭曲、幅值缩放、噪声注入 +- **学习率调度**：余弦退火学习率调度 + +实现细节： +- ResNet：18 层残差块处理 1D 时序 +- 特征融合：早期拼接 + 中期特征交互 +- 学习率调度：初始 lr=0.001，最小 lr=1e-5 +- 最终 Private LB：待补充 + +**7th Place - Team BBB** + +核心技巧： +- **LSTM + CNN 混合**：CNN 提取局部特征，LSTM 建模时序 +- **注意力机制**：关注重要时间步 +- **类别加权**：处理类别不平衡 +- **集成策略**：多个不同随机种子的模型 + +实现细节： +- CNN：3 层 1D 卷积提取局部特征 +- LSTM：2 层处理 CNN 输出序列 +- 类别加权：加权交叉熵，权重与频率成反比 +- 最终 Private LB：待补充 + +**8th Place - MambaSeries** + +核心技巧： +- **Mamba 架构**：状态空间模型处理长序列 +- **选择性扫描机制**：动态选择保留信息 +- **多尺度特征**：不同时间尺度的特征提取 +- **梯度裁剪**：防止梯度爆炸 + +实现细节： +- Mamba：3 层，状态维度 96 +- 选择性扫描：学习参数控制信息流 +- 多尺度：并行处理不同窗口大小 +- 梯度裁剪：max_norm=1.0 +- 最终 Private LB：待补充 + +**9th Place - SensorFusion** + +核心技巧： +- **晚期融合**：各传感器单独建模，决策层融合 +- **专家模型**：针对每个传感器类型训练专门模型 +- **元学习**：学习如何最优组合专家预测 +- **不确定性估计**：量化预测不确定性 + +实现细节： +- 晚期融合：加权平均各传感器模型预测 +- 专家模型：IMU-专家、THM-专家、TOF-专家 +- 元学习：小网络学习最优权重 +- 不确定性：MC Dropout 估计预测方差 +- 最终 Private LB：待补充 + +**10th Place - TSLearn** + +核心技巧： +- **时序专用库**：tslearn 库的时序分类方法 +- **动态时间规整**：DTW 距离度量时序相似性 +- **k-NN 方法**：基于 DTW 的 k-近邻分类 +- **集成多种 DTW 变体**：FastDTW, LB_Keogh, SAK 等变体 + +实现细节： +- tslearn：使用 DTW k-NN 和时序特征 +- k-NN：k=5，DTW 距离度量 +- DTW 变体：FastDTW（近似）、SAK（下界） +- 集成：投票组合多个 DTW 变体 +- 最终 Private LB：待补充 + +**13th Place - Bidirectional Mamba (Reference from summary)** + +核心技巧： +- **双向 Mamba**：前向和后向 Mamba 结合 +- **长期时序依赖**：处理最长 700 步序列 +- **高效计算**：Mamba 的线性复杂度优于 RNN +- **双向上下文**：同时利用过去和未来信息 + +实现细节： +- 双向 Mamba：前向 + 后向 Mamba 拼接输出 +- 状态维度：128，线性投影到输出类别 +- 效率：O(n) 复杂度，n 为序列长度 + +--- + +### CMI - Detect Behavior with Sensor Data (2025) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/cmi-detect-behavior-with-sensor-data) +**Category:** Time Series (多模态行为识别) +**Summary:** 多模态传感器数据行为识别竞赛。数据包含 IMU、THM、TOF 三种传感器，需分类 18 种手势行为（BFRB vs 非BFRB）。**1st Place: Devin | Ogurtsov | zyz** (Andrey Ogurtsov, Devin, zyz)。 + +**Key Techniques:** +- **多模态融合**：IMU + THM + TOF 特征融合 +- **TOF 图像化**：2×2 正方形 9 个区域平均 +- **四元数 6D 表现**：避免四元数不连续性 +- **阶段感知 Attention**：分阶段（Transition/Pause/Gesture）应用不同 attention +- **匈牙利算法**：全局最优标签分配 +- **数据增强**：mixup, cutmix, timeshift, rotation + +**Results:** 1st place (2657 teams) + +**Resources:** +- [1st Place Solution (Kaggle)](https://www.kaggle.com/competitions/cmi-detect-behavior-with-sensor-data/writeups/cmi-1st-place-solution) +- [Japanese Summary](https://zenn.dev/ottantachinque/articles/2025-09-14_cmi-detect-behavior-with-sensor-data) +- [Chinese EDA](https://zhuanlan.zhihu.com/p/1943779452640273827) + +### TOF 图像化处理 (1st Place approach) +```python +import numpy as np + +def tof_image_2x2_pooling(tof_data): + """ + TOF 图像化处理 - 2×2 正方形 9 个区域平均 + + 将每个 8×8 的 TOF 传感器数据转换为 2×2 的特征图 + + 参数: + tof_data: shape (n_timesteps, n_tof_sensors * 64) 或 (n_timesteps, n_tof_sensors, 8, 8) + 每个 TOF 传感器有 64 个像素（8×8） + + 返回: + pooled: shape (n_timesteps, n_tof_sensors * 9) - 每个 TOF 传感器 9 个区域 + """ + n_timesteps = tof_data.shape[0] + + # 如果是 2D 形状，重塑为 (n_timesteps, n_tof_sensors, 8, 8) + if len(tof_data.shape) == 2: + n_tof_sensors = tof_data.shape[1] // 64 + tof_reshaped = tof_data.reshape(n_timesteps, n_tof_sensors, 8, 8) + else: + tof_reshaped = tof_data + + n_tof_sensors = tof_reshaped.shape[1] + pooled_features = [] + + for t in range(n_timesteps): + for sensor in range(n_tof_sensors): + sensor_data = tof_reshaped[t, sensor] # (8, 8) + + # 2×2 池化，得到 9 个区域（每个 4×4） + # 也可以直接 2×2 池化得到 4 个区域 + # 这里假设使用 2×2 池化，步长为 2 + pooled = sensor_data.reshape(4, 4).mean(axis=1).mean(axis=0) # 得到 4 个值 + + # 或者更细粒度的 3×3 网格，得到 4 个区域，再加上全局统计 + # 根据日语描述："2x2の正方形を9つ" - 9 个正方形区域 + # 可能是 3×3 网格，步长为 2，得到 4 个区域，再加上某些额外特征 + + # 这里实现一种可能的解释：滑动窗口 2×2，步长 2 + patches = [] + for i in range(0, 8, 2): + for j in range(0, 8, 2): + patch = sensor_data[i:i+2, j:j+2] + patches.append(patch.mean()) + # 如果 4×4 网格，步长 2，得到 9 个区域 (4×4 / 2×2 = 4 区域 + 1 个额外) + # 这里简化处理，使用 4 个区域均值 + 全局均值 + pooled = np.array(patches) + + pooled_features.append(pooled) + + return np.array(pooled_features) # (n_timesteps, n_tof_sensors * n_patches) +``` + +### 四元数 6D 表现 (2nd Place approach) +```python +import numpy as np + +def quaternion_to_6d(quaternion_data): + """ + 四元数转 6D 连续表示 - 避免四元数不连续性 + + 参数: + quaternion_data: shape (..., 4) - 四元数 (w, x, y, z) + + 返回: + rotation_6d: shape (..., 6) - 6D 连续旋转表示 + + 参考: "On the Continuity of Rotation Representations in Neural Networks" + """ + # 提取四元数的最后两个分量 + # 有多种 6D 表现方法，这里使用其中一种 + # 方法 1: 使用旋转矩阵的前两列 + # 方法 2: 使用四元数的向量部分 + + w = quaternion_data[..., 0:1] + x = quaternion_data[..., 1:2] + y = quaternion_data[..., 2:3] + z = quaternion_data[..., 3:4] + + # 归一化 + norm = np.sqrt(w**2 + x**2 + y**2 + z**2) + w, x, y, z = w/norm, x/norm, y/norm, z/norm + + # 方法: 使用旋转矩阵的前两列 + # R = [w -z y z] + # [z w -x y] + # [-y x w z] + # 取前两列作为 6D 表现 + # col1 = [w, z, -y] + # col2 = [-z, w, x] + # 这里简化处理，使用更直接的 6D 表现 + + # 简化版本: 直接使用 (x, y, z) 和旋转角度/轴 + # 更好的方法: 将四元数转换为旋转矩阵，取前两列 + + # 计算 6D 表现: 取旋转矩阵的前两列 + # R[0,:] = [1 - 2(y^2 + z^2), 2(xy - wz), 2(xz + wy)] + # R[1,:] = [ 2(xy + wz), 1 - 2(x^2 + z^2), 2(yz - wx)] + + x2 = x * x + y2 = y * y + z2 = z * z + + # 旋转矩阵的第一行和第二行 + r00 = 1 - 2 * (y2 + z2) + r01 = 2 * (x * y - w * z) + r02 = 2 * (x * z + w * y) + r10 = 2 * (x * y + w * z) + r11 = 1 - 2 * (x2 + z2) + r12 = 2 * (y * z - w * x) + + # 取前两列作为 6D 表现 + rotation_6d = np.concatenate([ + r00, r01, r02, r10, r11, r12 + ], axis=-1) + + return rotation_6d + +# 使用示例 +# rot_data shape: (n_timesteps, 4) or (n_timesteps, n_samples, 4) +# rot_6d = quaternion_to_6d(rot_data) +``` + +### 阶段感知 Attention (2nd Place approach) +```python +import torch +import torch.nn as nn + +class PhaseAwareAttention(nn.Module): + """ + 阶段感知 Attention - 分阶段独立建模和加权 + + 利用 Transition/Pause/Gesture 三阶段结构 + """ + def __init__(self, d_model, n_heads=8, dropout=0.1): + super().__init__() + self.phase_embedding = nn.Embedding(3, d_model) # 3 个阶段 + + # 每个阶段独立的 Attention + self.attentions = nn.ModuleList([ + nn.MultiheadAttention(d_model, n_heads, dropout=dropout) + for _ in range(3) + ]) + self.norms = nn.ModuleList([nn.LayerNorm(d_model) for _ in range(3)]) + self.fcs = nn.ModuleList([nn.Linear(d_model, d_model) for _ in range(3)]) + + self.phase_classifier = nn.Sequential( + nn.Linear(d_model, d_model // 2), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(d_model // 2, 3) # 3 个阶段 + ) + + def forward(self, x, phase_labels=None): + """ + 参数: + x: (batch, seq_len, d_model) - 输入特征 + phase_labels: (batch, seq_len) - 阶段标签 (0=Transition, 1=Pause, 2=Gesture) + """ + batch_size, seq_len, d_model = x.shape + + # 预测阶段概率 + phase_probs = self.phase_classifier(x.mean(dim=1)) # (batch, 3) + phase_probs = torch.softmax(phase_probs, dim=-1) # (batch, 3) + + # 如果没有提供阶段标签，使用 argmax + if phase_labels is None: + phase_labels = torch.argmax(phase_probs, dim=-1) # (batch,) + + # 初始化输出 + output = torch.zeros_like(x) + + # 对每个样本应用对应的阶段 Attention + for b in range(batch_size): + phase = phase_labels[b].item() # 该样本的主要阶段 + + # 应用该阶段的 Attention + x_b = x[b:b+1] # (1, seq_len, d_model) + attn = self.attentions[phase] + norm = self.norms[phase] + fc = self.fcs[phase] + + x_b = norm(x_b) + x_b, _ = attn(x_b, x_b, x_b) + x_b = fc(x_b) + + # 用阶段概率加权 + weight = phase_probs[b, phase] + output[b:b+1] = x_b * weight + + return output, phase_probs +``` + +### 匈牙利算法全局最优标签分配 (2nd/3rd Place approach) +```python +import numpy as np +from scipy.optimize import linear_sum_assignment + +def hungarian_global_label_assignment(pred_probs, subject_ids, sequence_ids, + gesture_ids, orientation_ids): + """ + 匈牙利算法全局最优标签分配 + + 利用约束: 每个 subject × gesture × orientation 只出现一次 + + 参数: + pred_probs: (n_sequences, n_classes) - 预测概率 + subject_ids: (n_sequences,) - 每个 sequence 的 subject ID + sequence_ids: (n_sequences,) - sequence ID + gesture_ids: (n_sequences,) - 约束前的 gesture 标签 + orientation_ids: (n_sequences,) - 每个 sequence 的 orientation + + 返回: + final_labels: (n_sequences,) - 全局最优的标签分配 + """ + n_sequences = pred_probs.shape[0] + n_classes = pred_probs.shape[1] + + # 构建代价矩阵: cost[i, j] = -log(prob_i[j]) 表示将 sequence i 分配给标签 j 的代价 + cost_matrix = -np.log(pred_probs + 1e-10) + + # 构建约束矩阵: 不能违反 subject × gesture × orientation 唯一性约束 + # 这里简化处理，实际实现需要更复杂的约束 + + # 对每个 subject 单独处理 + final_labels = np.zeros(n_sequences, dtype=int) + + for subject_id in np.unique(subject_ids): + # 该 subject 的所有序列 + mask = subject_ids == subject_id + subject_seqs = np.where(mask)[0] + + if len(subject_seqs) == 0: + continue + + # 该 subject 的预测概率 + subject_probs = pred_probs[subject_seqs] # (n_subject_seqs, n_classes) + + # 使用匈牙利算法进行最优分配 + row_ind, col_ind = linear_sum_assignment(subject_probs) + + # 分配标签 + for seq_idx, label_idx in zip(row_ind, col_ind): + final_labels[subject_seqs[seq_idx]] = label_idx + + return final_labels + +# 备选方案：更简单的实现（仅针对 orientation × gesture 约束） +def simple_hungarian_assignment(pred_probs, sequence_ids, gesture_ids, orientation_ids): + """ + 简化的匈牙利算法实现 - 利用 orientation × gesture 唯一性约束 + + 参数: + pred_probs: (n_sequences, n_classes) + sequence_ids: (n_sequences,) + gesture_ids: (n_sequences,) + orientation_ids: (n_sequences,) + """ + n_sequences = pred_probs.shape[0] + n_classes = pred_probs.shape[1] + + # 构建 (orientation, gesture) 组合 + # 每个 orientation × gesture 组合只分配一次 + + final_labels = np.zeros(n_sequences, dtype=int) + + # 对每个 orientation 单独处理 + for orientation_id in np.unique(orientation_ids): + mask = orientation_ids == orientation_id + orientation_seqs = np.where(mask)[0] + + if len(orientation_seqs) == 0: + continue + + # 该 orientation 的所有序列 + orientation_probs = pred_probs[orientation_seqs] + orientation_gestures = gesture_ids[orientation_seqs] + + # 使用匈牙利算法 + row_ind, col_ind = linear_sum_assignment(orientation_probs) + + # 分配标签（考虑 gesture 约束） + # 这里需要更复杂的实现，确保每个 gesture 只分配一次 + + for seq_idx, label_idx in zip(row_ind, col_ind): + final_labels[orientation_seqs[seq_idx]] = label_idx + + return final_labels +``` + +### 相位 Mixup (2nd Place approach) +```python +import numpy as np + +def phase_aware_mixup(X, y, phase_labels, alpha=0.2, beta=0.2): + """ + 相位感知 Mixup - 按阶段分割后在同阶段内进行 Mixup + + 参数: + X: (batch, seq_len, n_features) - 输入特征 + y: (batch, n_classes) - 标签 + phase_labels: (batch, seq_len) - 阶段标签 (0=Transition, 1=Pause, 2=Gesture) + alpha: Mixup 强度 + beta: CutMix 强度 + + 返回: + mixed_X, mixed_y, lambda_a, lambda_b, phase_labels + """ + batch_size, seq_len, n_features = X.shape + + if phase_labels is None: + # 简单 Mixup + return standard_mixup(X, y, alpha) + + # 对每个样本进行相位 Mixup + mixed_X = X.copy() + mixed_y = y.copy() + lambda_as = np.zeros(batch_size) + lambda_bs = np.zeros(batch_size) + + for i in range(batch_size): + # 找到同一阶段的其他样本 + same_phase_mask = (phase_labels[i, 0] == phase_labels[:, 0]) + + if same_phase_mask.sum() == 0: + # 没有同阶段样本，跳过 + continue + + # 随机选择同阶段样本 j + same_phase_indices = np.where(same_phase_mask)[0] + j = np.random.choice(same_phase_indices) + + # Mixup + mixed_X[i] = alpha * X[i] + (1 - alpha) * X[j] + mixed_y[i] = alpha * y[i] + (1 - alpha) * y[j] + lambda_as[i] = alpha + + # CutMix（对标签） + if beta > 0: + # 简化的 CutMix 实现 + # 实际应该对特征进行 CutMix + pass + + return mixed_X, mixed_y, lambda_as, lambda_bs, phase_labels + +def standard_mixup(X, y, alpha=0.2): + """标准 Mixup""" + batch_size = X.shape[0] + + if batch_size < 2: + return X, y, np.zeros(batch_size), None, None + + mixed_X = X.copy() + mixed_y = y.copy() + lambda_as = np.random.beta(alpha, alpha, batch_size) + + for i in range(batch_size): + j = i + while j == i: + j = np.random.randint(0, batch_size) + + mixed_X[i] = lambda_as[i] * X[i] + (1 - lambda_as[i]) * X[j] + mixed_y[i] = lambda_as[i] * y[i] + (1 - lambda_as[i]) * y[j] + + return mixed_X, mixed_y, lambda_as, None, None +``` + +### 重力去除和特征工程 (1st Place approach) +```python +import numpy as np + +def remove_gravity_and_extract_features(acc_data): + """ + 去除重力影响并提取 35 个特征 + + 1st Place 的特征工程方法 + + 参数: + acc_data: shape (n_timesteps, 3) - 加速度数据 (acc_x, acc_y, acc_z) + + 返回: + features: shape (n_timesteps, 35) - 提取的特征 + """ + n_timesteps = acc_data.shape[0] + + # 1. 去除重力 + # 假设重力加速度约为 9.8 m/s² + # 计算重力方向（可以使用平均加速度估计） + gravity = np.mean(acc_data, axis=0) # 简化方法 + acc_no_gravity = acc_data - gravity + + # 2. 提取 35 个特征 + # 这里需要根据实际实现来定义这 35 个特征 + # 可能的特征类型： + # - 统计特征：均值、标准差、最大值、最小值等 + # - 频域特征：FFT 后的能量分布 + # - 时域特征：过零率、峰值数等 + # - 差分特征：一阶差分、二阶差分等 + + features = [] + + for t in range(n_timesteps): + feat = [] + + # 原始加速度（去除重力后） + feat.extend(acc_no_gravity[t]) # 3 个特征 + + # 加速度的范数 + feat.append(np.linalg.norm(acc_no_gravity[t])) # 1 个特征 + + # 加速度的绝对值 + feat.extend(np.abs(acc_no_gravity[t])) # 3 个特征 + + # 一阶差分 + if t > 0: + diff = acc_no_gravity[t] - acc_no_gravity[t-1] + feat.append(np.linalg.norm(diff)) # 1 个特征 + feat.extend(diff) # 3 个特征 + else: + feat.extend([0, 0, 0, 0]) # 4 个特征 + + # 统计特征（滑动窗口） + window = 10 + start = max(0, t - window) + end = min(n_timesteps, t + window + 1) + window_data = acc_no_gravity[start:end] + + feat.append(np.mean(window_data, axis=0)) # 3 个特征 + feat.append(np.std(window_data, axis=0)) # 3 个特征 + feat.append(np.max(window_data, axis=0) - np.min(window_data, axis=0)) # 3 个特征 + + # 频域特征（FFT） + if t >= window: + fft_data = np.fft.fft(acc_data[start:end, 0]) # 仅对 x 轴 + fft_energy = np.abs(fft_data) + feat.append(fft_energy[:5].mean()) # 前 5 个频点的能量 # 1 个特征 + else: + feat.append(0) + + features.append(feat) + + features = np.array(features) # (n_timesteps, n_features) + # 确保 n_features = 35 + if features.shape[1] < 35: + # 填充或截断到 35 个特征 + # 这里简化处理 + pass + + return features +``` + +### 时序转图像 (7th Place approach) +```python +import numpy as np + +def time_series_to_image(series_data, image_size=(224, 224)): + """ + 时序转图像 - 将时序数据转换为图像 + + 7th Place 的方法：使用 2D-CNN 处理时序数据 + + 参数: + series_data: shape (n_timesteps, n_features) - 时序数据 + image_size: 目标图像大小 (height, width) + + 返回: + images: (n_channels, height, width) - 图像数据 + """ + n_timesteps, n_features = series_data.shape + height, width = image_size + + # 方法 1: 直接重塑（如果 n_timesteps × n_features 适合） + # 如果 n_timesteps × n_features = height × width，直接重塑 + if n_timesteps * n_features == height * width: + image = series_data.reshape(height, width) + return image[np.newaxis, :, :] # (1, height, width) + + # 方法 2: 使用波形图（类似声谱图） + # 将时序数据转换为图像的灰度值 + # 可以使用 matplotlib 的 imshow 方法 + + # 简化实现：将每个特征作为一个通道 + # 如果 n_features == 3，可以直接作为 RGB 图像 + if n_features == 3: + # 归一化到 [0, 255] + normalized = (series_data - series_data.min()) / (series_data.max() - series_data.min() + 1e-10) + image = (normalized * 255).astype(np.uint8) + + # 调整大小 + # 这里可以使用 cv2.resize 或 interpolation + # 简化处理：直接采样 + if n_timesteps != height or n_features != width: + # 使用最近邻插值 + image = image.reshape(height, width, 3) + # 实际应该使用 cv2.resize + + return image.transpose(2, 0, 1) # (3, height, width) + + # 方法 3: 创建多通道图像（每个特征一个通道） + # 如果 n_features < 3，复制通道 + # 如果 n_features > 3，选择前 3 个特征或使用 PCA + + # 简化处理：只使用前 3 个特征 + if n_features >= 3: + selected_data = series_data[:, :3] + else: + selected_data = np.concatenate([series_data, series_data, series_data], axis=1)[:, :3] + + # 归一化到 [0, 255] + normalized = (selected_data - selected_data.min()) / (selected_data.max() - selected_data.min() + 1e-10) + image = (normalized * 255).astype(np.uint8) + + # 调整大小 + image = image.reshape(n_timesteps, 3, 1).reshape(height, width, 3) + + return image.transpose(2, 0, 1) # (3, height, width) +``` + +### 异常数据处理 +```python +import polars as pl +import numpy as np + +def remove_invalid_sequences(train_df, train_events): + """ + 删除无效序列 + + 1st Place 和其他前排方案的共同处理： + - SUBJ_019262: 没有正确佩戴设备 + - SUBJ_045235: 数据异常 + + 参数: + train_df: 训练数据 + train_events: 训练事件 + + 返回: + cleaned_df: 清理后的数据 + """ + # 删除特定 subject 的数据 + invalid_subjects = ['SUBJ_019262', 'SUBJ_045235'] + + # 方法 1: 完全删除 + cleaned_df = train_df.filter(~pl.col('subject').is_in(invalid_subjects)) + + # 方法 2: 数据转换（如果某些序列可以恢复） + # 这里需要根据实际情况处理 + + # 删除 gesture 不存在的序列 + # 统计每个 sequence_id 的 unique gesture 数量 + gesture_counts = train_df.groupby('sequence_id')['gesture'].n_unique() + valid_gestures = gesture_counts.filter(pl.col('gesture') > 0) + cleaned_df = cleaned_df.filter(pl.col('sequence_id').is_in(valid_gestures['sequence_id'])) + + return cleaned_df +``` + +### 左手系 → 右手系对齐 +```python +import numpy as np + +def align_left_to_right_handed(sensor_data, sensor_type='IMU'): + """ + 左手系 → 右手系对齐 + + 将左手佩戴设备的传感器数据转换为右手系的等效数据 + + 参数: + sensor_data: 传感器数据 + sensor_type: 'IMU' 或 'THM' 或 'TOF' + + 返回: + aligned_data: 对齐后的数据 + """ + if sensor_type == 'IMU': + # 对于 IMU（加速度计和陀螺仪）： + # 加速度：x → -x（左右翻转） + # 陀螺仪：某些分量需要取反 + + # 假设 sensor_data 的格式：(acc_x, acc_y, acc_z, rot_w, rot_x, rot_y, rot_z, ...) + # 或者其他格式 + + # 加速度：翻转 x 分量 + acc_x = sensor_data[:, 0] # 假设第 0 列是 acc_x + acc_y = sensor_data[:, 1] # acc_y + acc_z = sensor_data[:, 2] # acc_z + + aligned_acc_x = -acc_x # 左右翻转 + aligned_acc_y = acc_y + aligned_acc_z = acc_z + + # 陀螺仪：需要根据实际佩戴方式调整 + # 这里简化处理，保持不变 + + # 组合对齐后的数据 + aligned_data = sensor_data.copy() + aligned_data[:, 0] = aligned_acc_x + + elif sensor_type == 'THM': + # 对于热电堆传感器： + # 可能需要镜像处理 + + aligned_data = sensor_data.copy() + # 根据传感器位置进行镜像 + + elif sensor_type == 'TOF': + # 对于飞行时间传感器： + # 可能需要镜像处理 8×8 像素阵列 + + aligned_data = sensor_data.copy() + # 根据传感器位置进行镜像 + + return aligned_data +``` + +## CMI - Detect Behavior with Sensor Data - Top 10 Solutions Comparison + +> 基于日语总结和前排方案的综合分析，提取共性技术和差异创新 + +### 竞赛特点总结 + +与之前竞赛不同，这是一个**多模态时序行为识别**任务，核心挑战包括： +- **多模态传感器融合**：IMU + THM + TOF +- **严重数据缺失**：TOF 约 60% 缺失（-1），THM 约 3-4% 缺失 +- **细粒度分类**：18 个手势类别，区分 BFRB vs 日常动作 +- **个体约束**：每个 subject × gesture × orientation 只出现一次 +- **测试集变化**：约 50% 序列仅有 IMU 数据 + +### 前 3 名详细对比 + +#### 1st Place - Devin | Ogurtsov | zyz (Andrey Ogurtsov, Devin, zyz) + +**核心架构：** 多成员协作 + 多模型集成 + +``` +Devin's part: + TOF 处理: 2×2 正方形 9 个区域平均 + TOF-only 模型也加入集成 + +Ogurtsov's part: + 数据清理: 删除 gesture 不存在的序列 + 特征工程: 从 acc（去除重力后）提取 35 个特征 + 模型: LSTM, Attention, CNN 组合 + 增强: timeshift, timistretch + 集成: 每 Fold 选择 3 run 中最佳结果 + 推理: 序列延伸降低模型相关性 + +zyz part: + RNN + CNN1D 组合 +``` + +**关键技术：** +- **TOF 图像化**：2×2 正方形 9 个区域平均降维 +- **TOF-only 集成**：单独使用 TOF 数据的模型也加入集成 +- **数据清理**：删除无效序列（如 SUBJ_019262, SUBJ_045235） +- **特征工程**：35 个特征从 acc（去除重力后）提取 +- **多模型集成**：LSTM + Attention + CNN 组合 +- **推理优化**：序列延伸降低模型相关性，提升集成效果 + +#### 2nd Place - cucutzik + +**核心架构：** 4 模型系统 + 阶段感知 Attention + +``` +4 个独立模型: + IMU rotation 缺失/存在 × THM/TOF 缺失/存在 = 4 组合 + +核心创新: + 四元数 6D 表现 (避免不连续性) + Residual SE-CNN Block + Attention + +关键技巧: + 阶段感知 Attention: + 预测 3 类阶段概率 (移动中/目标位置/手势执行中) + 每个阶段独立 Attention，概率加权 + 相位 Mixup: + 按阶段分割序列 + 同阶段内进行 Mixup + "moves to target" 阶段对齐结束点 + Pseudo Label: + 测试数据生成 pseudo-label + 小 LR (5e-5) 1 step fine-tune + +后处理: + 匈牙利算法全局最优标签分配 + 约束: subject × gesture × orientation 唯一性 +``` + +**关键技术：** +- **四元数 6D 表现**：避免四元数不连续性问题 +- **阶段感知 Attention**：分阶段独立建模和加权 +- **相位 Mixup**：按阶段分割后同阶段内 Mixup +- **Pseudo Label**：测试数据生成伪标签进行微调 +- **匈牙利算法**：全局最优标签分配（利用个体约束） + +#### 3rd Place - Team RIST + +**核心架构：** 2D-CNN + 图像化时序 + +``` +数据预处理: + 四元数平滑处理 + 符号反转扩展 + Block 扩展 + +模型: + MaxViT, ConvNeXt-V2, EfficientNetB5 等 2D-CNN + 输入: 适当尺寸的图像 + +增强: + 世界坐标系 Z 轴旋转 (-60° 到 60°) + 本地坐标系 Y 轴旋转 (-7° 到 7°) + +后处理: + 匈牙利算法全局最优标签分配 +``` + +**关键技术：** +- **时序图像化**：时序数据转换为图像，使用 2D-CNN +- **四元数处理**：平滑、符号反转、Block 扩展 +- **双重旋转增强**：世界坐标 + 本地坐标旋转 +- **多 2D-CNN 集成**：MaxViT + ConvNeXt + EfficientNetB5 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **个体约束利用** | 1st, 2nd, 3rd, 4th | subject × gesture × orientation 唯一性 | +| **数据增强** | 1st, 2nd, 3rd, 4th, 6th... | mixup, cutmix, timeshift, rotation | +| **异常数据处理** | 几乎所有 | SUBJ_019262, SUBJ_045235 删除或转换 | +| **左手系 → 右手系对齐** | 大部分 | 将左手系传感器数据转换为右手系 | +| **多模型集成** | 1st, 2nd, 3rd | 至少 3+ 模型 | +| **阶段感知建模** | 2nd, 3rd, 6th | 利用 Transition/Pause/Gesture 结构 | +| **BatchNorm（无归一化）** | 9th | 不使用 scaler，用 BatchNorm | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st** | TOF 图像化（2×2 区域平均） | 简化 TOF 处理 | +| **1st** | TOF-only 模型集成 | 单独 TOF 也有价值 | +| **1st** | 序列延伸推理 | 降低模型相关性 | +| **2nd** | 四元数 6D 表现 | 避免不连续性 | +| **2nd** | 阶段感知 Attention | 分阶段独立建模 | +| **2nd** | 相位 Mixup | 同阶段内 Mixup，对齐结束点 | +| **2nd** | Pseudo Label fine-tune | 测试数据微调 | +| **3rd** | 时序转图像 | 使用 2D-CNN 处理 | +| **3rd** | 双重旋转增强 | 世界坐标 + 本地坐标 | +| **6th** | gesture segment U-Net | 估计手势时间段 | +| **9th** | 正向 + 反向模型 | 同时训练标准分类和反向分类 | +| **13th** | 双向 Mamba | 长期时序依赖建模 | +| **13th** | Hard Margin Loss | 针对困难样本的损失 | +| **13th** | Hard Mining | 困难样本采样率提升 | + +### 多模态传感器处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **TOF 图像化** | 1st | 2×2 正方形 9 个区域平均 | +| **TOF 2D-CNN** | 7th | 时序数据转图像，用 2D-CNN | +| **TOF U-Net** | 6th | gesture segment 估计 | +| **THM/TOF 独立模型** | 2nd | 4 个模型（缺失/存在组合） | +| **多模态融合** | 1st, 2nd, 3rd | IMU + THM + TOF 特征融合 | + +### 四元数处理对比 + +| 方法 | 使用排名 | 说明 | +|------|---------|------| +| **6D 表现** | 2nd | 避免四元数不连续性 | +| **平滑处理** | 3rd | 处理四元数不连续性 | +| **符号反转扩展** | 3rd | 扩展四元数表示 | +| **Block 扩展** | 3rd | 添加额外 Block | + +### 后处理策略对比 + +| 排名 | 方法 | 具体实现 | +|------|------|---------| +| **1st** | 简单集成 + 推理优化 | 序列延伸 | +| **2nd** | 匈牙利算法 | 全局最优标签分配，利用个体约束 | +| **3rd** | 匈牙利算法 | 全局最优标签分配 | +| **4th-15th** | 多种方法 | argmax, 约束优化等 | + +### 数据增强策略对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **Mixup** | 1st, 2nd, 4th, 10th | 标准或相位 Mixup | +| **CutMix** | 1st | 标准 CutMix | +| **Time Shift** | 1st | 时间偏移 | +| **Time Stretch** | 1st | 时间拉伸 | +| **Rotation** | 2nd, 3rd | 世界坐标 + 本地坐标旋转 | +| **Time Warping** | 7th | 时间非线性伸缩 | +| **Magnitude Warping** | 7th | 幅度时间变化 | +| **双重 Mixup** | 10th | `Mixup(Mixup(Mixup(x)))` | + +### 缺失数据处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **独立模型** | 2nd | 4 个模型（缺失/存在组合） | +| **TOF-only** | 1st | 单独 TOF 模型也集成 | +| **gesture segment** | 6th | U-Net 估计手势时间段 | +| **删除异常序列** | 1st | 删除无效序列 | +| **数据转换** | 几乎所有 | 左手系 → 右手系对齐 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **个体约束利用**：subject × gesture × orientation 唯一性 +2. **数据增强**：mixup, cutmix, timeshift, rotation +3. **异常数据处理**：SUBJ_019262, SUBJ_045235 删除或转换 +4. **左手系 → 右手系对齐**：统一左右手传感器数据 +5. **多模型集成**：至少 3+ 模型 +6. **阶段感知建模**：利用 Transition/Pause/Gesture 结构 + +#### 推荐选项（根据情况选择） +- **TOF 处理**：图像化 (1st) > 2D-CNN (7th) > U-Net (6th) +- **四元数处理**：6D 表现 (2nd) > 平滑 + 扩展 (3rd) +- **后处理**：匈牙利算法 (2nd, 3rd) > 简单集成 (1st) +- **模型架构**：根据数据特征选择 1D-CNN / 2D-CNN / Mamba + +#### 创新方向 +- **阶段感知建模**：分阶段独立 Attention 和特征提取 +- **相位 Mixup**：按阶段分割后同阶段内 Mixup +- **Pseudo Label**：测试数据生成伪标签微调 +- **时序图像化**：将时序数据转为图像，用 2D-CNN +- **双向 Mamba**：长期时序依赖建模 + +--- + +## 数据洞察与分析 + +### 数据特征理解 + +#### 标签质量的双峰分布 + +**发现：** 投票数呈现双峰分布 +- **低质量样本**：1-7 票 +- **高质量样本**：10-28 票 +- **关键发现**：**没有 8-9 票的样本** + +**含义：** +- 存在两组标注者：专家组（20人）和大众组（119人） +- 低投票数样本更不可靠，标签噪声更大 +- 高投票数样本代表专家共识，质量更高 + +**策略：** +- 使用 votes ≥10 作为高质量阈值 +- 仅用高质量样本建立验证集（CV/LB 相关性接近 1:1） +- 考虑对低投票样本进行更强正则化 + +**第 3 名的洞察：** 从 100,000+ 行筛选到 6,350 行高质量数据，性能反而提升 → **"少即是多"**，精确数据胜过大量噪声数据 + +#### 标签稀疏性 + +**发现：** 训练标签中某些类别的概率为 0 +- Softmax 输出所有值 > 0（数学性质） +- 但真实标签中某些类为 0 + +**解决方案（1st Place）：** +- 使用 **Entmax** 替换 Softmax +- Entmax 可以产生真正的 0 输出（稀疏激活） +- 结果：LB +0.004 提升 + +**实现：** +```python +def entmax(x, alpha=1.5, dim=-1): + return torch.softmax(x * alpha, dim=dim) +``` + +#### 双模态数据的时间对齐 + +**数据结构：** +- **Spectrogram**：10 分钟（低时间分辨率，高频率信息） +- **EEG**：50 秒中心段（高时间分辨率，低频率信息） +- 两者中心 50 秒是同一数据 + +**洞察：** +- Spectrogram 提供全局上下文（10分钟趋势） +- EEG 提供精细时序信息（50 秒细节） +- 这是**同一数据的两种表示**，不是独立信息 + +**处理策略：** +- 大多数获胜者**专注于 EEG**（2nd, 3rd） +- 1st Place 同时使用两种并集成 +- 时频分析（CWT/MelSpectrogram）比纯时序或纯频域更有效 + +#### 信号配对的重要性 + +**发现：** +- 脑电信号存在空间关系 +- 左右对称位置的电极信号应该成对处理 +- 通道顺序影响模型性能 + +**策略（3rd Place）：** +- 将左右脑节点配对：Fp1-F7, Fp2-F8, F7-T3, F8-T4 等 +- 而不是简单按顺序堆叠 +- 这样保留了脑部空间结构的先验知识 + +#### 频率范围选择的影响 + +**对比分析：** +| 频率范围 | 使用者 | 效果 | +|---------|--------|------| +| 0.5-20 Hz | 标准, 2nd | Kaggle 默认 | +| 0.5-40 Hz | 1st (suguuuuu) | 更佳结果 | +| 0.5-50 Hz | 部分 | 高频噪声可能增加 | + +**洞察：** +- 标准范围可能遗漏重要信息 +- 扩展到 40 Hz 能捕捉更多特征 +- 但过高频率（50 Hz+）可能引入噪声 +- 需要根据具体任务调整 + +#### 归一化的选择 + +**实验发现（3rd Place）：** +- Batch/Sample 归一化：效果不佳 +- MAD 归一化：对异常值更鲁棒 +- **Clip 归一化** `x.clip(-1024, 1024) / 32`：**最佳选择**（所有前 3 名都使用） + +**为什么 Clip/32 最好？** +1. **限制极端值**：EEG 信号存在大幅伪影 +2. **固定除数 32**：简单、可复现、不过拟合 +3. **保留信息**：相比标准化，保留更多原始信号特征 + +#### 数据增强的反向工程 + +**3rd Place 的关键发现：** +- 数据创建者对训练数据应用了 augmentation +- 这些 augmentation 在测试时不存在 +- **反向工程并移除这些 augmentation** 后，模型性能显著提升 + +**启示：** +- 理解数据来源和预处理历史很重要 +- "干净"的原始数据可能比"增强"的数据更好 +- 深入数据分析能发现隐藏的改进机会 + +### 数据质量评估框架 + +基于前 10 名的分析，可以建立以下数据质量评估维度： + +| 维度 | 评估方法 | 高质量指标 | +|------|---------|-----------| +| **投票数** | 统计每个样本的专家投票数 | votes ≥10 | +| **一致性** | 计算投票分布的熵 | 高一致性（低熵） | +| **标注者类型** | 区分专家 vs 大众 | 专家共识权重更高 | +| **信号质量** | 检查伪影、噪声水平 | 低噪声、少伪影 | +| **时序完整性** | 检查 50 秒段连续性 | 无断裂、无缺失 | + +### 数据预处理最佳流程 + +综合前 10 名方案，推荐的数据预处理流程： + +```python +def preprocess_eeg_optimal(eeg_raw, votes): + """ + 基于 Top 10 方案的最佳预处理流程 + """ + # 1. 双极导联（减少共模噪声） + bipolar = longitudinal_bipolar_montage(eeg_raw) + + # 2. 带通滤波（0.5-40 Hz，扩展频段） + filtered = bandpass_filter(bipolar, lowcut=0.5, highcut=40, fs=200) + + # 3. Clip 归一化（所有前 3 名使用） + normalized = np.clip(filtered, -1024, 1024) / 32.0 + + # 4. 数据质量筛选 + if votes < 10: + # 考虑降权重或使用 Pseudo Label + weight = votes / 20.0 # 2nd Place 方法 + else: + weight = 1.0 + + return normalized, weight +``` + +### 标签处理最佳实践 + +| 技术 | 目的 | 使用排名 | +|------|------|---------| +| **投票数归一化** | 转换为概率分布 | 所有 | +| **标签平滑（加 0.02）** | 防止过度自信 | 部分 | +| **Loss 权重** | 按投票数加权样本 | 2nd | +| **Offset 加法** | 低投票数更强正则化 | 部分 | + +### 关键数据洞察总结 + +1. **质量 > 数量**：6,350 行高质量数据 > 100,000 行噪声数据 +2. **稀疏标签需要稀疏激活**：Entmax > Softmax +3. **时频分析优于纯时序或纯频域**：CWT > STFT +4. **空间先验知识很重要**：信号配对、左右对称 +5. **归一化方法影响巨大**：Clip/32 是最佳选择 +6. **理解数据来源至关重要**：反向 Augmentation 提升性能 +7. **标签质量分布不均**：需要分层训练和评估 + +--- + +## Child Mind Institute - 数据洞察与分析 + +### 数据特征理解 + +#### 极度稀疏的标签 + +**发现：** 17280 步（24小时）中仅有 2 步有标签 +- **标签密度**：0.01%（1/10000） +- **事件类型**：onset（入睡）+ wakeup（觉醒） +- **标注粒度**：每夜 1 个 onset + 1 个 wakeup + +**含义：** +- 传统逐帧分类方法不适用 +- 需要特殊的目标创建策略（衰减目标） +- 后处理比模型预测更重要 +- 数据增强对缓解稀疏性至关重要 + +**策略：** +- **衰减目标**：按 tolerance_steps 创建衰减的标签分布 +- **多任务学习**：同时预测 onset, wakeup, asleep +- **后处理优化**：find_peaks, NMS, greedy search +- **数据增强**：序列反转、时间偏移等 + +#### 分钟偏差模式 + +**发现：** 真实事件总是发生在 hh:mm:00 整分钟时刻 + +**数据分布（YOURI MATIOUNINE 发现）：** +``` +标签分钟数 % 15 的分布： +- 0分钟：明显峰值 +- 3分钟：明显峰值 +- 7分钟：明显峰值 +- 11分钟：明显峰值 +- 其他分钟：很少出现 +``` + +**含义：** +- 手动标注导致精度有限 +- 存在 15 分钟的周期性模式 +- 模型应该学习这种模式 + +**策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | Minute Embedding | 残差连接到输出层 | +| **2nd** | Step 偏移 | 对预测 step 做偏移后重新预测 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | +| **5th** | 标签偏移 | target shift ~-11 步 | +| **6th** | 特征工程 | `(step // 12) % 15` | + +#### 未标注事件问题 + +**发现（YOURI MATIOUNINE）：** 很多序列有明显的 events 未被标注 + +**两类情况：** +1. **日周期性重复**：缺失 events 的夜晚跟前 24 小时数据完全一样 + - 推测：组织方用历史正常数据填补了缺失数据 +2. **无法解释的缺失**：没有明显规律的缺失标注 + +**处理策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | 周期性检测 + flag | 降采样 + 相似度计算，标记日周期性 | +| **3rd** | 噪声检测 | 相同 hour+step+anglez 重复值即为噪声 | +| **5th** | 样本加权 | 训练时权重设为 0 | +| **6th** | Hash 算法 | 散列和散列图查找重复模式，本地 CV +0.015 | +| **大部分** | 过滤序列 | 剔除未标注 events 出现多的序列 | + +**1st Place 的周期性检测方法：** +```python +def detect_periodicity(series): + """检测 24 小时周期性重复""" + # 1. 降采样 + downsampled = series[::12] # 5秒 → 1分钟 + + # 2. 分割序列（按天） + n_days = len(downsampled) // 1440 # 1440 = 24小时 + daily_chunks = [downsampled[i*1440:(i+1)*1440] for i in range(n_days)] + + # 3. 计算相邻天的相似度 + for i in range(n_days - 1): + # 方法1: 元素级比较 + similarity = np.mean(daily_chunks[i] == daily_chunks[i+1]) + + # 方法2: 余弦相似度 + cos_sim = np.dot(daily_chunks[i], daily_chunks[i+1]) / ( + np.linalg.norm(daily_chunks[i]) * np.linalg.norm(daily_chunks[i+1]) + ) + + if similarity > threshold or cos_sim > threshold: + return True # 检测到周期性 + + return False +``` + +#### 多 Tolerance AP 评估指标 + +**评估方式：** +```python +tolerances = [1, 3, 5, 7.5, 10, 12.5, 15, 20, 25, 30] # 分钟 +# 对每个 tolerance，计算 AP +# 最终分数 = mean(各tolerance AP) × mean(onset AP, wakeup AP) +``` + +**关键洞察（1st Place）：** +- **预测 hh:mm:00 不好**：tolerance 5,10,15,20,25,30 时边缘漏检 +- **预测 hh:mm:30 不好**：tolerance 7.5, 12.5 时边缘漏检 +- **预测 hh:mm:15 或 hh:mm:45 最佳**：覆盖所有 tolerance + +**原理示意：** +``` +00:23:15 ← 检测事件（15秒） + ← tolerance 7.5 分 → +00:23:00 ← 真实事件（0秒） + ← tolerance 7.5 分 → +00:22:45 + +如果检测事件在 00:23:00，则 tolerance 7.5 的右边缘会漏检 +如果检测事件在 00:23:15 或 00:22:45，则正好覆盖 +``` + +#### 15分钟周期性模式 + +**发现：** events 以 15 分钟为周期重复出现 + +**数据分布：** +- **峰值分钟**：0, 3, 7, 11（间隔 3-4 分钟） +- **周期**：15 分钟 +- **含义**：可能与定时检查或记录习惯有关 + +**应对策略：** +| 排名 | 策略 | 说明 | +|------|------|------| +| **1st** | 15/45秒技巧 | 无论 1-29秒 还是31-59秒，选15/45秒代表 | +| **2nd** | Step偏移 | 对step做多个偏移，覆盖所有可能时刻 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **周期性重复** | 降采样+相似度 | 与前24小时完全相同 | 标记 periodicity flag | +| **噪声重复** | hour+step+anglez计数 | 重复值>1 | 标记 noise | +| **未标注events** | 统计每夜events数 | <2 events | 过滤或降权 | +| **数据异常** | enmo统计 | enmo值异常大 | clip到1 | + +### 关键数据洞察总结 + +1. **极度稀疏标签**：需要衰减目标和后处理优化 +2. **分钟偏差是关键**：所有前排方案都处理了这个问题 +3. **未标注events普遍存在**：周期性检测可识别 +4. **多tolerance AP需要特殊优化**：15/45秒技巧是制胜关键 +5. **评估指标与数据分布不匹配**：需要针对tolerance优化 +6. **Daily Normalization有效**：利用每天只有2次活动的先验 +7. **15分钟周期性模式**：step偏移或频率编码可利用 + +## CMI - Detect Behavior 数据洞察与分析 + +### 数据特征理解 + +#### 多模态传感器数据 + +**三种传感器类型：** + +| 传感器 | 数据维度 | 特征 | 缺失率 | +|-------|---------|------|--------| +| **IMU** | 加速度计(x,y,z) + 陀螺仪(x,y,z) | 运动和旋转 | 无缺失 | +| **THM** | 5个温度传感器 | 温度分布 | ~3-4% | +| **TOF** | 5个8×8传感器阵列 | 距离映射 | ~60% | + +**IMU (Inertial Measurement Unit)：** +- 6 列：`X_accel`, `Y_accel`, `Z_accel`, `X_gyro`, `Y_gyro`, `Z_gyro` +- **重力分量**：加速度计包含重力，需去除 +- **四元数**：`orientation_X`, `orientation_Y`, `orientation_Z`, `orientation_W` + - 表示设备旋转姿态 + - **不连续性问题**：四元数在表示相同旋转时有多个值（q和-q表示相同旋转） + - **解决方案**：使用旋转矩阵前两列（6D连续表示） + +**THM (Thermopile)：** +- 5 列：`thermopile_0` ~ `thermopile_4` +- 温度传感器，用于检测物体接近 +- **缺失标记**：-1 表示缺失 +- **缺失率较低**：约3-4% + +**TOF (Time-of-Flight)：** +- 320 列：`tof_0` ~ `tof_319`（5个8×8阵列） +- 距离传感器，检测物体到设备距离 +- **缺失标记**：-1 表示缺失 +- **缺失严重**：约60%的数据为-1 +- **图像化处理**：将8×8阵列降采样为2×2特征图（1st Place创新） + +#### 严重数据缺失问题 + +**缺失分布：** +``` +TOF: ~60% 缺失 (-1 标记) +THM: ~3-4% 缺失 (-1 标记) +IMU: 无缺失 +``` + +**前排处理策略：** + +| 排名 | TOF 处理 | THM 处理 | +|------|---------|---------| +| **1st** | 2×2 pooling后标记缺失mask | 简单插值或mask | +| **2nd** | 特征工程提取有效点统计量 | 类似TOF处理 | +| **3rd** | 转图像，缺失填0 | 不使用或简单处理 | +| **其他** | 丢弃或mask | 丢弃或mask | + +**1st Place 的 TOF 处理创新：** +```python +def tof_2x2_pooling_with_mask(tof_data): + """ + TOF 数据 2×2 pooling + 缺失 mask + """ + # 每个 8×8 传感器 + for sensor_idx in range(5): + sensor = tof_data[:, sensor_idx*64:(sensor_idx+1)*64] + sensor = sensor.reshape(-1, 8, 8) + + # 2×2 pooling + pooled = sensor.reshape(-1, 4, 2, 2).mean(axis=(2, 3)) + + # 缺失 mask + mask = (sensor == -1).reshape(-1, 4, 2, 2).any(axis=(2, 3)) + + # 组合：特征 + mask + features[:, sensor_idx*4:(sensor_idx+1)*4] = pooled + features[:, 20+sensor_idx*4:20+(sensor_idx+1)*4] = mask + + return features +``` + +#### 个体约束利用 + +**关键约束：** 每个 subject × gesture × orientation 组合只出现一次 + +**含义：** +- 训练集中没有重复的 subject × gesture × orientation +- 验证时可以确保预测结果也满足这个约束 +- 可以用匈牙利算法做全局最优标签分配 + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **1st** | 匈牙利算法 | 全局最优分配，提升 LB 0.01 | +| **2nd** | 阶段感知建模 | 利用三阶段结构 | +| **其他** | 个体特征 embedding | 添加 subject embedding | + +**匈牙利算法实现（1st Place）：** +```python +from scipy.optimize import linear_sum_assignment + +def hungarian_post_process(predictions, subject_ids, sequence_ids): + """ + 利用 subject × gesture × orientation 唯一约束 + """ + # 对于每个 subject + for subject in unique(subject_ids): + # 获取该 subject 的所有预测 + mask = subject_ids == subject + preds = predictions[mask] + seqs = sequence_ids[mask] + + # 构建代价矩阵：-log(概率) + cost_matrix = -np.log(preds + 1e-10) + + # 匈牙利算法：找到最优分配 + row_ind, col_ind = linear_sum_assignment(cost_matrix) + + # 更新预测结果 + for i, j in zip(row_ind, col_ind): + predictions[mask][i] = np.zeros(n_classes) + predictions[mask][i][j] = 1.0 + + return predictions +``` + +#### 三阶段结构 + +**发现：** 行为序列有明显的三阶段结构 + +``` +Transition → Pause → Gesture +``` + +**阶段特征：** + +| 阶段 | 持续时间 | 特征 | 识别要点 | +|------|---------|------|---------| +| **Transition** | 变化 | 从上一个状态移动到手势位置 | 运动幅度大 | +| **Pause** | 短暂 | 手势开始前的准备 | 运动幅度小 | +| **Gesture** | 重复 | 核心行为模式（如咬指甲） | 周期性模式 | + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **2nd** | 阶段感知 Attention | 每个阶段独立的 attention 权重 | +| **6th** | U-Net分割 | 将手势阶段作为分割任务 | +| **其他** | 特征工程 | 添加阶段分类特征 | + +**2nd Place 阶段感知 Attention：** +```python +class PhaseAwareAttention(nn.Module): + """ + 阶段感知 Attention - 每个阶段独立建模 + """ + def __init__(self, d_model, n_heads=8): + super().__init__() + # 3个阶段 embedding + self.phase_emb = nn.Embedding(3, d_model) + + # 每个阶段独立的 attention + self.transition_attn = nn.MultiheadAttention(d_model, n_heads) + self.pause_attn = nn.MultiheadAttention(d_model, n_heads) + self.gesture_attn = nn.MultiheadAttention(d_model, n_heads) + + def forward(self, x, phase_labels): + # phase_labels: [batch, seq_len] ∈ {0, 1, 2} + batch, seq_len, d_model = x.shape + + outputs = [] + for t in range(seq_len): + phase = phase_labels[:, t] # [batch] + + if phase == 0: # Transition + attn_out, _ = self.transition_attn(x[:, t:t+1], x, x) + elif phase == 1: # Pause + attn_out, _ = self.pause_attn(x[:, t:t+1], x, x) + else: # Gesture + attn_out, _ = self.gesture_attn(x[:, t:t+1], x, x) + + outputs.append(attn_out) + + return torch.cat(outputs, dim=1) +``` + +#### BFRB vs 非BFRB 类别分布 + +**18个手势类别：** + +| 类别 | BFRB类型 | 典型行为 | +|------|---------|---------| +| 0-7 | BFRB | 咬指甲、拉头发、抠皮肤等 | +| 8-17 | 非BFRB | 拍手、挥手、其他手势 | + +**分布特点：** +- **训练集**：BFRB 和非BFRB 数量相近 +- **个体差异**：不同 subject 的手势偏好不同 +- **方向差异**：同一手势不同方向的表现不同 + +**处理策略：** +- **Phase-aware Mixup**：仅在 Gesture 阶段进行 mixup（2nd Place） +- **个体 normalization**：按 subject 做归一化 +- **类别平衡**：确保每个类别有足够样本 + +#### 测试集变化 + +**关键发现：** 测试集约50%的序列仅有 IMU 数据 + +**含义：** +- 不能过度依赖 TOF 和 THM 特征 +- 模型必须能够仅用 IMU 数据做出预测 +- 需要训练仅用 IMU 的模型作为集成成员 + +**前排应对策略：** + +| 排名 | 应对方法 | +|------|---------| +| **1st** | 训练IMU-only模型，集成时加权 | +| **2nd** | 4个模型：IMU-only, IMU+TOF, IMU+THM, All | +| **3rd** | TOF填0处理，但效果受限 | +| **其他** | 简单丢弃缺失传感器 | + +**推荐策略：** +```python +# 训练时模拟测试集情况 +def get_model_input(data): + """ + 根据可用传感器选择模型输入 + """ + has_tof = (data['tof'] != -1).any() + has_thm = (data['thm'] != -1).any() + + if has_tof and has_thm: + return model_all(data['imu'], data['tof'], data['thm']) + elif has_tof: + return model_imu_tof(data['imu'], data['tof']) + elif has_thm: + return model_imu_thm(data['imu'], data['thm']) + else: + return model_imu(data['imu']) +``` + +#### 异常数据识别 + +**两个异常 subject：** + +| Subject | 问题 | 处理策略 | +|---------|------|---------| +| **SUBJ_019262** | 数据异常，预测困难 | 训练时过滤或降权 | +| **SUBJ_045235** | 数据异常，预测困难 | 训练时过滤或降权 | + +**识别方法：** +- 训练集上该 subject 的 loss 异常高 +- 交叉验证该 subject 的预测准确率低 +- 可视化该 subject 的传感器数据，发现异常模式 + +**处理代码：** +```python +# 异常 subject 黑名单 +ANOMALY_SUBJECTS = ['SUBJ_019262', 'SUBJ_045235'] + +def filter_anomaly_subjects(dataframe): + """ + 过滤异常 subject + """ + mask = ~dataframe['subject'].isin(ANOMALY_SUBJECTS) + return dataframe[mask] +``` + +#### 左手系 vs 右手系对齐 + +**发现：** 测试集存在左手和右手两种设备朝向 + +**问题：** +- 左手系和右手系的传感器读数方向相反 +- 四元数表示旋转的方式不同 +- 直接混合训练会引入噪声 + +**解决方案（前排通用）：** +```python +def align_right_handed_system(data): + """ + 左手系 → 右手系对齐 + """ + # 翻转陀螺仪的 x, y 轴 + data['X_gyro'] = -data['X_gyro'] + data['Y_gyro'] = -data['Y_gyro'] + + # 调整四元数（取决于具体定义） + # 这里假设是绕 z 轴旋转 180 度 + data['orientation_X'] = -data['orientation_X'] + data['orientation_Y'] = -data['orientation_Y'] + + return data +``` + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **传感器缺失** | 统计-1值比例 | TOF>50%, THM>5% | mask处理或训练IMU-only模型 | +| **异常subject** | 按subject统计loss | loss > threshold | 过滤SUBJ_019262, SUBJ_045235 | +| **设备朝向** | 检测左右手系 | 四元数和陀螺仪方向 | 统一到右手系 | +| **三阶段一致性** | 检测阶段标签 | 阶段跳变 | 利用三阶段结构特征 | + +### 关键数据洞察总结 + +1. **多模态融合是关键**：IMU + THM + TOF，但测试集仅50%有完整数据 +2. **TOF 缺失严重（60%）**：需要创新处理（2×2 pooling + mask） +3. **个体约束必须利用**：subject × gesture × orientation 唯一约束可用匈牙利算法 +4. **三阶段结构重要**：Transition/Pause/Gesture，阶段感知建模有效 +5. **四元数不连续性**：需转换为6D连续表示（旋转矩阵前两列） +6. **测试集只有IMU数据**：必须训练IMU-only模型作为集成成员 +7. **异常数据需处理**：SUBJ_019262和SUBJ_045235应该过滤或降权 +8. **左手系右手系对齐**：统一到右手系避免噪声 + +### 多模态时间序列分类的最佳实践 + +与单模态分类任务不同，多模态任务的特殊考虑： + +| 方面 | 单模态任务 | 多模态任务 | +|------|-----------|-----------| +| **特征提取** | 单一特征工程 | 每个模态独立提取后融合 | +| **模型架构** | 单一编码器 | 多编码器或早期融合 | +| **缺失处理** | 插值或丢弃 | mask处理或模态specific模型 | +| **数据增强** | 简单增强 | 模态感知增强（Phase-aware Mixup） | +| **后处理** | 阈值或NMS | 利用约束（匈牙利算法） | + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/detect-sleep-states-2023.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/detect-sleep-states-2023.md new file mode 100644 index 0000000..9ae2447 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/detect-sleep-states-2023.md @@ -0,0 +1,1622 @@ +# Child Mind Institute - Detect Sleep States (2023) +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### Child Mind Institute - Detect Sleep States (2023) + +**竞赛背景：** +- **主办方**：Child Mind Institute +- **目标**：从手腕佩戴的加速度计数据中检测睡眠事件（入睡 onset 和觉醒 wakeup） +- **应用场景**：睡眠健康监测、可穿戴设备、睡眠质量分析 +- **社会意义**：自动化睡眠监测，减少人工标注成本，改善睡眠障碍诊断 + +**任务描述：** +从 5 秒间隔的加速度计时间序列数据中检测两类事件： +- **Onset**：入睡时刻 +- **Wakeup**：觉醒时刻 + +**数据集规模：** +- 总样本数：~500 个多日记录 +- 数据点：每个 series 最多 17280 步（24 小时 × 12 步/分钟 × 60 分钟） +- 特征：anglez（手臂角度）、enmo（加速度计信号） +- 标注：每夜 1 个 onset + 1 个 wakeup 事件 + +**数据特点：** +1. **稀疏标注**：17280 步中仅有 2 步有标签（0.01%） +2. **标签偏移**：真实事件总是发生在 hh:mm:00 整分钟时刻 +3. **周期性模式**：存在 24 小时周期性重复的数据（未标注事件） +4. **评估容差**：多个 tolerance 窗口（1, 3, 5, 7.5, 10, 12.5, 15, 20, 25, 30 分钟） + +**评估指标：** +- **Average Precision (AP)**：多 tolerance 平均 +- 对每个 tolerance 窗口，计算最高置信度匹配的 AP +- 最终分数 = 各 tolerance AP 的平均 × 各类别 AP 的平均 + +**竞赛约束：** +- 提交格式：series_id, step, event, score +- 每个系列最多预测多个事件（需后处理筛选） +- 事件必须成对（onset + wakeup） + +**最终排名：** +- 1st Place: shimacos vs sakami vs kami - Private LB: **0.852** +- 2nd Place: K-Mat - Private LB: ~0.850 +- 3rd Place: cucutzik - Private LB: ~0.849 +- 总参赛队伍：1,877 支 + +**技术趋势：** +- 几乎所有前排方案使用**两阶段建模**：5秒概率预测 → 1分钟精化 +- **分钟偏差处理**是关键涨分点：事件总是发生在整分钟 +- **未标注事件检测**：利用周期性识别缺失标签 +- **后处理优化**：针对 tolerance 指标的 greedy search +- **Daily Normalization**：按天归一化 2nd level 预测 + +**关键创新：** +- **15/45秒技巧** (1st Place)：针对 tolerance 边缘优化 +- **两阶段建模** (1st, 2nd)：5秒检测 + 1分钟精化 +- **Error Modeling** (2nd Place)：将差分变化转为分类任务 +- **数据增强** (3rd Place)：序列反转提升 CV +0.01 + +**后续影响：** +- 该竞赛推动可穿戴设备睡眠监测技术发展 +- 前排方案广泛开源，成为事件检测任务的参考 +- 后处理优化策略被后续竞赛采用 + +#### 前排方案详细技术分析 + +**1st Place - shimacos vs sakami vs kami (kami, sakami0000, shimacos)** + +核心技巧： +- **15/45秒技巧**：针对 tolerance 边缘优化，事件可能发生在整点前/后 15/45 秒 +- **两阶段建模**：Stage 1（5秒概率预测）→ Stage 2（1分钟精化） +- **Daily Normalization**：按天归一化 2nd level 预测，减少个体差异 +- **Greedy Post-Processing**：针对 AP 指标优化，选择最佳事件对 +- **衰减目标**：按 tolerance_steps 加权 + epoch 衰减 + +实现细节： +- Stage 1：LSTM + MLP，输出 5 秒间隔的概率预测 +- Stage 2：基于 Stage 1 预测，在 1 分钟窗口内精化事件位置 +- 考虑事件必须在整分钟时刻（label shift 0） +- 最终 Private LB：0.852 + +**2nd Place - K-Mat** + +核心技巧： +- **Error Modeling**：将差分变化转为分类任务（上升/下降/平稳） +- **序列反转数据增强**：提升 CV +0.01 +- **集成策略**：多个模型的不同配置集成 +- **后处理优化**：考虑事件对的约束条件 + +实现细节： +- 输入特征：anglez + enmo + 时间戳特征 +- 模型架构：LSTM + Attention 机制 +- Error Modeling：预测信号变化模式，辅助事件检测 +- 最终 Private LB：~0.850 + +**3rd Place - cucutzik** + +核心技巧： +- **序列反转数据增强**：镜像序列，增加数据多样性 +- **未标注事件利用**：利用周期性模式识别未标注事件 +- **时间窗口滑动**：多尺度窗口检测事件 +- **事件对约束**：确保 onset 和 wakeup 成对出现 + +实现细节： +- 数据增强：时间序列反转，保持标签一致性 +- 模型集成：3-5 个不同随机种子的模型 +- 后处理：基于置信度和时间约束筛选事件对 +- 最终 Private LB：~0.849 + +**4th Place - RSI (Recurring Sleep Inertia)** + +核心技巧： +- **周期性模式检测**：自动识别 24 小时周期性睡眠模式 +- **多时域建模**：5 秒、30 秒、5 分钟多尺度预测 +- **事件链预测**：预测 onset-wakeup 事件链而非单独事件 +- **置信度校准**：温度缩放校准预测概率 + +实现细节： +- 周期性检测：FFT 频谱分析识别 24 小时周期 +- 多尺度模型：不同时间窗口的 LSTM 集成 +- 事件链：onset → [sleep] → wakeup 约束 +- 最终 Private LB：~0.848 + +**5th Place - Andris (Andris Apinis)** + +核心技巧： +- **特征工程自动化**：时域、频域、时频域特征自动提取 +- **XGBoost 集成**：梯度提升树处理统计特征 +- **深度学习混合**：LSTM + XGBoost 混合架构 +- **滑动窗口集成**：多窗口大小预测融合 + +实现细节： +- 特征：统计特征（均值、方差、峰度）+ 频域特征（FFT 功率谱） +- XGBoost：100+ 棵树，max_depth=8 +- 混合架构：LSTM 处理时序 + XGBoost 处理特征 +- 滑动窗口：[30s, 60s, 120s, 300s] +- 最终 Private LB：~0.847 + +**6th Place - CPMP (Cyprien) 设为 0 + start_gt = max(0, best_idx - tol_step) + end_gt = min(len(remaining_predictions), best_idx + tol_step) + remaining_predictions[start_gt:end_gt] = 0 + + # 检测候选点 (15/45秒) -> 分数打折 + # 这里简化处理，实际可以只打折不置零 + + return selected_events + + return greedy_event_selection(predictions_2nd_level) +``` + +### Daily Normalization (1st Place approach) +```python +import numpy as np + +def daily_normalize(predictions, series_ids): + """ + 按天归一化预测值 - 利用每天只有1次 onset + 1次 wakeup 的先验 + + 原理： + - 每天只有 2 个事件（1 onset + 1 wakeup） + - 按天归一化可以使每天的最高预测值具有可比性 + """ + normalized = predictions.copy() + + for series_id in np.unique(series_ids): + mask = series_ids == series_id + daily_preds = predictions[mask] + + # 按天分组（17280 步 = 1 天） + n_days = len(daily_preds) // 17280 + + for day in range(n_days): + start = day * 17280 + end = start + 17280 + day_preds = daily_preds[start:end] + + # 归一化到 [0, 1] + day_min, day_max = day_preds.min(), day_preds.max() + if day_max > day_min: + normalized[mask][start:end] = (day_preds - day_min) / (day_max - day_min) + + return normalized +``` + +### Find Peaks 事件检测 +```python +from scipy.signal import find_peaks + +def detect_events_find_peaks(predictions, score_th=0.005, distance=72): + """ + 使用 find_peaks 检测事件 + + 参数: + predictions: 事件概率预测 (shape: [n_steps]) + score_th: 分数阈值（低于此值不检测） + distance: 最小峰值间隔（步数）72 = 6分钟 + + 返回: + events: 检测到的事件索引列表 + """ + onset_preds = predictions[:, 0] # onset 概率 + wakeup_preds = predictions[:, 1] # wakeup 概率 + + # 检测 onset 峰值 + onset_peaks, _ = find_peaks( + onset_preds, + height=score_th, + distance=distance + ) + + # 检测 wakeup 峰值 + wakeup_peaks, _ = find_peaks( + wakeup_preds, + height=score_th, + distance=distance + ) + + return { + 'onset': onset_peaks, + 'wakeup': wakeup_peaks + } +``` + +### Rolling Mean 平滑 (3rd Place approach) +```python +import numpy as np + +def rolling_mean_smooth(predictions, window=12, center=True): + """ + 使用滚动均值平滑预测结果 + + 参数: + predictions: 原始预测值 + window: 窗口大小（12 = 1分钟） + center: 是否居中 + """ + smoothed = np.zeros_like(predictions) + + for i in range(len(predictions)): + start = max(0, i - window // 2) + end = min(len(predictions), i + window // 2 + 1) + smoothed[i] = predictions[start:end].mean() + + return smoothed + +# 然后检测峰值 +def detect_events_with_smooth(predictions, window=12, distance=72): + """平滑后检测事件""" + smoothed = rolling_mean_smooth(predictions, window=window) + return detect_events_find_peaks(smoothed, distance=distance) +``` + +### 两阶段建模框架 (1st Place approach) +```python +def two_level_modeling(train_series, train_events): + """ + 两阶段建模框架 + + 1st Level: 5秒间隔预测事件概率 + 2nd Level: 1分钟间隔精化预测 + """ + # ==================== 1st Level ==================== + # 输入：5秒间隔的数据 + # 输出：5秒间隔的 onset/wakeup 概率 + + # 1st Level 模型示例 + first_level_models = [ + CNNGRUModel(), # CNN + GRU + CNN + CNNTransformerModel(), # CNN + GRU + Transformer + CNN + LSTMUNetModel(), # LSTM + UNet1d + UNet + # ... 更多模型 + ] + + # 训练 1st level + for model in first_level_models: + model.fit(train_series, train_events) + + # 生成 1st level 预测（5秒间隔） + first_level_preds = [] + for model in first_level_models: + pred = model.predict(train_series) # shape: [n_steps_5sec, 2] + first_level_preds.append(pred) + + # ==================== 2nd Level ==================== + # 输入：1st level 预测 + 原始特征（整合到整分钟） + # 输出：1分钟间隔的 onset/wakeup 概率 + + # 整合 1st level 预测到整分钟 + minute_features = aggregate_to_minute(first_level_preds, train_series) + + # 2nd Level 模型示例 + second_level_models = [ + LightGBMRegressor(), + CatBoostRegressor(), + CNNGRUModel(), + CNNTransformerModel(), + CNNModel() + ] + + # 训练 2nd level + for model in second_level_models: + model.fit(minute_features, train_events) + + # 生成 2nd level 预测（1分钟间隔） + second_level_preds = [] + for model in second_level_models: + pred = model.predict(minute_features) # shape: [n_steps_1min, 2] + second_level_preds.append(pred) + + # ==================== 后处理 ==================== + # Daily normalization + final_preds = np.mean(second_level_preds, axis=0) + final_preds = daily_normalize(final_preds, series_ids) + + # Greedy 事件选择（15/45秒技巧） + events = optimize_tolerance_edges(final_preds) + + return events + +def aggregate_to_minute(first_level_preds, train_series): + """将 5 秒预测整合到 1 分钟""" + # 每个 1 分钟包含 12 个 5 秒步 + n_steps_minute = len(train_series) // 12 + + minute_features = [] + for i in range(n_steps_minute): + start = i * 12 + end = start + 12 + + # 整合 1st level 预测（均值、最大值等） + preds_5sec = [p[start:end] for p in first_level_preds] + + # 整合原始特征（anglez, enmo 的统计量） + raw_feats = train_series[start:end] + + # 合并特征 + minute_feat = np.concatenate([ + np.mean([p.mean(axis=0) for p in preds_5sec], axis=0), # 预测均值 + np.max([p.max(axis=0) for p in preds_5sec], axis=0), # 预测最大值 + raw_feats.mean(axis=0), # 原始特征均值 + raw_feats.std(axis=0), # 原始特征标准差 + ]) + + minute_features.append(minute_feat) + + return np.array(minute_features) +``` + +### 时间序列特征工程 (基线方案) +```python +import pandas as pd +import numpy as np + +def create_sleep_features(series_df): + """ + 创建睡眠检测特征 + + 基于基线方案（银牌）的特征工程 + """ + df = series_df.copy() + + # ========== 传感器特征 ========== + # 平滑 + 一阶差分 + df['enmo_abs_diff'] = df['enmo'].diff().abs() + df['enmo'] = df['enmo_abs_diff'].rolling(window=5, center=True, min_periods=1).mean() + + df['anglez_abs_diff'] = df['anglez'].diff().abs() + df['anglez'] = df['anglez_abs_diff'].rolling(window=5, center=True, min_periods=1).mean() + + # ========== 时间特征 ========== + df['timestamp'] = pd.to_datetime(df['timestamp']) + df['hour'] = df['timestamp'].dt.hour + df['minute'] = df['timestamp'].dt.minute + df['weekday'] = df['timestamp'].dt.weekday + df['is_weekend'] = df['weekday'].isin([5, 6]).astype(int) + + # Sin/Cos 编码（周期性时间） + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + + # ========== 滚动特征 ========== + for col in ['enmo', 'anglez']: + for window in [10, 30, 60]: + df[f'{col}_rolling_mean_{window}'] = df[col].rolling(window=window, min_periods=1).mean() + df[f'{col}_rolling_std_{window}'] = df[col].rolling(window=window, min_periods=1).std() + df[f'{col}_rolling_max_{window}'] = df[col].rolling(window=window, min_periods=1).max() + df[f'{col}_rolling_min_{window}'] = df[col].rolling(window=window, min_periods=1).min() + + # ========== 交互特征 ========== + df['anglez_times_enmo'] = df['anglez_abs_diff'] * df['enmo_abs_diff'] + df['anglez_div_enmo'] = df['anglez_abs_diff'] / (df['enmo_abs_diff'] + 1e-6) + + return df +``` + +### 时间序列特征提取 + +| 方法 | 适用场景 | +|------|---------| +| **原始1D CNN** | 保留时序信息 | +| **CWT + 2D CNN** | 需要频域信息 | +| **统计特征** | 传统机器学习 | +| **Wavelet Scattering** | 信号分解 | + +--- + +## Top 10 Solutions Comparison (前 10 名方案对比分析) + +> 基于前 10 名解决方案的横向对比分析，提取共性技术和差异创新 + +### 架构分类总结 + +根据整体解决方案，前 10 名可分为两大架构流派： + +| 架构类型 | 代表排名 | 核心特点 | +|---------|---------|---------| +| **独立编码器** | 2nd, 3rd, 8th | 分别处理 EEG 和 Spectrogram，后期融合 | +| **单一编码器** | 1st, 4th, 5th, 6th, 7th, 9th, 10th | 早期合并信号，统一编码 | + +### 前 3 名详细对比 + +#### 1st Place - Team Sony (yamash, suguuuuu, kfuji, Muku) + +**核心架构：** 多模型集成 (4人独立方案) + +| 成员 | 技术 | Score | +|------|------|-------| +| yamash | 纵向双极导联 + 2D CNN (不同时长) | - | +| suguuuuu | CWT + MaxVIT (Morlet 小波) | - | +| kfuji | CWT + MaxVIT (Paul 小波) | - | +| Muku | 1D CNN 特征 + Superlet CWT + SwinV2 | CV: 0.2229 | + +**关键技术：** +- CWT (0.5-40 Hz 扩展频段) +- Entmax 替换 Softmax +- 非负线性回归集成 +- 2-Stage Training (votes ≥10) + +#### 2nd Place - COOLZ + +**核心架构：** 3D-CNN + 2D-CNN 双路模型 + +``` +输入 (16 channels EEG) + ↓ +┌─────┴─────┐ +↓ ↓ +3D-CNN 2D-CNN +(x3d-l) (EfficientNetB5) + ↓ ↓ +Spectrogram Raw EEG + └─────┬─────┘ + ↓ + Double Head + (特征融合) + ↓ + Ensemble +``` + +**关键技术：** +- **3D-CNN (x3d-l)** 处理 Spectrogram - CV: 0.21, PB: 0.25 +- **2D-CNN (EfficientNetB5)** 处理 Raw EEG - PB: 0.28 +- **双特征头**：EEG + Spectrum 特征融合 +- **不同滤波器**：MNE vs scipy.signal 增加多样性 +- **2-Stage Training**： + - Stage 1: 全数据 + loss weight = voters_num/20 + - Stage 2: votes ≥6 数据 +- **随机偏移采样**：根据 eeg_id 随机选择偏移 + +**归一化：** `x.clip(-1024, 1024) / 32` + +**最终集成权重：** [0.1, 0.1, 0.2, 0.2, 0.2, 0.2] (6 模型) + +#### 3rd Place - nvidia-dd (DIETER) + +**核心架构：** MelSpectrogram + Squeezeformer + +``` +EEG → MelSpectrogram → 2D CNN + ↓ +EEG → 1D-Convolutions → Squeezeformer + ↓ + Ensemble +``` + +**关键技术：** +- **数据质量筛选**：仅使用 6350 行高质量数据（从 100000+ 行中筛选） +- **反向 Augmentation**：发现并移除数据创建者应用的 augmentation +- **MelSpectrogram** 替代标准 Spectrogram +- **Squeezeformer** 用于时序建模 +- **信号配对**：左右脑节点一起处理 +- **归一化**：`x.clip(-1024, 1024) / 32` + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **带通滤波 (0.5-20/40 Hz)** | 1st, 2nd, 3rd | 几乎所有高分者使用 | +| **Clip 归一化** | 1st, 2nd, 3rd | `x.clip(-1024, 1024) / 32` | +| **2-Stage Training** | 1st, 2nd, 3rd | Stage 1 全数据，Stage 2 高质量样本 | +| **Votes ≥10 筛选** | 1st, 2nd, 3rd | 仅用高质量样本评估 | +| **Group K-Fold** | 1st, 2nd, 3rd | 按患者分组，防止数据泄露 | +| **Ensemble/Stacking** | 1st, 2nd, 3rd | 多模型集成 | +| **数据增强** | 1st, 2nd, 3rd | 时间偏移、通道翻转、Mixup | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st - Sony** | Entmax 替换 Softmax | LB +0.004 提升 | +| **1st - Sony** | Superlet CWT | 最高时频分辨率 | +| **2nd - COOLZ** | 3D-CNN 处理 Spectrogram | 保留通道位置信息 | +| **2nd - COOLZ** | 双特征头 (EEG + Spectrum) | 多模态融合 | +| **3rd - nvidia-dd** | 数据质量筛选 (6350→100000) | 性能提升显著 | +| **3rd - nvidia-dd** | 反向 Augmentation | 数据纯净度提升 | +| **4th - Cerberus** | 左右对称对比学习 | 位置编码 | +| **9th - ishikei** | Contrastive Learning | 特征对比 | + +### 归一化方法对比 + +| 方法 | 支持者 | 效果 | +|------|--------|------| +| **`x.clip(-1024, 1024) / 32`** | 1st, 2nd, 3rd | 最佳选择 | +| **MAD 归一化** | 3rd | 对异常值更鲁棒 | +| **Batch/Sample 归一化** | 部分尝试者 | 效果不佳 (3rd 发现) | +| **Standardize** | 低排名者 | 不推荐 | + +### 时频变换方法对比 + +| 方法 | 使用排名 | 优点 | 缺点 | +|------|---------|------|------| +| **CWT** | 1st, 4th, 5th, 6th | 多分辨率，适合非平稳信号 | 需选择小波 | +| **Superlet CWT** | 1st | 最高分辨率 | 计算成本高 | +| **MelSpectrogram** | 2nd, 3rd | 人耳感知特性 | 频率分辨率固定 | +| **STFT** | 7th, 8th, 10th | 简单易实现 | 时频权衡 | + +### 集成策略对比 + +| 排名 | 集成方法 | 模型数 | 权重确定 | +|------|---------|--------|---------| +| **1st** | 非负线性回归 | 6 (4人) | 自动学习 | +| **2nd** | 加权平均 | 6 | 手动调参 | +| **3rd** | 简单平均 | 多个 | 均等权重 | + +### 验证策略对比 + +| 策略 | 使用排名 | Votes 阈值 | 说明 | +|------|---------|------------|------| +| **≥10** | 1st, 2nd, 3rd | ≥10 | 专家 vs 大众一致意见 | +| **≥6** | 2nd | ≥6 | 较宽松 | +| **≥9** | 部分 | ≥9 | 接近专家标准 | +| **加权** | 部分 | 按投票数加权 | 少投票获得更高正则化 | + +### 频率范围选择 + +| 范围 | 使用排名 | 应用场景 | +|------|---------|---------| +| **0.5-20 Hz** | 标准, 2nd | Kaggle 默认 | +| **0.5-40 Hz** | 1st (suguuuuu) | 扩展信息，更佳结果 | +| **0.5-50 Hz** | 部分 | 包含更多高频信息 | + +### 训练 Epoch 配置 + +| 排名 | Stage 1 | Stage 2 | 说明 | +|------|---------|---------|------| +| **1st** | 5 epochs | 15 epochs | 保守选择 | +| **2nd** | 15 epochs | 5 epochs | 更长 Stage 1 | +| **3rd** | - | - | 单阶段或灵活配置 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **带通滤波 (0.5-20/40 Hz)** +2. **Clip 归一化**：`x.clip(-1024, 1024) / 32` +3. **2-Stage Training**：Stage 1 全数据，Stage 2 高质量样本 +4. **Votes ≥10 筛选**：仅用高质量样本评估 +5. **Group K-Fold**：按患者分组 +6. **Ensemble**：至少 3+ 模型集成 + +#### 推荐选项（根据情况选择） +- **时频分析**：CWT (最佳) > MelSpectrogram > STFT +- **归一化**：clip/32 (最佳) > MAD > batch/sample normalize +- **集成方法**：非负线性回归 (最佳) > 加权平均 > 简单平均 +- **模型架构**：根据数据特征选择 1D/2D/3D CNN + +#### 创新方向 +- **数据质量**：反向 Augmentation，质量筛选 +- **稀疏激活**：Entmax 替换 Softmax +- **位置编码**：3D-CNN 保留通道信息，左右对称对比 +- **特征融合**：双特征头，多模态集成 + +--- + +## Child Mind Institute - Top 10 Solutions Comparison + +> 基于前 10 名解决方案的横向对比分析，提取共性技术和差异创新 + +### 竞赛特点总结 + +与 HMS 不同，这是一个**事件检测任务**，核心挑战包括： +- **稀疏标注**：17280 步中仅 2 步有标签（0.01%） +- **分钟偏差**：真实事件总是发生在 hh:mm:00 +- **未标注事件**：存在周期性重复数据（缺失标签） +- **多 Tolerance AP**：需要同时优化多个容差窗口 + +### 前 3 名详细对比 + +#### 1st Place - shimacos vs sakami vs kami (kami, sakami0000, shimacos) + +**核心架构：** 两阶段建模 + Greedy 后处理优化 + +``` +1st Level (5秒间隔) + CNN+GRU+CNN, CNN+GRU+Transformer+CNN, + LSTM+UNet1d+UNet, LSTM+UNet1d+UNet, 1dCNN+UNet1d+Transformer + ↓ +2nd Level (1分钟间隔) + LightGBM, CatBoost, CNN+GRU, CNN+Transformer, CNN + ↓ +Post Processing (15/45秒技巧) + Daily Normalize → Greedy Search → Final Events +``` + +**关键技术：** +- **两阶段建模**：5秒检测 + 1分钟精化 +- **衰减目标**：按 tolerance_steps 加权 + epoch 衰减 +- **15/45秒技巧**：针对 tolerance 边缘优化 +- **Daily Normalization**：按天归一化 2nd level 预测 +- **Greedy 后处理**：针对 AP 指标的 greedy search + +**效果：** Public LB: 0.768 (18th) → Private LB: 0.852 (1st) + +#### 2nd Place - K-Mat + +**核心架构：** 三阶段建模 + Error Modeling + +``` +Stage 1: 事件检测 + 睡眠/清醒分类 + 多个模型预测 onset/wakeup/asleep 概率 + ↓ +Stage 2: Error Modeling (LGBM) + 基于 1st level 预测，计算 Error → Correctness → Target + 将分数差分转为分类任务 + ↓ +Stage 3: 时刻偏移 + WBF 融合 + 对 step 做时刻偏移，重新预测 + 用 WBF 整合结果 +``` + +**关键技术：** +- **Error Modeling**：将差分变化转为分类标签 +- **三阶段架构**：检测 → 重打分 → 偏移 +- **Minute Embedding**：将 minute_embedding 残差连接到输出层 +- **时刻偏移**：应对 15 分钟周期模式 +- **WBF 融合**：Weighted Box Fusion + +#### 3rd Place - cucutzik + +**核心架构：** 简洁干净的 GRU + UNET + LGB 集成 + +**关键技术：** +- **频率编码**：hour_min_onset, hour_min_wakeup +- **序列反转增强**：反转所有序列，CV +0.01 +- **目标扩展**：event step 前加2步，后加1步 +- **模型融合**：GRU (0.68) + UNET (0.2) + LGB (0.12) +- **Rolling Mean 平滑**：center=True，每隔距离取最高预测 +- **噪声检测**：相同 hour+step+anglez 重复值即为噪声 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **两阶段建模** | 1st, 2nd | 5秒检测 → 1分钟精化 | +| **分钟偏差处理** | 1st, 2nd, 3rd, 5th, 6th | 事件总是发生在整分钟 | +| **多模型集成** | 1st, 2nd, 3rd | 至少 5+ 模型 | +| **Daily Normalization** | 1st, 3rd | 按天归一化预测值 | +| **后处理优化** | 1st, 2nd, 3rd | find_peaks, NMS, greedy search | +| **多任务学习** | 2nd, 4th | onset, wakeup, asleep | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st** | 15/45秒技巧 | Public 18th → Private 1st | +| **1st** | 衰减目标 + epoch 衰减 | 使峰值更尖锐 | +| **1st** | Daily Normalization | 利用每天只有2次活动的先验 | +| **2nd** | Error Modeling | 将差分转为分类标签 | +| **2nd** | Minute Embedding | 残差连接到输出层 | +| **3rd** | 序列反转增强 | CV +0.01 | +| **3rd** | 频率编码特征 | hour_min_onset/wakeup | +| **4th** | Patch-based 模型 | 不同的 patch_size (3/4/5/6) | +| **5th** | Window Operations | left/right window 交互特征 | +| **6th** | Hash-based 周期检测 | 本地 CV +0.015 | + +### 分钟偏差处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **Minute Embedding** | 1st | 残差连接到输出层 | +| **频率编码** | 3rd | hour_min_onset, hour_min_wakeup | +| **Step 偏移** | 2nd | 偏移 step 重新预测 + WBF | +| **标签偏移** | 5th | target shift ~-11 步 | +| **特征工程** | 6th | `(step // 12) % 15` | + +### 未标注事件处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **周期性检测** | 1st | 降采样 + 相似度计算，标记日周期性 | +| **噪声检测** | 3rd | 相同 hour+step+anglez 重复值 | +| **样本加权** | 5th | 训练时权重设为 0 | +| **Hash 算法** | 6th | 散列和散列图查找重复模式 | +| **过滤序列** | 大部分 | 剔除未标注 events 出现多的序列 | + +### 后处理策略对比 + +| 排名 | 方法 | 参数 | 效果 | +|------|------|------|------| +| **1st** | Greedy + 15/45秒 | 500次迭代 | Public 18th → Private 1st | +| **2nd** | Step偏移 + WBF | 多个偏移量 | 显著提升 | +| **3rd** | Rolling Mean + find_peaks | window=12, distance=72 | 清晰方案 | +| **基线** | find_peaks + NMS | distance=72, IOU=0.995 | 银牌基础 | + +### 1st Level 模型对比 + +| 排名 | 模型数量 | 模型类型 | 集成方式 | +|------|---------|---------|---------| +| **1st** | 5 | CNN+GRU, CNN+Transformer, LSTM+UNet 等 | 加权平均 | +| **2nd** | 多个 | Spec2DCNN, PANNs, Transformer 等 | 融合后处理 | +| **3rd** | 10 | 8个GRU + 2个UNET | GRU 0.68 + UNET 0.2 + LGB 0.12 | + +### 2nd Level 模型对比 + +| 排名 | 模型类型 | 输入特征 | 说明 | +|------|---------|---------|------| +| **1st** | LGB, CatBoost, CNN+GRU 等 | 1st level 预测 + 原始特征 | 整合到整分钟 | +| **2nd** | LGBM | Error, Correctness, Top-k Accuracy | 重新打分 | +| **3rd** | LGB | 1st level 预测 | 加权融合 | + +### 数据增强策略对比 + +| 方法 | 使用排名 | 效果 | +|------|---------|------| +| **序列反转** | 3rd | CV +0.01 | +| **时间偏移** | 基线 | 标准增强 | +| **标签扩展** | 3rd | 前2步+后1步 | +| **周期性特征** | 1st | 日周期 flag | + +### 验证策略对比 + +| 策略 | 使用排名 | 说明 | +|------|---------|------| +| **Group K-Fold** | 1st, 2nd, 3rd | 按 series_id 分组 | +| **Stratified (事件数)** | 1st | 事件数 qcut(10) 分层 | +| **全部 fold 训练** | 1st | 单 fold 结果不稳定，需全 fold | +| **Trust CV** | 1st | Public 数据少且分布相似 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **两阶段建模**：5秒检测 → 1分钟精化 +2. **分钟偏差处理**：使用 minute 相关特征 +3. **Daily Normalization**：按天归一化预测值 +4. **多模型集成**：至少 5+ 模型 +5. **后处理优化**：find_peaks, NMS, greedy search +6. **Group K-Fold**：按 series_id 分组 + +#### 推荐选项（根据情况选择） +- **后处理方法**：Greedy (最佳) > WBF > NMS > find_peaks +- **2nd level 模型**：LGB/CatBoost > Neural Networks +- **分钟偏差处理**：Minute Embedding (最佳) > 频率编码 > step 偏移 +- **数据增强**：序列反转 > 时间偏移 + +#### 创新方向 +- **评估指标优化**：针对 tolerance 的 greedy search +- **Error Modeling**：将差分转为分类标签 +- **衰减目标**：按 tolerance 加权 + epoch 衰减 +- **周期性检测**：识别未标注 events + +--- + +## CMI - Detect Behavior with Sensor Data - Top 10 Solutions Comparison + +> 基于日语总结和前排方案的综合分析，提取共性技术和差异创新 + +### 竞赛特点总结 + +与之前竞赛不同，这是一个**多模态时序行为识别**任务，核心挑战包括： +- **多模态传感器融合**：IMU + THM + TOF +- **严重数据缺失**：TOF 约 60% 缺失（-1），THM 约 3-4% 缺失 +- **细粒度分类**：18 个手势类别，区分 BFRB vs 日常动作 +- **个体约束**：每个 subject × gesture × orientation 只出现一次 +- **测试集变化**：约 50% 序列仅有 IMU 数据 + +### 前 3 名详细对比 + +#### 1st Place - Devin | Ogurtsov | zyz (Andrey Ogurtsov, Devin, zyz) + +**核心架构：** 多成员协作 + 多模型集成 + +``` +Devin's part: + TOF 处理: 2×2 正方形 9 个区域平均 + TOF-only 模型也加入集成 + +Ogurtsov's part: + 数据清理: 删除 gesture 不存在的序列 + 特征工程: 从 acc（去除重力后）提取 35 个特征 + 模型: LSTM, Attention, CNN 组合 + 增强: timeshift, timistretch + 集成: 每 Fold 选择 3 run 中最佳结果 + 推理: 序列延伸降低模型相关性 + +zyz part: + RNN + CNN1D 组合 +``` + +**关键技术：** +- **TOF 图像化**：2×2 正方形 9 个区域平均降维 +- **TOF-only 集成**：单独使用 TOF 数据的模型也加入集成 +- **数据清理**：删除无效序列（如 SUBJ_019262, SUBJ_045235） +- **特征工程**：35 个特征从 acc（去除重力后）提取 +- **多模型集成**：LSTM + Attention + CNN 组合 +- **推理优化**：序列延伸降低模型相关性，提升集成效果 + +#### 2nd Place - cucutzik + +**核心架构：** 4 模型系统 + 阶段感知 Attention + +``` +4 个独立模型: + IMU rotation 缺失/存在 × THM/TOF 缺失/存在 = 4 组合 + +核心创新: + 四元数 6D 表现 (避免不连续性) + Residual SE-CNN Block + Attention + +关键技巧: + 阶段感知 Attention: + 预测 3 类阶段概率 (移动中/目标位置/手势执行中) + 每个阶段独立 Attention，概率加权 + 相位 Mixup: + 按阶段分割序列 + 同阶段内进行 Mixup + "moves to target" 阶段对齐结束点 + Pseudo Label: + 测试数据生成 pseudo-label + 小 LR (5e-5) 1 step fine-tune + +后处理: + 匈牙利算法全局最优标签分配 + 约束: subject × gesture × orientation 唯一性 +``` + +**关键技术：** +- **四元数 6D 表现**：避免四元数不连续性问题 +- **阶段感知 Attention**：分阶段独立建模和加权 +- **相位 Mixup**：按阶段分割后同阶段内 Mixup +- **Pseudo Label**：测试数据生成伪标签进行微调 +- **匈牙利算法**：全局最优标签分配（利用个体约束） + +#### 3rd Place - Team RIST + +**核心架构：** 2D-CNN + 图像化时序 + +``` +数据预处理: + 四元数平滑处理 + 符号反转扩展 + Block 扩展 + +模型: + MaxViT, ConvNeXt-V2, EfficientNetB5 等 2D-CNN + 输入: 适当尺寸的图像 + +增强: + 世界坐标系 Z 轴旋转 (-60° 到 60°) + 本地坐标系 Y 轴旋转 (-7° 到 7°) + +后处理: + 匈牙利算法全局最优标签分配 +``` + +**关键技术：** +- **时序图像化**：时序数据转换为图像，使用 2D-CNN +- **四元数处理**：平滑、符号反转、Block 扩展 +- **双重旋转增强**：世界坐标 + 本地坐标旋转 +- **多 2D-CNN 集成**：MaxViT + ConvNeXt + EfficientNetB5 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **个体约束利用** | 1st, 2nd, 3rd, 4th | subject × gesture × orientation 唯一性 | +| **数据增强** | 1st, 2nd, 3rd, 4th, 6th... | mixup, cutmix, timeshift, rotation | +| **异常数据处理** | 几乎所有 | SUBJ_019262, SUBJ_045235 删除或转换 | +| **左手系 → 右手系对齐** | 大部分 | 将左手系传感器数据转换为右手系 | +| **多模型集成** | 1st, 2nd, 3rd | 至少 3+ 模型 | +| **阶段感知建模** | 2nd, 3rd, 6th | 利用 Transition/Pause/Gesture 结构 | +| **BatchNorm（无归一化）** | 9th | 不使用 scaler，用 BatchNorm | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st** | TOF 图像化（2×2 区域平均） | 简化 TOF 处理 | +| **1st** | TOF-only 模型集成 | 单独 TOF 也有价值 | +| **1st** | 序列延伸推理 | 降低模型相关性 | +| **2nd** | 四元数 6D 表现 | 避免不连续性 | +| **2nd** | 阶段感知 Attention | 分阶段独立建模 | +| **2nd** | 相位 Mixup | 同阶段内 Mixup，对齐结束点 | +| **2nd** | Pseudo Label fine-tune | 测试数据微调 | +| **3rd** | 时序转图像 | 使用 2D-CNN 处理 | +| **3rd** | 双重旋转增强 | 世界坐标 + 本地坐标 | +| **6th** | gesture segment U-Net | 估计手势时间段 | +| **9th** | 正向 + 反向模型 | 同时训练标准分类和反向分类 | +| **13th** | 双向 Mamba | 长期时序依赖建模 | +| **13th** | Hard Margin Loss | 针对困难样本的损失 | +| **13th** | Hard Mining | 困难样本采样率提升 | + +## Child Mind Institute - 数据洞察与分析 + +### 数据特征理解 + +#### 极度稀疏的标签 + +**发现：** 17280 步（24小时）中仅有 2 步有标签 +- **标签密度**：0.01%（1/10000） +- **事件类型**：onset（入睡）+ wakeup（觉醒） +- **标注粒度**：每夜 1 个 onset + 1 个 wakeup + +**含义：** +- 传统逐帧分类方法不适用 +- 需要特殊的目标创建策略（衰减目标） +- 后处理比模型预测更重要 +- 数据增强对缓解稀疏性至关重要 + +**策略：** +- **衰减目标**：按 tolerance_steps 创建衰减的标签分布 +- **多任务学习**：同时预测 onset, wakeup, asleep +- **后处理优化**：find_peaks, NMS, greedy search +- **数据增强**：序列反转、时间偏移等 + +#### 分钟偏差模式 + +**发现：** 真实事件总是发生在 hh:mm:00 整分钟时刻 + +**数据分布（YOURI MATIOUNINE 发现）：** +``` +标签分钟数 % 15 的分布： +- 0分钟：明显峰值 +- 3分钟：明显峰值 +- 7分钟：明显峰值 +- 11分钟：明显峰值 +- 其他分钟：很少出现 +``` + +**含义：** +- 手动标注导致精度有限 +- 存在 15 分钟的周期性模式 +- 模型应该学习这种模式 + +**策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | Minute Embedding | 残差连接到输出层 | +| **2nd** | Step 偏移 | 对预测 step 做偏移后重新预测 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | +| **5th** | 标签偏移 | target shift ~-11 步 | +| **6th** | 特征工程 | `(step // 12) % 15` | + +#### 未标注事件问题 + +**发现（YOURI MATIOUNINE）：** 很多序列有明显的 events 未被标注 + +**两类情况：** +1. **日周期性重复**：缺失 events 的夜晚跟前 24 小时数据完全一样 + - 推测：组织方用历史正常数据填补了缺失数据 +2. **无法解释的缺失**：没有明显规律的缺失标注 + +**处理策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | 周期性检测 + flag | 降采样 + 相似度计算，标记日周期性 | +| **3rd** | 噪声检测 | 相同 hour+step+anglez 重复值即为噪声 | +| **5th** | 样本加权 | 训练时权重设为 0 | +| **6th** | Hash 算法 | 散列和散列图查找重复模式，本地 CV +0.015 | +| **大部分** | 过滤序列 | 剔除未标注 events 出现多的序列 | + +**1st Place 的周期性检测方法：** +```python +def detect_periodicity(series): + """检测 24 小时周期性重复""" + # 1. 降采样 + downsampled = series[::12] # 5秒 → 1分钟 + + # 2. 分割序列（按天） + n_days = len(downsampled) // 1440 # 1440 = 24小时 + daily_chunks = [downsampled[i*1440:(i+1)*1440] for i in range(n_days)] + + # 3. 计算相邻天的相似度 + for i in range(n_days - 1): + # 方法1: 元素级比较 + similarity = np.mean(daily_chunks[i] == daily_chunks[i+1]) + + # 方法2: 余弦相似度 + cos_sim = np.dot(daily_chunks[i], daily_chunks[i+1]) / ( + np.linalg.norm(daily_chunks[i]) * np.linalg.norm(daily_chunks[i+1]) + ) + + if similarity > threshold or cos_sim > threshold: + return True # 检测到周期性 + + return False +``` + +#### 多 Tolerance AP 评估指标 + +**评估方式：** +```python +tolerances = [1, 3, 5, 7.5, 10, 12.5, 15, 20, 25, 30] # 分钟 +# 对每个 tolerance，计算 AP +# 最终分数 = mean(各tolerance AP) × mean(onset AP, wakeup AP) +``` + +**关键洞察（1st Place）：** +- **预测 hh:mm:00 不好**：tolerance 5,10,15,20,25,30 时边缘漏检 +- **预测 hh:mm:30 不好**：tolerance 7.5, 12.5 时边缘漏检 +- **预测 hh:mm:15 或 hh:mm:45 最佳**：覆盖所有 tolerance + +**原理示意：** +``` +00:23:15 ← 检测事件（15秒） + ← tolerance 7.5 分 → +00:23:00 ← 真实事件（0秒） + ← tolerance 7.5 分 → +00:22:45 + +如果检测事件在 00:23:00，则 tolerance 7.5 的右边缘会漏检 +如果检测事件在 00:23:15 或 00:22:45，则正好覆盖 +``` + +#### 15分钟周期性模式 + +**发现：** events 以 15 分钟为周期重复出现 + +**数据分布：** +- **峰值分钟**：0, 3, 7, 11（间隔 3-4 分钟） +- **周期**：15 分钟 +- **含义**：可能与定时检查或记录习惯有关 + +**应对策略：** +| 排名 | 策略 | 说明 | +|------|------|------| +| **1st** | 15/45秒技巧 | 无论 1-29秒 还是31-59秒，选15/45秒代表 | +| **2nd** | Step偏移 | 对step做多个偏移，覆盖所有可能时刻 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **周期性重复** | 降采样+相似度 | 与前24小时完全相同 | 标记 periodicity flag | +| **噪声重复** | hour+step+anglez计数 | 重复值>1 | 标记 noise | +| **未标注events** | 统计每夜events数 | <2 events | 过滤或降权 | +| **数据异常** | enmo统计 | enmo值异常大 | clip到1 | + +### 关键数据洞察总结 + +1. **极度稀疏标签**：需要衰减目标和后处理优化 +2. **分钟偏差是关键**：所有前排方案都处理了这个问题 +3. **未标注events普遍存在**：周期性检测可识别 +4. **多tolerance AP需要特殊优化**：15/45秒技巧是制胜关键 +5. **评估指标与数据分布不匹配**：需要针对tolerance优化 +6. **Daily Normalization有效**：利用每天只有2次活动的先验 +7. **15分钟周期性模式**：step偏移或频率编码可利用 + +### 事件检测任务的最佳实践 + +与分类任务不同，事件检测任务的特殊考虑： + +| 方面 | 分类任务 | 事件检测任务 | +|------|---------|-------------| +| **目标创建** | 单标签 | 衰减目标（按tolerance加权） | +| **评估指标** | Accuracy/F1 | 多tolerance AP | +| **后处理** | Threshold | find_peaks, NMS, Greedy | +| **模型集成** | 概率平均 | 两阶段建模 | +| **验证策略** | K-Fold | Group K-Fold + 全fold训练 | + +--- + +## CMI - Detect Behavior 数据洞察与分析 + +### 数据特征理解 + +#### 多模态传感器数据 + +**三种传感器类型：** + +| 传感器 | 数据维度 | 特征 | 缺失率 | +|-------|---------|------|--------| +| **IMU** | 加速度计(x,y,z) + 陀螺仪(x,y,z) | 运动和旋转 | 无缺失 | +| **THM** | 5个温度传感器 | 温度分布 | ~3-4% | +| **TOF** | 5个8×8传感器阵列 | 距离映射 | ~60% | + +**IMU (Inertial Measurement Unit)：** +- 6 列：`X_accel`, `Y_accel`, `Z_accel`, `X_gyro`, `Y_gyro`, `Z_gyro` +- **重力分量**：加速度计包含重力，需去除 +- **四元数**：`orientation_X`, `orientation_Y`, `orientation_Z`, `orientation_W` + - 表示设备旋转姿态 + - **不连续性问题**：四元数在表示相同旋转时有多个值（q和-q表示相同旋转） + - **解决方案**：使用旋转矩阵前两列（6D连续表示） + +**THM (Thermopile)：** +- 5 列：`thermopile_0` ~ `thermopile_4` +- 温度传感器，用于检测物体接近 +- **缺失标记**：-1 表示缺失 +- **缺失率较低**：约3-4% + +**TOF (Time-of-Flight)：** +- 320 列：`tof_0` ~ `tof_319`（5个8×8阵列） +- 距离传感器，检测物体到设备距离 +- **缺失标记**：-1 表示缺失 +- **缺失严重**：约60%的数据为-1 +- **图像化处理**：将8×8阵列降采样为2×2特征图（1st Place创新） + +#### 严重数据缺失问题 + +**缺失分布：** +``` +TOF: ~60% 缺失 (-1 标记) +THM: ~3-4% 缺失 (-1 标记) +IMU: 无缺失 +``` + +**前排处理策略：** + +| 排名 | TOF 处理 | THM 处理 | +|------|---------|---------| +| **1st** | 2×2 pooling后标记缺失mask | 简单插值或mask | +| **2nd** | 特征工程提取有效点统计量 | 类似TOF处理 | +| **3rd** | 转图像，缺失填0 | 不使用或简单处理 | +| **其他** | 丢弃或mask | 丢弃或mask | + +**1st Place 的 TOF 处理创新：** +```python +def tof_2x2_pooling_with_mask(tof_data): + """ + TOF 数据 2×2 pooling + 缺失 mask + """ + # 每个 8×8 传感器 + for sensor_idx in range(5): + sensor = tof_data[:, sensor_idx*64:(sensor_idx+1)*64] + sensor = sensor.reshape(-1, 8, 8) + + # 2×2 pooling + pooled = sensor.reshape(-1, 4, 2, 2).mean(axis=(2, 3)) + + # 缺失 mask + mask = (sensor == -1).reshape(-1, 4, 2, 2).any(axis=(2, 3)) + + # 组合：特征 + mask + features[:, sensor_idx*4:(sensor_idx+1)*4] = pooled + features[:, 20+sensor_idx*4:20+(sensor_idx+1)*4] = mask + + return features +``` + +#### 个体约束利用 + +**关键约束：** 每个 subject × gesture × orientation 组合只出现一次 + +**含义：** +- 训练集中没有重复的 subject × gesture × orientation +- 验证时可以确保预测结果也满足这个约束 +- 可以用匈牙利算法做全局最优标签分配 + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **1st** | 匈牙利算法 | 全局最优分配，提升 LB 0.01 | +| **2nd** | 阶段感知建模 | 利用三阶段结构 | +| **其他** | 个体特征 embedding | 添加 subject embedding | + +**匈牙利算法实现（1st Place）：** +```python +from scipy.optimize import linear_sum_assignment + +def hungarian_post_process(predictions, subject_ids, sequence_ids): + """ + 利用 subject × gesture × orientation 唯一约束 + """ + # 对于每个 subject + for subject in unique(subject_ids): + # 获取该 subject 的所有预测 + mask = subject_ids == subject + preds = predictions[mask] + seqs = sequence_ids[mask] + + # 构建代价矩阵：-log(概率) + cost_matrix = -np.log(preds + 1e-10) + + # 匈牙利算法：找到最优分配 + row_ind, col_ind = linear_sum_assignment(cost_matrix) + + # 更新预测结果 + for i, j in zip(row_ind, col_ind): + predictions[mask][i] = np.zeros(n_classes) + predictions[mask][i][j] = 1.0 + + return predictions +``` + +#### 三阶段结构 + +**发现：** 行为序列有明显的三阶段结构 + +``` +Transition → Pause → Gesture +``` + +**阶段特征：** + +| 阶段 | 持续时间 | 特征 | 识别要点 | +|------|---------|------|---------| +| **Transition** | 变化 | 从上一个状态移动到手势位置 | 运动幅度大 | +| **Pause** | 短暂 | 手势开始前的准备 | 运动幅度小 | +| **Gesture** | 重复 | 核心行为模式（如咬指甲） | 周期性模式 | + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **2nd** | 阶段感知 Attention | 每个阶段独立的 attention 权重 | +| **6th** | U-Net分割 | 将手势阶段作为分割任务 | +| **其他** | 特征工程 | 添加阶段分类特征 | + +**2nd Place 阶段感知 Attention：** +```python +class PhaseAwareAttention(nn.Module): + """ + 阶段感知 Attention - 每个阶段独立建模 + """ + def __init__(self, d_model, n_heads=8): + super().__init__() + # 3个阶段 embedding + self.phase_emb = nn.Embedding(3, d_model) + + # 每个阶段独立的 attention + self.transition_attn = nn.MultiheadAttention(d_model, n_heads) + self.pause_attn = nn.MultiheadAttention(d_model, n_heads) + self.gesture_attn = nn.MultiheadAttention(d_model, n_heads) + + def forward(self, x, phase_labels): + # phase_labels: [batch, seq_len] ∈ {0, 1, 2} + batch, seq_len, d_model = x.shape + + outputs = [] + for t in range(seq_len): + phase = phase_labels[:, t] # [batch] + + if phase == 0: # Transition + attn_out, _ = self.transition_attn(x[:, t:t+1], x, x) + elif phase == 1: # Pause + attn_out, _ = self.pause_attn(x[:, t:t+1], x, x) + else: # Gesture + attn_out, _ = self.gesture_attn(x[:, t:t+1], x, x) + + outputs.append(attn_out) + + return torch.cat(outputs, dim=1) +``` + +#### BFRB vs 非BFRB 类别分布 + +**18个手势类别：** + +| 类别 | BFRB类型 | 典型行为 | +|------|---------|---------| +| 0-7 | BFRB | 咬指甲、拉头发、抠皮肤等 | +| 8-17 | 非BFRB | 拍手、挥手、其他手势 | + +**分布特点：** +- **训练集**：BFRB 和非BFRB 数量相近 +- **个体差异**：不同 subject 的手势偏好不同 +- **方向差异**：同一手势不同方向的表现不同 + +**处理策略：** +- **Phase-aware Mixup**：仅在 Gesture 阶段进行 mixup（2nd Place） +- **个体 normalization**：按 subject 做归一化 +- **类别平衡**：确保每个类别有足够样本 + +#### 测试集变化 + +**关键发现：** 测试集约50%的序列仅有 IMU 数据 + +**含义：** +- 不能过度依赖 TOF 和 THM 特征 +- 模型必须能够仅用 IMU 数据做出预测 +- 需要训练仅用 IMU 的模型作为集成成员 + +**前排应对策略：** + +| 排名 | 应对方法 | +|------|---------| +| **1st** | 训练IMU-only模型，集成时加权 | +| **2nd** | 4个模型：IMU-only, IMU+TOF, IMU+THM, All | +| **3rd** | TOF填0处理，但效果受限 | +| **其他** | 简单丢弃缺失传感器 | + +**推荐策略：** +```python +# 训练时模拟测试集情况 +def get_model_input(data): + """ + 根据可用传感器选择模型输入 + """ + has_tof = (data['tof'] != -1).any() + has_thm = (data['thm'] != -1).any() + + if has_tof and has_thm: + return model_all(data['imu'], data['tof'], data['thm']) + elif has_tof: + return model_imu_tof(data['imu'], data['tof']) + elif has_thm: + return model_imu_thm(data['imu'], data['thm']) + else: + return model_imu(data['imu']) +``` + +#### 异常数据识别 + +**两个异常 subject：** + +| Subject | 问题 | 处理策略 | +|---------|------|---------| +| **SUBJ_019262** | 数据异常，预测困难 | 训练时过滤或降权 | +| **SUBJ_045235** | 数据异常，预测困难 | 训练时过滤或降权 | + +**识别方法：** +- 训练集上该 subject 的 loss 异常高 +- 交叉验证该 subject 的预测准确率低 +- 可视化该 subject 的传感器数据，发现异常模式 + +**处理代码：** +```python +# 异常 subject 黑名单 +ANOMALY_SUBJECTS = ['SUBJ_019262', 'SUBJ_045235'] + +def filter_anomaly_subjects(dataframe): + """ + 过滤异常 subject + """ + mask = ~dataframe['subject'].isin(ANOMALY_SUBJECTS) + return dataframe[mask] +``` + +#### 左手系 vs 右手系对齐 + +**发现：** 测试集存在左手和右手两种设备朝向 + +**问题：** +- 左手系和右手系的传感器读数方向相反 +- 四元数表示旋转的方式不同 +- 直接混合训练会引入噪声 + +**解决方案（前排通用）：** +```python +def align_right_handed_system(data): + """ + 左手系 → 右手系对齐 + """ + # 翻转陀螺仪的 x, y 轴 + data['X_gyro'] = -data['X_gyro'] + data['Y_gyro'] = -data['Y_gyro'] + + # 调整四元数（取决于具体定义） + # 这里假设是绕 z 轴旋转 180 度 + data['orientation_X'] = -data['orientation_X'] + data['orientation_Y'] = -data['orientation_Y'] + + return data +``` + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **传感器缺失** | 统计-1值比例 | TOF>50%, THM>5% | mask处理或训练IMU-only模型 | +| **异常subject** | 按subject统计loss | loss > threshold | 过滤SUBJ_019262, SUBJ_045235 | +| **设备朝向** | 检测左右手系 | 四元数和陀螺仪方向 | 统一到右手系 | +| **三阶段一致性** | 检测阶段标签 | 阶段跳变 | 利用三阶段结构特征 | + +### 关键数据洞察总结 + +1. **多模态融合是关键**：IMU + THM + TOF，但测试集仅50%有完整数据 +2. **TOF 缺失严重（60%）**：需要创新处理（2×2 pooling + mask） +3. **个体约束必须利用**：subject × gesture × orientation 唯一约束可用匈牙利算法 +4. **三阶段结构重要**：Transition/Pause/Gesture，阶段感知建模有效 +5. **四元数不连续性**：需转换为6D连续表示（旋转矩阵前两列） +6. **测试集只有IMU数据**：必须训练IMU-only模型作为集成成员 +7. **异常数据需处理**：SUBJ_019262和SUBJ_045235应该过滤或降权 +8. **左手系右手系对齐**：统一到右手系避免噪声 + +### 多模态时间序列分类的最佳实践 + +与单模态分类任务不同，多模态任务的特殊考虑： + +| 方面 | 单模态任务 | 多模态任务 | +|------|-----------|-----------| +| **特征提取** | 单一特征工程 | 每个模态独立提取后融合 | +| **模型架构** | 单一编码器 | 多编码器或早期融合 | +| **缺失处理** | 插值或丢弃 | mask处理或模态specific模型 | +| **数据增强** | 简单增强 | 模态感知增强（Phase-aware Mixup） | +| **后处理** | 阈值或NMS | 利用约束（匈牙利算法） | + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/hms-2024.md b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/hms-2024.md new file mode 100644 index 0000000..87d7f53 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/kaggle-learner/references/knowledge/time-series/hms-2024.md @@ -0,0 +1,1722 @@ +# HMS - Harmful Brain Activity Classification (2024) +> Last updated: 2026-01-23 +> Source count: 1 +--- + +### HMS - Harmful Brain Activity Classification (2024) + +**竞赛背景：** +- **主办方**：Harvard Medical School (哈佛医学院) +- **目标**：自动分类患者脑电图（EEG）中的有害脑活动类型 +- **应用场景**：重症监护室的实时癫痫和异常脑活动检测 +- **社会意义**：减少神经科医生手动分析 EEG 的工作量，提高诊断速度和准确性 + +**任务描述：** +从 19 个电极记录的脑电信号中，分类 6 种有害脑活动类型： +- Seizure（癫痫发作） +- LPD（左侧周期性放电模式） +- GPD（广义周期性放电模式） +- LRDA（右侧周期性放电模式） +- Other（其他类型） +- Seizure 和其他模式的混合 + +**数据集规模：** +- 总样本数：106,800 个标注样本 +- EEG 记录：17,089 个（每个 50 秒，200 Hz 采样） +- Spectrogram：11,138 个（每个 10 分钟，从 EEG 计算的频谱图） +- 标注者：119 名大众标注者 + 20 名专家标注者 + +**数据特点：** +1. **双模态数据**：同时提供原始 EEG 信号和 Spectrogram 图像 +2. **标签不唯一**：每个样本由多人标注，输出是投票分布而非单一标签 +3. **质量不均**：投票数从 1 到 28 不等，双峰分布 +4. **时序对齐**：EEG 的中心 50 秒与 Spectrogram 的中心段对应 + +**评估指标：** +- **KL Divergence**：衡量预测分布与真实分布的差异 +- 这是非对称指标，对 0 值敏感 +- 需要预测 6 个类别的概率分布 + +**竞赛约束：** +- 代码提交：GPU/CPU 环境，最多 9 小时运行时间 +- 模型大小限制：需要考虑推理时间和内存占用 +- 数据隐私：医疗数据，需遵守隐私保护 + +**最终排名：** +- 1st Place: Team Sony - KL-Divergence **0.272332** +- 2nd Place: COOLZ - KL-Divergence ~0.275 +- 3rd Place: nvidia-dd (DIETER) - KL-Divergence ~0.280 +- 总参赛队伍：2,767 支 + +**技术趋势：** +- 前 10 名方案大量使用 CWT/MelSpectrogram 时频分析 +- 几乎所有高分者使用 Clip 归一化：`x.clip(-1024, 1024) / 32` +- 普遍采用 2-Stage Training：Stage 1 全数据，Stage 2 高质量样本 +- 集成策略是获胜关键：最少 3 个模型，最多 6+ 个模型 + +**关键创新：** +- Entmax 替换 Softmax (1st Place)：LB +0.004 提升 +- 数据质量筛选 (3rd Place)：从 100,000+ 行筛选到 6,350 行 +- 3D-CNN 处理 Spectrogram (2nd Place)：保留通道位置信息 +- Superlet CWT (1st Place)：最高时频分辨率 + +**后续影响：** +- 比赛后发表了 Nature 论文，介绍自动化分类方法 +- 该竞赛推动医疗 EEG 分析的自动化发展 +- 多个参赛方案开源，促进了技术共享 + +#### 前排方案详细技术分析 + +**1st Place - Team Sony (yamash, suguuuuu, kfuji, Muku)** + +核心技巧： +- **Entmax 替代 Softmax**：产生稀疏激活，LB +0.004 提升 +- **Superlet CWT 时频分析**：最高时频分辨率，比 STFT 更适合非平稳信号 +- **Bipolar Montage 预处理**：纵向双极导联 + 带通滤波 +- **非负线性回归集成**：4人模型集成，即使过拟合也能保持相关性 +- **2-Stage Training**：Stage 1 全数据，Stage 2 仅高质量样本 (votes ≥10) + +实现细节： +- 使用 1D EEG 信号，通过 CWT 转换为 Scalograms +- Entmax 参数 α=1.5，产生更稀疏的概率分布 +- 集成 4 个模型，使用非负线性回归组合预测 +- Group K-Fold 确保同一 patient 的 EEG 不分散 +- 最终 KL-Divergence：0.272332 + +**2nd Place - COOLZ** + +核心技巧： +- **3D-CNN 处理 Spectrogram**：保留通道位置信息 +- **时频图双路径**：同时利用原始 EEG 和 Spectrogram +- **数据增强组合**：SpecAugment + MixUp + CutMix +- **多尺度特征提取**：不同时间窗口的特征融合 + +实现细节： +- 输入：50 秒 EEG 转换的 Spectrogram（256×256×3 通道） +- 3D-CNN：3D 卷积核同时处理时间和频率维度 +- 两阶段训练：第一阶段 100 epoch，第二阶段 50 epoch +- 最终 KL-Divergence：~0.275 + +**3rd Place - nvidia-dd (DIETER)** + +核心技巧： +- **数据质量筛选**：从 100,000+ 行筛选到 6,350 行高质量样本 +- **高质量样本验证**：仅使用 votes ≥10 的样本建立验证集 +- **频域特征工程**：FFT 频谱 + 功率谱密度特征 +- **集成学习**：多模型集成 + 投票策略 + +实现细节： +- 筛选条件：votes ≥10，consensus 标签一致性高 +- 特征：时域（统计特征）+ 频域（FFT、PSD）+ 时频（CWT） +- 模型：ResNet-1D + EfficientNet-2D 双路径 +- 最终 KL-Divergence：~0.280 + +**4th Place - Grzegorz Gurdziel (ggurdziel)** + +核心技巧： +- **专家混合系统**：多个专家模型针对不同脑活动模式 +- **频带特征分离**：Alpha、Beta、Gamma 等频带独立建模 +- **时序一致性建模**：确保相邻时间步预测的连贯性 +- **双模态融合策略**：1D EEG 和 Spectrogram 的晚期融合 + +实现细节： +- 使用不同 EEG 频段训练专门模型 +- 融合 5-7 个专家模型的预测 +- 频带分离：Delta (0.5-4Hz), Theta (4-8Hz), Alpha (8-13Hz), Beta (13-30Hz), Gamma (30-100Hz) +- 最终 KL-Divergence：~0.283 + +**5th Place - cvtzf** + +核心技巧： +- **Wavelet Scattering Transform**：比 CWT 更稳定的时频表示 +- **深度残差网络**：ResNet-1D 处理 EEG 信号 +- **标签平滑策略**：处理标签模糊性 +- **模型蒸馏**：从大模型蒸馏到小模型提升推理速度 + +实现细节： +- 使用 Scattering Transform 替代传统 CWT +- ResNet-1D 架构：20-30 层深度 +- 标签平滑系数：0.1-0.2 +- 最终 KL-Divergence：~0.285 + +**6th Place - CHRTL Team** + +核心技巧： +- **注意力机制**：Self-Attention 捕获长程依赖 +- **多尺度特征提取**：并行处理不同时间窗口 +- **数据增强组合**：Time masking + Frequency masking + MixUp +- **集成策略优化**：加权平均代替简单平均 + +实现细节： +- Transformer 架构：8-12 层注意力层 +- 多尺度窗口：[5s, 10s, 20s, 50s] +- SpecAugment 风格的数据增强 +- 最终 KL-Divergence：~0.287 + +**7th Place - Tung Le (tungld)** + +核心技巧： +- **自适应频谱图**：根据 EEG 信号特性动态调整频谱参数 +- **类别平衡采样**：处理类别不平衡问题 +- **两阶段集成**：第一阶段多样模型，第二阶段精选最优组合 +- **后处理校准**：Platt Scaling 校准概率输出 + +实现细节： +- 自适应 Mel 频率：n_mels 从 64-256 动态调整 +- 过采样少数类，欠采样多数类 +- 第一阶段 20 个模型，第二阶段精选 8 个 +- Platt Scaling 校准：使用验证集学习校准参数 +- 最终 KL-Divergence：~0.289 + +**8th Place - Vialactea (Volodymyr)** + +核心技巧： +- **信号重建预处理**：去除 EEG 信号中的噪声和伪影 +- **频域归一化**：在频域进行标准化，更鲁棒 +- **时频图分割**：将长 EEG 分割为重叠片段处理 +- **模型集成多样性**：不同架构（ResNet, EfficientNet, DenseNet） + +实现细节： +- 信号重建：ICA 去除眼电、肌电伪影 +- 频域归一化：每通道独立标准化 +- 片段长度：10 秒，重叠 50% +- 5 种不同架构的模型集成 +- 最终 KL-Divergence：~0.291 + +**9th Place - Warati Kaewchada** + +核心技巧： +- **特征工程自动化**：AutoML 自动搜索最优特征组合 +- **时序建模增强**：BiLSTM + Attention 组合 +- **多视角学习**：从不同电极视角学习特征 +- **早停策略优化**：基于 KL-Divergence 的早停 + +实现细节： +- AutoML 工具：AutoGluon/TPOT +- BiLSTM：2 层双向，隐藏层 256 单位 +- 多视角：额叶区、颞叶区、顶叶区、枕叶区 +- 早停耐心值：15-20 epoch +- 最终 KL-Divergence：~0.293 + +**10th Place - Dmitry Ershov (dim)** + +核心技巧： +- **迁移学习**：从预训练 EEG 模型迁移到本任务 +- **领域适应**：适应不同患者间的 EEG 差异 +- **半监督学习**：利用未标注 EEG 数据 +- **知识蒸馏**：教师-学生模型架构 + +实现细节： +- 预训练模型：在大规模 EEG 数据集上预训练 +- 领域适应：对抗训练消除患者间差异 +- 半监督：一致性正则化 + 伪标签 +- 知识蒸馏：大教师模型 → 小学生模型（3:1 压缩） +- 最终 KL-Divergence：~0.295 + +--- + +### HMS - Harmful Brain Activity Classification (2024) - 2025-01-22 +**Source:** [Kaggle Competition](https://www.kaggle.com/competitions/hms-harmful-brain-activity-classification) +**Category:** Time Series (EEG 信号分类) +**Summary:** 患者脑波有害活动分类竞赛。数据包含 1D EEG 信号（50秒，200Hz）和 2D Spectrogram（10分钟），需要预测专家投票分布。**1st Place: Team Sony** (yamash, suguuuuu, kfuji, Muku)，KL-Divergence 0.272332。 + +**Key Techniques:** +- **CWT (连续小波变换)**: 将 EEG 转换为 Scalograms，比 STFT 更适合非平稳信号 +- **Entmax**: 用 entmax 替换 softmax 实现稀疏激活 +- **Bipolar Montage**: 纵向双极导联 + 带通滤波预处理 +- **Ensemble**: 4人模型集成，使用非负线性回归 +- **2-Stage Training**: Stage1 全数据，Stage2 仅高质量样本 (votes ≥10) + +**Results:** 1st place (KL-Divergence: 0.272332, 2767 teams) + +### CWT Scalogram 生成 (suguuuuu's approach) +```python +import numpy as np +import pywt + +def create_scalogram(eeg_data): + """ + EEG 时间序列生成 Scalogram (连续小波变换) + + 参数: + eeg_data: shape (18, 10000) - 18通道，50秒 (200Hz) + + 返回: + scalogram: shape (18, 40, 625) - 可拼接后resize到512x512 + """ + # 1. 归一化: clip到[-1024, 1024]，除以32 + x = np.clip(eeg_data, -1024, 1024) / 32.0 + + # 2. CWT参数 + scales = np.arange(1, 41) # n_scales=40 + wavelet = 'morl' # Morlet小波 + sampling_rate = 200 # fs=200 + + # 3. 对每个通道应用CWT + scalograms = [] + for channel in x: # 18个通道 + coeffs, freqs = pywt.cwt(channel, scales, wavelet, + sampling_period=1/sampling_rate) + scalograms.append(np.abs(coeffs)) + + return np.array(scalograms) # (18, 40, 625) + +# 使用示例 +# eeg_data: (18, 10000) - 18通道EEG，50秒 +# scalogram = create_scalogram(eeg_data) +# vertical_stack = np.vstack(scalograms) # 拼接后resize到512x512 +``` + +### Bipolar Montage 预处理 (yamash's approach) +```python +import numpy as np +from scipy import signal + +def longitudinal_bipolar_montage(eeg_raw): + """ + 纵向双极导联 - 从原始EEG创建差分信号 + + 参数: + eeg_raw: dict or array, shape (n_channels, n_samples) + + 返回: + bipolar: shape (18, n_samples) - 纵向拼接后的差分信号 + """ + # 10-20系统的纵向配对 + pairs = [ + ('Fp1-F7', 'Fp1', 'F7'), ('F7-T3', 'F7', 'T3'), + ('T3-T5', 'T3', 'T5'), ('T5-O1', 'T5', 'O1'), + ('Fp2-F8', 'Fp2', 'F8'), ('F8-T4', 'F8', 'T4'), + ('T4-T6', 'T4', 'T6'), ('T6-O2', 'T6', 'O2'), + ('Fz-Cz', 'Fz', 'Cz'), ('Cz-Pz', 'Cz', 'Pz'), + # ... 更多配对 + ] + + bipolar_signals = [] + for _, ch1, ch2 in pairs: + diff = eeg_raw[ch1] - eeg_raw[ch2] + bipolar_signals.append(diff) + + return np.array(bipolar_signals) + +def bandpass_filter(eeg, lowcut=0.5, highcut=40, fs=200, order=5): + """ + 带通滤波 - 仅保留特定频段 + + 参数: + eeg: shape (n_samples,) - 单通道EEG信号 + lowcut: 低频截止 (Hz) + highcut: 高频截止 (Hz) + fs: 采样率 (Hz) + """ + nyquist = 0.5 * fs + low = lowcut / nyquist + high = highcut / nyquist + b, a = signal.butter(order, [low, high], btype='band') + filtered = signal.filtfilt(b, a, eeg) + return filtered + +# 完整预处理流程 +def preprocess_eeg(eeg_raw): + """ + 完整EEG预处理流程 + """ + # 1. 双极导联 + bipolar = longitudinal_bipolar_montage(eeg_raw) + + # 2. 带通滤波 (0.5-40Hz) + filtered = np.array([bandpass_filter(ch) for ch in bipolar]) + + # 3. 归一化 + normalized = filtered / np.median(np.abs(filtered)) + + return normalized +``` + +### Entmax 替换 Softmax +```python +import torch +import torch.nn.functional as F + +def entmax(x, alpha=1.5, dim=-1): + """ + Entmax激活函数 - 比softmax更稀疏 + + 参数: + x: 输入logits + alpha: 稀疏参数 (1.0=softmax, >1.0更稀疏) + dim: 计算维度 + """ + # 简化实现，实际使用时可用pytorch-entmax库 + # 当alpha->inf时，趋近于argmax + return torch.softmax(x * alpha, dim=dim) + +# 模型输出层替换 +# 原来: F.softmax(logits, dim=-1) +# 改为: entmax(logits, alpha=1.5, dim=-1) + +# 带Entmax的分类头 +class ClassificationHead(nn.Module): + def __init__(self, in_features, num_classes, alpha=1.5): + super().__init__() + self.fc = nn.Linear(in_features, num_classes) + self.alpha = alpha + + def forward(self, x): + logits = self.fc(x) + return entmax(logits, alpha=self.alpha, dim=-1) +``` + +### 非负线性回归集成 +```python +from sklearn.linear_model import LinearRegression +import numpy as np + +class NonNegativeEnsemble: + """ + 非负线性回归集成 - 即使过拟合也能保持CV/LB相关性 + """ + def __init__(self): + self.model = LinearRegression(positive=True) # non-negative + self.weights = None + + def fit(self, predictions, targets): + """ + 参数: + predictions: (n_samples, n_models) - 各模型预测 + targets: (n_samples, n_classes) - 真实标签 + """ + self.model.fit(predictions, targets) + self.weights = self.model.coef_ # 非负权重 + return self + + def predict(self, predictions): + """加权预测""" + return predictions @ self.weights.T + +# 使用示例 +# train_preds = np.stack([model1.predict(X), model2.predict(X), ...], axis=1) +# ensemble = NonNegativeEnsemble().fit(train_preds, y_train) +# final_pred = ensemble.predict(test_preds) +``` + +### 2-Stage Training 训练流程 +```python +import torch +from torch.optim import Adam +from torch.optim.lr_scheduler import CosineAnnealingLR + +def two_stage_training(model, train_loader, hq_loader, device): + """ + 两阶段训练: Stage1全数据，Stage2高质量样本 + + 适用于标签质量不均的场景 + """ + optimizer = Adam(model.parameters(), lr=1e-3) + scheduler = CosineAnnealingLR(optimizer, T_max=20) + + # Stage 1: 全部数据 (votes > 1) + print("Stage 1: All data") + for epoch in range(5): # 5 epochs + train_one_epoch(model, train_loader, optimizer, device) + scheduler.step() + + # Stage 2: 高质量样本 (votes >= 10) + print("Stage 2: High-quality samples only") + for param_group in optimizer.param_groups: + param_group['lr'] = 1e-4 # 降低学习率 + + for epoch in range(15): # 15 epochs + train_one_epoch(model, hq_loader, optimizer, device) + scheduler.step() + +def train_one_epoch(model, dataloader, optimizer, device): + """单轮训练""" + model.train() + for batch in dataloader: + x, y = batch['x'].to(device), batch['y'].to(device) + optimizer.zero_grad() + pred = model(x) + loss = kl_div_loss(pred, y) # KL散度损失 + loss.backward() + optimizer.step() +``` + +### Group K-Fold 验证 +```python +from sklearn.model_selection import GroupKFold +import numpy as np + +def get_group_kfold_splits(df, n_splits=5, group_col='eeg_id'): + """ + Group K-Fold: 确保同一患者的EEG不会分散到train/val + + 对时间序列数据很重要 - 防止数据泄露 + """ + gkf = GroupKFold(n_splits=n_splits) + splits = [] + + for train_idx, val_idx in gkf.split(df, groups=df[group_col]): + train_df = df.iloc[train_idx] + val_df = df.iloc[val_idx] + + # 仅使用投票数>=10的样本 + train_df = train_df[train_df['total_votes'] >= 10] + val_df = val_df[val_df['total_votes'] >= 10] + + splits.append((train_df, val_df)) + + return splits +``` + +### Superlet CWT (Muku's approach) +```python +# Superlet Transform - 比STFT更高的时间/频率分辨率 +# 参考: https://github.com/antoninlff/superlet + +def superlet_cwt(eeg_signal): + """ + Superlet连续小波变换 + 提供比STFT更高的时间-频率分辨率 + """ + from superlet import superlet + + # 配置 + min_freq, max_freq = 0.5, 20.0 + base_cycle, min_order, max_order = 1, 1, 16 + + # 应用Superlet CWT + scalogram = superlet( + eeg_signal, + samplerate=200, + freqs=np.linspace(min_freq, max_freq, 40), + order_min=min_order, + order_max=max_order, + base_cycle=base_cycle + ) + + return scalogram +``` + +### 1D CNN for EEG (Muku's approach) +```python +import torch.nn as nn + +class EEGNet1D(nn.Module): + """ + 1D CNN用于EEG时间序列分类 + 参考: EEGNet, G2Net Gravitational Wave Detection + """ + def __init__(self, n_channels=18, n_classes=6): + super().__init__() + + # 1D卷积提取特征 + self.conv1d = nn.Conv1d( + n_channels, 64, + kernel_size=200, # 与采样率相同 + stride=1, + padding=0 + ) + + # 特征提取后可接2D CNN或GRU + self.feature_maps = nn.Sequential( + nn.BatchNorm1d(64), + nn.ReLU(), + ) + + # 分类头 + self.classifier = nn.Sequential( + nn.AdaptiveAvgPool1d(1), + nn.Flatten(), + nn.Linear(64, n_classes) + ) + + def forward(self, x): + # x: (batch, channels, time) + x = self.conv1d(x) + x = self.feature_maps(x) + return self.classifier(x) +``` + +### EEG预处理最佳流程 + +1. **双极导联** - 减少共模噪声 +2. **带通滤波** (0.5-40 Hz) - 保留有效频段 +3. **归一化** - MAD或标准化 +4. **CWT变换** - 生成Scalograms +5. **数据增强** - 时间偏移、滤波等 + +## Top 10 Solutions Comparison (前 10 名方案对比分析) + +> 基于前 10 名解决方案的横向对比分析，提取共性技术和差异创新 + +### 架构分类总结 + +根据整体解决方案，前 10 名可分为两大架构流派： + +| 架构类型 | 代表排名 | 核心特点 | +|---------|---------|---------| +| **独立编码器** | 2nd, 3rd, 8th | 分别处理 EEG 和 Spectrogram，后期融合 | +| **单一编码器** | 1st, 4th, 5th, 6th, 7th, 9th, 10th | 早期合并信号，统一编码 | + +### 前 3 名详细对比 + +#### 1st Place - Team Sony (yamash, suguuuuu, kfuji, Muku) + +**核心架构：** 多模型集成 (4人独立方案) + +| 成员 | 技术 | Score | +|------|------|-------| +| yamash | 纵向双极导联 + 2D CNN (不同时长) | - | +| suguuuuu | CWT + MaxVIT (Morlet 小波) | - | +| kfuji | CWT + MaxVIT (Paul 小波) | - | +| Muku | 1D CNN 特征 + Superlet CWT + SwinV2 | CV: 0.2229 | + +**关键技术：** +- CWT (0.5-40 Hz 扩展频段) +- Entmax 替换 Softmax +- 非负线性回归集成 +- 2-Stage Training (votes ≥10) + +#### 2nd Place - COOLZ + +**核心架构：** 3D-CNN + 2D-CNN 双路模型 + +``` +输入 (16 channels EEG) + ↓ +┌─────┴─────┐ +↓ ↓ +3D-CNN 2D-CNN +(x3d-l) (EfficientNetB5) + ↓ ↓ +Spectrogram Raw EEG + └─────┬─────┘ + ↓ + Double Head + (特征融合) + ↓ + Ensemble +``` + +**关键技术：** +- **3D-CNN (x3d-l)** 处理 Spectrogram - CV: 0.21, PB: 0.25 +- **2D-CNN (EfficientNetB5)** 处理 Raw EEG - PB: 0.28 +- **双特征头**：EEG + Spectrum 特征融合 +- **不同滤波器**：MNE vs scipy.signal 增加多样性 +- **2-Stage Training**： + - Stage 1: 全数据 + loss weight = voters_num/20 + - Stage 2: votes ≥6 数据 +- **随机偏移采样**：根据 eeg_id 随机选择偏移 + +**归一化：** `x.clip(-1024, 1024) / 32` + +**最终集成权重：** [0.1, 0.1, 0.2, 0.2, 0.2, 0.2] (6 模型) + +#### 3rd Place - nvidia-dd (DIETER) + +**核心架构：** MelSpectrogram + Squeezeformer + +``` +EEG → MelSpectrogram → 2D CNN + ↓ +EEG → 1D-Convolutions → Squeezeformer + ↓ + Ensemble +``` + +**关键技术：** +- **数据质量筛选**：仅使用 6350 行高质量数据（从 100000+ 行中筛选） +- **反向 Augmentation**：发现并移除数据创建者应用的 augmentation +- **MelSpectrogram** 替代标准 Spectrogram +- **Squeezeformer** 用于时序建模 +- **信号配对**：左右脑节点一起处理 +- **归一化**：`x.clip(-1024, 1024) / 32` + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **带通滤波 (0.5-20/40 Hz)** | 1st, 2nd, 3rd | 几乎所有高分者使用 | +| **Clip 归一化** | 1st, 2nd, 3rd | `x.clip(-1024, 1024) / 32` | +| **2-Stage Training** | 1st, 2nd, 3rd | Stage 1 全数据，Stage 2 高质量样本 | +| **Votes ≥10 筛选** | 1st, 2nd, 3rd | 仅用高质量样本评估 | +| **Group K-Fold** | 1st, 2nd, 3rd | 按患者分组，防止数据泄露 | +| **Ensemble/Stacking** | 1st, 2nd, 3rd | 多模型集成 | +| **数据增强** | 1st, 2nd, 3rd | 时间偏移、通道翻转、Mixup | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st - Sony** | Entmax 替换 Softmax | LB +0.004 提升 | +| **1st - Sony** | Superlet CWT | 最高时频分辨率 | +| **2nd - COOLZ** | 3D-CNN 处理 Spectrogram | 保留通道位置信息 | +| **2nd - COOLZ** | 双特征头 (EEG + Spectrum) | 多模态融合 | +| **3rd - nvidia-dd** | 数据质量筛选 (6350→100000) | 性能提升显著 | +| **3rd - nvidia-dd** | 反向 Augmentation | 数据纯净度提升 | +| **4th - Cerberus** | 左右对称对比学习 | 位置编码 | +| **9th - ishikei** | Contrastive Learning | 特征对比 | + +### 归一化方法对比 + +| 方法 | 支持者 | 效果 | +|------|--------|------| +| **`x.clip(-1024, 1024) / 32`** | 1st, 2nd, 3rd | 最佳选择 | +| **MAD 归一化** | 3rd | 对异常值更鲁棒 | +| **Batch/Sample 归一化** | 部分尝试者 | 效果不佳 (3rd 发现) | +| **Standardize** | 低排名者 | 不推荐 | + +### 时频变换方法对比 + +| 方法 | 使用排名 | 优点 | 缺点 | +|------|---------|------|------| +| **CWT** | 1st, 4th, 5th, 6th | 多分辨率，适合非平稳信号 | 需选择小波 | +| **Superlet CWT** | 1st | 最高分辨率 | 计算成本高 | +| **MelSpectrogram** | 2nd, 3rd | 人耳感知特性 | 频率分辨率固定 | +| **STFT** | 7th, 8th, 10th | 简单易实现 | 时频权衡 | + +### 集成策略对比 + +| 排名 | 集成方法 | 模型数 | 权重确定 | +|------|---------|--------|---------| +| **1st** | 非负线性回归 | 6 (4人) | 自动学习 | +| **2nd** | 加权平均 | 6 | 手动调参 | +| **3rd** | 简单平均 | 多个 | 均等权重 | + +### 验证策略对比 + +| 策略 | 使用排名 | Votes 阈值 | 说明 | +|------|---------|------------|------| +| **≥10** | 1st, 2nd, 3rd | ≥10 | 专家 vs 大众一致意见 | +| **≥6** | 2nd | ≥6 | 较宽松 | +| **≥9** | 部分 | ≥9 | 接近专家标准 | +| **加权** | 部分 | 按投票数加权 | 少投票获得更高正则化 | + +### 频率范围选择 + +| 范围 | 使用排名 | 应用场景 | +|------|---------|---------| +| **0.5-20 Hz** | 标准, 2nd | Kaggle 默认 | +| **0.5-40 Hz** | 1st (suguuuuu) | 扩展信息，更佳结果 | +| **0.5-50 Hz** | 部分 | 包含更多高频信息 | + +### 训练 Epoch 配置 + +| 排名 | Stage 1 | Stage 2 | 说明 | +|------|---------|---------|------| +| **1st** | 5 epochs | 15 epochs | 保守选择 | +| **2nd** | 15 epochs | 5 epochs | 更长 Stage 1 | +| **3rd** | - | - | 单阶段或灵活配置 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **带通滤波 (0.5-20/40 Hz)** +2. **Clip 归一化**：`x.clip(-1024, 1024) / 32` +3. **2-Stage Training**：Stage 1 全数据，Stage 2 高质量样本 +4. **Votes ≥10 筛选**：仅用高质量样本评估 +5. **Group K-Fold**：按患者分组 +6. **Ensemble**：至少 3+ 模型集成 + +#### 推荐选项（根据情况选择） +- **时频分析**：CWT (最佳) > MelSpectrogram > STFT +- **归一化**：clip/32 (最佳) > MAD > batch/sample normalize +- **集成方法**：非负线性回归 (最佳) > 加权平均 > 简单平均 +- **模型架构**：根据数据特征选择 1D/2D/3D CNN + +#### 创新方向 +- **数据质量**：反向 Augmentation，质量筛选 +- **稀疏激活**：Entmax 替换 Softmax +- **位置编码**：3D-CNN 保留通道信息，左右对称对比 +- **特征融合**：双特征头，多模态集成 + +--- + +## Child Mind Institute - Top 10 Solutions Comparison + +> 基于前 10 名解决方案的横向对比分析，提取共性技术和差异创新 + +### 竞赛特点总结 + +与 HMS 不同，这是一个**事件检测任务**，核心挑战包括： +- **稀疏标注**：17280 步中仅 2 步有标签（0.01%） +- **分钟偏差**：真实事件总是发生在 hh:mm:00 +- **未标注事件**：存在周期性重复数据（缺失标签） +- **多 Tolerance AP**：需要同时优化多个容差窗口 + +### 前 3 名详细对比 + +#### 1st Place - shimacos vs sakami vs kami (kami, sakami0000, shimacos) + +**核心架构：** 两阶段建模 + Greedy 后处理优化 + +``` +1st Level (5秒间隔) + CNN+GRU+CNN, CNN+GRU+Transformer+CNN, + LSTM+UNet1d+UNet, LSTM+UNet1d+UNet, 1dCNN+UNet1d+Transformer + ↓ +2nd Level (1分钟间隔) + LightGBM, CatBoost, CNN+GRU, CNN+Transformer, CNN + ↓ +Post Processing (15/45秒技巧) + Daily Normalize → Greedy Search → Final Events +``` + +**关键技术：** +- **两阶段建模**：5秒检测 + 1分钟精化 +- **衰减目标**：按 tolerance_steps 加权 + epoch 衰减 +- **15/45秒技巧**：针对 tolerance 边缘优化 +- **Daily Normalization**：按天归一化 2nd level 预测 +- **Greedy 后处理**：针对 AP 指标的 greedy search + +**效果：** Public LB: 0.768 (18th) → Private LB: 0.852 (1st) + +#### 2nd Place - K-Mat + +**核心架构：** 三阶段建模 + Error Modeling + +``` +Stage 1: 事件检测 + 睡眠/清醒分类 + 多个模型预测 onset/wakeup/asleep 概率 + ↓ +Stage 2: Error Modeling (LGBM) + 基于 1st level 预测，计算 Error → Correctness → Target + 将分数差分转为分类任务 + ↓ +Stage 3: 时刻偏移 + WBF 融合 + 对 step 做时刻偏移，重新预测 + 用 WBF 整合结果 +``` + +**关键技术：** +- **Error Modeling**：将差分变化转为分类标签 +- **三阶段架构**：检测 → 重打分 → 偏移 +- **Minute Embedding**：将 minute_embedding 残差连接到输出层 +- **时刻偏移**：应对 15 分钟周期模式 +- **WBF 融合**：Weighted Box Fusion + +#### 3rd Place - cucutzik + +**核心架构：** 简洁干净的 GRU + UNET + LGB 集成 + +**关键技术：** +- **频率编码**：hour_min_onset, hour_min_wakeup +- **序列反转增强**：反转所有序列，CV +0.01 +- **目标扩展**：event step 前加2步，后加1步 +- **模型融合**：GRU (0.68) + UNET (0.2) + LGB (0.12) +- **Rolling Mean 平滑**：center=True，每隔距离取最高预测 +- **噪声检测**：相同 hour+step+anglez 重复值即为噪声 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **两阶段建模** | 1st, 2nd | 5秒检测 → 1分钟精化 | +| **分钟偏差处理** | 1st, 2nd, 3rd, 5th, 6th | 事件总是发生在整分钟 | +| **多模型集成** | 1st, 2nd, 3rd | 至少 5+ 模型 | +| **Daily Normalization** | 1st, 3rd | 按天归一化预测值 | +| **后处理优化** | 1st, 2nd, 3rd | find_peaks, NMS, greedy search | +| **多任务学习** | 2nd, 4th | onset, wakeup, asleep | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st** | 15/45秒技巧 | Public 18th → Private 1st | +| **1st** | 衰减目标 + epoch 衰减 | 使峰值更尖锐 | +| **1st** | Daily Normalization | 利用每天只有2次活动的先验 | +| **2nd** | Error Modeling | 将差分转为分类标签 | +| **2nd** | Minute Embedding | 残差连接到输出层 | +| **3rd** | 序列反转增强 | CV +0.01 | +| **3rd** | 频率编码特征 | hour_min_onset/wakeup | +| **4th** | Patch-based 模型 | 不同的 patch_size (3/4/5/6) | +| **5th** | Window Operations | left/right window 交互特征 | +| **6th** | Hash-based 周期检测 | 本地 CV +0.015 | + +### 分钟偏差处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **Minute Embedding** | 1st | 残差连接到输出层 | +| **频率编码** | 3rd | hour_min_onset, hour_min_wakeup | +| **Step 偏移** | 2nd | 偏移 step 重新预测 + WBF | +| **标签偏移** | 5th | target shift ~-11 步 | +| **特征工程** | 6th | `(step // 12) % 15` | + +### 未标注事件处理对比 + +| 方法 | 使用排名 | 具体实现 | +|------|---------|---------| +| **周期性检测** | 1st | 降采样 + 相似度计算，标记日周期性 | +| **噪声检测** | 3rd | 相同 hour+step+anglez 重复值 | +| **样本加权** | 5th | 训练时权重设为 0 | +| **Hash 算法** | 6th | 散列和散列图查找重复模式 | +| **过滤序列** | 大部分 | 剔除未标注 events 出现多的序列 | + +### 后处理策略对比 + +| 排名 | 方法 | 参数 | 效果 | +|------|------|------|------| +| **1st** | Greedy + 15/45秒 | 500次迭代 | Public 18th → Private 1st | +| **2nd** | Step偏移 + WBF | 多个偏移量 | 显著提升 | +| **3rd** | Rolling Mean + find_peaks | window=12, distance=72 | 清晰方案 | +| **基线** | find_peaks + NMS | distance=72, IOU=0.995 | 银牌基础 | + +### 1st Level 模型对比 + +| 排名 | 模型数量 | 模型类型 | 集成方式 | +|------|---------|---------|---------| +| **1st** | 5 | CNN+GRU, CNN+Transformer, LSTM+UNet 等 | 加权平均 | +| **2nd** | 多个 | Spec2DCNN, PANNs, Transformer 等 | 融合后处理 | +| **3rd** | 10 | 8个GRU + 2个UNET | GRU 0.68 + UNET 0.2 + LGB 0.12 | + +### 2nd Level 模型对比 + +| 排名 | 模型类型 | 输入特征 | 说明 | +|------|---------|---------|------| +| **1st** | LGB, CatBoost, CNN+GRU 等 | 1st level 预测 + 原始特征 | 整合到整分钟 | +| **2nd** | LGBM | Error, Correctness, Top-k Accuracy | 重新打分 | +| **3rd** | LGB | 1st level 预测 | 加权融合 | + +### 数据增强策略对比 + +| 方法 | 使用排名 | 效果 | +|------|---------|------| +| **序列反转** | 3rd | CV +0.01 | +| **时间偏移** | 基线 | 标准增强 | +| **标签扩展** | 3rd | 前2步+后1步 | +| **周期性特征** | 1st | 日周期 flag | + +### 验证策略对比 + +| 策略 | 使用排名 | 说明 | +|------|---------|------| +| **Group K-Fold** | 1st, 2nd, 3rd | 按 series_id 分组 | +| **Stratified (事件数)** | 1st | 事件数 qcut(10) 分层 | +| **全部 fold 训练** | 1st | 单 fold 结果不稳定，需全 fold | +| **Trust CV** | 1st | Public 数据少且分布相似 | + +### 最佳实践总结 + +基于前 10 名对比分析，以下技术是获胜的关键： + +#### 必选项（银弹技术） +1. **两阶段建模**：5秒检测 → 1分钟精化 +2. **分钟偏差处理**：使用 minute 相关特征 +3. **Daily Normalization**：按天归一化预测值 +4. **多模型集成**：至少 5+ 模型 +5. **后处理优化**：find_peaks, NMS, greedy search +6. **Group K-Fold**：按 series_id 分组 + +#### 推荐选项（根据情况选择） +- **后处理方法**：Greedy (最佳) > WBF > NMS > find_peaks +- **2nd level 模型**：LGB/CatBoost > Neural Networks +- **分钟偏差处理**：Minute Embedding (最佳) > 频率编码 > step 偏移 +- **数据增强**：序列反转 > 时间偏移 + +#### 创新方向 +- **评估指标优化**：针对 tolerance 的 greedy search +- **Error Modeling**：将差分转为分类标签 +- **衰减目标**：按 tolerance 加权 + epoch 衰减 +- **周期性检测**：识别未标注 events + +--- + +## CMI - Detect Behavior with Sensor Data - Top 10 Solutions Comparison + +> 基于日语总结和前排方案的综合分析，提取共性技术和差异创新 + +### 竞赛特点总结 + +与之前竞赛不同，这是一个**多模态时序行为识别**任务，核心挑战包括： +- **多模态传感器融合**：IMU + THM + TOF +- **严重数据缺失**：TOF 约 60% 缺失（-1），THM 约 3-4% 缺失 +- **细粒度分类**：18 个手势类别，区分 BFRB vs 日常动作 +- **个体约束**：每个 subject × gesture × orientation 只出现一次 +- **测试集变化**：约 50% 序列仅有 IMU 数据 + +### 前 3 名详细对比 + +#### 1st Place - Devin | Ogurtsov | zyz (Andrey Ogurtsov, Devin, zyz) + +**核心架构：** 多成员协作 + 多模型集成 + +``` +Devin's part: + TOF 处理: 2×2 正方形 9 个区域平均 + TOF-only 模型也加入集成 + +Ogurtsov's part: + 数据清理: 删除 gesture 不存在的序列 + 特征工程: 从 acc（去除重力后）提取 35 个特征 + 模型: LSTM, Attention, CNN 组合 + 增强: timeshift, timistretch + 集成: 每 Fold 选择 3 run 中最佳结果 + 推理: 序列延伸降低模型相关性 + +zyz part: + RNN + CNN1D 组合 +``` + +**关键技术：** +- **TOF 图像化**：2×2 正方形 9 个区域平均降维 +- **TOF-only 集成**：单独使用 TOF 数据的模型也加入集成 +- **数据清理**：删除无效序列（如 SUBJ_019262, SUBJ_045235） +- **特征工程**：35 个特征从 acc（去除重力后）提取 +- **多模型集成**：LSTM + Attention + CNN 组合 +- **推理优化**：序列延伸降低模型相关性，提升集成效果 + +#### 2nd Place - cucutzik + +**核心架构：** 4 模型系统 + 阶段感知 Attention + +``` +4 个独立模型: + IMU rotation 缺失/存在 × THM/TOF 缺失/存在 = 4 组合 + +核心创新: + 四元数 6D 表现 (避免不连续性) + Residual SE-CNN Block + Attention + +关键技巧: + 阶段感知 Attention: + 预测 3 类阶段概率 (移动中/目标位置/手势执行中) + 每个阶段独立 Attention，概率加权 + 相位 Mixup: + 按阶段分割序列 + 同阶段内进行 Mixup + "moves to target" 阶段对齐结束点 + Pseudo Label: + 测试数据生成 pseudo-label + 小 LR (5e-5) 1 step fine-tune + +后处理: + 匈牙利算法全局最优标签分配 + 约束: subject × gesture × orientation 唯一性 +``` + +**关键技术：** +- **四元数 6D 表现**：避免四元数不连续性问题 +- **阶段感知 Attention**：分阶段独立建模和加权 +- **相位 Mixup**：按阶段分割后同阶段内 Mixup +- **Pseudo Label**：测试数据生成伪标签进行微调 +- **匈牙利算法**：全局最优标签分配（利用个体约束） + +#### 3rd Place - Team RIST + +**核心架构：** 2D-CNN + 图像化时序 + +``` +数据预处理: + 四元数平滑处理 + 符号反转扩展 + Block 扩展 + +模型: + MaxViT, ConvNeXt-V2, EfficientNetB5 等 2D-CNN + 输入: 适当尺寸的图像 + +增强: + 世界坐标系 Z 轴旋转 (-60° 到 60°) + 本地坐标系 Y 轴旋转 (-7° 到 7°) + +后处理: + 匈牙利算法全局最优标签分配 +``` + +**关键技术：** +- **时序图像化**：时序数据转换为图像，使用 2D-CNN +- **四元数处理**：平滑、符号反转、Block 扩展 +- **双重旋转增强**：世界坐标 + 本地坐标旋转 +- **多 2D-CNN 集成**：MaxViT + ConvNeXt + EfficientNetB5 + +### 共性技术（"银弹" - 高分者共同使用） + +| 技术 | 使用排名 | 说明 | +|------|---------|------| +| **个体约束利用** | 1st, 2nd, 3rd, 4th | subject × gesture × orientation 唯一性 | +| **数据增强** | 1st, 2nd, 3rd, 4th, 6th... | mixup, cutmix, timeshift, rotation | +| **异常数据处理** | 几乎所有 | SUBJ_019262, SUBJ_045235 删除或转换 | +| **左手系 → 右手系对齐** | 大部分 | 将左手系传感器数据转换为右手系 | +| **多模型集成** | 1st, 2nd, 3rd | 至少 3+ 模型 | +| **阶段感知建模** | 2nd, 3rd, 6th | 利用 Transition/Pause/Gesture 结构 | +| **BatchNorm（无归一化）** | 9th | 不使用 scaler，用 BatchNorm | + +### 差异创新（各排名者的独特贡献） + +| 排名 | 独特创新 | 影响 | +|------|---------|------| +| **1st** | TOF 图像化（2×2 区域平均） | 简化 TOF 处理 | +| **1st** | TOF-only 模型集成 | 单独 TOF 也有价值 | +| **1st** | 序列延伸推理 | 降低模型相关性 | +| **2nd** | 四元数 6D 表现 | 避免不连续性 | +| **2nd** | 阶段感知 Attention | 分阶段独立建模 | +| **2nd** | 相位 Mixup | 同阶段内 Mixup，对齐结束点 | +| **2nd** | Pseudo Label fine-tune | 测试数据微调 | +| **3rd** | 时序转图像 | 使用 2D-CNN 处理 | +| **3rd** | 双重旋转增强 | 世界坐标 + 本地坐标 | +| **6th** | gesture segment U-Net | 估计手势时间段 | +| **9th** | 正向 + 反向模型 | 同时训练标准分类和反向分类 | +| **13th** | 双向 Mamba | 长期时序依赖建模 | +| **13th** | Hard Margin Loss | 针对困难样本的损失 | +| **13th** | Hard Mining | 困难样本采样率提升 | + +## 数据洞察与分析 + +### 数据特征理解 + +#### 标签质量的双峰分布 + +**发现：** 投票数呈现双峰分布 +- **低质量样本**：1-7 票 +- **高质量样本**：10-28 票 +- **关键发现**：**没有 8-9 票的样本** + +**含义：** +- 存在两组标注者：专家组（20人）和大众组（119人） +- 低投票数样本更不可靠，标签噪声更大 +- 高投票数样本代表专家共识，质量更高 + +**策略：** +- 使用 votes ≥10 作为高质量阈值 +- 仅用高质量样本建立验证集（CV/LB 相关性接近 1:1） +- 考虑对低投票样本进行更强正则化 + +**第 3 名的洞察：** 从 100,000+ 行筛选到 6,350 行高质量数据，性能反而提升 → **"少即是多"**，精确数据胜过大量噪声数据 + +#### 标签稀疏性 + +**发现：** 训练标签中某些类别的概率为 0 +- Softmax 输出所有值 > 0（数学性质） +- 但真实标签中某些类为 0 + +**解决方案（1st Place）：** +- 使用 **Entmax** 替换 Softmax +- Entmax 可以产生真正的 0 输出（稀疏激活） +- 结果：LB +0.004 提升 + +**实现：** +```python +def entmax(x, alpha=1.5, dim=-1): + return torch.softmax(x * alpha, dim=dim) +``` + +#### 双模态数据的时间对齐 + +**数据结构：** +- **Spectrogram**：10 分钟（低时间分辨率，高频率信息） +- **EEG**：50 秒中心段（高时间分辨率，低频率信息） +- 两者中心 50 秒是同一数据 + +**洞察：** +- Spectrogram 提供全局上下文（10分钟趋势） +- EEG 提供精细时序信息（50 秒细节） +- 这是**同一数据的两种表示**，不是独立信息 + +**处理策略：** +- 大多数获胜者**专注于 EEG**（2nd, 3rd） +- 1st Place 同时使用两种并集成 +- 时频分析（CWT/MelSpectrogram）比纯时序或纯频域更有效 + +#### 信号配对的重要性 + +**发现：** +- 脑电信号存在空间关系 +- 左右对称位置的电极信号应该成对处理 +- 通道顺序影响模型性能 + +**策略（3rd Place）：** +- 将左右脑节点配对：Fp1-F7, Fp2-F8, F7-T3, F8-T4 等 +- 而不是简单按顺序堆叠 +- 这样保留了脑部空间结构的先验知识 + +#### 频率范围选择的影响 + +**对比分析：** +| 频率范围 | 使用者 | 效果 | +|---------|--------|------| +| 0.5-20 Hz | 标准, 2nd | Kaggle 默认 | +| 0.5-40 Hz | 1st (suguuuuu) | 更佳结果 | +| 0.5-50 Hz | 部分 | 高频噪声可能增加 | + +**洞察：** +- 标准范围可能遗漏重要信息 +- 扩展到 40 Hz 能捕捉更多特征 +- 但过高频率（50 Hz+）可能引入噪声 +- 需要根据具体任务调整 + +#### 归一化的选择 + +**实验发现（3rd Place）：** +- Batch/Sample 归一化：效果不佳 +- MAD 归一化：对异常值更鲁棒 +- **Clip 归一化** `x.clip(-1024, 1024) / 32`：**最佳选择**（所有前 3 名都使用） + +**为什么 Clip/32 最好？** +1. **限制极端值**：EEG 信号存在大幅伪影 +2. **固定除数 32**：简单、可复现、不过拟合 +3. **保留信息**：相比标准化，保留更多原始信号特征 + +#### 数据增强的反向工程 + +**3rd Place 的关键发现：** +- 数据创建者对训练数据应用了 augmentation +- 这些 augmentation 在测试时不存在 +- **反向工程并移除这些 augmentation** 后，模型性能显著提升 + +**启示：** +- 理解数据来源和预处理历史很重要 +- "干净"的原始数据可能比"增强"的数据更好 +- 深入数据分析能发现隐藏的改进机会 + +### 数据质量评估框架 + +基于前 10 名的分析，可以建立以下数据质量评估维度： + +| 维度 | 评估方法 | 高质量指标 | +|------|---------|-----------| +| **投票数** | 统计每个样本的专家投票数 | votes ≥10 | +| **一致性** | 计算投票分布的熵 | 高一致性（低熵） | +| **标注者类型** | 区分专家 vs 大众 | 专家共识权重更高 | +| **信号质量** | 检查伪影、噪声水平 | 低噪声、少伪影 | +| **时序完整性** | 检查 50 秒段连续性 | 无断裂、无缺失 | + +### 数据预处理最佳流程 + +综合前 10 名方案，推荐的数据预处理流程： + +```python +def preprocess_eeg_optimal(eeg_raw, votes): + """ + 基于 Top 10 方案的最佳预处理流程 + """ + # 1. 双极导联（减少共模噪声） + bipolar = longitudinal_bipolar_montage(eeg_raw) + + # 2. 带通滤波（0.5-40 Hz，扩展频段） + filtered = bandpass_filter(bipolar, lowcut=0.5, highcut=40, fs=200) + + # 3. Clip 归一化（所有前 3 名使用） + normalized = np.clip(filtered, -1024, 1024) / 32.0 + + # 4. 数据质量筛选 + if votes < 10: + # 考虑降权重或使用 Pseudo Label + weight = votes / 20.0 # 2nd Place 方法 + else: + weight = 1.0 + + return normalized, weight +``` + +### 标签处理最佳实践 + +| 技术 | 目的 | 使用排名 | +|------|------|---------| +| **投票数归一化** | 转换为概率分布 | 所有 | +| **标签平滑（加 0.02）** | 防止过度自信 | 部分 | +| **Loss 权重** | 按投票数加权样本 | 2nd | +| **Offset 加法** | 低投票数更强正则化 | 部分 | + +### 关键数据洞察总结 + +1. **质量 > 数量**：6,350 行高质量数据 > 100,000 行噪声数据 +2. **稀疏标签需要稀疏激活**：Entmax > Softmax +3. **时频分析优于纯时序或纯频域**：CWT > STFT +4. **空间先验知识很重要**：信号配对、左右对称 +5. **归一化方法影响巨大**：Clip/32 是最佳选择 +6. **理解数据来源至关重要**：反向 Augmentation 提升性能 +7. **标签质量分布不均**：需要分层训练和评估 + +--- + +## Child Mind Institute - 数据洞察与分析 + +### 数据特征理解 + +#### 极度稀疏的标签 + +**发现：** 17280 步（24小时）中仅有 2 步有标签 +- **标签密度**：0.01%（1/10000） +- **事件类型**：onset（入睡）+ wakeup（觉醒） +- **标注粒度**：每夜 1 个 onset + 1 个 wakeup + +**含义：** +- 传统逐帧分类方法不适用 +- 需要特殊的目标创建策略（衰减目标） +- 后处理比模型预测更重要 +- 数据增强对缓解稀疏性至关重要 + +**策略：** +- **衰减目标**：按 tolerance_steps 创建衰减的标签分布 +- **多任务学习**：同时预测 onset, wakeup, asleep +- **后处理优化**：find_peaks, NMS, greedy search +- **数据增强**：序列反转、时间偏移等 + +#### 分钟偏差模式 + +**发现：** 真实事件总是发生在 hh:mm:00 整分钟时刻 + +**数据分布（YOURI MATIOUNINE 发现）：** +``` +标签分钟数 % 15 的分布： +- 0分钟：明显峰值 +- 3分钟：明显峰值 +- 7分钟：明显峰值 +- 11分钟：明显峰值 +- 其他分钟：很少出现 +``` + +**含义：** +- 手动标注导致精度有限 +- 存在 15 分钟的周期性模式 +- 模型应该学习这种模式 + +**策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | Minute Embedding | 残差连接到输出层 | +| **2nd** | Step 偏移 | 对预测 step 做偏移后重新预测 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | +| **5th** | 标签偏移 | target shift ~-11 步 | +| **6th** | 特征工程 | `(step // 12) % 15` | + +#### 未标注事件问题 + +**发现（YOURI MATIOUNINE）：** 很多序列有明显的 events 未被标注 + +**两类情况：** +1. **日周期性重复**：缺失 events 的夜晚跟前 24 小时数据完全一样 + - 推测：组织方用历史正常数据填补了缺失数据 +2. **无法解释的缺失**：没有明显规律的缺失标注 + +**处理策略对比：** +| 排名 | 处理方法 | 具体实现 | +|------|---------|---------| +| **1st** | 周期性检测 + flag | 降采样 + 相似度计算，标记日周期性 | +| **3rd** | 噪声检测 | 相同 hour+step+anglez 重复值即为噪声 | +| **5th** | 样本加权 | 训练时权重设为 0 | +| **6th** | Hash 算法 | 散列和散列图查找重复模式，本地 CV +0.015 | +| **大部分** | 过滤序列 | 剔除未标注 events 出现多的序列 | + +**1st Place 的周期性检测方法：** +```python +def detect_periodicity(series): + """检测 24 小时周期性重复""" + # 1. 降采样 + downsampled = series[::12] # 5秒 → 1分钟 + + # 2. 分割序列（按天） + n_days = len(downsampled) // 1440 # 1440 = 24小时 + daily_chunks = [downsampled[i*1440:(i+1)*1440] for i in range(n_days)] + + # 3. 计算相邻天的相似度 + for i in range(n_days - 1): + # 方法1: 元素级比较 + similarity = np.mean(daily_chunks[i] == daily_chunks[i+1]) + + # 方法2: 余弦相似度 + cos_sim = np.dot(daily_chunks[i], daily_chunks[i+1]) / ( + np.linalg.norm(daily_chunks[i]) * np.linalg.norm(daily_chunks[i+1]) + ) + + if similarity > threshold or cos_sim > threshold: + return True # 检测到周期性 + + return False +``` + +#### 多 Tolerance AP 评估指标 + +**评估方式：** +```python +tolerances = [1, 3, 5, 7.5, 10, 12.5, 15, 20, 25, 30] # 分钟 +# 对每个 tolerance，计算 AP +# 最终分数 = mean(各tolerance AP) × mean(onset AP, wakeup AP) +``` + +**关键洞察（1st Place）：** +- **预测 hh:mm:00 不好**：tolerance 5,10,15,20,25,30 时边缘漏检 +- **预测 hh:mm:30 不好**：tolerance 7.5, 12.5 时边缘漏检 +- **预测 hh:mm:15 或 hh:mm:45 最佳**：覆盖所有 tolerance + +**原理示意：** +``` +00:23:15 ← 检测事件（15秒） + ← tolerance 7.5 分 → +00:23:00 ← 真实事件（0秒） + ← tolerance 7.5 分 → +00:22:45 + +如果检测事件在 00:23:00，则 tolerance 7.5 的右边缘会漏检 +如果检测事件在 00:23:15 或 00:22:45，则正好覆盖 +``` + +#### 15分钟周期性模式 + +**发现：** events 以 15 分钟为周期重复出现 + +**数据分布：** +- **峰值分钟**：0, 3, 7, 11（间隔 3-4 分钟） +- **周期**：15 分钟 +- **含义**：可能与定时检查或记录习惯有关 + +**应对策略：** +| 排名 | 策略 | 说明 | +|------|------|------| +| **1st** | 15/45秒技巧 | 无论 1-29秒 还是31-59秒，选15/45秒代表 | +| **2nd** | Step偏移 | 对step做多个偏移，覆盖所有可能时刻 | +| **3rd** | 频率编码 | hour_min_onset, hour_min_wakeup | + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **周期性重复** | 降采样+相似度 | 与前24小时完全相同 | 标记 periodicity flag | +| **噪声重复** | hour+step+anglez计数 | 重复值>1 | 标记 noise | +| **未标注events** | 统计每夜events数 | <2 events | 过滤或降权 | +| **数据异常** | enmo统计 | enmo值异常大 | clip到1 | + +### 关键数据洞察总结 + +1. **极度稀疏标签**：需要衰减目标和后处理优化 +2. **分钟偏差是关键**：所有前排方案都处理了这个问题 +3. **未标注events普遍存在**：周期性检测可识别 +4. **多tolerance AP需要特殊优化**：15/45秒技巧是制胜关键 +5. **评估指标与数据分布不匹配**：需要针对tolerance优化 +6. **Daily Normalization有效**：利用每天只有2次活动的先验 +7. **15分钟周期性模式**：step偏移或频率编码可利用 + +## CMI - Detect Behavior 数据洞察与分析 + +### 数据特征理解 + +#### 多模态传感器数据 + +**三种传感器类型：** + +| 传感器 | 数据维度 | 特征 | 缺失率 | +|-------|---------|------|--------| +| **IMU** | 加速度计(x,y,z) + 陀螺仪(x,y,z) | 运动和旋转 | 无缺失 | +| **THM** | 5个温度传感器 | 温度分布 | ~3-4% | +| **TOF** | 5个8×8传感器阵列 | 距离映射 | ~60% | + +**IMU (Inertial Measurement Unit)：** +- 6 列：`X_accel`, `Y_accel`, `Z_accel`, `X_gyro`, `Y_gyro`, `Z_gyro` +- **重力分量**：加速度计包含重力，需去除 +- **四元数**：`orientation_X`, `orientation_Y`, `orientation_Z`, `orientation_W` + - 表示设备旋转姿态 + - **不连续性问题**：四元数在表示相同旋转时有多个值（q和-q表示相同旋转） + - **解决方案**：使用旋转矩阵前两列（6D连续表示） + +**THM (Thermopile)：** +- 5 列：`thermopile_0` ~ `thermopile_4` +- 温度传感器，用于检测物体接近 +- **缺失标记**：-1 表示缺失 +- **缺失率较低**：约3-4% + +**TOF (Time-of-Flight)：** +- 320 列：`tof_0` ~ `tof_319`（5个8×8阵列） +- 距离传感器，检测物体到设备距离 +- **缺失标记**：-1 表示缺失 +- **缺失严重**：约60%的数据为-1 +- **图像化处理**：将8×8阵列降采样为2×2特征图（1st Place创新） + +#### 严重数据缺失问题 + +**缺失分布：** +``` +TOF: ~60% 缺失 (-1 标记) +THM: ~3-4% 缺失 (-1 标记) +IMU: 无缺失 +``` + +**前排处理策略：** + +| 排名 | TOF 处理 | THM 处理 | +|------|---------|---------| +| **1st** | 2×2 pooling后标记缺失mask | 简单插值或mask | +| **2nd** | 特征工程提取有效点统计量 | 类似TOF处理 | +| **3rd** | 转图像，缺失填0 | 不使用或简单处理 | +| **其他** | 丢弃或mask | 丢弃或mask | + +**1st Place 的 TOF 处理创新：** +```python +def tof_2x2_pooling_with_mask(tof_data): + """ + TOF 数据 2×2 pooling + 缺失 mask + """ + # 每个 8×8 传感器 + for sensor_idx in range(5): + sensor = tof_data[:, sensor_idx*64:(sensor_idx+1)*64] + sensor = sensor.reshape(-1, 8, 8) + + # 2×2 pooling + pooled = sensor.reshape(-1, 4, 2, 2).mean(axis=(2, 3)) + + # 缺失 mask + mask = (sensor == -1).reshape(-1, 4, 2, 2).any(axis=(2, 3)) + + # 组合：特征 + mask + features[:, sensor_idx*4:(sensor_idx+1)*4] = pooled + features[:, 20+sensor_idx*4:20+(sensor_idx+1)*4] = mask + + return features +``` + +#### 个体约束利用 + +**关键约束：** 每个 subject × gesture × orientation 组合只出现一次 + +**含义：** +- 训练集中没有重复的 subject × gesture × orientation +- 验证时可以确保预测结果也满足这个约束 +- 可以用匈牙利算法做全局最优标签分配 + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **1st** | 匈牙利算法 | 全局最优分配，提升 LB 0.01 | +| **2nd** | 阶段感知建模 | 利用三阶段结构 | +| **其他** | 个体特征 embedding | 添加 subject embedding | + +**匈牙利算法实现（1st Place）：** +```python +from scipy.optimize import linear_sum_assignment + +def hungarian_post_process(predictions, subject_ids, sequence_ids): + """ + 利用 subject × gesture × orientation 唯一约束 + """ + # 对于每个 subject + for subject in unique(subject_ids): + # 获取该 subject 的所有预测 + mask = subject_ids == subject + preds = predictions[mask] + seqs = sequence_ids[mask] + + # 构建代价矩阵：-log(概率) + cost_matrix = -np.log(preds + 1e-10) + + # 匈牙利算法：找到最优分配 + row_ind, col_ind = linear_sum_assignment(cost_matrix) + + # 更新预测结果 + for i, j in zip(row_ind, col_ind): + predictions[mask][i] = np.zeros(n_classes) + predictions[mask][i][j] = 1.0 + + return predictions +``` + +#### 三阶段结构 + +**发现：** 行为序列有明显的三阶段结构 + +``` +Transition → Pause → Gesture +``` + +**阶段特征：** + +| 阶段 | 持续时间 | 特征 | 识别要点 | +|------|---------|------|---------| +| **Transition** | 变化 | 从上一个状态移动到手势位置 | 运动幅度大 | +| **Pause** | 短暂 | 手势开始前的准备 | 运动幅度小 | +| **Gesture** | 重复 | 核心行为模式（如咬指甲） | 周期性模式 | + +**前排利用策略：** + +| 排名 | 利用方法 | 说明 | +|------|---------|------| +| **2nd** | 阶段感知 Attention | 每个阶段独立的 attention 权重 | +| **6th** | U-Net分割 | 将手势阶段作为分割任务 | +| **其他** | 特征工程 | 添加阶段分类特征 | + +**2nd Place 阶段感知 Attention：** +```python +class PhaseAwareAttention(nn.Module): + """ + 阶段感知 Attention - 每个阶段独立建模 + """ + def __init__(self, d_model, n_heads=8): + super().__init__() + # 3个阶段 embedding + self.phase_emb = nn.Embedding(3, d_model) + + # 每个阶段独立的 attention + self.transition_attn = nn.MultiheadAttention(d_model, n_heads) + self.pause_attn = nn.MultiheadAttention(d_model, n_heads) + self.gesture_attn = nn.MultiheadAttention(d_model, n_heads) + + def forward(self, x, phase_labels): + # phase_labels: [batch, seq_len] ∈ {0, 1, 2} + batch, seq_len, d_model = x.shape + + outputs = [] + for t in range(seq_len): + phase = phase_labels[:, t] # [batch] + + if phase == 0: # Transition + attn_out, _ = self.transition_attn(x[:, t:t+1], x, x) + elif phase == 1: # Pause + attn_out, _ = self.pause_attn(x[:, t:t+1], x, x) + else: # Gesture + attn_out, _ = self.gesture_attn(x[:, t:t+1], x, x) + + outputs.append(attn_out) + + return torch.cat(outputs, dim=1) +``` + +#### BFRB vs 非BFRB 类别分布 + +**18个手势类别：** + +| 类别 | BFRB类型 | 典型行为 | +|------|---------|---------| +| 0-7 | BFRB | 咬指甲、拉头发、抠皮肤等 | +| 8-17 | 非BFRB | 拍手、挥手、其他手势 | + +**分布特点：** +- **训练集**：BFRB 和非BFRB 数量相近 +- **个体差异**：不同 subject 的手势偏好不同 +- **方向差异**：同一手势不同方向的表现不同 + +**处理策略：** +- **Phase-aware Mixup**：仅在 Gesture 阶段进行 mixup（2nd Place） +- **个体 normalization**：按 subject 做归一化 +- **类别平衡**：确保每个类别有足够样本 + +#### 测试集变化 + +**关键发现：** 测试集约50%的序列仅有 IMU 数据 + +**含义：** +- 不能过度依赖 TOF 和 THM 特征 +- 模型必须能够仅用 IMU 数据做出预测 +- 需要训练仅用 IMU 的模型作为集成成员 + +**前排应对策略：** + +| 排名 | 应对方法 | +|------|---------| +| **1st** | 训练IMU-only模型，集成时加权 | +| **2nd** | 4个模型：IMU-only, IMU+TOF, IMU+THM, All | +| **3rd** | TOF填0处理，但效果受限 | +| **其他** | 简单丢弃缺失传感器 | + +**推荐策略：** +```python +# 训练时模拟测试集情况 +def get_model_input(data): + """ + 根据可用传感器选择模型输入 + """ + has_tof = (data['tof'] != -1).any() + has_thm = (data['thm'] != -1).any() + + if has_tof and has_thm: + return model_all(data['imu'], data['tof'], data['thm']) + elif has_tof: + return model_imu_tof(data['imu'], data['tof']) + elif has_thm: + return model_imu_thm(data['imu'], data['thm']) + else: + return model_imu(data['imu']) +``` + +#### 异常数据识别 + +**两个异常 subject：** + +| Subject | 问题 | 处理策略 | +|---------|------|---------| +| **SUBJ_019262** | 数据异常，预测困难 | 训练时过滤或降权 | +| **SUBJ_045235** | 数据异常，预测困难 | 训练时过滤或降权 | + +**识别方法：** +- 训练集上该 subject 的 loss 异常高 +- 交叉验证该 subject 的预测准确率低 +- 可视化该 subject 的传感器数据，发现异常模式 + +**处理代码：** +```python +# 异常 subject 黑名单 +ANOMALY_SUBJECTS = ['SUBJ_019262', 'SUBJ_045235'] + +def filter_anomaly_subjects(dataframe): + """ + 过滤异常 subject + """ + mask = ~dataframe['subject'].isin(ANOMALY_SUBJECTS) + return dataframe[mask] +``` + +#### 左手系 vs 右手系对齐 + +**发现：** 测试集存在左手和右手两种设备朝向 + +**问题：** +- 左手系和右手系的传感器读数方向相反 +- 四元数表示旋转的方式不同 +- 直接混合训练会引入噪声 + +**解决方案（前排通用）：** +```python +def align_right_handed_system(data): + """ + 左手系 → 右手系对齐 + """ + # 翻转陀螺仪的 x, y 轴 + data['X_gyro'] = -data['X_gyro'] + data['Y_gyro'] = -data['Y_gyro'] + + # 调整四元数（取决于具体定义） + # 这里假设是绕 z 轴旋转 180 度 + data['orientation_X'] = -data['orientation_X'] + data['orientation_Y'] = -data['orientation_Y'] + + return data +``` + +### 数据质量评估框架 + +基于前排方案，建立数据质量评估维度： + +| 维度 | 评估方法 | 低质量指标 | 处理策略 | +|------|---------|-----------|---------| +| **传感器缺失** | 统计-1值比例 | TOF>50%, THM>5% | mask处理或训练IMU-only模型 | +| **异常subject** | 按subject统计loss | loss > threshold | 过滤SUBJ_019262, SUBJ_045235 | +| **设备朝向** | 检测左右手系 | 四元数和陀螺仪方向 | 统一到右手系 | +| **三阶段一致性** | 检测阶段标签 | 阶段跳变 | 利用三阶段结构特征 | + +### 关键数据洞察总结 + +1. **多模态融合是关键**：IMU + THM + TOF，但测试集仅50%有完整数据 +2. **TOF 缺失严重（60%）**：需要创新处理（2×2 pooling + mask） +3. **个体约束必须利用**：subject × gesture × orientation 唯一约束可用匈牙利算法 +4. **三阶段结构重要**：Transition/Pause/Gesture，阶段感知建模有效 +5. **四元数不连续性**：需转换为6D连续表示（旋转矩阵前两列） +6. **测试集只有IMU数据**：必须训练IMU-only模型作为集成成员 +7. **异常数据需处理**：SUBJ_019262和SUBJ_045235应该过滤或降权 +8. **左手系右手系对齐**：统一到右手系避免噪声 + +### 多模态时间序列分类的最佳实践 + +与单模态分类任务不同，多模态任务的特殊考虑： + +| 方面 | 单模态任务 | 多模态任务 | +|------|-----------|-----------| +| **特征提取** | 单一特征工程 | 每个模态独立提取后融合 | +| **模型架构** | 单一编码器 | 多编码器或早期融合 | +| **缺失处理** | 插值或丢弃 | mask处理或模态specific模型 | +| **数据增强** | 简单增强 | 模态感知增强（Phase-aware Mixup） | +| **后处理** | 阈值或NMS | 利用约束（匈牙利算法） | + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/latex-conference-template-organizer/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/latex-conference-template-organizer/SKILL.md new file mode 100644 index 0000000..7cd5666 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/latex-conference-template-organizer/SKILL.md @@ -0,0 +1,509 @@ +--- +name: latex-conference-template-organizer +description: Organize messy conference LaTeX template .zip files into clean Overleaf-ready structure. Use when the user asks to "organize LaTeX template", "clean up .zip template", or "prepare Overleaf submission template". +version: 0.1.0 +--- + +# LaTeX Conference Template Organizer + +## Overview + +Transform messy conference LaTeX template .zip files into clean, Overleaf-ready submission templates. Official conference templates often contain excessive example content, instructional comments, and disorganized file structures. This skill converts them into templates ready for writing. + +## Working Mode + +**Analyze-then-confirm mode**: First analyze issues and present them to the user, then execute cleanup after confirmation. + +## Complete Workflow + +``` +Receive .zip file + ↓ +1. Extract and analyze file structure + ↓ +2. Identify main file and dependencies + ↓ +3. Diagnose issues (present to user) + ↓ +4. Ask for conference info (link/name) + ↓ +5. Wait for user confirmation of cleanup plan + ↓ +6. Execute cleanup, create output directory + ↓ +7. Generate README (with official website info) + ↓ +8. Output complete +``` + +## Step 1: Extract and Analyze + +### Extract Files + +Extract .zip to a temporary directory: + +```bash +unzip -q template.zip -d /tmp/latex-template-temp +cd /tmp/latex-template-temp +find . -type f -name "*.tex" -o -name "*.sty" -o -name "*.cls" -o -name "*.bib" +``` + +### Identify File Types + +| File Type | Purpose | +|-----------|---------| +| `.tex` | LaTeX source files | +| `.sty` / `.cls` | Style files | +| `.bib` | Bibliography database | +| `.pdf` / `.png` / `.jpg` | Image files | + +### Identify Main File + +**Common main file names:** +- `main.tex` +- `paper.tex` +- `document.tex` +- `sample-sigconf.tex` +- `template.tex` + +**Identification methods:** +1. Check if filename matches common patterns +2. Search for files containing `\documentclass` +3. If multiple candidates exist, ask user to confirm + +```bash +# Find files containing \documentclass +grep -l "\\documentclass" *.tex +``` + +## Step 2: Diagnose Issues + +Present discovered issues to the user: + +### Disorganized File Structure + +- Multi-level directory nesting +- .tex files scattered across directories +- Unclear which file is the main file + +### Redundant Content + +Detect the following patterns and flag for cleanup: +- Filenames containing: `sample`, `example`, `demo`, `test` +- Comments containing: `sample`, `example`, `template`, `delete this` + +### Dependency Issues + +- Referenced `.sty`/`.cls` files missing +- Image/table reference paths incorrect + +## Step 3: Ask for Conference Information + +Ask the user for the following information: + +```markdown +Please provide the following information (optional): + +1. **Conference submission link** (recommended): Used to extract official submission requirements +2. **Conference name**: If no link available +3. **Other special requirements**: Such as page limits, anonymity requirements, etc. +``` + +## Step 4: Present Cleanup Plan + +Present the cleanup plan to the user and wait for confirmation: + +```markdown +## Cleanup Plan + +### Issues Found +- [List diagnosed issues] + +### Cleanup Approach +1. Main file: main.tex (clean example content) +2. Section separation: text/ directory +3. Resource directories: figures/, tables/, styles/ + +### Output Structure +[Show output directory structure] + +Confirm execution? [Y/n] +``` + +## Step 5: Execute Cleanup + +### Create Output Directory Structure + +```bash +mkdir -p output/{text,figures,tables,styles} +``` + +### Clean Up Main File (main.tex) + +**Keep:** +- `\documentclass` declaration +- Required package imports +- Core configuration (e.g., anonymous mode) + +**Remove:** +- Example section content +- Verbose instructional comments +- Example author/title information + +**Add:** +- Import sections with `\input{text/XX-section}` + +**Example main.tex structure** (ACM template standard format): +```latex +\documentclass[...]{...} % Keep original template document class + +% Required packages (keep original template package declarations) + +%% ============================================================================ +%% Preamble: Before \begin{document} +%% ============================================================================ + +%% Title and author information +\title{Your Paper Title} +\author{Author Name} +\affiliation{...} + +%% Abstract (in preamble, before \maketitle) +\begin{abstract} +% TODO: Write abstract content +\end{abstract} + +%% CCS Concepts and Keywords (in preamble) +\begin{CCSXML} + + + 10010405.10010444.10010447 + Applied computing~... + 500 + + +\end{CCSXML} + +\ccsdesc[500]{Applied computing~...} +\keywords{keyword1, keyword2, keyword3} + +%% ============================================================================ +%% Document Body +%% ============================================================================ +\begin{document} + +\maketitle + +%% Section content (imported from text/) +\input{text/01-introduction} +\input{text/02-related-work} +\input{text/03-method} +\input{text/04-experiments} +\input{text/05-conclusion} + +\bibliographystyle{...} +\bibliography{references} + +\end{document} +``` + +### KDD 2026 Anonymous Submission Special Configuration + +For KDD 2026 (using ACM acmart template), add the `nonacm` option to the document class to remove footnotes: + +```latex +%% ============================================================================ +%% Document Class - KDD 2026 Anonymous Submission Configuration +%% Submission version: \documentclass[sigconf,anonymous,review,nonacm]{acmart} +%% Camera-ready: \documentclass[sigconf]{acmart} +%% ============================================================================ +\documentclass[sigconf,anonymous,review,nonacm]{acmart} + +%% ============================================================================ +%% Disable ACM metadata (submission version only) +%% ============================================================================ +\settopmatter{printacmref=false} % Disable ACM Reference Format +\setcopyright{none} % Disable copyright notice +\acmConference[]{}{}{} % Clear conference info (removes footnote) +\acmYear{} % Clear year +\acmISBN{} % Clear ISBN +\acmDOI{} % Clear DOI + +%% Content to restore for camera-ready version: +%% \acmConference[KDD '26]{Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining}{August 09--13, 2026}{Jeju, Korea} +%% \acmISBN{978-1-4503-XXXX-X/26/08} +%% \acmDOI{10.1145/nnnnnnn.nnnnnnn} +``` + +### Create Section Files (text/) + +Create independent .tex files for each section, **containing only section content** without `\begin{document}` etc.: + +**text/01-introduction.tex**: +```latex +\section{Introduction} +% TODO: Write introduction content +``` + +**text/02-related-work.tex**: +```latex +\section{Related Work} +% TODO: Write related work content +``` + +**text/03-method.tex**: +```latex +\section{Method} +% TODO: Write method content +``` + +**text/04-experiments.tex**: +```latex +\section{Experiments} +% TODO: Write experiments content +``` + +**text/05-conclusion.tex**: +```latex +\section{Conclusion} +% TODO: Write conclusion content +``` + +**Important notes:** +- **Abstract** should be placed in main.tex preamble (before `\begin{document}`), after `\maketitle` +- **Files in text/ contain only sections**, starting with `\section{...}` +- Do not include `\begin{document}` or other wrappers in text/ files + +### Copy Style Files (styles/) + +Copy all `.sty` and `.cls` files from the original template to `styles/`: + +```bash +find /tmp/latex-template-temp -type f \( -name "*.sty" -o -name "*.cls" \) -exec cp {} output/styles/ \; +``` + +**Note:** Maintain the original template's directory structure (e.g., `acmart/`), only move to `styles/`. + +### Handle Images and Tables + +```bash +# Copy image files +find /tmp/latex-template-temp -type f \( -name "*.png" -o -name "*.jpg" -o -name "*.jpeg" -o -name "*.pdf" \) -exec cp {} output/figures/ \; + +# Copy table files (if any) +find /tmp/latex-template-temp -type f -name "*.tex" | grep -i table | while read f; do cp "$f" output/tables/; done +``` + +### Create Example Table File + +**Important:** Overleaf automatically deletes empty directories. To prevent the `tables/` directory from being deleted, create an example table file: + +```bash +# Create example table file +cat > output/tables/example-table.tex << 'EOF' +% Example table file +% Can be deleted or replaced with your own tables + +\begin{table}[h] + \centering + \caption{Example Table} + \label{tab:example} + \begin{tabular}{lccc} + \toprule + Method & Metric 1 & Metric 2 & Metric 3 \\ + \midrule + Baseline & 85.3 & 12.4 & 0.92 \\ + Method A & 87.1 & 11.8 & 0.95 \\ + \textbf{Ours} & \textbf{89.4} & \textbf{10.2} & \textbf{0.97} \\ + \bottomrule + \end{tabular} +\end{table} +EOF +``` + +**Notes:** +- If the original template already has table files, this step can be skipped +- The example table is only to prevent directory deletion; it can be deleted or replaced +- Reference tables in the paper using `\input{tables/example-table.tex}` or copy table content directly into section files + +### Copy Bibliography + +```bash +# Copy .bib files +find /tmp/latex-template-temp -type f -name "*.bib" -exec cp {} output/ \; +``` + +## Step 6: Generate README + +### Information Source Priority + +1. **Conference link provided by user** → Extract using WebFetch +2. **Template file comments** → Extract from .tex files +3. **Default inference** → Infer from `\documentclass` + +### README Template + +```markdown +# [Conference Name] Submission Template + +## Template Information +- **Conference**: [Conference name] +- **Website**: [Conference link] +- **Template version**: [From template or website] +- **Document class**: [Extracted documentclass] + +## Submission Requirements + +### Page and Format +- **Page limit**: [From website or template] +- **Two-column/Single-column**: [Detect layout] +- **Font size**: [10pt/11pt etc.] + +### Anonymity Requirements +- **Blind review required**: [Detect template mode] +- **Author information handling**: [Instructions] + +### Compilation Requirements +- **Recommended compiler**: [XeLaTeX/pdfLaTeX/LuaLaTeX] +- **Special package requirements**: [If any] + +## Overleaf Usage + +### Upload Steps +1. Create a new project on Overleaf +2. Upload the entire `output/` directory +3. Set compiler to [specified compiler] +4. Click Recompile to test + +### File Description +- `main.tex` - Main file, start here +- `text/` - Section content, edit as needed +- `figures/` - Place images here +- `tables/` - Place tables here +- `styles/` - Style files, no modification needed +- `references.bib` - Bibliography database + +## Common Operations + +### Adding Images +```latex +\begin{figure}[h] + \centering + \includegraphics[width=0.8\linewidth]{figures/your-image.pdf} + \caption{Image caption} + \label{fig:your-label} +\end{figure} +``` + +### Adding Tables +```latex +\begin{table}[h] + \centering + \begin{tabular}{|c|c|} + \hline + Column 1 & Column 2 \\ + \hline + Content 1 & Content 2 \\ + \hline + \end{tabular} + \caption{Table caption} + \label{tab:your-label} +\end{table} +``` + +### Adding References +Add entries to `references.bib` and cite in text using `\cite{key}`. + +## Notes +- [Warnings extracted from template comments] +- [Important notes extracted from website] +``` + +### Extract Information from Website (if user provided a link) + +Use WebFetch to get conference submission page content and extract: +- Page limits +- Anonymity requirements +- Format requirements +- Submission deadlines + +## Step 7: Cleanup and Output + +```bash +# Clean up temporary files +rm -rf /tmp/latex-template-temp + +# Output completion message +echo "Template cleanup complete! Output directory: output/" +echo "Please upload the output/ directory to Overleaf to test compilation." +``` + +## Error Handling + +| Error Scenario | Handling Approach | +|----------------|-------------------| +| Main file not found | List all .tex files, let user choose | +| Dependency file missing | Warn user, attempt to locate from template directory | +| Cannot extract conference info | Use default info from template, mark as [To be confirmed] | +| Website inaccessible | Fall back to template comments, prompt user to fill in manually | +| Extraction failed | Prompt user to check .zip file integrity | + +## Common Conference Template Types + +| Conference | Document Class | Notes | +|------------|---------------|-------| +| **KDD (ACM SIGKDD)** | `acmart` | **Anonymous submission requires `nonacm` option to remove footnotes** | +| ACM Conferences | `acmart` | Requires anonymous mode `\acmReview{anonymous}` | +| CVPR/ICCV | `cvpr` | Two-column, strict page limits | +| NeurIPS | `neurips_2025` | Anonymous review, no page limit | +| ICLR | `iclr2025_conference` | Two-column, requires session info | +| AAAI | `aaai25` | Two-column, 8 pages + references | + +### KDD Anonymous Submission Configuration Notes + +KDD 2026 uses the ACM acmart template and requires special configuration for anonymous submission: + +**Submission version** (remove all ACM metadata footnotes): +```latex +\documentclass[sigconf,anonymous,review,nonacm]{acmart} +\settopmatter{printacmref=false} +\setcopyright{none} +\acmConference[]{}{}{} +\acmYear{} +\acmISBN{} +\acmDOI{} +``` + +**Camera-ready version** (restore ACM metadata): +```latex +\documentclass[sigconf]{acmart} +\settopmatter{printacmref=true} +\setcopyright{acmcopyright} +\acmConference[KDD '26]{...}{...}{...} +\acmYear{2026} +\acmISBN{978-1-4503-XXXX-X/26/08} +\acmDOI{10.1145/nnnnnnn.nnnnnnn} +``` + +## Quick Reference + +### Detect Document Type +```bash +# Detect document class +grep "\\documentclass" main.tex + +# Detect anonymous mode +grep -i "anonymous\|review\|blind" main.tex + +# Detect page settings +grep "pagelimit\|pageLimit\|page_limit" main.tex +``` + +### Common Cleanup Patterns +```bash +# Remove example files +rm -f sample-* example-* demo-* test-* + +# Remove temporary files +rm -f *.aux *.log *.out *.bbl *.blg +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/SKILL.md new file mode 100644 index 0000000..aee6c05 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/SKILL.md @@ -0,0 +1,554 @@ +--- +name: mcp-integration +description: This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration. +version: 0.1.0 +--- + +# MCP Integration for Claude Code Plugins + +## Overview + +Model Context Protocol (MCP) enables Claude Code plugins to integrate with external services and APIs by providing structured tool access. Use MCP integration to expose external service capabilities as tools within Claude Code. + +**Key capabilities:** +- Connect to external services (databases, APIs, file systems) +- Provide 10+ related tools from a single service +- Handle OAuth and complex authentication flows +- Bundle MCP servers with plugins for automatic setup + +## MCP Server Configuration Methods + +Plugins can bundle MCP servers in two ways: + +### Method 1: Dedicated .mcp.json (Recommended) + +Create `.mcp.json` at plugin root: + +```json +{ + "database-tools": { + "command": "${CLAUDE_PLUGIN_ROOT}/servers/db-server", + "args": ["--config", "${CLAUDE_PLUGIN_ROOT}/config.json"], + "env": { + "DB_URL": "${DB_URL}" + } + } +} +``` + +**Benefits:** +- Clear separation of concerns +- Easier to maintain +- Better for multiple servers + +### Method 2: Inline in plugin.json + +Add `mcpServers` field to plugin.json: + +```json +{ + "name": "my-plugin", + "version": "1.0.0", + "mcpServers": { + "plugin-api": { + "command": "${CLAUDE_PLUGIN_ROOT}/servers/api-server", + "args": ["--port", "8080"] + } + } +} +``` + +**Benefits:** +- Single configuration file +- Good for simple single-server plugins + +## MCP Server Types + +### stdio (Local Process) + +Execute local MCP servers as child processes. Best for local tools and custom servers. + +**Configuration:** +```json +{ + "filesystem": { + "command": "npx", + "args": ["-y", "@modelcontextprotocol/server-filesystem", "/allowed/path"], + "env": { + "LOG_LEVEL": "debug" + } + } +} +``` + +**Use cases:** +- File system access +- Local database connections +- Custom MCP servers +- NPM-packaged MCP servers + +**Process management:** +- Claude Code spawns and manages the process +- Communicates via stdin/stdout +- Terminates when Claude Code exits + +### SSE (Server-Sent Events) + +Connect to hosted MCP servers with OAuth support. Best for cloud services. + +**Configuration:** +```json +{ + "asana": { + "type": "sse", + "url": "https://mcp.asana.com/sse" + } +} +``` + +**Use cases:** +- Official hosted MCP servers (Asana, GitHub, etc.) +- Cloud services with MCP endpoints +- OAuth-based authentication +- No local installation needed + +**Authentication:** +- OAuth flows handled automatically +- User prompted on first use +- Tokens managed by Claude Code + +### HTTP (REST API) + +Connect to RESTful MCP servers with token authentication. + +**Configuration:** +```json +{ + "api-service": { + "type": "http", + "url": "https://api.example.com/mcp", + "headers": { + "Authorization": "Bearer ${API_TOKEN}", + "X-Custom-Header": "value" + } + } +} +``` + +**Use cases:** +- REST API-based MCP servers +- Token-based authentication +- Custom API backends +- Stateless interactions + +### WebSocket (Real-time) + +Connect to WebSocket MCP servers for real-time bidirectional communication. + +**Configuration:** +```json +{ + "realtime-service": { + "type": "ws", + "url": "wss://mcp.example.com/ws", + "headers": { + "Authorization": "Bearer ${TOKEN}" + } + } +} +``` + +**Use cases:** +- Real-time data streaming +- Persistent connections +- Push notifications from server +- Low-latency requirements + +## Environment Variable Expansion + +All MCP configurations support environment variable substitution: + +**${CLAUDE_PLUGIN_ROOT}** - Plugin directory (always use for portability): +```json +{ + "command": "${CLAUDE_PLUGIN_ROOT}/servers/my-server" +} +``` + +**User environment variables** - From user's shell: +```json +{ + "env": { + "API_KEY": "${MY_API_KEY}", + "DATABASE_URL": "${DB_URL}" + } +} +``` + +**Best practice:** Document all required environment variables in plugin README. + +## MCP Tool Naming + +When MCP servers provide tools, they're automatically prefixed: + +**Format:** `mcp__plugin____` + +**Example:** +- Plugin: `asana` +- Server: `asana` +- Tool: `create_task` +- **Full name:** `mcp__plugin_asana_asana__asana_create_task` + +### Using MCP Tools in Commands + +Pre-allow specific MCP tools in command frontmatter: + +```markdown +--- +allowed-tools: [ + "mcp__plugin_asana_asana__asana_create_task", + "mcp__plugin_asana_asana__asana_search_tasks" +] +--- +``` + +**Wildcard (use sparingly):** +```markdown +--- +allowed-tools: ["mcp__plugin_asana_asana__*"] +--- +``` + +**Best practice:** Pre-allow specific tools, not wildcards, for security. + +## Lifecycle Management + +**Automatic startup:** +- MCP servers start when plugin enables +- Connection established before first tool use +- Restart required for configuration changes + +**Lifecycle:** +1. Plugin loads +2. MCP configuration parsed +3. Server process started (stdio) or connection established (SSE/HTTP/WS) +4. Tools discovered and registered +5. Tools available as `mcp__plugin_...__...` + +**Viewing servers:** +Use `/mcp` command to see all servers including plugin-provided ones. + +## Authentication Patterns + +### OAuth (SSE/HTTP) + +OAuth handled automatically by Claude Code: + +```json +{ + "type": "sse", + "url": "https://mcp.example.com/sse" +} +``` + +User authenticates in browser on first use. No additional configuration needed. + +### Token-Based (Headers) + +Static or environment variable tokens: + +```json +{ + "type": "http", + "url": "https://api.example.com", + "headers": { + "Authorization": "Bearer ${API_TOKEN}" + } +} +``` + +Document required environment variables in README. + +### Environment Variables (stdio) + +Pass configuration to MCP server: + +```json +{ + "command": "python", + "args": ["-m", "my_mcp_server"], + "env": { + "DATABASE_URL": "${DB_URL}", + "API_KEY": "${API_KEY}", + "LOG_LEVEL": "info" + } +} +``` + +## Integration Patterns + +### Pattern 1: Simple Tool Wrapper + +Commands use MCP tools with user interaction: + +```markdown +# Command: create-item.md +--- +allowed-tools: ["mcp__plugin_name_server__create_item"] +--- + +Steps: +1. Gather item details from user +2. Use mcp__plugin_name_server__create_item +3. Confirm creation +``` + +**Use for:** Adding validation or preprocessing before MCP calls. + +### Pattern 2: Autonomous Agent + +Agents use MCP tools autonomously: + +```markdown +# Agent: data-analyzer.md + +Analysis Process: +1. Query data via mcp__plugin_db_server__query +2. Process and analyze results +3. Generate insights report +``` + +**Use for:** Multi-step MCP workflows without user interaction. + +### Pattern 3: Multi-Server Plugin + +Integrate multiple MCP servers: + +```json +{ + "github": { + "type": "sse", + "url": "https://mcp.github.com/sse" + }, + "jira": { + "type": "sse", + "url": "https://mcp.jira.com/sse" + } +} +``` + +**Use for:** Workflows spanning multiple services. + +## Security Best Practices + +### Use HTTPS/WSS + +Always use secure connections: + +```json +✅ "url": "https://mcp.example.com/sse" +❌ "url": "http://mcp.example.com/sse" +``` + +### Token Management + +**DO:** +- ✅ Use environment variables for tokens +- ✅ Document required env vars in README +- ✅ Let OAuth flow handle authentication + +**DON'T:** +- ❌ Hardcode tokens in configuration +- ❌ Commit tokens to git +- ❌ Share tokens in documentation + +### Permission Scoping + +Pre-allow only necessary MCP tools: + +```markdown +✅ allowed-tools: [ + "mcp__plugin_api_server__read_data", + "mcp__plugin_api_server__create_item" +] + +❌ allowed-tools: ["mcp__plugin_api_server__*"] +``` + +## Error Handling + +### Connection Failures + +Handle MCP server unavailability: +- Provide fallback behavior in commands +- Inform user of connection issues +- Check server URL and configuration + +### Tool Call Errors + +Handle failed MCP operations: +- Validate inputs before calling MCP tools +- Provide clear error messages +- Check rate limiting and quotas + +### Configuration Errors + +Validate MCP configuration: +- Test server connectivity during development +- Validate JSON syntax +- Check required environment variables + +## Performance Considerations + +### Lazy Loading + +MCP servers connect on-demand: +- Not all servers connect at startup +- First tool use triggers connection +- Connection pooling managed automatically + +### Batching + +Batch similar requests when possible: + +``` +# Good: Single query with filters +tasks = search_tasks(project="X", assignee="me", limit=50) + +# Avoid: Many individual queries +for id in task_ids: + task = get_task(id) +``` + +## Testing MCP Integration + +### Local Testing + +1. Configure MCP server in `.mcp.json` +2. Install plugin locally (`.claude-plugin/`) +3. Run `/mcp` to verify server appears +4. Test tool calls in commands +5. Check `claude --debug` logs for connection issues + +### Validation Checklist + +- [ ] MCP configuration is valid JSON +- [ ] Server URL is correct and accessible +- [ ] Required environment variables documented +- [ ] Tools appear in `/mcp` output +- [ ] Authentication works (OAuth or tokens) +- [ ] Tool calls succeed from commands +- [ ] Error cases handled gracefully + +## Debugging + +### Enable Debug Logging + +```bash +claude --debug +``` + +Look for: +- MCP server connection attempts +- Tool discovery logs +- Authentication flows +- Tool call errors + +### Common Issues + +**Server not connecting:** +- Check URL is correct +- Verify server is running (stdio) +- Check network connectivity +- Review authentication configuration + +**Tools not available:** +- Verify server connected successfully +- Check tool names match exactly +- Run `/mcp` to see available tools +- Restart Claude Code after config changes + +**Authentication failing:** +- Clear cached auth tokens +- Re-authenticate +- Check token scopes and permissions +- Verify environment variables set + +## Quick Reference + +### MCP Server Types + +| Type | Transport | Best For | Auth | +|------|-----------|----------|------| +| stdio | Process | Local tools, custom servers | Env vars | +| SSE | HTTP | Hosted services, cloud APIs | OAuth | +| HTTP | REST | API backends, token auth | Tokens | +| ws | WebSocket | Real-time, streaming | Tokens | + +### Configuration Checklist + +- [ ] Server type specified (stdio/SSE/HTTP/ws) +- [ ] Type-specific fields complete (command or url) +- [ ] Authentication configured +- [ ] Environment variables documented +- [ ] HTTPS/WSS used (not HTTP/WS) +- [ ] ${CLAUDE_PLUGIN_ROOT} used for paths + +### Best Practices + +**DO:** +- ✅ Use ${CLAUDE_PLUGIN_ROOT} for portable paths +- ✅ Document required environment variables +- ✅ Use secure connections (HTTPS/WSS) +- ✅ Pre-allow specific MCP tools in commands +- ✅ Test MCP integration before publishing +- ✅ Handle connection and tool errors gracefully + +**DON'T:** +- ❌ Hardcode absolute paths +- ❌ Commit credentials to git +- ❌ Use HTTP instead of HTTPS +- ❌ Pre-allow all tools with wildcards +- ❌ Skip error handling +- ❌ Forget to document setup + +## Additional Resources + +### Reference Files + +For detailed information, consult: + +- **`references/server-types.md`** - Deep dive on each server type +- **`references/authentication.md`** - Authentication patterns and OAuth +- **`references/tool-usage.md`** - Using MCP tools in commands and agents + +### Example Configurations + +Working examples in `examples/`: + +- **`stdio-server.json`** - Local stdio MCP server +- **`sse-server.json`** - Hosted SSE server with OAuth +- **`http-server.json`** - REST API with token auth + +### External Resources + +- **Official MCP Docs**: https://modelcontextprotocol.io/ +- **Claude Code MCP Docs**: https://docs.claude.com/en/docs/claude-code/mcp +- **MCP SDK**: @modelcontextprotocol/sdk +- **Testing**: Use `claude --debug` and `/mcp` command + +## Implementation Workflow + +To add MCP integration to a plugin: + +1. Choose MCP server type (stdio, SSE, HTTP, ws) +2. Create `.mcp.json` at plugin root with configuration +3. Use ${CLAUDE_PLUGIN_ROOT} for all file references +4. Document required environment variables in README +5. Test locally with `/mcp` command +6. Pre-allow MCP tools in relevant commands +7. Handle authentication (OAuth or tokens) +8. Test error cases (connection failures, auth errors) +9. Document MCP integration in plugin README + +Focus on stdio for custom/local servers, SSE for hosted services with OAuth. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/http-server.json b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/http-server.json new file mode 100644 index 0000000..e96448f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/http-server.json @@ -0,0 +1,20 @@ +{ + "_comment": "Example HTTP MCP server configuration for REST APIs", + "rest-api": { + "type": "http", + "url": "https://api.example.com/mcp", + "headers": { + "Authorization": "Bearer ${API_TOKEN}", + "Content-Type": "application/json", + "X-API-Version": "2024-01-01" + } + }, + "internal-service": { + "type": "http", + "url": "https://api.example.com/mcp", + "headers": { + "Authorization": "Bearer ${API_TOKEN}", + "X-Service-Name": "claude-plugin" + } + } +} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/sse-server.json b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/sse-server.json new file mode 100644 index 0000000..e6ec71c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/sse-server.json @@ -0,0 +1,19 @@ +{ + "_comment": "Example SSE MCP server configuration for hosted cloud services", + "asana": { + "type": "sse", + "url": "https://mcp.asana.com/sse" + }, + "github": { + "type": "sse", + "url": "https://mcp.github.com/sse" + }, + "custom-service": { + "type": "sse", + "url": "https://mcp.example.com/sse", + "headers": { + "X-API-Version": "v1", + "X-Client-ID": "${CLIENT_ID}" + } + } +} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/stdio-server.json b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/stdio-server.json new file mode 100644 index 0000000..60af1c6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/examples/stdio-server.json @@ -0,0 +1,26 @@ +{ + "_comment": "Example stdio MCP server configuration for local file system access", + "filesystem": { + "command": "npx", + "args": ["-y", "@modelcontextprotocol/server-filesystem", "${CLAUDE_PROJECT_DIR}"], + "env": { + "LOG_LEVEL": "info" + } + }, + "database": { + "command": "${CLAUDE_PLUGIN_ROOT}/servers/db-server.js", + "args": ["--config", "${CLAUDE_PLUGIN_ROOT}/config/db.json"], + "env": { + "DATABASE_URL": "${DATABASE_URL}", + "DB_POOL_SIZE": "10" + } + }, + "custom-tools": { + "command": "python", + "args": ["-m", "my_mcp_server", "--port", "8080"], + "env": { + "API_KEY": "${CUSTOM_API_KEY}", + "DEBUG": "false" + } + } +} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/references/authentication.md b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/references/authentication.md new file mode 100644 index 0000000..1d4ff38 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/mcp-integration/references/authentication.md @@ -0,0 +1,549 @@ +# MCP Authentication Patterns + +Complete guide to authentication methods for MCP servers in Claude Code plugins. + +## Overview + +MCP servers support multiple authentication methods depending on the server type and service requirements. Choose the method that best matches your use case and security requirements. + +## OAuth (Automatic) + +### How It Works + +Claude Code automatically handles the complete OAuth 2.0 flow for SSE and HTTP servers: + +1. User attempts to use MCP tool +2. Claude Code detects authentication needed +3. Opens browser for OAuth consent +4. User authorizes in browser +5. Tokens stored securely by Claude Code +6. Automatic token refresh + +### Configuration + +```json +{ + "service": { + "type": "sse", + "url": "https://mcp.example.com/sse" + } +} +``` + +No additional auth configuration needed! Claude Code handles everything. + +### Supported Services + +**Known OAuth-enabled MCP servers:** +- Asana: `https://mcp.asana.com/sse` +- GitHub (when available) +- Google services (when available) +- Custom OAuth servers + +### OAuth Scopes + +OAuth scopes are determined by the MCP server. Users see required scopes during the consent flow. + +**Document required scopes in your README:** +```markdown +## Authentication + +This plugin requires the following Asana permissions: +- Read tasks and projects +- Create and update tasks +- Access workspace data +``` + +### Token Storage + +Tokens are stored securely by Claude Code: +- Not accessible to plugins +- Encrypted at rest +- Automatic refresh +- Cleared on sign-out + +### Troubleshooting OAuth + +**Authentication loop:** +- Clear cached tokens (sign out and sign in) +- Check OAuth redirect URLs +- Verify server OAuth configuration + +**Scope issues:** +- User may need to re-authorize for new scopes +- Check server documentation for required scopes + +**Token expiration:** +- Claude Code auto-refreshes +- If refresh fails, prompts re-authentication + +## Token-Based Authentication + +### Bearer Tokens + +Most common for HTTP and WebSocket servers. + +**Configuration:** +```json +{ + "api": { + "type": "http", + "url": "https://api.example.com/mcp", + "headers": { + "Authorization": "Bearer ${API_TOKEN}" + } + } +} +``` + +**Environment variable:** +```bash +export API_TOKEN="your-secret-token-here" +``` + +### API Keys + +Alternative to Bearer tokens, often in custom headers. + +**Configuration:** +```json +{ + "api": { + "type": "http", + "url": "https://api.example.com/mcp", + "headers": { + "X-API-Key": "${API_KEY}", + "X-API-Secret": "${API_SECRET}" + } + } +} +``` + +### Custom Headers + +Services may use custom authentication headers. + +**Configuration:** +```json +{ + "service": { + "type": "sse", + "url": "https://mcp.example.com/sse", + "headers": { + "X-Auth-Token": "${AUTH_TOKEN}", + "X-User-ID": "${USER_ID}", + "X-Tenant-ID": "${TENANT_ID}" + } + } +} +``` + +### Documenting Token Requirements + +Always document in your README: + +```markdown +## Setup + +### Required Environment Variables + +Set these environment variables before using the plugin: + +\`\`\`bash +export API_TOKEN="your-token-here" +export API_SECRET="your-secret-here" +\`\`\` + +### Obtaining Tokens + +1. Visit https://api.example.com/tokens +2. Create a new API token +3. Copy the token and secret +4. Set environment variables as shown above + +### Token Permissions + +The API token needs the following permissions: +- Read access to resources +- Write access for creating items +- Delete access (optional, for cleanup operations) +\`\`\` +``` + +## Environment Variable Authentication (stdio) + +### Passing Credentials to Server + +For stdio servers, pass credentials via environment variables: + +```json +{ + "database": { + "command": "python", + "args": ["-m", "mcp_server_db"], + "env": { + "DATABASE_URL": "${DATABASE_URL}", + "DB_USER": "${DB_USER}", + "DB_PASSWORD": "${DB_PASSWORD}" + } + } +} +``` + +### User Environment Variables + +```bash +# User sets these in their shell +export DATABASE_URL="postgresql://localhost/mydb" +export DB_USER="myuser" +export DB_PASSWORD="mypassword" +``` + +### Documentation Template + +```markdown +## Database Configuration + +Set these environment variables: + +\`\`\`bash +export DATABASE_URL="postgresql://host:port/database" +export DB_USER="username" +export DB_PASSWORD="password" +\`\`\` + +Or create a `.env` file (add to `.gitignore`): + +\`\`\` +DATABASE_URL=postgresql://localhost:5432/mydb +DB_USER=myuser +DB_PASSWORD=mypassword +\`\`\` + +Load with: \`source .env\` or \`export $(cat .env | xargs)\` +\`\`\` +``` + +## Dynamic Headers + +### Headers Helper Script + +For tokens that change or expire, use a helper script: + +```json +{ + "api": { + "type": "sse", + "url": "https://api.example.com", + "headersHelper": "${CLAUDE_PLUGIN_ROOT}/scripts/get-headers.sh" + } +} +``` + +**Script (get-headers.sh):** +```bash +#!/bin/bash +# Generate dynamic authentication headers + +# Fetch fresh token +TOKEN=$(get-fresh-token-from-somewhere) + +# Output JSON headers +cat <___`. Use these tools in commands and agents just like built-in Claude Code tools. + +## Tool Naming Convention + +### Format + +``` +mcp__plugin____ +``` + +### Examples + +**Asana plugin with asana server:** +- `mcp__plugin_asana_asana__asana_create_task` +- `mcp__plugin_asana_asana__asana_search_tasks` +- `mcp__plugin_asana_asana__asana_get_project` + +**Custom plugin with database server:** +- `mcp__plugin_myplug_database__query` +- `mcp__plugin_myplug_database__execute` +- `mcp__plugin_myplug_database__list_tables` + +### Discovering Tool Names + +**Use `/mcp` command:** +```bash +/mcp +``` + +This shows: +- All available MCP servers +- Tools provided by each server +- Tool schemas and descriptions +- Full tool names for use in configuration + +## Using Tools in Commands + +### Pre-Allowing Tools + +Specify MCP tools in command frontmatter: + +```markdown +--- +description: Create a new Asana task +allowed-tools: [ + "mcp__plugin_asana_asana__asana_create_task" +] +--- + +# Create Task Command + +To create a task: +1. Gather task details from user +2. Use mcp__plugin_asana_asana__asana_create_task with the details +3. Confirm creation to user +``` + +### Multiple Tools + +```markdown +--- +allowed-tools: [ + "mcp__plugin_asana_asana__asana_create_task", + "mcp__plugin_asana_asana__asana_search_tasks", + "mcp__plugin_asana_asana__asana_get_project" +] +--- +``` + +### Wildcard (Use Sparingly) + +```markdown +--- +allowed-tools: ["mcp__plugin_asana_asana__*"] +--- +``` + +**Caution:** Only use wildcards if the command truly needs access to all tools from a server. + +### Tool Usage in Command Instructions + +**Example command:** +```markdown +--- +description: Search and create Asana tasks +allowed-tools: [ + "mcp__plugin_asana_asana__asana_search_tasks", + "mcp__plugin_asana_asana__asana_create_task" +] +--- + +# Asana Task Management + +## Searching Tasks + +To search for tasks: +1. Use mcp__plugin_asana_asana__asana_search_tasks +2. Provide search filters (assignee, project, etc.) +3. Display results to user + +## Creating Tasks + +To create a task: +1. Gather task details: + - Title (required) + - Description + - Project + - Assignee + - Due date +2. Use mcp__plugin_asana_asana__asana_create_task +3. Show confirmation with task link +``` + +## Using Tools in Agents + +### Agent Configuration + +Agents can use MCP tools autonomously without pre-allowing them: + +```markdown +--- +name: asana-status-updater +description: This agent should be used when the user asks to "update Asana status", "generate project report", or "sync Asana tasks" +model: inherit +color: blue +--- + +## Role + +Autonomous agent for generating Asana project status reports. + +## Process + +1. **Query tasks**: Use mcp__plugin_asana_asana__asana_search_tasks to get all tasks +2. **Analyze progress**: Calculate completion rates and identify blockers +3. **Generate report**: Create formatted status update +4. **Update Asana**: Use mcp__plugin_asana_asana__asana_create_comment to post report + +## Available Tools + +The agent has access to all Asana MCP tools without pre-approval. +``` + +### Agent Tool Access + +Agents have broader tool access than commands: +- Can use any tool Claude determines is necessary +- Don't need pre-allowed lists +- Should document which tools they typically use + +## Tool Call Patterns + +### Pattern 1: Simple Tool Call + +Single tool call with validation: + +```markdown +Steps: +1. Validate user provided required fields +2. Call mcp__plugin_api_server__create_item with validated data +3. Check for errors +4. Display confirmation +``` + +### Pattern 2: Sequential Tools + +Chain multiple tool calls: + +```markdown +Steps: +1. Search for existing items: mcp__plugin_api_server__search +2. If not found, create new: mcp__plugin_api_server__create +3. Add metadata: mcp__plugin_api_server__update_metadata +4. Return final item ID +``` + +### Pattern 3: Batch Operations + +Multiple calls with same tool: + +```markdown +Steps: +1. Get list of items to process +2. For each item: + - Call mcp__plugin_api_server__update_item + - Track success/failure +3. Report results summary +``` + +### Pattern 4: Error Handling + +Graceful error handling: + +```markdown +Steps: +1. Try to call mcp__plugin_api_server__get_data +2. If error (rate limit, network, etc.): + - Wait and retry (max 3 attempts) + - If still failing, inform user + - Suggest checking configuration +3. On success, process data +``` + +## Tool Parameters + +### Understanding Tool Schemas + +Each MCP tool has a schema defining its parameters. View with `/mcp`. + +**Example schema:** +```json +{ + "name": "asana_create_task", + "description": "Create a new Asana task", + "inputSchema": { + "type": "object", + "properties": { + "name": { + "type": "string", + "description": "Task title" + }, + "notes": { + "type": "string", + "description": "Task description" + }, + "workspace": { + "type": "string", + "description": "Workspace GID" + } + }, + "required": ["name", "workspace"] + } +} +``` + +### Calling Tools with Parameters + +Claude automatically structures tool calls based on schema: + +```typescript +// Claude generates this internally +{ + toolName: "mcp__plugin_asana_asana__asana_create_task", + input: { + name: "Review PR #123", + notes: "Code review for new feature", + workspace: "12345", + assignee: "67890", + due_on: "2025-01-15" + } +} +``` + +### Parameter Validation + +**In commands, validate before calling:** + +```markdown +Steps: +1. Check required parameters: + - Title is not empty + - Workspace ID is provided + - Due date is valid format (YYYY-MM-DD) +2. If validation fails, ask user to provide missing data +3. If validation passes, call MCP tool +4. Handle tool errors gracefully +``` + +## Response Handling + +### Success Responses + +```markdown +Steps: +1. Call MCP tool +2. On success: + - Extract relevant data from response + - Format for user display + - Provide confirmation message + - Include relevant links or IDs +``` + +### Error Responses + +```markdown +Steps: +1. Call MCP tool +2. On error: + - Check error type (auth, rate limit, validation, etc.) + - Provide helpful error message + - Suggest remediation steps + - Don't expose internal error details to user +``` + +### Partial Success + +```markdown +Steps: +1. Batch operation with multiple MCP calls +2. Track successes and failures separately +3. Report summary: + - "Successfully processed 8 of 10 items" + - "Failed items: [item1, item2] due to [reason]" + - Suggest retry or manual intervention +``` + +## Performance Optimization + +### Batching Requests + +**Good: Single query with filters** +```markdown +Steps: +1. Call mcp__plugin_api_server__search with filters: + - project_id: "123" + - status: "active" + - limit: 100 +2. Process all results +``` + +**Avoid: Many individual queries** +```markdown +Steps: +1. For each item ID: + - Call mcp__plugin_api_server__get_item + - Process item +``` + +### Caching Results + +```markdown +Steps: +1. Call expensive MCP operation: mcp__plugin_api_server__analyze +2. Store results in variable for reuse +3. Use cached results for subsequent operations +4. Only re-fetch if data changes +``` + +### Parallel Tool Calls + +When tools don't depend on each other, call in parallel: + +```markdown +Steps: +1. Make parallel calls (Claude handles this automatically): + - mcp__plugin_api_server__get_project + - mcp__plugin_api_server__get_users + - mcp__plugin_api_server__get_tags +2. Wait for all to complete +3. Combine results +``` + +## Integration Best Practices + +### User Experience + +**Provide feedback:** +```markdown +Steps: +1. Inform user: "Searching Asana tasks..." +2. Call mcp__plugin_asana_asana__asana_search_tasks +3. Show progress: "Found 15 tasks, analyzing..." +4. Present results +``` + +**Handle long operations:** +```markdown +Steps: +1. Warn user: "This may take a minute..." +2. Break into smaller steps with updates +3. Show incremental progress +4. Final summary when complete +``` + +### Error Messages + +**Good error messages:** +``` +❌ "Could not create task. Please check: + 1. You're logged into Asana + 2. You have access to workspace 'Engineering' + 3. The project 'Q1 Goals' exists" +``` + +**Poor error messages:** +``` +❌ "Error: MCP tool returned 403" +``` + +### Documentation + +**Document MCP tool usage in command:** +```markdown +## MCP Tools Used + +This command uses the following Asana MCP tools: +- **asana_search_tasks**: Search for tasks matching criteria +- **asana_create_task**: Create new task with details +- **asana_update_task**: Update existing task properties + +Ensure you're authenticated to Asana before running this command. +``` + +## Testing Tool Usage + +### Local Testing + +1. **Configure MCP server** in `.mcp.json` +2. **Install plugin locally** in `.claude-plugin/` +3. **Verify tools available** with `/mcp` +4. **Test command** that uses tools +5. **Check debug output**: `claude --debug` + +### Test Scenarios + +**Test successful calls:** +```markdown +Steps: +1. Create test data in external service +2. Run command that queries this data +3. Verify correct results returned +``` + +**Test error cases:** +```markdown +Steps: +1. Test with missing authentication +2. Test with invalid parameters +3. Test with non-existent resources +4. Verify graceful error handling +``` + +**Test edge cases:** +```markdown +Steps: +1. Test with empty results +2. Test with maximum results +3. Test with special characters +4. Test with concurrent access +``` + +## Common Patterns + +### Pattern: CRUD Operations + +```markdown +--- +allowed-tools: [ + "mcp__plugin_api_server__create_item", + "mcp__plugin_api_server__read_item", + "mcp__plugin_api_server__update_item", + "mcp__plugin_api_server__delete_item" +] +--- + +# Item Management + +## Create +Use create_item with required fields... + +## Read +Use read_item with item ID... + +## Update +Use update_item with item ID and changes... + +## Delete +Use delete_item with item ID (ask for confirmation first)... +``` + +### Pattern: Search and Process + +```markdown +Steps: +1. **Search**: mcp__plugin_api_server__search with filters +2. **Filter**: Apply additional local filtering if needed +3. **Transform**: Process each result +4. **Present**: Format and display to user +``` + +### Pattern: Multi-Step Workflow + +```markdown +Steps: +1. **Setup**: Gather all required information +2. **Validate**: Check data completeness +3. **Execute**: Chain of MCP tool calls: + - Create parent resource + - Create child resources + - Link resources together + - Add metadata +4. **Verify**: Confirm all steps succeeded +5. **Report**: Provide summary to user +``` + +## Troubleshooting + +### Tools Not Available + +**Check:** +- MCP server configured correctly +- Server connected (check `/mcp`) +- Tool names match exactly (case-sensitive) +- Restart Claude Code after config changes + +### Tool Calls Failing + +**Check:** +- Authentication is valid +- Parameters match tool schema +- Required parameters provided +- Check `claude --debug` logs + +### Performance Issues + +**Check:** +- Batching queries instead of individual calls +- Caching results when appropriate +- Not making unnecessary tool calls +- Parallel calls when possible + +## Conclusion + +Effective MCP tool usage requires: +1. **Understanding tool schemas** via `/mcp` +2. **Pre-allowing tools** in commands appropriately +3. **Handling errors gracefully** +4. **Optimizing performance** with batching and caching +5. **Providing good UX** with feedback and clear errors +6. **Testing thoroughly** before deployment + +Follow these patterns for robust MCP tool integration in your plugin commands and agents. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/SKILL.md new file mode 100644 index 0000000..bb102f1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/SKILL.md @@ -0,0 +1,1122 @@ +--- +name: ml-paper-writing +description: Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and paper discovery/evaluation criteria. +version: 1.0.0 +author: Orchestra Research +license: MIT +tags: [Academic Writing, NeurIPS, ICML, ICLR, ACL, AAAI, COLM, LaTeX, Paper Writing, Citations, Research] +dependencies: [semanticscholar, arxiv, habanero, requests] +--- + +# ML Paper Writing for Top AI Conferences + +Expert-level guidance for writing publication-ready papers targeting **NeurIPS, ICML, ICLR, ACL, AAAI, and COLM**. This skill combines writing philosophy from top researchers (Nanda, Farquhar, Karpathy, Lipton, Steinhardt) with practical tools: LaTeX templates, citation verification APIs, and conference checklists. + +## Default operating order + +Use this skill in the following order unless the task is unusually narrow: +1. lock the operating mode from `references/OPERATING-MODES.md`, +2. understand the repo or draft context, +3. use `references/citation-workflow.md` as the **canonical citation authority**, +4. load venue- or template-specific references only after the main writing path is clear. + +Google Scholar may still help with manual discovery, but it is **not** the canonical verification authority in this skill. Default verification should use programmatic sources such as Semantic Scholar, CrossRef, and arXiv. + +## Claim ledger gate + +Before a project plan, experiment note, or literature summary becomes manuscript prose: +- identify the Claim Candidate or Evidence Record that supports the sentence, +- preserve allowed wording and forbidden stronger wording, +- keep project plans as hypotheses unless experiment artifacts or verified papers support them, +- do not turn related-work motivation into evidence for the paper's own result, +- mark unsupported claims as `[CLAIM NEEDS EVIDENCE]` instead of polishing them. + +If the repo context is clear enough for a first draft, still apply this gate before stating contributions, results, related-work contrasts, or rebuttal-facing claims. + +## Core Philosophy: Collaborative Writing + +**Paper writing is collaborative, but Claude should be proactive in delivering drafts.** + +The typical workflow starts with a research repository containing code, results, and experimental artifacts. Claude's role is to: + +1. **Understand the project** by exploring the repo, results, and existing documentation +2. **Deliver a complete first draft** when confident about the contribution +3. **Search literature** using web search and APIs to find relevant citations +4. **Refine through feedback cycles** when the scientist provides input +5. **Ask for clarification** only when genuinely uncertain about key decisions + +**Key Principle**: Be proactive. If the repo and results are clear, deliver a full draft. Don't block waiting for feedback on every section—scientists are busy. Produce something concrete they can react to, then iterate based on their response. + +--- + +## ⚠️ CRITICAL: Never Hallucinate Citations + +**This is the most important rule in academic writing with AI assistance.** + +### The Problem +AI-generated citations have a **~40% error rate**. Hallucinated references—papers that don't exist, wrong authors, incorrect years, fabricated DOIs—are a serious form of academic misconduct that can result in desk rejection or retraction. + +### The Rule +**NEVER generate BibTeX entries from memory. ALWAYS fetch programmatically.** + +| Action | ✅ Correct | ❌ Wrong | +|--------|-----------|----------| +| Adding a citation | Search API → verify → fetch BibTeX | Write BibTeX from memory | +| Uncertain about a paper | Mark as `[CITATION NEEDED]` | Guess the reference | +| Can't find exact paper | Note: "placeholder - verify" | Invent similar-sounding paper | + +### When You Can't Verify a Citation + +If you cannot programmatically verify a citation, you MUST: + +```latex +% EXPLICIT PLACEHOLDER - requires human verification +\cite{PLACEHOLDER_author2024_verify_this} % TODO: Verify this citation exists +``` + +**Always tell the scientist**: "I've marked [X] citations as placeholders that need verification. I could not confirm these papers exist." + +### Recommended: Install Exa MCP for Paper Search + +For the best paper search experience, install **Exa MCP** which provides real-time academic search: + +**Claude Code:** +```bash +claude mcp add exa -- npx -y mcp-remote "https://mcp.exa.ai/mcp" +``` + +**Cursor / VS Code** (add to MCP settings): +```json +{ + "mcpServers": { + "exa": { + "type": "http", + "url": "https://mcp.exa.ai/mcp" + } + } +} +``` + +Exa MCP enables searches like: +- "Find papers on RLHF for language models published after 2023" +- "Search for transformer architecture papers by Vaswani" +- "Get recent work on sparse autoencoders for interpretability" + +Then verify results with Semantic Scholar API and fetch BibTeX via DOI. + +--- + +## Workflow 0: Starting from a Research Repository + +When beginning paper writing, start by understanding the project: + +``` +Project Understanding: +- [ ] Step 1: Explore the repository structure +- [ ] Step 2: Read README, existing docs, and key results +- [ ] Step 3: Identify the main contribution with the scientist +- [ ] Step 4: Find papers already cited in the codebase +- [ ] Step 5: Search for additional relevant literature +- [ ] Step 6: Outline the paper structure together +- [ ] Step 7: Draft sections iteratively with feedback +``` + +**Step 1: Explore the Repository** + +```bash +# Understand project structure +ls -la +find . -name "*.py" | head -20 +find . -name "*.md" -o -name "*.txt" | xargs grep -l -i "result\|conclusion\|finding" +``` + +Look for: +- `README.md` - Project overview and claims +- `results/`, `outputs/`, `experiments/` - Key findings +- `configs/` - Experimental settings +- Existing `.bib` files or citation references +- Any draft documents or notes + +**Step 2: Identify Existing Citations** + +Check for papers already referenced in the codebase: + +```bash +# Find existing citations +grep -r "arxiv\|doi\|cite" --include="*.md" --include="*.bib" --include="*.py" +find . -name "*.bib" +``` + +These are high-signal starting points for Related Work—the scientist has already deemed them relevant. + +**Step 3: Clarify the Contribution** + +Before writing, explicitly confirm with the scientist: + +> "Based on my understanding of the repo, the main contribution appears to be [X]. +> The key results show [Y]. Is this the framing you want for the paper, +> or should we emphasize different aspects?" + +**Never assume the narrative—always verify with the human.** + +**Step 4: Search for Additional Literature** + +Use web search to find relevant papers: + +``` +Search queries to try: +- "[main technique] + [application domain]" +- "[baseline method] comparison" +- "[problem name] state-of-the-art" +- Author names from existing citations +``` + +Then verify and retrieve BibTeX using the citation workflow below. + +**Step 5: Deliver a First Draft** + +**Be proactive—deliver a complete draft rather than asking permission for each section.** + +If the repo provides clear results and the contribution is apparent: +1. Check the claim ledger gate for contribution and result claims +2. Write the full first draft end-to-end only for supported claims +3. Mark unsupported or speculative claims explicitly +4. Present the complete draft for feedback +5. Iterate based on scientist's response + +If genuinely uncertain about framing or major claims: +1. Draft what you can confidently +2. Flag specific uncertainties: "I framed X as the main contribution—let me know if you'd prefer to emphasize Y instead" +3. Continue with the draft rather than blocking + +**Questions to include with the draft** (not before): +- "I emphasized X as the main contribution—adjust if needed" +- "I highlighted results A, B, C—let me know if others are more important" +- "Related work section includes [papers]—add any I missed" + +--- + +## When to Use This Skill + +Use this skill when: +- **Starting from a research repo** to write a paper +- **Drafting or revising** specific sections +- **Conducting literature reviews** and finding related work +- **Discovering recent papers** in your research area +- **Finding and verifying citations** for related work +- **Formatting** for conference submission +- **Resubmitting** to a different venue (format conversion) +- **Iterating** on drafts with scientist feedback + +**Always remember**: First drafts are starting points for discussion, not final outputs. + +--- + +## Workflow: Literature Research & Paper Discovery + +When conducting literature reviews, finding related work, or discovering recent papers, use this workflow to systematically search, evaluate, and select ML papers. + +### Workflow 5: Finding and Evaluating Papers + +``` +Literature Research Process: +- [ ] Step 1: Define search scope and keywords +- [ ] Step 2: Search arXiv and academic databases +- [ ] Step 3: Screen papers by title/abstract +- [ ] Step 4: Evaluate paper quality (5 dimensions) +- [ ] Step 5: Select top papers and extract citations +- [ ] Step 6: Verify citations programmatically +``` + +**Step 1: Define Search Scope** + +Identify specific research areas, methods, or applications: +- **Technique-focused**: `transformer architecture`, `graph neural networks`, `self-supervised learning` +- **Application-focused**: `medical image analysis`, `reinforcement learning for robotics`, `language model alignment` +- **Problem-focused**: `out-of-distribution generalization`, `continual learning`, `fairness in ML` + +**Step 2: Search arXiv** + +Use arXiv search with targeted keywords: +``` +URL Pattern: +https://arxiv.org/search/?searchtype=all&query=KEYWORDS&abstracts=show&order=-announced_date_first + +Example Searches: +- https://arxiv.org/search/?searchtype=all&query=graph+neural+networks&abstracts=show&order=-announced_date_first +- https://arxiv.org/search/?cat:cs.LG+AND+all:transformer&abstracts=show&order=-announced_date_first +``` + +**Tips:** +- Combine keywords with `+` for AND +- Filter by categories: `cs.LG`, `cs.AI`, `cs.CV`, `cs.CL` +- Sort by `announced_date_first` for recent papers +- Use Chrome MCP tools when available for automation + +**Step 3: Screen Papers** + +Quick screening by title and abstract: +- Relevance to research topic +- Novelty of contribution +- Venue/reputation of authors +- Code availability (check for GitHub links) + +**Step 4: Evaluate Quality** + +Use the 5-dimension quality criteria: + +| Dimension | Weight | Evaluation Focus | +|-----------|--------|------------------| +| **Innovation** | 30% | Novelty and originality | +| **Method Completeness** | 25% | Clarity and reproducibility | +| **Experimental Thoroughness** | 25% | Validation depth | +| **Writing Quality** | 10% | Presentation clarity | +| **Relevance & Impact** | 10% | Domain importance | + +**Scoring**: Rate each dimension 1-5, calculate weighted total + +**Step 5: Select and Extract** + +- Rank papers by total score +- Select top papers for detailed review +- Extract metadata: title, authors, arXiv ID, abstract +- Note code repository links + +**Step 6: Verify Citations** + +For selected papers, verify citations using Semantic Scholar API: +- Fetch BibTeX programmatically via DOI +- Mark unverified citations as `[CITATION NEEDED]` +- Store in bibliography with verification status + +### When to Use Literature Research + +Use this workflow when: +- **Starting a new project**: Find related work and baselines +- **Writing Related Work section**: Discover recent papers in your area +- **Staying updated**: Track recent publications in your field +- **Finding baselines**: Identify state-of-the-art methods for comparison +- **Literature review**: Comprehensive survey of research area + +### Quality Thresholds + +- **Excellent**: 4.0+ (include definitely) +- **Good**: 3.5-3.9 (include if relevant) +- **Fair**: 3.0-3.4 (include if highly relevant) +- **Poor**: <3.0 (exclude unless essential) + +### Reference Files + +For detailed literature research guidance: +- **`references/literature-research/arxiv-search-guide.md`** - arXiv search strategies and URL patterns +- **`references/literature-research/paper-quality-criteria.md`** - Detailed 5-dimension evaluation rubrics + +--- + +## Knowledge Base: Paper-Miner Installed Writing Memory + +This skill consumes the **active installed writing memory** maintained by `paper-miner`: + +- `references/knowledge/paper-miner-writing-memory.md` + +This memory belongs to the active installed skill home, not to the source checkout copy. + +Even when `paper-miner` is invoked while working inside a specific repository, it still writes mined writing knowledge only into the active installed skill memory. It does **not** maintain project-local writing memory unless the user explicitly requests that. + +### Canonical memory structure + +The maintained memory contains these sections: + +| Section | Purpose | +|----------|---------| +| `Writing patterns mined` | Reusable rhetorical and claim-evidence patterns | +| `Structure signals` | Section flow, paragraph progression, and paper organization signals | +| `Reusable phrasing` | Transition phrases, framing templates, and concise wording | +| `Venue-specific signals` | Visible venue-facing style and convention cues | +| `How this helps our writing` | Practical guidance for future drafts, reports, and rebuttals | +| `Source index` | Source attribution for mined papers | + +### How the memory is maintained + +The **paper-miner agent** reads papers and merges reusable writing knowledge into this one file: + +```text +You: "Learn writing patterns from this paper: path/to/paper.pdf" +↓ +paper-miner analyzes the paper +↓ +Extracts reusable writing signals +↓ +Updates paper-miner-writing-memory.md +↓ +ml-paper-writing reuses that memory later +``` + +### When to use this memory + +Use the active installed paper-miner memory when you need: +- structure inspiration for intros, methods, results, or discussion, +- reusable transition phrases or framing templates, +- venue-facing writing signals, +- rebuttal phrasing and response structure ideas, +- examples of how strong papers support and sequence claims. + +### Default read order + +When drafting or revising with `ml-paper-writing`, read this memory **before** writing if the task involves: +- introduction framing, +- related work organization, +- method exposition style, +- results narration, +- discussion framing, +- venue-facing polishing. + +Use this read order: +1. `references/knowledge/paper-miner-writing-memory.md` +2. repo-local evidence and experiment artifacts +3. cited papers or notes if needed +4. venue template and formatting constraints + +Read narrowly, not exhaustively: +- first scan `How this helps our writing`, +- then check `Writing patterns mined` and `Structure signals`, +- then inspect `Reusable phrasing` only for concrete wording help, +- use `Venue-specific signals` when targeting a known venue. + +### Contribution rule + +Every paper mined by `paper-miner` should improve the same active installed memory. + +Do not scatter newly mined knowledge across multiple maintained files. +Do not create project-specific paper-miner memory. +Do not duplicate near-identical patterns from the same source. + +See `references/knowledge/README.md` for the detailed knowledge-base contract. + +## Balancing Proactivity and Collaboration + +**Default: Be proactive. Deliver drafts, then iterate.** + +| Confidence Level | Action | +|-----------------|--------| +| **High** (clear repo, obvious contribution) | Write full draft, deliver, iterate on feedback | +| **Medium** (some ambiguity) | Write draft with flagged uncertainties, continue | +| **Low** (major unknowns) | Ask 1-2 targeted questions, then draft | + +**Draft first, ask with the draft** (not before): + +| Section | Draft Autonomously | Flag With Draft | +|---------|-------------------|-----------------| +| Abstract | Yes | "Framed contribution as X—adjust if needed" | +| Introduction | Yes | "Emphasized problem Y—correct if wrong" | +| Methods | Yes | "Included details A, B, C—add missing pieces" | +| Experiments | Yes | "Highlighted results 1, 2, 3—reorder if needed" | +| Related Work | Yes | "Cited papers X, Y, Z—add any I missed" | + +**Only block for input when:** +- Target venue is unclear (affects page limits, framing) +- Multiple contradictory framings seem equally valid +- Results seem incomplete or inconsistent +- Explicit request to review before continuing + +**Don't block for:** +- Word choice decisions +- Section ordering +- Which specific results to show (make a choice, flag it) +- Citation completeness (draft with what you find, note gaps) + +--- + +## The Narrative Principle + +**The single most critical insight**: Your paper is not a collection of experiments—it's a story with one clear contribution supported by evidence. + +Every successful ML paper centers on what Neel Nanda calls "the narrative": a short, rigorous, evidence-based technical story with a takeaway readers care about. + +**Three Pillars (must be crystal clear by end of introduction):** + +| Pillar | Description | Example | +|--------|-------------|---------| +| **The What** | 1-3 specific novel claims within cohesive theme | "We prove that X achieves Y under condition Z" | +| **The Why** | Rigorous empirical evidence supporting claims | Strong baselines, experiments distinguishing hypotheses | +| **The So What** | Why readers should care | Connection to recognized community problems | + +**If you cannot state your contribution in one sentence, you don't yet have a paper.** + +--- + +## Paper Structure Workflow + +### Workflow 1: Writing a Complete Paper (Iterative) + +Copy this checklist and track progress. **Each step involves drafting → feedback → revision:** + +``` +Paper Writing Progress: +- [ ] Step 1: Define the one-sentence contribution (with scientist) +- [ ] Step 2: Draft Figure 1 → get feedback → revise +- [ ] Step 3: Draft abstract → get feedback → revise +- [ ] Step 4: Draft introduction → get feedback → revise +- [ ] Step 5: Draft methods → get feedback → revise +- [ ] Step 6: Draft experiments → get feedback → revise +- [ ] Step 7: Draft related work → get feedback → revise +- [ ] Step 8: Draft limitations → get feedback → revise +- [ ] Step 9: Complete paper checklist (required) +- [ ] Step 10: Final review cycle and submission +``` + +**Step 1: Define the One-Sentence Contribution** + +**This step requires explicit confirmation from the scientist.** + +Before writing anything, articulate and verify: +- What is the single thing your paper contributes? +- What was not obvious or present before your work? + +> "I propose framing the contribution as: '[one sentence]'. Does this capture +> what you see as the main takeaway? Should we adjust the emphasis?" + +**Step 2: Draft Figure 1** + +Figure 1 deserves special attention—many readers skip directly to it. +- Convey core idea, approach, or most compelling result +- Use vector graphics (PDF/EPS for plots) +- Write captions that stand alone without main text +- Ensure readability in black-and-white (8% of men have color vision deficiency) + +**Step 3: Write Abstract (5-Sentence Formula)** + +From Sebastian Farquhar (DeepMind): + +``` +1. What you achieved: "We introduce...", "We prove...", "We demonstrate..." +2. Why this is hard and important +3. How you do it (with specialist keywords for discoverability) +4. What evidence you have +5. Your most remarkable number/result +``` + +**Delete** generic openings like "Large language models have achieved remarkable success..." + +**Step 4: Write Introduction (1-1.5 pages max)** + +Must include: +- 2-4 bullet contribution list (max 1-2 lines each in two-column format) +- Clear problem statement +- Brief approach overview +- Methods should start by page 2-3 maximum + +**Step 5: Methods Section** + +Enable reimplementation: +- Conceptual outline or pseudocode +- All hyperparameters listed +- Architectural details sufficient for reproduction +- Present final design decisions; ablations go in experiments + +**Step 6: Experiments Section** + +For each experiment, explicitly state: +- What claim it supports +- How it connects to main contribution +- Experimental setting (details in appendix) +- What to observe: "the blue line shows X, which demonstrates Y" + +Requirements: +- Error bars with methodology (standard deviation vs standard error) +- Hyperparameter search ranges +- Compute infrastructure (GPU type, total hours) +- Seed-setting methods + +**Step 7: Related Work** + +Organize methodologically, not paper-by-paper: + +**Good:** "One line of work uses Floogledoodle's assumption [refs] whereas we use Doobersnoddle's assumption because..." + +**Bad:** "Snap et al. introduced X while Crackle et al. introduced Y." + +Cite generously—reviewers likely authored relevant papers. + +**Step 8: Limitations Section (REQUIRED)** + +All major conferences require this. Counter-intuitively, honesty helps: +- Reviewers are instructed not to penalize honest limitation acknowledgment +- Pre-empt criticisms by identifying weaknesses first +- Explain why limitations don't undermine core claims + +**Step 9: Paper Checklist** + +NeurIPS, ICML, and ICLR all require paper checklists. See [references/checklists.md](references/checklists.md). + +--- + +## Writing Philosophy for Top ML Conferences + +**This section distills the most important writing principles from leading ML researchers.** These aren't optional style suggestions—they're what separates accepted papers from rejected ones. + +> "A paper is a short, rigorous, evidence-based technical story with a takeaway readers care about." — Neel Nanda + +### The Sources Behind This Guidance + +This skill synthesizes writing philosophy from researchers who have published extensively at top venues: + +| Source | Key Contribution | Link | +|--------|-----------------|------| +| **Neel Nanda** (Google DeepMind) | The Narrative Principle, What/Why/So What framework | [How to Write ML Papers](https://www.alignmentforum.org/posts/eJGptPbbFPZGLpjsp/highly-opinionated-advice-on-how-to-write-ml-papers) | +| **Sebastian Farquhar** (DeepMind) | 5-sentence abstract formula | [How to Write ML Papers](https://sebastianfarquhar.com/on-research/2024/11/04/how_to_write_ml_papers/) | +| **Gopen & Swan** | 7 principles of reader expectations | [Science of Scientific Writing](https://cseweb.ucsd.edu/~swanson/papers/science-of-writing.pdf) | +| **Zachary Lipton** | Word choice, eliminating hedging | [Heuristics for Scientific Writing](https://www.approximatelycorrect.com/2018/01/29/heuristics-technical-scientific-writing-machine-learning-perspective/) | +| **Jacob Steinhardt** (UC Berkeley) | Precision, consistent terminology | [Writing Tips](https://bounded-regret.ghost.io/) | +| **Ethan Perez** (Anthropic) | Micro-level clarity tips | [Easy Paper Writing Tips](https://ethanperez.net/easy-paper-writing-tips/) | +| **Andrej Karpathy** | Single contribution focus | Various lectures | + +**For deeper dives into any of these, see:** +- [references/writing-guide.md](references/writing-guide.md) - Full explanations with examples +- [references/sources.md](references/sources.md) - Complete bibliography + +### Time Allocation (From Neel Nanda) + +Spend approximately **equal time** on each of: +1. The abstract +2. The introduction +3. The figures +4. Everything else combined + +**Why?** Most reviewers form judgments before reaching your methods. Readers encounter your paper as: **title → abstract → introduction → figures → maybe the rest.** + +### Writing Style Guidelines + +#### Sentence-Level Clarity (Gopen & Swan's 7 Principles) + +These principles are based on how readers actually process prose. Violating them forces readers to spend cognitive effort on structure rather than content. + +| Principle | Rule | Example | +|-----------|------|---------| +| **Subject-verb proximity** | Keep subject and verb close | ❌ "The model, which was trained on..., achieves" → ✅ "The model achieves... after training on..." | +| **Stress position** | Place emphasis at sentence ends | ❌ "Accuracy improves by 15% when using attention" → ✅ "When using attention, accuracy improves by **15%**" | +| **Topic position** | Put context first, new info after | ✅ "Given these constraints, we propose..." | +| **Old before new** | Familiar info → unfamiliar info | Link backward, then introduce new | +| **One unit, one function** | Each paragraph makes one point | Split multi-point paragraphs | +| **Action in verb** | Use verbs, not nominalizations | ❌ "We performed an analysis" → ✅ "We analyzed" | +| **Context before new** | Set stage before presenting | Explain before showing equation | + +**Full 7 principles with detailed examples:** See [references/writing-guide.md](references/writing-guide.md#the-7-principles-of-reader-expectations) + +#### Micro-Level Tips (Ethan Perez) + +These small changes accumulate into significantly clearer prose: + +- **Minimize pronouns**: ❌ "This shows..." → ✅ "This result shows..." +- **Verbs early**: Position verbs near sentence start +- **Unfold apostrophes**: ❌ "X's Y" → ✅ "The Y of X" (when awkward) +- **Delete filler words**: "actually," "a bit," "very," "really," "basically," "quite," "essentially" + +**Full micro-tips with examples:** See [references/writing-guide.md](references/writing-guide.md#micro-level-writing-tips) + +#### Word Choice (Zachary Lipton) + +- **Be specific**: ❌ "performance" → ✅ "accuracy" or "latency" (say what you mean) +- **Eliminate hedging**: Drop "may" and "can" unless genuinely uncertain +- **Avoid incremental vocabulary**: ❌ "combine," "modify," "expand" → ✅ "develop," "propose," "introduce" +- **Delete intensifiers**: ❌ "provides *very* tight approximation" → ✅ "provides tight approximation" + +#### Precision Over Brevity (Jacob Steinhardt) + +- **Consistent terminology**: Different terms for same concept creates confusion. Pick one and stick with it. +- **State assumptions formally**: Before theorems, list all assumptions explicitly +- **Intuition + rigor**: Provide intuitive explanations alongside formal proofs + +### What Reviewers Actually Read + +Understanding reviewer behavior helps prioritize your effort: + +| Paper Section | % Reviewers Who Read | Implication | +|---------------|---------------------|-------------| +| Abstract | 100% | Must be perfect | +| Introduction | 90%+ (skimmed) | Front-load contribution | +| Figures | Examined before methods | Figure 1 is critical | +| Methods | Only if interested | Don't bury the lede | +| Appendix | Rarely | Put only supplementary details | + +**Bottom line**: If your abstract and intro don't hook reviewers, they may never read your brilliant methods section. + +--- + +## Conference Requirements Quick Reference + +| Conference | Page Limit | Extra for Camera-Ready | Key Requirement | +|------------|------------|------------------------|-----------------| +| **NeurIPS 2025** | 9 pages | +0 | Mandatory checklist, lay summary for accepted | +| **ICML 2026** | 8 pages | +1 | Broader Impact Statement required | +| **ICLR 2026** | 9 pages | +1 | LLM disclosure required, reciprocal reviewing | +| **ACL 2025** | 8 pages (long) | varies | Limitations section mandatory | +| **AAAI 2026** | 7 pages | +1 | Strict style file adherence | +| **COLM 2025** | 9 pages | +1 | Focus on language models | + +**Universal Requirements:** +- Double-blind review (anonymize submissions) +- References don't count toward page limit +- Appendices unlimited but reviewers not required to read +- LaTeX required for all venues + +**LaTeX Templates:** See [templates/](templates/) directory for all conference templates. + +--- + +## Using LaTeX Templates Properly + +### Workflow 4: Starting a New Paper from Template + +**Always copy the entire template directory first, then write within it.** + +``` +Template Setup Checklist: +- [ ] Step 1: Copy entire template directory to new project +- [ ] Step 2: Verify template compiles as-is (before any changes) +- [ ] Step 3: Read the template's example content to understand structure +- [ ] Step 4: Replace example content section by section +- [ ] Step 5: Keep template comments/examples as reference until done +- [ ] Step 6: Clean up template artifacts only at the end +``` + +**Step 1: Copy the Full Template** + +```bash +# Create your paper directory with the complete template +cp -r templates/neurips2025/ ~/papers/my-new-paper/ +cd ~/papers/my-new-paper/ + +# Verify structure is complete +ls -la +# Should see: main.tex, neurips.sty, Makefile, etc. +``` + +**⚠️ IMPORTANT**: Copy the ENTIRE directory, not just `main.tex`. Templates include: +- Style files (`.sty`) - required for compilation +- Bibliography styles (`.bst`) - required for references +- Example content - useful as reference +- Makefiles - for easy compilation + +**Step 2: Verify Template Compiles First** + +Before making ANY changes, compile the template as-is: + +```bash +# Using latexmk (recommended) +latexmk -pdf main.tex + +# Or manual compilation +pdflatex main.tex +bibtex main +pdflatex main.tex +pdflatex main.tex +``` + +If the unmodified template doesn't compile, fix that first. Common issues: +- Missing TeX packages → install via `tlmgr install ` +- Wrong TeX distribution → use TeX Live (recommended) + +**Step 3: Keep Template Content as Reference** + +Don't immediately delete all example content. Instead: + +```latex +% KEEP template examples commented out as you write +% This shows you the expected format + +% Template example (keep for reference): +% \begin{figure}[t] +% \centering +% \includegraphics[width=0.8\linewidth]{example-image} +% \caption{Template shows caption style} +% \end{figure} + +% Your actual figure: +\begin{figure}[t] + \centering + \includegraphics[width=0.8\linewidth]{your-figure.pdf} + \caption{Your caption following the same style.} +\end{figure} +``` + +**Step 4: Replace Content Section by Section** + +Work through the paper systematically: + +``` +Replacement Order: +1. Title and authors (anonymize for submission) +2. Abstract +3. Introduction +4. Methods +5. Experiments +6. Related Work +7. Conclusion +8. References (your .bib file) +9. Appendix +``` + +For each section: +1. Read the template's example content +2. Note any special formatting or macros used +3. Replace with your content following the same patterns +4. Compile frequently to catch errors early + +**Step 5: Use Template Macros** + +Templates often define useful macros. Check the preamble for: + +```latex +% Common template macros to use: +\newcommand{\method}{YourMethodName} % Consistent method naming +\newcommand{\eg}{e.g.,\xspace} % Proper abbreviations +\newcommand{\ie}{i.e.,\xspace} +\newcommand{\etal}{\textit{et al.}\xspace} +``` + +**Step 6: Clean Up Only at the End** + +Only remove template artifacts when paper is nearly complete: + +```latex +% BEFORE SUBMISSION - remove these: +% - Commented-out template examples +% - Unused packages +% - Template's example figures/tables +% - Lorem ipsum or placeholder text + +% KEEP these: +% - All style files (.sty) +% - Bibliography style (.bst) +% - Required packages from template +% - Any custom macros you're using +``` + +### Template Pitfalls to Avoid + +| Pitfall | Problem | Solution | +|---------|---------|----------| +| Copying only `main.tex` | Missing `.sty`, won't compile | Copy entire directory | +| Modifying `.sty` files | Breaks conference formatting | Never edit style files | +| Adding random packages | Conflicts, breaks template | Only add if necessary | +| Deleting template content too early | Lose formatting reference | Keep as comments until done | +| Not compiling frequently | Errors accumulate | Compile after each section | + +### Quick Template Reference + +| Conference | Main File | Key Style File | Notes | +|------------|-----------|----------------|-------| +| NeurIPS 2025 | `main.tex` | `neurips.sty` | Has Makefile | +| ICML 2026 | `example_paper.tex` | `icml2026.sty` | Includes algorithm packages | +| ICLR 2026 | `iclr2026_conference.tex` | `iclr2026_conference.sty` | Has math_commands.tex | +| ACL | `acl_latex.tex` | `acl.sty` | Strict formatting | +| AAAI 2026 | `aaai2026-unified-template.tex` | `aaai2026.sty` | Very strict compliance | +| COLM 2025 | `colm2025_conference.tex` | `colm2025_conference.sty` | Similar to ICLR | + +--- + +## Conference Resubmission & Format Conversion + +When a paper is rejected or withdrawn from one venue and resubmitted to another, format conversion is required. This is a common workflow in ML research. + +### Workflow 3: Converting Between Conference Formats + +``` +Format Conversion Checklist: +- [ ] Step 1: Identify source and target template differences +- [ ] Step 2: Create new project with target template +- [ ] Step 3: Copy content sections (not preamble) +- [ ] Step 4: Adjust page limits and content +- [ ] Step 5: Update conference-specific requirements +- [ ] Step 6: Verify compilation and formatting +``` + +**Step 1: Key Template Differences** + +| From → To | Page Change | Key Adjustments | +|-----------|-------------|-----------------| +| NeurIPS → ICML | 9 → 8 pages | Cut 1 page, add Broader Impact if missing | +| ICML → ICLR | 8 → 9 pages | Can expand experiments, add LLM disclosure | +| NeurIPS → ACL | 9 → 8 pages | Restructure for NLP conventions, add Limitations | +| ICLR → AAAI | 9 → 7 pages | Significant cuts needed, strict style adherence | +| Any → COLM | varies → 9 | Reframe for language model focus | + +**Step 2: Content Migration (NOT Template Merge)** + +**Never copy LaTeX preambles between templates.** Instead: + +```bash +# 1. Start fresh with target template +cp -r templates/icml2026/ new_submission/ + +# 2. Copy ONLY content sections from old paper +# - Abstract text +# - Section content (between \section{} commands) +# - Figures and tables +# - Bibliography entries + +# 3. Paste into target template structure +``` + +**Step 3: Adjusting for Page Limits** + +When cutting pages (e.g., NeurIPS 9 → AAAI 7): +- Move detailed proofs to appendix +- Condense related work (cite surveys instead of individual papers) +- Combine similar experiments into unified tables +- Use smaller figure sizes with subfigures +- Tighten writing: eliminate redundancy, use active voice + +When expanding (e.g., ICML 8 → ICLR 9): +- Add ablation studies reviewers requested +- Expand limitations discussion +- Include additional baselines +- Add qualitative examples + +**Step 4: Conference-Specific Adjustments** + +| Target Venue | Required Additions | +|--------------|-------------------| +| **ICML** | Broader Impact Statement (after conclusion) | +| **ICLR** | LLM usage disclosure, reciprocal reviewing agreement | +| **ACL/EMNLP** | Limitations section (mandatory), Ethics Statement | +| **AAAI** | Strict adherence to style file (no modifications) | +| **NeurIPS** | Paper checklist (appendix), lay summary if accepted | + +**Step 5: Update References** + +```latex +% Remove self-citations that reveal identity (for blind review) +% Update any "under review" citations to published versions +% Add new relevant work published since last submission +``` + +**Step 6: Addressing Previous Reviews** + +When resubmitting after rejection: +- **Do** address reviewer concerns in the new version +- **Do** add experiments/clarifications reviewers requested +- **Don't** include a "changes from previous submission" section (blind review) +- **Don't** reference the previous submission or reviews + +**Common Conversion Pitfalls:** +- ❌ Copying `\usepackage` commands (causes conflicts) +- ❌ Keeping old conference header/footer commands +- ❌ Forgetting to update `\bibliography{}` path +- ❌ Missing conference-specific required sections +- ❌ Exceeding page limit after format change + +--- + +## Citation Workflow (Hallucination Prevention) + +**⚠️ CRITICAL**: AI-generated citations are a high-risk failure mode. **Never write BibTeX from memory.** + +### Canonical authority + +Use `references/citation-workflow.md` as the default authority for citation verification. + +The default verification path is: +1. **Search programmatically** with Semantic Scholar / CrossRef / arXiv / OpenAlex when appropriate. +2. **Verify existence** in two sources when the claim is important. +3. **Retrieve BibTeX programmatically** from DOI or a trusted source. +4. **Validate the claim** against the actual paper content when the citation supports a specific statement. +5. **Add the citation** only after the metadata and claim are verified. + +### The golden rule + +```text +IF you cannot verify a citation programmatically: + -> mark it as [CITATION NEEDED] or [PLACEHOLDER - VERIFY] + -> tell the scientist explicitly + -> NEVER invent a plausible-sounding reference +``` + +### Workflow 2: Adding citations + +```text +Citation verification: +- [ ] Step 1: Search with Semantic Scholar / CrossRef / arXiv / OpenAlex as appropriate +- [ ] Step 2: Confirm title, authors, year, and venue +- [ ] Step 3: Retrieve BibTeX from DOI, arXiv, or another trusted export path +- [ ] Step 4: Verify that the claim being cited actually appears in the source +- [ ] Step 5: Add verified BibTeX to the bibliography +- [ ] Step 6: If any step fails -> mark as placeholder and report it explicitly +``` + +### Discovery vs authority + +- **Programmatic APIs** are the canonical verification path. +- **Google Scholar** may still be used as a manual discovery surface when coverage is weak, but not as the primary authority. +- If Google Scholar finds something that the canonical APIs do not, treat it as a lead that still requires explicit verification. + +### Summary: citation rules + +| Situation | Action | +|-----------|--------| +| Verified metadata + verified BibTeX + verified claim | ✅ Use the citation | +| Verified paper exists but the claim was not checked | ⚠️ Use only for general attribution, not for precise technical claims | +| Discovery surface suggests a paper but metadata is still weak | ⚠️ Keep as lead, not as final citation | +| Cannot verify programmatically | ❌ Mark `[CITATION NEEDED]`, inform the scientist | + +**🚨 NEVER generate BibTeX from memory. Use the programmatic workflow in `references/citation-workflow.md`. 🚨** + +### Complete Citation Workflow Example + +**Scenario**: You need to cite the Transformer paper. + +```text +Step 1: Search programmatically +- Semantic Scholar query: "Attention is All You Need Vaswani 2017" +- Result: title, authors, year, and DOI align + +Step 2: Verify existence +- CrossRef confirms DOI metadata +- Semantic Scholar record matches the same paper + +Step 3: Retrieve BibTeX +- Fetch BibTeX from the DOI / trusted export path + +Step 4: Verify the claim +- Read the abstract or paper section that supports the cited statement +- Confirm that the claim being cited is actually present + +Step 5: Add to bibliography +- Paste verified BibTeX into the .bib file +- Cite with the verified key + +Step 6: If any step fails +- mark the citation as [PLACEHOLDER - VERIFY] +- tell the scientist explicitly what remains unverified +``` + +--- + +## Common Issues and Solutions + +**Issue: Abstract too generic** + +Delete first sentence if it could be prepended to any ML paper. Start with your specific contribution. + +**Issue: Introduction exceeds 1.5 pages** + +Split background into Related Work. Front-load contribution bullets. Methods should start by page 2-3. + +**Issue: Experiments lack explicit claims** + +Add sentence before each experiment: "This experiment tests whether [specific claim]..." + +**Issue: Reviewers find paper hard to follow** + +- Add explicit signposting: "In this section, we show X" +- Use consistent terminology throughout +- Include figure captions that stand alone + +**Issue: Missing statistical significance** + +Always include: +- Error bars (specify: std dev or std error) +- Number of runs +- Statistical tests if comparing methods + +--- + +## Reviewer Evaluation Criteria + +Reviewers assess papers on four dimensions: + +| Criterion | What Reviewers Look For | +|-----------|------------------------| +| **Quality** | Technical soundness, well-supported claims | +| **Clarity** | Clear writing, reproducible by experts | +| **Significance** | Community impact, advances understanding | +| **Originality** | New insights (doesn't require new method) | + +**Scoring (NeurIPS 6-point scale):** +- 6: Strong Accept - Groundbreaking, flawless +- 5: Accept - Technically solid, high impact +- 4: Borderline Accept - Solid, limited evaluation +- 3: Borderline Reject - Solid but weaknesses outweigh +- 2: Reject - Technical flaws +- 1: Strong Reject - Known results or ethics issues + +See [references/reviewer-guidelines.md](references/reviewer-guidelines.md) for detailed reviewer instructions. + +--- + +## Tables and Figures + +If the task is to generate or redesign paper-ready figures/tables themselves, use `publication-chart-skill`; `ml-paper-writing` stays responsible for caption quality, placement, storyline, and paper integration. + +### Tables + +Use `booktabs` LaTeX package for professional tables: + +```latex +\usepackage{booktabs} +\begin{tabular}{lcc} +\toprule +Method & Accuracy ↑ & Latency ↓ \\ +\midrule +Baseline & 85.2 & 45ms \\ +\textbf{Ours} & \textbf{92.1} & 38ms \\ +\bottomrule +\end{tabular} +``` + +**Rules:** +- Bold best value per metric +- Include direction symbols (↑ higher is better, ↓ lower is better) +- Right-align numerical columns +- Consistent decimal precision + +### Figures + +- **Vector graphics** (PDF, EPS) for all plots and diagrams +- **Raster** (PNG 600 DPI) only for photographs +- Use **colorblind-safe palettes** (Okabe-Ito or Paul Tol) +- Verify **grayscale readability** (8% of men have color vision deficiency) +- **No title inside figure**—the caption serves this function +- **Self-contained captions**—reader should understand without main text + +--- + +## References & Resources + +### Reference Documents (Deep Dives) + +| Document | Contents | +|----------|----------| +| [writing-guide.md](references/writing-guide.md) | Gopen & Swan 7 principles, Ethan Perez micro-tips, word choice | +| [citation-workflow.md](references/citation-workflow.md) | Citation APIs, Python code, BibTeX management | +| [checklists.md](references/checklists.md) | NeurIPS 16-item, ICML, ICLR, ACL requirements | +| [reviewer-guidelines.md](references/reviewer-guidelines.md) | Evaluation criteria, scoring, rebuttals | +| [sources.md](references/sources.md) | Complete bibliography of all sources | +| **Literature Research:** | +| [arxiv-search-guide.md](references/literature-research/arxiv-search-guide.md) | arXiv search strategies, URL patterns, Chrome MCP automation | +| [paper-quality-criteria.md](references/literature-research/paper-quality-criteria.md) | 5-dimension paper evaluation rubrics (innovation, method, experiments, writing, impact) | + +### LaTeX Templates + +Templates in `templates/` directory: **ICML 2026**, **ICLR 2026**, **NeurIPS 2025**, **ACL/EMNLP**, **AAAI 2026**, **COLM 2025**. + +**Compiling to PDF:** +- **VS Code/Cursor**: Install LaTeX Workshop extension + TeX Live → Save to auto-compile +- **Command line**: `latexmk -pdf main.tex` or `pdflatex` + `bibtex` workflow +- **Online**: Upload to [Overleaf](https://overleaf.com) + +See [templates/README.md](templates/README.md) for detailed setup instructions. + +### Key External Sources + +**Writing Philosophy:** +- [Neel Nanda: How to Write ML Papers](https://www.alignmentforum.org/posts/eJGptPbbFPZGLpjsp/highly-opinionated-advice-on-how-to-write-ml-papers) - Narrative, "What/Why/So What" +- [Farquhar: How to Write ML Papers](https://sebastianfarquhar.com/on-research/2024/11/04/how_to_write_ml_papers/) - 5-sentence abstract +- [Gopen & Swan: Science of Scientific Writing](https://cseweb.ucsd.edu/~swanson/papers/science-of-writing.pdf) - 7 reader expectation principles +- [Lipton: Heuristics for Scientific Writing](https://www.approximatelycorrect.com/2018/01/29/heuristics-technical-scientific-writing-machine-learning-perspective/) - Word choice +- [Perez: Easy Paper Writing Tips](https://ethanperez.net/easy-paper-writing-tips/) - Micro-level clarity + +**APIs:** [Semantic Scholar](https://api.semanticscholar.org/api-docs/) | [CrossRef](https://www.crossref.org/documentation/retrieve-metadata/rest-api/) | [arXiv](https://info.arxiv.org/help/api/basics.html) + +**Venues:** [NeurIPS](https://neurips.cc/Conferences/2025/PaperInformation/StyleFiles) | [ICML](https://icml.cc/Conferences/2025/AuthorInstructions) | [ICLR](https://iclr.cc/Conferences/2026/AuthorGuide) | [ACL](https://github.com/acl-org/acl-style-files) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/OPERATING-MODES.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/OPERATING-MODES.md new file mode 100644 index 0000000..48dd753 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/OPERATING-MODES.md @@ -0,0 +1,25 @@ +# Operating Modes + +Use this file to decide how much of the writing stack to load. + +## Modes + +### 1. drafting +Use when writing or rewriting a paper section from repo evidence. +Load: core SKILL + writing guide + citation workflow. + +### 2. related-work +Use when searching, comparing, and integrating literature. +Load: citation workflow + reviewer guidelines + relevant venue notes. + +### 3. citation-only +Use when the task is primarily reference verification or bibliography repair. +Load: citation workflow first; do not load the full paper-writing stack unless needed. + +### 4. format-conversion +Use when moving between conference templates or preparing camera-ready assets. +Load: template / format references and only the relevant venue rules. + +### 5. camera-ready +Use when compliance, formatting, and final verification dominate over drafting. +Load: venue-specific checklist + citation workflow + final verification notes. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/checklists.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/checklists.md new file mode 100644 index 0000000..1c46b75 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/checklists.md @@ -0,0 +1,361 @@ +# Conference Paper Checklists + +This reference documents the mandatory checklist requirements for major ML/AI conferences. All major venues now require paper checklists—missing them results in desk rejection. + +--- + +## Contents + +- [NeurIPS Paper Checklist](#neurips-paper-checklist) +- [ICML Paper Checklist](#icml-paper-checklist) +- [ICLR Requirements](#iclr-requirements) +- [ACL Requirements](#acl-requirements) +- [Universal Pre-Submission Checklist](#universal-pre-submission-checklist) + +--- + +## NeurIPS Paper Checklist + +### Mandatory Components + +All NeurIPS submissions must include a completed paper checklist. Papers lacking this element face **automatic desk rejection**. The checklist appears after references and supplemental material, outside the page limit. + +### 16 Required Checklist Items + +#### 1. Claims Alignment +Authors must verify that abstract and introduction claims match theoretical and experimental results, with clearly stated contributions, assumptions, and limitations. + +**What to check:** +- [ ] Abstract claims match actual results +- [ ] Introduction doesn't overclaim +- [ ] Contributions are specific and falsifiable + +#### 2. Limitations Discussion +Papers should include a dedicated "Limitations" section addressing strong assumptions, robustness to violations, scope constraints, and performance-influencing factors. + +**What to include:** +- [ ] Dedicated Limitations section +- [ ] Honest assessment of scope +- [ ] Conditions where method may fail + +#### 3. Theory & Proofs +Theoretical contributions require full assumption statements and complete proofs (main paper or appendix with proof sketches for intuition). + +**What to check:** +- [ ] All assumptions stated formally +- [ ] Complete proofs provided (main text or appendix) +- [ ] Proof sketches for intuition in main text + +#### 4. Reproducibility +Authors must describe steps ensuring results verification through code release, detailed instructions, model access, or checkpoints appropriate to their contribution type. + +**What to provide:** +- [ ] Clear reproducibility statement +- [ ] Code availability information +- [ ] Model checkpoints if applicable + +#### 5. Data & Code Access +Instructions for reproducing main experimental results should be provided (supplemental material or URLs), including exact commands and environment specifications. + +**What to include:** +- [ ] Exact commands to run experiments +- [ ] Environment specifications (requirements.txt, conda env) +- [ ] Data access instructions + +#### 6. Experimental Details +Papers must specify training details: data splits, hyperparameters, and selection methods in the main paper or supplementary materials. + +**What to document:** +- [ ] Train/val/test split details +- [ ] All hyperparameters used +- [ ] Hyperparameter selection method + +#### 7. Statistical Significance +Results require error bars, confidence intervals, or statistical tests with clearly stated calculation methods and underlying assumptions. + +**What to include:** +- [ ] Error bars or confidence intervals +- [ ] Number of runs/seeds +- [ ] Calculation method (std dev vs std error) + +#### 8. Compute Resources +Specifications needed: compute worker types (CPU/GPU), memory, storage, execution time per run, and total project compute requirements. + +**What to document:** +- [ ] GPU type and count +- [ ] Training time per run +- [ ] Total compute used + +#### 9. Ethics Code Compliance +Authors confirm adherence to the NeurIPS Code of Ethics, noting any necessary deviations. + +**What to verify:** +- [ ] Read NeurIPS Code of Ethics +- [ ] Confirm compliance +- [ ] Note any deviations with justification + +#### 10. Broader Impacts +Discussion of potential negative societal applications, fairness concerns, privacy risks, and possible mitigation strategies when applicable. + +**What to address:** +- [ ] Potential negative applications +- [ ] Fairness considerations +- [ ] Privacy implications +- [ ] Mitigation strategies + +#### 11. Safeguards +High-risk models (language models, internet-scraped datasets) require controlled release mechanisms and usage guidelines. + +**What to consider:** +- [ ] Release strategy for sensitive models +- [ ] Usage guidelines if needed +- [ ] Access controls if appropriate + +#### 12. License Respect +All existing assets require creator citations, license names, URLs, version numbers, and terms-of-service acknowledgment. + +**What to document:** +- [ ] Dataset licenses cited +- [ ] Code licenses respected +- [ ] Version numbers included + +#### 13. Asset Documentation +New releases need structured templates documenting training details, limitations, consent procedures, and licensing information. + +**For new datasets/models:** +- [ ] Datasheet or model card +- [ ] Training data documentation +- [ ] Known limitations + +#### 14. Human Subjects +Crowdsourcing studies must include participant instructions, screenshots, compensation details, and comply with minimum wage requirements. + +**What to include:** +- [ ] Task instructions +- [ ] Compensation details +- [ ] Time estimates + +#### 15. IRB Approvals +Human subjects research requires documented institutional review board approval or equivalent, with risk descriptions disclosed (maintaining anonymity at submission). + +**What to verify:** +- [ ] IRB approval obtained +- [ ] Risk assessment completed +- [ ] Anonymized at submission + +#### 16. LLM Declaration +Usage of large language models as core methodology components requires disclosure; writing/editing use doesn't require declaration. + +**What to disclose:** +- [ ] LLM used as core methodology component +- [ ] How LLM was used +- [ ] (Writing assistance doesn't require disclosure) + +### Response Format + +Authors select "yes," "no," or "N/A" per question, with optional 1-2 sentence justifications. + +**Important:** Reviewers are explicitly instructed not to penalize honest limitation acknowledgment. + +--- + +## ICML Paper Checklist + +### Broader Impact Statement + +ICML requires a Broader Impact Statement at the end of the paper, before references. This does NOT count toward the page limit. + +**Required elements:** +- Potential positive impacts +- Potential negative impacts +- Mitigation strategies +- Who may be affected + +### ICML Specific Requirements + +#### Reproducibility Checklist + +- [ ] Data splits clearly specified +- [ ] Hyperparameters listed +- [ ] Search ranges documented +- [ ] Selection method explained +- [ ] Compute resources specified +- [ ] Code availability stated + +#### Statistical Reporting + +- [ ] Error bars on all figures +- [ ] Standard deviation vs standard error specified +- [ ] Number of runs stated +- [ ] Significance tests if comparing methods + +#### Anonymization + +- [ ] No author names in paper +- [ ] No acknowledgments +- [ ] No grant numbers +- [ ] Prior work cited in third person +- [ ] No identifiable repository URLs + +--- + +## ICLR Requirements + +### LLM Disclosure Policy (New for 2026) + +ICLR has a specific LLM disclosure requirement: + +> "If LLMs played a significant role in research ideation and/or writing to the extent that they could be regarded as a contributor, authors must describe their precise role in a separate appendix section." + +**When disclosure is required:** +- LLM used for significant research ideation +- LLM used for substantial writing +- LLM could be considered a contributor + +**When disclosure is NOT required:** +- Grammar checking +- Minor editing assistance +- Code completion tools + +**Consequences of non-disclosure:** +- Desk rejection +- Potential post-publication issues + +### ICLR Specific Requirements + +#### Reproducibility Statement (Optional but Recommended) + +Add a statement referencing: +- Supporting materials +- Code availability +- Data availability +- Model checkpoints + +#### Ethics Statement (Optional) + +Address potential concerns in ≤1 page. Does not count toward page limit. + +#### Reciprocal Reviewing + +- Authors on 3+ papers must serve as reviewers for ≥6 papers +- Each submission needs ≥1 author registered to review ≥3 papers + +--- + +## ACL Requirements + +### Limitations Section (Mandatory) + +ACL specifically requires a Limitations section: + +**What to include:** +- Strong assumptions made +- Scope limitations +- When method may fail +- Generalization concerns + +**Important:** The Limitations section does NOT count toward the page limit. + +### ACL Specific Checklist + +#### Responsible NLP + +- [ ] Bias considerations addressed +- [ ] Fairness evaluated if applicable +- [ ] Dual-use concerns discussed + +#### Multilingual Considerations + +If applicable: +- [ ] Language diversity addressed +- [ ] Non-English languages included +- [ ] Translation quality verified + +#### Human Evaluation + +If applicable: +- [ ] Annotator details provided +- [ ] Agreement metrics reported +- [ ] Compensation documented + +--- + +## Universal Pre-Submission Checklist + +### Before Every Submission + +#### Paper Content + +- [ ] Abstract ≤ word limit (usually 250-300 words) +- [ ] Main content within page limit +- [ ] References complete and verified +- [ ] Limitations section included +- [ ] All figures/tables have captions +- [ ] Captions are self-contained + +#### Formatting + +- [ ] Correct template used (venue + year specific) +- [ ] Margins not modified +- [ ] Font sizes not modified +- [ ] Double-blind requirements met +- [ ] Page numbers (for review) or none (camera-ready) + +#### Technical + +- [ ] All claims supported by evidence +- [ ] Error bars included +- [ ] Baselines appropriate +- [ ] Hyperparameters documented +- [ ] Compute resources stated + +#### Reproducibility + +- [ ] Code will be available (or justification) +- [ ] Data will be available (or justification) +- [ ] Environment documented +- [ ] Commands to reproduce provided + +#### Ethics + +- [ ] Broader impacts considered +- [ ] Limitations honestly stated +- [ ] Licenses respected +- [ ] IRB obtained if needed + +#### Final Checks + +- [ ] PDF compiles without errors +- [ ] All figures render correctly +- [ ] All citations resolve +- [ ] Supplementary material organized +- [ ] Conference checklist completed + +--- + +## Quick Reference: Page Limits + +| Conference | Main Content | References | Appendix | +|------------|-------------|------------|----------| +| NeurIPS 2025 | 9 pages | Unlimited | Unlimited (checklist separate) | +| ICML 2026 | 8 pages (+1 camera) | Unlimited | Unlimited | +| ICLR 2026 | 9 pages (+1 camera) | Unlimited | Unlimited | +| ACL 2025 | 8 pages (long) | Unlimited | Unlimited | +| AAAI 2026 | 7 pages (+1 camera) | Unlimited | Unlimited | +| COLM 2025 | 9 pages (+1 camera) | Unlimited | Unlimited | + +--- + +## Template Locations + +All conference templates are in the `templates/` directory: + +``` +templates/ +├── icml2026/ # ICML 2026 official +├── iclr2026/ # ICLR 2026 official +├── neurips2025/ # NeurIPS 2025 +├── acl/ # ACL style files +├── aaai2026/ # AAAI 2026 +└── colm2025/ # COLM 2025 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/citation-workflow.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/citation-workflow.md new file mode 100644 index 0000000..b7ec90b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/citation-workflow.md @@ -0,0 +1,562 @@ +# Citation Management & Hallucination Prevention + +This reference provides a complete workflow for managing citations programmatically, preventing AI-generated citation hallucinations, and maintaining clean bibliographies. + +--- + +## Contents + +- [Why Citation Verification Matters](#why-citation-verification-matters) +- [Citation APIs Overview](#citation-apis-overview) +- [Verified Citation Workflow](#verified-citation-workflow) +- [Python Implementation](#python-implementation) +- [BibTeX Management](#bibtex-management) +- [Common Citation Formats](#common-citation-formats) +- [Troubleshooting](#troubleshooting) + +--- + +## Why Citation Verification Matters + +### The Hallucination Problem + +Research has documented significant issues with AI-generated citations: +- **~40% error rate** in AI-generated citations (Enago Academy research) +- NeurIPS 2025 found **100+ hallucinated citations** slipped through review +- Common errors include: + - Fabricated paper titles with real author names + - Wrong publication venues or years + - Non-existent papers with plausible metadata + - Incorrect DOIs or arXiv IDs + +### Consequences + +- Desk rejection at some venues +- Loss of credibility with reviewers +- Potential retraction if published +- Wasted time chasing non-existent sources + +### Solution + +**Never generate citations from memory—always verify programmatically.** + +--- + +## Citation APIs Overview + +### Primary APIs + +| API | Coverage | Rate Limits | Best For | +|-----|----------|-------------|----------| +| **Semantic Scholar** | 214M papers | 1 RPS (free key) | ML/AI papers, citation graphs | +| **CrossRef** | 140M+ DOIs | Polite pool with mailto | DOI lookup, BibTeX retrieval | +| **arXiv** | Preprints | 3-second delays | ML preprints, PDF access | +| **OpenAlex** | 240M+ works | 100K/day, 10 RPS | Open alternative to MAG | + +### API Selection Guide + +``` +Need ML paper search? → Semantic Scholar +Have DOI, need BibTeX? → CrossRef content negotiation +Looking for preprint? → arXiv API +Need open data, bulk access? → OpenAlex +``` + +### No Official Google Scholar API + +Google Scholar has no official API. Scraping violates ToS. Use SerpApi ($75-275/month) only if Semantic Scholar coverage is insufficient. + +--- + +## Verified Citation Workflow + +### 5-Step Process + +``` +1. SEARCH → Query Semantic Scholar with specific keywords + ↓ +2. VERIFY → Confirm paper exists in 2+ sources + ↓ +3. RETRIEVE → Get BibTeX via DOI content negotiation + ↓ +4. VALIDATE → Confirm the claim appears in source + ↓ +5. ADD → Add verified entry to .bib file +``` + +### Step 1: Search + +Use Semantic Scholar for ML/AI papers: + +```python +from semanticscholar import SemanticScholar + +sch = SemanticScholar() +results = sch.search_paper("transformer attention mechanism", limit=10) + +for paper in results: + print(f"Title: {paper.title}") + print(f"Year: {paper.year}") + print(f"DOI: {paper.externalIds.get('DOI', 'N/A')}") + print(f"arXiv: {paper.externalIds.get('ArXiv', 'N/A')}") + print(f"Citation count: {paper.citationCount}") + print("---") +``` + +### Step 2: Verify Existence + +Confirm paper exists in at least two sources: + +```python +import requests + +def verify_paper(doi=None, arxiv_id=None, title=None): + """Verify paper exists in multiple sources.""" + sources_found = [] + + # Check Semantic Scholar + sch = SemanticScholar() + if doi: + paper = sch.get_paper(f"DOI:{doi}") + if paper: + sources_found.append("Semantic Scholar") + + # Check CrossRef (via DOI) + if doi: + resp = requests.get(f"https://api.crossref.org/works/{doi}") + if resp.status_code == 200: + sources_found.append("CrossRef") + + # Check arXiv + if arxiv_id: + resp = requests.get( + f"http://export.arxiv.org/api/query?id_list={arxiv_id}" + ) + if "" in resp.text: + sources_found.append("arXiv") + + return len(sources_found) >= 2, sources_found +``` + +### Step 3: Retrieve BibTeX + +Use DOI content negotiation for guaranteed accuracy: + +```python +import requests + +def doi_to_bibtex(doi: str) -> str: + """Get verified BibTeX from DOI via CrossRef content negotiation.""" + response = requests.get( + f"https://doi.org/{doi}", + headers={"Accept": "application/x-bibtex"}, + allow_redirects=True + ) + response.raise_for_status() + return response.text + +# Example: "Attention Is All You Need" +bibtex = doi_to_bibtex("10.48550/arXiv.1706.03762") +print(bibtex) +``` + +### Step 4: Validate Claims + +Before citing a paper for a specific claim, verify the claim exists: + +```python +def get_paper_abstract(doi): + """Get abstract to verify claims.""" + sch = SemanticScholar() + paper = sch.get_paper(f"DOI:{doi}") + return paper.abstract if paper else None + +# Verify claim appears in abstract +abstract = get_paper_abstract("10.48550/arXiv.1706.03762") +claim = "attention mechanism" +if claim.lower() in abstract.lower(): + print("Claim appears in paper") +``` + +### Step 5: Add to Bibliography + +Add verified entry to your .bib file with consistent key format: + +```python +def generate_citation_key(bibtex: str) -> str: + """Generate consistent citation key: author_year_firstword.""" + import re + + # Extract author + author_match = re.search(r'author\s*=\s*\{([^}]+)\}', bibtex, re.I) + if author_match: + first_author = author_match.group(1).split(',')[0].split()[-1] + else: + first_author = "unknown" + + # Extract year + year_match = re.search(r'year\s*=\s*\{?(\d{4})\}?', bibtex, re.I) + year = year_match.group(1) if year_match else "0000" + + # Extract title first word + title_match = re.search(r'title\s*=\s*\{([^}]+)\}', bibtex, re.I) + if title_match: + first_word = title_match.group(1).split()[0].lower() + first_word = re.sub(r'[^a-z]', '', first_word) + else: + first_word = "paper" + + return f"{first_author.lower()}_{year}_{first_word}" +``` + +--- + +## Python Implementation + +### Complete Citation Manager Class + +```python +""" +Citation Manager - Verified citation workflow for ML papers. +""" + +import requests +import time +from typing import Optional, List, Dict, Tuple +from dataclasses import dataclass + +try: + from semanticscholar import SemanticScholar +except ImportError: + print("Install: pip install semanticscholar") + SemanticScholar = None + +@dataclass +class Paper: + title: str + authors: List[str] + year: int + doi: Optional[str] + arxiv_id: Optional[str] + venue: Optional[str] + citation_count: int + abstract: Optional[str] + +class CitationManager: + """Manage citations with verification.""" + + def __init__(self, api_key: Optional[str] = None): + self.sch = SemanticScholar(api_key=api_key) if SemanticScholar else None + self.verified_papers: Dict[str, Paper] = {} + + def search(self, query: str, limit: int = 10) -> List[Paper]: + """Search for papers using Semantic Scholar.""" + if not self.sch: + raise RuntimeError("Semantic Scholar not available") + + results = self.sch.search_paper(query, limit=limit) + papers = [] + + for r in results: + paper = Paper( + title=r.title, + authors=[a.name for a in (r.authors or [])], + year=r.year or 0, + doi=r.externalIds.get('DOI') if r.externalIds else None, + arxiv_id=r.externalIds.get('ArXiv') if r.externalIds else None, + venue=r.venue, + citation_count=r.citationCount or 0, + abstract=r.abstract + ) + papers.append(paper) + + return papers + + def verify(self, paper: Paper) -> Tuple[bool, List[str]]: + """Verify paper exists in multiple sources.""" + sources = [] + + # Already found in Semantic Scholar via search + sources.append("Semantic Scholar") + + # Check CrossRef if DOI available + if paper.doi: + try: + resp = requests.get( + f"https://api.crossref.org/works/{paper.doi}", + timeout=10 + ) + if resp.status_code == 200: + sources.append("CrossRef") + except: + pass + + # Check arXiv if ID available + if paper.arxiv_id: + try: + resp = requests.get( + f"http://export.arxiv.org/api/query?id_list={paper.arxiv_id}", + timeout=10 + ) + if "" in resp.text and "" in resp.text: + sources.append("arXiv") + except: + pass + + return len(sources) >= 2, sources + + def get_bibtex(self, paper: Paper) -> Optional[str]: + """Get BibTeX for verified paper.""" + if paper.doi: + try: + resp = requests.get( + f"https://doi.org/{paper.doi}", + headers={"Accept": "application/x-bibtex"}, + timeout=10, + allow_redirects=True + ) + if resp.status_code == 200: + return resp.text + except: + pass + + # Fallback: generate from paper data + return self._generate_bibtex(paper) + + def _generate_bibtex(self, paper: Paper) -> str: + """Generate BibTeX from paper metadata.""" + # Generate citation key + first_author = paper.authors[0].split()[-1] if paper.authors else "unknown" + first_word = paper.title.split()[0].lower().replace(',', '').replace(':', '') + key = f"{first_author.lower()}_{paper.year}_{first_word}" + + # Format authors + authors = " and ".join(paper.authors) if paper.authors else "Unknown" + + bibtex = f"""@article{{{key}, + title = {{{paper.title}}}, + author = {{{authors}}}, + year = {{{paper.year}}}, + {'doi = {' + paper.doi + '},' if paper.doi else ''} + {'eprint = {' + paper.arxiv_id + '},' if paper.arxiv_id else ''} + {'journal = {' + paper.venue + '},' if paper.venue else ''} +}}""" + return bibtex + + def cite(self, query: str) -> Optional[str]: + """Full workflow: search, verify, return BibTeX.""" + # Search + papers = self.search(query, limit=5) + if not papers: + return None + + # Take top result + paper = papers[0] + + # Verify + verified, sources = self.verify(paper) + if not verified: + print(f"Warning: Could only verify in {sources}") + + # Get BibTeX + bibtex = self.get_bibtex(paper) + + # Cache + if bibtex: + self.verified_papers[paper.title] = paper + + return bibtex + + +# Usage example +if __name__ == "__main__": + cm = CitationManager() + + # Search and cite + bibtex = cm.cite("attention is all you need transformer") + if bibtex: + print(bibtex) +``` + +### Quick Functions + +```python +def quick_cite(query: str) -> str: + """One-liner citation.""" + cm = CitationManager() + return cm.cite(query) + +def batch_cite(queries: List[str], output_file: str = "references.bib"): + """Cite multiple papers and save to file.""" + cm = CitationManager() + bibtex_entries = [] + + for query in queries: + print(f"Processing: {query}") + bibtex = cm.cite(query) + if bibtex: + bibtex_entries.append(bibtex) + time.sleep(1) # Rate limiting + + with open(output_file, 'w') as f: + f.write("\n\n".join(bibtex_entries)) + + print(f"Saved {len(bibtex_entries)} citations to {output_file}") +``` + +--- + +## BibTeX Management + +### BibTeX vs BibLaTeX + +| Feature | BibTeX | BibLaTeX | +|---------|--------|----------| +| Unicode support | Limited | Full | +| Entry types | Standard | Extended (@online, @dataset) | +| Customization | Limited | Highly flexible | +| Backend | bibtex | Biber (recommended) | + +**Recommendation**: Use BibLaTeX with Biber for new papers. + +### LaTeX Setup + +```latex +% In preamble +\usepackage[ + backend=biber, + style=numeric, + sorting=none +]{biblatex} +\addbibresource{references.bib} + +% In document +\cite{vaswani_2017_attention} + +% At end +\printbibliography +``` + +### Citation Commands + +```latex +\cite{key} % Numeric: [1] +\citep{key} % Parenthetical: (Author, 2020) +\citet{key} % Textual: Author (2020) +\citeauthor{key} % Just author name +\citeyear{key} % Just year +``` + +### Consistent Citation Keys + +Use format: `author_year_firstword` + +``` +vaswani_2017_attention +devlin_2019_bert +brown_2020_language +``` + +--- + +## Common Citation Formats + +### Conference Paper + +```bibtex +@inproceedings{vaswani_2017_attention, + title = {Attention Is All You Need}, + author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and + Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and + Kaiser, Lukasz and Polosukhin, Illia}, + booktitle = {Advances in Neural Information Processing Systems}, + volume = {30}, + year = {2017}, + publisher = {Curran Associates, Inc.} +} +``` + +### Journal Article + +```bibtex +@article{hochreiter_1997_long, + title = {Long Short-Term Memory}, + author = {Hochreiter, Sepp and Schmidhuber, J{\"u}rgen}, + journal = {Neural Computation}, + volume = {9}, + number = {8}, + pages = {1735--1780}, + year = {1997}, + publisher = {MIT Press} +} +``` + +### arXiv Preprint + +```bibtex +@misc{brown_2020_language, + title = {Language Models are Few-Shot Learners}, + author = {Brown, Tom and Mann, Benjamin and Ryder, Nick and others}, + year = {2020}, + eprint = {2005.14165}, + archiveprefix = {arXiv}, + primaryclass = {cs.CL} +} +``` + +--- + +## Troubleshooting + +### Common Issues + +**Issue: Semantic Scholar returns no results** +- Try more specific keywords +- Check spelling of author names +- Use quotation marks for exact phrases + +**Issue: DOI doesn't resolve to BibTeX** +- DOI may be registered but not linked to CrossRef +- Try arXiv ID instead if available +- Generate BibTeX from metadata manually + +**Issue: Rate limiting errors** +- Add delays between requests (1-3 seconds) +- Use API key if available +- Cache results to avoid repeat queries + +**Issue: Encoding problems in BibTeX** +- Use proper LaTeX escaping: `{\"u}` for ü +- Ensure file is UTF-8 encoded +- Use BibLaTeX with Biber for better Unicode + +### Verification Checklist + +Before adding a citation: + +- [ ] Paper found in at least 2 sources +- [ ] DOI or arXiv ID verified +- [ ] BibTeX retrieved (not generated from memory) +- [ ] Entry type correct (@inproceedings vs @article) +- [ ] Author names complete and correctly formatted +- [ ] Year and venue verified +- [ ] Citation key follows consistent format + +--- + +## Additional Resources + +**APIs:** +- Semantic Scholar: https://api.semanticscholar.org/api-docs/ +- CrossRef: https://www.crossref.org/documentation/retrieve-metadata/rest-api/ +- arXiv: https://info.arxiv.org/help/api/basics.html +- OpenAlex: https://docs.openalex.org/ + +**Python Libraries:** +- `semanticscholar`: https://pypi.org/project/semanticscholar/ +- `arxiv`: https://pypi.org/project/arxiv/ +- `habanero` (CrossRef): https://github.com/sckott/habanero + +**Verification Tools:** +- Citely: https://citely.ai/citation-checker +- ReciteWorks: https://reciteworks.com/ diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/README.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/README.md new file mode 100644 index 0000000..42abdf6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/README.md @@ -0,0 +1,58 @@ +# Academic Writing Knowledge Base + +This knowledge base contains reusable academic writing knowledge mined from papers. + +## Canonical maintained memory + +The canonical paper-miner memory is: + +- `paper-miner-writing-memory.md` + +This is the **only maintained paper-miner writing memory**. + +It stores: +- writing patterns mined, +- structure signals, +- reusable phrasing, +- venue-specific signals, +- how those signals help future writing, +- and a source index. + +## Maintenance rule + +`paper-miner` always writes mined writing knowledge into `paper-miner-writing-memory.md`. + +This memory is: +- **global**, +- **cross-project**, +- **not project-specific**. + +If `paper-miner` is invoked inside a project, it may use project context to understand relevance, but it still writes only to the global memory. + +## Legacy files + +Older files such as: +- `structure.md` +- `writing-techniques.md` +- `submission-guides.md` +- `review-response.md` + +may still exist as historical material, but new paper-miner updates should treat `paper-miner-writing-memory.md` as the canonical maintained memory. + +## Usage + +Use this knowledge base when: +- drafting papers, +- improving section structure, +- borrowing reusable phrasing patterns, +- preparing rebuttals, +- studying venue-facing writing signals. + +## Contributing + +When `paper-miner` analyzes a new paper: +1. extract actionable writing knowledge, +2. merge it into `paper-miner-writing-memory.md`, +3. preserve source attribution, +4. avoid duplicate patterns, +5. keep the memory compact and reusable. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/design-simplification-papers-kaiming-he.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/design-simplification-papers-kaiming-he.md new file mode 100644 index 0000000..eea5087 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/design-simplification-papers-kaiming-he.md @@ -0,0 +1,605 @@ +# Design Simplification Papers: Less Is More + +**Source**: Kaiming He et al., "Exploring Plain Vision Transformer Backbones for Object Detection" (ViTDet, 2022) + +**Paper Type**: Design simplification / Minimal adaptations paper + +**Core Pattern**: Challenge design assumptions → Minimize changes → Surprising effectiveness → Fair comparison + +--- + +## 1. Abstract Structure: The "Surprisingly" Framework + +### Pattern: Conventional Practice → Simple Alternative → Unexpected Results + +**Template**: +```markdown +Abstract: +1. [Context] Standard practice in [domain] is [conventional design] +2. [Challenge] With [new technology], this faces [challenges] +3. [Common Solution] Most work addresses this by [abandoning philosophy / adding complexity] +4. [Our Direction] We explore [different direction]: [minimal approach] +5. [Surprisingly 1] Surprisingly, we observe: (i) [simple finding 1] + and (ii) [simple finding 2] +6. [Surprisingly 2] More surprisingly, [stronger claim under conditions] +7. [Implications] This enables [benefit] without [traditional requirement] +``` + +### ViTDet Abstract Example (annotated): + +```latex +Modern object detectors consist of hierarchical backbone feature extractors +and detection-specific necks/heads (e.g., FPN, RPN). + +With Vision Transformers (ViT) emerging as powerful backbones, their plain, +non-hierarchical nature poses challenges: How to address multi-scale objects? + +One solution abandons the plain ViT philosophy, re-introducing hierarchical +designs (e.g., Swin). + +We pursue a different direction: plain ViT backbones with minimal adaptations. + +Surprisingly, we observe: (i) A simple feature pyramid from a single-scale map +is sufficient (without FPN), and (ii) Window attention without shifting is +sufficient (with a few propagation blocks). + +More surprisingly, under some circumstances, our ViTDet can compete with +leading hierarchical detectors like Swin. + +With MAE pre-training, ViTDet outperforms hierarchical counterparts, +especially for larger models. + +This decouples pre-training from fine-tuning, maintaining independence of +upstream vs downstream tasks. +``` + +### Key Techniques: + +1. **"Modern...consist of..."** - Establish conventional practice +2. **"With...emerging as..."** - New technology, new challenge +3. **"abandons the...philosophy"** - Critique common solutions +4. **"We pursue a different direction"** - Clear positioning +5. **"Surprisingly, we observe: (i)... and (ii)..."** - First surprise +6. **"More surprisingly..."** - Second, deeper surprise +7. **"under some circumstances"** - Measured claim +8. **"sufficient"** - Scientific (not "optimal") +9. **"without [common practice]"** - Negative emphasis + +--- + +## 2. Introduction: The "Challenge Assumptions" Framework + +### Pattern: Tradition → New Challenge → Common Compromise → Your Alternative → Philosophy + +**Structure**: +```markdown +1. [Traditional Practice] Established design in [field] +2. [Evolution] How this emerged historically ("For a long while...") +3. [New Challenge] [New technology] with [different characteristics] +4. [Philosophy Clash] Original [tech] has "'minimalist' pursuit" + - Questions: "How can we...?" "Is [X] too inefficient?" +5. [Common Solution] One solution: [abandon philosophy] → [revert to old design] + - Acknowledge: "has shown successful results" +6. [Your Direction] "we pursue a different direction" + - Motivation: "If successful, enables [benefit]" +7. [Philosophy] "in part follows the [philosophy] of '[concept]'" +8. [Surprising Findings] "Surprisingly, we observe..." +9. [Implications] "More surprisingly..." → Competitive results +``` + +### ViTDet Introduction Flow: + +#### Traditional Practice (Establish Context) +```latex +Modern object detectors in general consist of a backbone feature extractor +that is agnostic to the detection task and a set of necks and heads that +incorporate detection-specific prior knowledge. + +Common components in the necks/heads may include Region-of-Interest (RoI) +operations, Region Proposal Networks (RPN) or anchors, Feature Pyramid +Networks (FPN), etc. +``` + +**Technique**: +- **"in general consist of"** - Standard architecture +- **"agnostic to"** vs **"detection-specific"** - Clear division +- **"may include"** - Examples, not exhaustive + +#### Historical Evolution +```latex +For a long while, these backbones have been multi-scale, hierarchical +architectures due to the de facto design of convolutional networks (ConvNet), +which has heavily influenced the neck/head design for detecting objects at +multiple scales (e.g., FPN). +``` + +**Technique**: +- **"For a long while"** - Historical dimension +- **"due to...which has heavily influenced"** - Causal chain +- **"de facto design"** - Established convention + +#### New Technology Challenge +```latex +Over the past year, Vision Transformers (ViT) have been established as a +powerful backbone for visual recognition. + +Unlike typical ConvNets, the original ViT is a plain, non-hierarchical +architecture that maintains a single-scale feature map throughout. + +Its 'minimalist' pursuit is met with challenges when applied to object +detection—e.g., How can we address multi-scale objects in a downstream task +with a plain backbone from upstream pre-training? Is a plain ViT too +inefficient to use with high-resolution detection images? +``` + +**Technique**: +- **"Over the past year...have been established as"** - Timeframe +- **"Unlike typical ConvNets"** - Direct contrast +- **"plain, non-hierarchical"**, **"single-scale"** - Key characteristics +- **"'minimalist' pursuit"** - Philosophy (in quotes) +- **Two questions**: Challenge reader to think + +#### Common Solution (Acknowledge then Pivot) +```latex +One solution, which abandons this pursuit, is to re-introduce hierarchical +designs into the backbone. + +This solution, e.g., Swin Transformers and related works, can inherit the +ConvNet-based detector design and has shown successful results. +``` + +**Technique**: +- **"which abandons this pursuit"** - Critique (respectful) +- **"can inherit"** - Acknowledge advantage +- **"has shown successful results"** - Don't deny effectiveness + +#### Your Different Direction +```latex +In this work, we pursue a different direction: we explore object detectors +that use only plain, non-hierarchical backbones. + +If this direction is successful, it will enable the use of original ViT +backbones for object detection; this will decouple the pre-training design +from the fine-tuning demands, maintaining the independence of upstream vs. +downstream tasks, as has been the case for ConvNet-based research. +``` + +**Technique**: +- **"we pursue a different direction"** - Clear positioning +- **"If this direction is successful, it will enable..."** - Motivation +- **"decouple"**, **"independence"** - Philosophy keywords +- **"as has been the case for..."** - Historical precedent + +#### Philosophy Elevation +```latex +This direction also in part follows the ViT philosophy of 'fewer inductive +biases' in the pursuit of universal features. + +As the non-local self-attention computation can learn translation-equivariant +features, they may also learn scale-equivariant features from certain forms +of supervised or self-supervised pre-training. +``` + +**Technique**: +- **"in part follows the...philosophy of"** - Theoretical connection +- **"fewer inductive biases"** - Core concept +- **Analogy**: translation-equivariant → scale-equivariant +- **"may also learn"** - Speculation (honest) + +#### Surprising Findings +```latex +Surprisingly, we observe: (i) it is sufficient to build a simple feature +pyramid from a single-scale feature map (without the common FPN design) and +(ii) it is sufficient to use window attention (without shifting) aided with +very few cross-window propagation blocks. +``` + +**Technique**: +- **"Surprisingly, we observe:"** - Marker +- **(i)** and **(ii)** - Structured list +- **"sufficient to"** - Not "optimal", scientific phrasing +- **"without the common [X]"** - Negative differentiation + +#### Deeper Surprise +```latex +More surprisingly, under some circumstances, our plain-backbone detector, +named ViTDet, can compete with the leading hierarchical-backbone detectors +(e.g., Swin, MViT). + +With Masked Autoencoder (MAE) pre-training, our plain-backbone detector can +outperform the hierarchical counterparts that are pre-trained on ImageNet-1K/21K +with supervision (Figure 3). + +The gains are more prominent for larger model sizes. +``` + +**Technique**: +- **"More surprisingly"** - Progressive emphasis +- **"under some circumstances"** - Measured claim +- **"named ViTDet"** - Brand at results +- **Specific comparison**: MAE vs ImageNet supervised +- **"The gains are more prominent for..."** - Pattern observation + +--- + +## 3. Methods Section: The "Minimal Adaptations" Narrative + +### Pattern: We Don't Aim to Invent, We Minimize + +**Structure**: +```markdown +1. [Declaration] We do NOT aim to develop new components +2. [Philosophy] Instead, make minimal adaptations sufficient to overcome challenges +3. [Specific] In particular, [what we actually do] +4. [Abandonment] This abandons [traditional component] +5. [Decoupling] Adaptations only during fine-tuning, do not alter pre-training +6. [Contrast] This is in contrast to [recent methods] that [what they do] +7. [Benefit] Our scenario enables [benefit], without [cost] +``` + +### ViTDet Methods Narrative: + +```latex +In our study, we do not aim to develop new components; instead, we make +minimal adaptations that are sufficient to overcome the aforementioned +challenges. + +In particular, our detector builds a simple feature pyramid from only the +last feature map of a plain ViT backbone (Figure 1). + +This abandons the FPN design and waives the requirement of a hierarchical +backbone. + +These adaptations are made only during fine-tuning and do not alter pre-training. + +This is in contrast to the recent methods that modify the attention computation +directly with backbone pre-training (e.g., Swin, MViT). + +Our scenario enables us to use the original ViT backbone for detection, without +redesigning pre-training architectures. +``` + +**Techniques**: +- **"we do not aim to develop new components"** - Clear scope +- **"minimal adaptations"** - Philosophy +- **"sufficient to"** - Not maximal, necessary +- **"This abandons..."** - What you give up +- **"only during fine-tuning"** - Temporal boundary +- **"do not alter pre-training"** - Upstream independence +- **"This is in contrast to"** - Competitor positioning +- **"enables us to use"** - Practical benefit + +--- + +## 4. Fair Comparison: The "Equal Effort" Declaration + +### Pattern: Admit Complexity → Claim Effort → Demonstrate Fairness + +**Structure**: +```markdown +1. [Admit] Modern systems involve [complexity] +2. [Claim] To compare as fairly as possible, we [effort] +3. [Specific 1] Use same [implementation] for all +4. [Specific 2] Different backbones get [appropriate treatment] +5. [Validation] Our results for [competitor] are [better/equal] to original +6. [Implication] Since we reproduce others well, comparisons are fair +``` + +### ViTDet Fair Comparison Statement: + +```latex +Modern detection systems involve many implementation details and subtleties. + +To focus on comparing backbones under as fair conditions as possible, we +incorporate the Swin and MViTv2 backbones into our implementation. + +We use the same implementation of Mask R-CNN and Cascade Mask R-CNN for all +ViT, Swin, and MViTv2 backbones. + +We use FPN for the hierarchical backbones of Swin/MViTv2. + +We search for optimal hyper-parameters separately for each backbone. +``` + +**Techniques**: +- **"involve many implementation details and subtleties"** - Admit difficulty +- **"under as fair conditions as possible"** - Effort disclaimer +- **"incorporate...into our implementation"** - What we did +- **"use the same...for all"** - Unified framework +- **"search for optimal...separately"** - Equal effort + +#### Self-Validation +```latex +Our Swin results are better than their counterparts in the original paper; +our MViTv2 results are better than or on par with those reported in the +original paper. +``` + +**Technique**: +- Report self-results → Show competence → Imply fairness + +--- + +## 5. Results: Multi-Factor Analysis + +### Pattern: Factors, Trends, Wall-Clock Time + +**Structure**: +```markdown +1. [Acknowledge Complexity] Comparisons involve [factors] +2. [Identify Trend] Our method presents better [trend behavior] +3. [Qualify] When [condition], our method [advantage] +4. [Expand] Moreover, [second dimension advantage] +5. [Explain] as [reason related to simplicity] +``` + +### ViTDet Results Narrative: + +```latex +Figure 3 plots the trade-offs. + +The comparisons here involve two factors: the backbone and the pre-training +strategy. + +Our plain-backbone detector, combined with MAE pre-training, presents better +scaling behavior. + +When the models are large, our method outperforms the hierarchical +counterparts of Swin/MViTv2, including those using IN-21K supervised +pre-training. + +Moreover, the plain ViT has a better wall-clock performance (Figure 3 right), +as the simpler blocks are more hardware-friendly. +``` + +**Techniques**: +- **"involve two factors"** - Analysis depth +- **"presents better scaling behavior"** - Trend, not just points +- **"When the models are large"** - Qualify claim +- **"Moreover"** - Second dimension +- **"better wall-clock performance"** - Practical metric +- **"simpler blocks are more hardware-friendly"** - Explain why + +--- + +## 6. "Surprisingly" Usage: Multi-Level Pattern + +### Level 1: Basic Surprise (Abstract) + +```latex +Surprisingly, we observe: (i) [simple sufficient without common practice] +and (ii) [simple sufficient without common practice] +``` + +**Characteristics**: +- Two findings (i) and (ii) +- "sufficient" not "optimal" +- "without [common practice]" +- Structured presentation + +### Level 2: Competitive Surprise (Introduction) + +```latex +More surprisingly, under some circumstances, our [method] can compete +with the leading [competitors]. +``` + +**Characteristics**: +- "More surprisingly" - Progressive +- "under some circumstances" - Measured +- "compete with" - Not "beat", competitive +- Name competitors specifically + +### Level 3: Superiority Surprise (Introduction) + +```latex +With [specific condition], our [method] can outperform the [competitors] +that use [stronger condition]. + +The gains are more prominent for [specific condition]. +``` + +**Characteristics**: +- Specific conditions compared +- "outperform" - Stronger claim here +- Pattern observation: "more prominent for" +- Shows understanding of when/where + +--- + +## 7. Ablation Study: Incremental + Destructive + +### Pattern: Baseline → Incremental Additions → Sufficient + +**Table Design**: +```markdown +Table X: [Component] Ablation +┌──────────────────────────────────────────┐ +│ Baseline | Metric | Δ │ +├──────────────────────────────────────────┤ +│ no [component] | 47.8 | - │ +│ (a) [common] | 50.3 | +2.5 │ +│ (b) [variant] | 50.9 | +3.1 │ +│ (c) ours: simple | 51.2 | +3.4 ✓ │ +├──────────────────────────────────────────┤ +│ Conclusion: Our simple [X] is sufficient │ +└──────────────────────────────────────────┘ +``` + +### ViTDet Table 1 Example: + +```latex +pyramid design APbox APmask +───────────────────────────────────────── +no feature pyramid 47.8 42.5 +(a) FPN, 4-stage 50.3 44.9 +(b) FPN, last-map 50.9 45.3 +(c) simple feature pyramid 51.2 45.5 +``` + +**Techniques**: +- **Baseline**: "no [X]" shows it's needed +- **(a), (b), (c)**: Progressive variations +- **Δ标注**: (+2.5) - Show incremental gains +- **Conclusion text**: "our simple pyramid is sufficient" + +--- + +## 8. "Interestingly" Usage: Pattern + Explanation + +### Pattern: Observation → Literature Support → Explanation + +**Structure**: +```markdown +Interestingly, [observation]. + +This is in line with the observation in [paper] that [their finding]. + +[Additional explanation or hypothesis]. +``` + +### ViTDet Example: + +```latex +Interestingly, performing propagation in the last 4 blocks is nearly as +good as even placement. + +This is in line with the observation in ViT [14] that ViT has longer +attention distance in later blocks and is more localized in earlier ones. +``` + +**Techniques**: +- **"Interestingly"** - Marker for unexpected +- **Observation**: Specific finding +- **"in line with the observation in"** - Literature support +- **Explanation**: Why it makes sense + +--- + +## 9. Minimalism Keywords: Design Simplification Vocabulary + +**Philosophy Keywords**: +- "minimal" - "minimal adaptations" +- "sufficient" - "is sufficient to" (not "optimal") +- "simple" - "simple feature pyramid" +- "plain" - "plain backbone" +- "decouple" - "decouple pre-training from fine-tuning" +- "independence" - "independence of upstream vs downstream" + +**Direction Keywords**: +- "pursue a different direction" - Positioning +- "in contrast to" - Differentiation +- "abandons" - What you give up +- "enables" - What your approach allows + +**Measured Claim Keywords**: +- "under some circumstances" - Not always +- "can compete with" - Competitive, not dominant +- "more prominent for" - When effect is stronger +- "is sufficient" - Necessary, not maximal + +**Surprise Markers** (use in order): +1. "Surprisingly" - First finding +2. "More surprisingly" - Deeper finding +3. "Interestingly" - Pattern observation +4. "Notably" - Important detail +5. "It is worth noting that" - Caveat/clarification + +--- + +## 10. Common Mistakes in Design Simplification Papers + +### ❌ Don't: +- Claim your method is "optimal" - You're simplifying, not optimizing +- Attack common practices - Acknowledge their value first +- Overgeneralize - "under some circumstances" is honest +- Forget to show fair comparison - Prove you tried hard with baselines +- Hide complexity - Admit what you don't address + +### ✅ Do: +- Use "sufficient" instead of "optimal" +- Say what you DON'T do ("do not aim to develop new components") +- Emphasize minimal changes ("minimal adaptations") +- Report when your method wins and when it doesn't +- Show "surprisingly" findings with proper qualification +- Demonstrate fair comparison effort +- Adapt only where necessary (fine-tuning, not pre-training) + +--- + +## 11. Revision Checklist for Design Simplification Papers + +**Before Submission, Verify:** + +- [ ] Abstract has "Surprisingly, we observe: (i)... and (ii)..." +- [ ] Introduction establishes conventional practice first +- [ ] Common solution is acknowledged ("has shown successful results") +- [ ] "We pursue a different direction" is stated clearly +- [ ] Philosophy is elevated ("fewer inductive biases") +- [ ] "More surprisingly" used for deeper claim +- [ ] Methods section says "we do not aim to develop new components" +- [ ] "minimal adaptations" philosophy stated +- [ ] "only during fine-tuning" boundary specified +- [ ] Fair comparison effort described explicitly +- [ ] Self-validation shown (our reproduction of others is good) +- [ ] Multi-factor analysis in results (scaling, wall-clock) +- [ ] Ablations show incremental progression +- [ ] "sufficient" used, not "optimal" +- [ ] Under what conditions is stated ("under some circumstances") + +--- + +## 12. Example: Applying This Pattern + +### Original Idea (Not Design Simplification): +"We propose a new feature pyramid that improves detection AP by 3%." + +### Design Simplification Version: +"Modern detectors use hierarchical backbones with FPN. With plain ViT +emerging as powerful backbones, a common solution re-introduces hierarchy +(abandoning the plain philosophy). We pursue a different direction: plain +backbones with minimal adaptations. Surprisingly, we observe a simple feature +pyramid from a single-scale map is sufficient (without FPN). More +surprisingly, with MAE pre-training, ViTDet competes with hierarchical +detectors, especially for larger models. This decouples pre-training from +fine-tuning, maintaining upstream/downstream independence." + +**The Design Simplification Frame**: +- Conventional: Hierarchy + FPN +- Challenge: Plain ViT is...plain +- Common: Swin (abandons philosophy) +- Ours: Minimal adaptations +- Surprise: Simple is sufficient +- Philosophy: Decoupling, independence + +--- + +## Paper Metadata + +**Title**: Exploring Plain Vision Transformer Backbones for Object Detection (ViTDet) + +**Authors**: Yanghao Li, Hanzi Mao, Kaiming He + +**Venue**: ECCV 2022 + +**arXiv**: 2203.16527 + +**Key Concepts**: +- Plain ViT for detection (no hierarchy needed) +- Simple feature pyramid (no FPN needed) +- Minimal adaptations philosophy +- Decoupling pre-training from fine-tuning +- MAE pre-training synergy + +--- + +## Extracted by + +**Date**: 2026-01-26 + +**Source**: Analysis of ViTDet paper (21 pages) + +**Extraction Focus**: Design simplification paper writing patterns, "surprisingly" +findings reporting, minimal adaptations philosophy, fair comparison strategies + +**For Integration**: ml-paper-writing skill knowledge base diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/kaiming_he_injection_record.json b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/kaiming_he_injection_record.json new file mode 100644 index 0000000..7ffd675 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/kaiming_he_injection_record.json @@ -0,0 +1,153 @@ +{ + "metadata": { + "source": "Kaiming He Papers Analysis", + "date": "2026-01-26", + "papers_analyzed": 11, + "analysis_method": "Text extraction and pattern mining", + "latest_addition": { + "papers": ["Mean Flows", "ViTDet", "MoCo v2", "Deconstructing Denoising Diffusion Models", "Autoregressive Image Generation (MAR)"], + "extraction_date": "2026-01-26", + "new_knowledge_files": [ + "theory-driven-papers-kaiming-he.md", + "design-simplification-papers-kaiming-he.md" + ] + } + }, + "knowledge_files": { + "structure.md": { + "status": "updated", + "last_update": "2026-01-26", + "contains": "Basic structure patterns from 19 Kaiming He papers" + }, + "writing-techniques.md": { + "status": "needs_update", + "last_update": "2026-01-26", + "contains": "Basic writing techniques from 19 Kaiming He papers" + }, + "rethinking-papers-kaiming-he.md": { + "status": "complete", + "focus": "Rethinking papers, challenging conventional wisdom", + "source_paper": "Autoregressive Image Generation without Vector Quantization (NeurIPS 2024 Spotlight)" + }, + "theory-driven-papers-kaiming-he.md": { + "status": "new", + "focus": "Theory-driven papers, first principles, MeanFlow Identity", + "source_paper": "Mean Flows for One-step Generative Modeling (2025)" + }, + "design-simplification-papers-kaiming-he.md": { + "status": "new", + "focus": "Design simplification, minimal adaptations, 'Surprisingly' findings", + "source_paper": "Exploring Plain Vision Transformer Backbones for Object Detection (ViTDet, ECCV 2022)" + } + }, + "patterns_extracted": { + "introduction_frameworks": { + "principle_introduction": { + "source": "MeanFlows", + "pattern": "Background → Problem → Critique (Despite...) → Core Concept → Theory → Advantage → Results", + "keywords": ["principled", "intrinsic", "well-defined", "naturally", "first principles"] + }, + "challenge_assumptions": { + "source": "ViTDet", + "pattern": "Traditional → New Challenge → Common Solution → Our Direction → Philosophy → Surprisingly → Implications", + "keywords": ["minimal adaptations", "sufficient", "decouple", "independence", "surprisingly"] + }, + "rethinking_conventional_wisdom": { + "source": "MAR", + "pattern": "Conventional wisdom → Question → Analysis → Alternative → Results → Vision", + "keywords": ["Conventional wisdom holds that", "Is it necessary", "not a necessity"] + } + }, + "surprisingly_findings": { + "level_1": { + "pattern": "Surprisingly, we observe: (i)... and (ii)...", + "usage": "First-level surprise - basic findings", + "example": "ViTDet Abstract" + }, + "level_2": { + "pattern": "More surprisingly, under some circumstances...", + "usage": "Second-level surprise - competitive results", + "example": "ViTDet Introduction" + }, + "level_3": { + "pattern": "With [condition], outperforms... gains more prominent for...", + "usage": "Third-level surprise - superiority under conditions", + "example": "ViTDet Introduction" + }, + "variants": { + "interestingly": "Observation + literature support + explanation", + "notably": "Important detail or counter-intuitive result", + "it_is_worth_noting": "Technical caveat or clarification" + } + }, + "ablation_techniques": { + "incremental_tables": { + "pattern": "Baseline → (a) → (b) → (c) with Δ标注", + "source": "ViTDet Table 1" + }, + "destructive_comparison": { + "pattern": "Intentionally wrong values to prove necessity", + "source": "MeanFlows Table 1b" + }, + "narrative_structure": { + "observation_then_explain": "Observe pattern → Provide explanation (literature/hypothesis/theory)" + } + }, + "theoretical_derivation": { + "naming_identity": { + "pattern": "Define → Derive → Name ('X Identity')", + "source": "MeanFlows MeanFlow Identity" + }, + "step_by_step": { + "pattern": "Motivation → Derivation with 'Now we...' → Justification with 'where...'", + "source": "MeanFlows Section 2" + } + }, + "comparison_techniques": { + "principled_vs_heuristic": { + "pattern": "At the core...does not depend on...In contrast, typically rely on...", + "source": "MeanFlows" + }, + "fair_comparison_declaration": { + "pattern": "Admit complexity → Claim effort → Demonstrate fairness", + "source": "ViTDet" + }, + "multi_factor_analysis": { + "pattern": "Factors identified → Trend behavior → Wall-clock time", + "source": "ViTDet Results" + } + }, + "keyword_strategies": { + "theory_paper": ["principled", "intrinsic", "well-defined", "naturally", "self-contained", "solely originated from"], + "design_paper": ["minimal", "sufficient", "decouple", "independence", "surprisingly", "abandons"], + "rethinking_paper": ["Conventional wisdom holds that", "not a necessity", "orthogonal to", "uncharted realm"] + } + }, + "papers_analyzed_list": [ + "Non-local Neural Networks", + "SlowFast Networks", + "Rethinking ImageNet Pre-training", + "Faster R-CNN", + "Delving Deep into Rectifiers (PReLU)", + "Spatial Pyramid Pooling (SPP-net)", + "Deconstructing Denoising Diffusion Models", + "Autoregressive Image Generation without Vector Quantization (MAR)", + "Mean Flows for One-step Generative Modeling", + "Exploring Plain Vision Transformer Backbones for Object Detection (ViTDet)", + "MoCo v2: Improved Baselines with Momentum Contrastive Learning" + ], + "integration_summary": { + "total_papers": 11, + "knowledge_files": 5, + "patterns_extracted": 25, + "paper_types_identified": [ + "Theory-driven (MeanFlows)", + "Design simplification (ViTDet)", + "Rethinking (MAR)", + "Deconstruction (DDM)", + "Milestone (PReLU)", + "Multi-task (SPP-net)", + "Technical note (MoCo v2)" + ] + } +} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md new file mode 100644 index 0000000..6370647 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md @@ -0,0 +1,37 @@ +# Paper-Miner Writing Memory + +This is the **active installed writing memory** maintained by `paper-miner`. + +It stores reusable academic writing knowledge mined from papers across venues and projects. + +## Rules + +- This is the **only maintained paper-miner writing memory**. +- `paper-miner` writes here even when invoked inside a specific project. +- Do **not** create project-specific paper-miner writing memory. +- Do **not** split new mined knowledge across multiple maintained category files. +- Keep source attribution explicit and avoid duplicate entries. + +## Writing patterns mined + +<!-- paper-miner adds reusable rhetorical patterns here --> + +## Structure signals + +<!-- paper-miner adds section-flow and organization signals here --> + +## Reusable phrasing + +<!-- paper-miner adds concise reusable phrasing and transition templates here --> + +## Venue-specific signals + +<!-- paper-miner adds venue-facing style and convention signals here --> + +## How this helps our writing + +<!-- paper-miner explains how mined signals can inform future writing decisions here --> + +## Source index + +<!-- one short source entry per analyzed paper --> diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/rethinking-papers-kaiming-he.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/rethinking-papers-kaiming-he.md new file mode 100644 index 0000000..26a7c86 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/rethinking-papers-kaiming-he.md @@ -0,0 +1,1023 @@ +# "Rethinking" Papers: Challenging Conventional Wisdom + +**Source**: Kaiming He et al., "Autoregressive Image Generation without Vector Quantization" (NeurIPS 2024 Spotlight) + +**Paper Type**: Paradigm-challenging / "Rethinking" paper + +**Core Pattern**: Question deeply-held assumptions → Propose alternative → Demonstrate effectiveness + +--- + +## 1. Abstract Structure: Challenging Conventional Wisdom + +### Pattern: The "Conventional Wisdom" Opening + +**Template**: +```markdown +Abstract: +1. [Hook] Conventional wisdom holds that [widely-believed assumption]. +2. [Observation] We observe that [counter-point or nuance]. +3. [Question] Is it necessary for [core assumption]? +4. [Proposal] In this work, we propose [alternative approach]. +5. [Solution] Rather than [traditional method], we [novel method]. +6. [Results] This approach [eliminates/enables] X, achieving [strong results]. +7. [Vision] We hope this work will [broader impact statement]. +``` + +### MAR Abstract Example (annotated): + +```latex +Conventional wisdom holds that [autoregressive models for image generation +are typically accompanied by vector-quantized tokens]. + +We observe that while [discrete-valued space can facilitate representing +a categorical distribution], it is [not a necessity for autoregressive modeling]. + +In this work, we propose to [model the per-token probability distribution +using a diffusion procedure], which allows us to [apply autoregressive models +in a continuous-valued space]. + +Rather than using [categorical cross-entropy loss], we define a +[Diffusion Loss function] to model the per-token probability. + +This approach [eliminates the need for discrete-valued tokenizers]. + +We evaluate its effectiveness across [a wide range of cases], including +[standard autoregressive models and generalized masked autoregressive (MAR) variants]. + +By removing vector quantization, our image generator achieves [strong results] +while enjoying [the speed advantage of sequence modeling]. + +We hope this work will motivate [the use of autoregressive generation in +other continuous-valued domains and applications]. +``` + +### Key Techniques: + +1. **"Conventional wisdom holds that..."** - Strong, respectful opening that acknowledges prevailing beliefs +2. **"We observe that..."** - Signals empirical insight rather than mere speculation +3. **"it is not a necessity for..."** - Gentle but direct challenge to the assumption +4. **"Rather than..."** - Clear alternative positioning +5. **"This approach eliminates the need for..."** - Practical benefit statement +6. **"We hope this work will..."** - Forward-looking vision + +--- + +## 2. Introduction: The Question-Driven Framework + +### Pattern: Start with the Question + +**Traditional Introduction** (less effective): +- "Image generation is an important problem..." +- "Existing methods use VQ tokenizers..." +- "We propose a new method..." + +**"Rethinking" Introduction** (Kaiming He style): +```markdown +1. [Establish Context] Domain context + prevailing approach +2. [Identify Assumption] The widely-held belief +3. [Formulate Question] "Is it necessary for..." +4. [Analyze Requirements] What is truly essential? +5. [Propose Alternative] If alternative model exists... +6. [Present Solution] Our specific proposal +7. [Broader Implications] What this enables +``` + +### MAR Introduction Structure (lines 20-79): + +#### Part 1: Context and Prevailing Belief (lines 20-29) +```latex +Autoregressive models are currently the de facto solution to generative +models in natural language processing [38, 39, 3]. These models predict +the next word or token in a sequence based on the previous words as input. + +Given the discrete nature of languages, the inputs and outputs of these +models are in a categorical, discrete-valued space. + +This prevailing approach has led to a widespread belief that autoregressive +models are inherently linked to discrete representations. +``` + +**Technique**: Start from uncontroversial facts (NLP success) → Show how they led to a belief (AR ↔ discrete) + +#### Part 2: Consequences of the Belief (lines 25-29) +```latex +As a result, research on generalizing autoregressive models to continuous- +valued domains—most notably, image generation—has intensely focused on +discretizing the data [6, 13, 40]. + +A commonly adopted strategy is to train a discrete-valued tokenizer on +images, which involves a finite vocabulary obtained by vector quantization +(VQ) [51, 41, 41]. +``` + +**Technique**: Show concrete consequences of the belief (VQ tokenizers everywhere) + +#### Part 3: The Research Question (lines 30-33) +```latex +In this work, we aim to address the following question: + +Is it necessary for autoregressive models to be coupled with vector- +quantized representations? +``` + +**Technique**: Explicit question format. Bold, direct, centered. + +#### Part 4: Analyzing What's Essential (lines 31-37) +```latex +We note that the autoregressive nature, i.e., "predicting next tokens based +on previous ones", is independent of whether the values are discrete or +continuous. + +What is needed is to model the per-token probability distribution, which +can be measured by a loss function and used to draw samples from. + +Discrete-valued representations can be conveniently modeled by a categorical +distribution, but it is not conceptually necessary. +``` + +**Technique**: Distinguish mechanism (autoregression) from implementation (discrete tokens) + +#### Part 5: The "If..." Condition (lines 36-37) +```latex +If alternative models for per-token probability distributions are presented, +autoregressive models can be approached without vector quantization. +``` + +**Technique**: Logical bridge - "If X, then Y" sets up your contribution + +#### Part 6: Your Solution (lines 38-58) +```latex +With this observation, we propose to model the per-token probability +distribution by a diffusion procedure operating on continuous-valued domains. + +[Technical description of Diffusion Loss...] +``` + +#### Part 7: Benefits and Implications (lines 59-79) +```latex +Our approach eliminates the need for discrete-valued tokenizers. Vector- +quantized tokenizers are difficult to train and are sensitive to gradient +approximation strategies [51, 41, 40, 27]. Their reconstruction quality +often falls short compared to continuous-valued counterparts [42]. + +Our approach allows autoregressive models to enjoy the benefits of higher- +quality, non-quantized tokenizers. + +[...] + +The effectiveness of our method reveals a largely uncharted realm of image +generation: modeling the interdependence of tokens by autoregression, +jointly with the per-token distribution by diffusion. +``` + +**Technique**: Multiple benefit levels: +- **Eliminates pain points**: VQ is hard to train +- **Enables benefits**: Higher-quality tokenizers +- **Reveals new territory**: "uncharted realm" + +--- + +## 3. Rethinking Section: Dissecting the Status Quo + +### Pattern: "Rethinking X" Chapter + +When challenging conventional wisdom, dedicate a section to re-examining the assumptions. + +### MAR Section 3.1: "Rethinking Discrete-Valued Tokens" + +**Structure**: +```markdown +1. [Setup] Define the conventional approach mathematically +2. [Analysis] Identify the essential properties (not the implementation) +3. [Insight] Show that the implementation is not necessary +4. [Conclusion] State what's actually needed +``` + +### MAR Example (lines 110-126): + +#### Step 1: Define the Conventional Approach +```latex +To begin with, we revisit the roles of discrete-valued tokens in +autoregressive generation models. + +Denote as x the ground-truth token to be predicted at the next position. +With a discrete tokenizer, x can be represented as an integer: 0 ≤ x < K, +with a vocabulary size K. + +The autoregressive model produces a continuous-valued D-dim vector z ∈ R^D, +which is then projected by a K-way classifier matrix W ∈ R^(K×D). + +Conceptually, this formulation models a categorical probability distribution +in the form of p(x|z) = softmax(Wz). +``` + +**Technique**: Mathematically precise setup. Shows you deeply understand the status quo. + +#### Step 2: Identify Essential Properties +```latex +In the context of generative modeling, this probability distribution must +exhibit two essential properties. + +(i) A loss function that can measure the difference between the estimated +and true distributions. + +(ii) A sampler that can draw samples from the distribution x ~ p(x|z) at +inference time. +``` + +**Technique**: Abstract away from implementation to functional requirements + +#### Step 3: Show Convention is Not Necessary +```latex +In the case of categorical distribution, this can be simply done by the +cross-entropy loss. + +[...] + +This analysis suggests that discrete-valued tokens are not necessary for +autoregressive models. +``` + +**Technique**: "This analysis suggests" - evidence-based conclusion + +#### Step 4: What's Actually Needed +```latex +Instead, it is the requirement of modeling a distribution that is essential. + +A discrete-valued token space implies a categorical distribution, whose loss +function and sampler are simple to define. + +What we actually need are a loss function and its corresponding sampler for +distribution modeling. +``` + +**Technique**: Reposition the problem - it's about distribution modeling, not discrete tokens + +--- + +## 4. Unifying Different Methods: The "Generalized Framework" Pattern + +### Pattern: Show Two Seemingly Different Methods Are Special Cases + +**MAR Section 3.4**: "Unifying Autoregressive and Masked Generative Models" + +**Structure**: +```markdown +1. [Observation] These methods seem different but share a core principle +2. [Insight] The core principle is X, not the surface differences +3. [Demonstration] Show how Method A fits the principle +4. [Demonstration] Show how Method B fits the principle +5. [Unification] Both are special cases of a general framework +6. [Benefit] This understanding enables new combinations/insights +``` + +### MAR Example (lines 181-259): + +#### Opening Observation +```latex +We show that masked generative models, e.g., MaskGIT [4] and MAGE [29], +can be generalized under the broad concept of autoregression, i.e., +next token prediction. +``` + +#### The Insight +```latex +Bidirectional attention can perform autoregression. + +The concept of autoregression is orthogonal to network architectures: +autoregression can be done by RNNs [50], CNNs [49, 7], and +Transformers [38, 36, 6]. + +When using Transformers, although autoregressive models are popularly +implemented by causal attention, we show that they can also be done by +bidirectional attention. +``` + +**Technique**: "Orthogonal to" - shows independence of concepts + +#### Visual Demonstration (Figure 2) +```latex +Note that the goal of autoregression is to predict the next token given +the previous tokens; it does not constrain how the previous tokens +communicate with the next token. + +We can adopt the bidirectional attention implementation as done in Masked +Autoencoder (MAE) [21]. See Figure 2(b). +``` + +**Technique**: Use visualization to show "unexpected" equivalence + +#### Generalization (Figure 3) +```latex +Autoregressive models in random orders... + +Masked autoregressive models: In masked generative modeling [4, 29], +the models predict a random subset of tokens based on known/predicted +tokens. + +This can be formulated as permuting the token sequence by a random order, +and then predicting multiple tokens based on previous tokens. + +Conceptually, this is an autoregressive procedure... +``` + +**Technique**: Mathematical unification - same formula, different instantiations + +#### Naming the Generalization +```latex +We refer to this variant as Masked Autoregressive (MAR) models. + +MAR is a random-order autoregressive model that can predict multiple +tokens simultaneously. +``` + +**Technique**: Define new terminology to capture the unified concept + +--- + +## 5. Flexibility Arguments: Demonstrating Generality + +### Pattern: Show Your Method Works in Many Configurations + +**MAR Section 5.1**: "Flexibility of Diffusion Loss" + +**Structure**: +```markdown +1. [Claim] One significant advantage is flexibility with various X +2. [Demonstration 1] Works with configuration A +3. [Demonstration 2] Works with configuration B (even surprising case) +4. [Demonstration 3] Works with configuration C +5. [Insight] This flexibility enables Y +``` + +### MAR Example (lines 349-366, Table 2): + +#### Opening Claim +```latex +One significant advantage of Diffusion Loss is its flexibility with +various tokenizers. +``` + +#### Surprising Case 1: VQ Tokenizers +```latex +Diffusion Loss can be easily used even given a VQ tokenizer. + +We simply treat the continuous-valued latent before the VQ layer as the +tokens. + +This variant gives us 7.82 FID (w/o CFG), compared favorably with 8.79 +FID (Table 1) of cross-entropy loss using the same VQ tokenizer. +``` + +**Technique**: Show it works even with the "wrong" tokenizer type (VQ) + +#### Surprising Case 2: Mismatched Stride +```latex +Interestingly, Diffusion Loss also enables us to use tokenizers with +mismatched strides. + +In Table 2, we study a KL-8 tokenizer whose stride is 8 and output +sequence length is 32×32. Without increasing the sequence length of the +generator, we group 2×2 tokens into a new token. + +Despite the mismatch, we are able to obtain decent results... +``` + +**Technique**: "Interestingly" + "Despite the mismatch" - emphasizes robustness + +#### Surprising Case 3: Different Architecture +```latex +Further, this property allows us to investigate other tokenizers, e.g., +Consistency Decoder [35], a non-VQ tokenizer of a different +architecture/stride designed for different goals. +``` + +**Technique**: Show applicability beyond original design space + +#### Comprehiveness Check +```latex +For comprehensiveness, we also train a KL-16 tokenizer on ImageNet using +the code of [42]... +``` + +**Technique**: "For comprehensiveness" - signals thoroughness + +--- + +## 6. Speed/Accuracy Trade-offs: Plotting the Pareto Frontier + +### Pattern: Show Your Method Dominates or Expands the Frontier + +**MAR Section 5.2**: "Speed/accuracy Trade-off" (Figure 6) + +**Structure**: +```markdown +1. [Setup] We enjoy flexibility of X +2. [Visualization] Figure/plot showing trade-off curves +3. [Comparison 1] Compare within your variants +4. [Comparison 2] Compare to other methods +5. [Highlight] Notable point on the curve +``` + +### MAR Example (lines 425-474): + +#### Setup +```latex +Following MaskGIT [4], our MAR enjoys the flexibility of predicting +multiple tokens at a time. + +This is controlled by the number of autoregressive steps at inference time. +``` + +#### Comparison Within Family +```latex +Figure 6 plots the speed/accuracy trade-off. + +MAR has a better trade-off than its AR counterpart, noting that AR is +with the efficient kv-cache. +``` + +**Technique**: "noting that..." - acknowledge AR's advantage, still win + +#### Comparison to Other Methods +```latex +With Diffusion Loss, MAR also shows a favorable trade-off in comparison +with the recently popular Diffusion Transformer (DiT) [37]. + +As a latent diffusion model, DiT models the interdependence of all tokens +by the diffusion process. The speed/accuracy trade-off of DiT is mainly +controlled by its diffusion steps. + +Unlike our diffusion process on a small MLP, the diffusion process of DiT +involves the entire Transformer architecture. + +Our method is more accurate and faster. +``` + +**Technique**: Explain *why* you win (architectural difference) + +#### Highlight Specific Point +```latex +Notably, our method can generate at a rate of <0.3 second per image with +a strong FID of <2.0. +``` + +**Technique**: "Notably" + impressive numbers - memorable takeaway + +--- + +## 7. System-Level Comparison Tables: Organizing by Categories + +### Pattern: Group Related Work, Highlight Your Position + +**MAR Table 4**: "System-level comparison on ImageNet 256×256" + +**Structure**: +```markdown +Table 4: +┌─────────────────────────────────┐ +│ Category 1: pixel-based │ +│ - Method A │ +│ - Method B │ +├─────────────────────────────────┤ +│ Category 2: vector-quantized │ +│ - Method C │ +│ - Method D │ +├─────────────────────────────────┤ +│ Category 3: continuous-valued │ +│ - Method E │ +│ - Method F │ +├─────────────────────────────────┤ +│ **Your Methods** (highlighted) │ +│ - Your Method B │ +│ - Your Method L │ +│ - Your Method H │ +└─────────────────────────────────┘ +``` + +### MAR Example (lines 448-470): + +```latex +Table 4: System-level comparison on ImageNet 256×256 conditional +generation. Diffusion Loss enables Masked Autoregression to achieve +leading results in comparison with previous systems. + +†: LDM operates on continuous-valued tokens, though this result uses +a quantized tokenizer. + +w/o CFG w/ CFG +#params FID↓ IS↑ Pre.↑ Rec.↑ FID↓ IS↑ Pre.↑ Rec.↑ +──────────────────────────────────────────────────────────── +pixel-based +ADM [10] 554M 10.94 101.0 0.69 0.63 4.59 186.7 0.82 0.52 +VDM++ [26] 2B 2.40 225.3 - - 2.12 267.7 - - + +vector-quantized tokens +Autoreg. w/ VQGAN [13] 1.4B 15.78 78.3 - - - - - - +MaskGIT [4] 227M 6.18 182.1 0.80 0.51 - - - - +MAGE [29] 230M 6.93 195.8 - - - - - - +MAGVIT-v2 [55] 307M 3.65 200.5 - - 1.78 319.4 - - + +continuous-valued tokens +LDM-4† [42] 400M 10.56 103.5 0.71 0.62 3.60 247.7 0.87 0.48 +U-ViT-H/2-G [2] 501M - - - - 2.29 263.9 0.82 0.57 +DiT-XL/2 [37] 675M 9.62 121.5 0.67 0.67 2.27 278.2 0.83 0.57 +[... other methods ...] + +MAR-B, Diff Loss 208M 3.48 192.4 0.78 0.58 2.31 281.7 0.82 0.57 +MAR-L, Diff Loss 479M 2.60 221.4 0.79 0.60 1.78 296.0 0.81 0.60 +MAR-H, Diff Loss 943M 2.35 227.8 0.79 0.62 1.55 303.7 0.81 0.62 +``` + +**Key Techniques**: +1. **Group by paradigm**: pixel-based → VQ → continuous-valued +2. **Show progression**: Earlier methods → later methods → yours +3. **Multiple metrics**: FID, IS, Precision, Recall (comprehensive) +4. **Multiple configurations**: w/o CFG and w/ CFG (fair comparison) +5. **Model sizes**: Show efficiency (your 479M vs their 675M) +6. **Dagger (†)**: Clarify edge cases (LDM uses quantized despite continuous) +7. **Bold your methods**: Visual separation (here shown as last group) + +--- + +## 8. Admitting Limitations: Honest and Specific + +### Pattern: Acknowledge Weaknesses Proactively + +**MAR Appendix A**: "Limitations and Broader Impacts" + +**Structure**: +```markdown +Limitations: +1. [Specific artifact] Show example (Figure 8) +2. [Dependency] Acknowledge reliance on external components +3. [Scope] Be honest about what you haven't tested + +Broader Impacts: +1. [Positive] How this advances the field +2. [Positive] Practical applications +3. [Negative] Potential misuse considerations +``` + +### MAR Limitations Example (lines 629-642): + +#### Limitation 1: Visual Artifacts +```latex +First of all, our image generation system can produce images with +noticeable artifacts (Figure 8). + +This limitation is commonly observed in existing methods, especially when +trained on controlled, academic data (e.g., ImageNet). + +Research-driven models trained on ImageNet still have a noticeable gap +in visual quality in comparison with commercial models trained on +massive data. +``` + +**Techniques**: +- Show example (Figure 8) - transparency +- "commonly observed" - you're not uniquely bad +- Contextualize: academic vs. commercial data + +#### Limitation 2: External Dependency +```latex +Second, our image generation system relies on existing pre-trained +tokenizers. + +The quality of our system can be limited by the quality of these tokenizers. + +Pre-training better tokenizers is beyond the scope of this paper. +``` + +**Techniques**: +- "relies on" - direct acknowledgment +- "can be limited by" - honest constraint +- "beyond the scope" - boundary setting + +#### Limitation 3: Unexplored Territory +```latex +Last, we note that given the limited computational resources, we have +primarily tested our method on the ImageNet benchmark. + +Further validation is needed to assess the scalability and robustness +of our approach in more diverse and real-world scenarios. +``` + +**Techniques**: +- "given limited computational resources" - context, not excuse +- "primarily tested" - honesty about scope +- "Further validation is needed" - explicit call for future work + +--- + +## 9. Visionary Conclusion: The "We Hope" Pattern + +### Pattern: End with Forward-Looking Impact Statement + +**MAR Conclusion** (lines 482-488): + +```latex +The effectiveness of Diffusion Loss on various autoregressive models +suggests new opportunities: modeling the interdependence of tokens by +autoregression, jointly with the per-token distribution by diffusion. + +This is unlike the common usage of diffusion that models the joint +distribution of all tokens. + +Our strong results on image generation suggest that autoregressive models +or their extensions are powerful tools beyond language modeling. + +These models do not need to be constrained by vector-quantized +representations. + +We hope our work will motivate the research community to explore sequence +models with continuous-valued representations in other domains. +``` + +### Structure: +```markdown +1. [Synthesis] What your results suggest (new opportunities) +2. [Contrast] How this differs from common usage +3. [Generalization] Broader lesson (powerful tools beyond X) +4. [Freedom] Removing constraints (not limited by Y) +5. [Call to action] "We hope" - inspire future work +``` + +### Key Phrases: +- "suggests new opportunities" +- "unlike the common usage" +- "powerful tools beyond [original domain]" +- "do not need to be constrained by" +- "We hope our work will motivate..." + +--- + +## 10. Writing Style: Kaiming He's Signature Techniques + +### Tone Characteristics: + +1. **Respectful but Firm Challenge** + - "Conventional wisdom holds that..." (respect) + - "...is not a necessity" (firm) + - Never dismissive of prior work + +2. **Empirically Grounded** + - "We observe that..." (not "We believe that...") + - "This analysis suggests..." (evidence-based) + - Show, don't just tell + +3. **Logical Precision** + - Distinguish mechanism from implementation + - "If X, then Y" formulations + - Mathematical clarity in conceptual arguments + +4. **Measured Claims** + - "can be" not "is always" + - "suggests" not "proves" + - "enables" not "guarantees" + +5. **Generous Citation** + - Cite the methods you're challenging + - Credit relevant prior work + - "following [X]" for techniques you adopt + +### Sentence Patterns: + +**Challenge Patterns:** +- "Conventional wisdom holds that [X]. We observe that [Y]." +- "This prevailing approach has led to a widespread belief that [X]." +- "[X] is not a necessity for [Y]." +- "What is needed is [X], not [Y]." + +**Insight Patterns:** +- "The concept of [X] is orthogonal to [Y]." +- "This is unlike the common usage of [X]." +- "These models do not need to be constrained by [X]." +- "This reveals a largely uncharted realm of [X]." + +**Demonstration Patterns:** +- "Interestingly, [X] also enables us to..." +- "Despite [challenge], we are able to..." +- "For comprehensiveness, we also..." +- "Notably, [impressive result]." + +**Vision Patterns:** +- "We hope this work will motivate..." +- "This suggests new opportunities for..." +- "We believe this will be beneficial to..." +- "Further validation is needed to assess..." + +--- + +## 11. Figures: Making the Invisible Visible + +### Pattern: Use Visualization to Show Conceptual Equivalence + +**MAR Figure 2**: "Bidirectional attention can do autoregression" + +**Purpose**: Challenge the assumption that autoregression requires causal attention + +**Technique**: Side-by-side comparison +- (a) Causal attention (conventional) +- (b) Bidirectional attention (surprising but equivalent) + +**Annotation Key Points**: +- "next token prediction" (highlight both do this) +- "loss on [all/unknown] tokens" (show the difference) +- Arrows showing attention flow + +**MAR Figure 3**: "Generalized Autoregressive Models" + +**Purpose**: Show AR, random-order AR, and MAR are special cases + +**Technique**: Progressive generalization +- (a) AR, raster order (standard) +- (b) AR, random order (small variation) +- (c) Masked AR (generalization) + +**Visual Language**: +- "unknown" vs "known/predicted" tokens +- Color coding for what's predicted at each step +- Consistent notation across panels + +**Key**: Figures should make conceptual contributions visually obvious + +--- + +## 12. Related Work: Positioning Within Traditions + +### Pattern: Acknowledge Lineage, Show Departure + +**MAR Section 2**: "Related Work" (lines 80-103) + +**Structure**: +```markdown +1. [Main tradition] Sequence Models for Image Generation + - Pioneering work [citations] + - Your position: "Related to our work, [X] also focuses on..." + - Contrast: "In [X], [limitation]. In contrast, our method..." + +2. [Adjacent tradition] Diffusion for Representation Learning + - Prior work [citations] + - Clarify difference: "These efforts have been focused on [X], + rather than [Y]" + - "In their scenarios, [goal] is not a goal" + +3. [Conceptual connection] Diffusion for Policy Learning + - "Our work is conceptually related to [X]" + - Analogy: "In image generation, we can think of [X] as [Y]" + - Difference: "Despite this conceptual connection, [key difference]" +``` + +### Key Techniques: + +1. **"Related to our work..."** - Acknowledge contemporaries generously +2. **"In contrast..."** - Sharp differentiation +3. **"These efforts have been focused on..."** - Respectful boundary setting +4. **"In their scenarios..."** - Contextualize differences +5. **"Conceptually related to..."** - Find connections across domains +6. **"We can think of X as Y"** - Analogies for insight +7. **"Despite this conceptual connection..."** - Honest differences + +--- + +## 13. Experiments: Ablation as Storytelling + +### Pattern: Experiments Should Validate the "Rethinking" + +**MAR Section 5**: Experiments organized to prove the rethinking + +**Flow**: +```markdown +1. Properties of Diffusion Loss (prove the alternative works) + - vs Cross-entropy (Table 1) + - Flexibility (Table 2) + - Ablations (Table 3, Figures 4-5) + +2. Properties of Generalized AR (prove the unification) + - From AR to MAR (Table 1) + - Speed/accuracy trade-off (Figure 6) + +3. Benchmarking (prove the results are strong) + - System-level comparison (Table 4) + - Qualitative results (Figure 7) +``` + +**Key**: Every experiment should map to a conceptual claim from the introduction + +### Table Design Patterns: + +**Comparison Tables** (Table 1): +- Group by variants (AR → MAR) +- Show progression (Cross-ent → Diff Loss) +- Multiple configurations (w/ and w/o CFG) +- Clear metrics (FID↓, IS↑) + +**Flexibility Tables** (Table 2): +- "Flexibility of X" in caption +- Diverse configurations +- Architecture variations +- Stride mismatches +- rFID column (reconstruction quality) + +**Ablation Tables** (Table 3): +- One dimension varied (MLP width) +- Show params and inference time +- Demonstrate efficiency +- Default row marked (implicit) + +--- + +## 14. Summary: The "Rethinking" Paper Template + +### When to Use This Pattern: + +**Your paper is a "Rethinking" paper if:** +- You challenge a widely-held assumption in your field +- You show two seemingly different methods are equivalent +- You propose removing a "necessary" component +- You unify multiple approaches under one framework + +**Not a "Rethinking" paper if:** +- You propose an incremental improvement +- You combine existing techniques without conceptual insight +- You're optimizing within an established paradigm + +### Abstract Template: +``` +Conventional wisdom holds that [assumption]. We observe that [nuance]. +Is it necessary for [assumption]? In this work, we propose [alternative]. +Rather than [traditional method], we [novel method]. This approach [benefits]. +We hope this work will [vision]. +``` + +### Introduction Template: +``` +[Context] Domain X uses method Y widely. +[Belief] This has led to belief that Z. +[Question] Is Z necessary? +[Analysis] What's actually needed is W. +[Proposal] We propose alternative that achieves W. +[Results] Strong performance + [specific benefit]. +[Vision] This opens new direction. +``` + +### Section Template ("Rethinking X"): +``` +1. Define the conventional approach mathematically +2. Identify essential properties (2-3 items) +3. Show conventional is just one way to achieve these +4. State what's actually needed (abstract) +5. Position your method as satisfying these needs +``` + +### Unification Template: +``` +[Observation] Methods A and B seem different. +[Insight] But they share core principle X. +[Demonstration] Show A = X + implementation Y +[Demonstration] Show B = X + implementation Z +[Generalization] Both are special cases of framework F +[Benefit] This understanding enables [new possibilities] +``` + +### Conclusion Template: +``` +Our results suggest [new opportunity]. +Unlike common usage that [old approach], we show [new insight]. +This reveals [uncharted realm]. +We hope this will motivate [future direction]. +``` + +--- + +## 15. Common Pitfalls to Avoid + +### ❌ Don't: +- Dismiss prior work as "wrong" - it led to the belief for good reasons +- Overstate your case - "completely eliminates" vs "reduces the need for" +- Ignore implementation realities - VQ was solving real problems +- Be vague about alternatives - show concrete alternatives +- Forget to cite the methods you're challenging + +### ✅ Do: +- Acknowledge why the conventional wisdom emerged +- Show limitations respectfully +- Provide rigorous comparisons +- Admit when your method doesn't help +- Credit relevant work extensively +- Use precise language ("can be" not "is always") + +--- + +## 16. Citation Integration Examples + +### How MAR Cites Challenges: + +**Citing the method you're improving:** +```latex +Discrete tokenizers are difficult to train [51, 41, 40, 27]. +``` +- Multiple citations show it's a known problem +- Recent citations ([27]) show it's still active + +**Citing contemporaries:** +```latex +Related to our work, the recent work on GIVT [48] also focuses on +continuous-valued tokens in sequence models. + +GIVT and our work both reveal the significance and potential of this +direction. + +In GIVT, [limitation]. In contrast, our method [advantage]. +``` +- "Related to our work" - generous positioning +- "both reveal" - shared progress +- "In contrast" - clear differentiation + +**Citing the technique you adapt:** +```latex +We can adopt the bidirectional attention implementation as done in +Masked Autoencoder (MAE) [21]. + +See Figure 2(b). +``` +- "as done in" - giving credit +- Reference to figure for transparency + +--- + +## 17. Revision Checklist for "Rethinking" Papers + +**Before Submission, Verify:** + +- [ ] Abstract clearly states the challenged assumption +- [ ] Introduction asks an explicit question ("Is it necessary...") +- [ ] "Rethinking" section dissects the status quo rigorously +- [ ] Unification section shows mathematical/conceptual equivalence +- [ ] Experiments directly test the rethinking claims +- [ ] Flexibility/robustness experiments included +- [ ] Limitations acknowledge remaining challenges +- [ ] Related work cites challenged methods generously +- [ ] Conclusion frames work as opening new territory +- [ ] Figures make conceptual contributions visible +- [ ] Tone is respectful but firm +- [ ] Claims are measured ("can be", "suggests", not "proves") +- [ ] Vision statement inspires without overpromising + +--- + +## 18. Example: Applying This Pattern + +### Original Idea (Not "Rethinking"): +"We propose a new tokenizer that improves image quality by 10%." + +### Rethinking Version: +"Conventional wisdom holds that autoregressive models require +vector-quantized tokenizers. We observe that VQ introduces artifacts and +training difficulties. Is quantization necessary for autoregressive +image generation? We propose Diffusion Loss that enables continuous-valued +tokens, eliminating VQ while achieving SOTA results. We hope this will +motivate continuous-valued modeling in other domains." + +**The Rethinking Frame:** +- Assumption: AR ↔ VQ (challenged) +- Insight: What's needed is distribution modeling, not discreteness +- Alternative: Diffusion Loss for continuous tokens +- Benefit: Eliminates VQ artifacts + enables better tokenizers +- Vision: Continuous-valued AR beyond images + +--- + +## Paper Metadata + +**Title**: Autoregressive Image Generation without Vector Quantization + +**Authors**: Tianhong Li, Yonglong Tian, He Li, Mingyang Deng, Kaiming He + +**Venue**: NeurIPS 2024 (Spotlight) + +**arXiv**: 2406.11838 + +**Code**: https://github.com/LTH14/mar + +**Key Citations**: +- VQ-VAE [51]: Original VQ paper +- MaskGIT [4], MAGE [29]: Masked generative models +- MAE [21]: Bidirectional attention implementation +- DiT [37]: Speed/accuracy comparison +- LDM [42]: Tokenizer source + +--- + +## Extracted by + +**Date**: 2025-01-26 + +**Source**: Full PDF analysis of arXiv:2406.11838v3 + +**Extraction Focus**: Writing patterns for challenging conventional wisdom, +unifying methods, and structuring "rethinking" papers + +**For Integration**: ml-paper-writing skill knowledge base diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/review-response.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/review-response.md new file mode 100644 index 0000000..e6e5748 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/review-response.md @@ -0,0 +1,429 @@ +# Review Response and Rebuttal Strategies + +This file contains effective strategies for responding to reviewer comments and addressing reviewer concerns, extracted from successful ML conference paper rebuttals. + +--- + +## General Rebuttal Principles + +### Core Philosophy +**Source:** Analysis of successful NeurIPS/ICML rebuttals + +**Key Principles:** +1. **Respectful tone**: Thank reviewers for their time +2. **Direct addressing**: Respond point-by-point to each concern +3. **Evidence-based**: Support claims with data, experiments, or citations +4. **Concise communication**: Be clear but brief +5. **No over-committing**: Only promise what can be done + +### Response Structure + +**Template:** +```markdown +# Response to Reviewer [Number] + +Thank you for this insightful comment. We [address the concern]. + +[Specific response to concern]. + +[Additional evidence/experiments if needed]. + +We have revised the manuscript to clarify this point (see changes marked in blue). +``` + +--- + +## Addressing Specific Concerns + +### Concern: Clarity Issues + +**Strategy:** +- Acknowledge the confusion +- Clarify with revised text +- Add examples if helpful + +**Template:** +```markdown +# Response to Clarity Concern + +We apologize for the confusion. The original text was: + +[Original unclear text] + +We have revised this to: +"Revised text with clearer explanation" + +We also added an example (Figure X) to illustrate this concept. +``` + +**Real Example:** +- **Concern:** "The algorithm description is unclear." +- **Response:** "We've rewritten Algorithm 1 with more detailed steps and added pseudocode. We also included a concrete example in Appendix B to illustrate the algorithm's execution." + +### Concern: Missing Experiments + +**Strategy:** +- Assess whether experiment is feasible +- If yes: add experiment and report results +- If not: explain why experiment is not essential +- Offer alternative evidence if possible + +**Template:** +```markdown +# Response to Missing Experiment Request + +We agree that [experiment] would strengthen the evaluation. We have: +[Option 1: Added experiment and results] +OR +[Option 2: Explained why not essential with alternative evidence] + +We believe this addresses the concern while maintaining focus on our core contribution. +``` + +**Real Example:** +- **Concern:** "Add comparison with Method X on dataset Y." +- **Response:** "We've added results on dataset Y (Table 3). Our method outperforms Method X by 5%. We also include ablation showing our improvement comes from [feature], not just better optimization." + +### Concern: Statistical Significance + +**Strategy:** +- Add statistical tests if appropriate +- Report confidence intervals +- Discuss practical significance vs statistical significance +- Note sample size limitations + +**Template:** +```markdown +# Response to Statistical Significance + +We agree statistical testing is important. We have: +- Added paired t-test results showing significance (p<0.01) +- Included 95% confidence intervals in Figure 3 +- Reported standard deviations across 5 runs +- Noted that while some differences are not statistically significant due to sample size, they are practically meaningful for [application] + +We have updated Section 4.2 with these statistical details. +``` + +### Concern: Insufficient Baselines + +**Strategy:** +- Add missing baselines if available +- Explain why certain baselines are inappropriate +- Cite reasons for exclusions with references + +**Template:** +```markdown +# Response to Baseline Concern + +We have added comparisons with: +- [Method A]: Added in Table 2 +- [Method B]: Excluded because [reason with citation] + +For Method B, while it seems related, it [specific reason why not comparable], making direct comparison inappropriate. +``` + +### Concern: Writing Quality + +**Strategy:** +- Revise problematic text +- Fix grammatical issues +- Improve flow and clarity +- Add signposting + +**Template:** +```markdown +# Response to Writing Concern + +We've revised the writing to address your concerns: +- Restructured Section 3 for better flow +- Fixed typos and grammar +- Added transition sentences between paragraphs +- Clarified technical terminology + +The revised manuscript has been proofread and edited for clarity. +``` + +### Concern: Overclaiming + +**Strategy:** +- Tone down absolute statements +- Add qualifications where appropriate +- Acknowledge limitations more explicitly +- Reframe claims to match evidence + +**Template:** +```markdown +# Response to Overclaiming Concern + +We accept that our original claim was too strong. We have revised the text: + +Original: "Our method achieves state-of-the-art on all tasks." +Revised: "Our method achieves state-of-the-art on [specific tasks] and competitive performance on [other tasks]." + +We also added a Limitations section acknowledging that our method may not generalize to [condition]. +``` + +--- + +## Tone and Phrasing Patterns + +### Opening Statements + +**Thanking:** +- "Thank you for this insightful comment." +- "We appreciate the reviewer's suggestion to..." +- "We thank the reviewer for pointing this out." + +**Acknowledging Valid Points:** +- "The reviewer is right that..." +- "We agree this is a limitation." +- "This is an excellent suggestion." + +### Addressing Disagreements + +**Respectful Disagreement:** +- "We respectfully disagree with this assessment based on..." +- "While we understand the concern, our results suggest..." +- "We believe our approach is justified because..." + +**Providing Evidence:** +- "Our experimental results (Table 3) show..." +- "As shown in Figure 4, the difference is..." +- "This is supported by prior work [Citation]." + +### Making Commitments + +**Full Commitments:** +- "We will add this experiment in the revised version." +- "We have added additional ablation studies in Section 5." + +**Partial Commitments:** +- "We have added clarification in the appendix due to space constraints." +- "We've expanded discussion of this point in the revision." + +**Declining Requests:** +- "Unfortunately, due to [constraint], we cannot add this experiment." +- "This would require substantial additional resources beyond our current scope." +- "We believe this is beyond the scope of the current paper but note it as future work." + +--- + +## Common Rebuttal Strategies + +### Strategy: Organized Response + +**Structure:** +```markdown +# Summary of Changes + +We thank the reviewers for their constructive feedback. In this response, we: +- [Major change 1] +- [Major change 2] +- [Improvement 3] + +We believe these changes have significantly strengthened the paper. + +# Response to Reviewer 1 + +[Point-by-point responses] + +# Response to Reviewer 2 + +[Point-by-point responses] +``` + +### Strategy: Evidence-Based Arguments + +**Template:** +```markdown +# Response to Technical Concern + +Our approach is valid because: +1. [Reason 1 with reference/evidence] +2. [Reason 2 with data/figure] +3. [Reason 3 with theoretical justification] + +This is supported by [Citation], which demonstrates that [fact]. +``` + +### Strategy: Highlighting Improvements + +**Template:** +```markdown +# Major Revisions + +1. **New Experiments**: Added comparison with [method] on [dataset] +2. **New Analysis**: Included ablation study in Table 4 +3. **Clarified Writing**: Rewrote Section 3 for clarity +4. **Added Limitations**: New section 5.2 acknowledging constraints + +These additions strengthen our core claims about [contribution]. +``` + +--- + +## Venue-Specific Considerations + +### NeurIPS + +**Emphasis:** +- Novelty and conceptual contribution +- Broader impact (lay summary) +- Reproducibility checklist + +**Rebuttal Focus:** +- How work advances understanding +- Significance of contribution +- Ethical considerations + +### ICML + +**Emphasis:** +- Methodological rigor +- Theoretical contributions +- Broader impact statement + +**Rebuttal Focus:** +- Soundness of methods +- Theoretical guarantees +- Practical implications + +### ICLR + +**Emphasis:** +- Experimental thoroughness +- Limitations acknowledgment +- LLM usage disclosure + +**Rebuttal Focus:** +- Comprehensive evaluation +- Honest limitation discussion +- Transparency about methods + +### ACL + +**Emphasis:** +- Linguistic appropriateness +- Ethical considerations +- Clear limitations + +**Rebuttal Focus:** +- Language quality and appropriateness +- Data provenance and ethics +- Practical utility + +--- + +## Tips for Successful Rebuttals + +### Before Writing + +1. **Understand the concerns**: Read carefully, identify key issues +2. **Prioritize**: Address major concerns first +3. **Be realistic**: Only promise what can deliver +4. **Gather evidence**: Collect data, results, citations +5. **Coordinate**: Discuss with co-authors if applicable + +### While Writing + +1. **Be specific**: Reference exact sections, figures, tables +2. **Be concise**: Keep responses focused and brief +3. **Be respectful**: Thank reviewers, acknowledge good points +4. **Be confident**: Defend your work appropriately +5. **Be honest**: Acknowledge limitations, don't overpromise + +### Common Mistakes to Avoid + +- **Defensive tone**: Don't argue excessively +- **Vague responses**: Be specific about changes +- **Ignoring concerns**: Address every point +- **Over-promising**: Only commit to feasible additions +- **Disorganized:** +- **Poor formatting:** Use clear sections and structure +- **Rude language:** Maintain professional tone + +--- + +## Rebuttal Examples + +### Example 1: Clarity Concern + +**Reviewer:** "The method description in Section 3 is unclear and hard to follow." + +**Response:** +```markdown +We apologize for the confusion. We have rewritten Section 3.2 to clarify our algorithm: + +**Original:** "We process the data using our method and get results." + +**Revised:** "Our method consists of three stages: (1) We first normalize the input +features using [technique]. (2) We then apply our core algorithm, which iteratively [process]. +(3) Finally, we post-process the outputs using [method]." + +We also added Algorithm 1 with detailed steps and included a concrete example in +Appendix A. We believe this revision makes the method reproducible and clear. +``` + +### Example 2: Missing Baseline + +**Reviewer:** "You should compare with Method X (Smith et al., 2022)." + +**Response:** +```markdown +Thank you for this suggestion. We have added comparisons with Method X in our +revised manuscript: + +**Results in Table 3:** Our method achieves 92% accuracy compared to Method X's +85% on dataset Y. This 7% improvement demonstrates the value of our [key innovation]. + +**Ablation Study:** We show in Table 4 that our improvement comes specifically from +[feature], not just better optimization. + +We chose not to include Method Z because [reason with citation]. +``` + +### Example 3: Overclaiming + +**Reviewer:** "The abstract claims 'state-of-the-art' too broadly." + +**Response:** +```markdown +We accept this critique. Our original claim was too broad. We have revised the +abstract: + +**Original:** "Our method achieves state-of-the-art performance across all tasks." + +**Revised:** "Our method achieves state-of-the-art on [specific tasks A and B] (Table 1) +and competitive performance on [other tasks C and D] (Table 2)." + +We also added a Limitations section (Section 5) noting that performance may vary +across domains and tasks. +``` + +--- + +## Final Checklist + +Before submitting rebuttal: + +- [ ] All reviewer concerns addressed +- [ ] Responses are clear and specific +- [ ] Tone is respectful and professional +- [ ] Changes are marked in manuscript +- [ ] Evidence provided for claims +- [ ] Feasible commitments made +- [ ] Co-authors agree with responses +- [ ] Proofread for errors +- [ ] Check formatting requirements + +--- + +## Notes + +- **Learn from successful rebuttals**: Read well-received papers' reviewer exchanges +- **Practice humility**: Acknowledge mistakes, show willingness to improve +- **Focus on core contribution**: Defend your main contribution without overclaiming +- **Keep it concise**: Reviewers are busy; be respectful of their time + +**Updates:** This file is periodically updated with new strategies and examples from successful rebuttals. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/structure.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/structure.md new file mode 100644 index 0000000..9c77d88 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/structure.md @@ -0,0 +1,349 @@ +# Paper Structure Patterns + +This file contains actionable patterns for organizing ML conference papers, extracted from successful publications. + +--- + +## Introduction Patterns + +### Pattern: Contribution Statement Structure +**Source:** "Attention Is All You Need", NeurIPS (2017) +**Context:** Introducing the main contribution + +**Pattern:** +1. Start with broader context or problem +2. Narrow down to specific limitation +3. Present your approach as solution +4. State clear contribution upfront + +**Example Template:** +```markdown +[Context/Problem]: Existing approaches struggle with [limitation] due to [reason]. + +[Our Approach]: We propose [method name], which [key innovation]. + +[Contribution]: This achieves [result] and enables [capability]. +``` + +**Application:** Use this pattern when introducing your main contribution in the first or second paragraph of the introduction. + +--- + +### Pattern: Bulleted Contribution List +**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019) +**Context:** Summarizing contributions for clarity + +**Pattern:** +- Place near end of Introduction (after Related Work) +- Use 2-4 bullets +- Each bullet: 1-2 lines max (in two-column format) +- Start with strong verbs ("We propose", "We demonstrate", "We show") + +**Example Template:** +```markdown +Our contributions are three-fold: +- We propose [method], which achieves [result]. +- We demonstrate that [technique] improves [metric]. +- We show that [approach] enables [new capability]. +``` + +**Application:** Use this when you need to clearly delineate multiple contributions for reviewers. + +--- + +### Pattern: Related Work Organization +**Source:** "Attention Is All You Need", NeurIPS (2017) +**Context:** Structuring literature review + +**Pattern:** +- Organize methodologically, not chronologically +- Group papers by approach/assumption +- Contrast your approach with each group +- Use "One line of work uses X whereas we use Y because..." + +**Example Template:** +```markdown +[Approach Category]: Several approaches use [assumption A] [refs]. +[Contrast]: We adopt [assumption B] because it allows [benefit]. + +[Alternative Category]: Other methods focus on [aspect C] [refs]. +[Positioning]: We build on this by adding [our innovation]. +``` + +**Application:** Use this to position your work relative to existing literature without paper-by-paper reviews. + +--- + +## Methods Section Patterns + +### Pattern: Algorithm Presentation +**Source:** "Adam: A Method for Stochastic Optimization", ICLR (2015) +**Context:** Describing algorithms clearly + +**Pattern:** +1. High-level overview first +2. Mathematical formulation +3. Algorithm pseudocode (if complex) +4. Implementation details + +**Example Template:** +```markdown +[Overview]: We formulate [problem] as optimization. Let [objective] be our goal. + +[Method]: Our approach optimizes [objective] using [technique]. +Specifically, we [algorithm description]. + +[Algorithm]: The full procedure is shown in Algorithm 1. + +[Implementation]: In practice, we [practical details]. +``` + +**Application:** Use this when presenting novel algorithms or optimization methods. + +--- + +### Pattern: Component Breakdown +**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019) +**Context:** Describing multi-component systems + +**Pattern:** +- Present model architecture first +- Break down into key components +- Explain each component's role +- Show how components interact + +**Example Template:** +```markdown +[Architecture]: Our model consists of [N components]: [list]. + +[Component 1]: The [component] module [function]. +[Component 2]: The [component] layer [operation]. + +[Integration]: These components are stacked sequentially, with [connection pattern]. +``` + +**Application:** Use this when describing complex architectures with multiple interacting parts. + +--- + +## Results Section Patterns + +### Pattern: Quantitative Opening +**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019) +**Context:** Presenting main findings + +**Pattern:** +- Start with strongest quantitative result +- Use exact numbers and metrics +- Include comparison to baselines +- State statistical significance + +**Example Template:** +```markdown +[Main Result]: Our method achieves [score] on [dataset], improving +over the previous best of [baseline] by [margin] (p<0.001). + +[Comparison]: Compared to baselines: +- [Method A]: [score] +- [Method B]: [score] +- Ours: [score] + +[Significance]: Results are averaged over N runs; standard deviations shown in parentheses. +``` + +**Application:** Use this to open your Results section with your strongest finding. + +--- + +### Pattern: Table Integration +**Source:** "Attention Is All All You Need", NeurIPS (2017) +**Context:** Presenting results in tables + +**Pattern:** +- Bold best results in each column +- Include direction indicators (↑↓) +- Provide table caption that stands alone +- Reference table in text before presenting + +**Example Template:** +```markdown +Table 1 shows our method's performance. Our model (bold) outperforms +all baselines across datasets. + +[Table content] + +As shown in Table 1, we achieve state-of-the-art on [datasets]. +``` + +**Application:** Use this when presenting comparative results in table format. + +--- + +## Discussion Section Patterns + +### Pattern: Limitations First +**Source:** "Attention Is All You Need", NeurIPS (2017) +**Context:** Acknowledging limitations proactively + +**Pattern:** +- State limitations clearly in first paragraph +- Explain why limitations don't undermine core claims +- Distinguish between limitations and future work + +**Example Template:** +```markdown +[Limitation Statement]: Our approach has [limitation]. Specifically, +[constraint]. + +[Mitigation]: Despite this, our core findings about [main contribution] remain +valid because [reason]. + +[Future Work]: Addressing this limitation is an important direction for +future research. +``` + +**Application:** Use this to acknowledge limitations honestly while maintaining paper strength. + +--- + +### Pattern: Broader Impact Framing +**Source:** "Language Models are Few-Shot Learners", GPT-3 Paper (2020) +**Context:** Discussing wider implications + +**Pattern:** +- Start with direct implications +- Expand to related domains +- Consider societal impact (if appropriate) +- End with forward-looking statement + +**Example Template:** +```markdown +[Direct Impact]: Our findings suggest that [implication for domain]. + +[Broader Implications]: Beyond [specific domain], this approach could +enable [application in other areas]. + +[Future Outlook]: As [trend] continues, methods like ours will become +increasingly important for [reason]. +``` + +**Application:** Use this when writing the final paragraphs of Discussion or Conclusion. + +--- + +## Transition Patterns + +### Pattern: Section Transitions +**Source:** "Attention Is All You Need", NeurIPS (2017) +**Context:** Moving between sections + +**Pattern:** +- Introduction → Methods: "We now describe our approach." +- Methods → Results: "We evaluate our method on [tasks]." +- Results → Discussion: "These results suggest that [insight]." + +**Example Template:** +```markdown +[Transition to Methods]: Having established [motivation], we present +our method. + +[Transition to Results]: To validate our approach, we conduct experiments +on [datasets]. + +[Transition to Discussion]: The experimental results reveal several insights +about [phenomenon], which we discuss next. +``` + +**Application:** Use these to create smooth transitions between major sections. + +--- + +## Notes + +- **Consistency**: Maintain consistent terminology throughout the paper +- **Flow**: Each section should logically lead to the next +- **Clarity**: Make structure explicit with signposting +- **Audience**: Write for tired reviewers - make their job easy + + + +## 何凯明（Kaiming He）的论文结构模式 + +> 来源: 分析了何凯明的 19 篇代表性论文 +> 添加时间: {datetime.now().strftime('%Y-%m-%d')} + +### 摘要结构模式 + +何凯明在摘要中常用的开场模式： + +**模式 1: 直接陈述贡献** +``` +We introduce [method name], a [key feature] framework for [task]. +We show that [method] achieves [result] on [dataset]. +``` + +**模式 2: 问题-解决方案** +``` +[Problem] is difficult for [task]. We present [solution] +that addresses this by [key mechanism]. +``` + +**示例** (来自 ResNet): +``` +Deeper neural networks are more difficult to train. We present a +residual learning framework to ease the training of networks that +are substantially deeper than those used previously. +``` + +### 引言结构模式 + +**三段式引言:** +1. **问题陈述** (2-3段) - 描述挑战和现有方法 +2. **方法概述** (1-2段) - 简洁介绍解决方案 +3. **主要贡献** (1段) - 列表形式，每条 1-2 行 + +**贡献列表模式:** +```markdown +- 我们提出了 [方法]，解决了 [问题] +- 我们展示了 [方法] 在 [数据集] 上的 [性能提升] +- 我们证明了 [原理] 是有效的 +``` + +### 方法部分结构 + +何凯明的方法部分通常包含： + +1. **符号定义** - 清晰定义所有变量和符号 +2. **问题形式化** - 数学公式表达 +3. **方法描述** - 逐步算法解释 +4. **实现细节** - 网络架构、训练设置 + +**常用句式:** +- "Let us consider [变量] as [定义]" +- "Formally, we define [公式]" +- "We hypothesize that [假设]" +- "To the extreme, [极端情况]" + +### 实验部分结构 + +1. **实验设置** - 数据集、评价指标、实现细节 +2. **主要结果** - 核心性能对比 +3. **消融实验** - 组件分析 +4. **可视化分析** - 图表展示 + +**结果描述模式:** +- "Table X shows that [结果]" +- "Fig. Y illustrates that [观察]" +- "Our method achieves [指标] on [任务]" +- "This represents a [X]% improvement over baseline" + +### 相关工作部分组织 + +何凯明倾向于**主题式组织**而非时间顺序： + +**好的组织方式:** +- "One line of work uses [方法A] [引用], whereas we use [方法B]" +- "[方法A] [引用] assumes [假设], but we show [反驳]" + +**避免:** +- "X et al. introduced [方法]. Y et al. improved [方法]" diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/submission-guides.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/submission-guides.md new file mode 100644 index 0000000..993df52 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/submission-guides.md @@ -0,0 +1,326 @@ +# Submission Guides and Venue Requirements + +This file contains venue-specific submission requirements, formatting guidelines, and checklist items extracted from ML conference and journal publications. + +--- + +## NeurIPS Requirements + +### Format Requirements +**Source:** NeurIPS 2025 Conference Guidelines + +**Page Limits:** +- Main paper: 9 pages (excluding references) +- References: Unlimited (don't count toward page limit) +- Appendices: Allowed but reviewers not required to read + +**Required Sections:** +- Abstract: 150-250 words +- Introduction: Must clearly state contribution +- Methods: Sufficient for reproduction +- Experiments: Comprehensive evaluation +- Discussion: Interpret results and limitations +- References: Complete citations +- **Checklist**: Mandatory submission checklist (16 items) +- **Lay Summary**: Required for accepted papers (1 page, non-technical) + +**Formatting:** +- Double-blind review (anonymize submissions) +- LaTeX template required +- 9pt font, two-column format +- Margins: 1 inch on all sides + +**Submission Checklist Items:** +1. Do the main claims of the paper match the checklist? +2. Have you checked the checklist for missing items? +3. Is the paper anonymized? +4. Are all figures/tables clear and readable? +5. Have you included code and data availability statements? +6. Are all equations properly formatted? +7. Is the abstract within word limit? +8. Are all citations complete and correct? +9. Have you addressed potential ethical concerns? +10. Are experimental settings clearly described? +11. Is statistical significance properly reported? +12. Have you included limitations? +13. Is the broader impact discussed (if required)? +14. Are all figures referenced in text? +15. Is the supplementary material well-organized? +16. Have you proofread for typos and grammar? + +--- + +## ICML Requirements + +### Format Requirements +**Source:** ICML 2026 Conference Guidelines + +**Page Limits:** +- Main paper: 8 pages +- Camera-ready: +1 page (9 total) +- References: Unlimited (don't count toward page limit) + +**Required Sections:** +- Abstract: Clear summary of contribution +- Introduction: Problem and contribution +- Methods: Complete description +- Experiments: Thorough evaluation +- **Broader Impact Statement**: Required (after conclusion) +- References: Complete citations + +**Formatting:** +- Double-blind review (anonymize submissions) +- LaTeX template required +- Two-column format +- Margins as per template + +**Broader Impact Statement:** +- Discuss positive and negative societal impacts +- Consider biases, fairness, environmental impact +- 1 page maximum +- Required for all submissions + +--- + +## ICLR Requirements + +### Format Requirements +**Source:** ICLR 2026 Conference Guidelines + +**Page Limits:** +- Main paper: 9 pages +- Camera-ready: +1 page (10 total) +- References: Unlimited (don't count toward page limit) + +**Required Sections:** +- Abstract: Summary of contribution +- Introduction: Clear problem statement +- Methods: Reproducible description +- Experiments: Comprehensive evaluation +- **Limitations Section**: MANDATORY +- **LLM Disclosure**: Required if using LLMs +- References: Complete citations + +**Formatting:** +- Double-blind review (anonymize submissions) +- LaTeX template required +- Two-column format + +**LLM Disclosure Requirements:** +- Describe LLM use in the paper +- Include model details (architecture, training data, compute) +- Acknowledge LLM limitations +- Note any automated text generation + +--- + +## ACL Requirements + +### Format Requirements +**Source:** ACL 2025 Conference Guidelines + +**Page Limits:** +- Main paper: 8 pages (long papers) +- Short papers: 4 pages +- References: Unlimited (don't count toward page limit) + +**Required Sections:** +- Abstract: 150-200 words +- Introduction: Background and contribution +- Methods: Technical description +- Experiments: Evaluation +- **Limitations Section**: MANDATORY +- **Ethics Statement**: Required if applicable +- References: Complete citations + +**Formatting:** +- Double-blind review (anonymize submissions) +- LaTeX template required (ACL style files) +- Two-column format + +**Ethics Considerations:** +- Human subjects research: IRB approval required +- Data privacy: Anonymization and consent +- Environmental impact: Compute resource usage + +--- + +## AAAI Requirements + +### Format Requirements +**Source:** AAAI 2026 Conference Guidelines + +**Page Limits:** +- Main paper: 7 pages +- Camera-ready: +1 page (8 total) +- References: Unlimited (don't count toward page limit) + +**Required Sections:** +- Abstract: 150-250 words +- Introduction: Problem and contribution +- Methods: Technical description +- Experiments: Evaluation +- References: Complete citations + +**Formatting:** +- Double-blind review (anonymize submissions) +- **Strict style file adherence**: Must use official template +- Two-column format +- No modifications to style files + +**Strict Requirements:** +- Follow AAAI template exactly +- No custom formatting beyond template +- Font sizes and margins as specified +- Page limits strictly enforced + +--- + +## COLM Requirements + +### Format Requirements +**Source:** COLM 2025 Conference Guidelines + +**Page Limits:** +- Main paper: 9 pages +- Camera-ready: +1 page (10 total) +- References: Unlimited (don't count toward page limit) + +**Required Sections:** +- Abstract: Summary of contribution +- Introduction: Problem and contribution +- Methods: Technical description +- Experiments: Evaluation +- **Focus**: Language models specifically +- References: Complete citations + +**Formatting:** +- Double-blind review (anonymize submissions) +- LaTeX template required +- Two-column format + +**Language Model Focus:** +- Papers should address language model challenges +- Method contributions applicable to LM community +- Experimental setup relevant to language tasks + +--- + +## Common Submission Requirements + +### Double-Blind Review +**Applies to:** NeurIPS, ICML, ICLR, ACL, AAAI, COLM + +**Requirements:** +- Remove author names and affiliations +- Anonymize citations to own work (use [Anonymous, 2024]) +- Remove acknowledgments that reveal identity +- Avoid distinctive phrases that identify authors +- Supplementary materials must also be anonymized + +**Common Mistakes:** +- Forgetting to anonymize GitHub links +- Including author names in file paths +- Thanking specific colleagues in acknowledgments +- Citing own work with author names + +### Code and Data Availability + +**Increasingly Required:** + +**NeurIPS:** Encourages code/data availability statements +**ICML:** Encourages reproducibility +**ICLR:** Recommends code sharing + +**Best Practices:** +- Include code repository link (anonymized if under review) +- Provide data access instructions +- Describe hyperparameters and settings +- Note any proprietary constraints + +### Supplementary Materials + +**General Guidelines:** +- Appendices allowed but not required reading +- Use for additional experiments, proofs, tables +- Keep main paper self-contained +- Reference supplementary in main text + +**Formatting:** +- Same style as main paper +- Clear section numbering (S1, S2, etc.) +- Include in submission PDF or as separate file + +--- + +## Citation Styles + +### Common Styles in ML + +**IEEE Style (Numbered):** +``` +[1] J. Doe, "Paper title," Conference Name, Year. +[2] A. Smith, "Another paper," Journal Name, vol. 10, pp. 1-15, 2020. +``` + +**ACM Style (Numbered):** +``` +[J. Doe and A. Smith, "Paper title," Conference Name, Year. +[A. Smith and B. Jones, "Another paper," Journal Name, 2020. +``` + +**Author-Year (APA-like):** +``` +Doe (2020) J. Doe. Paper title. Conference Name. +Smith (2019) A. Smith. Another paper. Journal Name. +``` + +### Reference Management + +**Best Practices:** +- Use consistent style throughout +- Include DOIs when available +- Provide arXiv links for preprints +- Check for broken links +- Verify all citations before submission + +--- + +## Checklists and Templates + +### Pre-Submission Checklist + +**Content:** +- [ ] Novel contribution clearly stated +- [ ] Related work comprehensive +- [ ] Methods reproducible +- [ ] Results support all claims +- [ ] Limitations acknowledged +- [ ] Broader impact addressed (if required) +- [ ] Ethics compliance verified + +**Formatting:** +- [ ] Page limits respected +- [ ] Style file followed exactly +- [ ] References complete and consistent +- [ ] Figures/tables clear and readable +- [ ] Equations numbered and referenced +- [ ] Supplementary material organized + +**Anonymity:** +- [ ] Author names removed +- [ ] Acknowledgements anonymized +- [ ] Self-citations anonymized +- [ ] GitHub links anonymized +- [ ] Identifying information removed + +--- + +## Notes + +- **Always verify**: Requirements change between years - always check current conference guidelines +- **Plan ahead**: Some venues have strict formatting - start early +- **Read examples**: Look at well-received papers from previous years +- **Ask for help**: If unsure about a requirement, consult program chairs or experienced colleagues + +**Updates:** This file is regularly updated as new conference requirements become available. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/theory-driven-papers-kaiming-he.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/theory-driven-papers-kaiming-he.md new file mode 100644 index 0000000..8c0a0e3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/theory-driven-papers-kaiming-he.md @@ -0,0 +1,561 @@ +# Theory-Driven Papers: From First Principles + +**Source**: Kaiming He et al., "Mean Flows for One-step Generative Modeling" (2025) + +**Paper Type**: Theory-driven / First-principles paper + +**Core Pattern**: Start from first principles → Derive theory → Build method → Demonstrate superiority + +--- + +## 1. Abstract Structure: The "Principle Introduction" Framework + +### Pattern: From Theory to Results + +**Template**: +```markdown +Abstract: +1. [Background] Established framework provides [foundation] +2. [Problem] Recent research focuses on [challenge], but existing methods have [limitation] +3. [Critique] Despite encouraging results, [specific problem with prior approaches] +4. [Core Concept] We introduce [new concept], in contrast to [old concept] +5. [Theory] Solely from definition, we derive [theoretical foundation] +6. [Advantage] This provides [principled basis] vs [heuristic approaches] +7. [Results] Achieves [strong result] - [relative improvement] over SOTA +8. [Significance] Self-contained, [independence from external components] +``` + +### MeanFlows Abstract Example (annotated): + +```latex +Flow Matching provides an intuitive and conceptually simple framework for +constructing flow paths that transport one distribution to another. + +Recent research has paid significant attention to few-step—and in +particular, one-step, feedforward—generative models. + +Despite encouraging results, the consistency constraint is imposed as a +property of the network's behavior, while the properties of the underlying +ground-truth field that should guide learning remain unknown. + +The core idea is to introduce a new ground-truth field representing the +average velocity, in contrast to the instantaneous velocity typically +modeled in Flow Matching. + +Solely originated from this definition, we derive a well-defined, intrinsic +relation between the average and instantaneous velocities, which naturally +serves as a principled basis for guiding network training. + +Our method achieves an FID of 3.43 using 1-NFE generation, significantly +outperforming previous state-of-the-art methods by a relative margin of 50% +to 70%. + +It is trained entirely from scratch, without any pre-training, distillation, +or curriculum learning. +``` + +### Key Techniques: + +1. **"Provides an intuitive and conceptually simple framework"** - Light touch introduction +2. **"Recent research has paid significant attention to..."** - Establish context +3. **"Despite encouraging results..."** - The critique pattern (acknowledge then problem) +4. **"The core idea is to introduce..."** - Clear concept statement +5. **"in contrast to"** - Conceptual differentiation +6. **"Solely originated from this definition"** - First-principles emphasis +7. **"well-defined, intrinsic relation"** - Theory keywords +8. **"naturally serves as a principled basis"** - Naturalness emphasis +9. **Relative improvement (50-70%)** - More impactful than absolute numbers +10. **Negative list** - What you DON'T need (pre-training, distillation, curriculum) + +--- + +## 2. Introduction: The "Critique-First" Framework + +### Pattern: Build Up → Identify Flaw → Propose Alternative + +**Structure**: +```markdown +1. [Background] Established field with [characteristic] +2. [Problem Shift] Research focus has moved to [new direction] +3. [Specific Problem] Existing approaches address this by [method] +4. [The Critique] Despite [acknowledgment], [fundamental problem] + - "imposed as a property of [X]" + - "[Y] remains unknown" +5. [Consequences] Consequently, [practical problems] +6. [Your Concept] We propose [alternative] with [differentiation] +7. [Theory] From [first principles], we derive [result] +8. [Advantage] This is [principled/natural/intrinsic] vs [heuristic/artificial] +9. [Results] [Quantitative result] with [qualitative advantage] +``` + +### MeanFlows Introduction Flow: + +#### Background (Light Touch) +```latex +Flow Matching provides an intuitive and conceptually simple framework +for constructing flow paths that transport one distribution to another. +``` + +**Technique**: +- "intuitive and conceptually simple" - Modest, not revolutionary +- Focus on what it IS, not how important it is + +#### Problem Shift +```latex +Closely related to diffusion models, Flow Matching focuses on the velocity +fields that guide model training. + +Both Flow Matching and diffusion models perform iterative sampling during +generation. Recent research has paid significant attention to few-step +—and in particular, one-step, feedforward—generative models. +``` + +**Technique**: +- "Closely related to" - Establish connection +- "Recent research has paid significant attention to" - Research trend +- "few-step—and in particular, one-step" - Progressive emphasis + +#### The Critique (Key Pattern) +```latex +Consistency Models [46, 43, 15, 31] achieve few-step generation by enforcing +a consistency constraint on the velocity field. + +Despite encouraging results, the consistency constraint is imposed as a +property of the network's behavior, while the properties of the underlying +ground-truth field that should guide learning remain unknown. + +Consequently, training can be unstable and requires a carefully designed +'discretization curriculum' to progressively constrain the time domain. +``` + +**Technique**: +- **"Despite encouraging results"** - Always acknowledge first +- **"imposed as a property of the network's behavior"** - It's artificial +- **"underlying ground-truth field...remain unknown"** - Missing theory +- **"Consequently"** - Show practical consequences +- **Specific problems**: "training can be unstable", "requires...curriculum" + +#### Your Concept +```latex +The core idea is to introduce a new ground-truth field representing the +average velocity, in contrast to the instantaneous velocity typically +modeled in Flow Matching. +``` + +**Technique**: +- **"The core idea is to introduce"** - Direct statement +- **"in contrast to"** - Conceptual differentiation +- **Old vs New**: "average velocity" vs "instantaneous velocity" + +#### Theory First +```latex +Average velocity is defined as the ratio of displacement to a time interval, +with displacement given by the time integral of the instantaneous velocity. + +Solely originated from this definition, we derive a well-defined, intrinsic +relation between the average and instantaneous velocities, which naturally +serves as a principled basis for guiding network training. +``` + +**Technique**: +- **"Solely originated from this definition"** - Pure derivation +- **"well-defined, intrinsic relation"** - Theory keywords +- **"naturally serves as"** - Not forced +- **"principled basis"** - Foundation + +--- + +## 3. Methods Section: The "Named Identity" Pattern + +### Pattern: Define → Derive → Name + +**Structure**: +```markdown +1. [Concept Name] Define with formal notation +2. [Motivation] Explain why we need this +3. [Derivation] Step-by-step with justifications +4. [Naming] Give it a memorable name +5. [Comparison] Contrast with prior approaches +``` + +### MeanFlows Example: + +#### Step 1: Concept Naming +```latex +Average Velocity. We define average velocity as the displacement between +two time steps t and r (obtained by integration) divided by the time interval. + +Formally, the average velocity u is: + +u(zt, r, t) ≜ 1/(t−r) ∫_r^t v(zτ, τ)dτ. (3) +``` + +**Techniques**: +- **Bold heading**: "Average Velocity." - Makes it memorable +- **Text description first**: Explain before formula +- **"Formally,"**: Signals math coming +- **≜ symbol**: "defined as" (clearer than =) + +#### Step 2: Derivation with Motivation +```latex +To have a formulation amenable to training, we rewrite Eq. (3) as: + +(t−r)u(zt, r, t) = ∫_r^t v(zτ, τ)dτ. (4) + +Now we differentiate both sides with respect to t, treating r as independent +of t. This leads to: + +d/dt(t−r)u = d/dt∫_r^t v(zτ, τ)dτ + +⇒ u + (t−r)d/dt u = v(zt, t), (5) + +where the manipulation of the left hand side employs the product rule and +the right hand side uses the fundamental theorem of calculus. +``` + +**Techniques**: +- **"To have a formulation amenable to training"** - Explain why +- **"Now we differentiate..."** - Guide reader +- **Step-by-step**: Don't skip +- **"where..."**: Explain each manipulation +- **"⇒" symbol**: Clear direction + +#### Step 3: Naming the Identity +```latex +Rearranging terms, we obtain the identity: + +u(zt, r, t) = v(zt, t) − (t−r)d/dt u(zt, r, t) (6) + +We refer to this equation as the "MeanFlow Identity", which describes the +relation between v and u. +``` + +**Techniques**: +- **"Rearranging terms, we obtain..."** - What you did +- **"We refer to this equation as the 'X Identity'"** - Brand it +- **Explain**: "which describes..." - What it does + +--- + +## 4. Comparison: Principled vs Heuristic + +### Pattern: Emphasize Theoretical Independence + +**Structure**: +```markdown +1. [Your Core] At the core of our method is [fundamental principle] +2. [Independence] This [does not depend on / is independent of] [implementation] +3. [Contrast] In contrast, prior works typically rely on [heuristic/artificial constraint] +4. [Qualitative] [Natural/principled/intrinsic] vs [imposed/empirical/heuristic] +``` + +### MeanFlows Example: + +```latex +At the core of our method is the functional relationship between two +underlying fields v and u, which naturally leads to the MeanFlow Identity +that u must satisfy (Eq. (6)). + +This identity does not depend on the introduction of neural networks. + +In contrast, prior works typically rely on extra consistency constraints, +imposed on the behavior of the neural network. +``` + +**Techniques**: +- **"At the core of our method is..."** - What matters +- **"naturally leads to"** - Not forced +- **"does not depend on"** - Independence +- **"In contrast"** - Clear pivot +- **"imposed on"** - Theirs is artificial + +### Specific Method Comparison + +```latex +Consistency Models [46, 43, 15, 31] are focused on paths anchored at the +data side: in our notations, this corresponds to fixing r≡0 for any t. + +As a result, Consistency Models are conditioned on a single time variable, +unlike ours. +``` + +**Techniques**: +- **"focused on X"** - Their scope +- **"in our notations, this corresponds to..."** - Precise mapping +- **"As a result"** - Consequence +- **"unlike ours"** - One-word differentiation + +--- + +## 5. Results: Significant Improvements with Context + +### Pattern: Relative Improvement + Independence + +**Structure**: +```markdown +1. [Absolute] We achieve [metric] on [task] +2. [Relative] This represents [X-Y%] relative improvement over [comparison] +3. [Context] Our method is [self-contained / independent] +4. [Negative List] without [list of things you don't need] +``` + +### MeanFlows Example: + +```latex +Our method achieves an FID of 3.43 using 1-NFE generation. + +This result significantly outperforms previous state-of-the-art methods in +its class by a relative margin of 50% to 70% (Fig. 1). + +In addition, our method stands as a self-contained generative model: it is +trained entirely from scratch, without any pre-training, distillation, or +curriculum learning. +``` + +**Techniques**: +- **Absolute first**: "FID of 3.43" +- **"significantly outperforms"** - Strong but not "dramatically" +- **"by a relative margin of 50% to 70%"** - Range, not single number +- **Reference to figure**: "(Fig. 1)" +- **"In addition"** - Second dimension of value +- **"self-contained"** - Independence keyword +- **"trained entirely from scratch"** - Complete independence +- **Negative list**: "without any pre-training, distillation, or curriculum learning" + +--- + +## 6. Table Design: System-Level Comparison + +### Pattern: Multiple Paradigms, Clear Highlighting + +**Structure**: +```markdown +Table X: +┌────────────────────────────────────┐ +│ Left side: Your direct competitors │ +│ (1-NFE and 2-NFE methods) │ +├────────────────────────────────────┤ +│ Right side: Other paradigms │ +│ (GANs, autoregressive, etc.) │ +├────────────────────────────────────┤ +│ **Your method** (bold, positioned) │ +└────────────────────────────────────┘ +``` + +### MeanFlows Table 2 Organization: + +```latex +Table 2: Comparison on ImageNet 256×256. + +Left: 1-NFE and 2-NFE diffusion/flow models +Right: Other generative models + +Highlighted: MeanFlow (our method) +``` + +**Key Techniques**: +1. **Split paradigm**: Direct competitors on left, others on right +2. **Fair metrics**: params, NFE, FID (same for all) +3. **Bold your method**: Visual emphasis +4. **Position strategically**: Where you look best +5. **Comprehensive**: Include all major paradigms + +--- + +## 7. Figure Design: Visual Storytelling + +### Pattern: Multi-Panel Narrative + +**MeanFlows Figure 1**: "One-step generation on ImageNet 256×256 from scratch" + +**Structure**: +- **Main panel**: Generated images (visual evidence) +- **Caption**: Detailed comparison table +- **Annotations**: FID scores of competing methods +- **Highlight**: "Our MeanFlow (MF) model achieves significantly better..." + +**Techniques**: +1. **Title tells the story**: "from scratch" - key differentiator +2. **Images + numbers**: Both visual and quantitative +3. **Competitor scores in caption**: Reader doesn't need to flip pages +4. **"significantly better"**: In the figure caption itself + +--- + +## 8. Ablation Study: Destructive Testing + +### Pattern: Prove Necessity by Breaking Things + +**Structure**: +```markdown +Table X: +┌──────────────────────────────────┐ +│ (a) Vary one design dimension │ +│ - Show effect of parameter │ +│ - Mark default in gray │ +├──────────────────────────────────┤ +│ (b) Destructive comparison │ +│ - Intentionally use WRONG values │ +│ - Show only correct works │ +└──────────────────────────────────┘ +``` + +### MeanFlows Table 1 Example: + +#### Part (a): Design Sweep +```latex +(a) Ratio of sampling r≠t +% of r≠t FID, 1-NFE +0% (= FM) 328.91 +25% 61.06 +50% 63.14 +100% 67.32 +``` + +**Techniques**: +- **Descriptive caption**: "Ratio of sampling r≠t" +- **Show failure mode**: "0% (= FM) 328.91" - pure FM fails +- **Range**: 0% to 100% of parameter +- **Default marked**: In original (not shown here) + +#### Part (b): Destructive Testing +```latex +(b) JVP computation +jvp tangent FID, 1-NFE +(v, 0, 1) 61.06 +(v, 0, 0) [wrong] 268.06 +(v, 1, 0) [wrong] 329.22 +(v, 1, 1) [wrong] 137.96 +``` + +**Techniques**: +- **"Destructive comparison"** in caption +- **"intentionally performed"** in text +- **Only first row works**: Others are wrong by design +- **Proves necessity**: "meaningful results are achieved only when..." + +--- + +## 9. Writing Style: Theory Keywords + +### Emphasis Words for Theory-Driven Papers + +**Naturalness Keywords** (use these to describe your theory): +- "naturally" - "This naturally leads to..." +- "intrinsic" - "intrinsic relation" +- "well-defined" - "well-defined problem" +- "principled" - "principled basis" +- "first principles" - "from first principles" +- "solely originated from" - "solely from definition" + +**Independence Keywords**: +- "does not depend on" - Theory independence +- "independent of" - Implementation independence +- "self-contained" - System independence +- "from scratch" - No external dependencies +- "without any X" - Negative list + +**Differentiation Keywords**: +- "in contrast to" - Conceptual contrast +- "unlike" - Direct comparison +- "typically" - "typically modeled" (their approach) +- "prior works typically rely on" - Their limitation +- "imposed as" - Artificial constraint (theirs) + +### Avoid These (Too Promotional): +- ❌ "revolutionary" - Too strong +- ❌ "breakthrough" - Let others say it +- ❌ "completely eliminates" - Too absolute +- ✅ "significantly outperforms" - Strong but measured +- ✅ "substantial improvement" - Professional + +--- + +## 10. Common Mistakes in Theory Papers + +### ❌ Don't: +- Derive without explaining motivation - Why are we doing this? +- Skip steps in derivation - Readers aren't you +- Use heuristics without admitting it - Be honest +- Overclaim - "proves optimal" vs "improves over" +- Forget to acknowledge dependencies - If you use X, say it + +### ✅ Do: +- Start from first principles explicitly +- Give each equation/dentity a memorable name +- Show "destructive" ablations to prove necessity +- Report relative improvements (more impactful) +- Use "principled" keywords consistently +- Admit what you DON'T need (negative list) + +--- + +## 11. Revision Checklist for Theory-Driven Papers + +**Before Submission, Verify:** + +- [ ] Abstract starts from established framework (not "X is important") +- [ ] Introduction has "Despite encouraging results..." critique +- [ ] Core concept has a memorable name +- [ ] Derivation is step-by-step with justifications +- [ ] Key equation is named ("X Identity") +- [ ] Theory is contrasted as "principled" vs "heuristic" +- [ ] Results include relative improvement (X-Y%) +- [ ] Self-containment is emphasized (what you don't need) +- [ ] Ablations include destructive tests +- [ ] Tables organize by paradigm, highlight your position +- [ ] Figures tell visual story with captions +- [ ] Theory keywords used consistently (principled, intrinsic, natural) + +--- + +## 12. Example: Applying This Pattern + +### Original Idea (Not Theory-Driven): +"We propose a new training method that improves FID by 20%." + +### Theory-Driven Version: +"Flow Matching provides an intuitive framework for generative modeling, +but recent one-step methods impose consistency constraints heuristically. +Despite encouraging results, the underlying ground-truth field properties +remain unknown. We introduce average velocity (in contrast to instantaneous +velocity), deriving the MeanFlow Identity solely from first principles. +This provides a principled basis for training, achieving 3.43 FID with +50-70% relative improvement. Our method is self-contained, trained from +scratch without pre-training or distillation." + +**The Theory-Driven Frame**: +- Foundation: Flow Matching (established) +- Problem: Heuristic constraints (theory gap) +- Concept: Average velocity (new) +- Theory: MeanFlow Identity (derived) +- Result: Strong + independent (no external deps) + +--- + +## Paper Metadata + +**Title**: Mean Flows for One-step Generative Modeling + +**Authors**: Kaiming He et al. + +**Year**: 2025 + +**Key Concepts**: +- Average velocity vs instantaneous velocity +- MeanFlow Identity +- Principled vs heuristic training +- Self-contained generative models + +--- + +## Extracted by + +**Date**: 2026-01-26 + +**Source**: Analysis of Mean Flows paper (16 pages) + +**Extraction Focus**: Theory-driven paper writing patterns, first-principles +derivations, principled vs heuristic positioning + +**For Integration**: ml-paper-writing skill knowledge base diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/writing-techniques.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/writing-techniques.md new file mode 100644 index 0000000..ae91c01 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/knowledge/writing-techniques.md @@ -0,0 +1,637 @@ +# Writing Techniques and Patterns + +This file contains actionable sentence patterns, transition phrases, and writing techniques extracted from successful ML conference papers. + +--- + +## Transition Phrases + +### Literature Review Transitions +**Source:** Various NeurIPS/ICML papers + +**Introducing Problems:** +- "However, these methods suffer from [limitation]." +- "Despite recent progress, [challenge] remains unsolved." +- "While existing approaches address [aspect], they struggle with [issue]." + +**Presenting Solutions:** +- "To address this, we propose..." +- "We overcome this limitation by..." +- "Our key insight is that..." + +**Connecting to Related Work:** +- "Building on [prior work], we extend..." +- "Unlike approaches that [method], we instead..." +- "Following the success of [paper], we apply..." + +### Methods Section Transitions +**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019) + +**Describing Components:** +- "Our model consists of two main components: [A] and [B]." +- "We divide our approach into [N] stages: [list]." + +**Explaining Rationale:** +- "We choose this architecture because..." +- "This formulation allows us to..." +- "Motivated by [intuition], we design..." + +### Results Section Transitions +**Source:** "Attention Is All You Need", NeurIPS (2017) + +**Presenting Findings:** +- "Our method achieves [result], outperforming baselines by [margin]." +- "As shown in Table 1, our approach..." +- "Figure 2 demonstrates that..." + +**Analyzing Results:** +- "These results suggest that [insight]." +- "Notably, we observe that..." +- "This improvement indicates that..." + +### Discussion Transitions +**Source:** "Language Models are Few-Shot Learners", GPT-3 (2020) + +**Interpreting Findings:** +- "These findings reveal that..." +- "This performance gap suggests that..." +- "The strong correlation between...indicates..." + +**Connecting to Broader Context:** +- "Beyond the specific task, our results imply..." +- "This has important implications for..." + +**Acknowledging Limitations:** +- "It is important to note that our study is limited to..." +- "While these results are promising, several questions remain..." + +--- + +## Sentence Patterns + +### Claim Presentation +**Source:** "Attention Is All You Need", NeurIPS (2017) + +**Strong Claims:** +- "We show that [approach] achieves [result]." +- "We demonstrate that [method] outperforms..." +- "We prove that [technique] converges to..." + +**Nuanced Claims:** +- "Our results suggest that [factor] contributes to..." +- "We observe that [phenomenon] emerges when..." +- "Experiments indicate that [approach] is particularly effective for..." + +### Technical Description +**Source:** "Adam: A Method for Stochastic Optimization", ICLR (2015) + +**Algorithm Description:** +- "Formally, we optimize [objective] using [method]." +- "The update rule for [parameter] is given by..." +- "We modify the standard [approach] by..." + +**Implementation Details:** +- "In practice, we implement [feature] as..." +- "For computational efficiency, we approximate..." +- "We initialize [parameters] using..." + +### Results Presentation +**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019) + +**Quantitative Results:** +- "Our model achieves [score] (±[std]), improving over..." +- "On [dataset], we obtain [result], compared to..." +- "We observe a [percentage]% improvement over baselines." + +**Statistical Reporting:** +- "Results are averaged over N runs with different seeds." +- "Standard deviations are shown in parentheses." +- "The improvement is statistically significant (p<0.01)." + +--- + +## Clarity Techniques + +### Active Voice Usage +**Source:** Various well-written papers + +**Passive (avoid):** +- "The model was trained using..." +- "Experiments were conducted on..." + +**Active (prefer):** +- "We trained the model using..." +- "We conducted experiments on..." + +**Guideline:** Use active voice for actions you performed. Use passive for general facts or when the actor is unclear. + +### Specificity Over Generality +**Source:** "Attention Is All You Need", NeurIPS (2017) + +**Vague (avoid):** +- "This approach improves performance." +- "The method learns good representations." + +**Specific (prefer):** +- "This approach improves accuracy by 15%." +- "The method learns representations that transfer to downstream tasks." + +**Guideline:** Be quantitative whenever possible. Use specific numbers and metrics. + +### Signposting +**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019) + +**Section Openings:** +- "We now describe our model architecture." +- "We evaluate on three tasks: [list]." +- "The results suggest three key insights:" + +**Internal Structure:** +- "First, we [action]. Next, we [action]. Finally, we [action]." +- "Our approach has three stages: [A], [B], and [C]." + +**Guideline:** Use explicit signposting to help tired reviewers follow your paper. + +--- + +## Common Phrase Templates + +### Opening Abstract +**Good Examples:** +- "We introduce [method], a novel approach for [task]." +- "We present [method], which achieves [result] by [mechanism]." +- "We propose [framework] to address [challenge]." + +**Avoid:** +- "In this paper, we study..." (generic) +- "Large language models have..." (overused opening) + +### Introducing Related Work +**Good Examples:** +- "Recent work has shown promise in [area] [refs]." +- "Several approaches have been proposed for [task] [refs]." +- "The standard approach to [problem] is [method] [refs]." + +### Describing Experiments +**Good Examples:** +- "We evaluate on [datasets], comparing against [baselines]." +- "We conduct ablation studies to validate [component]." +- "To verify [claim], we experiment with [variations]." + +### Presenting Results +**Good Examples:** +- "Table 1 shows that our method outperforms all baselines." +- "As shown in Figure 3, performance improves as [factor] increases." +- "Our method achieves state-of-the-art on [task/metric]." + +### Discussing Limitations +**Good Examples:** +- "Our approach has limitations: [constraint]." +- "We note that our method is currently restricted to [condition]." +- "A key limitation is [issue], which we leave for future work." + +--- + +## Writing Principles + +### From Top Papers + +**Clarity First:** +- "Make it easy for reviewers to understand your contribution." +- "Use concrete examples and specific language." +- "Avoid vague or ambiguous statements." + +**Rigorous Presentation:** +- "Provide enough detail for reproduction." +- "Include error bars and statistical tests." +- "Show negative results when relevant." + +**Storytelling:** +- "Your paper tells a story: problem → approach → solution → impact." +- "Make the narrative clear in the introduction." +- "Each section should advance the story." + +**Honesty:** +- "Acknowledge limitations explicitly." +- "Don't overclaim results." +- "Trust reviewers to appreciate honesty." + +--- + +## Notes + +- **Adapt patterns**: These templates can and should be adapted to your specific context +- **Venue matters**: Some venues prefer certain styles (check venue-specific guides) +- **Consistency**: Use consistent terminology throughout +- **Tone**: Maintain professional, objective tone +- **Length**: Keep transitions concise; don't over-explain + +**Attribution:** All patterns extracted from analyzed papers with source citations for traceability. + + +--- + +## "Surprisingly" Findings: Multi-Level Reporting Pattern + +**Source**: Kaiming He et al., "Exploring Plain Vision Transformer Backbones for Object Detection" (ViTDet, ECCV 2022), "Mean Flows" (2025) + +**Paper Type**: Design simplification, unexpected findings + +### The Three-Level "Surprisingly" Pattern + +#### Level 1: Basic Surprise (Abstract/Opening) + +**Pattern**: +```markdown +Surprisingly, we observe: (i) [simple sufficient without common practice] +and (ii) [simple sufficient without common practice] +``` + +**Example (ViTDet Abstract)**: +```latex +Surprisingly, we observe: (i) it is sufficient to build a simple feature +pyramid from a single-scale feature map (without the common FPN design) and +(ii) it is sufficient to use window attention (without shifting) aided with +very few cross-window propagation blocks. +``` + +**Key Techniques**: +- **Structured list**: Use (i) and (ii) to separate findings +- **"sufficient"**: Scientific phrasing (not "optimal") +- **"without [common practice]"**: Negative differentiation + +#### Level 2: Competitive Surprise (Introduction) + +**Pattern**: +```markdown +More surprisingly, under some circumstances, our [method] can compete +with the leading [competitors]. +``` + +**Example (ViTDet Introduction)**: +```latex +More surprisingly, under some circumstances, our plain-backbone detector, +named ViTDet, can compete with the leading hierarchical-backbone detectors +(e.g., Swin, MViT). +``` + +**Key Techniques**: +- **"More surprisingly"**: Progressive emphasis +- **"under some circumstances"**: Measured claim +- **"can compete with"**: Not "beat", competitive +- **Name competitors**: Specific (Swin, MViT) + +#### Level 3: Superiority Surprise (Results) + +**Pattern**: +```markdown +With [specific condition], our [method] can outperform the [competitors] +that use [stronger condition]. The gains are more prominent for [condition]. +``` + +**Example**: +```latex +With Masked Autoencoder (MAE) pre-training, our plain-backbone detector can +outperform the hierarchical counterparts that are pre-trained on ImageNet-1K/21K +with supervision (Figure 3). The gains are more prominent for larger model sizes. +``` + +**Key Techniques**: +- **Specific conditions compared**: MAE vs ImageNet supervised +- **"outperform"**: Stronger claim here (qualified by conditions) +- **"The gains are more prominent for..."**: Pattern observation + +--- + +### "Surprisingly" Variants + +#### "Interestingly" - Pattern Observation + Explanation + +**Pattern**: +```markdown +Interestingly, [observation]. This is in line with the observation in [paper] +that [their finding]. [Additional explanation]. +``` + +**Example (ViTDet)**: +```latex +Interestingly, performing propagation in the last 4 blocks is nearly as +good as even placement. This is in line with the observation in ViT [14] +that ViT has longer attention distance in later blocks and is more localized +in earlier ones. +``` + +**Use when**: You have literature support for your observation + +#### "Notably" - Important Detail + +**Pattern**: +```markdown +Notably, [counter-intuitive result or impressive number]. +``` + +**Examples**: +- "Notably, even embedding only the interval t−r yields reasonable results." +- "Notably, our method is self-contained and trained entirely from scratch." + +**Use when**: Emphasizing importance or counter-intuitive finding + +#### "It is worth noting that" - Caveat/Clarification + +**Pattern**: +```markdown +It is worth noting that [technical caveat or clarification]. +``` + +**Examples**: +- "It is worth noting that even when the conditional flows are designed to be straight ('rectified'), the marginal velocity field typically induces a curved trajectory." +- "It is worth noting that the 3.34× memory (49G) is estimated as if the same training implementation could be used, which is not practical and requires special memory optimization." + +**Use when**: Preventing misunderstanding or clarifying technical details + +--- + +### When to Use "Surprisingly" + +**DO use**: +- When finding genuinely contradicts common practice +- When simple solution works as well as complex one +- When you have explanation (literature, hypothesis, theory) +- With measured claims ("under some circumstances", "can compete") +- With "sufficient" not "optimal" + +**DON'T use**: +- For incremental improvements (use "additionally" instead) +- Without explanation/justification +- Overgeneralizing ("always", "proves") +- For expected results + +--- + +## Ablation Study Writing Techniques + +**Source**: Kaiming He papers (ViTDet, MeanFlows, MoCo v2) + +### Table Design: Incremental Progression + +**Pattern**: +```markdown +Table X: [Component] Ablation +┌──────────────────────────────────────────┐ +│ no [component] | AP | Δ │ +│ (a) [common variant] | AP | +X.X │ +│ (b) [another variant] | AP | +Y.Y │ +│ (c) ours: simple | AP | +Z.Z ✓ │ +└──────────────────────────────────────────┘ +``` + +**Example (ViTDet Table 1)**: +```latex +pyramid design APbox APmask +───────────────────────────────────────── +no feature pyramid 47.8 42.5 +(a) FPN, 4-stage 50.3 44.9 +(b) FPN, last-map 50.9 45.3 +(c) simple feature pyramid 51.2 45.5 +``` + +**Techniques**: +- **Baseline**: "no [X]" shows it's needed +- **(a), (b), (c)**: Progressive variations +- **Δ标注**: (+2.5) - Show incremental gains +- **Correspondence**: "The entries (a-c) correspond to Figure X (a-c)" +- **Conclusion**: "our simple pyramid is sufficient" + +--- + +### Destructive Ablation: Proving Necessity + +**Pattern**: +```markdown +We conduct a destructive comparison in which [wrong choice] is intentionally +performed. Meaningful results are achieved only when [correct choice]. +``` + +**Example (MeanFlows Table 1b)**: +```latex +In Tab. 1b, we conduct a destructive comparison in which incorrect JVP +computation is intentionally performed. + +jvp tangent FID, 1-NFE +(v, 0, 1) [correct] 61.06 +(v, 0, 0) [wrong] 268.06 +(v, 1, 0) [wrong] 329.22 +(v, 1, 1) [wrong] 137.96 + +It shows that meaningful results are achieved only when the JVP computation +is correct. +``` + +**Use when**: You need to prove a design choice is necessary (not just optional) + +--- + +### Ablation Narrative: Observation → Explanation + +**Pattern 1: Observation + Literature Support** +```latex +We observe that [observation]. This is consistent with the observation in +[paper] that [their finding]. +``` + +**Pattern 2: Observation + Hypothesis** +```latex +We hypothesize that this is because [reason 1] and also because [reason 2]. +``` + +**Pattern 3: Observation + Theory** +```latex +[Observation]. This indicates that [theoretical explanation]. +``` + +--- + +## Theory-Driven Paper Keywords + +**Source**: Kaiming He et al., "Mean Flows for One-step Generative Modeling" (2025) + +### Naturalness Keywords (use to describe your theory) + +- **"naturally"** - "This naturally leads to..." +- **"intrinsic"** - "intrinsic relation between..." +- **"well-defined"** - "well-defined problem" +- **"principled"** - "principled basis for..." +- **"first principles"** - "from first principles" +- **"solely originated from"** - "solely from definition" + +### Independence Keywords + +- **"does not depend on"** - Theory independence from implementation +- **"independent of"** - Independent of specific choices +- **"self-contained"** - System independence +- **"from scratch"** - No external dependencies +- **"without any X"** - Negative list (what you don't need) + +### Differentiation Keywords + +- **"in contrast to"** - Conceptual contrast +- **"unlike"** - Direct comparison +- **"typically"** - "typically modeled" (their approach) +- **"prior works typically rely on"** - Their limitation +- **"imposed as"** - Artificial constraint (theirs) + +### Avoid (Too Promotional) + +- ❌ "revolutionary" - Let others say it +- ❌ "breakthrough" - Overused +- ❌ "completely eliminates" - Too absolute +- ✅ "significantly outperforms" - Strong but measured +- ✅ "substantial improvement" - Professional + +--- + +## Design Simplification Paper Keywords + +**Source**: Kaiming He et al., "Exploring Plain Vision Transformer Backbones for Object Detection" (ViTDet, 2022) + +### Philosophy Keywords + +- **"minimal"** - "minimal adaptations" +- **"sufficient"** - "is sufficient to" (not "optimal") +- **"simple"** - "simple feature pyramid" +- **"plain"** - "plain backbone" +- **"decouple"** - "decouple pre-training from fine-tuning" +- **"independence"** - "independence of upstream vs downstream" + +### Direction Keywords + +- **"pursue a different direction"** - Clear positioning +- **"in contrast to"** - Differentiation +- **"abandons"** - What you give up (respectfully) +- **"enables"** - What your approach allows + +### Measured Claim Keywords + +- **"under some circumstances"** - Not always +- **"can compete with"** - Competitive, not dominant +- **"more prominent for"** - When effect is stronger +- **"is sufficient"** - Necessary, not maximal + + +--- + +## Updated: 何凯明的写作技巧 + +> 来源: 分析了何凯明的 11 篇代表性论文（扩展分析，包括 MeanFlows、ViTDet、MAR 等） +> 添加时间: 2026-01-26 + +> 扩展内容包括： +> - "Surprisingly" 发现的多层次报告模式 +> - Ablation Study 的增量式和破坏性实验设计 +> - 理论驱动型论文的关键词策略 +> - 设计简化型论文的关键词策略 + +### 句子结构偏好 + +**主动语态优先** (被动语态仅 9.3%) +何凯明偏好使用主动、直接的陈述： + +**✅ 推荐 (何凯明的风格):** +- "We present a framework for [task]" +- "Our method achieves [result]" +- "This formulation enables [benefit]" + +**❌ 避免:** +- "A framework is presented for [task]" +- "Results are achieved by our method" + +### 贡献表达方式 + +何凯明常用的贡献表达模式： + +**模式 1: 直接陈述** +``` +We propose [method] that [feature]. +We demonstrate [result] on [dataset]. +``` + +**模式 2: 对比强调** +``` +Unlike [previous work], our approach [difference]. +This leads to [improvement] in [metric]. +``` + +**模式 3: 问题-解决方案** +``` +[Challenge] remains difficult. We address this by [solution]. +``` + +### 技术术语使用 + +何凯明论文中的高频术语组合： + +| 术语类别 | 常用术语 | +|---------|---------| +| **网络架构** | deep neural networks, convolutional, residual, activation | +| **训练过程** | training, validation, optimization, convergence | +| **性能评估** | outperforms, achieves, improves, surpasses | +| **方法定位** | state-of-the-art, baseline, framework, algorithm | +| **所有权** | our method, our approach, our framework | + +### 过渡短语 + +何凯明论文中常用的过渡短语（按频率排序）： + +1. **however** - 用于对比不同观点 +2. **in addition/additionally** - 补充信息 +3. **furthermore** - 递进说明 +4. **therefore/thus** - 得出结论 +5. **specifically** - 举例说明 +6. **conversely** - 对比说明 + +### 数值结果呈现 + +何凯明在呈现数值结果时的模式： + +**精确性优先:** +``` +Our method achieves 76.4% accuracy (Table X). +This represents a 28% relative improvement. +``` + +**对比式呈现:** +``` +Compared to baseline (73.2%), our method (76.4%) improves +by 3.2 percentage points. +``` + +**强调意义:** +``` +This result won the 1st place in [competition/task]. +``` + +### 图表引用模式 + +何凯明引用图表的标准格式： + +**图表引入:** +- "Fig. X shows [现象]" +- "Table Y summarizes [结果]" +- "As shown in Fig. Z, [结论]" + +**图表描述:** +- "The solid line denotes [条件 A], the dashed line [条件 B]" +- "The blue curve shows [指标], while the red curve shows [指标]" + +### 网络架构描述 + +何凯明在描述网络架构时的特点： + +1. **表格化呈现** - 使用表格列出层配置 +2. **可视化辅助** - 配合架构图 +3. **简洁符号** - 使用清晰的数学符号 +4. **示例:** +``` +layer name | output size | configuration +conv1 | 112×112 | 7×7, 64, /2 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/literature-research/arxiv-search-guide.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/literature-research/arxiv-search-guide.md new file mode 100644 index 0000000..c37c868 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/literature-research/arxiv-search-guide.md @@ -0,0 +1,199 @@ +# arXiv Literature Search Guide + +## Overview + +This guide provides workflows for discovering and evaluating recent ML research papers on arXiv. Use this when conducting literature reviews, finding related work, or staying updated on recent publications. + +--- + +## Search Strategies + +### 1. Keyword-Based Search + +**arXiv Search URL Pattern:** +``` +https://arxiv.org/search/?searchtype=all&query=KEYWORDS&abstracts=show&order=-announced_date_first +``` + +**Common ML Search Keywords:** +- **General ML**: `machine learning`, `deep learning`, `neural networks` +- **Specific Areas**: `reinforcement learning`, `transformer`, `attention mechanism`, `graph neural networks` +- **Applications**: `computer vision`, `natural language processing`, `reinforcement learning` +- **Methods**: `self-supervised learning`, `contrastive learning`, `foundation models` + +**Tips:** +- Combine keywords with `+` for AND operation +- Use `|` for OR operation +- Put phrases in quotes for exact matches: `"attention is all you need"` + +### 2. Category-Based Search + +**Recommended arXiv Categories for ML:** +- `cs.LG` (Machine Learning) +- `cs.AI` (Artificial Intelligence) +- `cs.CV` (Computer Vision and Pattern Recognition) +- `cs.CL` (Computation and Language) +- `cs.NE` (Neural and Evolutionary Computing) +- `stat.ML` (Machine Learning - Statistics) + +**Category Filter URL:** +``` +https://arxiv.org/search/?cat:cs.LG+OR+cat:cs.AI+AND+all:transformer&abstracts=show&order=-announced_date_first +``` + +### 3. Time-Based Filtering + +**Recent Papers (Last 3 Months):** +- Use `order=-announced_date_first` for newest first +- Manually filter by submission date +- Check paper metadata for submission date + +--- + +## Using Chrome MCP for arXiv Search + +When available, use Chrome MCP tools for automated arXiv searching: + +1. **Navigate to arXiv search** using Chrome MCP navigation +2. **Extract paper information** from search results: + - Paper title + - Authors + - arXiv ID + - Abstract preview + - Publication date + +3. **Navigate to individual papers** for detailed review + +--- + +## Paper Quality Evaluation + +Evaluate papers using the 5-dimension criteria below: + +| Dimension | Weight | Key Points | +|-----------|--------|------------| +| **Innovation** | 30% | Novelty of contribution | +| **Method Completeness** | 25% | Clarity and reproducibility | +| **Experimental Thoroughness** | 25% | Validation depth | +| **Writing Quality** | 10% | Clarity of expression | +| **Relevance & Impact** | 10% | Domain importance | + +### Scoring Guidelines (1-5 scale) + +**Innovation (30%):** +- 5: Breakthrough contribution, major impact +- 4: Significant improvement, new insights +- 3: Methodological innovation +- 2: Incremental improvement +- 1: Minor improvements + +**Method Completeness (25%):** +- 5: Complete and rigorous, easily reproducible +- 4: Very detailed, mostly reproducible +- 3: Core method clear, basically reproducible +- 2: Lacks key details +- 1: Unclear description + +**Experimental Thoroughness (25%):** +- 5: Comprehensive multi-dataset, ablation studies +- 4: Multiple datasets, reasonable ablations +- 3: Main experiments complete +- 2: Limited experiments +- 1: Minimal validation + +**Writing Quality (10%):** +- 5: Excellent clarity and rigor +- 4: Clear and well-structured +- 3: Understandable +- 2: Some ambiguity +- 1: Confusing + +**Relevance & Impact (10%):** +- 5: Solves important problem, wide impact +- 4: Important domain problem +- 3: Meaningful contribution +- 2: Niche problem +- 1: Limited impact + +### Selection Process + +1. **Screen by title/abstract** for relevance +2. **Navigate to full paper** for detailed review +3. **Score each dimension** (1-5) +4. **Calculate weighted total** +5. **Rank and select** top papers + +--- + +## Extracting Paper Metadata + +**From arXiv Abstract Page (`https://arxiv.org/abs/ARXIV_ID`):** + +- Title (from `<h1>` tag) +- Authors (from `.authors` element) +- Abstract (from `blockquote.abstract`) +- Submission date (from `.dateline`) +- arXiv ID (from URL) +- Categories (from `.subjects`) +- Comments (if present) +- Code repository (check abstract for GitHub links) + +--- + +## Integration with Citation Workflow + +After finding relevant papers: + +1. **Verify citations** using Semantic Scholar API (see `../citation-workflow.md`) +2. **Fetch BibTeX** programmatically via DOI +3. **Store in bibliography** with verification status + +--- + +## Common Use Cases + +### Finding Related Work + +When writing a paper, use arXiv search to: +1. Find recent papers on your topic +2. Identify state-of-the-art methods +3. Discover competing approaches +4. Find baseline comparisons + +### Staying Updated + +Set up regular searches for: +- Your specific research area +- Competing labs/researchers +- New methods in your domain +- Conference proceedings (preprints) + +### Literature Reviews + +For comprehensive reviews: +1. Start with broad keyword searches +2. Filter by recent publications (last 1-3 years) +3. Use citation chaining (forward and backward) +4. Evaluate and select high-quality papers +5. Organize by theme/contribution + +--- + +## Tips for Effective Searching + +1. **Use specific keywords** rather than broad terms +2. **Combine techniques** (keywords + categories + time filters) +3. **Check code availability** (many arXiv papers link to GitHub) +4. **Look for citations** to understand impact +5. **Read abstracts carefully** before full papers +6. **Use paper metrics** (citation count, code stars) as indicators + +--- + +## External Resources + +- **arXiv**: https://arxiv.org/ +- **Semantic Scholar**: https://www.semanticscholar.org/ +- **Papers With Code**: https://paperswithcode.com/ +- **Connected Papers**: https://www.connectedpapers.com/ +- **arXiv API**: http://export.arxiv.org/api_help/ diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/literature-research/paper-quality-criteria.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/literature-research/paper-quality-criteria.md new file mode 100644 index 0000000..0e07a8a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/literature-research/paper-quality-criteria.md @@ -0,0 +1,303 @@ +# ML Paper Quality Evaluation Criteria + +## Overview + +Use these criteria to evaluate ML research papers found during literature search or when selecting papers for detailed review. The 5-dimension framework provides structured assessment for paper selection and comparison. + +--- + +## Evaluation Dimensions + +| Dimension | Weight | Description | +|-----------|--------|-------------| +| **Innovation** | 30% | Novelty and originality of contribution | +| **Method Completeness** | 25% | Clarity, rigor, and reproducibility | +| **Experimental Thoroughness** | 25% | Validation depth and analysis quality | +| **Writing Quality** | 10% | Clarity and presentation | +| **Relevance & Impact** | 10% | Domain importance and potential impact | + +--- + +## Detailed Scoring Rubrics + +### 1. Innovation (30%) + +**Score 5 - Breakthrough:** +- Proposes entirely new paradigm or framework +- Solves long-standing open problem +- Major impact expected on the field +- Challenges fundamental assumptions + +**Score 4 - Significant Innovation:** +- Substantial improvement over existing methods +- New insights or perspectives +- Novel combination of techniques +- Clear advancement over state-of-the-art + +**Score 3 - Methodological Innovation:** +- New method or architecture proposed +- Some novelty but incremental +- Reasonable contribution +- Standard type of innovation + +**Score 2 - Incremental Improvement:** +- Minor improvements to existing methods +- Limited novelty +- Small advancement +- Mostly derivative + +**Score 1 - Trivial:** +- Minimal contribution +- Obvious extension +- No real innovation +- Known results + +**Evaluation Questions:** +- Does this paper propose something genuinely new? +- Does it advance the state-of-the-art? +- Will this influence future work? +- Is the contribution significant or marginal? + +--- + +### 2. Method Completeness (25%) + +**Score 5 - Complete and Rigorous:** +- Full mathematical derivation +- All hyperparameters specified +- Complete algorithmic details +- Easily reproducible +- Code available + +**Score 4 - Very Complete:** +- Detailed method description +- Most important details included +- Mostly reproducible +- Minor gaps in documentation + +**Score 3 - Reproducible:** +- Core method clearly described +- Key details present +- Can be reproduced with effort +- Some ambiguity in details + +**Score 2 - Lacks Details:** +- Key details missing +- Difficult to reproduce +- Incomplete description +- Ambiguous in important areas + +**Score 1 - Unclear:** +- Method description unclear +- Missing critical information +- Cannot determine validity +- Poorly explained + +**Evaluation Questions:** +- Can another researcher reproduce this work? +- Are all important details specified? +- Is mathematical derivation sound? +- Is code available and documented? + +--- + +### 3. Experimental Thoroughness (25%) + +**Score 5 - Comprehensive:** +- Multiple diverse datasets +- Extensive ablation studies +- Statistical significance testing +- Thorough analysis and discussion +- Comparison with strong baselines + +**Score 4 - Very Thorough:** +- Multiple datasets +- Reasonable ablation studies +- Proper baseline comparisons +- Good analysis + +**Score 3 - Adequate:** +- Main experiments complete +- Standard datasets +- Basic baselines +- Results are credible + +**Score 2 - Limited:** +- Limited experiments +- Few datasets +- Weak baselines +- Minimal analysis + +**Score 1 - Insufficient:** +- Minimal validation +- Toy examples only +- No meaningful comparisons +- Results not convincing + +**Evaluation Questions:** +- Are experiments comprehensive? +- Are baselines strong and appropriate? +- Are statistical tests used? +- Is there ablation analysis? +- Are results on standard datasets? + +--- + +### 4. Writing Quality (10%) + +**Score 5 - Excellent:** +- Clear, precise, well-structured +- Logical flow throughout +- Professional presentation +- High-quality figures +- No ambiguity + +**Score 4 - Very Good:** +- Clear and well-written +- Mostly logical structure +- Good presentation +- Minor issues + +**Score 3 - Understandable:** +- Basically clear +- Some organizational issues +- Acceptable presentation +- Understandable with effort + +**Score 2 - Fair:** +- Some confusing sections +- Organization problems +- Presentation issues +- Hard to follow at times + +**Score 1 - Poor:** +- Unclear or confusing +- Poor organization +- Difficult to understand +- Major presentation problems + +**Evaluation Questions:** +- Is the paper easy to understand? +- Is the structure logical? +- Are figures/tables clear? +- Is the writing professional? + +--- + +### 5. Relevance & Impact (10%) + +**Score 5 - High Impact:** +- Solves important problem +- Broad applicability +- Expected wide influence +- Addresses fundamental challenge + +**Score 4 - Domain Important:** +- Important problem in field +- Significant potential impact +- Relevant to many researchers + +**Score 3 - Meaningful:** +- Meaningful contribution +- Moderate impact expected +- Relevant to subset of field + +**Score 2 - Niche:** +- Specialized problem +- Limited applicability +- Narrow impact + +**Score 1 - Limited:** +- Very narrow problem +- Minimal impact expected +- Limited relevance + +**Evaluation Questions:** +- Is this an important problem? +- Will this influence future work? +- Is it relevant to current research needs? +- Does it address a significant challenge? + +--- + +## Scoring Calculation + +**Weighted Total:** +``` +Total = (Innovation × 0.30) + (Method × 0.25) + (Experiments × 0.25) + (Writing × 0.10) + (Impact × 0.10) +``` + +**Example Calculation:** +- Innovation: 4/5 +- Method: 3/5 +- Experiments: 4/5 +- Writing: 3/5 +- Impact: 4/5 + +``` +Total = (4 × 0.30) + (3 × 0.25) + (4 × 0.25) + (3 × 0.10) + (4 × 0.10) + = 1.20 + 0.75 + 1.00 + 0.30 + 0.40 + = 3.65 / 5.0 +``` + +--- + +## Selection Process + +### For Literature Reviews + +1. **Screen papers** by title/abstract for relevance +2. **Full review** of potentially relevant papers +3. **Score each paper** using all 5 dimensions +4. **Rank by total score** +5. **Select top papers** for detailed review + +### Quality Thresholds + +- **Excellent**: 4.0+ (include definitely) +- **Good**: 3.5-3.9 (include if relevant) +- **Fair**: 3.0-3.4 (include if highly relevant) +- **Poor**: <3.0 (exclude unless essential) + +--- + +## Quick Screening Indicators + +Before detailed review, check: + +**Positive Indicators:** +- Published at top venue (NeurIPS, ICML, ICLR) +- Citations in top papers +- Code available with stars +- Authors from top labs +- Clear novelty in abstract + +**Negative Indicators:** +- Vague abstract +- Limited experiments mentioned +- No baselines mentioned +- Poor writing in abstract +- incremental claims only + +--- + +## Integration with Paper Discovery + +When using arXiv search (`arxiv-search-guide.md`): + +1. **Search** for relevant papers +2. **Extract metadata** from arXiv pages +3. **Quick screen** by abstract/relevance +4. **Detailed review** of promising papers +5. **Score using** these criteria +6. **Rank and select** top candidates + +--- + +## Notes + +- These criteria are designed for ML papers specifically +- Adjust weights based on your specific needs +- Use scores as relative comparisons, not absolute judgments +- Consider venue reputation as additional signal +- Code availability is increasingly important for reproducibility diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/reviewer-guidelines.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/reviewer-guidelines.md new file mode 100644 index 0000000..17e7cf0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/reviewer-guidelines.md @@ -0,0 +1,367 @@ +# Reviewer Guidelines & Evaluation Criteria + +This reference documents how reviewers evaluate papers at major ML/AI conferences, helping authors anticipate and address reviewer concerns. + +--- + +## Contents + +- [Universal Evaluation Dimensions](#universal-evaluation-dimensions) +- [NeurIPS Reviewer Guidelines](#neurips-reviewer-guidelines) +- [ICML Reviewer Guidelines](#icml-reviewer-guidelines) +- [ICLR Reviewer Guidelines](#iclr-reviewer-guidelines) +- [ACL Reviewer Guidelines](#acl-reviewer-guidelines) +- [What Makes Reviews Strong](#what-makes-reviews-strong) +- [Common Reviewer Concerns](#common-reviewer-concerns) +- [How to Address Reviewer Feedback](#how-to-address-reviewer-feedback) + +--- + +## Universal Evaluation Dimensions + +All major ML conferences assess papers across four core dimensions: + +### 1. Quality (Technical Soundness) + +**What reviewers ask:** +- Are claims well-supported by theoretical analysis or experimental results? +- Are the proofs correct? Are the experiments properly controlled? +- Are baselines appropriate and fairly compared? +- Is the methodology sound? + +**How to ensure high quality:** +- Include complete proofs (main paper or appendix with sketches) +- Use appropriate baselines (not strawmen) +- Report variance/error bars with methodology +- Document hyperparameter selection process + +### 2. Clarity (Writing & Organization) + +**What reviewers ask:** +- Is the paper clearly written and well organized? +- Can an expert in the field reproduce the results? +- Is notation consistent? Are terms defined? +- Is the paper self-contained? + +**How to ensure clarity:** +- Use consistent terminology throughout +- Define all notation at first use +- Include reproducibility details (appendix acceptable) +- Have non-authors read before submission + +### 3. Significance (Impact & Importance) + +**What reviewers ask:** +- Are the results impactful for the community? +- Will others build upon this work? +- Does it address an important problem? +- What is the potential for real-world impact? + +**How to demonstrate significance:** +- Clearly articulate the problem's importance +- Connect to broader research themes +- Discuss potential applications +- Compare to existing approaches meaningfully + +### 4. Originality (Novelty & Contribution) + +**What reviewers ask:** +- Does this provide new insights? +- How does it differ from prior work? +- Is the contribution non-trivial? + +**Key insight from NeurIPS guidelines:** +> "Originality does not necessarily require introducing an entirely new method. Papers that provide novel insights from evaluating existing approaches or shed light on why methods succeed can also be highly original." + +--- + +## NeurIPS Reviewer Guidelines + +### Scoring System (1-6 Scale) + +| Score | Label | Description | +|-------|-------|-------------| +| **6** | Strong Accept | Groundbreaking, flawless work; top 2-3% of submissions | +| **5** | Accept | Technically solid, high impact; would benefit the community | +| **4** | Borderline Accept | Solid work with limited evaluation; leans accept | +| **3** | Borderline Reject | Solid but weaknesses outweigh strengths; leans reject | +| **2** | Reject | Technical flaws or weak evaluation | +| **1** | Strong Reject | Well-known results or unaddressed ethics concerns | + +### Reviewer Instructions + +Reviewers are explicitly instructed to: + +1. **Evaluate the paper as written** - not what it could be with revisions +2. **Provide constructive feedback** - 3-5 actionable points +3. **Not penalize honest limitations** - acknowledging weaknesses is encouraged +4. **Assess reproducibility** - can the work be verified? +5. **Consider ethical implications** - potential misuse or harm + +### What Reviewers Should Avoid + +- Superficial, uninformed reviews +- Demanding unreasonable additional experiments +- Penalizing authors for honest limitation acknowledgment +- Rejecting for missing citations to reviewer's own work + +### Timeline (NeurIPS 2025) + +- Bidding: May 17-21 +- Reviewing period: May 29 - July 2 +- Author rebuttals: July 24-30 +- Discussion period: July 31 - August 13 +- Final notifications: September 18 + +--- + +## ICML Reviewer Guidelines + +### Review Structure + +ICML reviewers provide: + +1. **Summary** - Brief description of contributions +2. **Strengths** - Positive aspects +3. **Weaknesses** - Areas for improvement +4. **Questions** - Clarifications for authors +5. **Limitations** - Assessment of stated limitations +6. **Ethics** - Any concerns +7. **Overall Score** - Recommendation + +### Scoring Guidelines + +ICML uses a similar 1-6 scale with calibration: +- Top 25% of accepted papers: Score 5-6 +- Typical accepted paper: Score 4-5 +- Borderline: Score 3-4 +- Clear reject: Score 1-2 + +### Key Evaluation Points + +1. **Reproducibility** - Are there enough details? +2. **Experimental rigor** - Multiple seeds, proper baselines? +3. **Writing quality** - Clear, organized, well-structured? +4. **Novelty** - Non-trivial contribution? + +--- + +## ICLR Reviewer Guidelines + +### OpenReview Process + +ICLR uses OpenReview with: +- Public reviews (after acceptance decisions) +- Author responses visible to reviewers +- Discussion between reviewers and ACs + +### Scoring + +ICLR reviews include: +- **Soundness**: 1-4 scale +- **Presentation**: 1-4 scale +- **Contribution**: 1-4 scale +- **Overall**: 1-10 scale +- **Confidence**: 1-5 scale + +### Unique ICLR Considerations + +1. **LLM Disclosure** - Reviewers assess whether LLM use is properly disclosed +2. **Reproducibility** - Emphasis on code availability +3. **Reciprocal Reviewing** - Authors must also serve as reviewers + +--- + +## ACL Reviewer Guidelines + +### ACL-Specific Criteria + +ACL adds NLP-specific evaluation: + +1. **Linguistic soundness** - Are linguistic claims accurate? +2. **Resource documentation** - Are datasets/models properly documented? +3. **Multilingual consideration** - If applicable, is language diversity addressed? + +### Limitations Section + +ACL specifically requires a Limitations section. Reviewers check: +- Are limitations honest and comprehensive? +- Do limitations undermine core claims? +- Are potential negative impacts addressed? + +### Ethics Review + +ACL has a dedicated ethics review process for: +- Dual-use concerns +- Data privacy issues +- Bias and fairness implications + +--- + +## What Makes Reviews Strong + +### Following Daniel Dennett's Rules + +Good reviewers follow these principles: + +1. **Re-express the position fairly** - Show you understand the paper +2. **List agreements** - Acknowledge what works well +3. **List what you learned** - Credit the contribution +4. **Only then critique** - After establishing understanding + +### Review Structure Best Practices + +**Strong Review Structure:** +``` +Summary (1 paragraph): +- What the paper does +- Main contribution claimed + +Strengths (3-5 bullets): +- Specific positive aspects +- Why these matter + +Weaknesses (3-5 bullets): +- Specific concerns +- Why these matter +- Suggestions for addressing + +Questions (2-4 items): +- Clarifications needed +- Things that would change assessment + +Minor Issues (optional): +- Typos, unclear sentences +- Formatting issues + +Overall Assessment: +- Clear recommendation with reasoning +``` + +--- + +## Common Reviewer Concerns + +### Technical Concerns + +| Concern | How to Pre-empt | +|---------|-----------------| +| "Baselines too weak" | Use state-of-the-art baselines, cite recent work | +| "Missing ablations" | Include systematic ablation study | +| "No error bars" | Report std dev/error, multiple runs | +| "Hyperparameters not tuned" | Document tuning process, search ranges | +| "Claims not supported" | Ensure every claim has evidence | + +### Novelty Concerns + +| Concern | How to Pre-empt | +|---------|-----------------| +| "Incremental contribution" | Clearly articulate what's new vs prior work | +| "Similar to [paper X]" | Explicitly compare to X in Related Work | +| "Straightforward extension" | Highlight non-obvious aspects | + +### Clarity Concerns + +| Concern | How to Pre-empt | +|---------|-----------------| +| "Hard to follow" | Use clear structure, signposting | +| "Notation inconsistent" | Review all notation, create notation table | +| "Missing details" | Include reproducibility appendix | +| "Figures unclear" | Self-contained captions, proper sizing | + +### Significance Concerns + +| Concern | How to Pre-empt | +|---------|-----------------| +| "Limited impact" | Discuss broader implications | +| "Narrow evaluation" | Evaluate on multiple benchmarks | +| "Only works in restricted setting" | Acknowledge scope, explain why still valuable | + +--- + +## How to Address Reviewer Feedback + +### Rebuttal Best Practices + +**Do:** +- Thank reviewers for their time +- Address each concern specifically +- Provide evidence (new experiments if possible) +- Be concise—reviewers are busy +- Acknowledge valid criticisms + +**Don't:** +- Be defensive or dismissive +- Make promises you can't keep +- Ignore difficult criticisms +- Write excessively long rebuttals +- Argue about subjective assessments + +### Rebuttal Template + +```markdown +We thank the reviewers for their thoughtful feedback. + +## Reviewer 1 + +**R1-Q1: [Quoted concern]** +[Direct response with evidence] + +**R1-Q2: [Quoted concern]** +[Direct response with evidence] + +## Reviewer 2 + +... + +## Summary of Changes +If accepted, we will: +1. [Specific change] +2. [Specific change] +3. [Specific change] +``` + +### When to Accept Criticism + +Some reviewer feedback should simply be accepted: +- Valid technical errors +- Missing important related work +- Unclear explanations +- Missing experimental details + +Acknowledge these gracefully: "The reviewer is correct that... We will revise to..." + +### When to Push Back + +You can respectfully disagree when: +- Reviewer misunderstood the paper +- Requested experiments are out of scope +- Criticism is factually incorrect + +Frame disagreements constructively: "We appreciate this perspective. However, [explanation]..." + +--- + +## Pre-Submission Reviewer Simulation + +Before submitting, ask yourself: + +**Quality:** +- [ ] Would I trust these results if I saw them? +- [ ] Are all claims supported by evidence? +- [ ] Are baselines fair and recent? + +**Clarity:** +- [ ] Can someone reproduce this from the paper? +- [ ] Is the writing clear to non-experts in this subfield? +- [ ] Are all terms and notation defined? + +**Significance:** +- [ ] Why should the community care about this? +- [ ] What can people do with this work? +- [ ] Is the problem important? + +**Originality:** +- [ ] What specifically is new here? +- [ ] How does this differ from closest related work? +- [ ] Is the contribution non-trivial? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/sources.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/sources.md new file mode 100644 index 0000000..1690d2b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/sources.md @@ -0,0 +1,159 @@ +# Source Bibliography + +This document lists all authoritative sources used to build this skill, organized by topic. + +--- + +## Writing Philosophy & Guides + +### Primary Sources (Must-Read) + +| Source | Author | URL | Key Contribution | +|--------|--------|-----|------------------| +| **Highly Opinionated Advice on How to Write ML Papers** | Neel Nanda | [Alignment Forum](https://www.alignmentforum.org/posts/eJGptPbbFPZGLpjsp/highly-opinionated-advice-on-how-to-write-ml-papers) | Narrative framework, "What/Why/So What", time allocation | +| **How to Write ML Papers** | Sebastian Farquhar (DeepMind) | [Blog](https://sebastianfarquhar.com/on-research/2024/11/04/how_to_write_ml_papers/) | 5-sentence abstract formula, structure templates | +| **A Survival Guide to a PhD** | Andrej Karpathy | [Blog](http://karpathy.github.io/2016/09/07/phd/) | Paper structure recipe, contribution framing | +| **Heuristics for Scientific Writing** | Zachary Lipton (CMU) | [Blog](https://www.approximatelycorrect.com/2018/01/29/heuristics-technical-scientific-writing-machine-learning-perspective/) | Word choice, section balance, intensifier warnings | +| **Advice for Authors** | Jacob Steinhardt (UC Berkeley) | [Blog](https://jsteinhardt.stat.berkeley.edu/blog/advice-for-authors) | Precision over brevity, consistent terminology | +| **Easy Paper Writing Tips** | Ethan Perez (Anthropic) | [Blog](https://ethanperez.net/easy-paper-writing-tips/) | Micro-level tips, apostrophe unfolding, clarity tricks | + +### Foundational Scientific Writing + +| Source | Author | URL | Key Contribution | +|--------|--------|-----|------------------| +| **The Science of Scientific Writing** | Gopen & Swan | [PDF](https://cseweb.ucsd.edu/~swanson/papers/science-of-writing.pdf) | Topic/stress positions, old-before-new, 7 principles | +| **Summary of Science of Scientific Writing** | Lawrence Crowl | [Summary](https://www.crowl.org/Lawrence/writing/GopenSwan90.html) | Condensed version of Gopen & Swan | + +### Additional Resources + +| Source | URL | Key Contribution | +|--------|-----|------------------| +| How To Write A Research Paper In ML | [Blog](https://grigorisg9gr.github.io/machine%20learning/research%20paper/how-to-write-a-research-paper-in-machine-learning/) | Practical walkthrough, LaTeX tips | +| A Recipe for Training Neural Networks | [Karpathy Blog](http://karpathy.github.io/2019/04/25/recipe/) | Debugging methodology that translates to paper structure | +| ICML Paper Writing Best Practices | [ICML](https://icml.cc/Conferences/2022/BestPractices) | Official venue guidance | +| Bill Freeman's Writing Slides | [MIT](https://billf.mit.edu/sites/default/files/documents/cvprPapers.pdf) | Visual guide to paper structure | + +--- + +## Official Conference Guidelines + +### NeurIPS + +| Document | URL | Purpose | +|----------|-----|---------| +| Paper Checklist Guidelines | [NeurIPS](https://neurips.cc/public/guides/PaperChecklist) | 16-item mandatory checklist | +| Reviewer Guidelines 2025 | [NeurIPS](https://neurips.cc/Conferences/2025/ReviewerGuidelines) | Evaluation criteria, scoring | +| Style Files | [NeurIPS](https://neurips.cc/Conferences/2025/PaperInformation/StyleFiles) | LaTeX templates | + +### ICML + +| Document | URL | Purpose | +|----------|-----|---------| +| Paper Guidelines | [ICML](https://icml.cc/Conferences/2024/PaperGuidelines) | Submission requirements | +| Reviewer Instructions 2025 | [ICML](https://icml.cc/Conferences/2025/ReviewerInstructions) | Review form, evaluation | +| Style & Author Instructions | [ICML](https://icml.cc/Conferences/2022/StyleAuthorInstructions) | Formatting specifications | + +### ICLR + +| Document | URL | Purpose | +|----------|-----|---------| +| Author Guide 2026 | [ICLR](https://iclr.cc/Conferences/2026/AuthorGuide) | Submission requirements, LLM disclosure | +| Reviewer Guide 2025 | [ICLR](https://iclr.cc/Conferences/2025/ReviewerGuide) | Review process, evaluation | + +### ACL/EMNLP + +| Document | URL | Purpose | +|----------|-----|---------| +| ACL Style Files | [GitHub](https://github.com/acl-org/acl-style-files) | LaTeX templates | +| ACL Rolling Review | [ARR](https://aclrollingreview.org/) | Submission process | + +### AAAI + +| Document | URL | Purpose | +|----------|-----|---------| +| Author Kit 2026 | [AAAI](https://aaai.org/authorkit26/) | Templates and guidelines | + +### COLM + +| Document | URL | Purpose | +|----------|-----|---------| +| Template | [GitHub](https://github.com/COLM-org/Template) | LaTeX templates | + +--- + +## Citation APIs & Tools + +### APIs + +| API | Documentation | Best For | +|-----|---------------|----------| +| **Semantic Scholar** | [Docs](https://api.semanticscholar.org/api-docs/) | ML/AI papers, citation graphs | +| **CrossRef** | [Docs](https://www.crossref.org/documentation/retrieve-metadata/rest-api/) | DOI lookup, BibTeX retrieval | +| **arXiv** | [Docs](https://info.arxiv.org/help/api/basics.html) | Preprints, PDF access | +| **OpenAlex** | [Docs](https://docs.openalex.org/) | Open alternative, bulk access | + +### Python Libraries + +| Library | Install | Purpose | +|---------|---------|---------| +| `semanticscholar` | `pip install semanticscholar` | Semantic Scholar wrapper | +| `arxiv` | `pip install arxiv` | arXiv search and download | +| `habanero` | `pip install habanero` | CrossRef client | + +### Citation Verification + +| Tool | URL | Purpose | +|------|-----|---------| +| Citely | [citely.ai](https://citely.ai/citation-checker) | Batch verification | +| ReciteWorks | [reciteworks.com](https://reciteworks.com/) | In-text citation checking | + +--- + +## Visualization & Formatting + +### Figure Creation + +| Tool | URL | Purpose | +|------|-----|---------| +| PlotNeuralNet | [GitHub](https://github.com/HarisIqbal88/PlotNeuralNet) | TikZ neural network diagrams | +| SciencePlots | [GitHub](https://github.com/garrettj403/SciencePlots) | Publication-ready matplotlib | +| Okabe-Ito Palette | [Reference](https://jfly.uni-koeln.de/color/) | Colorblind-safe colors | + +### LaTeX Resources + +| Resource | URL | Purpose | +|----------|-----|---------| +| Overleaf Templates | [Overleaf](https://www.overleaf.com/latex/templates) | Online LaTeX editor | +| BibLaTeX Guide | [CTAN](https://ctan.org/pkg/biblatex) | Modern citation management | + +--- + +## Research on AI Writing & Hallucination + +| Source | URL | Key Finding | +|--------|-----|-------------| +| AI Hallucinations in Citations | [Enago](https://www.enago.com/academy/ai-hallucinations-research-citations/) | ~40% error rate | +| Hallucination in AI Writing | [PMC](https://pmc.ncbi.nlm.nih.gov/articles/PMC10726751/) | Types of citation errors | +| NeurIPS 2025 AI Report | [ByteIota](https://byteiota.com/neurips-2025-100-ai-hallucinations-slip-through-review/) | 100+ hallucinated citations | + +--- + +## Quick Reference by Topic + +### For Narrative & Structure +→ Start with: Neel Nanda, Sebastian Farquhar, Andrej Karpathy + +### For Sentence-Level Clarity +→ Start with: Gopen & Swan, Ethan Perez, Zachary Lipton + +### For Word Choice & Style +→ Start with: Zachary Lipton, Jacob Steinhardt + +### For Conference-Specific Requirements +→ Start with: Official venue guidelines (NeurIPS, ICML, ICLR, ACL) + +### For Citation Management +→ Start with: Semantic Scholar API, CrossRef, citation-workflow.md + +### For Reviewer Expectations +→ Start with: Venue reviewer guidelines, reviewer-guidelines.md diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/writing-guide.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/writing-guide.md new file mode 100644 index 0000000..3da7233 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/references/writing-guide.md @@ -0,0 +1,476 @@ +# ML Paper Writing Philosophy & Best Practices + +This reference compiles writing advice from prominent ML researchers including Neel Nanda, Andrej Karpathy, Sebastian Farquhar, Zachary Lipton, and Jacob Steinhardt. + +--- + +## Contents + +- [The Narrative Principle](#the-narrative-principle) +- [Time Allocation](#time-allocation) +- [Abstract Writing Formula](#abstract-writing-formula) +- [Introduction Structure](#introduction-structure) +- [Sentence-Level Clarity](#sentence-level-clarity) +- [Word Choice and Precision](#word-choice-and-precision) +- [Mathematical Writing](#mathematical-writing) +- [Figure Design](#figure-design) +- [Common Mistakes to Avoid](#common-mistakes-to-avoid) + +--- + +## The Narrative Principle + +### From Neel Nanda + +"A paper is a short, rigorous, evidence-based technical story with a takeaway readers care about." + +The narrative rests on three pillars that must be crystal clear by the end of your introduction: + +**The "What"**: One to three specific novel claims fitting within a cohesive theme. Vague contributions like "we study X" fail immediately—reviewers need precise, falsifiable claims. + +**The "Why"**: Rigorous empirical evidence that convincingly supports those claims, including strong baselines honestly tuned and experiments that distinguish between competing hypotheses rather than merely showing "decent results." + +**The "So What"**: Why readers should care, connecting your contribution to problems the community recognizes as important. + +### From Andrej Karpathy + +"A paper is not a random collection of experiments you report on. The paper sells a single thing that was not obvious or present before. The entire paper is organized around this core contribution with surgical precision." + +This applies whether you're presenting a new architecture, a theoretical result, or improved understanding of existing methods—NeurIPS explicitly notes that "originality does not necessarily require an entirely new method." + +**Practical Implication**: If you cannot state your contribution in one sentence, you don't yet have a paper. Everything else—experiments, related work, discussion—exists only to support that core claim. + +--- + +## Time Allocation + +### From Neel Nanda + +Spend approximately **the same amount of time** on each of: +1. The abstract +2. The introduction +3. The figures +4. Everything else combined + +This isn't hyperbole—most reviewers form preliminary judgments before reaching your methods section. Readers encounter your paper in a predictable pattern: **title → abstract → introduction → figures → maybe the rest.** + +### Reviewer Reading Patterns + +Studies of reviewer behavior show: +- Abstract is read 100% of the time +- Introduction is skimmed by 90%+ of reviewers +- Figures are examined before methods by most reviewers +- Full methods are read only if interest is established + +**Implication**: Front-load your paper's value. Don't bury the contribution. + +--- + +## Abstract Writing Formula + +### Sebastian Farquhar's 5-Sentence Formula + +1. **What you achieved**: "We introduce...", "We prove...", "We demonstrate..." +2. **Why this is hard and important** +3. **How you do it** (with specialist keywords for discoverability) +4. **What evidence you have** +5. **Your most remarkable number/result** + +### Example (Good Abstract) + +``` +We prove that gradient descent on overparameterized neural networks +converges to global minima at a linear rate. [What] +This resolves a fundamental question about why deep learning works +despite non-convex optimization landscapes. [Why hard/important] +Our proof relies on showing that the Neural Tangent Kernel remains +approximately constant during training, reducing the problem to +kernel regression. [How with keywords] +We validate our theory on CIFAR-10 and ImageNet, showing that +predicted convergence rates match experiments within 5%. [Evidence] +This is the first polynomial-time convergence guarantee for +networks with practical depth and width. [Remarkable result] +``` + +### What to Avoid + +From Zachary Lipton: "If the first sentence can be pre-pended to any ML paper, delete it." + +**Delete these openings**: +- "Large language models have achieved remarkable success..." +- "Deep learning has revolutionized..." +- "In recent years, neural networks have..." + +**Start with your specific contribution instead.** + +--- + +## Introduction Structure + +### Requirements + +- **1-1.5 pages maximum** (in two-column format) +- **Methods should start by page 2-3** +- Must include **2-4 bullet contribution list** (max 1-2 lines each) + +### Structure Template + +```markdown +1. Opening Hook (2-3 sentences) + - State the problem your paper addresses + - Why it matters RIGHT NOW + +2. Background/Challenge (1 paragraph) + - What makes this problem hard? + - What have others tried? Why is it insufficient? + +3. Your Approach (1 paragraph) + - What do you do differently? + - Key insight that enables your contribution + +4. Contribution Bullets (2-4 items) + - Be specific and falsifiable + - Each bullet: 1-2 lines maximum + +5. Results Preview (2-3 sentences) + - Most impressive numbers + - Scope of evaluation + +6. Paper Organization (optional, 1-2 sentences) + - "Section 2 presents... Section 3 describes..." +``` + +### Contribution Bullets: Good vs Bad + +**Good:** +- We prove that X converges in O(n log n) time under assumption Y +- We introduce Z, a 3-layer architecture that reduces memory by 40% +- We demonstrate that A outperforms B by 15% on benchmark C + +**Bad:** +- We study the problem of X (not a contribution) +- We provide extensive experiments (too vague) +- We make several contributions to the field (says nothing) + +--- + +## Sentence-Level Clarity + +### From Gopen & Swan: "The Science of Scientific Writing" + +The seminal 1990 paper by George Gopen and Judith Swan establishes that **readers have structural expectations** about where information appears in prose. Violating these expectations forces readers to spend energy on structure rather than content. + +> "If the reader is to grasp what the writer means, the writer must understand what the reader needs." + +#### The 7 Principles of Reader Expectations + +**Principle 1: Subject-Verb Proximity** + +Keep grammatical subject and verb close together. Anything intervening reads as interruption of lesser importance. + +**Weak**: "The model, which was trained on 100M tokens and fine-tuned on domain-specific data using LoRA with rank 16, achieves state-of-the-art results" + +**Strong**: "The model achieves state-of-the-art results after training on 100M tokens and fine-tuning with LoRA (rank 16)" + +**Principle 2: Stress Position (Save the Best for Last)** + +Readers naturally emphasize the **last words of a sentence**. Place your most important information there. + +**Weak**: "Accuracy improves by 15% when using attention" +**Strong**: "When using attention, accuracy improves by **15%**" + +**Principle 3: Topic Position (First Things First)** + +The beginning of a sentence establishes perspective. Put the "whose story" element first—readers expect the sentence to be about whoever shows up first. + +**Weak**: "A novel attention mechanism that computes alignment scores is introduced" +**Strong**: "To address the alignment problem, we introduce a novel attention mechanism" + +**Principle 4: Old Information Before New** + +Put familiar information (old) in the topic position for backward linkage; put new information in the stress position for emphasis. + +**Weak**: "Sparse attention was introduced by Child et al. The quadratic complexity of standard attention motivates this work." +**Strong**: "Standard attention has quadratic complexity. To address this, Child et al. introduced sparse attention." + +**Principle 5: One Unit, One Function** + +Each unit of discourse (sentence, paragraph, section) should serve a single function. If you have two points, use two units. + +**Principle 6: Articulate Action in the Verb** + +Express the action of each sentence in its verb, not in nominalized nouns. + +**Weak**: "We performed an analysis of the results" (nominalization) +**Strong**: "We analyzed the results" (action in verb) + +**Principle 7: Context Before New Information** + +Provide context before asking the reader to consider anything new. This applies at all levels—sentence, paragraph, section. + +**Weak**: "Equation 3 shows that convergence is guaranteed when the learning rate satisfies..." +**Strong**: "For convergence to be guaranteed, the learning rate must satisfy the condition in Equation 3..." + +#### Summary Table + +| Principle | Rule | Mnemonic | +|-----------|------|----------| +| Subject-Verb Proximity | Keep subject and verb close | "Don't interrupt yourself" | +| Stress Position | Emphasis at sentence end | "Save the best for last" | +| Topic Position | Context at sentence start | "First things first" | +| Old Before New | Familiar → unfamiliar | "Build on known ground" | +| One Unit, One Function | Each paragraph = one point | "One idea per container" | +| Action in Verb | Use verbs, not nominalizations | "Verbs do, nouns sit" | +| Context Before New | Explain before presenting | "Set the stage first" | + +--- + +--- + +## Micro-Level Writing Tips + +### From Ethan Perez (Anthropic) + +These practical micro-level tips improve clarity at the sentence and word level. + +#### Pronoun Management + +**Minimize pronouns** ("this," "it," "these," "that"). When pronouns are necessary, use them as adjectives with a noun: + +**Weak**: "This shows that the model converges." +**Strong**: "This result shows that the model converges." + +**Weak**: "It improves performance." +**Strong**: "This modification improves performance." + +#### Verb Placement + +**Position verbs early** in sentences for better parsing: + +**Weak**: "The gradient, after being computed and normalized, updates the weights." +**Strong**: "The gradient updates the weights after being computed and normalized." + +#### Apostrophe Unfolding + +Transform possessive constructions for clarity: + +**Original**: "X's Y" → **Unfolded**: "The Y of X" + +**Before**: "The model's accuracy on the test set" +**After**: "The accuracy of the model on the test set" + +This isn't always better, but when sentences feel awkward, try unfolding. + +#### Words to Eliminate + +Delete these filler words in almost all cases: +- "actually" +- "a bit" +- "fortunately" / "unfortunately" +- "very" / "really" +- "quite" +- "basically" +- "essentially" +- Excessive connectives ("however," "moreover," "furthermore" when not needed) + +#### Sentence Construction Rules + +1. **One idea per sentence** - If struggling to express an idea in one sentence, it needs two +2. **No repeated sounds** - Avoid similar-sounding words in the same sentence +3. **Every sentence adds information** - Delete sentences that merely restate +4. **Active voice always** - Specify the actor ("We find..." not "It is found...") +5. **Expand contractions** - "don't" → "do not" for formality + +#### Paragraph Architecture + +- **First sentence**: State the point clearly +- **Middle sentences**: Support with evidence +- **Last sentence**: Reinforce or transition + +Don't bury key information in the middle of paragraphs. + +--- + +## Word Choice and Precision + +### From Zachary Lipton + +**Eliminate hedging** unless genuine uncertainty exists: +- Delete "may" and "can" unless necessary +- "provides *very* tight approximation" drips with insecurity +- "provides tight approximation" is confident + +**Avoid vacuous intensifiers**: +- Delete: very, extremely, highly, significantly (unless statistical) +- These words signal insecurity, not strength + +### From Jacob Steinhardt + +**Precision over brevity**: Replace vague terms with specific ones. + +| Vague | Specific | +|-------|----------| +| performance | accuracy, latency, throughput | +| improves | increases accuracy by X%, reduces latency by Y | +| large | 1B parameters, 100M tokens | +| fast | 3x faster, 50ms latency | +| good results | 92% accuracy, 0.85 F1 | + +**Consistent terminology**: Referring to the same concept with different terms creates confusion. + +**Choose one and stick with it**: +- "model" vs "network" vs "architecture" +- "training" vs "learning" vs "optimization" +- "sample" vs "example" vs "instance" + +### Vocabulary Signaling + +**Avoid words signaling incremental work**: +- Never: "combine," "modify," "expand," "extend" +- Instead: "develop," "propose," "introduce" + +**Why**: "We combine X and Y" sounds like you stapled two existing ideas together. "We develop a method that leverages X for Y" sounds like genuine contribution. + +--- + +## Mathematical Writing + +### From Ethan Perez + +**Unfold apostrophes** for clarity: +- Weak: "X's Y" +- Strong: "The Y of X" + +Example: "the model's accuracy" → "the accuracy of the model" + +### General Principles + +1. **State all assumptions formally** before theorems +2. **Provide intuitive explanations** alongside proofs +3. **Use consistent notation** throughout the paper +4. **Define symbols at first use** + +### Notation Conventions + +```latex +% Scalars: lowercase italic +$x$, $y$, $\alpha$, $\beta$ + +% Vectors: lowercase bold +$\mathbf{x}$, $\mathbf{v}$ + +% Matrices: uppercase bold +$\mathbf{W}$, $\mathbf{X}$ + +% Sets: uppercase calligraphic +$\mathcal{X}$, $\mathcal{D}$ + +% Functions: roman for named functions +$\mathrm{softmax}$, $\mathrm{ReLU}$ +``` + +--- + +## Figure Design + +### From Neel Nanda + +Figures should tell a coherent story even if the reader skips the text. Many readers DO skip the text initially. + +### Design Principles + +1. **Figure 1 is crucial**: Often the first thing readers examine after abstract +2. **Self-contained captions**: Reader should understand figure without main text +3. **No title inside figure**: The caption serves this function (ICML/NeurIPS rule) +4. **Vector graphics**: PDF/EPS for plots, PNG (600 DPI) only for photographs + +### Accessibility Requirements + +8% of men have color vision deficiency. Your figures must work for them. + +**Solutions**: +- Use colorblind-safe palettes: Okabe-Ito or Paul Tol +- Avoid red-green combinations +- Verify figures work in grayscale +- Use different line styles (solid, dashed, dotted) in addition to colors + +### Tools + +```python +# SciencePlots: Publication-ready styles +import matplotlib.pyplot as plt +plt.style.use(['science', 'ieee']) + +# Or for Nature-style +plt.style.use(['science', 'nature']) +``` + +--- + +## Common Mistakes to Avoid + +### Structure Mistakes + +| Mistake | Solution | +|---------|----------| +| Introduction too long (>1.5 pages) | Move background to Related Work | +| Methods buried (after page 3) | Front-load contribution, cut intro | +| Missing contribution bullets | Add 2-4 specific, falsifiable claims | +| Experiments without explicit claims | State what each experiment tests | + +### Writing Mistakes + +| Mistake | Solution | +|---------|----------| +| Generic abstract opening | Start with your specific contribution | +| Inconsistent terminology | Choose one term per concept | +| Passive voice overuse | Use active voice: "We show" not "It is shown" | +| Hedging everywhere | Be confident unless genuinely uncertain | + +### Figure Mistakes + +| Mistake | Solution | +|---------|----------| +| Raster graphics for plots | Use vector (PDF/EPS) | +| Red-green color scheme | Use colorblind-safe palette | +| Title inside figure | Put title in caption | +| Captions require main text | Make captions self-contained | + +### Citation Mistakes + +| Mistake | Solution | +|---------|----------| +| Paper-by-paper Related Work | Organize methodologically | +| Missing relevant citations | Reviewers authored papers—cite generously | +| AI-generated citations | Always verify via APIs | +| Inconsistent citation format | Use BibLaTeX with consistent keys | + +--- + +## Pre-Submission Checklist + +Before submitting, verify: + +**Narrative**: +- [ ] Can state contribution in one sentence +- [ ] Three pillars (What/Why/So What) clear in intro +- [ ] Every experiment supports a specific claim + +**Structure**: +- [ ] Abstract follows 5-sentence formula +- [ ] Introduction ≤1.5 pages +- [ ] Methods start by page 2-3 +- [ ] 2-4 contribution bullets included +- [ ] Limitations section present + +**Writing**: +- [ ] Consistent terminology throughout +- [ ] No generic opening sentences +- [ ] Hedging removed unless necessary +- [ ] All figures have self-contained captions + +**Technical**: +- [ ] All citations verified via API +- [ ] Error bars included with methodology +- [ ] Compute resources documented +- [ ] Code/data availability stated diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/README.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/README.md new file mode 100644 index 0000000..0633b73 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/README.md @@ -0,0 +1,251 @@ +# LaTeX Templates for ML/AI Conferences + +This directory contains official LaTeX templates for major machine learning and AI conferences. + +--- + +## Compiling LaTeX to PDF + +### Option 1: VS Code with LaTeX Workshop (Recommended) + +**Setup:** +1. Install [TeX Live](https://www.tug.org/texlive/) (full distribution recommended) + - macOS: `brew install --cask mactex` + - Ubuntu: `sudo apt install texlive-full` + - Windows: Download from [tug.org/texlive](https://www.tug.org/texlive/) + +2. Install VS Code extension: **LaTeX Workshop** by James Yu + - Open VS Code → Extensions (Cmd/Ctrl+Shift+X) → Search "LaTeX Workshop" → Install + +**Usage:** +- Open any `.tex` file in VS Code +- Save the file (Cmd/Ctrl+S) → Auto-compiles to PDF +- Click the green play button or use `Cmd/Ctrl+Alt+B` to build +- View PDF: Click "View LaTeX PDF" icon or `Cmd/Ctrl+Alt+V` +- Side-by-side view: `Cmd/Ctrl+Alt+V` then drag tab + +**Settings** (add to VS Code `settings.json`): +```json +{ + "latex-workshop.latex.autoBuild.run": "onSave", + "latex-workshop.view.pdf.viewer": "tab", + "latex-workshop.latex.recipes": [ + { + "name": "pdflatex → bibtex → pdflatex × 2", + "tools": ["pdflatex", "bibtex", "pdflatex", "pdflatex"] + } + ] +} +``` + +### Option 2: Command Line + +```bash +# Basic compilation +pdflatex main.tex + +# With bibliography (full workflow) +pdflatex main.tex +bibtex main +pdflatex main.tex +pdflatex main.tex + +# Using latexmk (handles dependencies automatically) +latexmk -pdf main.tex + +# Continuous compilation (watches for changes) +latexmk -pdf -pvc main.tex +``` + +### Option 3: Overleaf (Online) + +1. Go to [overleaf.com](https://www.overleaf.com) +2. New Project → Upload Project → Upload the template folder as ZIP +3. Edit online with real-time PDF preview +4. No local installation needed + +### Option 4: Other IDEs + +| IDE | Extension/Plugin | Notes | +|-----|------------------|-------| +| **Cursor** | LaTeX Workshop | Same as VS Code | +| **Sublime Text** | LaTeXTools | Popular, well-maintained | +| **Vim/Neovim** | VimTeX | Powerful, keyboard-driven | +| **Emacs** | AUCTeX | Comprehensive LaTeX environment | +| **TeXstudio** | Built-in | Dedicated LaTeX IDE | +| **Texmaker** | Built-in | Cross-platform LaTeX editor | + +### Troubleshooting Compilation + +**"File not found" errors:** +```bash +# Ensure you're in the template directory +cd templates/icml2026 +pdflatex example_paper.tex +``` + +**Bibliography not appearing:** +```bash +# Run bibtex after first pdflatex +pdflatex main.tex +bibtex main # Uses main.aux to find citations +pdflatex main.tex # Incorporates bibliography +pdflatex main.tex # Resolves references +``` + +**Missing packages:** +```bash +# TeX Live package manager +tlmgr install <package-name> + +# Or install full distribution to avoid this +``` + +--- + +## Available Templates + +| Conference | Directory | Year | Source | +|------------|-----------|------|--------| +| ICML | `icml2026/` | 2026 | [Official ICML](https://icml.cc/Conferences/2026/AuthorInstructions) | +| ICLR | `iclr2026/` | 2026 | [Official GitHub](https://github.com/ICLR/Master-Template) | +| NeurIPS | `neurips2025/` | 2025 | Community template | +| ACL | `acl/` | 2025+ | [Official ACL](https://github.com/acl-org/acl-style-files) | +| AAAI | `aaai2026/` | 2026 | [AAAI Author Kit](https://aaai.org/authorkit26/) | +| COLM | `colm2025/` | 2025 | [Official COLM](https://github.com/COLM-org/Template) | + +## Usage + +### ICML 2026 + +```latex +\documentclass{article} +\usepackage{icml2026} % For submission +% \usepackage[accepted]{icml2026} % For camera-ready + +\begin{document} +% Your paper content +\end{document} +``` + +Key files: +- `icml2026.sty` - Style file +- `icml2026.bst` - Bibliography style +- `example_paper.tex` - Example document + +### ICLR 2026 + +```latex +\documentclass{article} +\usepackage[submission]{iclr2026_conference} % For submission +% \usepackage[final]{iclr2026_conference} % For camera-ready + +\begin{document} +% Your paper content +\end{document} +``` + +Key files: +- `iclr2026_conference.sty` - Style file +- `iclr2026_conference.bst` - Bibliography style +- `iclr2026_conference.tex` - Example document + +### ACL Venues (ACL, EMNLP, NAACL) + +```latex +\documentclass[11pt]{article} +\usepackage[review]{acl} % For review +% \usepackage{acl} % For camera-ready + +\begin{document} +% Your paper content +\end{document} +``` + +Key files: +- `acl.sty` - Style file +- `acl_natbib.bst` - Bibliography style +- `acl_latex.tex` - Example document + +### AAAI 2026 + +```latex +\documentclass[letterpaper]{article} +\usepackage[submission]{aaai2026} % For submission +% \usepackage{aaai2026} % For camera-ready + +\begin{document} +% Your paper content +\end{document} +``` + +Key files: +- `aaai2026.sty` - Style file +- `aaai2026.bst` - Bibliography style + +### COLM 2025 + +```latex +\documentclass{article} +\usepackage[submission]{colm2025_conference} % For submission +% \usepackage[final]{colm2025_conference} % For camera-ready + +\begin{document} +% Your paper content +\end{document} +``` + +Key files: +- `colm2025_conference.sty` - Style file +- `colm2025_conference.bst` - Bibliography style + +## Page Limits Summary + +| Conference | Submission | Camera-Ready | Notes | +|------------|-----------|--------------|-------| +| ICML 2026 | 8 pages | 9 pages | +unlimited refs/appendix | +| ICLR 2026 | 9 pages | 10 pages | +unlimited refs/appendix | +| NeurIPS 2025 | 9 pages | 9 pages | +checklist outside limit | +| ACL 2025 | 8 pages (long) | varies | +unlimited refs/appendix | +| AAAI 2026 | 7 pages | 8 pages | +unlimited refs/appendix | +| COLM 2025 | 9 pages | 10 pages | +unlimited refs/appendix | + +## Common Issues + +### Compilation Errors + +1. **Missing packages**: Install full TeX distribution (TeX Live Full or MikTeX) +2. **Bibliography errors**: Use the provided `.bst` file with `\bibliographystyle{}` +3. **Font warnings**: Install `cm-super` or use `\usepackage{lmodern}` + +### Anonymization + +For submission, ensure: +- No author names in `\author{}` +- No acknowledgments section +- No grant numbers +- Use anonymous repositories +- Cite own work in third person + +### Common LaTeX Packages + +```latex +% Recommended packages (check compatibility with venue style) +\usepackage{amsmath,amsthm,amssymb} % Math +\usepackage{graphicx} % Figures +\usepackage{booktabs} % Tables +\usepackage{hyperref} % Links +\usepackage{algorithm,algorithmic} % Algorithms +\usepackage{natbib} % Citations +``` + +## Updating Templates + +Templates are updated annually. Check official sources before each submission: + +- ICML: https://icml.cc/ +- ICLR: https://iclr.cc/ +- NeurIPS: https://neurips.cc/ +- ACL: https://github.com/acl-org/acl-style-files +- AAAI: https://aaai.org/ +- COLM: https://colmweb.org/ diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/README.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/README.md new file mode 100644 index 0000000..401ff3e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/README.md @@ -0,0 +1,534 @@ +# AAAI 2026 统一LaTeX模板使用说明 / AAAI 2026 Unified LaTeX Template Guide + +> **📝 重要说明 / Important Notice**: 本仓库借助Cursor在AAAI 2026官方模板基础上改进得到。如果遇到不满足或有冲突的情况，请积极提issues。 +> +> **📝 Important Notice**: This repository is improved based on the official AAAI 2026 template with the assistance of Cursor. If you encounter any issues or conflicts, please actively submit issues. + +[中文](#中文版本) | [English](#english-version) + +--- + +## 🌐 在线查看 / Online Access + +**📖 在线阅读和测试模板**: [https://cn.overleaf.com/read/wyhcnvcrtpyt#cd4a07](https://cn.overleaf.com/read/wyhcnvcrtpyt#cd4a07) + +**📖 Online View and Test Template**: [https://cn.overleaf.com/read/wyhcnvcrtpyt#cd4a07](https://cn.overleaf.com/read/wyhcnvcrtpyt#cd4a07) + +💡 **提示 / Tips**: +- 中文：您可以通过上述链接在Overleaf中直接查看、编辑和编译模板，无需本地安装LaTeX环境 +- English: You can view, edit, and compile the template directly in Overleaf using the link above, without needing a local LaTeX installation + +--- + +## 中文版本 + +### 概述 ✅ + +我已经将AAAI 2026的两个版本（匿名投稿版本和camera-ready版本）**完整合并**成一个统一的模板文件 `aaai2026-unified-template.tex`。 + +该模板包含了原始两个模板的**所有完整内容**（共886行，比原始文件更全面），包括： +- 所有格式化说明和要求 +- 完整的示例代码和表格 +- 图片处理指南 +- 参考文献格式要求 +- 所有章节和附录内容 +- 版本特定的Acknowledgments部分 + +### 主要差异分析 + +通过比较原始的两个模板，我发现主要差异在于： + +#### 1. 包的加载方式 +- **匿名版本**: `\usepackage[submission]{aaai2026}` +- **Camera-ready版本**: `\usepackage{aaai2026}` + +#### 2. 标题差异 +- **匿名版本**: "AAAI Press Anonymous Submission Instructions for Authors Using LaTeX" +- **Camera-ready版本**: "AAAI Press Formatting Instructions for Authors Using LaTeX --- A Guide" + +#### 3. Links环境的处理 +- **匿名版本**: Links环境被注释掉，防止泄露作者身份 +- **Camera-ready版本**: Links环境正常显示 + +#### 4. 内容部分差异 +- **匿名版本**: 包含"Preparing an Anonymous Submission"部分的特殊说明 +- **Camera-ready版本**: 包含完整的格式说明和版权信息 + +### 依赖文件检查结果 + +✅ **已验证并复制到主目录的文件**： + +- `aaai2026.sty` - AAAI 2026 样式文件（两个版本完全相同） +- `aaai2026.bst` - 参考文献样式文件（两个版本完全相同） +- `aaai2026.bib` - 示例参考文献文件 +- `figure1.pdf` 和 `figure2.pdf` - 示例图片文件 + +所有这些文件在两个版本中都是相同的，因此统一模板可以正常工作。 + +### 如何使用统一模板 + +#### 切换到匿名投稿版本 +在模板文件第11行，**取消注释**这一行： +```latex +\def\aaaianonymous{true} +``` + +#### 切换到Camera-ready版本 +在模板文件第11行，**注释掉**或**删除**这一行： +```latex +% \def\aaaianonymous{true} +``` + +### 一键切换的核心机制 + +统一模板使用了LaTeX的条件编译功能： + +```latex +% 条件包加载 +\ifdefined\aaaianonymous + \usepackage[submission]{aaai2026} % 匿名版本 +\else + \usepackage{aaai2026} % Camera-ready版本 +\fi + +% 条件标题设置 +\ifdefined\aaaianonymous + \title{AAAI Press Anonymous Submission\\Instructions for Authors Using \LaTeX{}} +\else + \title{AAAI Press Formatting Instructions \\for Authors Using \LaTeX{} --- A Guide} +\fi + +% 条件内容显示 +\ifdefined\aaaianonymous + % 匿名版本特有内容 +\else + % Camera-ready版本特有内容 +\fi +``` + +### 文件清单 + +主目录现在包含以下文件： + +- `aaai2026-unified-template.tex` - 统一主论文模板文件 +- `aaai2026-unified-supp.tex` - 统一补充材料模板文件 +- `aaai2026.sty` - AAAI 2026 LaTeX 样式文件 +- `aaai2026.bst` - 参考文献样式文件 +- `aaai2026.bib` - 示例参考文献文件 +- `figure1.pdf` - 示例图片1 +- `figure2.pdf` - 示例图片2 +- `README.md` - 本说明文档 + +### 补充材料模板 (Supplementary Material Template) + +#### 概述 +`aaai2026-unified-supp.tex` 是专门为AAAI 2026补充材料设计的统一模板，与主论文模板使用相同的版本切换机制。 + +#### 主要功能 +- **版本切换**: 通过修改一行代码在匿名投稿和camera-ready版本间切换 +- **补充内容支持**: 支持额外的实验、推导、数据、图表、算法等 +- **格式一致性**: 与主论文模板保持完全一致的格式要求 +- **代码示例**: 包含算法、代码列表等补充材料的示例 + +#### 使用方法 +与主论文模板相同，只需修改第11行： +```latex +% 匿名投稿版本 +\def\aaaianonymous{true} + +% Camera-ready版本 +% \def\aaaianonymous{true} +``` + +#### 补充材料内容建议 +- 额外的实验结果和消融研究 +- 详细的数学推导和证明 +- 更多的图表和可视化 +- 算法伪代码和实现细节 +- 数据集描述和预处理步骤 +- 超参数设置和实验配置 +- 失败案例分析 +- 计算复杂度分析 + +### 使用检查清单 (Usage Checklist) + +#### 📋 投稿前检查清单 (Pre-Submission Checklist) + +**版本设置**: +- [ ] 已设置 `\def\aaaianonymous{true}` (匿名投稿) +- [ ] 已注释掉所有可能暴露身份的信息 +- [ ] 已匿名化参考文献（移除作者姓名） + +**内容完整性**: +- [ ] 标题、摘要、关键词已填写 +- [ ] 所有章节内容完整 +- [ ] 图表编号连续且正确 +- [ ] 参考文献格式正确 +- [ ] 补充材料（如有）已准备 + +**格式检查**: +- [ ] 页面边距符合要求 +- [ ] 字体和字号正确 +- [ ] 行间距符合标准 +- [ ] 图表位置和大小合适 +- [ ] 数学公式格式正确 + +**技术检查**: +- [ ] LaTeX编译无错误 +- [ ] 参考文献正确生成 +- [ ] PDF输出正常 +- [ ] 文件大小在限制范围内 + +#### 📋 录用后检查清单 (Post-Acceptance Checklist) + +**版本切换**: +- [ ] 已注释掉 `\def\aaaianonymous{true}` (camera-ready) +- [ ] 已添加完整的作者信息 +- [ ] 已添加所有作者单位信息 +- [ ] 已恢复所有被注释的内容 + +**内容更新**: +- [ ] 已根据审稿意见修改内容 +- [ ] 已更新所有图表和实验 +- [ ] 已完善补充材料 +- [ ] 已检查所有链接和引用 + +**最终检查**: +- [ ] 最终PDF质量检查 +- [ ] 所有文件已备份 +- [ ] 符合会议最终提交要求 +- [ ] 补充材料已单独提交（如需要） + +#### 📋 补充材料检查清单 (Supplementary Material Checklist) + +**内容组织**: +- [ ] 补充材料与主论文内容对应 +- [ ] 章节结构清晰合理 +- [ ] 图表编号与主论文不冲突 +- [ ] 参考文献格式一致 + +**技术细节**: +- [ ] 算法伪代码清晰完整 +- [ ] 实验设置详细说明 +- [ ] 数据预处理步骤明确 +- [ ] 超参数配置完整 + +**格式要求**: +- [ ] 使用统一的supp模板 +- [ ] 页面设置与主论文一致 +- [ ] 字体和格式符合要求 +- [ ] 文件大小在限制范围内 + +### 实际使用建议 + +1. **投稿阶段**: + - 取消注释 `\def\aaaianonymous{true}` + - 确保不包含任何可能暴露身份的信息 + - 检查参考文献是否已匿名化 + +2. **录用后准备final版本**: + - 注释掉或删除 `\def\aaaianonymous{true}` 这一行 + - 添加完整的作者信息和affiliations + - 取消注释links环境（如果需要） + +3. **编译测试**: + - 分别在两种模式下编译，确保都能正常工作 + - 检查输出的PDF是否符合要求 + - 验证参考文献格式是否正确 + +4. **依赖文件确认**: + - 确保所有依赖文件都在同一目录下 + - 如果移动模板文件，记得同时移动依赖文件 + +### 重要注意事项 + +⚠️ **关于Bibliography Style**: +- `aaai2026.sty`文件已经自动设置了`\bibliographystyle{aaai2026}` +- **不要**在文档中再次添加`\bibliographystyle{aaai2026}`命令 +- 否则会出现"`Illegal, another \bibstyle command`"错误 +- 只需要使用`\bibliography{aaai2026}`命令即可 + +### 编译命令示例 + +```bash +# 编译LaTeX文档 +pdflatex aaai2026-unified-template.tex +bibtex aaai2026-unified-template +pdflatex aaai2026-unified-template.tex +pdflatex aaai2026-unified-template.tex +``` + +### 常见问题解决 + +#### 1. "Illegal, another \bibstyle command"错误 +**原因**: 重复设置了bibliography style +**解决方案**: 删除文档中的`\bibliographystyle{aaai2026}`命令，`aaai2026.sty`会自动处理 + +#### 2. 参考文献格式不正确 +**原因**: 可能缺少natbib包或者BibTeX文件问题 +**解决方案**: 确保按照标准的LaTeX编译流程：pdflatex → bibtex → pdflatex → pdflatex + +--- + +## English Version + +### Overview ✅ + +I have **completely merged** the two AAAI 2026 versions (anonymous submission and camera-ready) into a single unified template file `aaai2026-unified-template.tex`. + +This template contains **all complete content** from both original templates (886 lines total, more comprehensive than the original files), including: +- All formatting instructions and requirements +- Complete example codes and tables +- Image processing guidelines +- Reference formatting requirements +- All sections and appendix content +- Version-specific Acknowledgments sections + +### Key Differences Analysis + +By comparing the two original templates, the main differences are: + +#### 1. Package Loading Method +- **Anonymous version**: `\usepackage[submission]{aaai2026}` +- **Camera-ready version**: `\usepackage{aaai2026}` + +#### 2. Title Differences +- **Anonymous version**: "AAAI Press Anonymous Submission Instructions for Authors Using LaTeX" +- **Camera-ready version**: "AAAI Press Formatting Instructions for Authors Using LaTeX --- A Guide" + +#### 3. Links Environment Handling +- **Anonymous version**: Links environment commented out to prevent identity disclosure +- **Camera-ready version**: Links environment displayed normally + +#### 4. Content Section Differences +- **Anonymous version**: Contains special instructions in "Preparing an Anonymous Submission" section +- **Camera-ready version**: Contains complete formatting instructions and copyright information + +### Dependency Files Verification + +✅ **Files verified and copied to main directory**: + +- `aaai2026.sty` - AAAI 2026 style file (identical in both versions) +- `aaai2026.bst` - Bibliography style file (identical in both versions) +- `aaai2026.bib` - Sample bibliography file +- `figure1.pdf` and `figure2.pdf` - Sample image files + +All these files are identical in both versions, so the unified template works properly. + +### How to Use the Unified Template + +#### Switch to Anonymous Submission Version +On line 11 of the template file, **uncomment** this line: +```latex +\def\aaaianonymous{true} +``` + +#### Switch to Camera-ready Version +On line 11 of the template file, **comment out** or **delete** this line: +```latex +% \def\aaaianonymous{true} +``` + +### Core Mechanism of One-Click Switching + +The unified template uses LaTeX conditional compilation: + +```latex +% Conditional package loading +\ifdefined\aaaianonymous + \usepackage[submission]{aaai2026} % Anonymous version +\else + \usepackage{aaai2026} % Camera-ready version +\fi + +% Conditional title setting +\ifdefined\aaaianonymous + \title{AAAI Press Anonymous Submission\\Instructions for Authors Using \LaTeX{}} +\else + \title{AAAI Press Formatting Instructions \\for Authors Using \LaTeX{} --- A Guide} +\fi + +% Conditional content display +\ifdefined\aaaianonymous + % Anonymous version specific content +\else + % Camera-ready version specific content +\fi +``` + +### File List + +The main directory now contains the following files: + +- `aaai2026-unified-template.tex` - Unified main paper template file +- `aaai2026-unified-supp.tex` - Unified supplementary material template file +- `aaai2026.sty` - AAAI 2026 LaTeX style file +- `aaai2026.bst` - Bibliography style file +- `aaai2026.bib` - Sample bibliography file +- `figure1.pdf` - Sample image 1 +- `figure2.pdf` - Sample image 2 +- `README.md` - This documentation + +### Supplementary Material Template + +#### Overview +`aaai2026-unified-supp.tex` is a unified template specifically designed for AAAI 2026 supplementary materials, using the same version switching mechanism as the main paper template. + +#### Key Features +- **Version Switching**: Switch between anonymous submission and camera-ready versions by modifying one line of code +- **Supplementary Content Support**: Supports additional experiments, derivations, data, figures, algorithms, etc. +- **Format Consistency**: Maintains complete format consistency with the main paper template +- **Code Examples**: Includes examples for algorithms, code listings, and other supplementary materials + +#### Usage +Same as the main paper template, just modify line 11: +```latex +% Anonymous submission version +\def\aaaianonymous{true} + +% Camera-ready version +% \def\aaaianonymous{true} +``` + +#### Supplementary Material Content Suggestions +- Additional experimental results and ablation studies +- Detailed mathematical derivations and proofs +- More figures and visualizations +- Algorithm pseudocode and implementation details +- Dataset descriptions and preprocessing steps +- Hyperparameter settings and experimental configurations +- Failure case analysis +- Computational complexity analysis + +### Usage Checklist + +#### 📋 Pre-Submission Checklist + +**Version Setup**: +- [ ] Set `\def\aaaianonymous{true}` (anonymous submission) +- [ ] Commented out all information that could reveal identity +- [ ] Anonymized references (removed author names) + +**Content Completeness**: +- [ ] Title, abstract, and keywords filled +- [ ] All sections complete +- [ ] Figure and table numbers consecutive and correct +- [ ] Reference format correct +- [ ] Supplementary materials prepared (if any) + +**Format Check**: +- [ ] Page margins meet requirements +- [ ] Font and font size correct +- [ ] Line spacing meets standards +- [ ] Figure and table positions and sizes appropriate +- [ ] Mathematical formula format correct + +**Technical Check**: +- [ ] LaTeX compilation error-free +- [ ] References generated correctly +- [ ] PDF output normal +- [ ] File size within limits + +#### 📋 Post-Acceptance Checklist + +**Version Switch**: +- [ ] Commented out `\def\aaaianonymous{true}` (camera-ready) +- [ ] Added complete author information +- [ ] Added all author affiliation information +- [ ] Restored all commented content + +**Content Updates**: +- [ ] Modified content according to reviewer comments +- [ ] Updated all figures and experiments +- [ ] Completed supplementary materials +- [ ] Checked all links and citations + +**Final Check**: +- [ ] Final PDF quality check +- [ ] All files backed up +- [ ] Meets conference final submission requirements +- [ ] Supplementary materials submitted separately (if needed) + +#### 📋 Supplementary Material Checklist + +**Content Organization**: +- [ ] Supplementary materials correspond to main paper content +- [ ] Chapter structure clear and reasonable +- [ ] Figure and table numbers don't conflict with main paper +- [ ] Reference format consistent + +**Technical Details**: +- [ ] Algorithm pseudocode clear and complete +- [ ] Experimental setup explained in detail +- [ ] Data preprocessing steps clear +- [ ] Hyperparameter configuration complete + +**Format Requirements**: +- [ ] Using unified supp template +- [ ] Page settings consistent with main paper +- [ ] Font and format meet requirements +- [ ] File size within limits + +### Practical Usage Recommendations + +1. **Submission Stage**: + - Uncomment `\def\aaaianonymous{true}` + - Ensure no information that could reveal identity is included + - Check that references are anonymized + +2. **Preparing final version after acceptance**: + - Comment out or delete the `\def\aaaianonymous{true}` line + - Add complete author information and affiliations + - Uncomment links environment (if needed) + +3. **Compilation Testing**: + - Compile in both modes to ensure proper functionality + - Check if the output PDF meets requirements + - Verify reference formatting is correct + +4. **Dependency File Confirmation**: + - Ensure all dependency files are in the same directory + - Remember to move dependency files when moving the template file + +### Important Notes + +⚠️ **About Bibliography Style**: +- The `aaai2026.sty` file automatically sets `\bibliographystyle{aaai2026}` +- **Do NOT** add `\bibliographystyle{aaai2026}` command again in your document +- Otherwise you'll get "`Illegal, another \bibstyle command`" error +- Just use the `\bibliography{aaai2026}` command + +### Compilation Commands Example + +```bash +# Compile LaTeX document +pdflatex aaai2026-unified-template.tex +bibtex aaai2026-unified-template +pdflatex aaai2026-unified-template.tex +pdflatex aaai2026-unified-template.tex +``` + +### Common Issues and Solutions + +#### 1. "Illegal, another \bibstyle command" Error +**Cause**: Duplicate bibliography style setting +**Solution**: Remove the `\bibliographystyle{aaai2026}` command from your document, `aaai2026.sty` handles it automatically + +#### 2. Incorrect Reference Format +**Cause**: Missing natbib package or BibTeX file issues +**Solution**: Follow the standard LaTeX compilation process: pdflatex → bibtex → pdflatex → pdflatex + +--- + +## 版本信息 / Version Information + +- **模板版本 / Template Version**: AAAI 2026 Unified (Main + Supplementary) +- **创建日期 / Created**: 2024年12月 +- **支持格式 / Supported Formats**: Anonymous Submission & Camera-Ready +- **模板类型 / Template Types**: Main Paper Template & Supplementary Material Template +- **兼容性 / Compatibility**: LaTeX 2020+ / TeXLive 2024+ + +--- + +🎉 **现在您只需要修改一行代码就可以在两个版本之间切换，同时所有必要的依赖文件都已经准备就绪！** +🎉 **Now you only need to modify one line of code to switch between the two versions, with all necessary dependency files ready to use!** \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026-unified-supp.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026-unified-supp.tex new file mode 100644 index 0000000..e59d365 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026-unified-supp.tex @@ -0,0 +1,144 @@ +%File: aaai2026-unified-supp.tex +% +% UNIFIED AAAI 2026 SUPPLEMENTARY MATERIAL TEMPLATE +% To switch between anonymous submission and camera-ready versions, +% simply change the next line: +% +% For ANONYMOUS SUBMISSION: uncomment the next line +% \def\aaaianonymous{true} +% +% For CAMERA-READY VERSION: comment out or delete the next line +% \def\aaaianonymous{true} +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +\documentclass[letterpaper]{article} % DO NOT CHANGE THIS + +% Conditional package loading based on version +\ifdefined\aaaianonymous + \usepackage[submission]{aaai2026} % Anonymous submission version +\else + \usepackage{aaai2026} % Camera-ready version +\fi + +\usepackage{times} % DO NOT CHANGE THIS +\usepackage{helvet} % DO NOT CHANGE THIS +\usepackage{courier} % DO NOT CHANGE THIS +\usepackage[hyphens]{url} % DO NOT CHANGE THIS +\usepackage{graphicx} % DO NOT CHANGE THIS +\urlstyle{rm} % DO NOT CHANGE THIS +\def\UrlFont{\rm} % DO NOT CHANGE THIS +\usepackage{natbib} % DO NOT CHANGE THIS AND DO NOT ADD ANY OPTIONS TO IT +\usepackage{caption} % DO NOT CHANGE THIS AND DO NOT ADD ANY OPTIONS TO IT +\frenchspacing % DO NOT CHANGE THIS +\setlength{\pdfpagewidth}{8.5in} % DO NOT CHANGE THIS +\setlength{\pdfpageheight}{11in} % DO NOT CHANGE THIS + +% These are recommended to typeset algorithms but not required. +\usepackage{algorithm} +\usepackage{algorithmic} + +% These are recommended to typeset listings but not required. +\usepackage{newfloat} +\usepackage{listings} +\DeclareCaptionStyle{ruled}{labelfont=normalfont,labelsep=colon,strut=off} % DO NOT CHANGE THIS +\lstset{% + basicstyle={\footnotesize\ttfamily}, + numbers=left,numberstyle=\footnotesize,xleftmargin=2em, + aboveskip=0pt,belowskip=0pt, + showstringspaces=false,tabsize=2,breaklines=true} +\floatstyle{ruled} +\newfloat{listing}{tb}{lst}{} +\floatname{listing}{Listing} + +\pdfinfo{ +/TemplateVersion (2026.1) +} + +\setcounter{secnumdepth}{0} %May be changed to 1 or 2 if section numbers are desired. + +% Title - conditionally set based on version +\ifdefined\aaaianonymous + \title{AAAI 2026 Supplementary Material\\Anonymous Submission} +\else + \title{AAAI 2026 Supplementary Material\\Camera Ready} +\fi + +% Author and affiliation information +\ifdefined\aaaianonymous +\author{ + Anonymous Submission +} +\affiliations{ + % Leave affiliations empty for anonymous submission +} +\else +\author{ + %Authors + Written by AAAI Press Staff\textsuperscript{\rm 1}\thanks{With help from the AAAI Publications Committee.}\\ + AAAI Style Contributions by Pater Patel Schneider, + Sunil Issar,\\ + J. Scott Penberthy, + George Ferguson, + Hans Guesgen, + Francisco Cruz\equalcontrib, + Marc Pujol-Gonzalez\equalcontrib +} +\affiliations{ + \textsuperscript{\rm 1}Association for the Advancement of Artificial Intelligence\\ + 1101 Pennsylvania Ave, NW Suite 300\\ + Washington, DC 20004 USA\\ + proceedings-questions@aaai.org +} +\fi + +\begin{document} + +\maketitle + +\begin{abstract} +This document provides supplementary material for the main paper, including additional experiments, derivations, data, figures, algorithms, and other relevant content. Please add detailed information as needed. This supplementary material is submitted together with the main paper to further support and complement the main findings. +\end{abstract} + +% ----------- Supplementary Content Starts Here ----------- + +\section{Example Supplementary Content} + +This is the main body of the supplementary material. You may add extra experimental results, ablation studies, detailed derivations, additional figures, pseudocode, dataset descriptions, etc. + +\subsection{Additional Experiments} + +% Example: Insert a figure +% Uncomment and modify the following lines to add your own figures: +% \begin{figure}[h] +% \centering +% \includegraphics[width=0.9\columnwidth]{your-figure-name} +% \caption{Your figure caption here.} +% \label{fig:supp1} +% \end{figure} + +\subsection{Detailed Derivations} + +You may provide detailed mathematical derivations, proofs, or other technical details here. + +\subsection{Pseudocode} + +\begin{algorithm}[h] +\caption{Example Supplementary Algorithm} +\begin{algorithmic}[1] +\STATE Initialize parameters +\FOR{each sample} + \STATE Compute loss + \STATE Update parameters +\ENDFOR +\STATE \textbf{return} optimal parameters +\end{algorithmic} +\end{algorithm} + +% ----------- Supplementary Content Ends Here ----------- + +% References and End of Paper +% These lines must be placed at the end of your paper +\bibliography{aaai2026} + +\end{document} \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026-unified-template.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026-unified-template.tex new file mode 100644 index 0000000..0a7612f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026-unified-template.tex @@ -0,0 +1,952 @@ +%File: aaai2026-unified-template.tex +% +% UNIFIED AAAI 2026 TEMPLATE +% To switch between anonymous submission and camera-ready versions, +% simply change the next line: +% +% For ANONYMOUS SUBMISSION: uncomment the next line +% \def\aaaianonymous{true} +% +% For CAMERA-READY VERSION: comment out or delete the next line +% \def\aaaianonymous{true} +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +\documentclass[letterpaper]{article} % DO NOT CHANGE THIS + +% Conditional package loading based on version +\ifdefined\aaaianonymous + \usepackage[submission]{aaai2026} % Anonymous submission version +\else + \usepackage{aaai2026} % Camera-ready version +\fi + +\usepackage{times} % DO NOT CHANGE THIS +\usepackage{helvet} % DO NOT CHANGE THIS +\usepackage{courier} % DO NOT CHANGE THIS +\usepackage[hyphens]{url} % DO NOT CHANGE THIS +\usepackage{graphicx} % DO NOT CHANGE THIS +\urlstyle{rm} % DO NOT CHANGE THIS +\def\UrlFont{\rm} % DO NOT CHANGE THIS +\usepackage{natbib} % DO NOT CHANGE THIS AND DO NOT ADD ANY OPTIONS TO IT +\usepackage{caption} % DO NOT CHANGE THIS AND DO NOT ADD ANY OPTIONS TO IT +\frenchspacing % DO NOT CHANGE THIS +\setlength{\pdfpagewidth}{8.5in} % DO NOT CHANGE THIS +\setlength{\pdfpageheight}{11in} % DO NOT CHANGE THIS + +% +% These are recommended to typeset algorithms but not required. See the subsubsection on algorithms. Remove them if you don't have algorithms in your paper. +\usepackage{algorithm} +\usepackage{algorithmic} + +% +% These are are recommended to typeset listings but not required. See the subsubsection on listing. Remove this block if you don't have listings in your paper. +\usepackage{newfloat} +\usepackage{listings} +\DeclareCaptionStyle{ruled}{labelfont=normalfont,labelsep=colon,strut=off} % DO NOT CHANGE THIS +\lstset{% + basicstyle={\footnotesize\ttfamily},% footnotesize acceptable for monospace + numbers=left,numberstyle=\footnotesize,xleftmargin=2em,% show line numbers, remove this entire line if you don't want the numbers. + aboveskip=0pt,belowskip=0pt,% + showstringspaces=false,tabsize=2,breaklines=true} +\floatstyle{ruled} +\newfloat{listing}{tb}{lst}{} +\floatname{listing}{Listing} + +% +% Keep the \pdfinfo as shown here. There's no need +% for you to add the /Title and /Author tags. +\pdfinfo{ +/TemplateVersion (2026.1) +} + +% DISALLOWED PACKAGES +% \usepackage{authblk} -- This package is specifically forbidden +% \usepackage{balance} -- This package is specifically forbidden +% \usepackage{color (if used in text) +% \usepackage{CJK} -- This package is specifically forbidden +% \usepackage{float} -- This package is specifically forbidden +% \usepackage{flushend} -- This package is specifically forbidden +% \usepackage{fontenc} -- This package is specifically forbidden +% \usepackage{fullpage} -- This package is specifically forbidden +% \usepackage{geometry} -- This package is specifically forbidden +% \usepackage{grffile} -- This package is specifically forbidden +% \usepackage{hyperref} -- This package is specifically forbidden +% \usepackage{navigator} -- This package is specifically forbidden +% (or any other package that embeds links such as navigator or hyperref) +% \indentfirst} -- This package is specifically forbidden +% \layout} -- This package is specifically forbidden +% \multicol} -- This package is specifically forbidden +% \nameref} -- This package is specifically forbidden +% \usepackage{savetrees} -- This package is specifically forbidden +% \usepackage{setspace} -- This package is specifically forbidden +% \usepackage{stfloats} -- This package is specifically forbidden +% \usepackage{tabu} -- This package is specifically forbidden +% \usepackage{titlesec} -- This package is specifically forbidden +% \usepackage{tocbibind} -- This package is specifically forbidden +% \usepackage{ulem} -- This package is specifically forbidden +% \usepackage{wrapfig} -- This package is specifically forbidden + +% DISALLOWED COMMANDS +% \nocopyright -- Your paper will not be published if you use this command +% \addtolength -- This command may not be used +% \balance -- This command may not be used +% \baselinestretch -- Your paper will not be published if you use this command +% \clearpage -- No page breaks of any kind may be used for the final version of your paper +% \columnsep -- This command may not be used +% \newpage -- No page breaks of any kind may be used for the final version of your paper +% \pagebreak -- No page breaks of any kind may be used for the final version of your paperr +% \pagestyle -- This command may not be used +% \tiny -- This is not an acceptable font size. +% \vspace{- -- No negative value may be used in proximity of a caption, figure, table, section, subsection, subsubsection, or reference +% \vskip{- -- No negative value may be used to alter spacing above or below a caption, figure, table, section, subsection, subsubsection, or reference + +\setcounter{secnumdepth}{0} %May be changed to 1 or 2 if section numbers are desired. + +% The file aaai2026.sty is the style file for AAAI Press +% proceedings, working notes, and technical reports. +% + +% Title - conditionally set based on version +\ifdefined\aaaianonymous + \title{AAAI Press Anonymous Submission\\Instructions for Authors Using \LaTeX{}} +\else + \title{AAAI Press Formatting Instructions \\for Authors Using \LaTeX{} --- A Guide} +\fi + +% Author and affiliation information +\author{ + %Authors + % All authors must be in the same font size and format. + Written by AAAI Press Staff\textsuperscript{\rm 1}\thanks{With help from the AAAI Publications Committee.}\\ + AAAI Style Contributions by Pater Patel Schneider, + Sunil Issar,\\ + J. Scott Penberthy, + George Ferguson, + Hans Guesgen, + Francisco Cruz\equalcontrib, + Marc Pujol-Gonzalez\equalcontrib +} +\affiliations{ + %Afiliations + \textsuperscript{\rm 1}Association for the Advancement of Artificial Intelligence\\ + % If you have multiple authors and multiple affiliations + % use superscripts in text and roman font to identify them. + % For example, + + % Sunil Issar\textsuperscript{\rm 2}, + % J. Scott Penberthy\textsuperscript{\rm 3}, + % George Ferguson\textsuperscript{\rm 4}, + % Hans Guesgen\textsuperscript{\rm 5} + % Note that the comma should be placed after the superscript + + 1101 Pennsylvania Ave, NW Suite 300\\ + Washington, DC 20004 USA\\ + % email address must be in roman text type, not monospace or sans serif + proceedings-questions@aaai.org +% +% See more examples next +} + +%Example, Single Author, ->> remove \iffalse,\fi and place them surrounding AAAI title to use it +\iffalse +\title{My Publication Title --- Single Author} +\author { + Author Name +} +\affiliations{ + Affiliation\\ + Affiliation Line 2\\ + name@example.com +} +\fi + +\iffalse +%Example, Multiple Authors, ->> remove \iffalse,\fi and place them surrounding AAAI title to use it +\title{My Publication Title --- Multiple Authors} +\author { + % Authors + First Author Name\textsuperscript{\rm 1}, + Second Author Name\textsuperscript{\rm 2}, + Third Author Name\textsuperscript{\rm 1} +} +\affiliations { + % Affiliations + \textsuperscript{\rm 1}Affiliation 1\\ + \textsuperscript{\rm 2}Affiliation 2\\ + firstAuthor@affiliation1.com, secondAuthor@affilation2.com, thirdAuthor@affiliation1.com +} +\fi + +% REMOVE THIS: bibentry +% This is only needed to show inline citations in the guidelines document. You should not need it and can safely delete it. +\usepackage{bibentry} +% END REMOVE bibentry + +\begin{document} + +\maketitle + +\begin{abstract} +AAAI creates proceedings, working notes, and technical reports directly from electronic source furnished by the authors. To ensure that all papers in the publication have a uniform appearance, authors must adhere to the following instructions. +\end{abstract} + +% Links section - only shown in camera-ready version +\ifdefined\aaaianonymous +% Uncomment the following to link to your code, datasets, an extended version or similar. +% You must keep this block between (not within) the abstract and the main body of the paper. +% NOTE: For anonymous submissions, do not include links that could reveal your identity +% \begin{links} +% \link{Code}{https://aaai.org/example/code} +% \link{Datasets}{https://aaai.org/example/datasets} +% \link{Extended version}{https://aaai.org/example/extended-version} +% \end{links} +\else +% Uncomment the following to link to your code, datasets, an extended version or similar. +% You must keep this block between (not within) the abstract and the main body of the paper. +\begin{links} + \link{Code}{https://aaai.org/example/code} + \link{Datasets}{https://aaai.org/example/datasets} + \link{Extended version}{https://aaai.org/example/extended-version} +\end{links} +\fi + +% Version-specific content +\ifdefined\aaaianonymous +\section{Preparing an Anonymous Submission} + +This document details the formatting requirements for anonymous submissions. The requirements are the same as for camera ready papers but with a few notable differences: + +\begin{itemize} + \item Anonymous submissions must not include the author names and affiliations. Write ``Anonymous Submission'' as the ``sole author'' and leave the affiliations empty. + \item The PDF document's metadata should be cleared with a metadata-cleaning tool before submitting it. This is to prevent leaked information from revealing your identity. + \item References must be anonymized whenever the reader can infer that they are to the authors' previous work. + \item AAAI's copyright notice should not be included as a footer in the first page. + \item Only the PDF version is required at this stage. No source versions will be requested, nor any copyright transfer form. +\end{itemize} + +You can remove the copyright notice and ensure that your names aren't shown by including \texttt{submission} option when loading the \texttt{aaai2026} package: + +\begin{quote}\begin{scriptsize}\begin{verbatim} +\documentclass[letterpaper]{article} +\usepackage[submission]{aaai2026} +\end{verbatim}\end{scriptsize}\end{quote} + +The remainder of this document are the original camera-ready instructions. Any contradiction of the above points ought to be ignored while preparing anonymous submissions. + +\section{Camera-Ready Guidelines} +\else +\section{Introduction} +\fi + +Congratulations on having a paper selected for inclusion in an AAAI Press proceedings or technical report! This document details the requirements necessary to get your accepted paper published using PDF\LaTeX{}. If you are using Microsoft Word, instructions are provided in a different document. AAAI Press does not support any other formatting software. + +The instructions herein are provided as a general guide for experienced \LaTeX{} users. If you do not know how to use \LaTeX{}, please obtain assistance locally. AAAI cannot provide you with support and the accompanying style files are \textbf{not} guaranteed to work. If the results you obtain are not in accordance with the specifications you received, you must correct your source file to achieve the correct result. + +These instructions are generic. Consequently, they do not include specific dates, page charges, and so forth. Please consult your specific written conference instructions for details regarding your submission. Please review the entire document for specific instructions that might apply to your particular situation. All authors must comply with the following: + +\begin{itemize} +\item You must use the 2026 AAAI Press \LaTeX{} style file and the aaai2026.bst bibliography style files, which are located in the 2026 AAAI Author Kit (aaai2026.sty, aaai2026.bst). +\item You must complete, sign, and return by the deadline the AAAI copyright form (unless directed by AAAI Press to use the AAAI Distribution License instead). +\item You must read and format your paper source and PDF according to the formatting instructions for authors. +\item You must submit your electronic files and abstract using our electronic submission form \textbf{on time.} +\item You must pay any required page or formatting charges to AAAI Press so that they are received by the deadline. +\item You must check your paper before submitting it, ensuring that it compiles without error, and complies with the guidelines found in the AAAI Author Kit. +\end{itemize} + +\ifdefined\aaaianonymous +\else +\section{Copyright} +All papers submitted for publication by AAAI Press must be accompanied by a valid signed copyright form. They must also contain the AAAI copyright notice at the bottom of the first page of the paper. There are no exceptions to these requirements. If you fail to provide us with a signed copyright form or disable the copyright notice, we will be unable to publish your paper. There are \textbf{no exceptions} to this policy. You will find a PDF version of the AAAI copyright form in the AAAI AuthorKit. Please see the specific instructions for your conference for submission details. +\fi + +\section{Formatting Requirements in Brief} +We need source and PDF files that can be used in a variety of ways and can be output on a variety of devices. The design and appearance of the paper is \ifdefined\aaaianonymous governed by the aaai2026.sty file (aaai2026.bst for the bibliography style).\else strictly governed by the aaai style file (aaai2026.sty).\fi +\ifdefined\aaaianonymous +\begin{itemize} +\item You must not modify the aaai2026.sty file or change the TeX commands. +\item You must not use any commands that alter the layout or formatting of your document (i.e., you cannot change the default margins, line spacing, etc.). +\item You may include other font size changes, color changes, or other formatting commands in your own source, but the paper has to be able to compile, and the styling commands are ignored. +\end{itemize} +\else +\textbf{You must not make any changes to the aaai style file, nor use any commands, packages, style files, or macros within your own paper that alter that design, including, but not limited to spacing, floats, margins, fonts, font size, and appearance.} AAAI imposes requirements on your source and PDF files that must be followed. Most of these requirements are based on our efforts to standardize conference manuscript properties and layout. All papers submitted to AAAI for publication will be recompiled for standardization purposes. Consequently, every paper submission must comply with the following requirements: + +\begin{itemize} +\item Your .tex file must compile in PDF\LaTeX{} --- (you may not include .ps or .eps figure files.) +\item All fonts must be embedded in the PDF file --- including your figures. +\item Modifications to the style file, whether directly or via commands in your document may not ever be made, most especially when made in an effort to avoid extra page charges or make your paper fit in a specific number of pages. +\item No type 3 fonts may be used (even in illustrations). +\item You may not alter the spacing above and below captions, figures, headings, and subheadings. +\item You may not alter the font sizes of text elements, footnotes, heading elements, captions, or title information (for references and mathematics, please see the limited exceptions provided herein). +\item You may not alter the line spacing of text. +\item Your title must follow Title Case capitalization rules (not sentence case). +\item \LaTeX{} documents must use the Times or Nimbus font package (you may not use Computer Modern for the text of your paper). +\item No \LaTeX{} 209 documents may be used or submitted. +\item Your source must not require use of fonts for non-Roman alphabets within the text itself. If your paper includes symbols in other languages (such as, but not limited to, Arabic, Chinese, Hebrew, Japanese, Thai, Russian and other Cyrillic languages), you must restrict their use to bit-mapped figures. Fonts that require non-English language support (CID and Identity-H) must be converted to outlines or 300 dpi bitmap or removed from the document (even if they are in a graphics file embedded in the document). +\item Two-column format in AAAI style is required for all papers. +\item The paper size for final submission must be US letter without exception. +\item The source file must exactly match the PDF. +\item The document margins may not be exceeded (no overfull boxes). +\item The number of pages and the file size must be as specified for your event. +\item No document may be password protected. +\item Neither the PDFs nor the source may contain any embedded links or bookmarks (no hyperref or navigator packages). +\item Your source and PDF must not have any page numbers, footers, or headers (no pagestyle commands). +\item Your PDF must be compatible with Acrobat 5 or higher. +\item Your \LaTeX{} source file (excluding references) must consist of a \textbf{single} file (use of the ``input" command is not allowed. +\item Your graphics must be sized appropriately outside of \LaTeX{} (do not use the ``clip" or ``trim'' command) . +\end{itemize} + +If you do not follow these requirements, your paper will be returned to you to correct the deficiencies. +\fi + +\section{What Files to Submit} +You must submit the following items to ensure that your paper is published: +\begin{itemize} +\item A fully-compliant PDF file. +\item Your \LaTeX{} source file submitted as a \textbf{single} .tex file (do not use the ``input" command to include sections of your paper --- every section must be in the single source file). (The only allowable exception is .bib file, which should be included separately). +\item The bibliography (.bib) file(s). +\item Your source must compile on our system, which includes only standard \LaTeX{} 2020 TeXLive support files. +\item Only the graphics files used in compiling paper. +\item The \LaTeX{}-generated files (e.g. .aux, .bbl file, PDF, etc.). +\end{itemize} + +Your \LaTeX{} source will be reviewed and recompiled on our system (if it does not compile, your paper will be returned to you. \textbf{Do not submit your source in multiple text files.} Your single \LaTeX{} source file must include all your text, your bibliography (formatted using aaai2026.bst), and any custom macros. + +Your files should work without any supporting files (other than the program itself) on any computer with a standard \LaTeX{} distribution. + +\textbf{Do not send files that are not actually used in the paper.} Avoid including any files not needed for compiling your paper, including, for example, this instructions file, unused graphics files, style files, additional material sent for the purpose of the paper review, intermediate build files and so forth. + +\textbf{Obsolete style files.} The commands for some common packages (such as some used for algorithms), may have changed. Please be certain that you are not compiling your paper using old or obsolete style files. + +\textbf{Final Archive.} Place your source files in a single archive which should be compressed using .zip. The final file size may not exceed 10 MB. +Name your source file with the last (family) name of the first author, even if that is not you. + +\section{Using \LaTeX{} to Format Your Paper} + +The latest version of the AAAI style file is available on AAAI's website. Download this file and place it in the \TeX\ search path. Placing it in the same directory as the paper should also work. You must download the latest version of the complete AAAI Author Kit so that you will have the latest instruction set and style file. + +\subsection{Document Preamble} + +In the \LaTeX{} source for your paper, you \textbf{must} place the following lines as shown in the example in this subsection. This command set-up is for three authors. Add or subtract author and address lines as necessary, and uncomment the portions that apply to you. In most instances, this is all you need to do to format your paper in the Times font. The helvet package will cause Helvetica to be used for sans serif. These files are part of the PSNFSS2e package, which is freely available from many Internet sites (and is often part of a standard installation). + +Leave the setcounter for section number depth commented out and set at 0 unless you want to add section numbers to your paper. If you do add section numbers, you must uncomment this line and change the number to 1 (for section numbers), or 2 (for section and subsection numbers). The style file will not work properly with numbering of subsubsections, so do not use a number higher than 2. + +\subsubsection{The Following Must Appear in Your Preamble} +\ifdefined\aaaianonymous +\begin{quote} +\begin{scriptsize}\begin{verbatim} +\documentclass[letterpaper]{article} +% DO NOT CHANGE THIS +\usepackage[submission]{aaai2026} % DO NOT CHANGE THIS +\usepackage{times} % DO NOT CHANGE THIS +\usepackage{helvet} % DO NOT CHANGE THIS +\usepackage{courier} % DO NOT CHANGE THIS +\usepackage[hyphens]{url} % DO NOT CHANGE THIS +\usepackage{graphicx} % DO NOT CHANGE THIS +\urlstyle{rm} % DO NOT CHANGE THIS +\def\UrlFont{\rm} % DO NOT CHANGE THIS +\usepackage{graphicx} % DO NOT CHANGE THIS +\usepackage{natbib} % DO NOT CHANGE THIS +\usepackage{caption} % DO NOT CHANGE THIS +\frenchspacing % DO NOT CHANGE THIS +\setlength{\pdfpagewidth}{8.5in} % DO NOT CHANGE THIS +\setlength{\pdfpageheight}{11in} % DO NOT CHANGE THIS +% +% Keep the \pdfinfo as shown here. There's no need +% for you to add the /Title and /Author tags. +\pdfinfo{ +/TemplateVersion (2026.1) +} +\end{verbatim}\end{scriptsize} +\end{quote} +\else +\begin{quote} +\begin{scriptsize}\begin{verbatim} +\documentclass[letterpaper]{article} +% DO NOT CHANGE THIS +\usepackage{aaai2026} % DO NOT CHANGE THIS +\usepackage{times} % DO NOT CHANGE THIS +\usepackage{helvet} % DO NOT CHANGE THIS +\usepackage{courier} % DO NOT CHANGE THIS +\usepackage[hyphens]{url} % DO NOT CHANGE THIS +\usepackage{graphicx} % DO NOT CHANGE THIS +\urlstyle{rm} % DO NOT CHANGE THIS +\def\UrlFont{\rm} % DO NOT CHANGE THIS +\usepackage{graphicx} % DO NOT CHANGE THIS +\usepackage{natbib} % DO NOT CHANGE THIS +\usepackage{caption} % DO NOT CHANGE THIS +\frenchspacing % DO NOT CHANGE THIS +\setlength{\pdfpagewidth}{8.5in} % DO NOT CHANGE THIS +\setlength{\pdfpageheight}{11in} % DO NOT CHANGE THIS +% +% Keep the \pdfinfo as shown here. There's no need +% for you to add the /Title and /Author tags. +\pdfinfo{ +/TemplateVersion (2026.1) +} +\end{verbatim}\end{scriptsize} +\end{quote} +\fi + +\subsection{Preparing Your Paper} + +After the preamble above, you should prepare your paper as follows: +\begin{quote} +\begin{scriptsize}\begin{verbatim} +\begin{document} +\maketitle +\begin{abstract} +%... +\end{abstract}\end{verbatim}\end{scriptsize} +\end{quote} + +\noindent If you want to add links to the paper's code, dataset(s), and extended version or similar this is the place to add them, within a \emph{links} environment: +\begin{quote}% +\begin{scriptsize}\begin{verbatim} +\begin{links} + \link{Code}{https://aaai.org/example/guidelines} + \link{Datasets}{https://aaai.org/example/datasets} + \link{Extended version}{https://aaai.org/example} +\end{links}\end{verbatim}\end{scriptsize} +\end{quote} +\ifdefined\aaaianonymous +\noindent Make sure that you do not de-anonymize yourself with these links. +\fi + +\noindent You should then continue with the body of your paper. Your paper must conclude with the references, which should be inserted as follows: +\begin{quote} +\begin{scriptsize}\begin{verbatim} +% References and End of Paper +% These lines must be placed at the end of your paper +\bibliography{Bibliography-File} +\end{document} +\end{verbatim}\end{scriptsize} +\end{quote} + +\begin{quote} +\begin{scriptsize}\begin{verbatim} +\begin{document}\\ +\maketitle\\ +...\\ +\bibliography{Bibliography-File}\\ +\end{document}\\ +\end{verbatim}\end{scriptsize} +\end{quote} + +\subsection{Commands and Packages That May Not Be Used} +\begin{table*}[t] +\centering +\begin{tabular}{l|l|l|l} +\textbackslash abovecaption & +\textbackslash abovedisplay & +\textbackslash addevensidemargin & +\textbackslash addsidemargin \\ +\textbackslash addtolength & +\textbackslash baselinestretch & +\textbackslash belowcaption & +\textbackslash belowdisplay \\ +\textbackslash break & +\textbackslash clearpage & +\textbackslash clip & +\textbackslash columnsep \\ +\textbackslash float & +\textbackslash input & +\textbackslash input & +\textbackslash linespread \\ +\textbackslash newpage & +\textbackslash pagebreak & +\textbackslash renewcommand & +\textbackslash setlength \\ +\textbackslash text height & +\textbackslash tiny & +\textbackslash top margin & +\textbackslash trim \\ +\textbackslash vskip\{- & +\textbackslash vspace\{- \\ +\end{tabular} +\caption{Commands that must not be used} +\label{table1} +\end{table*} + +\begin{table}[t] +\centering +\begin{tabular}{l|l|l|l} + authblk & babel & cjk & dvips \\ + epsf & epsfig & euler & float \\ + fullpage & geometry & graphics & hyperref \\ + layout & linespread & lmodern & maltepaper \\ + navigator & pdfcomment & pgfplots & psfig \\ + pstricks & t1enc & titlesec & tocbind \\ + ulem +\end{tabular} +\caption{LaTeX style packages that must not be used.} +\label{table2} +\end{table} + +There are a number of packages, commands, scripts, and macros that are incompatable with aaai2026.sty. The common ones are listed in tables \ref{table1} and \ref{table2}. Generally, if a command, package, script, or macro alters floats, margins, fonts, sizing, linespacing, or the presentation of the references and citations, it is unacceptable. Note that negative vskip and vspace may not be used except in certain rare occurances, and may never be used around tables, figures, captions, sections, subsections, subsubsections, or references. + +\subsection{Page Breaks} +For your final camera ready copy, you must not use any page break commands. References must flow directly after the text without breaks. Note that some conferences require references to be on a separate page during the review process. AAAI Press, however, does not require this condition for the final paper. + +\subsection{Paper Size, Margins, and Column Width} +Papers must be formatted to print in two-column format on 8.5 x 11 inch US letter-sized paper. The margins must be exactly as follows: +\begin{itemize} +\ifdefined\aaaianonymous +\item Top margin: 1.25 inches (first page), .75 inches (others) +\else +\item Top margin: .75 inches +\fi +\item Left margin: .75 inches +\item Right margin: .75 inches +\item Bottom margin: 1.25 inches +\end{itemize} + +The default paper size in most installations of \LaTeX{} is A4. However, because we require that your electronic paper be formatted in US letter size, the preamble we have provided includes commands that alter the default to US letter size. Please note that using any other package to alter page size (such as, but not limited to the Geometry package) will result in your final paper being returned to you for correction. + +\subsubsection{Column Width and Margins.} +To ensure maximum readability, your paper must include two columns. Each column should be 3.3 inches wide (slightly more than 3.25 inches), with a .375 inch (.952 cm) gutter of white space between the two columns. The aaai2026.sty file will automatically create these columns for you. + +\subsection{Overlength Papers} +If your paper is too long and you resort to formatting tricks to make it fit, it is quite likely that it will be returned to you. The best way to retain readability if the paper is overlength is to cut text, figures, or tables. There are a few acceptable ways to reduce paper size that don't affect readability. First, turn on \textbackslash frenchspacing, which will reduce the space after periods. Next, move all your figures and tables to the top of the page. Consider removing less important portions of a figure. If you use \textbackslash centering instead of \textbackslash begin\{center\} in your figure environment, you can also buy some space. For mathematical environments, you may reduce fontsize {\bf but not below 6.5 point}. + +Commands that alter page layout are forbidden. These include \textbackslash columnsep, \textbackslash float, \textbackslash topmargin, \textbackslash topskip, \textbackslash textheight, \textbackslash textwidth, \textbackslash oddsidemargin, and \textbackslash evensizemargin (this list is not exhaustive). If you alter page layout, you will be required to pay the page fee. Other commands that are questionable and may cause your paper to be rejected include \textbackslash parindent, and \textbackslash parskip. Commands that alter the space between sections are forbidden. The title sec package is not allowed. Regardless of the above, if your paper is obviously ``squeezed" it is not going to to be accepted. Options for reducing the length of a paper include reducing the size of your graphics, cutting text, or paying the extra page charge (if it is offered). + +\subsection{Type Font and Size} +Your paper must be formatted in Times Roman or Nimbus. We will not accept papers formatted using Computer Modern or Palatino or some other font as the text or heading typeface. Sans serif, when used, should be Courier. Use Symbol or Lucida or Computer Modern for \textit{mathematics only. } + +Do not use type 3 fonts for any portion of your paper, including graphics. Type 3 bitmapped fonts are designed for fixed resolution printers. Most print at 300 dpi even if the printer resolution is 1200 dpi or higher. They also often cause high resolution imagesetter devices to crash. Consequently, AAAI will not accept electronic files containing obsolete type 3 fonts. Files containing those fonts (even in graphics) will be rejected. (Authors using blackboard symbols must avoid packages that use type 3 fonts.) + +Fortunately, there are effective workarounds that will prevent your file from embedding type 3 bitmapped fonts. The easiest workaround is to use the required times, helvet, and courier packages with \LaTeX{}2e. (Note that papers formatted in this way will still use Computer Modern for the mathematics. To make the math look good, you'll either have to use Symbol or Lucida, or you will need to install type 1 Computer Modern fonts --- for more on these fonts, see the section ``Obtaining Type 1 Computer Modern.") + +If you are unsure if your paper contains type 3 fonts, view the PDF in Acrobat Reader. The Properties/Fonts window will display the font name, font type, and encoding properties of all the fonts in the document. If you are unsure if your graphics contain type 3 fonts (and they are PostScript or encapsulated PostScript documents), create PDF versions of them, and consult the properties window in Acrobat Reader. + +The default size for your type must be ten-point with twelve-point leading (line spacing). Start all pages (except the first) directly under the top margin. (See the next section for instructions on formatting the title page.) Indent ten points when beginning a new paragraph, unless the paragraph begins directly below a heading or subheading. + +\subsubsection{Obtaining Type 1 Computer Modern for \LaTeX{}.} +If you use Computer Modern for the mathematics in your paper (you cannot use it for the text) you may need to download type 1 Computer fonts. They are available without charge from the American Mathematical Society: +http://www.ams.org/tex/type1-fonts.html. + +\subsubsection{Nonroman Fonts.} +If your paper includes symbols in other languages (such as, but not limited to, Arabic, Chinese, Hebrew, Japanese, Thai, Russian and other Cyrillic languages), you must restrict their use to bit-mapped figures. + +\subsection{Title and Authors} +Your title must appear centered over both text columns in sixteen-point bold type (twenty-four point leading). The title must be written in Title Case capitalization rules (not sentence case). The rules are a bit involved, but in general verbs (including short verbs like be, is, using, and go), nouns, adverbs, adjectives, and pronouns should be capitalized, (including both words in hyphenated terms), while articles, conjunctions, and prepositions are lower case unless they directly follow a colon or long dash. You can use the online tool \url{https://titlecaseconverter.com/} to double-check the proper capitalization (select the "Chicago" style and mark the "Show explanations" checkbox). + +Author's names should appear below the title of the paper, centered in twelve-point type (with fifteen point leading), along with affiliation(s) and complete address(es) (including electronic mail address if available) in nine-point roman type (the twelve point leading). You should begin the two-column format when you come to the abstract. + +\subsubsection{Formatting Author Information.} +Author information has to be set according to the following specification depending if you have one or more than one affiliation. You may not use a table nor may you employ the \textbackslash authorblk.sty package. For one or several authors from the same institution, please separate them with commas and write all affiliation directly below (one affiliation per line) using the macros \textbackslash author and \textbackslash affiliations: + +\begin{quote}\begin{scriptsize}\begin{verbatim} +\author{ + Author 1, ..., Author n\\ +} +\affiliations { + Address line\\ + ... \\ + Address line\\ +} +\end{verbatim}\end{scriptsize}\end{quote} + +\noindent For authors from different institutions, use \textbackslash textsuperscript \{\textbackslash rm x \} to match authors and affiliations. Notice that there should not be any spaces between the author name (or comma following it) and the superscript. + +\begin{quote}\begin{scriptsize}\begin{verbatim} +\author{ + AuthorOne\equalcontrib\textsuperscript{\rm 1,\rm 2}, + AuthorTwo\equalcontrib\textsuperscript{\rm 2}, + AuthorThree\textsuperscript{\rm 3},\\ + AuthorFour\textsuperscript{\rm 4}, + AuthorFive \textsuperscript{\rm 5}} +} +\affiliations { + \textsuperscript{\rm 1}AffiliationOne,\\ + \textsuperscript{\rm 2}AffiliationTwo,\\ + \textsuperscript{\rm 3}AffiliationThree,\\ + \textsuperscript{\rm 4}AffiliationFour,\\ + \textsuperscript{\rm 5}AffiliationFive\\ + \{email, email\}@affiliation.com, + email@affiliation.com, + email@affiliation.com, + email@affiliation.com +} +\end{verbatim}\end{scriptsize}\end{quote} + +You can indicate that some authors contributed equally using the \textbackslash equalcontrib command. This will add a marker after the author names and a footnote on the first page. + +Note that you may want to break the author list for better visualization. You can achieve this using a simple line break (\textbackslash \textbackslash). + +\subsection{\LaTeX{} Copyright Notice} +The copyright notice automatically appears if you use aaai2026.sty. It has been hardcoded and may not be disabled. + +\subsection{Credits} +Any credits to a sponsoring agency should appear in the acknowledgments section, unless the agency requires different placement. If it is necessary to include this information on the front page, use +\textbackslash thanks in either the \textbackslash author or \textbackslash title commands. +For example: +\begin{quote} +\begin{small} +\textbackslash title\{Very Important Results in AI\textbackslash thanks\{This work is + supported by everybody.\}\} +\end{small} +\end{quote} +Multiple \textbackslash thanks commands can be given. Each will result in a separate footnote indication in the author or title with the corresponding text at the botton of the first column of the document. Note that the \textbackslash thanks command is fragile. You will need to use \textbackslash protect. + +Please do not include \textbackslash pubnote commands in your document. + +\subsection{Abstract} +Follow the example commands in this document for creation of your abstract. The command \textbackslash begin\{abstract\} will automatically indent the text block. Please do not indent it further. {Do not include references in your abstract!} + +\subsection{Page Numbers} +Do not print any page numbers on your paper. The use of \textbackslash pagestyle is forbidden. + +\subsection{Text} +The main body of the paper must be formatted in black, ten-point Times Roman with twelve-point leading (line spacing). You may not reduce font size or the linespacing. Commands that alter font size or line spacing (including, but not limited to baselinestretch, baselineshift, linespread, and others) are expressly forbidden. In addition, you may not use color in the text. + +\subsection{Citations} +Citations within the text should include the author's last name and year, for example (Newell 1980). Append lower-case letters to the year in cases of ambiguity. Multiple authors should be treated as follows: (Feigenbaum and Engelmore 1988) or (Ford, Hayes, and Glymour 1992). In the case of four or more authors, list only the first author, followed by et al. (Ford et al. 1997). + +\subsection{Extracts} +Long quotations and extracts should be indented ten points from the left and right margins. + +\begin{quote} +This is an example of an extract or quotation. Note the indent on both sides. Quotation marks are not necessary if you offset the text in a block like this, and properly identify and cite the quotation in the text. +\end{quote} + +\subsection{Footnotes} +Use footnotes judiciously, taking into account that they interrupt the reading of the text. When required, they should be consecutively numbered throughout with superscript Arabic numbers. Footnotes should appear at the bottom of the page, separated from the text by a blank line space and a thin, half-point rule. + +\subsection{Headings and Sections} +When necessary, headings should be used to separate major sections of your paper. Remember, you are writing a short paper, not a lengthy book! An overabundance of headings will tend to make your paper look more like an outline than a paper. The aaai2026.sty package will create headings for you. Do not alter their size nor their spacing above or below. + +\subsubsection{Section Numbers.} +The use of section numbers in AAAI Press papers is optional. To use section numbers in \LaTeX{}, uncomment the setcounter line in your document preamble and change the 0 to a 1. Section numbers should not be used in short poster papers and/or extended abstracts. + +\subsubsection{Section Headings.} +Sections should be arranged and headed as follows: +\begin{enumerate} +\item Main content sections +\item Appendices (optional) +\item Ethical Statement (optional, unnumbered) +\item Acknowledgements (optional, unnumbered) +\item References (unnumbered) +\end{enumerate} + +\subsubsection{Appendices.} +Any appendices must appear after the main content. If your main sections are numbered, appendix sections must use letters instead of arabic numerals. In \LaTeX{} you can use the \texttt{\textbackslash appendix} command to achieve this effect and then use \texttt{\textbackslash section\{Heading\}} normally for your appendix sections. + +\subsubsection{Ethical Statement.} +You can write a statement about the potential ethical impact of your work, including its broad societal implications, both positive and negative. If included, such statement must be written in an unnumbered section titled \emph{Ethical Statement}. + +\subsubsection{Acknowledgments.} +The acknowledgments section, if included, appears right before the references and is headed ``Acknowledgments". It must not be numbered even if other sections are (use \texttt{\textbackslash section*\{Acknowledgements\}} in \LaTeX{}). This section includes acknowledgments of help from associates and colleagues, credits to sponsoring agencies, financial support, and permission to publish. Please acknowledge other contributors, grant support, and so forth, in this section. Do not put acknowledgments in a footnote on the first page. If your grant agency requires acknowledgment of the grant on page 1, limit the footnote to the required statement, and put the remaining acknowledgments at the back. Please try to limit acknowledgments to no more than three sentences. + +\subsubsection{References.} +The references section should be labeled ``References" and must appear at the very end of the paper (don't end the paper with references, and then put a figure by itself on the last page). A sample list of references is given later on in these instructions. Please use a consistent format for references. Poorly prepared or sloppy references reflect badly on the quality of your paper and your research. Please prepare complete and accurate citations. + +\subsection{Illustrations and Figures} + +\begin{figure}[t] +\centering +\includegraphics[width=0.9\columnwidth]{figure1} % Reduce the figure size so that it is slightly narrower than the column. Don't use precise values for figure width.This setup will avoid overfull boxes. +\caption{Using the trim and clip commands produces fragile layers that can result in disasters (like this one from an actual paper) when the color space is corrected or the PDF combined with others for the final proceedings. Crop your figures properly in a graphics program -- not in LaTeX.} +\label{fig1} +\end{figure} + +\begin{figure*}[t] +\centering +\includegraphics[width=0.8\textwidth]{figure2} % Reduce the figure size so that it is slightly narrower than the column. +\caption{Adjusting the bounding box instead of actually removing the unwanted data resulted multiple layers in this paper. It also needlessly increased the PDF size. In this case, the size of the unwanted layer doubled the paper's size, and produced the following surprising results in final production. Crop your figures properly in a graphics program. Don't just alter the bounding box.} +\label{fig2} +\end{figure*} + +Your paper must compile in PDF\LaTeX{}. Consequently, all your figures must be .jpg, .png, or .pdf. You may not use the .gif (the resolution is too low), .ps, or .eps file format for your figures. + +Figures, drawings, tables, and photographs should be placed throughout the paper on the page (or the subsequent page) where they are first discussed. Do not group them together at the end of the paper. If placed at the top of the paper, illustrations may run across both columns. Figures must not invade the top, bottom, or side margin areas. Figures must be inserted using the \textbackslash usepackage\{graphicx\}. Number figures sequentially, for example, figure 1, and so on. Do not use minipage to group figures. + +If you normally create your figures using pgfplots, please create the figures first, and then import them as pdfs with proper bounding boxes, as the bounding and trim boxes created by pfgplots are fragile and not valid. + +When you include your figures, you must crop them \textbf{outside} of \LaTeX{}. The command \textbackslash includegraphics*[clip=true, viewport 0 0 10 10]{...} might result in a PDF that looks great, but the image is \textbf{not really cropped.} The full image can reappear (and obscure whatever it is overlapping) when page numbers are applied or color space is standardized. Figures \ref{fig1}, and \ref{fig2} display some unwanted results that often occur. + +If your paper includes illustrations that are not compatible with PDF\TeX{} (such as .eps or .ps documents), you will need to convert them. The epstopdf package will usually work for eps files. You will need to convert your ps files to PDF in either case. + +\subsubsection {Figure Captions.}The illustration number and caption must appear \textit{under} the illustration. Labels and other text with the actual illustration must be at least nine-point type. However, the font and size of figure captions must be 10 point roman. Do not make them smaller, bold, or italic. (Individual words may be italicized if the context requires differentiation.) + +\subsection{Tables} +Tables should be presented in 10 point roman type. If necessary, they may be altered to 9 point type. You must not use \texttt{\textbackslash resizebox} or other commands that resize the entire table to make it smaller, because you can't control the final font size this way. +If your table is too large you can use \texttt{\textbackslash setlength\{\textbackslash tabcolsep\}\{1mm\}} to compress the columns a bit or you can adapt the content (e.g.: reduce the decimal precision when presenting numbers, use shortened column titles, make some column duble-line to get it narrower). + +Tables that do not fit in a single column must be placed across double columns. If your table won't fit within the margins even when spanning both columns and using the above techniques, you must split it in two separate tables. + +\subsubsection {Table Captions.} The number and caption for your table must appear \textit{under} (not above) the table. Additionally, the font and size of table captions must be 10 point roman and must be placed beneath the figure. Do not make them smaller, bold, or italic. (Individual words may be italicized if the context requires differentiation.) + +\subsubsection{Low-Resolution Bitmaps.} +You may not use low-resolution (such as 72 dpi) screen-dumps and GIF files---these files contain so few pixels that they are always blurry, and illegible when printed. If they are color, they will become an indecipherable mess when converted to black and white. This is always the case with gif files, which should never be used. The resolution of screen dumps can be increased by reducing the print size of the original file while retaining the same number of pixels. You can also enlarge files by manipulating them in software such as PhotoShop. Your figures should be 300 dpi when incorporated into your document. + +\subsubsection{\LaTeX{} Overflow.} +\LaTeX{} users please beware: \LaTeX{} will sometimes put portions of the figure or table or an equation in the margin. If this happens, you need to make the figure or table span both columns. If absolutely necessary, you may reduce the figure, or reformat the equation, or reconfigure the table.{ \bf Check your log file!} You must fix any overflow into the margin (that means no overfull boxes in \LaTeX{}). \textbf{Nothing is permitted to intrude into the margin or gutter.} + +\subsubsection{Using Color.} +Use of color is restricted to figures only. It must be WACG 2.0 compliant. (That is, the contrast ratio must be greater than 4.5:1 no matter the font size.) It must be CMYK, NOT RGB. It may never be used for any portion of the text of your paper. The archival version of your paper will be printed in black and white and grayscale. The web version must be readable by persons with disabilities. Consequently, because conversion to grayscale can cause undesirable effects (red changes to black, yellow can disappear, and so forth), we strongly suggest you avoid placing color figures in your document. If you do include color figures, you must (1) use the CMYK (not RGB) colorspace and (2) be mindful of readers who may happen to have trouble distinguishing colors. Your paper must be decipherable without using color for distinction. + +\subsubsection{Drawings.} +We suggest you use computer drawing software (such as Adobe Illustrator or, (if unavoidable), the drawing tools in Microsoft Word) to create your illustrations. Do not use Microsoft Publisher. These illustrations will look best if all line widths are uniform (half- to two-point in size), and you do not create labels over shaded areas. Shading should be 133 lines per inch if possible. Use Times Roman or Helvetica for all figure call-outs. \textbf{Do not use hairline width lines} --- be sure that the stroke width of all lines is at least .5 pt. Zero point lines will print on a laser printer, but will completely disappear on the high-resolution devices used by our printers. + +\subsubsection{Photographs and Images.} +Photographs and other images should be in grayscale (color photographs will not reproduce well; for example, red tones will reproduce as black, yellow may turn to white, and so forth) and set to a minimum of 300 dpi. Do not prescreen images. + +\subsubsection{Resizing Graphics.} +Resize your graphics \textbf{before} you include them with LaTeX. You may \textbf{not} use trim or clip options as part of your \textbackslash includegraphics command. Resize the media box of your PDF using a graphics program instead. + +\subsubsection{Fonts in Your Illustrations.} +You must embed all fonts in your graphics before including them in your LaTeX document. + +\subsubsection{Algorithms.} +Algorithms and/or programs are a special kind of figures. Like all illustrations, they should appear floated to the top (preferably) or bottom of the page. However, their caption should appear in the header, left-justified and enclosed between horizontal lines, as shown in Algorithm~\ref{alg:algorithm}. The algorithm body should be terminated with another horizontal line. It is up to the authors to decide whether to show line numbers or not, how to format comments, etc. + +In \LaTeX{} algorithms may be typeset using the {\tt algorithm} and {\tt algorithmic} packages, but you can also use one of the many other packages for the task. + +\begin{algorithm}[tb] +\caption{Example algorithm} +\label{alg:algorithm} +\textbf{Input}: Your algorithm's input\\ +\textbf{Parameter}: Optional list of parameters\\ +\textbf{Output}: Your algorithm's output +\begin{algorithmic}[1] %[1] enables line numbers +\STATE Let $t=0$. +\WHILE{condition} +\STATE Do some action. +\IF {conditional} +\STATE Perform task A. +\ELSE +\STATE Perform task B. +\ENDIF +\ENDWHILE +\STATE \textbf{return} solution +\end{algorithmic} +\end{algorithm} + +\subsubsection{Listings.} +Listings are much like algorithms and programs. They should also appear floated to the top (preferably) or bottom of the page. Listing captions should appear in the header, left-justified and enclosed between horizontal lines as shown in Listing~\ref{lst:listing}. Terminate the body with another horizontal line and avoid any background color. Line numbers, if included, must appear within the text column. + +\begin{listing}[tb]% +\caption{Example listing {\tt quicksort.hs}}% +\label{lst:listing}% +\begin{lstlisting}[language=Haskell] +quicksort :: Ord a => [a] -> [a] +quicksort [] = [] +quicksort (p:xs) = (quicksort lesser) ++ [p] ++ (quicksort greater) + where + lesser = filter (< p) xs + greater = filter (>= p) xs +\end{lstlisting} +\end{listing} + +\subsection{References} +The AAAI style includes a set of definitions for use in formatting references with BibTeX. These definitions make the bibliography style fairly close to the ones specified in the Reference Examples appendix below. To use these definitions, you also need the BibTeX style file ``aaai2026.bst," available in the AAAI Author Kit on the AAAI web site. Then, at the end of your paper but before \textbackslash end{document}, you need to put the following lines: + +\begin{quote} +\begin{small} +\textbackslash bibliography\{bibfile1,bibfile2,...\} +\end{small} +\end{quote} + +Please note that the aaai2026.sty class already sets the bibliographystyle for you, so you do not have to place any \textbackslash bibliographystyle command in the document yourselves. The aaai2026.sty file is incompatible with the hyperref and navigator packages. If you use either, your references will be garbled and your paper will be returned to you. + +References may be the same size as surrounding text. +However, in this section (only), you may reduce the size to {\em \textbackslash small} (9pt) if your paper exceeds the allowable number of pages. Making it any smaller than 9 point with 10 point linespacing, however, is not allowed. + +The list of files in the \textbackslash bibliography command should be the names of your BibTeX source files (that is, the .bib files referenced in your paper). + +The following commands are available for your use in citing references: +\begin{quote} +{\em \textbackslash cite:} Cites the given reference(s) with a full citation. This appears as ``(Author Year)'' for one reference, or ``(Author Year; Author Year)'' for multiple references.\smallskip\\ +{\em \textbackslash shortcite:} Cites the given reference(s) with just the year. This appears as ``(Year)'' for one reference, or ``(Year; Year)'' for multiple references.\smallskip\\ +{\em \textbackslash citeauthor:} Cites the given reference(s) with just the author name(s) and no parentheses.\smallskip\\ +{\em \textbackslash citeyear:} Cites the given reference(s) with just the date(s) and no parentheses. +\end{quote} +You may also use any of the \emph{natbib} citation commands. + +\section{Proofreading Your PDF} +Please check all the pages of your PDF file. The most commonly forgotten element is the acknowledgements --- especially the correct grant number. Authors also commonly forget to add the metadata to the source, use the wrong reference style file, or don't follow the capitalization rules or comma placement for their author-title information properly. A final common problem is text (expecially equations) that runs into the margin. You will need to fix these common errors before submitting your file. + +\section{Improperly Formatted Files } +In the past, AAAI has corrected improperly formatted files submitted by the authors. Unfortunately, this has become an increasingly burdensome expense that we can no longer absorb). Consequently, if your file is improperly formatted, it will be returned to you for correction. + +\section{Naming Your Electronic File} +We require that you name your \LaTeX{} source file with the last name (family name) of the first author so that it can easily be differentiated from other submissions. Complete file-naming instructions will be provided to you in the submission instructions. + +\section{Submitting Your Electronic Files to AAAI} +Instructions on paper submittal will be provided to you in your acceptance letter. + +\section{Inquiries} +If you have any questions about the preparation or submission of your paper as instructed in this document, please contact AAAI Press at the address given below. If you have technical questions about implementation of the aaai style file, please contact an expert at your site. We do not provide technical support for \LaTeX{} or any other software package. To avoid problems, please keep your paper simple, and do not incorporate complicated macros and style files. + +\begin{quote} +\noindent AAAI Press\\ +1101 Pennsylvania Ave, NW Suite 300\\ +Washington, DC 20004 USA\\ +\textit{Telephone:} 1-202-360-4062\\ +\textit{E-mail:} See the submission instructions for your particular conference or event. +\end{quote} + +\section{Additional Resources} +\LaTeX{} is a difficult program to master. If you've used that software, and this document didn't help or some items were not explained clearly, we recommend you read Michael Shell's excellent document (testflow doc.txt V1.0a 2002/08/13) about obtaining correct PS/PDF output on \LaTeX{} systems. (It was written for another purpose, but it has general application as well). It is available at www.ctan.org in the tex-archive. + +\appendix +\section{Reference Examples} +\label{sec:reference_examples} + +\nobibliography* +Formatted bibliographies should look like the following examples. You should use BibTeX to generate the references. Missing fields are unacceptable when compiling references, and usually indicate that you are using the wrong type of entry (BibTeX class). + +\paragraph{Book with multiple authors~\nocite{em:86}} Use the \texttt{@book} class.\\[.2em] +\bibentry{em:86}. + +\paragraph{Journal and magazine articles~\nocite{r:80, hcr:83}} Use the \texttt{@article} class.\\[.2em] +\bibentry{r:80}.\\[.2em] +\bibentry{hcr:83}. + +\paragraph{Proceedings paper published by a society, press or publisher~\nocite{c:83, c:84}} Use the \texttt{@inproceedings} class. You may abbreviate the \emph{booktitle} field, but make sure that the conference edition is clear.\\[.2em] +\bibentry{c:84}.\\[.2em] +\bibentry{c:83}. + +\paragraph{University technical report~\nocite{r:86}} Use the \texttt{@techreport} class.\\[.2em] +\bibentry{r:86}. + +\paragraph{Dissertation or thesis~\nocite{c:79}} Use the \texttt{@phdthesis} class.\\[.2em] +\bibentry{c:79}. + +\paragraph{Forthcoming publication~\nocite{c:21}} Use the \texttt{@misc} class with a \texttt{note="Forthcoming"} annotation. +\begin{quote} +\begin{footnotesize} +\begin{verbatim} +@misc(key, + [...] + note="Forthcoming", +) +\end{verbatim} +\end{footnotesize} +\end{quote} +\bibentry{c:21}. + +\paragraph{ArXiv paper~\nocite{c:22}} Fetch the BibTeX entry from the "Export Bibtex Citation" link in the arXiv website. Notice it uses the \texttt{@misc} class instead of the \texttt{@article} one, and that it includes the \texttt{eprint} and \texttt{archivePrefix} keys. +\begin{quote} +\begin{footnotesize} +\begin{verbatim} +@misc(key, + [...] + eprint="xxxx.yyyy", + archivePrefix="arXiv", +) +\end{verbatim} +\end{footnotesize} +\end{quote} +\bibentry{c:22}. + +\paragraph{Website or online resource~\nocite{c:23}} Use the \texttt{@misc} class. Add the url in the \texttt{howpublished} field and the date of access in the \texttt{note} field: +\begin{quote} +\begin{footnotesize} +\begin{verbatim} +@misc(key, + [...] + howpublished="\url{http://...}", + note="Accessed: YYYY-mm-dd", +) +\end{verbatim} +\end{footnotesize} +\end{quote} +\bibentry{c:23}. + +\vspace{.2em} +For the most up to date version of the AAAI reference style, please consult the \textit{AI Magazine} Author Guidelines at \url{https://aaai.org/ojs/index.php/aimagazine/about/submissions#authorGuidelines} + +\section{Acknowledgments} + +% Anonymous submission version - shorter acknowledgments +AAAI is especially grateful to Peter Patel Schneider for his work in implementing the aaai2026.sty file, liberally using the ideas of other style hackers, including Barbara Beeton. We also acknowledge with thanks the work of George Ferguson for his guide to using the style and BibTeX files --- which has been incorporated into this document --- and Hans Guesgen, who provided several timely modifications, as well as the many others who have, from time to time, sent in suggestions on improvements to the AAAI style. We are especially grateful to Francisco Cruz, Marc Pujol-Gonzalez, and Mico Loretan for the improvements to the Bib\TeX{} and \LaTeX{} files made in 2020. + +The preparation of the \LaTeX{} and Bib\TeX{} files that implement these instructions was supported by Schlumberger Palo Alto Research, AT\&T Bell Laboratories, Morgan Kaufmann Publishers, The Live Oak Press, LLC, and AAAI Press. Bibliography style changes were added by Sunil Issar. \verb+\+pubnote was added by J. Scott Penberthy. George Ferguson added support for printing the AAAI copyright slug. Additional changes to aaai2026.sty and aaai2026.bst have been made by Francisco Cruz and Marc Pujol-Gonzalez. + +\bigskip +\noindent Thank you for reading these instructions carefully. We look forward to receiving your electronic files! + + + +% Note: \bibliographystyle{aaai2026} is automatically set by aaai2026.sty +% Do not add \bibliographystyle{aaai2026} here as it will cause "Illegal, another \bibstyle command" error +\bibliography{aaai2026} + +\section{Reproducibility Checklist} + +Unless specified otherwise, please answer ``yes'' to each question if the relevant information is described either in the paper itself or in a technical appendix with an explicit reference from the main paper. If you wish to explain an answer further, please do so in a section titled ``Reproducibility Checklist'' at the end of the technical appendix. + +This paper: + +Includes a conceptual outline and/or pseudocode description of AI methods introduced (yes/partial/no/NA) + +Clearly delineates statements that are opinions, hypothesis, and speculation from objective facts and results (yes/no) + +Provides well marked pedagogical references for less-familiare readers to gain background necessary to replicate the paper (yes/no) + +Does this paper make theoretical contributions? (yes/no) + +If yes, please complete the list below. + +All assumptions and restrictions are stated clearly and formally. (yes/partial/no) + +All novel claims are stated formally (e.g., in theorem statements). (yes/partial/no) + +Proofs of all novel claims are included. (yes/partial/no) + +Proof sketches or intuitions are given for complex and/or novel results. (yes/partial/no) + +Appropriate citations to theoretical tools used are given. (yes/partial/no) + +All theoretical claims are demonstrated empirically to hold. (yes/partial/no/NA) + +All experimental code used to eliminate or disprove claims is included. (yes/no/NA) + +Does this paper rely on one or more datasets? (yes/no) + +If yes, please complete the list below. + +A motivation is given for why the experiments are conducted on the selected datasets (yes/partial/no/NA) + +All novel datasets introduced in this paper are included in a data appendix. (yes/partial/no/NA) + +All novel datasets introduced in this paper will be made publicly available upon publication of the paper with a license that allows free usage for research purposes. (yes/partial/no/NA) + +All datasets drawn from the existing literature (potentially including authors' own previously published work) are accompanied by appropriate citations. (yes/no/NA) + +All datasets drawn from the existing literature (potentially including authors' own previously published work) are publicly available. (yes/partial/no/NA) + +All datasets that are not publicly available are described in detail, with explanation why publicly available alternatives are not scientifically satisficing. (yes/partial/no/NA) + +Does this paper include computational experiments? (yes/no) + +If yes, please complete the list below. + +This paper states the number and range of values tried per (hyper-) parameter during development of the paper, along with the criterion used for selecting the final parameter setting. (yes/partial/no/NA) + +Any code required for pre-processing data is included in the appendix. (yes/partial/no). + +All source code required for conducting and analyzing the experiments is included in a code appendix. (yes/partial/no) + +All source code required for conducting and analyzing the experiments will be made publicly available upon publication of the paper with a license that allows free usage for research purposes. (yes/partial/no) + +All source code implementing new methods have comments detailing the implementation, with references to the paper where each step comes from (yes/partial/no) + +If an algorithm depends on randomness, then the method used for setting seeds is described in a way sufficient to allow replication of results. (yes/partial/no/NA) + +This paper specifies the computing infrastructure used for running experiments (hardware and software), including GPU/CPU models; amount of memory; operating system; names and versions of relevant software libraries and frameworks. (yes/partial/no) + +This paper formally describes evaluation metrics used and explains the motivation for choosing these metrics. (yes/partial/no) + +This paper states the number of algorithm runs used to compute each reported result. (yes/no) + +Analysis of experiments goes beyond single-dimensional summaries of performance (e.g., average; median) to include measures of variation, confidence, or other distributional information. (yes/no) + +The significance of any improvement or decrease in performance is judged using appropriate statistical tests (e.g., Wilcoxon signed-rank). (yes/partial/no) + +This paper lists all final (hyper-)parameters used for each model/algorithm in the paper's experiments. (yes/partial/no/NA). + +\end{document} \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.bib b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.bib new file mode 100644 index 0000000..7b7d2bc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.bib @@ -0,0 +1,111 @@ +@book{em:86, + editor = "Engelmore, Robert and Morgan, Anthony", + title = "Blackboard Systems", + year = 1986, + address = "Reading, Mass.", + publisher = "Addison-Wesley", +} + +@inproceedings{c:83, + author = "Clancey, William J.", + year = 1983, + title = "{Communication, Simulation, and Intelligent +Agents: Implications of Personal Intelligent Machines +for Medical Education}", + booktitle="Proceedings of the Eighth International Joint Conference on Artificial Intelligence {(IJCAI-83)}", + pages = "556-560", + address = "Menlo Park, Calif", + publisher = "{IJCAI Organization}", +} +@inproceedings{c:84, + author = "Clancey, William J.", + year = 1984, + title = "{Classification Problem Solving}", + booktitle = "Proceedings of the Fourth National + Conference on Artificial Intelligence", + pages = "45-54", + address = "Menlo Park, Calif.", + publisher="AAAI Press", +} +@article{r:80, + author = {Robinson, Arthur L.}, + title = {New Ways to Make Microcircuits Smaller}, + volume = {208}, + number = {4447}, + pages = {1019--1022}, + year = {1980}, + doi = {10.1126/science.208.4447.1019}, + publisher = {American Association for the Advancement of Science}, + issn = {0036-8075}, + URL = {https://science.sciencemag.org/content/208/4447/1019}, + eprint = {https://science.sciencemag.org/content/208/4447/1019.full.pdf}, + journal = {Science}, +} +@article{r:80x, + author = "Robinson, Arthur L.", + year = 1980, + title = "{New Ways to Make Microcircuits Smaller---Duplicate Entry}", + journal = "Science", + volume = 208, + pages = "1019-1026", +} +@article{hcr:83, +title = {Strategic explanations for a diagnostic consultation system}, +journal = {International Journal of Man-Machine Studies}, +volume = {20}, +number = {1}, +pages = {3-19}, +year = {1984}, +issn = {0020-7373}, +doi = {https://doi.org/10.1016/S0020-7373(84)80003-6}, +url = {https://www.sciencedirect.com/science/article/pii/S0020737384800036}, +author = {Diane Warner Hasling and William J. Clancey and Glenn Rennels}, +abstract = {This article examines the problem of automatte explanation of reasoning, especially as it relates to expert systems. By explanation we mean the ability of a program to discuss what it is doing in some understandable way. We first present a general framework in which to view explanation and review some of the research done in this area. We then focus on the explanation system for NEOMYCIN, a medical consultation program. A consultation program interactively helps a user to solve a problem. Our goal is to have NEOMYCIN explain its problem-solving strategies. An explanation of strategy describes the plan the program is using to reach a solution. Such an explanation is usually concrete, referring to aspects of the current problem situation. Abstract explanations articulate a general principle, which can be applied in different situations; such explanations are useful in teaching and in explaining by analogy. We describe the aspects of NEOMYCIN that make abstract strategic explanations possible—the representation of strategic knowledge explicitly and separately from domain knowledge— and demonstrate how this representation can be used to generate explanations.} +} +@article{hcrt:83, + author = "Hasling, Diane Warner and Clancey, William J. and Rennels, Glenn R. and Test, Thomas", + year = 1983, + title = "{Strategic Explanations in Consultation---Duplicate}", + journal = "The International Journal of Man-Machine Studies", + volume = 20, + number = 1, + pages = "3-19", +} +@techreport{r:86, + author = "Rice, James", + year = 1986, + title = "{Poligon: A System for Parallel Problem Solving}", + type = "Technical Report", + number = "KSL-86-19", + institution = "Dept.\ of Computer Science, Stanford Univ.", +} +@phdthesis{c:79, + author = "Clancey, William J.", + year = 1979, + title = "{Transfer of Rule-Based Expertise +through a Tutorial Dialogue}", + type = "{Ph.D.} diss.", + school = "Dept.\ of Computer Science, Stanford Univ.", + address = "Stanford, Calif.", +} +@unpublished{c:21, + author = "Clancey, William J.", + title = "{The Engineering of Qualitative Models}", + year = 2021, + note = "Forthcoming", +} +@misc{c:22, + title={Attention Is All You Need}, + author={Ashish Vaswani and Noam Shazeer and Niki Parmar and Jakob Uszkoreit and Llion Jones and Aidan N. Gomez and Lukasz Kaiser and Illia Polosukhin}, + year={2017}, + eprint={1706.03762}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +@misc{c:23, + title = "Pluto: The 'Other' Red Planet", + author = "{NASA}", + howpublished = "\url{https://www.nasa.gov/nh/pluto-the-other-red-planet}", + year = 2015, + note = "Accessed: 2018-12-06" +} \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.bst b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.bst new file mode 100644 index 0000000..bc73330 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.bst @@ -0,0 +1,1493 @@ +%% +%% This is file `aaai2026.bst', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% merlin.mbs (with options: `head,ay,nat,ed-au,nm-rev,ed-rev,jnrlst,aunm-semi,mcite,mct-1,mct-x3,keyxyr,dt-beg,yr-per,yrp-per,note-yr,atit-u,volp-sp,num-xser,bkpg-x,add-pub,isbn,ppx,ed,xedn,and-com,and-com-ed,etal-xc,nfss,,{}') +%% merlin.mbs (with options: `tail,ay,nat,ed-au,nm-rev,ed-rev,jnrlst,aunm-semi,mcite,mct-1,mct-x3,keyxyr,dt-beg,yr-per,yrp-per,note-yr,atit-u,volp-sp,num-xser,bkpg-x,add-pub,isbn,ppx,ed,xedn,and-com,and-com-ed,etal-xc,nfss,,{}') +%% ---------------------------------------- +%% *** Natbib-compatible implementation of 'aaai' bib style *** +%% + % =============================================================== + % IMPORTANT NOTICE: + % This bibliographic style (bst) file has been generated from one or + % more master bibliographic style (mbs) files, listed above. + % + % This generated file can be redistributed and/or modified under the terms + % of the LaTeX Project Public License Distributed from CTAN + % archives in directory macros/latex/base/lppl.txt; either + % version 1 of the License, or any later version. + % =============================================================== + % Name and version information of the main mbs file: + % \ProvidesFile{merlin.mbs}[2011/11/18 4.33 (PWD, AO, DPC)] + % For use with BibTeX version 0.99a or later + %------------------------------------------------------------------- + % This bibliography style file is intended for texts in ENGLISH + % This is an author-year citation style bibliography. As such, it is + % non-standard LaTeX, and requires a special package file to function properly. + % Such a package is natbib.sty by Patrick W. Daly + % The form of the \bibitem entries is + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Smith]{key}... + % The essential feature is that the label (the part in brackets) consists + % of the author names, as they should appear in the citation, with the year + % in parentheses following. There must be no space before the opening + % parenthesis! + % With natbib v5.3, a full list of authors may also follow the year. + % In natbib.sty, it is possible to define the type of enclosures that is + % really wanted (brackets or parentheses), but in either case, there must + % be parentheses in the label. + % The \cite command functions as follows: + % \citet{key} ==>> Jones et al. (1990) + % \citet*{key} ==>> Jones, Baker, and Smith (1990) + % \citep{key} ==>> (Jones et al., 1990) + % \citep*{key} ==>> (Jones, Baker, and Smith, 1990) + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.][]{key} ==>> (e.g. Jones et al., 1990) + % \citep[e.g.][p. 32]{key} ==>> (e.g. Jones et al., 1990, p. 32) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Smith + % \citeyear{key} ==>> 1990 + %--------------------------------------------------------------------- + +ENTRY + { address + archivePrefix + author + booktitle + chapter + edition + editor + eid + eprint + howpublished + institution + isbn + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label short.list } +INTEGERS { output.state before.all mid.sentence after.sentence after.block } +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} +STRINGS { s t} +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} +FUNCTION {add.blank} +{ " " * before.all 'output.state := +} + +FUNCTION {date.block} +{ + new.block +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} +FUNCTION {tie.or.space.prefix} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ +} + +FUNCTION {capitalize} +{ "u" change.case$ "t" change.case$ } + +FUNCTION {space.word} +{ " " swap$ * " " * } + % Here are the language-specific definitions for explicit words. + % Each function has a name bbl.xxx where xxx is the English word. + % The language selected here is ENGLISH +FUNCTION {bbl.and} +{ "and"} + +FUNCTION {bbl.etal} +{ "et~al." } + +FUNCTION {bbl.editors} +{ "eds." } + +FUNCTION {bbl.editor} +{ "ed." } + +FUNCTION {bbl.edby} +{ "edited by" } + +FUNCTION {bbl.edition} +{ "edition" } + +FUNCTION {bbl.volume} +{ "volume" } + +FUNCTION {bbl.of} +{ "of" } + +FUNCTION {bbl.number} +{ "number" } + +FUNCTION {bbl.nr} +{ "no." } + +FUNCTION {bbl.in} +{ "in" } + +FUNCTION {bbl.pages} +{ "" } + +FUNCTION {bbl.page} +{ "" } + +FUNCTION {bbl.chapter} +{ "chapter" } + +FUNCTION {bbl.techrep} +{ "Technical Report" } + +FUNCTION {bbl.mthesis} +{ "Master's thesis" } + +FUNCTION {bbl.phdthesis} +{ "Ph.D. thesis" } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} +FUNCTION {bibinfo.check} +{ swap$ + duplicate$ missing$ + { + pop$ pop$ + "" + } + { duplicate$ empty$ + { + swap$ pop$ + } + { swap$ + pop$ + } + if$ + } + if$ +} +FUNCTION {bibinfo.warn} +{ swap$ + duplicate$ missing$ + { + swap$ "missing " swap$ * " in " * cite$ * warning$ pop$ + "" + } + { duplicate$ empty$ + { + swap$ "empty " swap$ * " in " * cite$ * warning$ + } + { swap$ + pop$ + } + if$ + } + if$ +} +FUNCTION {format.eprint} +{ eprint duplicate$ empty$ + 'skip$ + { archivePrefix duplicate$ empty$ + 'skip$ + { ":" * swap$ } + if$ + * "." * + } + if$ +} +INTEGERS { nameptr namesleft numnames } + + +STRINGS { bibinfo} + +FUNCTION {format.names} +{ 'bibinfo := + duplicate$ empty$ 'skip$ { + 's := + "" 't := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}{, f.}{, jj}" + format.name$ + bibinfo bibinfo.check + 't := + nameptr #1 > + { + namesleft #1 > + { "; " * t * } + { + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + ";" * + t "others" = + { + " " * bbl.etal * + } + { + bbl.and + space.word * t * + } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ + } if$ +} +FUNCTION {format.names.ed} +{ + format.names +} +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author "author" format.names +} +FUNCTION {get.bbl.editor} +{ editor num.names$ #1 > 'bbl.editors 'bbl.editor if$ } + +FUNCTION {format.editors} +{ editor "editor" format.names duplicate$ empty$ 'skip$ + { + "," * + " " * + get.bbl.editor + * + } + if$ +} +FUNCTION {format.isbn} +{ isbn "isbn" bibinfo.check + duplicate$ empty$ 'skip$ + { + new.block + "ISBN " swap$ * + } + if$ +} + +FUNCTION {format.note} +{ + note empty$ + { "" } + { note #1 #1 substring$ + duplicate$ "{" = + 'skip$ + { output.state mid.sentence = + { "l" } + { "u" } + if$ + change.case$ + } + if$ + note #2 global.max$ substring$ * "note" bibinfo.check + } + if$ +} + +FUNCTION {format.title} +{ title + "title" bibinfo.check +} +FUNCTION {format.full.names} +{'s := + "" 't := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " " * bbl.etal * + } + { + numnames #2 > + { "," * } + 'skip$ + if$ + bbl.and + space.word * t * + } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.key.full} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.key.full} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {editor.key.full} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.full + { type$ "proceedings" = + 'editor.key.full + 'author.key.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[{" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "}]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ + 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {word.in} +{ bbl.in capitalize + " " * } + +FUNCTION {format.date} +{ year "year" bibinfo.check duplicate$ empty$ + { + "empty year in " cite$ * "; set to ????" * warning$ + pop$ "????" + } + 'skip$ + if$ + extra.label * + before.all 'output.state := + after.sentence 'output.state := +} +FUNCTION {format.btitle} +{ title "title" bibinfo.check + duplicate$ empty$ 'skip$ + { + emphasize + } + if$ +} +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { bbl.volume volume tie.or.space.prefix + "volume" bibinfo.check * * + series "series" bibinfo.check + duplicate$ empty$ 'pop$ + { swap$ bbl.of space.word * swap$ + emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { series empty$ + { number "number" bibinfo.check } + { output.state mid.sentence = + { bbl.number } + { bbl.number capitalize } + if$ + number tie.or.space.prefix "number" bibinfo.check * * + bbl.in space.word * + series "series" bibinfo.check * + } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition duplicate$ empty$ 'skip$ + { + output.state mid.sentence = + { "l" } + { "t" } + if$ change.case$ + "edition" bibinfo.check + " " * bbl.edition * + } + if$ +} +INTEGERS { multiresult } +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} +FUNCTION {format.pages} +{ pages duplicate$ empty$ 'skip$ + { duplicate$ multi.page.check + { + n.dashify + } + { + } + if$ + "pages" bibinfo.check + } + if$ +} +FUNCTION {format.journal.pages} +{ pages duplicate$ empty$ 'pop$ + { swap$ duplicate$ empty$ + { pop$ pop$ format.pages } + { + ": " * + swap$ + n.dashify + "pages" bibinfo.check + * + } + if$ + } + if$ +} +FUNCTION {format.journal.eid} +{ eid "eid" bibinfo.check + duplicate$ empty$ 'pop$ + { swap$ duplicate$ empty$ 'skip$ + { + ": " * + } + if$ + swap$ * + } + if$ +} +FUNCTION {format.vol.num.pages} +{ volume field.or.null + duplicate$ empty$ 'skip$ + { + "volume" bibinfo.check + } + if$ + number "number" bibinfo.check duplicate$ empty$ 'skip$ + { + swap$ duplicate$ empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + swap$ + "(" swap$ * ")" * + } + if$ * + eid empty$ + { format.journal.pages } + { format.journal.eid } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { bbl.chapter } + { type "l" change.case$ + "type" bibinfo.check + } + if$ + chapter tie.or.space.prefix + "chapter" bibinfo.check + * * + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.booktitle} +{ + booktitle "booktitle" bibinfo.check + emphasize +} +FUNCTION {format.in.ed.booktitle} +{ format.booktitle duplicate$ empty$ 'skip$ + { + editor "editor" format.names.ed duplicate$ empty$ 'pop$ + { + "," * + " " * + get.bbl.editor + ", " * + * swap$ + * } + if$ + word.in swap$ * + } + if$ +} +FUNCTION {format.thesis.type} +{ type duplicate$ empty$ + 'pop$ + { swap$ pop$ + "t" change.case$ "type" bibinfo.check + } + if$ +} +FUNCTION {format.tr.number} +{ number "number" bibinfo.check + type duplicate$ empty$ + { pop$ bbl.techrep } + 'skip$ + if$ + "type" bibinfo.check + swap$ duplicate$ empty$ + { pop$ "t" change.case$ } + { tie.or.space.prefix * * } + if$ +} +FUNCTION {format.article.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} +FUNCTION {format.book.crossref} +{ volume duplicate$ empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + pop$ word.in + } + { bbl.volume + capitalize + swap$ tie.or.space.prefix "volume" bibinfo.check * * bbl.of space.word * + } + if$ + " \cite{" * crossref * "}" * +} +FUNCTION {format.incoll.inproc.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} +FUNCTION {format.org.or.pub} +{ 't := + "" + address empty$ t empty$ and + 'skip$ + { + address "address" bibinfo.check * + t empty$ + 'skip$ + { address empty$ + 'skip$ + { ": " * } + if$ + t * + } + if$ + } + if$ +} +FUNCTION {format.publisher.address} +{ publisher "publisher" bibinfo.warn format.org.or.pub +} + +FUNCTION {format.organization.address} +{ organization "organization" bibinfo.check format.org.or.pub +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + format.title "title" output.check + new.block + crossref missing$ + { + journal + "journal" bibinfo.check + emphasize + "journal" output.check + format.vol.num.pages output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + format.note output + fin.entry +} +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + format.publisher.address output + } + { + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.isbn output + new.block + format.note output + fin.entry +} +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + format.date "year" output.check + date.block + format.title "title" output.check + new.block + howpublished "howpublished" bibinfo.check output + address "address" bibinfo.check output + format.isbn output + new.block + format.note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + format.btitle "title" output.check + crossref missing$ + { + format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + format.publisher.address output + } + { + format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + crossref missing$ + { format.isbn output } + 'skip$ + if$ + new.block + format.note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + format.publisher.address output + format.edition output + format.isbn output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + format.note output + fin.entry +} +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + new.sentence + publisher empty$ + { format.organization.address output } + { organization "organization" bibinfo.check output + format.publisher.address output + } + if$ + format.isbn output + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + format.note output + fin.entry +} +FUNCTION {conference} { inproceedings } +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + format.date "year" output.check + date.block + format.btitle "title" output.check + organization address new.block.checkb + organization "organization" bibinfo.check output + address "address" bibinfo.check output + format.edition output + new.block + format.note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + format.btitle + "title" output.check + new.block + bbl.mthesis format.thesis.type output.nonnull + school "school" bibinfo.warn output + address "address" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + format.date "year" output.check + date.block + format.title output + new.block + howpublished "howpublished" bibinfo.check output + new.block + format.note output + format.eprint output + fin.entry +} +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + format.btitle + "title" output.check + new.block + bbl.phdthesis format.thesis.type output.nonnull + school "school" bibinfo.warn output + address "address" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + format.editors output + editor format.key output + format.date "year" output.check + date.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + new.sentence + publisher empty$ + { format.organization.address output } + { organization "organization" bibinfo.check output + format.publisher.address output + } + if$ + format.isbn output + new.block + format.note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + format.title + "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" bibinfo.warn output + address "address" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + format.title "title" output.check + new.block + format.note "note" output.check + fin.entry +} + +FUNCTION {default.type} { misc } +READ +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} +INTEGERS { len } +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} +FUNCTION {format.lab.names} +{'s := + "" 't := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ + 't := + nameptr #1 > + { + nameptr #2 = + numnames #3 > and + { "others" 't := + #1 'namesleft := } + 'skip$ + if$ + namesleft #1 > + { ", " * t * } + { + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " " * bbl.etal * + } + { + numnames #2 > + { "," * } + 'skip$ + if$ + bbl.and + space.word * t * + } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.label} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.label + 'author.key.label + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + short.list key field.or.null = or + { pop$ "" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv{ } }{ll{ }}{ f{ }}{ jj{ }}" + format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" 't := } + 'skip$ + if$ + t sortify * + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} +FUNCTION {editor.sort} +{ editor empty$ + { key empty$ + { "to sort, need editor or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ +} +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.sort + 'author.sort + if$ + } + if$ + #1 entry.max$ substring$ + 'sort.label := + sort.label + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} +SORT +STRINGS { last.label next.extra } +INTEGERS { last.extra.num last.extra.num.extended last.extra.num.blank number.label } +FUNCTION {initialize.extra.label.stuff} +{ #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'last.extra.num := + "a" chr.to.int$ #1 - 'last.extra.num.blank := + last.extra.num.blank 'last.extra.num.extended := + #0 'number.label := +} +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num "z" chr.to.int$ > + { "a" chr.to.int$ 'last.extra.num := + last.extra.num.extended #1 + 'last.extra.num.extended := + } + 'skip$ + if$ + last.extra.num.extended last.extra.num.blank > + { last.extra.num.extended int.to.chr$ + last.extra.num int.to.chr$ + * 'extra.label := } + { last.extra.num int.to.chr$ 'extra.label := } + if$ + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} +EXECUTE {initialize.extra.label.stuff} +ITERATE {forward.pass} +REVERSE {reverse.pass} +FUNCTION {bib.sort.order} +{ sort.label + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} +ITERATE {bib.sort.order} +SORT +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\providecommand{\natexlab}[1]{#1}" + write$ newline$ +} +EXECUTE {begin.bib} +EXECUTE {init.state.consts} +ITERATE {call.type$} +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} +EXECUTE {end.bib} +%% End of customized bst file +%% +%% End of file `aaai2026.bst'. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.sty new file mode 100644 index 0000000..1c587a5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/aaai2026/aaai2026.sty @@ -0,0 +1,315 @@ +\NeedsTeXFormat{LaTeX2e}% +\ProvidesPackage{aaai2026}[2026/04/29 AAAI 2026 Submission format]% +\def\year{2026}% +\typeout{Conference Style for AAAI for LaTeX 2e -- version for submission}% +% +\def\copyright@on{T} +\def\showauthors@on{T} +\def\nocopyright{\gdef\copyright@on{}} % Copyright notice is required for camera-ready only. +\DeclareOption{submission}{% + \gdef\copyright@on{}% + \gdef\showauthors@on{}% + \long\gdef\pdfinfo #1{\relax}% +}% +\DeclareOption{draft}{% + \gdef\copyright@on{}% +}% +\ProcessOptions\relax% +% WARNING: IF YOU ARE USING THIS STYLE SHEET FOR AN AAAI PUBLICATION, YOU +% MAY NOT MODIFY IT FOR ANY REASON. MODIFICATIONS (IN YOUR SOURCE +% OR IN THIS STYLE SHEET WILL RESULT IN REJECTION OF YOUR PAPER). +% +% WARNING: This style is NOT guaranteed to work. It is provided in the +% hope that it might make the preparation of papers easier, but this style +% file is provided "as is" without warranty of any kind, either express or +% implied, including but not limited to the implied warranties of +% merchantability, fitness for a particular purpose, or noninfringement. +% You use this style file at your own risk. Standard disclaimers apply. +% There are undoubtably bugs in this style. If you would like to submit +% bug fixes, improvements, etc. please let us know. Please use the contact form +% at www.aaai.org. +% +% Do not use this file unless you are an experienced LaTeX user. +% +% PHYSICAL PAGE LAYOUT +\setlength\topmargin{-0.25in} \setlength\oddsidemargin{-0.25in} +\setlength\textheight{9.0in} \setlength\textwidth{7.0in} +\setlength\columnsep{0.375in} \newlength\titlebox \setlength\titlebox{2.25in} +\setlength\headheight{0pt} \setlength\headsep{0pt} +%\setlength\footheight{0pt} \setlength\footskip{0pt} +\thispagestyle{empty} \pagestyle{empty} +\flushbottom \twocolumn \sloppy +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} +% gf: PRINT COPYRIGHT NOTICE +\def\copyright@year{\number\year} +\def\copyright@text{Copyright \copyright\space \copyright@year, +Association for the Advancement of Artificial Intelligence (www.aaai.org). +All rights reserved.} +\def\copyrighttext#1{\gdef\copyright@on{T}\gdef\copyright@text{#1}} +\def\copyrightyear#1{\gdef\copyright@on{T}\gdef\copyright@year{#1}} +% gf: End changes for copyright notice (used in \maketitle, below) +% Title stuff, taken from deproc. +% +\def\maketitle{% + \par% + \begingroup % to make the footnote style local to the title + \def\thefootnote{\fnsymbol{footnote}} + \twocolumn[\@maketitle] \@thanks% + \endgroup% + % Insert copyright slug unless turned off + \if T\copyright@on\insert\footins{\noindent\footnotesize\copyright@text}\fi% + % + \setcounter{footnote}{0}% + \let\maketitle\relax% + \let\@maketitle\relax% + \gdef\@thanks{}% + \gdef\@author{}% + \gdef\@title{}% + \let\thanks\relax% +}% +\long\gdef\affiliations #1{ \def \affiliations_{\if T\showauthors@on#1\fi}}% +% +\def\@maketitle{% + \def\theauthors{\if T\showauthors@on\@author\else Anonymous submission\fi} + \newcounter{eqfn}\setcounter{eqfn}{0}% + \newsavebox{\titlearea} + \sbox{\titlearea}{ + \let\footnote\relax\let\thanks\relax% + \setcounter{footnote}{0}% + \def\equalcontrib{% + \ifnum\value{eqfn}=0% + \footnote{These authors contributed equally.}% + \setcounter{eqfn}{\value{footnote}}% + \else% + \footnotemark[\value{eqfn}]% + \fi% + }% + \vbox{% + \hsize\textwidth% + \linewidth\hsize% + \vskip 0.625in minus 0.125in% + \centering% + {\LARGE\bf \@title \par}% + \vskip 0.1in plus 0.5fil minus 0.05in% + {\Large{\textbf{\theauthors\ifhmode\\\fi}}}% + \vskip .2em plus 0.25fil% + {\normalsize \affiliations_\ifhmode\\\fi}% + \vskip 1em plus 2fil% + }% + }% +% + \newlength\actualheight% + \settoheight{\actualheight}{\usebox{\titlearea}}% + \ifdim\actualheight>\titlebox% + \setlength{\titlebox}{\actualheight}% + \fi% +% + \vbox to \titlebox {% + \let\footnote\thanks\relax% + \setcounter{footnote}{0}% + \def\equalcontrib{% + \ifnum\value{eqfn}=0% + \footnote{These authors contributed equally.}% + \setcounter{eqfn}{\value{footnote}}% + \else% + \footnotemark[\value{eqfn}]% + \fi% + }% + \hsize\textwidth% + \linewidth\hsize% + \vskip 0.625in minus 0.125in% + \centering% + {\LARGE\bf \@title \par}% + \vskip 0.1in plus 0.5fil minus 0.05in% + {\Large{\textbf{\theauthors\ifhmode\\\fi}}}% + \vskip .2em plus 0.25fil% + {\normalsize \affiliations_\ifhmode\\\fi}% + \vskip 1em plus 2fil% + }% +}% +% +\renewenvironment{abstract}{% + \centerline{\bf Abstract}% + \vspace{0.5ex}% + \setlength{\leftmargini}{10pt}% + \begin{quote}% + \small% +}{% + \par% + \end{quote}% + \vskip 1ex% +}% +\newenvironment{links}{% + \newcommand{\link}[2]{\par\textbf{##1} --- \url{##2}}% + \setlength{\hangindent}{10pt}% + \setlength{\parskip}{2pt}% + \begin{flushleft}% +}{% + \end{flushleft}% + \vskip 1ex% +}% +% jsp added: +\def\pubnote#1{ + \thispagestyle{myheadings}% + \pagestyle{myheadings}% + \markboth{#1}{#1}% + \setlength\headheight{10pt}% + \setlength\headsep{10pt}% +}% +% +% SECTIONS with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus +-0.5ex minus -.2ex}{3pt plus 2pt minus 1pt}{\Large\bf\centering}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-2.0ex plus +-0.5ex minus -.2ex}{3pt plus 2pt minus 1pt}{\large\bf\raggedright}} +\def\subsubsection{\@startsection{subparagraph}{3}{\z@}{-6pt plus +%%% DIEGO changed: 29/11/2009 +%% 2pt minus 1pt}{-1em}{\normalsize\bf}} +-2pt minus -1pt}{-1em}{\normalsize\bf}} +%%% END changed +\renewcommand\paragraph{\@startsection{paragraph}{4}{\z@}{-6pt plus -2pt minus -1pt}{-1em}{\normalsize\bf}}% +\setcounter{secnumdepth}{0} +% add period to section (but not subsection) numbers, reduce space after +%\renewcommand{\thesection} +% {\arabic{section}.\hskip-0.6em} +%\renewcommand{\thesubsection} +% {\arabic{section}.\arabic{subsection}\hskip-0.6em} +% FOOTNOTES +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } +\setcounter{footnote}{0} +% LISTS AND PARAGRAPHS +\parindent 10pt +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 0.5pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt +\leftmargin 10pt \leftmargini 13pt \leftmarginii 10pt \leftmarginiii 5pt \leftmarginiv 5pt \leftmarginv 5pt \leftmarginvi 5pt +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii +\labelwidth\leftmarginii\advance\labelwidth-\labelsep +\topsep 2pt plus 1pt minus 0.5pt +\parsep 1pt plus 0.5pt minus 0.5pt +\itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii +\labelwidth\leftmarginiii\advance\labelwidth-\labelsep +\topsep 1pt plus 0.5pt minus 0.5pt +\parsep \z@ +\partopsep 0.5pt plus 0pt minus 0.5pt +\itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv +\labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv +\labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi +\labelwidth\leftmarginvi\advance\labelwidth-\labelsep} +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +\def\normalsize{\@setfontsize\normalsize\@xpt{11}} % 10 point on 11 +\def\small{\@setfontsize\small\@ixpt{10}} % 9 point on 10 +\def\footnotesize{\@setfontsize\footnotesize\@ixpt{10}} % 9 point on 10 +\def\scriptsize{\@setfontsize\scriptsize\@viipt{10}} % 7 point on 8 +\def\tiny{\@setfontsize\tiny\@vipt{7}} % 6 point on 7 +\def\large{\@setfontsize\large\@xipt{12}} % 11 point on 12 +\def\Large{\@setfontsize\Large\@xiipt{14}} % 12 point on 14 +\def\LARGE{\@setfontsize\LARGE\@xivpt{16}} % 14 point on 16 +\def\huge{\@setfontsize\huge\@xviipt{20}} % 17 point on 20 +\def\Huge{\@setfontsize\Huge\@xxpt{23}} % 20 point on 23 + +\AtBeginDocument{% + \@ifpackageloaded{natbib}% + {% + % When natbib is in use, set the proper style and fix a few things + \let\cite\citep + \let\shortcite\citeyearpar + \setcitestyle{aysep={}} + \setlength\bibhang{0pt} + \bibliographystyle{aaai2026} + }{}% + \@ifpackageloaded{hyperref}% + {% + \PackageError{aaai}{You must not use hyperref in AAAI papers.}{You (or one of the packages you imported) are importing the hyperref package, which is forbidden in AAAI papers. You must remove it from the paper to proceed.} + }{}% + \@ifpackageloaded{bbm}% + {% + \PackageError{aaai}{You must not use bbm package in AAAI papers because it introduces Type 3 fonts which are forbidden.}{See https://tex.stackexchange.com/questions/479160/a-replacement-to-mathbbm1-with-type-1-fonts for possible alternatives.} + }{}% + \@ifpackageloaded{authblk}% + {% + \PackageError{aaai}{Package authblk is forbbidden.}{Package authblk is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{balance}% + {% + \PackageError{aaai}{Package balance is forbbidden.}{Package balance is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{CJK}% + {% + \PackageError{aaai}{Package CJK is forbbidden.}{Package CJK is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{flushend}% + {% + \PackageError{aaai}{Package flushend is forbbidden.}{Package flushend is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{fontenc}% + {% + \PackageError{aaai}{Package fontenc is forbbidden.}{Package fontenc is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{fullpage}% + {% + \PackageError{aaai}{Package fullpage is forbbidden.}{Package fullpage is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{geometry}% + {% + \PackageError{aaai}{Package geometry is forbbidden.}{Package geometry is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{grffile}% + {% + \PackageError{aaai}{Package grffile is forbbidden.}{Package grffile is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{navigator}% + {% + \PackageError{aaai}{Package navigator is forbbidden.}{Package navigator is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{savetrees}% + {% + \PackageError{aaai}{Package savetrees is forbbidden.}{Package savetrees is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{setspace}% + {% + \PackageError{aaai}{Package setspace is forbbidden.}{Package setspace is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{stfloats}% + {% + \PackageError{aaai}{Package stfloats is forbbidden.}{Package stfloats is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{tabu}% + {% + \PackageError{aaai}{Package tabu is forbbidden.}{Package tabu is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{titlesec}% + {% + \PackageError{aaai}{Package titlesec is forbbidden.}{Package titlesec is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{tocbibind}% + {% + \PackageError{aaai}{Package tocbibind is forbbidden.}{Package tocbibind is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{ulem}% + {% + \PackageError{aaai}{Package ulem is forbbidden.}{Package ulem is forbbiden. You must find an alternative.} + }{}% + \@ifpackageloaded{wrapfig}% + {% + \PackageError{aaai}{Package wrapfig is forbbidden.}{Package wrapfig is forbbiden. You must find an alternative.} + }{}% +} + +\let\endthebibliography=\endlist diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/README.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/README.md new file mode 100644 index 0000000..a940427 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/README.md @@ -0,0 +1,50 @@ +# *ACL Paper Styles + +This directory contains the latest LaTeX templates for *ACL conferences. + +## Instructions for authors + +Paper submissions to *ACL conferences must use the official ACL style +templates. + +The LaTeX style files are available + +- as an [Overleaf template](https://www.overleaf.com/latex/templates/association-for-computational-linguistics-acl-conference/jvxskxpnznfj) +- in this repository +- as a [.zip file](https://github.com/acl-org/acl-style-files/archive/refs/heads/master.zip) + +Please see [`acl_latex.tex`](https://github.com/acl-org/acl-style-files/blob/master/acl_latex.tex) for an example. + +Please follow the paper formatting guidelines general to *ACL +conferences: + +- [Paper formatting guidelines](https://acl-org.github.io/ACLPUB/formatting.html) + +Authors may not modify these style files or use templates designed for +other conferences. + +## Instructions for publications chairs + +To adapt the style files for your conference, please fork this repository and +make necessary changes. Minimally, you'll need to update the name of +the conference and rename the files. + +If you make improvements to the templates that should be propagated to +future conferences, please submit a pull request. Thank you in +advance! + +In older versions of the templates, authors were asked to fill in the +START submission ID so that it would be stamped at the top of each +page of the anonymized version. This is no longer needed, because it +is now possible to do this stamping automatically within +START. Currently, the way to do this is for the program chair to email +support@softconf.com and request it. + +## Instructions for making changes to style files + +- merge pull request in github, or push to github +- git pull from github to a local repository +- then, git push from your local repository to overleaf project + - Overleaf project is https://www.overleaf.com/project/5f64f1fb97c4c50001b60549 + - Overleaf git url is https://git.overleaf.com/5f64f1fb97c4c50001b60549 +- then, click "Submit" and then "Submit as Template" in overleaf in order to ask overleaf to update the overleaf template from the overleaf project diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl.sty new file mode 100644 index 0000000..d9b74d0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl.sty @@ -0,0 +1,312 @@ +% This is the LaTex style file for *ACL. +% The official sources can be found at +% +% https://github.com/acl-org/acl-style-files/ +% +% This package is activated by adding +% +% \usepackage{acl} +% +% to your LaTeX file. When submitting your paper for review, add the "review" option: +% +% \usepackage[review]{acl} + +\newif\ifacl@finalcopy +\newif\ifacl@anonymize +\newif\ifacl@linenumbers +\newif\ifacl@pagenumbers +\DeclareOption{final}{\acl@finalcopytrue\acl@anonymizefalse\acl@linenumbersfalse\acl@pagenumbersfalse} +\DeclareOption{review}{\acl@finalcopyfalse\acl@anonymizetrue\acl@linenumberstrue\acl@pagenumberstrue} +\DeclareOption{preprint}{\acl@finalcopytrue\acl@anonymizefalse\acl@linenumbersfalse\acl@pagenumberstrue} +\ExecuteOptions{final} % final copy is the default + +% include hyperref, unless user specifies nohyperref option like this: +% \usepackage[nohyperref]{acl} +\newif\ifacl@hyperref +\DeclareOption{hyperref}{\acl@hyperreftrue} +\DeclareOption{nohyperref}{\acl@hyperreffalse} +\ExecuteOptions{hyperref} % default is to use hyperref +\ProcessOptions\relax + +\typeout{Conference Style for ACL} + +\usepackage{xcolor} + +\ifacl@linenumbers + % Add draft line numbering via the lineno package + % https://texblog.org/2012/02/08/adding-line-numbers-to-documents/ + \usepackage[switch,mathlines]{lineno} + + % Line numbers in gray Helvetica 8pt + \font\aclhv = phvb at 8pt + \renewcommand\linenumberfont{\aclhv\color{lightgray}} + + % Zero-fill line numbers + % NUMBER with left flushed zeros \fillzeros[<WIDTH>]<NUMBER> + \newcount\cv@tmpc@ \newcount\cv@tmpc + \def\fillzeros[#1]#2{\cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi + \cv@tmpc=1 % + \loop\ifnum\cv@tmpc@<10 \else \divide\cv@tmpc@ by 10 \advance\cv@tmpc by 1 \fi + \ifnum\cv@tmpc@=10\relax\cv@tmpc@=11\relax\fi \ifnum\cv@tmpc@>10 \repeat + \ifnum#2<0\advance\cv@tmpc1\relax-\fi + \loop\ifnum\cv@tmpc<#1\relax0\advance\cv@tmpc1\relax\fi \ifnum\cv@tmpc<#1 \repeat + \cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi \relax\the\cv@tmpc@}% + \renewcommand\thelinenumber{\fillzeros[3]{\arabic{linenumber}}} + \AtBeginDocument{\linenumbers} + + \setlength{\linenumbersep}{1.6cm} + + % Bug: An equation with $$ ... $$ isn't numbered, nor is the previous line. + + % Patch amsmath commands so that the previous line and the equation itself + % are numbered. Bug: multline has an extra line number. + % https://tex.stackexchange.com/questions/461186/how-to-use-lineno-with-amsmath-align + \usepackage{etoolbox} %% <- for \pretocmd, \apptocmd and \patchcmd + + \newcommand*\linenomathpatch[1]{% + \expandafter\pretocmd\csname #1\endcsname {\linenomath}{}{}% + \expandafter\pretocmd\csname #1*\endcsname {\linenomath}{}{}% + \expandafter\apptocmd\csname end#1\endcsname {\endlinenomath}{}{}% + \expandafter\apptocmd\csname end#1*\endcsname {\endlinenomath}{}{}% + } + \newcommand*\linenomathpatchAMS[1]{% + \expandafter\pretocmd\csname #1\endcsname {\linenomathAMS}{}{}% + \expandafter\pretocmd\csname #1*\endcsname {\linenomathAMS}{}{}% + \expandafter\apptocmd\csname end#1\endcsname {\endlinenomath}{}{}% + \expandafter\apptocmd\csname end#1*\endcsname {\endlinenomath}{}{}% + } + + %% Definition of \linenomathAMS depends on whether the mathlines option is provided + \expandafter\ifx\linenomath\linenomathWithnumbers + \let\linenomathAMS\linenomathWithnumbers + %% The following line gets rid of an extra line numbers at the bottom: + \patchcmd\linenomathAMS{\advance\postdisplaypenalty\linenopenalty}{}{}{} + \else + \let\linenomathAMS\linenomathNonumbers + \fi + + \AtBeginDocument{% + \linenomathpatch{equation}% + \linenomathpatchAMS{gather}% + \linenomathpatchAMS{multline}% + \linenomathpatchAMS{align}% + \linenomathpatchAMS{alignat}% + \linenomathpatchAMS{flalign}% + } +\else + % Hack to ignore these commands, which review mode puts into the .aux file. + \newcommand{\@LN@col}[1]{} + \newcommand{\@LN}[2]{} + \newcommand{\nolinenumbers}{} +\fi + +\PassOptionsToPackage{a4paper,margin=2.5cm,heightrounded=true}{geometry} +\RequirePackage{geometry} + +\setlength\columnsep{0.6cm} +\newlength\titlebox +\setlength\titlebox{11\baselineskip} +% \titlebox should be a multiple of \baselineskip so that +% column height remaining fits an exact number of lines of text + +\flushbottom \twocolumn \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +\ifacl@pagenumbers + \pagenumbering{arabic} +\else + \thispagestyle{empty} + \pagestyle{empty} +\fi + +%% Title and Authors %% + +\let\Thanks\thanks % \Thanks and \thanks used to be different, but keep this for backwards compatibility. + +\newcommand\outauthor{% + \begin{tabular}[t]{c} + \ifacl@anonymize + \bfseries Anonymous ACL submission + \else + \bfseries\@author + \fi + \end{tabular}} + +% Mostly taken from deproc. +\AtBeginDocument{ +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \twocolumn[\@maketitle] + \@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax + \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} +\def\@maketitle{\vbox to \titlebox{\hsize\textwidth + \linewidth\hsize \vskip 0.125in minus 0.125in \centering + {\Large\bfseries \@title \par} \vskip 0.2in plus 1fil minus 0.1in + {\def\and{\unskip\enspace{\rmfamily and}\enspace}% + \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bfseries}% + \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup + \vskip 0.25in plus 1fil minus 0.125in + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bfseries} + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss + \outauthor + \hss\egroup + \hfil\hfil\egroup} + \vskip 0.3in plus 2fil minus 0.1in +}} +} + +% margins and font size for abstract +\renewenvironment{abstract}% + {\begin{center}\large\textbf{\abstractname}\end{center}% + \begin{list}{}% + {\setlength{\rightmargin}{0.6cm}% + \setlength{\leftmargin}{0.6cm}}% + \item[]\ignorespaces% + \@setsize\normalsize{12pt}\xpt\@xpt + }% + {\unskip\end{list}} + +% Resizing figure and table captions - SL +% Support for interacting with the caption, subfigure, and subcaption packages - SL +\RequirePackage{caption} +\DeclareCaptionFont{10pt}{\fontsize{10pt}{12pt}\selectfont} +\captionsetup{font=10pt} + +\RequirePackage{natbib} +% for citation commands in the .tex, authors can use: +% \citep, \citet, and \citeyearpar for compatibility with natbib, or +% \cite, \newcite, and \shortcite for compatibility with older ACL .sty files +\renewcommand\cite{\citep} % to get "(Author Year)" with natbib +\newcommand\shortcite{\citeyearpar}% to get "(Year)" with natbib +\newcommand\newcite{\citet} % to get "Author (Year)" with natbib +\newcommand{\citeposs}[1]{\citeauthor{#1}'s (\citeyear{#1})} % to get "Author's (Year)" + +\bibliographystyle{acl_natbib} + +% Bibliography + +% Don't put a label in the bibliography at all. Just use the unlabeled format +% instead. +\def\thebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{References\@mkboth + {References}{References}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthebibliography=\endlist + + +% Allow for a bibliography of sources of attested examples +\def\thesourcebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{Sources of Attested Examples\@mkboth + {Sources of Attested Examples}{Sources of Attested Examples}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthesourcebibliography=\endlist + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bfseries\raggedright}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus + -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bfseries\raggedright}} +%% changed by KO to - values to get the initial parindent right +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex plus + -0.5ex minus -.2ex}{0.5ex plus .2ex}{\normalsize\bfseries\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bfseries}} +\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bfseries}} + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 1em +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt + +\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} + +% The hyperref manual (section 9) says hyperref should be loaded after natbib +\ifacl@hyperref + \PassOptionsToPackage{breaklinks}{hyperref} + \RequirePackage{hyperref} + % make links dark blue + \definecolor{darkblue}{rgb}{0, 0, 0.5} + \hypersetup{colorlinks=true, citecolor=darkblue, linkcolor=darkblue, urlcolor=darkblue} +\else + % This definition is used if the hyperref package is not loaded. + % It provides a backup, no-op definiton of \href. + % This is necessary because \href command is used in the acl_natbib.bst file. + \def\href#1#2{{#2}} + \usepackage{url} +\fi diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_latex.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_latex.tex new file mode 100644 index 0000000..2eba2f1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_latex.tex @@ -0,0 +1,377 @@ +\documentclass[11pt]{article} + +% Change "review" to "final" to generate the final (sometimes called camera-ready) version. +% Change to "preprint" to generate a non-anonymous version with page numbers. +\usepackage[review]{acl} + +% Standard package includes +\usepackage{times} +\usepackage{latexsym} + +% For proper rendering and hyphenation of words containing Latin characters (including in bib files) +\usepackage[T1]{fontenc} +% For Vietnamese characters +% \usepackage[T5]{fontenc} +% See https://www.latex-project.org/help/documentation/encguide.pdf for other character sets + +% This assumes your files are encoded as UTF8 +\usepackage[utf8]{inputenc} + +% This is not strictly necessary, and may be commented out, +% but it will improve the layout of the manuscript, +% and will typically save some space. +\usepackage{microtype} + +% This is also not strictly necessary, and may be commented out. +% However, it will improve the aesthetics of text in +% the typewriter font. +\usepackage{inconsolata} + +%Including images in your LaTeX document requires adding +%additional package(s) +\usepackage{graphicx} + +% If the title and author information does not fit in the area allocated, uncomment the following +% +%\setlength\titlebox{<dim>} +% +% and set <dim> to something 5cm or larger. + +\title{Instructions for *ACL Proceedings} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a separate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +\author{First Author \\ + Affiliation / Address line 1 \\ + Affiliation / Address line 2 \\ + Affiliation / Address line 3 \\ + \texttt{email@domain} \\\And + Second Author \\ + Affiliation / Address line 1 \\ + Affiliation / Address line 2 \\ + Affiliation / Address line 3 \\ + \texttt{email@domain} \\} + +%\author{ +% \textbf{First Author\textsuperscript{1}}, +% \textbf{Second Author\textsuperscript{1,2}}, +% \textbf{Third T. Author\textsuperscript{1}}, +% \textbf{Fourth Author\textsuperscript{1}}, +%\\ +% \textbf{Fifth Author\textsuperscript{1,2}}, +% \textbf{Sixth Author\textsuperscript{1}}, +% \textbf{Seventh Author\textsuperscript{1}}, +% \textbf{Eighth Author \textsuperscript{1,2,3,4}}, +%\\ +% \textbf{Ninth Author\textsuperscript{1}}, +% \textbf{Tenth Author\textsuperscript{1}}, +% \textbf{Eleventh E. Author\textsuperscript{1,2,3,4,5}}, +% \textbf{Twelfth Author\textsuperscript{1}}, +%\\ +% \textbf{Thirteenth Author\textsuperscript{3}}, +% \textbf{Fourteenth F. Author\textsuperscript{2,4}}, +% \textbf{Fifteenth Author\textsuperscript{1}}, +% \textbf{Sixteenth Author\textsuperscript{1}}, +%\\ +% \textbf{Seventeenth S. Author\textsuperscript{4,5}}, +% \textbf{Eighteenth Author\textsuperscript{3,4}}, +% \textbf{Nineteenth N. Author\textsuperscript{2,5}}, +% \textbf{Twentieth Author\textsuperscript{1}} +%\\ +%\\ +% \textsuperscript{1}Affiliation 1, +% \textsuperscript{2}Affiliation 2, +% \textsuperscript{3}Affiliation 3, +% \textsuperscript{4}Affiliation 4, +% \textsuperscript{5}Affiliation 5 +%\\ +% \small{ +% \textbf{Correspondence:} \href{mailto:email@domain}{email@domain} +% } +%} + +\begin{document} +\maketitle +\begin{abstract} +This document is a supplement to the general instructions for *ACL authors. It contains instructions for using the \LaTeX{} style files for ACL conferences. +The document itself conforms to its own specifications, and is therefore an example of what your manuscript should look like. +These instructions should be used both for papers submitted for review and for final versions of accepted papers. +\end{abstract} + +\section{Introduction} + +These instructions are for authors submitting papers to *ACL conferences using \LaTeX. They are not self-contained. All authors must follow the general instructions for *ACL proceedings,\footnote{\url{http://acl-org.github.io/ACLPUB/formatting.html}} and this document contains additional instructions for the \LaTeX{} style files. + +The templates include the \LaTeX{} source of this document (\texttt{acl\_latex.tex}), +the \LaTeX{} style file used to format it (\texttt{acl.sty}), +an ACL bibliography style (\texttt{acl\_natbib.bst}), +an example bibliography (\texttt{custom.bib}), +and the bibliography for the ACL Anthology (\texttt{anthology.bib}). + +\section{Engines} + +To produce a PDF file, pdf\LaTeX{} is strongly recommended (over original \LaTeX{} plus dvips+ps2pdf or dvipdf). +The style file \texttt{acl.sty} can also be used with +lua\LaTeX{} and +Xe\LaTeX{}, which are especially suitable for text in non-Latin scripts. +The file \texttt{acl\_lualatex.tex} in this repository provides +an example of how to use \texttt{acl.sty} with either +lua\LaTeX{} or +Xe\LaTeX{}. + +\section{Preamble} + +The first line of the file must be +\begin{quote} +\begin{verbatim} +\documentclass[11pt]{article} +\end{verbatim} +\end{quote} + +To load the style file in the review version: +\begin{quote} +\begin{verbatim} +\usepackage[review]{acl} +\end{verbatim} +\end{quote} +For the final version, omit the \verb|review| option: +\begin{quote} +\begin{verbatim} +\usepackage{acl} +\end{verbatim} +\end{quote} + +To use Times Roman, put the following in the preamble: +\begin{quote} +\begin{verbatim} +\usepackage{times} +\end{verbatim} +\end{quote} +(Alternatives like txfonts or newtx are also acceptable.) + +Please see the \LaTeX{} source of this document for comments on other packages that may be useful. + +Set the title and author using \verb|\title| and \verb|\author|. Within the author list, format multiple authors using \verb|\and| and \verb|\And| and \verb|\AND|; please see the \LaTeX{} source for examples. + +By default, the box containing the title and author names is set to the minimum of 5 cm. If you need more space, include the following in the preamble: +\begin{quote} +\begin{verbatim} +\setlength\titlebox{<dim>} +\end{verbatim} +\end{quote} +where \verb|<dim>| is replaced with a length. Do not set this length smaller than 5 cm. + +\section{Document Body} + +\subsection{Footnotes} + +Footnotes are inserted with the \verb|\footnote| command.\footnote{This is a footnote.} + +\subsection{Tables and figures} + +See Table~\ref{tab:accents} for an example of a table and its caption. +\textbf{Do not override the default caption sizes.} + +\begin{table} + \centering + \begin{tabular}{lc} + \hline + \textbf{Command} & \textbf{Output} \\ + \hline + \verb|{\"a}| & {\"a} \\ + \verb|{\^e}| & {\^e} \\ + \verb|{\`i}| & {\`i} \\ + \verb|{\.I}| & {\.I} \\ + \verb|{\o}| & {\o} \\ + \verb|{\'u}| & {\'u} \\ + \verb|{\aa}| & {\aa} \\\hline + \end{tabular} + \begin{tabular}{lc} + \hline + \textbf{Command} & \textbf{Output} \\ + \hline + \verb|{\c c}| & {\c c} \\ + \verb|{\u g}| & {\u g} \\ + \verb|{\l}| & {\l} \\ + \verb|{\~n}| & {\~n} \\ + \verb|{\H o}| & {\H o} \\ + \verb|{\v r}| & {\v r} \\ + \verb|{\ss}| & {\ss} \\ + \hline + \end{tabular} + \caption{Example commands for accented characters, to be used in, \emph{e.g.}, Bib\TeX{} entries.} + \label{tab:accents} +\end{table} + +As much as possible, fonts in figures should conform +to the document fonts. See Figure~\ref{fig:experiments} for an example of a figure and its caption. + +Using the \verb|graphicx| package graphics files can be included within figure +environment at an appropriate point within the text. +The \verb|graphicx| package supports various optional arguments to control the +appearance of the figure. +You must include it explicitly in the \LaTeX{} preamble (after the +\verb|\documentclass| declaration and before \verb|\begin{document}|) using +\verb|\usepackage{graphicx}|. + +\begin{figure}[t] + \includegraphics[width=\columnwidth]{example-image-golden} + \caption{A figure with a caption that runs for more than one line. + Example image is usually available through the \texttt{mwe} package + without even mentioning it in the preamble.} + \label{fig:experiments} +\end{figure} + +\begin{figure*}[t] + \includegraphics[width=0.48\linewidth]{example-image-a} \hfill + \includegraphics[width=0.48\linewidth]{example-image-b} + \caption {A minimal working example to demonstrate how to place + two images side-by-side.} +\end{figure*} + +\subsection{Hyperlinks} + +Users of older versions of \LaTeX{} may encounter the following error during compilation: +\begin{quote} +\verb|\pdfendlink| ended up in different nesting level than \verb|\pdfstartlink|. +\end{quote} +This happens when pdf\LaTeX{} is used and a citation splits across a page boundary. The best way to fix this is to upgrade \LaTeX{} to 2018-12-01 or later. + +\subsection{Citations} + +\begin{table*} + \centering + \begin{tabular}{lll} + \hline + \textbf{Output} & \textbf{natbib command} & \textbf{ACL only command} \\ + \hline + \citep{Gusfield:97} & \verb|\citep| & \\ + \citealp{Gusfield:97} & \verb|\citealp| & \\ + \citet{Gusfield:97} & \verb|\citet| & \\ + \citeyearpar{Gusfield:97} & \verb|\citeyearpar| & \\ + \citeposs{Gusfield:97} & & \verb|\citeposs| \\ + \hline + \end{tabular} + \caption{\label{citation-guide} + Citation commands supported by the style file. + The style is based on the natbib package and supports all natbib citation commands. + It also supports commands defined in previous ACL style files for compatibility. + } +\end{table*} + +Table~\ref{citation-guide} shows the syntax supported by the style files. +We encourage you to use the natbib styles. +You can use the command \verb|\citet| (cite in text) to get ``author (year)'' citations, like this citation to a paper by \citet{Gusfield:97}. +You can use the command \verb|\citep| (cite in parentheses) to get ``(author, year)'' citations \citep{Gusfield:97}. +You can use the command \verb|\citealp| (alternative cite without parentheses) to get ``author, year'' citations, which is useful for using citations within parentheses (e.g. \citealp{Gusfield:97}). + +A possessive citation can be made with the command \verb|\citeposs|. +This is not a standard natbib command, so it is generally not compatible +with other style files. + +\subsection{References} + +\nocite{Ando2005,andrew2007scalable,rasooli-tetrault-2015} + +The \LaTeX{} and Bib\TeX{} style files provided roughly follow the American Psychological Association format. +If your own bib file is named \texttt{custom.bib}, then placing the following before any appendices in your \LaTeX{} file will generate the references section for you: +\begin{quote} +\begin{verbatim} +\bibliography{custom} +\end{verbatim} +\end{quote} + +You can obtain the complete ACL Anthology as a Bib\TeX{} file from \url{https://aclweb.org/anthology/anthology.bib.gz}. +To include both the Anthology and your own .bib file, use the following instead of the above. +\begin{quote} +\begin{verbatim} +\bibliography{anthology,custom} +\end{verbatim} +\end{quote} + +Please see Section~\ref{sec:bibtex} for information on preparing Bib\TeX{} files. + +\subsection{Equations} + +An example equation is shown below: +\begin{equation} + \label{eq:example} + A = \pi r^2 +\end{equation} + +Labels for equation numbers, sections, subsections, figures and tables +are all defined with the \verb|\label{label}| command and cross references +to them are made with the \verb|\ref{label}| command. + +This an example cross-reference to Equation~\ref{eq:example}. + +\subsection{Appendices} + +Use \verb|\appendix| before any appendix section to switch the section numbering over to letters. See Appendix~\ref{sec:appendix} for an example. + +\section{Bib\TeX{} Files} +\label{sec:bibtex} + +Unicode cannot be used in Bib\TeX{} entries, and some ways of typing special characters can disrupt Bib\TeX's alphabetization. The recommended way of typing special characters is shown in Table~\ref{tab:accents}. + +Please ensure that Bib\TeX{} records contain DOIs or URLs when possible, and for all the ACL materials that you reference. +Use the \verb|doi| field for DOIs and the \verb|url| field for URLs. +If a Bib\TeX{} entry has a URL or DOI field, the paper title in the references section will appear as a hyperlink to the paper, using the hyperref \LaTeX{} package. + +\section*{Limitations} + +This document does not cover the content requirements for ACL or any +other specific venue. Check the author instructions for +information on +maximum page lengths, the required ``Limitations'' section, +and so on. + +\section*{Acknowledgments} + +This document has been adapted +by Steven Bethard, Ryan Cotterell and Rui Yan +from the instructions for earlier ACL and NAACL proceedings, including those for +ACL 2019 by Douwe Kiela and Ivan Vuli\'{c}, +NAACL 2019 by Stephanie Lukin and Alla Roskovskaya, +ACL 2018 by Shay Cohen, Kevin Gimpel, and Wei Lu, +NAACL 2018 by Margaret Mitchell and Stephanie Lukin, +Bib\TeX{} suggestions for (NA)ACL 2017/2018 from Jason Eisner, +ACL 2017 by Dan Gildea and Min-Yen Kan, +NAACL 2017 by Margaret Mitchell, +ACL 2012 by Maggie Li and Michael White, +ACL 2010 by Jing-Shin Chang and Philipp Koehn, +ACL 2008 by Johanna D. Moore, Simone Teufel, James Allan, and Sadaoki Furui, +ACL 2005 by Hwee Tou Ng and Kemal Oflazer, +ACL 2002 by Eugene Charniak and Dekang Lin, +and earlier ACL and EACL formats written by several people, including +John Chen, Henry S. Thompson and Donald Walker. +Additional elements were taken from the formatting instructions of the \emph{International Joint Conference on Artificial Intelligence} and the \emph{Conference on Computer Vision and Pattern Recognition}. + +% Bibliography entries for the entire Anthology, followed by custom entries +%\bibliography{custom,anthology-overleaf-1,anthology-overleaf-2} + +% Custom bibliography entries only +\bibliography{custom} + +\appendix + +\section{Example Appendix} +\label{sec:appendix} + +This is an appendix. + +\end{document} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_lualatex.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_lualatex.tex new file mode 100644 index 0000000..6684e89 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_lualatex.tex @@ -0,0 +1,101 @@ +% This file compiles with both LuaLaTeX and XeLaTeX +\documentclass[11pt]{article} + +% Change "review" to "final" to generate the final (sometimes called camera-ready) version. +% Change to "preprint" to generate a non-anonymous version with page numbers. +\usepackage[review]{acl} + +% This is not strictly necessary, and may be commented out, +% but it will improve the layout of the manuscript, +% and will typically save some space. + \usepackage{microtype} + +% If the title and author information does not fit in the area allocated, uncomment the following +% +%\setlength\titlebox{<dim>} +% +% and set <dim> to something 5cm or larger. + +% These font selection commands work with +% LuaLaTeX and XeLaTeX, but not pdfLaTeX. +\usepackage[english,bidi=default]{babel} % English as the main language. +\babelfont{rm}{TeXGyreTermesX} % similar to Times +%%% include whatever languages you need below this line +\babelprovide[import]{hindi} +\babelfont[*devanagari]{rm}{Lohit Devanagari} +\babelprovide[import]{arabic} +\babelfont[*arabic]{rm}{Noto Sans Arabic} + + +%\usepackage{polyglossia} +%\setdefaultlanguage{english} +%\setotherlanguages{arabic,russian,thai,hindi,kannada} + +%%%%% + + +\title{LuaLaTeX and XeLaTeX Template for *ACL Style Files} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a seperate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +\author{First Author \\ + Affiliation / Address line 1 \\ + Affiliation / Address line 2 \\ + Affiliation / Address line 3 \\ + \texttt{email@domain} \\\And + Second Author \\ + Affiliation / Address line 1 \\ + Affiliation / Address line 2 \\ + Affiliation / Address line 3 \\ + \texttt{email@domain} \\} + +\begin{document} + +\maketitle +\begin{abstract} +This document provides an example showing how +to use the *ACL style files with either +LuaLaTeX or XeLaTeX. +\end{abstract} + + +\section{Introduction} + +Please see the general instructions +in the file \verb|acl_latex.tex|. + +Here are some examples of text in various languages. + +Hindi: \foreignlanguage{hindi}{मानव अधिकारों की सार्वभौम घोषणा} + +Arabic: \foreignlanguage{arabic}{الإعلان العالمي لحقوق الإنسان} + +Here is an example citation: +\citet{Gusfield:97} argues that... + + +% Entries for the entire Anthology, followed by custom entries +\bibliography{custom} + +\appendix + +\section{Example Appendix} +\label{sec:appendix} + +This is an appendix. + +\end{document} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_natbib.bst b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_natbib.bst new file mode 100644 index 0000000..4919681 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/acl_natbib.bst @@ -0,0 +1,1940 @@ +%%% Modification of BibTeX style file acl_natbib_nourl.bst +%%% ... by urlbst, version 0.9.1 (marked with "% urlbst") +%%% See <https://purl.org/nxg/dist/urlbst> and repository <https://heptapod.host/nxg/urlbst> +%%% Modifications Copyright 2002–23, Norman Gray, +%%% and distributed under the terms of the LPPL; see README for discussion. +%%% +%%% Added webpage entry type, and url and lastchecked fields. +%%% Added eprint support. +%%% Added DOI support. +%%% Added PUBMED support. +%%% Added hyperref support. +%%% Original headers follow... + +%% +%% This is file `acl_natbib_basic.bst', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% merlin.mbs (with options: `ay,nat,pres,ed-au,keyxyr,blkyear,dt-beg,yr-per,note-yr,num-xser,pre-edn,xedn,nfss') +%% ---------------------------------------- +%% *** Intended for ACL conferences *** +%% +%% Copyright 1994-2011 Patrick W Daly + % =============================================================== + % IMPORTANT NOTICE: + % This bibliographic style (bst) file has been generated from one or + % more master bibliographic style (mbs) files, listed above. + % + % This generated file can be redistributed and/or modified under the terms + % of the LaTeX Project Public License Distributed from CTAN + % archives in directory macros/latex/base/lppl.txt; either + % version 1 of the License, or any later version. + % =============================================================== + % Name and version information of the main mbs file: + % \ProvidesFile{merlin.mbs}[2011/11/18 4.33 (PWD, AO, DPC)] + % For use with BibTeX version 0.99a or later + %------------------------------------------------------------------- + % This bibliography style file is intended for texts in ENGLISH + % This is an author-year citation style bibliography. As such, it is + % non-standard LaTeX, and requires a special package file to function properly. + % Such a package is natbib.sty by Patrick W. Daly + % The form of the \bibitem entries is + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Smith]{key}... + % The essential feature is that the label (the part in brackets) consists + % of the author names, as they should appear in the citation, with the year + % in parentheses following. There must be no space before the opening + % parenthesis! + % With natbib v5.3, a full list of authors may also follow the year. + % In natbib.sty, it is possible to define the type of enclosures that is + % really wanted (brackets or parentheses), but in either case, there must + % be parentheses in the label. + % The \cite command functions as follows: + % \citet{key} ==>> Jones et al. (1990) + % \citet*{key} ==>> Jones, Baker, and Smith (1990) + % \citep{key} ==>> (Jones et al., 1990) + % \citep*{key} ==>> (Jones, Baker, and Smith, 1990) + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.][]{key} ==>> (e.g. Jones et al., 1990) + % \citep[e.g.][p. 32]{key} ==>> (e.g. Jones et al., 1990, p. 32) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Smith + % \citeyear{key} ==>> 1990 + %--------------------------------------------------------------------- + +%% 2025 modified to truncate author lists of more than 20 authors + +ENTRY + { address + archivePrefix + author + booktitle + chapter + edition + editor + eid + eprint + eprinttype % = archivePrefix + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + doi % urlbst + pubmed % urlbst + url % urlbst + lastchecked % urlbst + } + {} + { label extra.label sort.label short.list } +INTEGERS { output.state before.all mid.sentence after.sentence after.block } +% urlbst... +% urlbst constants and state variables +STRINGS { urlintro + eprinturl eprintprefix doiprefix doiurl pubmedprefix pubmedurl + citedstring onlinestring linktextstring + openinlinelink closeinlinelink } +INTEGERS { hrefform doiform inlinelinks makeinlinelink + addeprints adddoi addpubmed } +FUNCTION {init.urlbst.variables} +{ + % The following constants may be adjusted by hand, if desired + + % The first set allow you to enable or disable certain functionality. + #1 'addeprints := % 0=no eprints; 1=include eprints + #2 'hrefform := % 0=no crossrefs; 1=hypertex hrefs; 2=hyperref hrefs + #1 'inlinelinks := % 0=URLs explicit; 1=URLs attached to titles + #1 'adddoi := % 0=no DOI resolver; 1=include it + #1 'addpubmed := % 0=no PUBMED resolver; 1=include it + #0 'doiform := % 0=with href; 1=with \doi{} + + % String constants, which you _might_ want to tweak. + "online" 'onlinestring := % label that a resource is online + "[link]" 'linktextstring := % anonymous link text + "http://www.ncbi.nlm.nih.gov/pubmed/" 'pubmedurl := % prefix to make URL from PUBMED + "https://doi.org/" 'doiurl := % prefix to make URL from DOI + "doi:" 'doiprefix := % printed text to introduce DOI + "https://arxiv.org/abs/" 'eprinturl := % prefix to make URL from eprint ref + "cited " 'citedstring := % label in "lastchecked" remark + "arXiv:" 'eprintprefix := % text prefix printed before eprint ref + "PMID:" 'pubmedprefix := % text prefix printed before PUBMED ref + "URL: " 'urlintro := % text prefix before URL + + % The following are internal state variables, not configuration constants, + % so they shouldn't be fiddled with. + #0 'makeinlinelink := % state variable managed by possibly.setup.inlinelink + "" 'openinlinelink := % ditto + "" 'closeinlinelink := % ditto +} +INTEGERS { + bracket.state + outside.brackets + open.brackets + within.brackets + close.brackets +} +% ...urlbst to here +FUNCTION {init.state.consts} +{ #0 'outside.brackets := % urlbst... + #1 'open.brackets := + #2 'within.brackets := + #3 'close.brackets := % ...urlbst to here + + #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} +STRINGS { s t} +% urlbst +FUNCTION {output.nonnull.original} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +% urlbst... +% Minimal DOI parsing. +% Given a DOI on the stack, check whether it starts with 'doiurl' or not. +% In either case, leave on the stack first a DOI with, and then a DOI without, the URL prefix. +FUNCTION {parse.doi} +{ + #1 doiurl text.length$ substring$ + doiurl = + { doi + doi doiurl text.length$ #1 + #999 substring$ } + { doiurl doi * + doi } + if$ +} +% The following three functions are for handling inlinelink. They wrap +% a block of text which is potentially output with write$ by multiple +% other functions, so we don't know the content a priori. +% They communicate between each other using the variables makeinlinelink +% (which is true if a link should be made), and closeinlinelink (which holds +% the string which should close any current link. They can be called +% at any time, but start.inlinelink will be a no-op unless something has +% previously set makeinlinelink true, and the two ...end.inlinelink functions +% will only do their stuff if start.inlinelink has previously set +% closeinlinelink to be non-empty. +% (thanks to 'ijvm' for suggested code here) +FUNCTION {uand} +{ 'skip$ { pop$ #0 } if$ } % 'and' (which isn't defined at this point in the file) +FUNCTION {possibly.setup.inlinelink} +{ makeinlinelink hrefform #0 > uand + { doi empty$ adddoi uand + { pubmed empty$ addpubmed uand + { eprint empty$ addeprints uand + { url empty$ + { "" } + { url } + if$ } + { eprinturl eprint * } + if$ } + { pubmedurl pubmed * } + if$ } +% { doiurl doi * } + { doi empty$ + { "XXX" } + { doi parse.doi pop$ } + if$ + } + if$ + % an appropriately-formatted URL is now on the stack + hrefform #1 = % hypertex + { "\special {html:<a href=" quote$ * swap$ * quote$ * "> }{" * 'openinlinelink := + "\special {html:</a>}" 'closeinlinelink := } + { "\href {" swap$ * "} {" * 'openinlinelink := % hrefform=#2 -- hyperref + % the space between "} {" matters: a URL of just the right length can cause "\% newline em" + "}" 'closeinlinelink := } + if$ + #0 'makeinlinelink := + } + 'skip$ + if$ % makeinlinelink +} +FUNCTION {add.inlinelink} +{ openinlinelink empty$ + 'skip$ + { openinlinelink swap$ * closeinlinelink * + "" 'openinlinelink := + } + if$ +} +FUNCTION {output.nonnull} +{ % Save the thing we've been asked to output + 's := + % If the bracket-state is close.brackets, then add a close-bracket to + % what is currently at the top of the stack, and set bracket.state + % to outside.brackets + bracket.state close.brackets = + { "]" * + outside.brackets 'bracket.state := + } + 'skip$ + if$ + bracket.state outside.brackets = + { % We're outside all brackets -- this is the normal situation. + % Write out what's currently at the top of the stack, using the + % original output.nonnull function. + s + add.inlinelink + output.nonnull.original % invoke the original output.nonnull + } + { % Still in brackets. Add open-bracket or (continuation) comma, add the + % new text (in s) to the top of the stack, and move to the close-brackets + % state, ready for next time (unless inbrackets resets it). If we come + % into this branch, then output.state is carefully undisturbed. + bracket.state open.brackets = + { " [" * } + { ", " * } % bracket.state will be within.brackets + if$ + s * + close.brackets 'bracket.state := + } + if$ +} + +% Call this function just before adding something which should be presented in +% brackets. bracket.state is handled specially within output.nonnull. +FUNCTION {inbrackets} +{ bracket.state close.brackets = + { within.brackets 'bracket.state := } % reset the state: not open nor closed + { open.brackets 'bracket.state := } + if$ +} + +FUNCTION {format.lastchecked} +{ lastchecked empty$ + { "" } + { inbrackets citedstring lastchecked * } + if$ +} +% ...urlbst to here +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} +FUNCTION {fin.entry.original} % urlbst (renamed from fin.entry, so it can be wrapped below) +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} +FUNCTION {add.blank} +{ " " * before.all 'output.state := +} + +FUNCTION {date.block} +{ + new.block +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} +FUNCTION {tie.or.space.prefix} % puts ~ before the preceding part if it is of length <3 +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ +} + +FUNCTION {capitalize} +{ "u" change.case$ "t" change.case$ } + +FUNCTION {space.word} +{ " " swap$ * " " * } + % Here are the language-specific definitions for explicit words. + % Each function has a name bbl.xxx where xxx is the English word. + % The language selected here is ENGLISH +FUNCTION {bbl.and} +{ "and"} + +FUNCTION {bbl.etal} +{ "et~al." } + +FUNCTION {bbl.editors} +{ "editors" } + +FUNCTION {bbl.editor} +{ "editor" } + +FUNCTION {bbl.edby} +{ "edited by" } + +FUNCTION {bbl.edition} +{ "edition" } + +FUNCTION {bbl.volume} +{ "volume" } + +FUNCTION {bbl.of} +{ "of" } + +FUNCTION {bbl.number} +{ "number" } + +FUNCTION {bbl.nr} +{ "no." } + +FUNCTION {bbl.in} +{ "in" } + +FUNCTION {bbl.pages} +{ "pages" } + +FUNCTION {bbl.page} +{ "page" } + +FUNCTION {bbl.chapter} +{ "chapter" } + +FUNCTION {bbl.techrep} +{ "Technical Report" } + +FUNCTION {bbl.mthesis} +{ "Master's thesis" } + +FUNCTION {bbl.phdthesis} +{ "Ph.D. thesis" } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +% bibinfo.check avoids acting on missing fields while bibinfo.warn will +% issue a warning message if a missing field is detected. Prior to calling +% the bibinfo functions, the user should push the field value and then its +% name string, in that order. +FUNCTION {bibinfo.check} +{ swap$ + duplicate$ missing$ + { + pop$ pop$ + "" + } + { duplicate$ empty$ + { + swap$ pop$ + } + { swap$ + pop$ + } + if$ + } + if$ +} +FUNCTION {bibinfo.warn} +{ swap$ + duplicate$ missing$ + { + swap$ "missing " swap$ * " in " * cite$ * warning$ pop$ + "" + } + { duplicate$ empty$ + { + swap$ "empty " swap$ * " in " * cite$ * warning$ + } + { swap$ + pop$ + } + if$ + } + if$ +} +INTEGERS { nameptr namesleft numnames } + + +STRINGS { bibinfo} + +FUNCTION {format.names} +{ 'bibinfo := + duplicate$ empty$ 'skip$ { + 's := + "" 't := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{ff~}{vv~}{ll}{, jj}" % first name first for all authors + format.name$ + bibinfo bibinfo.check + 't := + nameptr #1 > + { + nameptr #19 % truncate after 19 names + #1 + = + numnames #20 % if there are more than 20 names + > and + { "others" 't := + #1 'namesleft := } + 'skip$ + if$ % end truncation of long list of names + namesleft #1 > + { ", " * t * } + { + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { + %% " " * bbl.etal * + % compute the number of remaining authors + " and " * numnames nameptr - #1 + int.to.str$ * " others" * + } + { + bbl.and + space.word * t * + } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ + } if$ +} +FUNCTION {format.names.ed} +{ + format.names +} +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author "author" format.names +} +FUNCTION {get.bbl.editor} +{ editor num.names$ #1 > 'bbl.editors 'bbl.editor if$ } + +FUNCTION {format.editors} +{ editor "editor" format.names duplicate$ empty$ 'skip$ + { + "," * + " " * + get.bbl.editor + * + } + if$ +} +FUNCTION {format.note} +{ + note empty$ + { "" } + { note #1 #1 substring$ + duplicate$ "{" = + 'skip$ + { output.state mid.sentence = + { "l" } + { "u" } + if$ + change.case$ + } + if$ + note #2 global.max$ substring$ * "note" bibinfo.check + } + if$ +} + +FUNCTION {format.title} +{ title + duplicate$ empty$ 'skip$ + { "t" change.case$ } + if$ + "title" bibinfo.check +} +FUNCTION {format.full.names} +{'s := + "" 't := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ + 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + s nameptr "{ll}" format.name$ duplicate$ "others" = + { 't := } + { pop$ } + if$ + t "others" = + { + " " * bbl.etal * + } + { + numnames #2 > + { "," * } + 'skip$ + if$ + bbl.and + space.word * t * + } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.key.full} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.key.full} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {editor.key.full} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.full + { type$ "proceedings" = + 'editor.key.full + 'author.key.full + if$ + } + if$ +} + +FUNCTION {output.bibitem.original} % urlbst (renamed from output.bibitem, so it can be wrapped below) +{ newline$ + "\bibitem[{" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "}]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ + 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {word.in} +{ bbl.in capitalize + " " * } + +FUNCTION {format.date} +{ year "year" bibinfo.check duplicate$ empty$ + { + } + 'skip$ + if$ + extra.label * + before.all 'output.state := + after.sentence 'output.state := +} +FUNCTION {format.btitle} +{ title "title" bibinfo.check + duplicate$ empty$ 'skip$ + { + emphasize + } + if$ +} +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { bbl.volume volume tie.or.space.prefix + "volume" bibinfo.check * * + series "series" bibinfo.check + duplicate$ empty$ 'pop$ + { swap$ bbl.of space.word * swap$ + emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { series empty$ + { number "number" bibinfo.check } + { output.state mid.sentence = + { bbl.number } + { bbl.number capitalize } + if$ + number tie.or.space.prefix "number" bibinfo.check * * + bbl.in space.word * + series "series" bibinfo.check * + } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition duplicate$ empty$ 'skip$ + { + output.state mid.sentence = + { "l" } + { "t" } + if$ change.case$ + "edition" bibinfo.check + " " * bbl.edition * + } + if$ +} +INTEGERS { multiresult } +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} +FUNCTION {format.pages} +{ pages duplicate$ empty$ 'skip$ + { duplicate$ multi.page.check + { + bbl.pages swap$ + n.dashify + } + { + bbl.page swap$ + } + if$ + tie.or.space.prefix + "pages" bibinfo.check + * * + } + if$ +} +FUNCTION {format.journal.pages} +{ pages duplicate$ empty$ 'pop$ + { swap$ duplicate$ empty$ + { pop$ pop$ format.pages } + { + ":" * + swap$ + n.dashify + "pages" bibinfo.check + * + } + if$ + } + if$ +} +FUNCTION {format.journal.eid} +{ eid "eid" bibinfo.check + duplicate$ empty$ 'pop$ + { swap$ duplicate$ empty$ 'skip$ + { + ":" * + } + if$ + swap$ * + } + if$ +} +FUNCTION {format.vol.num.pages} +{ volume field.or.null + duplicate$ empty$ 'skip$ + { + "volume" bibinfo.check + } + if$ + number "number" bibinfo.check duplicate$ empty$ 'skip$ + { + swap$ duplicate$ empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + swap$ + "(" swap$ * ")" * + } + if$ * + eid empty$ + { format.journal.pages } + { format.journal.eid } + if$ +} + +FUNCTION {format.chapter} +{ chapter empty$ + 'format.pages + { type empty$ + { bbl.chapter } + { type "l" change.case$ + "type" bibinfo.check + } + if$ + chapter tie.or.space.prefix + "chapter" bibinfo.check + * * + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { bbl.chapter } + { type "l" change.case$ + "type" bibinfo.check + } + if$ + chapter tie.or.space.prefix + "chapter" bibinfo.check + * * + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.booktitle} +{ + booktitle "booktitle" bibinfo.check + emphasize +} +FUNCTION {format.in.booktitle} +{ format.booktitle duplicate$ empty$ 'skip$ + { + word.in swap$ * + } + if$ +} +FUNCTION {format.in.ed.booktitle} +{ format.booktitle duplicate$ empty$ 'skip$ + { + editor "editor" format.names.ed duplicate$ empty$ 'pop$ + { + "," * + " " * + get.bbl.editor + ", " * + * swap$ + * } + if$ + word.in swap$ * + } + if$ +} +FUNCTION {format.thesis.type} +{ type duplicate$ empty$ + 'pop$ + { swap$ pop$ + "t" change.case$ "type" bibinfo.check + } + if$ +} +FUNCTION {format.tr.number} +{ number "number" bibinfo.check + type duplicate$ empty$ + { pop$ bbl.techrep } + 'skip$ + if$ + "type" bibinfo.check + swap$ duplicate$ empty$ + { pop$ "t" change.case$ } + { tie.or.space.prefix * * } + if$ +} +FUNCTION {format.article.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} +FUNCTION {format.book.crossref} +{ volume duplicate$ empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + pop$ word.in + } + { bbl.volume + capitalize + swap$ tie.or.space.prefix "volume" bibinfo.check * * bbl.of space.word * + } + if$ + " \cite{" * crossref * "}" * +} +FUNCTION {format.incoll.inproc.crossref} +{ + word.in + " \cite{" * crossref * "}" * +} +FUNCTION {format.org.or.pub} +{ 't := + "" + address empty$ t empty$ and + 'skip$ + { + t empty$ + { address "address" bibinfo.check * + } + { t * + address empty$ + 'skip$ + { ", " * address "address" bibinfo.check * } + if$ + } + if$ + } + if$ +} +FUNCTION {format.publisher.address} +{ publisher "publisher" bibinfo.warn format.org.or.pub +} + +FUNCTION {format.organization.address} +{ organization "organization" bibinfo.check format.org.or.pub +} + +FUNCTION {archiveprefix.or.eprinttype} % holder for eprinttype with archiveprefix precedence +{ + archiveprefix empty$ + { + eprinttype empty$ + { "" } % not using 'skip$ to reduce errors like "nothing to pop from stack" + { eprinttype } + if$ + } + { archiveprefix } + if$ +} + +FUNCTION {output.eprint} % this is only used with the @misc record type (common for arXiv and other preprint server bibtex records) +{ + eprint empty$ + {% if eprint field is empty + publisher field.or.null "arXiv" = % field.or.null here helps when no publisher field in the record + { publisher " preprint" * } % add " preprint" to publisher with the idea that publisher is the name of the preprint server + { "" } % if publisher != "arXiv" then empty output + if$ + emphasize % no output function after emphasize because nothing goes after this + } + {% if eprint field is not empty + archiveprefix.or.eprinttype empty$ + { "" } % not using 'skip$ to reduce errors like "nothing to pop from stack" + {% if archiveprefix or eprinttype fields are not empty + journal empty$ + { "Preprint" } % if journal field is empty: output just "Preprint" emphasized like a journal name + { journal } % if journal field is not empty, output it (takes precedence) + if$ + emphasize output % emphasize what we formed before, setting output as a border to the subblock that follows with the comma delimiter + archiveprefix.or.eprinttype ":" * eprint * % subblock with eprinttype and eprint number + } + if$ + } + if$ +} + +% urlbst... +% Functions for making hypertext links. +% In all cases, the stack has (link-text href-url) +% +% make 'null' specials +FUNCTION {make.href.null} +{ + pop$ +} +% make hypertex specials +FUNCTION {make.href.hypertex} +{ + "\special {html:<a href=" quote$ * + swap$ * quote$ * "> }" * swap$ * + "\special {html:</a>}" * +} +% make hyperref specials +FUNCTION {make.href.hyperref} +{ + "\href {" swap$ * "} {\path{" * swap$ * "}}" * +} +FUNCTION {make.href} +{ hrefform #2 = + 'make.href.hyperref % hrefform = 2 + { hrefform #1 = + 'make.href.hypertex % hrefform = 1 + 'make.href.null % hrefform = 0 (or anything else) + if$ + } + if$ +} + +% If inlinelinks is true, then format.url should be a no-op, since it's +% (a) redundant, and (b) could end up as a link-within-a-link. +FUNCTION {format.url} +{ inlinelinks #1 = url empty$ or + { "" } + { hrefform #1 = + { % special case -- add HyperTeX specials + urlintro "\url{" url * "}" * url make.href.hypertex * } + { urlintro "\url{" * url * "}" * } + if$ + } + if$ +} +FUNCTION {format.eprint} +{ eprint empty$ + { "" } + { eprintprefix eprint * eprinturl eprint * make.href } + if$ +} + +FUNCTION {format.doi} +{ doi empty$ + { "" } + { doi parse.doi % leaves "https://doi.org/DOI" DOI on the stack + 's := 't := + doiform #1 = + { "\doi{" s * "}" * } + { doiprefix s * t make.href } + if$ + } + if$ +} + +FUNCTION {format.pubmed} +{ pubmed empty$ + { "" } + { pubmedprefix pubmed * pubmedurl pubmed * make.href } + if$ +} + +% Output a URL. We can't use the more normal idiom (something like +% `format.url output'), because the `inbrackets' within +% format.lastchecked applies to everything between calls to `output', +% so that `format.url format.lastchecked * output' ends up with both +% the URL and the lastchecked in brackets. +FUNCTION {output.url} +{ url empty$ + 'skip$ + { new.block + format.url output + format.lastchecked output + } + if$ +} + +FUNCTION {output.web.refs} +{ + new.block + inlinelinks + 'skip$ % links were inline -- don't repeat them + { % If the generated DOI will be the same as the URL, + % then don't print the URL (thanks to Joseph Wright + % for (the original version of) this code, + % at http://tex.stackexchange.com/questions/5660) + adddoi + doi empty$ { "X" } { doi parse.doi pop$ } if$ % DOI URL to be generated + url empty$ { "Y" } { url } if$ % the URL, or "Y" if empty + = % are the strings equal? + and + 'skip$ + { output.url } + if$ + addeprints eprint empty$ not and + { format.eprint output.nonnull } + 'skip$ + if$ + adddoi doi empty$ not and + { format.doi output.nonnull } + 'skip$ + if$ + addpubmed pubmed empty$ not and + { format.pubmed output.nonnull } + 'skip$ + if$ + } + if$ +} + +% Wrapper for output.bibitem.original. +% If the URL field is not empty, set makeinlinelink to be true, +% so that an inline link will be started at the next opportunity +FUNCTION {output.bibitem} +{ outside.brackets 'bracket.state := + output.bibitem.original + inlinelinks url empty$ not doi empty$ not or pubmed empty$ not or eprint empty$ not or and + { #1 'makeinlinelink := } + { #0 'makeinlinelink := } + if$ +} + +% Wrapper for fin.entry.original +FUNCTION {fin.entry} +{ output.web.refs % urlbst + makeinlinelink % ooops, it appears we didn't have a title for inlinelink + { possibly.setup.inlinelink % add some artificial link text here, as a fallback + linktextstring output.nonnull } + 'skip$ + if$ + bracket.state close.brackets = % urlbst + { "]" * } + 'skip$ + if$ + fin.entry.original +} + +% Webpage entry type. +% Title and url fields required; +% author, note, year, month, and lastchecked fields optional +% See references +% ISO 690-2 http://www.nlc-bnc.ca/iso/tc46sc9/standard/690-2e.htm +% http://www.classroom.net/classroom/CitingNetResources.html +% http://neal.ctstateu.edu/history/cite.html +% http://www.cas.usf.edu/english/walker/mla.html +% for citation formats for web pages. +FUNCTION {webpage} +{ output.bibitem + author empty$ + { editor empty$ + 'skip$ % author and editor both optional + { format.editors output.nonnull } + if$ + } + { editor empty$ + { format.authors output.nonnull } + { "can't use both author and editor fields in " cite$ * warning$ } + if$ + } + if$ + new.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ + format.title "title" output.check + inbrackets onlinestring output + new.block + year empty$ + 'skip$ + { format.date "year" output.check } + if$ + % We don't need to output the URL details ('lastchecked' and 'url'), + % because fin.entry does that for us, using output.web.refs. The only + % reason we would want to put them here is if we were to decide that + % they should go in front of the rather miscellaneous information in 'note'. + new.block + note output + fin.entry +} +% ...urlbst to here + + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title "title" output.check + new.block + crossref missing$ + { + journal + "journal" bibinfo.check + emphasize + "journal" output.check + possibly.setup.inlinelink format.vol.num.pages output% urlbst + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + format.note output + fin.entry +} +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.btitle "title" output.check + format.edition output + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + format.publisher.address output + } + { + new.block + format.book.crossref output.nonnull + } + if$ + new.block + format.note output + fin.entry +} +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title "title" output.check + new.block + howpublished "howpublished" bibinfo.check output + address "address" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.btitle "title" output.check + crossref missing$ + { + format.edition output + format.bvolume output + format.chapter "chapter" output.check + new.block + format.number.series output + new.sentence + format.publisher.address output + } + { + format.chapter "chapter" output.check + new.block + format.book.crossref output.nonnull + } + if$ + new.block + format.note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.edition output + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + format.publisher.address output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + format.note output + fin.entry +} +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title "title" output.check + new.block + crossref missing$ + { format.in.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address "address" bibinfo.check output + new.sentence + organization "organization" bibinfo.check output + publisher "publisher" bibinfo.check output + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + format.note output + fin.entry +} +FUNCTION {conference} { inproceedings } +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.btitle "title" output.check + format.edition output + organization address new.block.checkb + organization "organization" bibinfo.check output + address "address" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title + "title" output.check + new.block + bbl.mthesis format.thesis.type output.nonnull + school "school" bibinfo.warn output + address "address" bibinfo.check output + month "month" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title output + new.block + howpublished "howpublished" bibinfo.check output + new.block + output.eprint output + new.block + format.note output + fin.entry +} +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.btitle + "title" output.check + new.block + bbl.phdthesis format.thesis.type output.nonnull + school "school" bibinfo.warn output + address "address" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {presentation} +{ output.bibitem + format.authors output + author format.key output + new.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title output + new.block + format.organization.address "organization and address" output.check + month "month" output.check + year "year" output.check + new.block + format.note output + new.sentence + type missing$ 'skip$ + {"(" type capitalize * ")" * output} + if$ + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + format.editors output + editor format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.btitle "title" output.check + format.bvolume output + format.number.series output + new.sentence + publisher empty$ + { format.organization.address output } + { organization "organization" bibinfo.check output + new.sentence + format.publisher.address output + } + if$ + new.block + format.note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title + "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" bibinfo.warn output + address "address" bibinfo.check output + new.block + format.note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + format.date "year" output.check + date.block + title empty$ 'skip$ 'possibly.setup.inlinelink if$ % urlbst + format.title "title" output.check + new.block + format.note "note" output.check + fin.entry +} + +FUNCTION {default.type} { misc } +READ +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} +INTEGERS { len } +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} +FUNCTION {format.lab.names} +{ 's := + "" 't := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ + " " * bbl.etal * + } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { + " " * bbl.etal * + } + { bbl.and space.word * s #2 "{vv~}{ll}" format.name$ + * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.label} +{ editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.label + 'author.key.label + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + short.list key field.or.null = or + { pop$ "" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" + format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" 't := } + 'skip$ + if$ + t sortify * + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} +FUNCTION {editor.sort} +{ editor empty$ + { key empty$ + { "to sort, need editor or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ +} +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.sort + 'author.sort + if$ + } + if$ + #1 entry.max$ substring$ + 'sort.label := + sort.label + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} +SORT +STRINGS { last.label next.extra } +INTEGERS { last.extra.num last.extra.num.extended last.extra.num.blank number.label } +FUNCTION {initialize.extra.label.stuff} +{ #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'last.extra.num := + "a" chr.to.int$ #1 - 'last.extra.num.blank := + last.extra.num.blank 'last.extra.num.extended := + #0 'number.label := +} +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num "z" chr.to.int$ > + { "a" chr.to.int$ 'last.extra.num := + last.extra.num.extended #1 + 'last.extra.num.extended := + } + 'skip$ + if$ + last.extra.num.extended last.extra.num.blank > + { last.extra.num.extended int.to.chr$ + last.extra.num int.to.chr$ + * 'extra.label := } + { last.extra.num int.to.chr$ 'extra.label := } + if$ + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { year field.or.null #-1 #1 substring$ chr.to.int$ #65 < + { "{\natexlab{" swap$ * "}}" * } + { "{(\natexlab{" swap$ * "})}" * } + if$ } + if$ + 'extra.label := + label extra.label * 'label := +} +EXECUTE {initialize.extra.label.stuff} +ITERATE {forward.pass} +REVERSE {reverse.pass} +FUNCTION {bib.sort.order} +{ sort.label + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} +ITERATE {bib.sort.order} +SORT +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\providecommand{\natexlab}[1]{#1}" + write$ newline$ +} +EXECUTE {begin.bib} +EXECUTE {init.urlbst.variables} % urlbst +EXECUTE {init.state.consts} +ITERATE {call.type$} +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} +EXECUTE {end.bib} +%% End of customized bst file +%% +%% End of file `acl_natbib_basic.bst'. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/anthology.bib.txt b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/anthology.bib.txt new file mode 100644 index 0000000..0d9f1fd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/anthology.bib.txt @@ -0,0 +1,26 @@ +For citing papers in the ACL Anthology, we provide a single consolidated +BibTeX file containing all of its papers. The bibkeys in these papers are +designed to be semantic in nature: {names}-{year}-{words}, where +- `names` is the concatenated last names of the authors when there is just + one or two authors, or `lastname-etal` for 3+ +- `year` is the four-digit year +- `words` is the first significant word in the title, or more, if necessary, + to preserve uniqueness + +For example, https://aclanthology.org/N04-1035 can be cited as \cite{galley-etal-2004-whats}. + +The consolidated file can be downloaded from here: +- https://aclanthology.org/anthology.bib + +Unfortunately, as of 2024 or so, this file is now larger than 50 MB, which is Overleaf's +bib file size limit. Consequently, the Anthology shards the file automatically into +49 MB shards. + +There are currently (2025) two files: +- https://aclanthology.org/anthology-1.bib +- https://aclanthology.org/anthology-2.bib + +You can download these directly from Overleaf from New File -> From External URL, +and then adding them to the \bibliography line in acl_latex.tex: + + \bibliography{custom,anthology-1,anthology-2} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/custom.bib b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/custom.bib new file mode 100644 index 0000000..c2c0106 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/custom.bib @@ -0,0 +1,70 @@ +% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib"). + +@book{Aho:72, + author = {Alfred V. Aho and Jeffrey D. Ullman}, + title = {The Theory of Parsing, Translation and Compiling}, + year = "1972", + volume = "1", + publisher = {Prentice-Hall}, + address = {Englewood Cliffs, NJ} +} + +@book{APA:83, + author = {{American Psychological Association}}, + title = {Publications Manual}, + year = "1983", + publisher = {American Psychological Association}, + address = {Washington, DC} +} + +@article{Chandra:81, + author = {Ashok K. Chandra and Dexter C. Kozen and Larry J. Stockmeyer}, + year = "1981", + title = {Alternation}, + journal = {Journal of the Association for Computing Machinery}, + volume = "28", + number = "1", + pages = "114--133", + doi = "10.1145/322234.322243", +} + +@inproceedings{andrew2007scalable, + title={Scalable training of {L1}-regularized log-linear models}, + author={Andrew, Galen and Gao, Jianfeng}, + booktitle={Proceedings of the 24th International Conference on Machine Learning}, + pages={33--40}, + year={2007}, +} + +@book{Gusfield:97, + author = {Dan Gusfield}, + title = {Algorithms on Strings, Trees and Sequences}, + year = "1997", + publisher = {Cambridge University Press}, + address = {Cambridge, UK} +} + +@article{rasooli-tetrault-2015, + author = {Mohammad Sadegh Rasooli and Joel R. Tetreault}, + title = {Yara Parser: {A} Fast and Accurate Dependency Parser}, + journal = {Computing Research Repository}, + volume = {arXiv:1503.06733}, + year = {2015}, + url = {http://arxiv.org/abs/1503.06733}, + note = {version 2} +} + +@article{Ando2005, + Acmid = {1194905}, + Author = {Ando, Rie Kubota and Zhang, Tong}, + Issn = {1532-4435}, + Issue_Date = {12/1/2005}, + Journal = {Journal of Machine Learning Research}, + Month = dec, + Numpages = {37}, + Pages = {1817--1853}, + Publisher = {JMLR.org}, + Title = {A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data}, + Volume = {6}, + Year = {2005} +} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/formatting.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/formatting.md new file mode 100644 index 0000000..eeb1ce1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/acl/formatting.md @@ -0,0 +1,326 @@ +# Instructions for *ACL Proceedings + +The following instructions are for authors of papers submitted for review to ACL conferences (hereafter, "review version") or paper accepted for publication in its proceedings (hereafter, "final version"). +All authors are required to adhere to these specifications. + +## Style Files + +*ACL provides style files for LaTeX and Microsoft Word that meet these requirements. They can be found at: + +> https://acl-org.github.io/ACLPUB/ + +We strongly recommend the use of these style files, which have been appropriately tailored for the *ACL proceedings. + +## Paper Length + +The conference accepts submissions of long papers and short papers. +Review versions of long papers may have up to eight (8) pages of content plus unlimited pages for references. +Upon acceptance, final versions of long papers will be given one additional page -- up to nine (9) pages of content plus unlimited pages for acknowledgements and references -- so that reviewers' comments can be taken into account. +Review versions of short papers may have up to four (4) pages of content, plus unlimited pages for references. +Final versions of short papers may have up to five (5) pages, plus unlimited pages for acknowledgements and references. +For both long and short papers, all figures and tables that are part of the main text must fit within these page limits. + +The conference encourages submission of appendices and supplementary material, which are not required to fit within these page limits. However, review versions of papers must be self-contained: it is optional for reviewers to look at appendices or supplementary material. Please see [Appendices](#Appendices) and [Supplementary](#Supplementary Material) for more information. + +Review versions should not refer, for further detail, to documents, code or data resources that are not available to the reviewers. + +Papers that do not conform to these requirements may be rejected without review. + +Workshop chairs may have different rules for allowed length and whether appendices or supplementary materials are welcome. +As always, the respective call for papers is the authoritative source. + +## Anonymity + +As reviewing will be double-blind, review versions must not include any identifying information about the authors (such as names, affiliations, or URLs). +Self-references that reveal the author's identity, e.g., + +> We previously showed (Gusfield, 1997)... + +must be avoided, and anonymous citations, e.g., + +> We previously showed (Anonymous, 1997)... + +should also be avoided. Instead, use citations such as + +> Gusfield (1997) previously showed... + +Review versions must not include acknowledgements. + +**Papers that do not conform to these requirements may be rejected without review.** + +Any preliminary non-archival versions of submitted papers should be listed in the submission form but not in the review version of the paper. +Reviewers are generally aware that authors may present preliminary versions of their work in other venues, but will not be provided the list of previous presentations from the submission form. + +Once a paper has been accepted to the conference, the final version should include the author's names and affiliations, and is allowed to use self-references. + +## Multiple Submission + +Papers that have been or will be submitted to other meetings or publications must indicate this at submission time in the START submission form, and must be withdrawn from the other venues if accepted by *ACL. +Authors of papers accepted for presentation at *ACL must notify the program chairs by the deadline for final versions ("camera-ready deadline") whether the paper will be presented. +We will not accept for publication or presentation any papers that overlap significantly in content or results with papers that will be (or have been) published elsewhere. + +Authors submitting more than one paper to *ACL must ensure that submissions do not overlap significantly (>25%) with each other in content or results. + +## Formatting Instructions + +### File Format + +Papers must be in Adobe Portable Document Format (PDF). +Please make sure that your PDF file embeds all necessary fonts (especially for tree diagrams, symbols, and Asian languages). +When you print or create the PDF file, there is usually an option in your printer setup to include none, all or just non-standard fonts. +Please make sure that you select the option of including *all* the fonts. +**Before sending it, test your PDF by printing it from a computer different from the one where it was created.** + +Some word processors may generate very large PDF files, where each page is rendered as an image. +Such images may reproduce poorly. +In this case, try alternative ways to obtain the PDF. + +All papers must use **A4 paper format** (21 cm x 29.7 cm). +Papers must not be submitted with any other paper size. + +If you cannot meet the above requirements, please contact the publication chairs as soon as possible. + +### Layout + +All text except for page numbers must fit within the margins. + +Review versions should have page numbers, centered in the bottom margin, but **pages should not be numbered in the final version.** + +Manuscripts must be set in two columns. +Exceptions to the two-column format include the title, authors' names and complete addresses, which must be centered at the top of the first page, and any full-width figures or tables. + +The exact dimensions for a page on A4 paper are: + +* Left margin: 2.5 cm +* Right margin: 2.5 cm +* Top margin: 2.5 cm +* Bottom margin: 2.5 cm +* Column width: 7.7 cm +* Column height: 24.7 cm +* Gap between columns: 0.6 cm + +In the review version, a ruler (line numbers in the left and right margins of the article) should be printed, so that reviewers may comment on particular lines in the paper. +The ruler should not change the appearance of any other content on the page. +The final version should not contain a ruler. + +### Fonts + +All text (except non-Latin scripts and mathematical formulas) should be set in **Times Roman**. +If Times Roman is unavailable, you may use **Times New Roman** or **Computer Modern Roman.** + +The following table specifies what font sizes and styles must be used for each type of text in the manuscript. + +| Type of Text | Font Size | Style | +| --------------------- | --------- | ----- | +| paper title | 15 pt | bold | +| author names | 12 pt | bold | +| author affiliation | 12 pt | | +| the word ``Abstract'' | 12 pt | bold | +| section titles | 12 pt | bold | +| subsection titles | 11 pt | bold | +| document text | 11 pt | | +| captions | 10 pt | | +| abstract text | 10 pt | | +| bibliography | 10 pt | | +| footnotes | 9 pt | | + +### Title and Authors + +Center the title, author's name(s) and affiliation(s) across both columns. + +Place the title centered at the top of the first page, in 15-point bold. +Long titles should be typed on two lines without a blank line intervening. +Put the title 2.5 cm from the top of the page. +Write the title in [title case](https://apastyle.apa.org/style-grammar-guidelines/capitalization/title-case); do not write the title in all capital letters, except for acronyms (e.g., "BLEU") or proper nouns ("English") that are normally uppercased or capitalized. + +Place the author name(s) and affiliation(s) under the title. +Write authors' full names; do not abbreviate given names to initials, unless they are normally written as initials ("Margaret Mitchell", not "M. Mitchell"). +Do not format surnames in all capitals ("Mitchell", not "MITCHELL"). + +Do not use footnotes for affiliations. +The affiliation should contain the author's complete address, and if possible, an electronic mail address. + +The title, author names and addresses should be completely identical to those entered to the paper submission website in order to maintain the consistency of author information among all publications of the conference. +If they are different, the publication chairs may resolve the difference without consulting with you; so it is in your own interest to double-check that the information is consistent. + +Start the body of the first page 7.5 cm from the top of the page. +**Even in the review version of the paper, you should maintain space for names and addresses so that they will fit in the final version.** + +### Abstract + +Type the abstract at the beginning of the first column. +Center the word **Abstract** in 12 point bold above the body of the abstract. +The width of the abstract should be smaller than the +normal column width by 0.6 cm on each side. +The abstract text should be 10 point roman, single-spaced. + +The abstract should be a concise summary of the general thesis and conclusions of the paper. +It should be no longer than 200 words. + +### Text + +Begin typing the main body of the text immediately after the abstract, continuing in two columns. +The text should be 11 point roman, single-spaced. + +Indent 0.4 cm when starting a new paragraph, except for the first paragraph in a section. + +### Sections + +Use numbered sections (Arabic numerals) to facilitate cross references. +Number subsections with the section number and the subsection number separated by a dot, in Arabic numerals, e.g., + +> 1 Introduction + +or + +> 6.1 File Format + +### Footnotes +Put footnotes at the bottom of the page and use 9 point font. +They may be numbered or referred to by asterisks or other symbols. +Footnotes should be separated from the text by a line. + +### Figures and tables + +Place figures and tables in the paper near where they are first discussed, rather than at the end, if possible. +Wide figures/tables may run across both columns. + +To accommodate people who are color-blind (as well as those printing with black-and-white printers), grayscale readability is strongly encouraged. +Color is not forbidden, but authors should ensure that tables and figures do not rely solely on color to convey critical distinctions. + +**Captions:** +Provide a caption for every figure/table; number each one sequentially in the form: + +> Figure 1: Caption of the Figure. + +and + +> Table 1: Caption of the Table. + +Captions should be placed below figures/tables, in 10 point roman type. +Captions that are one line are centered. +Captions longer than one line are left-aligned. + +### Hyperlinks + +Within-document and external hyperlinks should be dark blue (hex #000099), not underlined or boxed. + +### Non-English Text + +Text in languages other than English should be accompanied by translations into English, and text in scripts other than Latin should \emph{also} be accompanied by transliterations into Latin script, since not all readers can recognize non-Latin characters easily. + +For example, παράδειγμα *paradeigma* ‘example’ is a Greek word, and this is a Greek sentence: + +> Αυτό είναι ένα παράδειγμα. +> auto einai ena paradeigma. +> ‘This is an example.’ + +### Citations + +Citations within the text appear in parentheses (Gusfield, 1997), or, if the author's name appears in the text itself: Gusfield (1997). +Append lowercase letters to the year in cases of ambiguities. +Cite papers with two authors using both authors' names (Aho and Ullman, 1972), but cite papers with more than two authors by the first author's name and ``et al.'' (Chandra et al., 1981). +Collapse multiple citations into a single pair of parentheses (Gusfield, 1997; Aho and Ullman, 1972). + +Refrain from using full citations as sentence constituents. +Instead of + +> (Gusfield, 1997) showed that ... +> In (Gusfield, 1997), ...'' + +write + +> Gusfield (1997) showed that ... +> In Gusfield (1997), ... + +Submissions should accurately reference prior and related work, including code and data. +If a piece of prior work appeared in multiple venues, the version that appeared in a refereed, archival venue should be referenced. +If multiple versions of a piece of prior work exist, the one used by the authors should be referenced. + +### Acknowledgments + +The acknowledgments should go immediately before the references. +Do not number the acknowledgments section. +Do not include this section in the review version. + +### References + +Gather the full set of references together under the unnumbered section heading **References**. +Place the References section before any Appendices. +Arrange the references alphabetically by first author, rather than by order of occurrence in the text. + +Provide as complete a citation as possible, using a consistent format, such as the [one for Computational Linguistics](http://cljournal.org/style_guide_refs.html) or the one in the [Publication Manual of the American Psychological Association](https://apastyle.apa.org/products/publication-manual-7th-edition). +Use full names for authors, not just initials. +Authors should not rely on automated citation indices to provide accurate references for prior and related work. + +As part of our work to make ACL materials more widely used and cited outside of our discipline, ACL has registered as a CrossRef member, as a registrant of Digital Object Identifiers (DOIs), the standard for registering permanent URNs for referencing scholarly materials. + +All references are required to contain DOIs of all cited works when possible, or, as a second resort, links to ACL Anthology pages. +Appropriate records should be found for most materials in the current [ACL Anthology](https://aclweb.org/anthology/). + +Example article in a journal: + +> Rie Kubota Ando and Tong Zhang. 2005. [A framework for learning predictive structures from multiple tasks and unlabeled data](https://www.jmlr.org/papers/v6/ando05a.html). *Journal of Machine Learning Research*, 6:1817–1853. + +Example paper in non-ACL proceedings, with DOI: + +> Galen Andrew and Jianfeng Gao. 2007. [Scalable training of L1-regularized log-linear models](https://doi.org/10.1145/1273496.1273501). In *Proceedings of the 24th International Conference on Machine Learning*, pages 33–40. + +Example ACL Anthology paper with DOI: + +> James Goodman, Andreas Vlachos, and Jason Naradowsky. 2016. [Noise reduction and targeted exploration in imitation learning for Abstract Meaning Representation parsing](http://dx.doi.org/10.18653/v1/P16-1001). In *Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*, pages 1–45711, Berlin, Germany. Association for Computational Linguistics. + +Example ACL Anthology paper without DOI: + +> Benjamin Börschinger and Mark Johnson. 2011. [A particle filter algorithm for Bayesian word segmentation](https://www.aclweb.org/anthology/U11-1004/). In *Proceedings of the Australasian Language Technology Association Workshop 2011*, pages 10–44718, Canberra, Australia. + +Example arXiv paper: + +> Mohammad Sadegh Rasooli and Joel R. Tetreault. 2015. [Yara parser: A fast and accurate dependency parser](http://arxiv.org/abs/1503.06733). *Computing Research Repository*, arXiv:1503.06733. Version 2. + +## Appendices + +Appendices are material that can be read, and include lemmas, formulas, proofs, and tables that are not critical to the reading and understanding of the paper. +Letter them in sequence and provide an informative title: + +> Appendix A. Title of Appendix + +The appendices come after the references. + +Review versions of appendices must follow the same anonymity guidelines as the main paper. + +## Supplementary Material + +Submissions may include non-readable supplementary material used in the work and described in the paper. +Any accompanying software and/or data should include licenses and documentation of research review as appropriate. +Supplementary material may report preprocessing decisions, model parameters, and other details necessary for the replication of the experiments reported in the paper. +Seemingly small preprocessing decisions can sometimes make a large difference in performance, so it is crucial to record such decisions to precisely characterize state-of-the-art methods. + +Nonetheless, supplementary material should be supplementary (rather than central) to the paper. +**Submissions that misuse the supplementary material may be rejected without review.** +Supplementary material may include explanations or details of proofs or derivations that do not fit into the paper, lists of features or feature templates, sample inputs and outputs for a system, pseudo-code or source code, and data. +(Source code and data should be separate uploads, rather than part of the paper). + +The paper should not rely on the supplementary material: while the paper may refer to and cite the supplementary material and the supplementary material will be available to the reviewers, they will not be asked to review the supplementary material. + +Review versions of supplementary material must follow the same anonymity guidelines as the main paper. + +## Credits + +This document has been adapted from the instructions for earlier ACL and NAACL proceedings, including those for +ACL 2020 by Steven Bethard, Ryan Cotterell and Rui Yan, +ACL 2019 by Douwe Kiela and Ivan Ivan Vulić, +NAACL 2019 by Stephanie Lukin and Alla Roskovskaya, +ACL 2018 by Shay Cohen, Kevin Gimpel, and Wei Lu, +NAACL 2018 by Margaret Mitchell and Stephanie Lukin, +BibTeX suggestions for (NA)ACL 2017/2018 from Jason Eisner, +ACL 2017 by Dan Gildea and Min-Yen Kan, +NAACL 2017 by Margaret Mitchell, +ACL 2012 by Maggie Li and Michael White, +ACL 2010 by Jing-Shin Chang and Philipp Koehn, +ACL 2008 by Johanna D. Moore, Simone Teufel, James Allan, and Sadaoki Furui, +ACL 2005 by Hwee Tou Ng and Kemal Oflazer, +ACL 2002 by Eugene Charniak and Dekang Lin, +and earlier ACL and EACL formats written by several people, including +John Chen, Henry S. Thompson and Donald Walker. +Additional elements were taken from the formatting instructions of the *International Joint Conference on Artificial Intelligence* and the *Conference on Computer Vision and Pattern Recognition*. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/README.md b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/README.md new file mode 100644 index 0000000..5a2c5ff --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/README.md @@ -0,0 +1,3 @@ +# Template + +Template and style files for CoLM 2025 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.bib b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.bib new file mode 100644 index 0000000..95744c2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.bib @@ -0,0 +1,11 @@ +@inproceedings{Vaswani+2017, + author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, \L ukasz and Polosukhin, Illia}, + booktitle = {Advances in Neural Information Processing Systems}, + pages = {}, + publisher = {Curran Associates, Inc.}, + title = {Attention is All you Need}, + url = {https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf}, + volume = {30}, + year = {2017} +} + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.bst b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.bst new file mode 100644 index 0000000..a85a008 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.bst @@ -0,0 +1,1440 @@ +%% File: `iclr2024.bst' +%% A copy of iclm2010.bst, which is a modification of `plainnl.bst' for use with natbib package +%% +%% Copyright 2010 Hal Daum\'e III +%% Modified by J. Fürnkranz +%% - Changed labels from (X and Y, 2000) to (X & Y, 2000) +%% +%% Copyright 1993-2007 Patrick W Daly +%% Max-Planck-Institut f\"ur Sonnensystemforschung +%% Max-Planck-Str. 2 +%% D-37191 Katlenburg-Lindau +%% Germany +%% E-mail: daly@mps.mpg.de +%% +%% This program can be redistributed and/or modified under the terms +%% of the LaTeX Project Public License Distributed from CTAN +%% archives in directory macros/latex/base/lppl.txt; either +%% version 1 of the License, or any later version. +%% + % Version and source file information: + % \ProvidesFile{icml2010.mbs}[2007/11/26 1.93 (PWD)] + % + % BibTeX `plainnat' family + % version 0.99b for BibTeX versions 0.99a or later, + % for LaTeX versions 2.09 and 2e. + % + % For use with the `natbib.sty' package; emulates the corresponding + % member of the `plain' family, but with author-year citations. + % + % With version 6.0 of `natbib.sty', it may also be used for numerical + % citations, while retaining the commands \citeauthor, \citefullauthor, + % and \citeyear to print the corresponding information. + % + % For version 7.0 of `natbib.sty', the KEY field replaces missing + % authors/editors, and the date is left blank in \bibitem. + % + % Includes field EID for the sequence/citation number of electronic journals + % which is used instead of page numbers. + % + % Includes fields ISBN and ISSN. + % + % Includes field URL for Internet addresses. + % + % Includes field DOI for Digital Object Idenfifiers. + % + % Works best with the url.sty package of Donald Arseneau. + % + % Works with identical authors and year are further sorted by + % citation key, to preserve any natural sequence. + % +ENTRY + { address + author + booktitle + chapter + doi + eid + edition + editor + howpublished + institution + isbn + issn + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + url + volume + year + } + {} + { label extra.label sort.label short.list } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { " (eds.)" * } + { " (ed.)" * } + if$ + } + if$ +} + +FUNCTION {format.isbn} +{ isbn empty$ + { "" } + { new.block "ISBN " isbn * } + if$ +} + +FUNCTION {format.issn} +{ issn empty$ + { "" } + { new.block "ISSN " issn * } + if$ +} + +FUNCTION {format.url} +{ url empty$ + { "" } + { new.block "URL \url{" url * "}" * } + if$ +} + +FUNCTION {format.doi} +{ doi empty$ + { "" } + { new.block "\doi{" doi * "}" * } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + { title "t" change.case$ } + if$ +} + +FUNCTION {format.full.names} +{'s := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.full} +{ author empty$ + { editor empty$ + { "" } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.full} +{ author empty$ + { "" } + { author format.full.names } + if$ +} + +FUNCTION {editor.full} +{ editor empty$ + { "" } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.full + { type$ "proceedings" = + 'editor.full + 'author.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year duplicate$ empty$ + { "empty year in " cite$ * warning$ + pop$ "" } + 'skip$ + if$ + month empty$ + 'skip$ + { month + " " * swap$ * + } + if$ + extra.label * +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pp.\ " pages n.dashify tie.or.space.connect } + { "pp.\ " pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.eid} +{ eid empty$ + { "" } + { "art." eid tie.or.space.connect } + if$ +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":\penalty0 " * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.vol.num.eid} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + eid empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.eid } + { ":\penalty0 " * eid * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + key empty$ not and + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In \emph{" journal * "}" * } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "\emph{" * series * "}" * } + if$ + } + 'skip$ + if$ + } + 'skip$ + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In \emph{" booktitle * "}" * } + if$ + } + { "In " } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + eid empty$ + { format.vol.num.pages output } + { format.vol.num.eid output } + if$ + format.date "year" output.check + } + { format.article.crossref output.nonnull + eid empty$ + { format.pages output } + { format.eid output } + if$ + } + if$ + format.issn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date "year" output.check + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date "year" output.check + } + { address output.nonnull + format.date "year" output.check + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + new.block + format.btitle "title" output.check + organization address new.block.checkb + organization output + address output + format.edition output + format.date output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + format.issn output + format.url output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.btitle "title" output.check + new.block + "PhD thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + format.editors output + editor format.key output + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address output + format.date "year" output.check + new.sentence + organization output + publisher output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + format.url output + fin.entry +} + +FUNCTION {default.type} { misc } + + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + + + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " \& " * s #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + short.list key field.or.null = or + { pop$ "" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" * } + { numnames #2 > nameptr #2 = and + { "zz" * year field.or.null * " " * } + 'skip$ + if$ + t sortify * + } + if$ + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + + +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + " " + * + year field.or.null sortify + * + " " + * + cite$ + * + #1 entry.max$ substring$ + 'sort.label := + sort.label * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.label next.extra } + +INTEGERS { longest.label.width last.extra.num number.label } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := + #0 'number.label := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\providecommand{\natexlab}[1]{#1}" + write$ newline$ + "\providecommand{\url}[1]{\texttt{#1}}" + write$ newline$ + "\expandafter\ifx\csname urlstyle\endcsname\relax" + write$ newline$ + " \providecommand{\doi}[1]{doi: #1}\else" + write$ newline$ + " \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi" + write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.pdf b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.pdf new file mode 100644 index 0000000000000000000000000000000000000000..1e78480975a5878619e71b1dc7957d6eb9489c4b GIT binary patch literal 122635 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October 2014 + +% This file can be used with Latex2e whether running in main mode, or +% 2.09 compatibility mode. +% +% If using main mode, you need to include the commands +% \documentclass{article} +% \usepackage{colm14submit_e} +% + +% Define options +\newif\ifcolmsubmission +\newif\ifcolmpreprint +\newif\ifcolmfinal + +% Set submission as default +\colmsubmissiontrue +\colmpreprintfalse +\colmfinalfalse + +% Define option handling +\DeclareOption{submission}{\colmsubmissiontrue\colmpreprintfalse\colmfinalfalse} +\DeclareOption{preprint}{\colmsubmissionfalse\colmpreprinttrue\colmfinalfalse} +\DeclareOption{final}{\colmsubmissionfalse\colmpreprintfalse\colmfinaltrue} +\ProcessOptions\relax + + +% Palatino font +\RequirePackage{tgpagella} % text only +\RequirePackage{mathpazo} % math & text +\RequirePackage{inconsolata} % for tt font + +% Change the overall width of the page. If these parameters are +% changed, they will require corresponding changes in the +% maketitle section. +% +\usepackage{eso-pic} % used by \AddToShipoutPicture +\RequirePackage{fancyhdr} +\RequirePackage{natbib} + +% modification to natbib citations +\setcitestyle{authoryear,round,citesep={;},aysep={,},yysep={;}} + +\renewcommand{\topfraction}{0.95} % let figure take up nearly whole page +\renewcommand{\textfraction}{0.05} % let figure take up nearly whole page + + +% Specify the dimensions of each page + +\setlength{\paperheight}{11in} +\setlength{\paperwidth}{8.5in} + + +\oddsidemargin .5in % Note \oddsidemargin = \evensidemargin +\evensidemargin .5in +\marginparwidth 0.07 true in +%\marginparwidth 0.75 true in +%\topmargin 0 true pt % Nominal distance from top of page to top of +%\topmargin 0.125in +\topmargin -0.625in +\addtolength{\headsep}{0.25in} +\textheight 9.0 true in % Height of text (including footnotes & figures) +\textwidth 5.5 true in % Width of text line. +\widowpenalty=10000 +\clubpenalty=10000 + +% \thispagestyle{empty} \pagestyle{empty} +\flushbottom \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par +\begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} % for perfect author + % name centering +% The footnote-mark was overlapping the footnote-text, +% added the following to fix this problem (MK) + \long\def\@makefntext##1{\parindent 1em\noindent + \hbox to1.8em{\hss $\m@th ^{\@thefnmark}$}##1} + \@maketitle \@thanks +\endgroup +\setcounter{footnote}{0} +\let\maketitle\relax \let\@maketitle\relax +\gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} + +% The toptitlebar has been raised to top-justify the first page + +\usepackage{fancyhdr} +\pagestyle{fancy} +\renewcommand{\headrulewidth}{1.5pt} +\fancyhead{} + +% Title (includes both anonymized and non-anonymized versions) +\def\@maketitle{\vbox{\hsize\textwidth +%\linewidth\hsize \vskip 0.1in \toptitlebar \centering +{\Large\bf \@title\par} +%\bottomtitlebar % \vskip 0.1in % minus +\ifcolmfinal + \lhead{Published as a conference paper at COLM 2025} + \def\And{\end{tabular}\hfil\linebreak[0]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \def\AND{\end{tabular}\hfil\linebreak[4]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\@author\end{tabular}% +\else\ifcolmpreprint +\lhead{Preprint. Under review.} +\def\And{\end{tabular}\hfil\linebreak[0]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% +\def\AND{\end{tabular}\hfil\linebreak[4]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% +\begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\@author\end{tabular}% +\else +\lhead{Under review as a conference paper at COLM 2025} + \def\And{\end{tabular}\hfil\linebreak[0]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \def\AND{\end{tabular}\hfil\linebreak[4]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}Anonymous authors\\Paper under double-blind review\end{tabular}% +\fi\fi +\vskip 0.3in minus 0.1in}} + +\renewenvironment{abstract}{\vskip.075in\centerline{\large\bf +Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +%\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} % got rid of @ (MK) +\def\normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} + + + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex +minus0.2ex}{\large\bf\raggedright}} + +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus +-0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex +plus -0.5ex minus -.2ex}{0.5ex plus +.2ex}{\normalsize\bf\itshape\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus +0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\it}} +\def\subsubsubsection{\vskip +5pt{\noindent\normalsize\raggedright}} + + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 12pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 0pt +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt +\parskip .5pc + + +%\leftmargin2em +\leftmargin3pc +\leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em + +%\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + + +\def\toptitlebar{\hrule height4pt\vskip .25in\vskip-\parskip} + +\def\bottomtitlebar{\vskip .29in\vskip-\parskip\hrule height1pt\vskip +.09in} % +%Reduced second vskip to compensate for adding the strut in \@author + + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.tex new file mode 100644 index 0000000..cd02cdc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/colm2025_conference.tex @@ -0,0 +1,305 @@ + +\documentclass{article} % For LaTeX2e +\usepackage[submission]{colm2025_conference} + +\usepackage{microtype} +\usepackage{hyperref} +\usepackage{url} +\usepackage{booktabs} + +\usepackage{lineno} + +\definecolor{darkblue}{rgb}{0, 0, 0.5} +\hypersetup{colorlinks=true, citecolor=darkblue, linkcolor=darkblue, urlcolor=darkblue} + + +\title{Formatting Instructions for COLM 2025 \\ Conference Submissions} + +% Authors must not appear in the submitted version. They should be hidden +% as long as the \colmfinalcopy macro remains commented out below. +% Non-anonymous submissions will be rejected without review. + +\author{Antiquus S.~Hippocampus, Natalia Cerebro \& Amelie P. Amygdale \thanks{ Use footnote for providing further information +about author (webpage, alternative address)---\emph{not} for acknowledging +funding agencies. Funding acknowledgements go at the end of the paper.} \\ +Department of Computer Science\\ +Cranberry-Lemon University\\ +Pittsburgh, PA 15213, USA \\ +\texttt{\{hippo,brain,jen\}@cs.cranberry-lemon.edu} \\ +\And +Ji Q. Ren \& Yevgeny LeNet \\ +Department of Computational Neuroscience \\ +University of the Witwatersrand \\ +Joburg, South Africa \\ +\texttt{\{robot,net\}@wits.ac.za} \\ +\AND +Coauthor \\ +Affiliation \\ +Address \\ +\texttt{email} +} + +% The \author macro works with any number of authors. There are two commands +% used to separate the names and addresses of multiple authors: \And and \AND. +% +% Using \And between authors leaves it to \LaTeX{} to determine where to break +% the lines. Using \AND forces a linebreak at that point. So, if \LaTeX{} +% puts 3 of 4 authors names on the first line, and the last on the second +% line, try using \AND instead of \And before the third author name. + +\newcommand{\fix}{\marginpar{FIX}} +\newcommand{\new}{\marginpar{NEW}} + +\begin{document} + +\ifcolmsubmission +\linenumbers +\fi + +\maketitle + +\begin{abstract} +The abstract paragraph should be indented 1/2~inch (3~picas) on both left and +right-hand margins. Use 10~point type, with a vertical spacing of 11~points. +The word \textit{Abstract} must be centered and in point size 12. Two +line spaces precede the abstract. The abstract must be limited to one +paragraph. +\end{abstract} + +\section{Submission of conference papers to COLM 2025} + +COLM requires electronic submissions, processed by +\url{https://openreview.net/}. See COLM's website for more instructions. +The format for the submissions is a variant of the NeurIPS and ICLR formats. +Please read carefully the instructions below, and follow them +faithfully. + + +\subsection{Style} + +Papers to be submitted to COLM 2025 must be prepared according to the +instructions presented here. + +%% Please note that we have introduced automatic line number generation +%% into the style file for \LaTeXe. This is to help reviewers +%% refer to specific lines of the paper when they make their comments. Please do +%% NOT refer to these line numbers in your paper as they will be removed from the +%% style file for the final version of accepted papers. + +Authors are required to use the COLM \LaTeX{} style files obtainable at the +COLM website. Please make sure you use the current files and +not previous versions. Tweaking the style files may be grounds for rejection. + +\subsubsection{Copy Options} + +If your paper is ultimately accepted, the option {\tt + {\textbackslash}final} should be set for the {\tt {\textbackslash}usepackage[submission]\{colm2025\_conference\}} command for the camera ready version. The {\tt submission} options is the default, and is to be used for all submissions during the review process. It also turns on the line numbers. If you wish to submit a preprint, the option {\tt preprint} should be used. + + + +\subsection{Retrieval of style files} + +The style files for COLM and other conference information are available online at: +\begin{center} + \url{http://www.colmweb.org/} +\end{center} +The file \verb+colm2025_conference.pdf+ contains these +instructions and illustrates the +various formatting requirements your COLM paper must satisfy. +Submissions must be made using \LaTeX{} and the style files +\verb+colm2025_conference.sty+ and \verb+colm2025_conference.bst+ (to be used with \LaTeX{}2e). The file +\verb+colm2025_conference.tex+ may be used as a ``shell'' for writing your paper. All you +have to do is replace the author, title, abstract, and text of the paper with +your own. + +The formatting instructions contained in these style files are summarized in +sections \ref{gen_inst}, \ref{headings}, and \ref{others} below. + +\section{General formatting instructions} +\label{gen_inst} + +The text must be confined within a rectangle 5.5~inches (33~picas) wide and +9~inches (54~picas) long. The left margin is 1.5~inch (9~picas). +Use 10~point type with a vertical spacing of 11~points. Palatino is the +preferred typeface throughout, and is mandatory for the main text. Paragraphs are separated by 1/2~line space, with no indentation. + +Paper title is 17~point and left-aligned. +All pages should start at 1~inch (6~picas) from the top of the page. + +Please verify that any custom header information you may add does not override the style defined in this document. This has been known to occur especially when submissions are converted to a new template from a previous one (i.e., for re-submission to a different venue). + +Authors' names are +set in boldface, and each name is placed above its corresponding +address. The lead author's name is to be listed first, and +the co-authors' names are set to follow. Authors sharing the +same address can be on the same line. + +Please pay special attention to the instructions in section \ref{others} +regarding figures, tables, acknowledgements, and references. + + +There will be a strict upper limit of 9 pages for the main text of the initial submission, with unlimited additional pages for citations. + +We strongly recommend following arXiv's guidelines for making your paper friendly for HTML conversion: \url{https://info.arxiv.org/help/submit_latex_best_practices.html}. + + +\section{Headings: first level} +\label{headings} + +First level headings are in lower case (except for first word and proper nouns), bold face, +flush left and in point size 12. One line space before the first level +heading and 1/2~line space after the first level heading. + +\subsection{Headings: second level} + +Second level headings are in lower case (except for first word and proper nouns), bold face, +flush left and in point size 10. One line space before the second level +heading and 1/2~line space after the second level heading. + +\subsubsection{Headings: third level} + +Third level headings are in lower case (except for first word and proper nouns), bold face, italics, +flush left and in point size 10. One line space before the third level +heading and 1/2~line space after the third level heading. + +\section{Citations, figures, tables, references}\label{others} + +These instructions apply to everyone, regardless of the formatter being used. + +\subsection{Citations within the text} + +Citations within the text should be based on the \texttt{natbib} package +and include the authors' last names and year (with the ``et~al.'' construct +for more than two authors). When the authors or the publication are +included in the sentence, the citation should not be in parenthesis using \verb|\citet{}| (as +in ``See \citet{Vaswani+2017} for more information.''). Otherwise, the citation +should be in parenthesis using \verb|\citep{}| (as in ``Transformers are a key tool +for developing language models~\citep{Vaswani+2017}.''). + +The corresponding references are to be listed in alphabetical order of +authors, in the \textsc{References} section. As to the format of the +references themselves, any style is acceptable as long as it is used +consistently. + +\subsection{Footnotes} + +Indicate footnotes with a number\footnote{Sample of the first footnote} in the +text. Place the footnotes at the bottom of the page on which they appear. +Precede the footnote with a horizontal rule of 2~inches +(12~picas).\footnote{Sample of the second footnote} + +\subsection{Figures} + +All artwork must be neat, clean, and legible. Lines should be dark +enough for purposes of reproduction; art work should not be +hand-drawn. Any text within the figure must be readable. We ask to not use font sizes below {\tt small}. We strongly recommend to use vector representations (e.g., pdf or svg) for all diagrams. +We strongly recommend positioning all figures at the top or bottom of the page. + +The figure number and caption always appear below the figure. Place one line space before the figure caption, and one line space after the figure. The figure caption is lower case (except for first word and proper nouns); figures are numbered consecutively. +Make sure the figure caption does not get separated from the figure. +Leave sufficient space to avoid splitting the figure and figure caption. + +You may use color figures. +However, it is best for the +figure captions and the paper body to make sense if the paper is printed +either in black/white or in color. +\begin{figure}[t] +\begin{center} +%\framebox[4.0in]{$\;$} +\fbox{\rule[-.5cm]{0cm}{4cm} \rule[-.5cm]{4cm}{0cm}} +\end{center} +\caption{Sample figure caption.} +\end{figure} + +\subsection{Tables} + +All tables must be centered, neat, clean and legible. Do not use hand-drawn tables. The table number and title always appear below the table. See Table~\ref{sample-table}. Please do not use font sizes below {\tt small} in tables. We recommend using {\tt booktabs} or a similar package to style tables. +We strongly recommend positioning all tables at the top or bottom of the page. + +Place one line space before the table title, one line space after the table title, and one line space after the table. The table title must be lowercase (except for first word and proper nouns); tables are numbered consecutively. + +\begin{table}[t] +\begin{center} +\begin{tabular}{ll} +\toprule +\multicolumn{1}{c}{\bf PART} &\multicolumn{1}{c}{\bf DESCRIPTION} \\ +\midrule +Dendrite &Input terminal \\ +Axon &Output terminal \\ +Soma &Cell body (contains cell nucleus) \\ +\bottomrule +\end{tabular} +\end{center} +\caption{Sample table title}\label{sample-table} +\end{table} + + + + +\section{Final instructions} +Do not change any aspects of the formatting parameters in the style files. +In particular, do not modify the width or length of the rectangle the text +should fit into, and do not change font sizes (except perhaps in the +\textsc{References} section; see below). Please note that pages should be +numbered. + +\section{Preparing PostScript or PDF files} + +Please prepare PostScript or PDF files with paper size ``US Letter'', and +not, for example, ``A4''. The -t +letter option on dvips will produce US Letter files. + +Consider directly generating PDF files using \verb+pdflatex+ +(especially if you are a MiKTeX user). +PDF figures must be substituted for EPS figures, however. + +Otherwise, please generate your PostScript and PDF files with the following commands: +\begin{verbatim} +dvips mypaper.dvi -t letter -Ppdf -G0 -o mypaper.ps +ps2pdf mypaper.ps mypaper.pdf +\end{verbatim} + +\subsection{Margins in LaTeX} + +Most of the margin problems come from figures positioned by hand using +\verb+\special+ or other commands. We suggest using the command +\verb+\includegraphics+ +from the graphicx package. Always specify the figure width as a multiple of +the line width as in the example below using .eps graphics +\begin{verbatim} + \usepackage[dvips]{graphicx} ... + \includegraphics[width=0.8\linewidth]{myfile.eps} +\end{verbatim} +or % Apr 2009 addition +\begin{verbatim} + \usepackage[pdftex]{graphicx} ... + \includegraphics[width=0.8\linewidth]{myfile.pdf} +\end{verbatim} +for .pdf graphics. +See section~4.4 in the graphics bundle documentation (\url{http://www.ctan.org/tex-archive/macros/latex/required/graphics/grfguide.ps}) + +A number of width problems arise when LaTeX cannot properly hyphenate a +line. Please give LaTeX hyphenation hints using the \verb+\-+ command. + +\section*{Author Contributions} +If you'd like to, you may include a section for author contributions as is done +in many journals. This is optional and at the discretion of the authors. + +\section*{Acknowledgments} +Use unnumbered first level headings for the acknowledgments. All +acknowledgments, including those to funding agencies, go at the end of the paper. + +\section*{Ethics Statement} +Authors can add an optional ethics statement to the paper. +For papers that touch on ethical issues, this section will be evaluated as part of the review process. The ethics statement should come at the end of the paper. It does not count toward the page limit, but should not be more than 1 page. + + + +\bibliography{colm2025_conference} +\bibliographystyle{colm2025_conference} + +\appendix +\section{Appendix} +You may include other additional sections here. + +\end{document} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/fancyhdr.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/fancyhdr.sty new file mode 100644 index 0000000..77ed4e3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/fancyhdr.sty @@ -0,0 +1,485 @@ +% fancyhdr.sty version 3.2 +% Fancy headers and footers for LaTeX. +% Piet van Oostrum, +% Dept of Computer and Information Sciences, University of Utrecht, +% Padualaan 14, P.O. Box 80.089, 3508 TB Utrecht, The Netherlands +% Telephone: +31 30 2532180. Email: piet@cs.uu.nl +% ======================================================================== +% LICENCE: +% This file may be distributed under the terms of the LaTeX Project Public +% License, as described in lppl.txt in the base LaTeX distribution. +% Either version 1 or, at your option, any later version. +% ======================================================================== +% MODIFICATION HISTORY: +% Sep 16, 1994 +% version 1.4: Correction for use with \reversemargin +% Sep 29, 1994: +% version 1.5: Added the \iftopfloat, \ifbotfloat and \iffloatpage commands +% Oct 4, 1994: +% version 1.6: Reset single spacing in headers/footers for use with +% setspace.sty or doublespace.sty +% Oct 4, 1994: +% version 1.7: changed \let\@mkboth\markboth to +% \def\@mkboth{\protect\markboth} to make it more robust +% Dec 5, 1994: +% version 1.8: corrections for amsbook/amsart: define \@chapapp and (more +% importantly) use the \chapter/sectionmark definitions from ps@headings if +% they exist (which should be true for all standard classes). +% May 31, 1995: +% version 1.9: The proposed \renewcommand{\headrulewidth}{\iffloatpage... +% construction in the doc did not work properly with the fancyplain style. +% June 1, 1995: +% version 1.91: The definition of \@mkboth wasn't restored on subsequent +% \pagestyle{fancy}'s. +% June 1, 1995: +% version 1.92: The sequence \pagestyle{fancyplain} \pagestyle{plain} +% \pagestyle{fancy} would erroneously select the plain version. +% June 1, 1995: +% version 1.93: \fancypagestyle command added. +% Dec 11, 1995: +% version 1.94: suggested by Conrad Hughes <chughes@maths.tcd.ie> +% CJCH, Dec 11, 1995: added \footruleskip to allow control over footrule +% position (old hardcoded value of .3\normalbaselineskip is far too high +% when used with very small footer fonts). +% Jan 31, 1996: +% version 1.95: call \@normalsize in the reset code if that is defined, +% otherwise \normalsize. +% this is to solve a problem with ucthesis.cls, as this doesn't +% define \@currsize. Unfortunately for latex209 calling \normalsize doesn't +% work as this is optimized to do very little, so there \@normalsize should +% be called. Hopefully this code works for all versions of LaTeX known to +% mankind. +% April 25, 1996: +% version 1.96: initialize \headwidth to a magic (negative) value to catch +% most common cases that people change it before calling \pagestyle{fancy}. +% Note it can't be initialized when reading in this file, because +% \textwidth could be changed afterwards. This is quite probable. +% We also switch to \MakeUppercase rather than \uppercase and introduce a +% \nouppercase command for use in headers. and footers. +% May 3, 1996: +% version 1.97: Two changes: +% 1. Undo the change in version 1.8 (using the pagestyle{headings} defaults +% for the chapter and section marks. The current version of amsbook and +% amsart classes don't seem to need them anymore. Moreover the standard +% latex classes don't use \markboth if twoside isn't selected, and this is +% confusing as \leftmark doesn't work as expected. +% 2. include a call to \ps@empty in ps@@fancy. This is to solve a problem +% in the amsbook and amsart classes, that make global changes to \topskip, +% which are reset in \ps@empty. Hopefully this doesn't break other things. +% May 7, 1996: +% version 1.98: +% Added % after the line \def\nouppercase +% May 7, 1996: +% version 1.99: This is the alpha version of fancyhdr 2.0 +% Introduced the new commands \fancyhead, \fancyfoot, and \fancyhf. +% Changed \headrulewidth, \footrulewidth, \footruleskip to +% macros rather than length parameters, In this way they can be +% conditionalized and they don't consume length registers. There is no need +% to have them as length registers unless you want to do calculations with +% them, which is unlikely. Note that this may make some uses of them +% incompatible (i.e. if you have a file that uses \setlength or \xxxx=) +% May 10, 1996: +% version 1.99a: +% Added a few more % signs +% May 10, 1996: +% version 1.99b: +% Changed the syntax of \f@nfor to be resistent to catcode changes of := +% Removed the [1] from the defs of \lhead etc. because the parameter is +% consumed by the \@[xy]lhead etc. macros. +% June 24, 1997: +% version 1.99c: +% corrected \nouppercase to also include the protected form of \MakeUppercase +% \global added to manipulation of \headwidth. +% \iffootnote command added. +% Some comments added about \@fancyhead and \@fancyfoot. +% Aug 24, 1998 +% version 1.99d +% Changed the default \ps@empty to \ps@@empty in order to allow +% \fancypagestyle{empty} redefinition. +% Oct 11, 2000 +% version 2.0 +% Added LPPL license clause. +% +% A check for \headheight is added. An errormessage is given (once) if the +% header is too large. Empty headers don't generate the error even if +% \headheight is very small or even 0pt. +% Warning added for the use of 'E' option when twoside option is not used. +% In this case the 'E' fields will never be used. +% +% Mar 10, 2002 +% version 2.1beta +% New command: \fancyhfoffset[place]{length} +% defines offsets to be applied to the header/footer to let it stick into +% the margins (if length > 0). +% place is like in fancyhead, except that only E,O,L,R can be used. +% This replaces the old calculation based on \headwidth and the marginpar +% area. +% \headwidth will be dynamically calculated in the headers/footers when +% this is used. +% +% Mar 26, 2002 +% version 2.1beta2 +% \fancyhfoffset now also takes h,f as possible letters in the argument to +% allow the header and footer widths to be different. +% New commands \fancyheadoffset and \fancyfootoffset added comparable to +% \fancyhead and \fancyfoot. +% Errormessages and warnings have been made more informative. +% +% Dec 9, 2002 +% version 2.1 +% The defaults for \footrulewidth, \plainheadrulewidth and +% \plainfootrulewidth are changed from \z@skip to 0pt. In this way when +% someone inadvertantly uses \setlength to change any of these, the value +% of \z@skip will not be changed, rather an errormessage will be given. + +% March 3, 2004 +% Release of version 3.0 + +% Oct 7, 2004 +% version 3.1 +% Added '\endlinechar=13' to \fancy@reset to prevent problems with +% includegraphics in header when verbatiminput is active. + +% March 22, 2005 +% version 3.2 +% reset \everypar (the real one) in \fancy@reset because spanish.ldf does +% strange things with \everypar between << and >>. + +\def\ifancy@mpty#1{\def\temp@a{#1}\ifx\temp@a\@empty} + +\def\fancy@def#1#2{\ifancy@mpty{#2}\fancy@gbl\def#1{\leavevmode}\else + \fancy@gbl\def#1{#2\strut}\fi} + +\let\fancy@gbl\global + +\def\@fancyerrmsg#1{% + \ifx\PackageError\undefined + \errmessage{#1}\else + \PackageError{Fancyhdr}{#1}{}\fi} +\def\@fancywarning#1{% + \ifx\PackageWarning\undefined + \errmessage{#1}\else + \PackageWarning{Fancyhdr}{#1}{}\fi} + +% Usage: \@forc \var{charstring}{command to be executed for each char} +% This is similar to LaTeX's \@tfor, but expands the charstring. + +\def\@forc#1#2#3{\expandafter\f@rc\expandafter#1\expandafter{#2}{#3}} +\def\f@rc#1#2#3{\def\temp@ty{#2}\ifx\@empty\temp@ty\else + \f@@rc#1#2\f@@rc{#3}\fi} +\def\f@@rc#1#2#3\f@@rc#4{\def#1{#2}#4\f@rc#1{#3}{#4}} + +% Usage: \f@nfor\name:=list\do{body} +% Like LaTeX's \@for but an empty list is treated as a list with an empty +% element + +\newcommand{\f@nfor}[3]{\edef\@fortmp{#2}% + \expandafter\@forloop#2,\@nil,\@nil\@@#1{#3}} + +% Usage: \def@ult \cs{defaults}{argument} +% sets \cs to the characters from defaults appearing in argument +% or defaults if it would be empty. All characters are lowercased. + +\newcommand\def@ult[3]{% + \edef\temp@a{\lowercase{\edef\noexpand\temp@a{#3}}}\temp@a + \def#1{}% + \@forc\tmpf@ra{#2}% + {\expandafter\if@in\tmpf@ra\temp@a{\edef#1{#1\tmpf@ra}}{}}% + \ifx\@empty#1\def#1{#2}\fi} +% +% \if@in <char><set><truecase><falsecase> +% +\newcommand{\if@in}[4]{% + \edef\temp@a{#2}\def\temp@b##1#1##2\temp@b{\def\temp@b{##1}}% + \expandafter\temp@b#2#1\temp@b\ifx\temp@a\temp@b #4\else #3\fi} + +\newcommand{\fancyhead}{\@ifnextchar[{\f@ncyhf\fancyhead h}% + {\f@ncyhf\fancyhead h[]}} +\newcommand{\fancyfoot}{\@ifnextchar[{\f@ncyhf\fancyfoot f}% + {\f@ncyhf\fancyfoot f[]}} +\newcommand{\fancyhf}{\@ifnextchar[{\f@ncyhf\fancyhf{}}% + {\f@ncyhf\fancyhf{}[]}} + +% New commands for offsets added + +\newcommand{\fancyheadoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyheadoffset h}% + {\f@ncyhfoffs\fancyheadoffset h[]}} +\newcommand{\fancyfootoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyfootoffset f}% + {\f@ncyhfoffs\fancyfootoffset f[]}} +\newcommand{\fancyhfoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyhfoffset{}}% + {\f@ncyhfoffs\fancyhfoffset{}[]}} + +% The header and footer fields are stored in command sequences with +% names of the form: \f@ncy<x><y><z> with <x> for [eo], <y> from [lcr] +% and <z> from [hf]. + +\def\f@ncyhf#1#2[#3]#4{% + \def\temp@c{}% + \@forc\tmpf@ra{#3}% + {\expandafter\if@in\tmpf@ra{eolcrhf,EOLCRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else + \@fancyerrmsg{Illegal char `\temp@c' in \string#1 argument: + [#3]}% + \fi + \f@nfor\temp@c{#3}% + {\def@ult\f@@@eo{eo}\temp@c + \if@twoside\else + \if\f@@@eo e\@fancywarning + {\string#1's `E' option without twoside option is useless}\fi\fi + \def@ult\f@@@lcr{lcr}\temp@c + \def@ult\f@@@hf{hf}{#2\temp@c}% + \@forc\f@@eo\f@@@eo + {\@forc\f@@lcr\f@@@lcr + {\@forc\f@@hf\f@@@hf + {\expandafter\fancy@def\csname + f@ncy\f@@eo\f@@lcr\f@@hf\endcsname + {#4}}}}}} + +\def\f@ncyhfoffs#1#2[#3]#4{% + \def\temp@c{}% + \@forc\tmpf@ra{#3}% + {\expandafter\if@in\tmpf@ra{eolrhf,EOLRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else + \@fancyerrmsg{Illegal char `\temp@c' in \string#1 argument: + [#3]}% + \fi + \f@nfor\temp@c{#3}% + {\def@ult\f@@@eo{eo}\temp@c + \if@twoside\else + \if\f@@@eo e\@fancywarning + {\string#1's `E' option without twoside option is useless}\fi\fi + \def@ult\f@@@lcr{lr}\temp@c + \def@ult\f@@@hf{hf}{#2\temp@c}% + \@forc\f@@eo\f@@@eo + {\@forc\f@@lcr\f@@@lcr + {\@forc\f@@hf\f@@@hf + {\expandafter\setlength\csname + f@ncyO@\f@@eo\f@@lcr\f@@hf\endcsname + {#4}}}}}% + \fancy@setoffs} + +% Fancyheadings version 1 commands. These are more or less deprecated, +% but they continue to work. + +\newcommand{\lhead}{\@ifnextchar[{\@xlhead}{\@ylhead}} +\def\@xlhead[#1]#2{\fancy@def\f@ncyelh{#1}\fancy@def\f@ncyolh{#2}} +\def\@ylhead#1{\fancy@def\f@ncyelh{#1}\fancy@def\f@ncyolh{#1}} + +\newcommand{\chead}{\@ifnextchar[{\@xchead}{\@ychead}} +\def\@xchead[#1]#2{\fancy@def\f@ncyech{#1}\fancy@def\f@ncyoch{#2}} +\def\@ychead#1{\fancy@def\f@ncyech{#1}\fancy@def\f@ncyoch{#1}} + +\newcommand{\rhead}{\@ifnextchar[{\@xrhead}{\@yrhead}} +\def\@xrhead[#1]#2{\fancy@def\f@ncyerh{#1}\fancy@def\f@ncyorh{#2}} +\def\@yrhead#1{\fancy@def\f@ncyerh{#1}\fancy@def\f@ncyorh{#1}} + +\newcommand{\lfoot}{\@ifnextchar[{\@xlfoot}{\@ylfoot}} +\def\@xlfoot[#1]#2{\fancy@def\f@ncyelf{#1}\fancy@def\f@ncyolf{#2}} +\def\@ylfoot#1{\fancy@def\f@ncyelf{#1}\fancy@def\f@ncyolf{#1}} + +\newcommand{\cfoot}{\@ifnextchar[{\@xcfoot}{\@ycfoot}} +\def\@xcfoot[#1]#2{\fancy@def\f@ncyecf{#1}\fancy@def\f@ncyocf{#2}} +\def\@ycfoot#1{\fancy@def\f@ncyecf{#1}\fancy@def\f@ncyocf{#1}} + +\newcommand{\rfoot}{\@ifnextchar[{\@xrfoot}{\@yrfoot}} +\def\@xrfoot[#1]#2{\fancy@def\f@ncyerf{#1}\fancy@def\f@ncyorf{#2}} +\def\@yrfoot#1{\fancy@def\f@ncyerf{#1}\fancy@def\f@ncyorf{#1}} + +\newlength{\fancy@headwidth} +\let\headwidth\fancy@headwidth +\newlength{\f@ncyO@elh} +\newlength{\f@ncyO@erh} +\newlength{\f@ncyO@olh} +\newlength{\f@ncyO@orh} +\newlength{\f@ncyO@elf} +\newlength{\f@ncyO@erf} +\newlength{\f@ncyO@olf} +\newlength{\f@ncyO@orf} +\newcommand{\headrulewidth}{0.4pt} +\newcommand{\footrulewidth}{0pt} +\newcommand{\footruleskip}{.3\normalbaselineskip} + +% Fancyplain stuff shouldn't be used anymore (rather +% \fancypagestyle{plain} should be used), but it must be present for +% compatibility reasons. + +\newcommand{\plainheadrulewidth}{0pt} +\newcommand{\plainfootrulewidth}{0pt} +\newif\if@fancyplain \@fancyplainfalse +\def\fancyplain#1#2{\if@fancyplain#1\else#2\fi} + +\headwidth=-123456789sp %magic constant + +% Command to reset various things in the headers: +% a.o. single spacing (taken from setspace.sty) +% and the catcode of ^^M (so that epsf files in the header work if a +% verbatim crosses a page boundary) +% It also defines a \nouppercase command that disables \uppercase and +% \Makeuppercase. It can only be used in the headers and footers. +\let\fnch@everypar\everypar% save real \everypar because of spanish.ldf +\def\fancy@reset{\fnch@everypar{}\restorecr\endlinechar=13 + \def\baselinestretch{1}% + \def\nouppercase##1{{\let\uppercase\relax\let\MakeUppercase\relax + \expandafter\let\csname MakeUppercase \endcsname\relax##1}}% + \ifx\undefined\@newbaseline% NFSS not present; 2.09 or 2e + \ifx\@normalsize\undefined \normalsize % for ucthesis.cls + \else \@normalsize \fi + \else% NFSS (2.09) present + \@newbaseline% + \fi} + +% Initialization of the head and foot text. + +% The default values still contain \fancyplain for compatibility. +\fancyhf{} % clear all +% lefthead empty on ``plain'' pages, \rightmark on even, \leftmark on odd pages +% evenhead empty on ``plain'' pages, \leftmark on even, \rightmark on odd pages +\if@twoside + \fancyhead[el,or]{\fancyplain{}{\sl\rightmark}} + \fancyhead[er,ol]{\fancyplain{}{\sl\leftmark}} +\else + \fancyhead[l]{\fancyplain{}{\sl\rightmark}} + \fancyhead[r]{\fancyplain{}{\sl\leftmark}} +\fi +\fancyfoot[c]{\rm\thepage} % page number + +% Use box 0 as a temp box and dimen 0 as temp dimen. +% This can be done, because this code will always +% be used inside another box, and therefore the changes are local. + +\def\@fancyvbox#1#2{\setbox0\vbox{#2}\ifdim\ht0>#1\@fancywarning + {\string#1 is too small (\the#1): ^^J Make it at least \the\ht0.^^J + We now make it that large for the rest of the document.^^J + This may cause the page layout to be inconsistent, however\@gobble}% + \dimen0=#1\global\setlength{#1}{\ht0}\ht0=\dimen0\fi + \box0} + +% Put together a header or footer given the left, center and +% right text, fillers at left and right and a rule. +% The \lap commands put the text into an hbox of zero size, +% so overlapping text does not generate an errormessage. +% These macros have 5 parameters: +% 1. LEFTSIDE BEARING % This determines at which side the header will stick +% out. When \fancyhfoffset is used this calculates \headwidth, otherwise +% it is \hss or \relax (after expansion). +% 2. \f@ncyolh, \f@ncyelh, \f@ncyolf or \f@ncyelf. This is the left component. +% 3. \f@ncyoch, \f@ncyech, \f@ncyocf or \f@ncyecf. This is the middle comp. +% 4. \f@ncyorh, \f@ncyerh, \f@ncyorf or \f@ncyerf. This is the right component. +% 5. RIGHTSIDE BEARING. This is always \relax or \hss (after expansion). + +\def\@fancyhead#1#2#3#4#5{#1\hbox to\headwidth{\fancy@reset + \@fancyvbox\headheight{\hbox + {\rlap{\parbox[b]{\headwidth}{\raggedright#2}}\hfill + \parbox[b]{\headwidth}{\centering#3}\hfill + \llap{\parbox[b]{\headwidth}{\raggedleft#4}}}\headrule}}#5} + +\def\@fancyfoot#1#2#3#4#5{#1\hbox to\headwidth{\fancy@reset + \@fancyvbox\footskip{\footrule + \hbox{\rlap{\parbox[t]{\headwidth}{\raggedright#2}}\hfill + \parbox[t]{\headwidth}{\centering#3}\hfill + \llap{\parbox[t]{\headwidth}{\raggedleft#4}}}}}#5} + +\def\headrule{{\if@fancyplain\let\headrulewidth\plainheadrulewidth\fi + \hrule\@height\headrulewidth\@width\headwidth \vskip-\headrulewidth}} + +\def\footrule{{\if@fancyplain\let\footrulewidth\plainfootrulewidth\fi + \vskip-\footruleskip\vskip-\footrulewidth + \hrule\@width\headwidth\@height\footrulewidth\vskip\footruleskip}} + +\def\ps@fancy{% +\@ifundefined{@chapapp}{\let\@chapapp\chaptername}{}%for amsbook +% +% Define \MakeUppercase for old LaTeXen. +% Note: we used \def rather than \let, so that \let\uppercase\relax (from +% the version 1 documentation) will still work. +% +\@ifundefined{MakeUppercase}{\def\MakeUppercase{\uppercase}}{}% +\@ifundefined{chapter}{\def\sectionmark##1{\markboth +{\MakeUppercase{\ifnum \c@secnumdepth>\z@ + \thesection\hskip 1em\relax \fi ##1}}{}}% +\def\subsectionmark##1{\markright {\ifnum \c@secnumdepth >\@ne + \thesubsection\hskip 1em\relax \fi ##1}}}% +{\def\chaptermark##1{\markboth {\MakeUppercase{\ifnum \c@secnumdepth>\m@ne + \@chapapp\ \thechapter. \ \fi ##1}}{}}% +\def\sectionmark##1{\markright{\MakeUppercase{\ifnum \c@secnumdepth >\z@ + \thesection. \ \fi ##1}}}}% +%\csname ps@headings\endcsname % use \ps@headings defaults if they exist +\ps@@fancy +\gdef\ps@fancy{\@fancyplainfalse\ps@@fancy}% +% Initialize \headwidth if the user didn't +% +\ifdim\headwidth<0sp +% +% This catches the case that \headwidth hasn't been initialized and the +% case that the user added something to \headwidth in the expectation that +% it was initialized to \textwidth. We compensate this now. This loses if +% the user intended to multiply it by a factor. But that case is more +% likely done by saying something like \headwidth=1.2\textwidth. +% The doc says you have to change \headwidth after the first call to +% \pagestyle{fancy}. This code is just to catch the most common cases were +% that requirement is violated. +% + \global\advance\headwidth123456789sp\global\advance\headwidth\textwidth +\fi} +\def\ps@fancyplain{\ps@fancy \let\ps@plain\ps@plain@fancy} +\def\ps@plain@fancy{\@fancyplaintrue\ps@@fancy} +\let\ps@@empty\ps@empty +\def\ps@@fancy{% +\ps@@empty % This is for amsbook/amsart, which do strange things with \topskip +\def\@mkboth{\protect\markboth}% +\def\@oddhead{\@fancyhead\fancy@Oolh\f@ncyolh\f@ncyoch\f@ncyorh\fancy@Oorh}% +\def\@oddfoot{\@fancyfoot\fancy@Oolf\f@ncyolf\f@ncyocf\f@ncyorf\fancy@Oorf}% +\def\@evenhead{\@fancyhead\fancy@Oelh\f@ncyelh\f@ncyech\f@ncyerh\fancy@Oerh}% +\def\@evenfoot{\@fancyfoot\fancy@Oelf\f@ncyelf\f@ncyecf\f@ncyerf\fancy@Oerf}% +} +% Default definitions for compatibility mode: +% These cause the header/footer to take the defined \headwidth as width +% And to shift in the direction of the marginpar area + +\def\fancy@Oolh{\if@reversemargin\hss\else\relax\fi} +\def\fancy@Oorh{\if@reversemargin\relax\else\hss\fi} +\let\fancy@Oelh\fancy@Oorh +\let\fancy@Oerh\fancy@Oolh + +\let\fancy@Oolf\fancy@Oolh +\let\fancy@Oorf\fancy@Oorh +\let\fancy@Oelf\fancy@Oelh +\let\fancy@Oerf\fancy@Oerh + +% New definitions for the use of \fancyhfoffset +% These calculate the \headwidth from \textwidth and the specified offsets. + +\def\fancy@offsolh{\headwidth=\textwidth\advance\headwidth\f@ncyO@olh + \advance\headwidth\f@ncyO@orh\hskip-\f@ncyO@olh} +\def\fancy@offselh{\headwidth=\textwidth\advance\headwidth\f@ncyO@elh + \advance\headwidth\f@ncyO@erh\hskip-\f@ncyO@elh} + +\def\fancy@offsolf{\headwidth=\textwidth\advance\headwidth\f@ncyO@olf + \advance\headwidth\f@ncyO@orf\hskip-\f@ncyO@olf} +\def\fancy@offself{\headwidth=\textwidth\advance\headwidth\f@ncyO@elf + \advance\headwidth\f@ncyO@erf\hskip-\f@ncyO@elf} + +\def\fancy@setoffs{% +% Just in case \let\headwidth\textwidth was used + \fancy@gbl\let\headwidth\fancy@headwidth + \fancy@gbl\let\fancy@Oolh\fancy@offsolh + \fancy@gbl\let\fancy@Oelh\fancy@offselh + \fancy@gbl\let\fancy@Oorh\hss + \fancy@gbl\let\fancy@Oerh\hss + \fancy@gbl\let\fancy@Oolf\fancy@offsolf + \fancy@gbl\let\fancy@Oelf\fancy@offself + \fancy@gbl\let\fancy@Oorf\hss + \fancy@gbl\let\fancy@Oerf\hss} + +\newif\iffootnote +\let\latex@makecol\@makecol +\def\@makecol{\ifvoid\footins\footnotetrue\else\footnotefalse\fi +\let\topfloat\@toplist\let\botfloat\@botlist\latex@makecol} +\def\iftopfloat#1#2{\ifx\topfloat\empty #2\else #1\fi} +\def\ifbotfloat#1#2{\ifx\botfloat\empty #2\else #1\fi} +\def\iffloatpage#1#2{\if@fcolmade #1\else #2\fi} + +\newcommand{\fancypagestyle}[2]{% + \@namedef{ps@#1}{\let\fancy@gbl\relax#2\relax\ps@fancy}} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/math_commands.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/math_commands.tex new file mode 100644 index 0000000..0668f93 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/math_commands.tex @@ -0,0 +1,508 @@ +%%%%% NEW MATH DEFINITIONS %%%%% + +\usepackage{amsmath,amsfonts,bm} + +% Mark sections of captions for referring to divisions of figures +\newcommand{\figleft}{{\em (Left)}} +\newcommand{\figcenter}{{\em (Center)}} +\newcommand{\figright}{{\em (Right)}} +\newcommand{\figtop}{{\em (Top)}} +\newcommand{\figbottom}{{\em (Bottom)}} +\newcommand{\captiona}{{\em (a)}} +\newcommand{\captionb}{{\em (b)}} +\newcommand{\captionc}{{\em (c)}} +\newcommand{\captiond}{{\em (d)}} + +% Highlight a newly defined term +\newcommand{\newterm}[1]{{\bf #1}} + + +% Figure reference, lower-case. +\def\figref#1{figure~\ref{#1}} +% Figure reference, capital. For start of sentence +\def\Figref#1{Figure~\ref{#1}} +\def\twofigref#1#2{figures \ref{#1} and \ref{#2}} +\def\quadfigref#1#2#3#4{figures \ref{#1}, \ref{#2}, \ref{#3} and \ref{#4}} +% Section reference, lower-case. +\def\secref#1{section~\ref{#1}} +% Section reference, capital. +\def\Secref#1{Section~\ref{#1}} +% Reference to two sections. +\def\twosecrefs#1#2{sections \ref{#1} and \ref{#2}} +% Reference to three sections. +\def\secrefs#1#2#3{sections \ref{#1}, \ref{#2} and \ref{#3}} +% Reference to an equation, lower-case. +\def\eqref#1{equation~\ref{#1}} +% Reference to an equation, upper case +\def\Eqref#1{Equation~\ref{#1}} +% A raw reference to an equation---avoid using if possible +\def\plaineqref#1{\ref{#1}} +% Reference to a chapter, lower-case. +\def\chapref#1{chapter~\ref{#1}} +% Reference to an equation, upper case. +\def\Chapref#1{Chapter~\ref{#1}} +% Reference to a range of chapters +\def\rangechapref#1#2{chapters\ref{#1}--\ref{#2}} +% Reference to an algorithm, lower-case. +\def\algref#1{algorithm~\ref{#1}} +% Reference to an algorithm, upper case. +\def\Algref#1{Algorithm~\ref{#1}} +\def\twoalgref#1#2{algorithms \ref{#1} and \ref{#2}} +\def\Twoalgref#1#2{Algorithms \ref{#1} and \ref{#2}} +% Reference to a part, lower case +\def\partref#1{part~\ref{#1}} +% Reference to a part, upper case +\def\Partref#1{Part~\ref{#1}} +\def\twopartref#1#2{parts \ref{#1} and \ref{#2}} + +\def\ceil#1{\lceil #1 \rceil} +\def\floor#1{\lfloor #1 \rfloor} +\def\1{\bm{1}} +\newcommand{\train}{\mathcal{D}} +\newcommand{\valid}{\mathcal{D_{\mathrm{valid}}}} +\newcommand{\test}{\mathcal{D_{\mathrm{test}}}} + +\def\eps{{\epsilon}} + + +% Random variables +\def\reta{{\textnormal{$\eta$}}} +\def\ra{{\textnormal{a}}} +\def\rb{{\textnormal{b}}} +\def\rc{{\textnormal{c}}} +\def\rd{{\textnormal{d}}} +\def\re{{\textnormal{e}}} +\def\rf{{\textnormal{f}}} +\def\rg{{\textnormal{g}}} +\def\rh{{\textnormal{h}}} +\def\ri{{\textnormal{i}}} +\def\rj{{\textnormal{j}}} +\def\rk{{\textnormal{k}}} +\def\rl{{\textnormal{l}}} +% rm is already a command, just don't name any random variables m +\def\rn{{\textnormal{n}}} +\def\ro{{\textnormal{o}}} +\def\rp{{\textnormal{p}}} +\def\rq{{\textnormal{q}}} +\def\rr{{\textnormal{r}}} +\def\rs{{\textnormal{s}}} +\def\rt{{\textnormal{t}}} +\def\ru{{\textnormal{u}}} +\def\rv{{\textnormal{v}}} +\def\rw{{\textnormal{w}}} +\def\rx{{\textnormal{x}}} +\def\ry{{\textnormal{y}}} +\def\rz{{\textnormal{z}}} + +% Random vectors +\def\rvepsilon{{\mathbf{\epsilon}}} +\def\rvtheta{{\mathbf{\theta}}} +\def\rva{{\mathbf{a}}} +\def\rvb{{\mathbf{b}}} +\def\rvc{{\mathbf{c}}} +\def\rvd{{\mathbf{d}}} +\def\rve{{\mathbf{e}}} +\def\rvf{{\mathbf{f}}} +\def\rvg{{\mathbf{g}}} +\def\rvh{{\mathbf{h}}} +\def\rvu{{\mathbf{i}}} +\def\rvj{{\mathbf{j}}} +\def\rvk{{\mathbf{k}}} +\def\rvl{{\mathbf{l}}} +\def\rvm{{\mathbf{m}}} +\def\rvn{{\mathbf{n}}} +\def\rvo{{\mathbf{o}}} +\def\rvp{{\mathbf{p}}} +\def\rvq{{\mathbf{q}}} +\def\rvr{{\mathbf{r}}} +\def\rvs{{\mathbf{s}}} +\def\rvt{{\mathbf{t}}} +\def\rvu{{\mathbf{u}}} +\def\rvv{{\mathbf{v}}} +\def\rvw{{\mathbf{w}}} +\def\rvx{{\mathbf{x}}} +\def\rvy{{\mathbf{y}}} +\def\rvz{{\mathbf{z}}} + +% Elements of random vectors +\def\erva{{\textnormal{a}}} +\def\ervb{{\textnormal{b}}} +\def\ervc{{\textnormal{c}}} +\def\ervd{{\textnormal{d}}} +\def\erve{{\textnormal{e}}} +\def\ervf{{\textnormal{f}}} +\def\ervg{{\textnormal{g}}} +\def\ervh{{\textnormal{h}}} +\def\ervi{{\textnormal{i}}} +\def\ervj{{\textnormal{j}}} +\def\ervk{{\textnormal{k}}} +\def\ervl{{\textnormal{l}}} +\def\ervm{{\textnormal{m}}} +\def\ervn{{\textnormal{n}}} +\def\ervo{{\textnormal{o}}} +\def\ervp{{\textnormal{p}}} +\def\ervq{{\textnormal{q}}} +\def\ervr{{\textnormal{r}}} +\def\ervs{{\textnormal{s}}} +\def\ervt{{\textnormal{t}}} +\def\ervu{{\textnormal{u}}} +\def\ervv{{\textnormal{v}}} +\def\ervw{{\textnormal{w}}} +\def\ervx{{\textnormal{x}}} +\def\ervy{{\textnormal{y}}} +\def\ervz{{\textnormal{z}}} + +% Random matrices +\def\rmA{{\mathbf{A}}} +\def\rmB{{\mathbf{B}}} +\def\rmC{{\mathbf{C}}} +\def\rmD{{\mathbf{D}}} +\def\rmE{{\mathbf{E}}} +\def\rmF{{\mathbf{F}}} +\def\rmG{{\mathbf{G}}} +\def\rmH{{\mathbf{H}}} +\def\rmI{{\mathbf{I}}} +\def\rmJ{{\mathbf{J}}} +\def\rmK{{\mathbf{K}}} +\def\rmL{{\mathbf{L}}} +\def\rmM{{\mathbf{M}}} +\def\rmN{{\mathbf{N}}} +\def\rmO{{\mathbf{O}}} +\def\rmP{{\mathbf{P}}} +\def\rmQ{{\mathbf{Q}}} +\def\rmR{{\mathbf{R}}} +\def\rmS{{\mathbf{S}}} +\def\rmT{{\mathbf{T}}} +\def\rmU{{\mathbf{U}}} +\def\rmV{{\mathbf{V}}} +\def\rmW{{\mathbf{W}}} +\def\rmX{{\mathbf{X}}} +\def\rmY{{\mathbf{Y}}} +\def\rmZ{{\mathbf{Z}}} + +% Elements of random matrices +\def\ermA{{\textnormal{A}}} +\def\ermB{{\textnormal{B}}} +\def\ermC{{\textnormal{C}}} +\def\ermD{{\textnormal{D}}} +\def\ermE{{\textnormal{E}}} +\def\ermF{{\textnormal{F}}} +\def\ermG{{\textnormal{G}}} +\def\ermH{{\textnormal{H}}} +\def\ermI{{\textnormal{I}}} +\def\ermJ{{\textnormal{J}}} +\def\ermK{{\textnormal{K}}} +\def\ermL{{\textnormal{L}}} +\def\ermM{{\textnormal{M}}} +\def\ermN{{\textnormal{N}}} +\def\ermO{{\textnormal{O}}} +\def\ermP{{\textnormal{P}}} +\def\ermQ{{\textnormal{Q}}} +\def\ermR{{\textnormal{R}}} +\def\ermS{{\textnormal{S}}} +\def\ermT{{\textnormal{T}}} +\def\ermU{{\textnormal{U}}} +\def\ermV{{\textnormal{V}}} +\def\ermW{{\textnormal{W}}} +\def\ermX{{\textnormal{X}}} +\def\ermY{{\textnormal{Y}}} +\def\ermZ{{\textnormal{Z}}} + +% Vectors +\def\vzero{{\bm{0}}} +\def\vone{{\bm{1}}} +\def\vmu{{\bm{\mu}}} +\def\vtheta{{\bm{\theta}}} +\def\va{{\bm{a}}} +\def\vb{{\bm{b}}} +\def\vc{{\bm{c}}} +\def\vd{{\bm{d}}} +\def\ve{{\bm{e}}} +\def\vf{{\bm{f}}} +\def\vg{{\bm{g}}} +\def\vh{{\bm{h}}} +\def\vi{{\bm{i}}} +\def\vj{{\bm{j}}} +\def\vk{{\bm{k}}} +\def\vl{{\bm{l}}} +\def\vm{{\bm{m}}} +\def\vn{{\bm{n}}} +\def\vo{{\bm{o}}} +\def\vp{{\bm{p}}} +\def\vq{{\bm{q}}} +\def\vr{{\bm{r}}} +\def\vs{{\bm{s}}} +\def\vt{{\bm{t}}} +\def\vu{{\bm{u}}} +\def\vv{{\bm{v}}} +\def\vw{{\bm{w}}} +\def\vx{{\bm{x}}} +\def\vy{{\bm{y}}} +\def\vz{{\bm{z}}} + +% Elements of vectors +\def\evalpha{{\alpha}} +\def\evbeta{{\beta}} +\def\evepsilon{{\epsilon}} +\def\evlambda{{\lambda}} +\def\evomega{{\omega}} +\def\evmu{{\mu}} +\def\evpsi{{\psi}} +\def\evsigma{{\sigma}} +\def\evtheta{{\theta}} +\def\eva{{a}} +\def\evb{{b}} +\def\evc{{c}} +\def\evd{{d}} +\def\eve{{e}} +\def\evf{{f}} +\def\evg{{g}} +\def\evh{{h}} +\def\evi{{i}} +\def\evj{{j}} +\def\evk{{k}} +\def\evl{{l}} +\def\evm{{m}} +\def\evn{{n}} +\def\evo{{o}} +\def\evp{{p}} +\def\evq{{q}} +\def\evr{{r}} +\def\evs{{s}} +\def\evt{{t}} +\def\evu{{u}} +\def\evv{{v}} +\def\evw{{w}} +\def\evx{{x}} +\def\evy{{y}} +\def\evz{{z}} + +% Matrix +\def\mA{{\bm{A}}} +\def\mB{{\bm{B}}} +\def\mC{{\bm{C}}} +\def\mD{{\bm{D}}} +\def\mE{{\bm{E}}} +\def\mF{{\bm{F}}} +\def\mG{{\bm{G}}} +\def\mH{{\bm{H}}} +\def\mI{{\bm{I}}} +\def\mJ{{\bm{J}}} +\def\mK{{\bm{K}}} +\def\mL{{\bm{L}}} +\def\mM{{\bm{M}}} +\def\mN{{\bm{N}}} +\def\mO{{\bm{O}}} +\def\mP{{\bm{P}}} +\def\mQ{{\bm{Q}}} +\def\mR{{\bm{R}}} +\def\mS{{\bm{S}}} +\def\mT{{\bm{T}}} +\def\mU{{\bm{U}}} +\def\mV{{\bm{V}}} +\def\mW{{\bm{W}}} +\def\mX{{\bm{X}}} +\def\mY{{\bm{Y}}} +\def\mZ{{\bm{Z}}} +\def\mBeta{{\bm{\beta}}} +\def\mPhi{{\bm{\Phi}}} +\def\mLambda{{\bm{\Lambda}}} +\def\mSigma{{\bm{\Sigma}}} + +% Tensor +\DeclareMathAlphabet{\mathsfit}{\encodingdefault}{\sfdefault}{m}{sl} +\SetMathAlphabet{\mathsfit}{bold}{\encodingdefault}{\sfdefault}{bx}{n} +\newcommand{\tens}[1]{\bm{\mathsfit{#1}}} +\def\tA{{\tens{A}}} +\def\tB{{\tens{B}}} +\def\tC{{\tens{C}}} +\def\tD{{\tens{D}}} +\def\tE{{\tens{E}}} +\def\tF{{\tens{F}}} +\def\tG{{\tens{G}}} +\def\tH{{\tens{H}}} +\def\tI{{\tens{I}}} +\def\tJ{{\tens{J}}} +\def\tK{{\tens{K}}} +\def\tL{{\tens{L}}} +\def\tM{{\tens{M}}} +\def\tN{{\tens{N}}} +\def\tO{{\tens{O}}} +\def\tP{{\tens{P}}} +\def\tQ{{\tens{Q}}} +\def\tR{{\tens{R}}} +\def\tS{{\tens{S}}} +\def\tT{{\tens{T}}} +\def\tU{{\tens{U}}} +\def\tV{{\tens{V}}} +\def\tW{{\tens{W}}} +\def\tX{{\tens{X}}} +\def\tY{{\tens{Y}}} +\def\tZ{{\tens{Z}}} + + +% Graph +\def\gA{{\mathcal{A}}} +\def\gB{{\mathcal{B}}} +\def\gC{{\mathcal{C}}} +\def\gD{{\mathcal{D}}} +\def\gE{{\mathcal{E}}} +\def\gF{{\mathcal{F}}} +\def\gG{{\mathcal{G}}} +\def\gH{{\mathcal{H}}} +\def\gI{{\mathcal{I}}} +\def\gJ{{\mathcal{J}}} +\def\gK{{\mathcal{K}}} +\def\gL{{\mathcal{L}}} +\def\gM{{\mathcal{M}}} +\def\gN{{\mathcal{N}}} +\def\gO{{\mathcal{O}}} +\def\gP{{\mathcal{P}}} +\def\gQ{{\mathcal{Q}}} +\def\gR{{\mathcal{R}}} +\def\gS{{\mathcal{S}}} +\def\gT{{\mathcal{T}}} +\def\gU{{\mathcal{U}}} +\def\gV{{\mathcal{V}}} +\def\gW{{\mathcal{W}}} +\def\gX{{\mathcal{X}}} +\def\gY{{\mathcal{Y}}} +\def\gZ{{\mathcal{Z}}} + +% Sets +\def\sA{{\mathbb{A}}} +\def\sB{{\mathbb{B}}} +\def\sC{{\mathbb{C}}} +\def\sD{{\mathbb{D}}} +% Don't use a set called E, because this would be the same as our symbol +% for expectation. +\def\sF{{\mathbb{F}}} +\def\sG{{\mathbb{G}}} +\def\sH{{\mathbb{H}}} +\def\sI{{\mathbb{I}}} +\def\sJ{{\mathbb{J}}} +\def\sK{{\mathbb{K}}} +\def\sL{{\mathbb{L}}} +\def\sM{{\mathbb{M}}} +\def\sN{{\mathbb{N}}} +\def\sO{{\mathbb{O}}} +\def\sP{{\mathbb{P}}} +\def\sQ{{\mathbb{Q}}} +\def\sR{{\mathbb{R}}} +\def\sS{{\mathbb{S}}} +\def\sT{{\mathbb{T}}} +\def\sU{{\mathbb{U}}} +\def\sV{{\mathbb{V}}} +\def\sW{{\mathbb{W}}} +\def\sX{{\mathbb{X}}} +\def\sY{{\mathbb{Y}}} +\def\sZ{{\mathbb{Z}}} + +% Entries of a matrix +\def\emLambda{{\Lambda}} +\def\emA{{A}} +\def\emB{{B}} +\def\emC{{C}} +\def\emD{{D}} +\def\emE{{E}} +\def\emF{{F}} +\def\emG{{G}} +\def\emH{{H}} +\def\emI{{I}} +\def\emJ{{J}} +\def\emK{{K}} +\def\emL{{L}} +\def\emM{{M}} +\def\emN{{N}} +\def\emO{{O}} +\def\emP{{P}} +\def\emQ{{Q}} +\def\emR{{R}} +\def\emS{{S}} +\def\emT{{T}} +\def\emU{{U}} +\def\emV{{V}} +\def\emW{{W}} +\def\emX{{X}} +\def\emY{{Y}} +\def\emZ{{Z}} +\def\emSigma{{\Sigma}} + +% entries of a tensor +% Same font as tensor, without \bm wrapper +\newcommand{\etens}[1]{\mathsfit{#1}} +\def\etLambda{{\etens{\Lambda}}} +\def\etA{{\etens{A}}} +\def\etB{{\etens{B}}} +\def\etC{{\etens{C}}} +\def\etD{{\etens{D}}} +\def\etE{{\etens{E}}} +\def\etF{{\etens{F}}} +\def\etG{{\etens{G}}} +\def\etH{{\etens{H}}} +\def\etI{{\etens{I}}} +\def\etJ{{\etens{J}}} +\def\etK{{\etens{K}}} +\def\etL{{\etens{L}}} +\def\etM{{\etens{M}}} +\def\etN{{\etens{N}}} +\def\etO{{\etens{O}}} +\def\etP{{\etens{P}}} +\def\etQ{{\etens{Q}}} +\def\etR{{\etens{R}}} +\def\etS{{\etens{S}}} +\def\etT{{\etens{T}}} +\def\etU{{\etens{U}}} +\def\etV{{\etens{V}}} +\def\etW{{\etens{W}}} +\def\etX{{\etens{X}}} +\def\etY{{\etens{Y}}} +\def\etZ{{\etens{Z}}} + +% The true underlying data generating distribution +\newcommand{\pdata}{p_{\rm{data}}} +% The empirical distribution defined by the training set +\newcommand{\ptrain}{\hat{p}_{\rm{data}}} +\newcommand{\Ptrain}{\hat{P}_{\rm{data}}} +% The model distribution +\newcommand{\pmodel}{p_{\rm{model}}} +\newcommand{\Pmodel}{P_{\rm{model}}} +\newcommand{\ptildemodel}{\tilde{p}_{\rm{model}}} +% Stochastic autoencoder distributions +\newcommand{\pencode}{p_{\rm{encoder}}} +\newcommand{\pdecode}{p_{\rm{decoder}}} +\newcommand{\precons}{p_{\rm{reconstruct}}} + +\newcommand{\laplace}{\mathrm{Laplace}} % Laplace distribution + +\newcommand{\E}{\mathbb{E}} +\newcommand{\Ls}{\mathcal{L}} +\newcommand{\R}{\mathbb{R}} +\newcommand{\emp}{\tilde{p}} +\newcommand{\lr}{\alpha} +\newcommand{\reg}{\lambda} +\newcommand{\rect}{\mathrm{rectifier}} +\newcommand{\softmax}{\mathrm{softmax}} +\newcommand{\sigmoid}{\sigma} +\newcommand{\softplus}{\zeta} +\newcommand{\KL}{D_{\mathrm{KL}}} +\newcommand{\Var}{\mathrm{Var}} +\newcommand{\standarderror}{\mathrm{SE}} +\newcommand{\Cov}{\mathrm{Cov}} +% Wolfram Mathworld says $L^2$ is for function spaces and $\ell^2$ is for vectors +% But then they seem to use $L^2$ for vectors throughout the site, and so does +% wikipedia. +\newcommand{\normlzero}{L^0} +\newcommand{\normlone}{L^1} +\newcommand{\normltwo}{L^2} +\newcommand{\normlp}{L^p} +\newcommand{\normmax}{L^\infty} + +\newcommand{\parents}{Pa} % See usage in notation.tex. Chosen to match Daphne's book. + +\DeclareMathOperator*{\argmax}{arg\,max} +\DeclareMathOperator*{\argmin}{arg\,min} + +\DeclareMathOperator{\sign}{sign} +\DeclareMathOperator{\Tr}{Tr} +\let\ab\allowbreak diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/natbib.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/natbib.sty new file mode 100644 index 0000000..ff0d0b9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/colm2025/natbib.sty @@ -0,0 +1,1246 @@ +%% +%% This is file `natbib.sty', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% natbib.dtx (with options: `package,all') +%% ============================================= +%% IMPORTANT NOTICE: +%% +%% This program can be redistributed and/or modified under the terms +%% of the LaTeX Project Public License Distributed from CTAN +%% archives in directory macros/latex/base/lppl.txt; either +%% version 1 of the License, or any later version. +%% +%% This is a generated file. +%% It may not be distributed without the original source file natbib.dtx. +%% +%% Full documentation can be obtained by LaTeXing that original file. +%% Only a few abbreviated comments remain here to describe the usage. +%% ============================================= +%% Copyright 1993-2009 Patrick W Daly +%% Max-Planck-Institut f\"ur Sonnensystemforschung +%% Max-Planck-Str. 2 +%% D-37191 Katlenburg-Lindau +%% Germany +%% E-mail: daly@mps.mpg.de +\NeedsTeXFormat{LaTeX2e}[1995/06/01] +\ProvidesPackage{natbib} + [2009/07/16 8.31 (PWD, AO)] + + % This package reimplements the LaTeX \cite command to be used for various + % citation styles, both author-year and numerical. It accepts BibTeX + % output intended for many other packages, and therefore acts as a + % general, all-purpose citation-style interface. + % + % With standard numerical .bst files, only numerical citations are + % possible. With an author-year .bst file, both numerical and + % author-year citations are possible. + % + % If author-year citations are selected, \bibitem must have one of the + % following forms: + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Williams]{key}... + % \bibitem[Jones et al., 1990]{key}... + % \bibitem[\protect\citeauthoryear{Jones, Baker, and Williams}{Jones + % et al.}{1990}]{key}... + % \bibitem[\protect\citeauthoryear{Jones et al.}{1990}]{key}... + % \bibitem[\protect\astroncite{Jones et al.}{1990}]{key}... + % \bibitem[\protect\citename{Jones et al., }1990]{key}... + % \harvarditem[Jones et al.]{Jones, Baker, and Williams}{1990}{key}... + % + % This is either to be made up manually, or to be generated by an + % appropriate .bst file with BibTeX. + % Author-year mode || Numerical mode + % Then, \citet{key} ==>> Jones et al. (1990) || Jones et al. [21] + % \citep{key} ==>> (Jones et al., 1990) || [21] + % Multiple citations as normal: + % \citep{key1,key2} ==>> (Jones et al., 1990; Smith, 1989) || [21,24] + % or (Jones et al., 1990, 1991) || [21,24] + % or (Jones et al., 1990a,b) || [21,24] + % \cite{key} is the equivalent of \citet{key} in author-year mode + % and of \citep{key} in numerical mode + % Full author lists may be forced with \citet* or \citep*, e.g. + % \citep*{key} ==>> (Jones, Baker, and Williams, 1990) + % Optional notes as: + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.,][]{key} ==>> (e.g., Jones et al., 1990) + % \citep[see][pg. 34]{key}==>> (see Jones et al., 1990, pg. 34) + % (Note: in standard LaTeX, only one note is allowed, after the ref. + % Here, one note is like the standard, two make pre- and post-notes.) + % \citealt{key} ==>> Jones et al. 1990 + % \citealt*{key} ==>> Jones, Baker, and Williams 1990 + % \citealp{key} ==>> Jones et al., 1990 + % \citealp*{key} ==>> Jones, Baker, and Williams, 1990 + % Additional citation possibilities (both author-year and numerical modes) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Williams + % \citeyear{key} ==>> 1990 + % \citeyearpar{key} ==>> (1990) + % \citetext{priv. comm.} ==>> (priv. comm.) + % \citenum{key} ==>> 11 [non-superscripted] + % Note: full author lists depends on whether the bib style supports them; + % if not, the abbreviated list is printed even when full requested. + % + % For names like della Robbia at the start of a sentence, use + % \Citet{dRob98} ==>> Della Robbia (1998) + % \Citep{dRob98} ==>> (Della Robbia, 1998) + % \Citeauthor{dRob98} ==>> Della Robbia + % + % + % Citation aliasing is achieved with + % \defcitealias{key}{text} + % \citetalias{key} ==>> text + % \citepalias{key} ==>> (text) + % + % Defining the citation mode and punctual (citation style) + % \setcitestyle{<comma-separated list of keywords, same + % as the package options>} + % Example: \setcitestyle{square,semicolon} + % Alternatively: + % Use \bibpunct with 6 mandatory arguments: + % 1. opening bracket for citation + % 2. closing bracket + % 3. citation separator (for multiple citations in one \cite) + % 4. the letter n for numerical styles, s for superscripts + % else anything for author-year + % 5. punctuation between authors and date + % 6. punctuation between years (or numbers) when common authors missing + % One optional argument is the character coming before post-notes. It + % appears in square braces before all other arguments. May be left off. + % Example (and default) \bibpunct[, ]{(}{)}{;}{a}{,}{,} + % + % To make this automatic for a given bib style, named newbib, say, make + % a local configuration file, natbib.cfg, with the definition + % \newcommand{\bibstyle@newbib}{\bibpunct...} + % Then the \bibliographystyle{newbib} will cause \bibstyle@newbib to + % be called on THE NEXT LATEX RUN (via the aux file). + % + % Such preprogrammed definitions may be invoked anywhere in the text + % by calling \citestyle{newbib}. This is only useful if the style specified + % differs from that in \bibliographystyle. + % + % With \citeindextrue and \citeindexfalse, one can control whether the + % \cite commands make an automatic entry of the citation in the .idx + % indexing file. For this, \makeindex must also be given in the preamble. + % + % Package Options: (for selecting punctuation) + % round - round parentheses are used (default) + % square - square brackets are used [option] + % curly - curly braces are used {option} + % angle - angle brackets are used <option> + % semicolon - multiple citations separated by semi-colon (default) + % colon - same as semicolon, an earlier confusion + % comma - separated by comma + % authoryear - selects author-year citations (default) + % numbers- selects numerical citations + % super - numerical citations as superscripts + % sort - sorts multiple citations according to order in ref. list + % sort&compress - like sort, but also compresses numerical citations + % compress - compresses without sorting + % longnamesfirst - makes first citation full author list + % sectionbib - puts bibliography in a \section* instead of \chapter* + % merge - allows the citation key to have a * prefix, + % signifying to merge its reference with that of the previous citation. + % elide - if references are merged, repeated portions of later ones may be removed. + % mcite - recognizes and ignores the * prefix for merging. + % Punctuation so selected dominates over any predefined ones. + % Package options are called as, e.g. + % \usepackage[square,comma]{natbib} + % LaTeX the source file natbib.dtx to obtain more details + % or the file natnotes.tex for a brief reference sheet. + %----------------------------------------------------------- +\providecommand\@ifxundefined[1]{% + \ifx#1\@undefined\expandafter\@firstoftwo\else\expandafter\@secondoftwo\fi +}% +\providecommand\@ifnum[1]{% + \ifnum#1\expandafter\@firstoftwo\else\expandafter\@secondoftwo\fi +}% +\providecommand\@ifx[1]{% + \ifx#1\expandafter\@firstoftwo\else\expandafter\@secondoftwo\fi +}% +\providecommand\appdef[2]{% + \toks@\expandafter{#1}\@temptokena{#2}% + \edef#1{\the\toks@\the\@temptokena}% +}% +\@ifclassloaded{agu2001}{\PackageError{natbib} + {The agu2001 class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{agutex}{\PackageError{natbib} + {The AGUTeX class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{aguplus}{\PackageError{natbib} + {The aguplus class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{nlinproc}{\PackageError{natbib} + {The nlinproc class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{egs}{\PackageError{natbib} + {The egs class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{egu}{\PackageError{natbib} + {The egu class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} + % Define citation punctuation for some author-year styles + % One may add and delete at this point + % Or put additions into local configuration file natbib.cfg +\newcommand\bibstyle@chicago{\bibpunct{(}{)}{;}{a}{,}{,}} +\newcommand\bibstyle@named{\bibpunct{[}{]}{;}{a}{,}{,}} +\newcommand\bibstyle@agu{\bibpunct{[}{]}{;}{a}{,}{,~}}%Amer. Geophys. Union +\newcommand\bibstyle@copernicus{\bibpunct{(}{)}{;}{a}{,}{,}}%Copernicus Publications +\let\bibstyle@egu=\bibstyle@copernicus +\let\bibstyle@egs=\bibstyle@copernicus +\newcommand\bibstyle@agsm{\bibpunct{(}{)}{,}{a}{}{,}\gdef\harvardand{\&}} +\newcommand\bibstyle@kluwer{\bibpunct{(}{)}{,}{a}{}{,}\gdef\harvardand{\&}} +\newcommand\bibstyle@dcu{\bibpunct{(}{)}{;}{a}{;}{,}\gdef\harvardand{and}} +\newcommand\bibstyle@aa{\bibpunct{(}{)}{;}{a}{}{,}} %Astronomy & Astrophysics +\newcommand\bibstyle@pass{\bibpunct{(}{)}{;}{a}{,}{,}}%Planet. & Space Sci +\newcommand\bibstyle@anngeo{\bibpunct{(}{)}{;}{a}{,}{,}}%Annales Geophysicae +\newcommand\bibstyle@nlinproc{\bibpunct{(}{)}{;}{a}{,}{,}}%Nonlin.Proc.Geophys. + % Define citation punctuation for some numerical styles +\newcommand\bibstyle@cospar{\bibpunct{/}{/}{,}{n}{}{}% + \gdef\bibnumfmt##1{##1.}} +\newcommand\bibstyle@esa{\bibpunct{(Ref.~}{)}{,}{n}{}{}% + \gdef\bibnumfmt##1{##1.\hspace{1em}}} +\newcommand\bibstyle@nature{\bibpunct{}{}{,}{s}{}{\textsuperscript{,}}% + \gdef\bibnumfmt##1{##1.}} + % The standard LaTeX styles +\newcommand\bibstyle@plain{\bibpunct{[}{]}{,}{n}{}{,}} +\let\bibstyle@alpha=\bibstyle@plain +\let\bibstyle@abbrv=\bibstyle@plain +\let\bibstyle@unsrt=\bibstyle@plain + % The author-year modifications of the standard styles +\newcommand\bibstyle@plainnat{\bibpunct{[}{]}{,}{a}{,}{,}} +\let\bibstyle@abbrvnat=\bibstyle@plainnat +\let\bibstyle@unsrtnat=\bibstyle@plainnat +\newif\ifNAT@numbers \NAT@numbersfalse +\newif\ifNAT@super \NAT@superfalse +\let\NAT@merge\z@ +\DeclareOption{numbers}{\NAT@numberstrue + \ExecuteOptions{square,comma,nobibstyle}} +\DeclareOption{super}{\NAT@supertrue\NAT@numberstrue + \renewcommand\NAT@open{}\renewcommand\NAT@close{} + \ExecuteOptions{nobibstyle}} +\DeclareOption{authoryear}{\NAT@numbersfalse + \ExecuteOptions{round,semicolon,bibstyle}} +\DeclareOption{round}{% + \renewcommand\NAT@open{(} \renewcommand\NAT@close{)} + \ExecuteOptions{nobibstyle}} +\DeclareOption{square}{% + \renewcommand\NAT@open{[} \renewcommand\NAT@close{]} + \ExecuteOptions{nobibstyle}} +\DeclareOption{angle}{% + \renewcommand\NAT@open{$<$} \renewcommand\NAT@close{$>$} + \ExecuteOptions{nobibstyle}} +\DeclareOption{curly}{% + \renewcommand\NAT@open{\{} \renewcommand\NAT@close{\}} + \ExecuteOptions{nobibstyle}} +\DeclareOption{comma}{\renewcommand\NAT@sep{,} + \ExecuteOptions{nobibstyle}} +\DeclareOption{semicolon}{\renewcommand\NAT@sep{;} + \ExecuteOptions{nobibstyle}} +\DeclareOption{colon}{\ExecuteOptions{semicolon}} +\DeclareOption{nobibstyle}{\let\bibstyle=\@gobble} +\DeclareOption{bibstyle}{\let\bibstyle=\@citestyle} +\newif\ifNAT@openbib \NAT@openbibfalse +\DeclareOption{openbib}{\NAT@openbibtrue} +\DeclareOption{sectionbib}{\def\NAT@sectionbib{on}} +\def\NAT@sort{\z@} +\def\NAT@cmprs{\z@} +\DeclareOption{sort}{\def\NAT@sort{\@ne}} +\DeclareOption{compress}{\def\NAT@cmprs{\@ne}} +\DeclareOption{sort&compress}{\def\NAT@sort{\@ne}\def\NAT@cmprs{\@ne}} +\DeclareOption{mcite}{\let\NAT@merge\@ne} +\DeclareOption{merge}{\@ifnum{\NAT@merge<\tw@}{\let\NAT@merge\tw@}{}} +\DeclareOption{elide}{\@ifnum{\NAT@merge<\thr@@}{\let\NAT@merge\thr@@}{}} +\@ifpackageloaded{cite}{\PackageWarningNoLine{natbib} + {The `cite' package should not be used\MessageBreak + with natbib. Use option `sort' instead}\ExecuteOptions{sort}}{} +\@ifpackageloaded{mcite}{\PackageWarningNoLine{natbib} + {The `mcite' package should not be used\MessageBreak + with natbib. Use option `merge' instead}\ExecuteOptions{merge}}{} +\@ifpackageloaded{citeref}{\PackageError{natbib} + {The `citeref' package must be loaded after natbib}% + {Move \protect\usepackage{citeref} to after \string\usepackage{natbib}}}{} +\newif\ifNAT@longnames\NAT@longnamesfalse +\DeclareOption{longnamesfirst}{\NAT@longnamestrue} +\DeclareOption{nonamebreak}{\def\NAT@nmfmt#1{\mbox{\NAT@up#1}}} +\def\NAT@nmfmt#1{{\NAT@up#1}} +\renewcommand\bibstyle[1]{\csname bibstyle@#1\endcsname} +\AtBeginDocument{\global\let\bibstyle=\@gobble} +\let\@citestyle\bibstyle +\newcommand\citestyle[1]{\@citestyle{#1}\let\bibstyle\@gobble} +\newcommand\bibpunct[7][, ]% + {\gdef\NAT@open{#2}\gdef\NAT@close{#3}\gdef + \NAT@sep{#4}\global\NAT@numbersfalse + \ifx #5n\global\NAT@numberstrue\global\NAT@superfalse + \else + \ifx #5s\global\NAT@numberstrue\global\NAT@supertrue + \fi\fi + \gdef\NAT@aysep{#6}\gdef\NAT@yrsep{#7}% + \gdef\NAT@cmt{#1}% + \NAT@@setcites + } +\newcommand\setcitestyle[1]{ + \@for\@tempa:=#1\do + {\def\@tempb{round}\ifx\@tempa\@tempb + \renewcommand\NAT@open{(}\renewcommand\NAT@close{)}\fi + \def\@tempb{square}\ifx\@tempa\@tempb + \renewcommand\NAT@open{[}\renewcommand\NAT@close{]}\fi + \def\@tempb{angle}\ifx\@tempa\@tempb + \renewcommand\NAT@open{$<$}\renewcommand\NAT@close{$>$}\fi + \def\@tempb{curly}\ifx\@tempa\@tempb + \renewcommand\NAT@open{\{}\renewcommand\NAT@close{\}}\fi + \def\@tempb{semicolon}\ifx\@tempa\@tempb + \renewcommand\NAT@sep{;}\fi + \def\@tempb{colon}\ifx\@tempa\@tempb + \renewcommand\NAT@sep{;}\fi + \def\@tempb{comma}\ifx\@tempa\@tempb + \renewcommand\NAT@sep{,}\fi + \def\@tempb{authoryear}\ifx\@tempa\@tempb + \NAT@numbersfalse\fi + \def\@tempb{numbers}\ifx\@tempa\@tempb + \NAT@numberstrue\NAT@superfalse\fi + \def\@tempb{super}\ifx\@tempa\@tempb + \NAT@numberstrue\NAT@supertrue\fi + \expandafter\NAT@find@eq\@tempa=\relax\@nil + \if\@tempc\relax\else + \expandafter\NAT@rem@eq\@tempc + \def\@tempb{open}\ifx\@tempa\@tempb + \xdef\NAT@open{\@tempc}\fi + \def\@tempb{close}\ifx\@tempa\@tempb + \xdef\NAT@close{\@tempc}\fi + \def\@tempb{aysep}\ifx\@tempa\@tempb + \xdef\NAT@aysep{\@tempc}\fi + \def\@tempb{yysep}\ifx\@tempa\@tempb + \xdef\NAT@yrsep{\@tempc}\fi + \def\@tempb{notesep}\ifx\@tempa\@tempb + \xdef\NAT@cmt{\@tempc}\fi + \def\@tempb{citesep}\ifx\@tempa\@tempb + \xdef\NAT@sep{\@tempc}\fi + \fi + }% + \NAT@@setcites +} + \def\NAT@find@eq#1=#2\@nil{\def\@tempa{#1}\def\@tempc{#2}} + \def\NAT@rem@eq#1={\def\@tempc{#1}} + \def\NAT@@setcites{\global\let\bibstyle\@gobble} +\AtBeginDocument{\let\NAT@@setcites\NAT@set@cites} +\newcommand\NAT@open{(} \newcommand\NAT@close{)} +\newcommand\NAT@sep{;} +\ProcessOptions +\newcommand\NAT@aysep{,} \newcommand\NAT@yrsep{,} +\newcommand\NAT@cmt{, } +\newcommand\NAT@cite% + [3]{\ifNAT@swa\NAT@@open\if*#2*\else#2\NAT@spacechar\fi + #1\if*#3*\else\NAT@cmt#3\fi\NAT@@close\else#1\fi\endgroup} +\newcommand\NAT@citenum% + [3]{\ifNAT@swa\NAT@@open\if*#2*\else#2\NAT@spacechar\fi + #1\if*#3*\else\NAT@cmt#3\fi\NAT@@close\else#1\fi\endgroup} +\newcommand\NAT@citesuper[3]{\ifNAT@swa +\if*#2*\else#2\NAT@spacechar\fi +\unskip\kern\p@\textsuperscript{\NAT@@open#1\NAT@@close}% + \if*#3*\else\NAT@spacechar#3\fi\else #1\fi\endgroup} +\providecommand\textsuperscript[1]{\mbox{$^{\mbox{\scriptsize#1}}$}} +\begingroup \catcode`\_=8 +\gdef\NAT@ifcat@num#1{% + \ifcat_\ifnum\z@<0#1_\else A\fi + \expandafter\@firstoftwo + \else + \expandafter\@secondoftwo + \fi +}% +\endgroup +\providecommand\@firstofone[1]{#1} +\newcommand\NAT@citexnum{} +\def\NAT@citexnum[#1][#2]#3{% + \NAT@reset@parser + \NAT@sort@cites{#3}% + \NAT@reset@citea + \@cite{\def\NAT@num{-1}\let\NAT@last@yr\relax\let\NAT@nm\@empty + \@for\@citeb:=\NAT@cite@list\do + {\@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \@ifundefined{b@\@citeb\@extra@b@citeb}{% + {\reset@font\bfseries?} + \NAT@citeundefined\PackageWarning{natbib}% + {Citation `\@citeb' on page \thepage \space undefined}}% + {\let\NAT@last@num\NAT@num\let\NAT@last@nm\NAT@nm + \NAT@parse{\@citeb}% + \ifNAT@longnames\@ifundefined{bv@\@citeb\@extra@b@citeb}{% + \let\NAT@name=\NAT@all@names + \global\@namedef{bv@\@citeb\@extra@b@citeb}{}}{}% + \fi + \ifNAT@full\let\NAT@nm\NAT@all@names\else + \let\NAT@nm\NAT@name\fi + \ifNAT@swa + \@ifnum{\NAT@ctype>\@ne}{% + \@citea + \NAT@hyper@{\@ifnum{\NAT@ctype=\tw@}{\NAT@test{\NAT@ctype}}{\NAT@alias}}% + }{% + \@ifnum{\NAT@cmprs>\z@}{% + \NAT@ifcat@num\NAT@num + {\let\NAT@nm=\NAT@num}% + {\def\NAT@nm{-2}}% + \NAT@ifcat@num\NAT@last@num + {\@tempcnta=\NAT@last@num\relax}% + {\@tempcnta\m@ne}% + \@ifnum{\NAT@nm=\@tempcnta}{% + \@ifnum{\NAT@merge>\@ne}{}{\NAT@last@yr@mbox}% + }{% + \advance\@tempcnta by\@ne + \@ifnum{\NAT@nm=\@tempcnta}{% + \ifx\NAT@last@yr\relax + \def@NAT@last@yr{\@citea}% + \else + \def@NAT@last@yr{--\NAT@penalty}% + \fi + }{% + \NAT@last@yr@mbox + }% + }% + }{% + \@tempswatrue + \@ifnum{\NAT@merge>\@ne}{\@ifnum{\NAT@last@num=\NAT@num\relax}{\@tempswafalse}{}}{}% + \if@tempswa\NAT@citea@mbox\fi + }% + }% + \NAT@def@citea + \else + \ifcase\NAT@ctype + \ifx\NAT@last@nm\NAT@nm \NAT@yrsep\NAT@penalty\NAT@space\else + \@citea \NAT@test{\@ne}\NAT@spacechar\NAT@mbox{\NAT@super@kern\NAT@@open}% + \fi + \if*#1*\else#1\NAT@spacechar\fi + \NAT@mbox{\NAT@hyper@{{\citenumfont{\NAT@num}}}}% + \NAT@def@citea@box + \or + \NAT@hyper@citea@space{\NAT@test{\NAT@ctype}}% + \or + \NAT@hyper@citea@space{\NAT@test{\NAT@ctype}}% + \or + \NAT@hyper@citea@space\NAT@alias + \fi + \fi + }% + }% + \@ifnum{\NAT@cmprs>\z@}{\NAT@last@yr}{}% + \ifNAT@swa\else + \@ifnum{\NAT@ctype=\z@}{% + \if*#2*\else\NAT@cmt#2\fi + }{}% + \NAT@mbox{\NAT@@close}% + \fi + }{#1}{#2}% +}% +\def\NAT@citea@mbox{% + \@citea\mbox{\NAT@hyper@{{\citenumfont{\NAT@num}}}}% +}% +\def\NAT@hyper@#1{% + \hyper@natlinkstart{\@citeb\@extra@b@citeb}#1\hyper@natlinkend +}% +\def\NAT@hyper@citea#1{% + \@citea + \NAT@hyper@{#1}% + \NAT@def@citea +}% +\def\NAT@hyper@citea@space#1{% + \@citea + \NAT@hyper@{#1}% + \NAT@def@citea@space +}% +\def\def@NAT@last@yr#1{% + \protected@edef\NAT@last@yr{% + #1% + \noexpand\mbox{% + \noexpand\hyper@natlinkstart{\@citeb\@extra@b@citeb}% + {\noexpand\citenumfont{\NAT@num}}% + \noexpand\hyper@natlinkend + }% + }% +}% +\def\NAT@last@yr@mbox{% + \NAT@last@yr\let\NAT@last@yr\relax + \NAT@citea@mbox +}% +\newcommand\NAT@test[1]{% + \@ifnum{#1=\@ne}{% + \ifx\NAT@nm\NAT@noname + \begingroup\reset@font\bfseries(author?)\endgroup + \PackageWarning{natbib}{% + Author undefined for citation`\@citeb' \MessageBreak on page \thepage% + }% + \else \NAT@nm + \fi + }{% + \if\relax\NAT@date\relax + \begingroup\reset@font\bfseries(year?)\endgroup + \PackageWarning{natbib}{% + Year undefined for citation`\@citeb' \MessageBreak on page \thepage% + }% + \else \NAT@date + \fi + }% +}% +\let\citenumfont=\@empty +\newcommand\NAT@citex{} +\def\NAT@citex% + [#1][#2]#3{% + \NAT@reset@parser + \NAT@sort@cites{#3}% + \NAT@reset@citea + \@cite{\let\NAT@nm\@empty\let\NAT@year\@empty + \@for\@citeb:=\NAT@cite@list\do + {\@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \@ifundefined{b@\@citeb\@extra@b@citeb}{\@citea% + {\reset@font\bfseries ?}\NAT@citeundefined + \PackageWarning{natbib}% + {Citation `\@citeb' on page \thepage \space undefined}\def\NAT@date{}}% + {\let\NAT@last@nm=\NAT@nm\let\NAT@last@yr=\NAT@year + \NAT@parse{\@citeb}% + \ifNAT@longnames\@ifundefined{bv@\@citeb\@extra@b@citeb}{% + \let\NAT@name=\NAT@all@names + \global\@namedef{bv@\@citeb\@extra@b@citeb}{}}{}% + \fi + \ifNAT@full\let\NAT@nm\NAT@all@names\else + \let\NAT@nm\NAT@name\fi + \ifNAT@swa\ifcase\NAT@ctype + \if\relax\NAT@date\relax + \@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}\NAT@date}% + \else + \ifx\NAT@last@nm\NAT@nm\NAT@yrsep + \ifx\NAT@last@yr\NAT@year + \def\NAT@temp{{?}}% + \ifx\NAT@temp\NAT@exlab\PackageWarningNoLine{natbib}% + {Multiple citation on page \thepage: same authors and + year\MessageBreak without distinguishing extra + letter,\MessageBreak appears as question mark}\fi + \NAT@hyper@{\NAT@exlab}% + \else\unskip\NAT@spacechar + \NAT@hyper@{\NAT@date}% + \fi + \else + \@citea\NAT@hyper@{% + \NAT@nmfmt{\NAT@nm}% + \hyper@natlinkbreak{% + \NAT@aysep\NAT@spacechar}{\@citeb\@extra@b@citeb + }% + \NAT@date + }% + \fi + \fi + \or\@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}}% + \or\@citea\NAT@hyper@{\NAT@date}% + \or\@citea\NAT@hyper@{\NAT@alias}% + \fi \NAT@def@citea + \else + \ifcase\NAT@ctype + \if\relax\NAT@date\relax + \@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}}% + \else + \ifx\NAT@last@nm\NAT@nm\NAT@yrsep + \ifx\NAT@last@yr\NAT@year + \def\NAT@temp{{?}}% + \ifx\NAT@temp\NAT@exlab\PackageWarningNoLine{natbib}% + {Multiple citation on page \thepage: same authors and + year\MessageBreak without distinguishing extra + letter,\MessageBreak appears as question mark}\fi + \NAT@hyper@{\NAT@exlab}% + \else + \unskip\NAT@spacechar + \NAT@hyper@{\NAT@date}% + \fi + \else + \@citea\NAT@hyper@{% + \NAT@nmfmt{\NAT@nm}% + \hyper@natlinkbreak{\NAT@spacechar\NAT@@open\if*#1*\else#1\NAT@spacechar\fi}% + {\@citeb\@extra@b@citeb}% + \NAT@date + }% + \fi + \fi + \or\@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}}% + \or\@citea\NAT@hyper@{\NAT@date}% + \or\@citea\NAT@hyper@{\NAT@alias}% + \fi + \if\relax\NAT@date\relax + \NAT@def@citea + \else + \NAT@def@citea@close + \fi + \fi + }}\ifNAT@swa\else\if*#2*\else\NAT@cmt#2\fi + \if\relax\NAT@date\relax\else\NAT@@close\fi\fi}{#1}{#2}} +\def\NAT@spacechar{\ }% +\def\NAT@separator{\NAT@sep\NAT@penalty}% +\def\NAT@reset@citea{\c@NAT@ctr\@ne\let\@citea\@empty}% +\def\NAT@def@citea{\def\@citea{\NAT@separator\NAT@space}}% +\def\NAT@def@citea@space{\def\@citea{\NAT@separator\NAT@spacechar}}% +\def\NAT@def@citea@close{\def\@citea{\NAT@@close\NAT@separator\NAT@space}}% +\def\NAT@def@citea@box{\def\@citea{\NAT@mbox{\NAT@@close}\NAT@separator\NAT@spacechar}}% +\newif\ifNAT@par \NAT@partrue +\newcommand\NAT@@open{\ifNAT@par\NAT@open\fi} +\newcommand\NAT@@close{\ifNAT@par\NAT@close\fi} +\newcommand\NAT@alias{\@ifundefined{al@\@citeb\@extra@b@citeb}{% + {\reset@font\bfseries(alias?)}\PackageWarning{natbib} + {Alias undefined for citation `\@citeb' + \MessageBreak on page \thepage}}{\@nameuse{al@\@citeb\@extra@b@citeb}}} +\let\NAT@up\relax +\newcommand\NAT@Up[1]{{\let\protect\@unexpandable@protect\let~\relax + \expandafter\NAT@deftemp#1}\expandafter\NAT@UP\NAT@temp} +\newcommand\NAT@deftemp[1]{\xdef\NAT@temp{#1}} +\newcommand\NAT@UP[1]{\let\@tempa\NAT@UP\ifcat a#1\MakeUppercase{#1}% + \let\@tempa\relax\else#1\fi\@tempa} +\newcommand\shortcites[1]{% + \@bsphack\@for\@citeb:=#1\do + {\@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \global\@namedef{bv@\@citeb\@extra@b@citeb}{}}\@esphack} +\newcommand\NAT@biblabel[1]{\hfill} +\newcommand\NAT@biblabelnum[1]{\bibnumfmt{#1}} +\let\bibnumfmt\@empty +\providecommand\@biblabel[1]{[#1]} +\AtBeginDocument{\ifx\bibnumfmt\@empty\let\bibnumfmt\@biblabel\fi} +\newcommand\NAT@bibsetnum[1]{\settowidth\labelwidth{\@biblabel{#1}}% + \setlength{\leftmargin}{\labelwidth}\addtolength{\leftmargin}{\labelsep}% + \setlength{\itemsep}{\bibsep}\setlength{\parsep}{\z@}% + \ifNAT@openbib + \addtolength{\leftmargin}{\bibindent}% + \setlength{\itemindent}{-\bibindent}% + \setlength{\listparindent}{\itemindent}% + \setlength{\parsep}{0pt}% + \fi +} +\newlength{\bibhang} +\setlength{\bibhang}{1em} +\newlength{\bibsep} + {\@listi \global\bibsep\itemsep \global\advance\bibsep by\parsep} + +\newcommand\NAT@bibsetup% + [1]{\setlength{\leftmargin}{\bibhang}\setlength{\itemindent}{-\leftmargin}% + \setlength{\itemsep}{\bibsep}\setlength{\parsep}{\z@}} +\newcommand\NAT@set@cites{% + \ifNAT@numbers + \ifNAT@super \let\@cite\NAT@citesuper + \def\NAT@mbox##1{\unskip\nobreak\textsuperscript{##1}}% + \let\citeyearpar=\citeyear + \let\NAT@space\relax + \def\NAT@super@kern{\kern\p@}% + \else + \let\NAT@mbox=\mbox + \let\@cite\NAT@citenum + \let\NAT@space\NAT@spacechar + \let\NAT@super@kern\relax + \fi + \let\@citex\NAT@citexnum + \let\@biblabel\NAT@biblabelnum + \let\@bibsetup\NAT@bibsetnum + \renewcommand\NAT@idxtxt{\NAT@name\NAT@spacechar\NAT@open\NAT@num\NAT@close}% + \def\natexlab##1{}% + \def\NAT@penalty{\penalty\@m}% + \else + \let\@cite\NAT@cite + \let\@citex\NAT@citex + \let\@biblabel\NAT@biblabel + \let\@bibsetup\NAT@bibsetup + \let\NAT@space\NAT@spacechar + \let\NAT@penalty\@empty + \renewcommand\NAT@idxtxt{\NAT@name\NAT@spacechar\NAT@open\NAT@date\NAT@close}% + \def\natexlab##1{##1}% + \fi} +\AtBeginDocument{\NAT@set@cites} +\AtBeginDocument{\ifx\SK@def\@undefined\else +\ifx\SK@cite\@empty\else + \SK@def\@citex[#1][#2]#3{\SK@\SK@@ref{#3}\SK@@citex[#1][#2]{#3}}\fi +\ifx\SK@citeauthor\@undefined\def\HAR@checkdef{}\else + \let\citeauthor\SK@citeauthor + \let\citefullauthor\SK@citefullauthor + \let\citeyear\SK@citeyear\fi +\fi} +\newif\ifNAT@full\NAT@fullfalse +\newif\ifNAT@swa +\DeclareRobustCommand\citet + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@partrue + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\newcommand\NAT@citetp{\@ifnextchar[{\NAT@@citetp}{\NAT@@citetp[]}} +\newcommand\NAT@@citetp{} +\def\NAT@@citetp[#1]{\@ifnextchar[{\@citex[#1]}{\@citex[][#1]}} +\DeclareRobustCommand\citep + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@partrue + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\cite + {\begingroup\let\NAT@ctype\z@\NAT@partrue\NAT@swatrue + \@ifstar{\NAT@fulltrue\NAT@cites}{\NAT@fullfalse\NAT@cites}} +\newcommand\NAT@cites{\@ifnextchar [{\NAT@@citetp}{% + \ifNAT@numbers\else + \NAT@swafalse + \fi + \NAT@@citetp[]}} +\DeclareRobustCommand\citealt + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@parfalse + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\citealp + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@parfalse + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\citenum + {\begingroup + \NAT@swatrue\let\NAT@ctype\z@\NAT@parfalse\let\textsuperscript\NAT@spacechar + \NAT@citexnum[][]} +\DeclareRobustCommand\citeauthor + {\begingroup\NAT@swafalse\let\NAT@ctype\@ne\NAT@parfalse + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citet + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@partrue + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citep + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@partrue + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citealt + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@parfalse + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citealp + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@parfalse + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citeauthor + {\begingroup\NAT@swafalse\let\NAT@ctype\@ne\NAT@parfalse + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\citeyear + {\begingroup\NAT@swafalse\let\NAT@ctype\tw@\NAT@parfalse\NAT@citetp} +\DeclareRobustCommand\citeyearpar + {\begingroup\NAT@swatrue\let\NAT@ctype\tw@\NAT@partrue\NAT@citetp} +\newcommand\citetext[1]{\NAT@open#1\NAT@close} +\DeclareRobustCommand\citefullauthor + {\citeauthor*} +\newcommand\defcitealias[2]{% + \@ifundefined{al@#1\@extra@b@citeb}{} + {\PackageWarning{natbib}{Overwriting existing alias for citation #1}} + \@namedef{al@#1\@extra@b@citeb}{#2}} +\DeclareRobustCommand\citetalias{\begingroup + \NAT@swafalse\let\NAT@ctype\thr@@\NAT@parfalse\NAT@citetp} +\DeclareRobustCommand\citepalias{\begingroup + \NAT@swatrue\let\NAT@ctype\thr@@\NAT@partrue\NAT@citetp} +\renewcommand\nocite[1]{\@bsphack + \@for\@citeb:=#1\do{% + \@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \if@filesw\immediate\write\@auxout{\string\citation{\@citeb}}\fi + \if*\@citeb\else + \@ifundefined{b@\@citeb\@extra@b@citeb}{% + \NAT@citeundefined \PackageWarning{natbib}% + {Citation `\@citeb' undefined}}{}\fi}% + \@esphack} +\newcommand\NAT@parse[1]{% + \begingroup + \let\protect=\@unexpandable@protect + \let~\relax + \let\active@prefix=\@gobble + \edef\NAT@temp{\csname b@#1\@extra@b@citeb\endcsname}% + \aftergroup\NAT@split + \expandafter + \endgroup + \NAT@temp{}{}{}{}{}@@% + \expandafter\NAT@parse@date\NAT@date??????@@% + \ifciteindex\NAT@index\fi +}% +\def\NAT@split#1#2#3#4#5@@{% + \gdef\NAT@num{#1}\gdef\NAT@name{#3}\gdef\NAT@date{#2}% + \gdef\NAT@all@names{#4}% + \ifx\NAT@num\@empty\gdef\NAT@num{0}\fi + \ifx\NAT@noname\NAT@all@names \gdef\NAT@all@names{#3}\fi +}% +\def\NAT@reset@parser{% + \global\let\NAT@num\@empty + \global\let\NAT@name\@empty + \global\let\NAT@date\@empty + \global\let\NAT@all@names\@empty +}% +\newcommand\NAT@parse@date{} +\def\NAT@parse@date#1#2#3#4#5#6@@{% + \ifnum\the\catcode`#1=11\def\NAT@year{}\def\NAT@exlab{#1}\else + \ifnum\the\catcode`#2=11\def\NAT@year{#1}\def\NAT@exlab{#2}\else + \ifnum\the\catcode`#3=11\def\NAT@year{#1#2}\def\NAT@exlab{#3}\else + \ifnum\the\catcode`#4=11\def\NAT@year{#1#2#3}\def\NAT@exlab{#4}\else + \def\NAT@year{#1#2#3#4}\def\NAT@exlab{{#5}}\fi\fi\fi\fi} +\newcommand\NAT@index{} +\let\NAT@makeindex=\makeindex +\renewcommand\makeindex{\NAT@makeindex + \renewcommand\NAT@index{\@bsphack\begingroup + \def~{\string~}\@wrindex{\NAT@idxtxt}}} +\newcommand\NAT@idxtxt{\NAT@name\NAT@spacechar\NAT@open\NAT@date\NAT@close} +\@ifxundefined\@indexfile{}{\let\NAT@makeindex\relax\makeindex} +\newif\ifciteindex \citeindexfalse +\newcommand\citeindextype{default} +\newcommand\NAT@index@alt{{\let\protect=\noexpand\let~\relax + \xdef\NAT@temp{\NAT@idxtxt}}\expandafter\NAT@exp\NAT@temp\@nil} +\newcommand\NAT@exp{} +\def\NAT@exp#1\@nil{\index[\citeindextype]{#1}} + +\AtBeginDocument{% +\@ifpackageloaded{index}{\let\NAT@index=\NAT@index@alt}{}} +\newcommand\NAT@ifcmd{\futurelet\NAT@temp\NAT@ifxcmd} +\newcommand\NAT@ifxcmd{\ifx\NAT@temp\relax\else\expandafter\NAT@bare\fi} +\def\NAT@bare#1(#2)#3(@)#4\@nil#5{% + \if @#2 + \expandafter\NAT@apalk#1, , \@nil{#5}% + \else + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{#3}{#5}% +\fi +} +\newcommand\NAT@wrout[5]{% +\if@filesw + {\let\protect\noexpand\let~\relax + \immediate + \write\@auxout{\string\bibcite{#5}{{#1}{#2}{{#3}}{{#4}}}}}\fi +\ignorespaces} +\def\NAT@noname{{}} +\renewcommand\bibitem{\@ifnextchar[{\@lbibitem}{\@lbibitem[]}}% +\let\NAT@bibitem@first@sw\@secondoftwo +\def\@lbibitem[#1]#2{% + \if\relax\@extra@b@citeb\relax\else + \@ifundefined{br@#2\@extra@b@citeb}{}{% + \@namedef{br@#2}{\@nameuse{br@#2\@extra@b@citeb}}% + }% + \fi + \@ifundefined{b@#2\@extra@b@citeb}{% + \def\NAT@num{}% + }{% + \NAT@parse{#2}% + }% + \def\NAT@tmp{#1}% + \expandafter\let\expandafter\bibitemOpen\csname NAT@b@open@#2\endcsname + \expandafter\let\expandafter\bibitemShut\csname NAT@b@shut@#2\endcsname + \@ifnum{\NAT@merge>\@ne}{% + \NAT@bibitem@first@sw{% + \@firstoftwo + }{% + \@ifundefined{NAT@b*@#2}{% + \@firstoftwo + }{% + \expandafter\def\expandafter\NAT@num\expandafter{\the\c@NAT@ctr}% + \@secondoftwo + }% + }% + }{% + \@firstoftwo + }% + {% + \global\advance\c@NAT@ctr\@ne + \@ifx{\NAT@tmp\@empty}{\@firstoftwo}{% + \@secondoftwo + }% + {% + \expandafter\def\expandafter\NAT@num\expandafter{\the\c@NAT@ctr}% + \global\NAT@stdbsttrue + }{}% + \bibitem@fin + \item[\hfil\NAT@anchor{#2}{\NAT@num}]% + \global\let\NAT@bibitem@first@sw\@secondoftwo + \NAT@bibitem@init + }% + {% + \NAT@anchor{#2}{}% + \NAT@bibitem@cont + \bibitem@fin + }% + \@ifx{\NAT@tmp\@empty}{% + \NAT@wrout{\the\c@NAT@ctr}{}{}{}{#2}% + }{% + \expandafter\NAT@ifcmd\NAT@tmp(@)(@)\@nil{#2}% + }% +}% +\def\bibitem@fin{% + \@ifxundefined\@bibstop{}{\csname bibitem@\@bibstop\endcsname}% +}% +\def\NAT@bibitem@init{% + \let\@bibstop\@undefined +}% +\def\NAT@bibitem@cont{% + \let\bibitem@Stop\bibitemStop + \let\bibitem@NoStop\bibitemContinue +}% +\def\BibitemOpen{% + \bibitemOpen +}% +\def\BibitemShut#1{% + \bibitemShut + \def\@bibstop{#1}% + \let\bibitem@Stop\bibitemStop + \let\bibitem@NoStop\bibitemNoStop +}% +\def\bibitemStop{}% +\def\bibitemNoStop{.\spacefactor\@mmm\space}% +\def\bibitemContinue{\spacefactor\@mmm\space}% +\mathchardef\@mmm=3000 % +\providecommand{\bibAnnote}[3]{% + \BibitemShut{#1}% + \def\@tempa{#3}\@ifx{\@tempa\@empty}{}{% + \begin{quotation}\noindent + \textsc{Key:}\ #2\\\textsc{Annotation:}\ \@tempa + \end{quotation}% + }% +}% +\providecommand{\bibAnnoteFile}[2]{% + \IfFileExists{#2}{% + \bibAnnote{#1}{#2}{\input{#2}}% + }{% + \bibAnnote{#1}{#2}{}% + }% +}% +\let\bibitemOpen\relax +\let\bibitemShut\relax +\def\bibfield{\@ifnum{\NAT@merge>\tw@}{\@bibfield}{\@secondoftwo}}% +\def\@bibfield#1#2{% + \begingroup + \let\Doi\@gobble + \let\bibinfo\relax + \let\restore@protect\@empty + \protected@edef\@tempa{#2}% + \aftergroup\def\aftergroup\@tempa + \expandafter\endgroup\expandafter{\@tempa}% + \expandafter\@ifx\expandafter{\csname @bib#1\endcsname\@tempa}{% + \expandafter\let\expandafter\@tempa\csname @bib@X#1\endcsname + }{% + \expandafter\let\csname @bib#1\endcsname\@tempa + \expandafter\let\expandafter\@tempa\csname @bib@Y#1\endcsname + }% + \@ifx{\@tempa\relax}{\let\@tempa\@firstofone}{}% + \@tempa{#2}% +}% +\def\bibinfo#1{% + \expandafter\let\expandafter\@tempa\csname bibinfo@X@#1\endcsname + \@ifx{\@tempa\relax}{\@firstofone}{\@tempa}% +}% +\def\@bib@Xauthor#1{\let\@bib@Xjournal\@gobble}% +\def\@bib@Xjournal#1{\begingroup\let\bibinfo@X@journal\@bib@Z@journal#1\endgroup}% +\def\@bibibid@#1{\textit{ibid}.}% +\appdef\NAT@bibitem@init{% + \let\@bibauthor \@empty + \let\@bibjournal \@empty + \let\@bib@Z@journal\@bibibid@ +}% +\ifx\SK@lbibitem\@undefined\else + \let\SK@lbibitem\@lbibitem + \def\@lbibitem[#1]#2{% + \SK@lbibitem[#1]{#2}\SK@\SK@@label{#2}\ignorespaces}\fi +\newif\ifNAT@stdbst \NAT@stdbstfalse + +\AtEndDocument{% + \ifNAT@stdbst\if@filesw + \immediate\write\@auxout{% + \string\providecommand\string\NAT@force@numbers{}% + \string\NAT@force@numbers + }% + \fi\fi + } +\newcommand\NAT@force@numbers{% + \ifNAT@numbers\else + \PackageError{natbib}{Bibliography not compatible with author-year + citations.\MessageBreak + Press <return> to continue in numerical citation style} + {Check the bibliography entries for non-compliant syntax,\MessageBreak + or select author-year BibTeX style, e.g. plainnat}% + \global\NAT@numberstrue\fi} + +\providecommand\bibcite{} +\renewcommand\bibcite[2]{% + \@ifundefined{b@#1\@extra@binfo}{\relax}{% + \NAT@citemultiple + \PackageWarningNoLine{natbib}{Citation `#1' multiply defined}% + }% + \global\@namedef{b@#1\@extra@binfo}{#2}% +}% +\AtEndDocument{\NAT@swatrue\let\bibcite\NAT@testdef} +\newcommand\NAT@testdef[2]{% + \def\NAT@temp{#2}% + \expandafter \ifx \csname b@#1\@extra@binfo\endcsname\NAT@temp + \else + \ifNAT@swa \NAT@swafalse + \PackageWarningNoLine{natbib}{% + Citation(s) may have changed.\MessageBreak + Rerun to get citations correct% + }% + \fi + \fi +}% +\newcommand\NAT@apalk{} +\def\NAT@apalk#1, #2, #3\@nil#4{% + \if\relax#2\relax + \global\NAT@stdbsttrue + \NAT@wrout{#1}{}{}{}{#4}% + \else + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{}{#4}% + \fi +}% +\newcommand\citeauthoryear{} +\def\citeauthoryear#1#2#3(@)(@)\@nil#4{% + \if\relax#3\relax + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{}{#4}% + \else + \NAT@wrout{\the\c@NAT@ctr}{#3}{#2}{#1}{#4}% + \fi +}% +\newcommand\citestarts{\NAT@open}% +\newcommand\citeends{\NAT@close}% +\newcommand\betweenauthors{and}% +\newcommand\astroncite{} +\def\astroncite#1#2(@)(@)\@nil#3{% + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{}{#3}% +}% +\newcommand\citename{} +\def\citename#1#2(@)(@)\@nil#3{\expandafter\NAT@apalk#1#2, \@nil{#3}} +\newcommand\harvarditem[4][]{% + \if\relax#1\relax + \bibitem[#2(#3)]{#4}% + \else + \bibitem[#1(#3)#2]{#4}% + \fi +}% +\newcommand\harvardleft{\NAT@open} +\newcommand\harvardright{\NAT@close} +\newcommand\harvardyearleft{\NAT@open} +\newcommand\harvardyearright{\NAT@close} +\AtBeginDocument{\providecommand{\harvardand}{and}} +\newcommand\harvardurl[1]{\textbf{URL:} \textit{#1}} +\providecommand\bibsection{} +\@ifundefined{chapter}{% + \renewcommand\bibsection{% + \section*{\refname\@mkboth{\MakeUppercase{\refname}}{\MakeUppercase{\refname}}}% + }% +}{% + \@ifxundefined\NAT@sectionbib{% + \renewcommand\bibsection{% + \chapter*{\bibname\@mkboth{\MakeUppercase{\bibname}}{\MakeUppercase{\bibname}}}% + }% + }{% + \renewcommand\bibsection{% + \section*{\bibname\ifx\@mkboth\@gobbletwo\else\markright{\MakeUppercase{\bibname}}\fi}% + }% + }% +}% +\@ifclassloaded{amsart}{\renewcommand\bibsection{\section*{\refname}}}{}% +\@ifclassloaded{amsbook}{\renewcommand\bibsection{\chapter*{\bibname}}}{}% +\@ifxundefined\bib@heading{}{\let\bibsection\bib@heading}% +\newcounter{NAT@ctr} +\renewenvironment{thebibliography}[1]{% + \bibsection + \parindent\z@ + \bibpreamble + \bibfont + \list{\@biblabel{\the\c@NAT@ctr}}{\@bibsetup{#1}\global\c@NAT@ctr\z@}% + \ifNAT@openbib + \renewcommand\newblock{\par}% + \else + \renewcommand\newblock{\hskip .11em \@plus.33em \@minus.07em}% + \fi + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.\@m + \let\NAT@bibitem@first@sw\@firstoftwo + \let\citeN\cite \let\shortcite\cite + \let\citeasnoun\cite +}{% + \bibitem@fin + \bibpostamble + \def\@noitemerr{% + \PackageWarning{natbib}{Empty `thebibliography' environment}% + }% + \endlist + \bibcleanup +}% +\let\bibfont\@empty +\let\bibpreamble\@empty +\let\bibpostamble\@empty +\def\bibcleanup{\vskip-\lastskip}% +\providecommand\reset@font{\relax} +\providecommand\bibname{Bibliography} +\providecommand\refname{References} +\newcommand\NAT@citeundefined{\gdef \NAT@undefined {% + \PackageWarningNoLine{natbib}{There were undefined citations}}} +\let \NAT@undefined \relax +\newcommand\NAT@citemultiple{\gdef \NAT@multiple {% + \PackageWarningNoLine{natbib}{There were multiply defined citations}}} +\let \NAT@multiple \relax +\AtEndDocument{\NAT@undefined\NAT@multiple} +\providecommand\@mkboth[2]{} +\providecommand\MakeUppercase{\uppercase} +\providecommand{\@extra@b@citeb}{} +\gdef\@extra@binfo{} +\def\NAT@anchor#1#2{% + \hyper@natanchorstart{#1\@extra@b@citeb}% + \def\@tempa{#2}\@ifx{\@tempa\@empty}{}{\@biblabel{#2}}% + \hyper@natanchorend +}% +\providecommand\hyper@natanchorstart[1]{}% +\providecommand\hyper@natanchorend{}% +\providecommand\hyper@natlinkstart[1]{}% +\providecommand\hyper@natlinkend{}% +\providecommand\hyper@natlinkbreak[2]{#1}% +\AtBeginDocument{% + \@ifpackageloaded{babel}{% + \let\org@@citex\@citex}{}} +\providecommand\@safe@activestrue{}% +\providecommand\@safe@activesfalse{}% + +\newcommand\NAT@sort@cites[1]{% + \let\NAT@cite@list\@empty + \@for\@citeb:=#1\do{\expandafter\NAT@star@cite\@citeb\@@}% + \if@filesw + \expandafter\immediate\expandafter\write\expandafter\@auxout + \expandafter{\expandafter\string\expandafter\citation\expandafter{\NAT@cite@list}}% + \fi + \@ifnum{\NAT@sort>\z@}{% + \expandafter\NAT@sort@cites@\expandafter{\NAT@cite@list}% + }{}% +}% +\def\NAT@star@cite{% + \let\NAT@star@sw\@secondoftwo + \@ifnum{\NAT@merge>\z@}{% + \@ifnextchar*{% + \let\NAT@star@sw\@firstoftwo + \NAT@star@cite@star + }{% + \NAT@star@cite@nostar + }% + }{% + \NAT@star@cite@noextension + }% +}% +\def\NAT@star@cite@star*{% + \NAT@star@cite@nostar +}% +\def\NAT@star@cite@nostar{% + \let\nat@keyopt@open\@empty + \let\nat@keyopt@shut\@empty + \@ifnextchar[{\NAT@star@cite@pre}{\NAT@star@cite@pre[]}% +}% +\def\NAT@star@cite@pre[#1]{% + \def\nat@keyopt@open{#1}% + \@ifnextchar[{\NAT@star@cite@post}{\NAT@star@cite@post[]}% +}% +\def\NAT@star@cite@post[#1]#2\@@{% + \def\nat@keyopt@shut{#1}% + \NAT@star@sw{\expandafter\global\expandafter\let\csname NAT@b*@#2\endcsname\@empty}{}% + \NAT@cite@list@append{#2}% +}% +\def\NAT@star@cite@noextension#1\@@{% + \let\nat@keyopt@open\@empty + \let\nat@keyopt@shut\@empty + \NAT@cite@list@append{#1}% +}% +\def\NAT@cite@list@append#1{% + \edef\@citeb{\@firstofone#1\@empty}% + \if@filesw\@ifxundefined\@cprwrite{}{\expandafter\@cprwrite\@citeb=}\fi + \if\relax\nat@keyopt@open\relax\else + \global\expandafter\let\csname NAT@b@open@\@citeb\endcsname\nat@keyopt@open + \fi + \if\relax\nat@keyopt@shut\relax\else + \global\expandafter\let\csname NAT@b@shut@\@citeb\endcsname\nat@keyopt@shut + \fi + \toks@\expandafter{\NAT@cite@list}% + \ifx\NAT@cite@list\@empty + \@temptokena\expandafter{\@citeb}% + \else + \@temptokena\expandafter{\expandafter,\@citeb}% + \fi + \edef\NAT@cite@list{\the\toks@\the\@temptokena}% +}% +\newcommand\NAT@sort@cites@[1]{% + \count@\z@ + \@tempcntb\m@ne + \let\@celt\delimiter + \def\NAT@num@list{}% + \let\NAT@cite@list\@empty + \let\NAT@nonsort@list\@empty + \@for \@citeb:=#1\do{\NAT@make@cite@list}% + \ifx\NAT@nonsort@list\@empty\else + \protected@edef\NAT@cite@list{\NAT@cite@list\NAT@nonsort@list}% + \fi + \ifx\NAT@cite@list\@empty\else + \protected@edef\NAT@cite@list{\expandafter\NAT@xcom\NAT@cite@list @@}% + \fi +}% +\def\NAT@make@cite@list{% + \advance\count@\@ne + \@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \@ifundefined{b@\@citeb\@extra@b@citeb}% + {\def\NAT@num{A}}% + {\NAT@parse{\@citeb}}% + \NAT@ifcat@num\NAT@num + {\@tempcnta\NAT@num \relax + \@ifnum{\@tempcnta<\@tempcntb}{% + \let\NAT@@cite@list=\NAT@cite@list + \let\NAT@cite@list\@empty + \begingroup\let\@celt=\NAT@celt\NAT@num@list\endgroup + \protected@edef\NAT@num@list{% + \expandafter\NAT@num@celt \NAT@num@list \@gobble @% + }% + }{% + \protected@edef\NAT@num@list{\NAT@num@list \@celt{\NAT@num}}% + \protected@edef\NAT@cite@list{\NAT@cite@list\@citeb,}% + \@tempcntb\@tempcnta + }% + }% + {\protected@edef\NAT@nonsort@list{\NAT@nonsort@list\@citeb,}}% +}% +\def\NAT@celt#1{% + \@ifnum{#1>\@tempcnta}{% + \xdef\NAT@cite@list{\NAT@cite@list\@citeb,\NAT@@cite@list}% + \let\@celt\@gobble + }{% + \expandafter\def@NAT@cite@lists\NAT@@cite@list\@@ + }% +}% +\def\NAT@num@celt#1#2{% + \ifx#1\@celt + \@ifnum{#2>\@tempcnta}{% + \@celt{\number\@tempcnta}% + \@celt{#2}% + }{% + \@celt{#2}% + \expandafter\NAT@num@celt + }% + \fi +}% +\def\def@NAT@cite@lists#1,#2\@@{% + \xdef\NAT@cite@list{\NAT@cite@list#1,}% + \xdef\NAT@@cite@list{#2}% +}% +\def\NAT@nextc#1,#2@@{#1,} +\def\NAT@restc#1,#2{#2} +\def\NAT@xcom#1,@@{#1} +\InputIfFileExists{natbib.cfg} + {\typeout{Local config file natbib.cfg used}}{} +%% +%% <<<<< End of generated file <<<<<< +%% +%% End of file `natbib.sty'. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/fancyhdr.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/fancyhdr.sty new file mode 100644 index 0000000..77ed4e3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/fancyhdr.sty @@ -0,0 +1,485 @@ +% fancyhdr.sty version 3.2 +% Fancy headers and footers for LaTeX. +% Piet van Oostrum, +% Dept of Computer and Information Sciences, University of Utrecht, +% Padualaan 14, P.O. Box 80.089, 3508 TB Utrecht, The Netherlands +% Telephone: +31 30 2532180. Email: piet@cs.uu.nl +% ======================================================================== +% LICENCE: +% This file may be distributed under the terms of the LaTeX Project Public +% License, as described in lppl.txt in the base LaTeX distribution. +% Either version 1 or, at your option, any later version. +% ======================================================================== +% MODIFICATION HISTORY: +% Sep 16, 1994 +% version 1.4: Correction for use with \reversemargin +% Sep 29, 1994: +% version 1.5: Added the \iftopfloat, \ifbotfloat and \iffloatpage commands +% Oct 4, 1994: +% version 1.6: Reset single spacing in headers/footers for use with +% setspace.sty or doublespace.sty +% Oct 4, 1994: +% version 1.7: changed \let\@mkboth\markboth to +% \def\@mkboth{\protect\markboth} to make it more robust +% Dec 5, 1994: +% version 1.8: corrections for amsbook/amsart: define \@chapapp and (more +% importantly) use the \chapter/sectionmark definitions from ps@headings if +% they exist (which should be true for all standard classes). +% May 31, 1995: +% version 1.9: The proposed \renewcommand{\headrulewidth}{\iffloatpage... +% construction in the doc did not work properly with the fancyplain style. +% June 1, 1995: +% version 1.91: The definition of \@mkboth wasn't restored on subsequent +% \pagestyle{fancy}'s. +% June 1, 1995: +% version 1.92: The sequence \pagestyle{fancyplain} \pagestyle{plain} +% \pagestyle{fancy} would erroneously select the plain version. +% June 1, 1995: +% version 1.93: \fancypagestyle command added. +% Dec 11, 1995: +% version 1.94: suggested by Conrad Hughes <chughes@maths.tcd.ie> +% CJCH, Dec 11, 1995: added \footruleskip to allow control over footrule +% position (old hardcoded value of .3\normalbaselineskip is far too high +% when used with very small footer fonts). +% Jan 31, 1996: +% version 1.95: call \@normalsize in the reset code if that is defined, +% otherwise \normalsize. +% this is to solve a problem with ucthesis.cls, as this doesn't +% define \@currsize. Unfortunately for latex209 calling \normalsize doesn't +% work as this is optimized to do very little, so there \@normalsize should +% be called. Hopefully this code works for all versions of LaTeX known to +% mankind. +% April 25, 1996: +% version 1.96: initialize \headwidth to a magic (negative) value to catch +% most common cases that people change it before calling \pagestyle{fancy}. +% Note it can't be initialized when reading in this file, because +% \textwidth could be changed afterwards. This is quite probable. +% We also switch to \MakeUppercase rather than \uppercase and introduce a +% \nouppercase command for use in headers. and footers. +% May 3, 1996: +% version 1.97: Two changes: +% 1. Undo the change in version 1.8 (using the pagestyle{headings} defaults +% for the chapter and section marks. The current version of amsbook and +% amsart classes don't seem to need them anymore. Moreover the standard +% latex classes don't use \markboth if twoside isn't selected, and this is +% confusing as \leftmark doesn't work as expected. +% 2. include a call to \ps@empty in ps@@fancy. This is to solve a problem +% in the amsbook and amsart classes, that make global changes to \topskip, +% which are reset in \ps@empty. Hopefully this doesn't break other things. +% May 7, 1996: +% version 1.98: +% Added % after the line \def\nouppercase +% May 7, 1996: +% version 1.99: This is the alpha version of fancyhdr 2.0 +% Introduced the new commands \fancyhead, \fancyfoot, and \fancyhf. +% Changed \headrulewidth, \footrulewidth, \footruleskip to +% macros rather than length parameters, In this way they can be +% conditionalized and they don't consume length registers. There is no need +% to have them as length registers unless you want to do calculations with +% them, which is unlikely. Note that this may make some uses of them +% incompatible (i.e. if you have a file that uses \setlength or \xxxx=) +% May 10, 1996: +% version 1.99a: +% Added a few more % signs +% May 10, 1996: +% version 1.99b: +% Changed the syntax of \f@nfor to be resistent to catcode changes of := +% Removed the [1] from the defs of \lhead etc. because the parameter is +% consumed by the \@[xy]lhead etc. macros. +% June 24, 1997: +% version 1.99c: +% corrected \nouppercase to also include the protected form of \MakeUppercase +% \global added to manipulation of \headwidth. +% \iffootnote command added. +% Some comments added about \@fancyhead and \@fancyfoot. +% Aug 24, 1998 +% version 1.99d +% Changed the default \ps@empty to \ps@@empty in order to allow +% \fancypagestyle{empty} redefinition. +% Oct 11, 2000 +% version 2.0 +% Added LPPL license clause. +% +% A check for \headheight is added. An errormessage is given (once) if the +% header is too large. Empty headers don't generate the error even if +% \headheight is very small or even 0pt. +% Warning added for the use of 'E' option when twoside option is not used. +% In this case the 'E' fields will never be used. +% +% Mar 10, 2002 +% version 2.1beta +% New command: \fancyhfoffset[place]{length} +% defines offsets to be applied to the header/footer to let it stick into +% the margins (if length > 0). +% place is like in fancyhead, except that only E,O,L,R can be used. +% This replaces the old calculation based on \headwidth and the marginpar +% area. +% \headwidth will be dynamically calculated in the headers/footers when +% this is used. +% +% Mar 26, 2002 +% version 2.1beta2 +% \fancyhfoffset now also takes h,f as possible letters in the argument to +% allow the header and footer widths to be different. +% New commands \fancyheadoffset and \fancyfootoffset added comparable to +% \fancyhead and \fancyfoot. +% Errormessages and warnings have been made more informative. +% +% Dec 9, 2002 +% version 2.1 +% The defaults for \footrulewidth, \plainheadrulewidth and +% \plainfootrulewidth are changed from \z@skip to 0pt. In this way when +% someone inadvertantly uses \setlength to change any of these, the value +% of \z@skip will not be changed, rather an errormessage will be given. + +% March 3, 2004 +% Release of version 3.0 + +% Oct 7, 2004 +% version 3.1 +% Added '\endlinechar=13' to \fancy@reset to prevent problems with +% includegraphics in header when verbatiminput is active. + +% March 22, 2005 +% version 3.2 +% reset \everypar (the real one) in \fancy@reset because spanish.ldf does +% strange things with \everypar between << and >>. + +\def\ifancy@mpty#1{\def\temp@a{#1}\ifx\temp@a\@empty} + +\def\fancy@def#1#2{\ifancy@mpty{#2}\fancy@gbl\def#1{\leavevmode}\else + \fancy@gbl\def#1{#2\strut}\fi} + +\let\fancy@gbl\global + +\def\@fancyerrmsg#1{% + \ifx\PackageError\undefined + \errmessage{#1}\else + \PackageError{Fancyhdr}{#1}{}\fi} +\def\@fancywarning#1{% + \ifx\PackageWarning\undefined + \errmessage{#1}\else + \PackageWarning{Fancyhdr}{#1}{}\fi} + +% Usage: \@forc \var{charstring}{command to be executed for each char} +% This is similar to LaTeX's \@tfor, but expands the charstring. + +\def\@forc#1#2#3{\expandafter\f@rc\expandafter#1\expandafter{#2}{#3}} +\def\f@rc#1#2#3{\def\temp@ty{#2}\ifx\@empty\temp@ty\else + \f@@rc#1#2\f@@rc{#3}\fi} +\def\f@@rc#1#2#3\f@@rc#4{\def#1{#2}#4\f@rc#1{#3}{#4}} + +% Usage: \f@nfor\name:=list\do{body} +% Like LaTeX's \@for but an empty list is treated as a list with an empty +% element + +\newcommand{\f@nfor}[3]{\edef\@fortmp{#2}% + \expandafter\@forloop#2,\@nil,\@nil\@@#1{#3}} + +% Usage: \def@ult \cs{defaults}{argument} +% sets \cs to the characters from defaults appearing in argument +% or defaults if it would be empty. All characters are lowercased. + +\newcommand\def@ult[3]{% + \edef\temp@a{\lowercase{\edef\noexpand\temp@a{#3}}}\temp@a + \def#1{}% + \@forc\tmpf@ra{#2}% + {\expandafter\if@in\tmpf@ra\temp@a{\edef#1{#1\tmpf@ra}}{}}% + \ifx\@empty#1\def#1{#2}\fi} +% +% \if@in <char><set><truecase><falsecase> +% +\newcommand{\if@in}[4]{% + \edef\temp@a{#2}\def\temp@b##1#1##2\temp@b{\def\temp@b{##1}}% + \expandafter\temp@b#2#1\temp@b\ifx\temp@a\temp@b #4\else #3\fi} + +\newcommand{\fancyhead}{\@ifnextchar[{\f@ncyhf\fancyhead h}% + {\f@ncyhf\fancyhead h[]}} +\newcommand{\fancyfoot}{\@ifnextchar[{\f@ncyhf\fancyfoot f}% + {\f@ncyhf\fancyfoot f[]}} +\newcommand{\fancyhf}{\@ifnextchar[{\f@ncyhf\fancyhf{}}% + {\f@ncyhf\fancyhf{}[]}} + +% New commands for offsets added + +\newcommand{\fancyheadoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyheadoffset h}% + {\f@ncyhfoffs\fancyheadoffset h[]}} +\newcommand{\fancyfootoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyfootoffset f}% + {\f@ncyhfoffs\fancyfootoffset f[]}} +\newcommand{\fancyhfoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyhfoffset{}}% + {\f@ncyhfoffs\fancyhfoffset{}[]}} + +% The header and footer fields are stored in command sequences with +% names of the form: \f@ncy<x><y><z> with <x> for [eo], <y> from [lcr] +% and <z> from [hf]. + +\def\f@ncyhf#1#2[#3]#4{% + \def\temp@c{}% + \@forc\tmpf@ra{#3}% + {\expandafter\if@in\tmpf@ra{eolcrhf,EOLCRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else + \@fancyerrmsg{Illegal char `\temp@c' in \string#1 argument: + [#3]}% + \fi + \f@nfor\temp@c{#3}% + {\def@ult\f@@@eo{eo}\temp@c + \if@twoside\else + \if\f@@@eo e\@fancywarning + {\string#1's `E' option without twoside option is useless}\fi\fi + \def@ult\f@@@lcr{lcr}\temp@c + \def@ult\f@@@hf{hf}{#2\temp@c}% + \@forc\f@@eo\f@@@eo + {\@forc\f@@lcr\f@@@lcr + {\@forc\f@@hf\f@@@hf + {\expandafter\fancy@def\csname + f@ncy\f@@eo\f@@lcr\f@@hf\endcsname + {#4}}}}}} + +\def\f@ncyhfoffs#1#2[#3]#4{% + \def\temp@c{}% + \@forc\tmpf@ra{#3}% + {\expandafter\if@in\tmpf@ra{eolrhf,EOLRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else + \@fancyerrmsg{Illegal char `\temp@c' in \string#1 argument: + [#3]}% + \fi + \f@nfor\temp@c{#3}% + {\def@ult\f@@@eo{eo}\temp@c + \if@twoside\else + \if\f@@@eo e\@fancywarning + {\string#1's `E' option without twoside option is useless}\fi\fi + \def@ult\f@@@lcr{lr}\temp@c + \def@ult\f@@@hf{hf}{#2\temp@c}% + \@forc\f@@eo\f@@@eo + {\@forc\f@@lcr\f@@@lcr + {\@forc\f@@hf\f@@@hf + {\expandafter\setlength\csname + f@ncyO@\f@@eo\f@@lcr\f@@hf\endcsname + {#4}}}}}% + \fancy@setoffs} + +% Fancyheadings version 1 commands. These are more or less deprecated, +% but they continue to work. + +\newcommand{\lhead}{\@ifnextchar[{\@xlhead}{\@ylhead}} +\def\@xlhead[#1]#2{\fancy@def\f@ncyelh{#1}\fancy@def\f@ncyolh{#2}} +\def\@ylhead#1{\fancy@def\f@ncyelh{#1}\fancy@def\f@ncyolh{#1}} + +\newcommand{\chead}{\@ifnextchar[{\@xchead}{\@ychead}} +\def\@xchead[#1]#2{\fancy@def\f@ncyech{#1}\fancy@def\f@ncyoch{#2}} +\def\@ychead#1{\fancy@def\f@ncyech{#1}\fancy@def\f@ncyoch{#1}} + +\newcommand{\rhead}{\@ifnextchar[{\@xrhead}{\@yrhead}} +\def\@xrhead[#1]#2{\fancy@def\f@ncyerh{#1}\fancy@def\f@ncyorh{#2}} +\def\@yrhead#1{\fancy@def\f@ncyerh{#1}\fancy@def\f@ncyorh{#1}} + +\newcommand{\lfoot}{\@ifnextchar[{\@xlfoot}{\@ylfoot}} +\def\@xlfoot[#1]#2{\fancy@def\f@ncyelf{#1}\fancy@def\f@ncyolf{#2}} +\def\@ylfoot#1{\fancy@def\f@ncyelf{#1}\fancy@def\f@ncyolf{#1}} + +\newcommand{\cfoot}{\@ifnextchar[{\@xcfoot}{\@ycfoot}} +\def\@xcfoot[#1]#2{\fancy@def\f@ncyecf{#1}\fancy@def\f@ncyocf{#2}} +\def\@ycfoot#1{\fancy@def\f@ncyecf{#1}\fancy@def\f@ncyocf{#1}} + +\newcommand{\rfoot}{\@ifnextchar[{\@xrfoot}{\@yrfoot}} +\def\@xrfoot[#1]#2{\fancy@def\f@ncyerf{#1}\fancy@def\f@ncyorf{#2}} +\def\@yrfoot#1{\fancy@def\f@ncyerf{#1}\fancy@def\f@ncyorf{#1}} + +\newlength{\fancy@headwidth} +\let\headwidth\fancy@headwidth +\newlength{\f@ncyO@elh} +\newlength{\f@ncyO@erh} +\newlength{\f@ncyO@olh} +\newlength{\f@ncyO@orh} +\newlength{\f@ncyO@elf} +\newlength{\f@ncyO@erf} +\newlength{\f@ncyO@olf} +\newlength{\f@ncyO@orf} +\newcommand{\headrulewidth}{0.4pt} +\newcommand{\footrulewidth}{0pt} +\newcommand{\footruleskip}{.3\normalbaselineskip} + +% Fancyplain stuff shouldn't be used anymore (rather +% \fancypagestyle{plain} should be used), but it must be present for +% compatibility reasons. + +\newcommand{\plainheadrulewidth}{0pt} +\newcommand{\plainfootrulewidth}{0pt} +\newif\if@fancyplain \@fancyplainfalse +\def\fancyplain#1#2{\if@fancyplain#1\else#2\fi} + +\headwidth=-123456789sp %magic constant + +% Command to reset various things in the headers: +% a.o. single spacing (taken from setspace.sty) +% and the catcode of ^^M (so that epsf files in the header work if a +% verbatim crosses a page boundary) +% It also defines a \nouppercase command that disables \uppercase and +% \Makeuppercase. It can only be used in the headers and footers. +\let\fnch@everypar\everypar% save real \everypar because of spanish.ldf +\def\fancy@reset{\fnch@everypar{}\restorecr\endlinechar=13 + \def\baselinestretch{1}% + \def\nouppercase##1{{\let\uppercase\relax\let\MakeUppercase\relax + \expandafter\let\csname MakeUppercase \endcsname\relax##1}}% + \ifx\undefined\@newbaseline% NFSS not present; 2.09 or 2e + \ifx\@normalsize\undefined \normalsize % for ucthesis.cls + \else \@normalsize \fi + \else% NFSS (2.09) present + \@newbaseline% + \fi} + +% Initialization of the head and foot text. + +% The default values still contain \fancyplain for compatibility. +\fancyhf{} % clear all +% lefthead empty on ``plain'' pages, \rightmark on even, \leftmark on odd pages +% evenhead empty on ``plain'' pages, \leftmark on even, \rightmark on odd pages +\if@twoside + \fancyhead[el,or]{\fancyplain{}{\sl\rightmark}} + \fancyhead[er,ol]{\fancyplain{}{\sl\leftmark}} +\else + \fancyhead[l]{\fancyplain{}{\sl\rightmark}} + \fancyhead[r]{\fancyplain{}{\sl\leftmark}} +\fi +\fancyfoot[c]{\rm\thepage} % page number + +% Use box 0 as a temp box and dimen 0 as temp dimen. +% This can be done, because this code will always +% be used inside another box, and therefore the changes are local. + +\def\@fancyvbox#1#2{\setbox0\vbox{#2}\ifdim\ht0>#1\@fancywarning + {\string#1 is too small (\the#1): ^^J Make it at least \the\ht0.^^J + We now make it that large for the rest of the document.^^J + This may cause the page layout to be inconsistent, however\@gobble}% + \dimen0=#1\global\setlength{#1}{\ht0}\ht0=\dimen0\fi + \box0} + +% Put together a header or footer given the left, center and +% right text, fillers at left and right and a rule. +% The \lap commands put the text into an hbox of zero size, +% so overlapping text does not generate an errormessage. +% These macros have 5 parameters: +% 1. LEFTSIDE BEARING % This determines at which side the header will stick +% out. When \fancyhfoffset is used this calculates \headwidth, otherwise +% it is \hss or \relax (after expansion). +% 2. \f@ncyolh, \f@ncyelh, \f@ncyolf or \f@ncyelf. This is the left component. +% 3. \f@ncyoch, \f@ncyech, \f@ncyocf or \f@ncyecf. This is the middle comp. +% 4. \f@ncyorh, \f@ncyerh, \f@ncyorf or \f@ncyerf. This is the right component. +% 5. RIGHTSIDE BEARING. This is always \relax or \hss (after expansion). + +\def\@fancyhead#1#2#3#4#5{#1\hbox to\headwidth{\fancy@reset + \@fancyvbox\headheight{\hbox + {\rlap{\parbox[b]{\headwidth}{\raggedright#2}}\hfill + \parbox[b]{\headwidth}{\centering#3}\hfill + \llap{\parbox[b]{\headwidth}{\raggedleft#4}}}\headrule}}#5} + +\def\@fancyfoot#1#2#3#4#5{#1\hbox to\headwidth{\fancy@reset + \@fancyvbox\footskip{\footrule + \hbox{\rlap{\parbox[t]{\headwidth}{\raggedright#2}}\hfill + \parbox[t]{\headwidth}{\centering#3}\hfill + \llap{\parbox[t]{\headwidth}{\raggedleft#4}}}}}#5} + +\def\headrule{{\if@fancyplain\let\headrulewidth\plainheadrulewidth\fi + \hrule\@height\headrulewidth\@width\headwidth \vskip-\headrulewidth}} + +\def\footrule{{\if@fancyplain\let\footrulewidth\plainfootrulewidth\fi + \vskip-\footruleskip\vskip-\footrulewidth + \hrule\@width\headwidth\@height\footrulewidth\vskip\footruleskip}} + +\def\ps@fancy{% +\@ifundefined{@chapapp}{\let\@chapapp\chaptername}{}%for amsbook +% +% Define \MakeUppercase for old LaTeXen. +% Note: we used \def rather than \let, so that \let\uppercase\relax (from +% the version 1 documentation) will still work. +% +\@ifundefined{MakeUppercase}{\def\MakeUppercase{\uppercase}}{}% +\@ifundefined{chapter}{\def\sectionmark##1{\markboth +{\MakeUppercase{\ifnum \c@secnumdepth>\z@ + \thesection\hskip 1em\relax \fi ##1}}{}}% +\def\subsectionmark##1{\markright {\ifnum \c@secnumdepth >\@ne + \thesubsection\hskip 1em\relax \fi ##1}}}% +{\def\chaptermark##1{\markboth {\MakeUppercase{\ifnum \c@secnumdepth>\m@ne + \@chapapp\ \thechapter. \ \fi ##1}}{}}% +\def\sectionmark##1{\markright{\MakeUppercase{\ifnum \c@secnumdepth >\z@ + \thesection. \ \fi ##1}}}}% +%\csname ps@headings\endcsname % use \ps@headings defaults if they exist +\ps@@fancy +\gdef\ps@fancy{\@fancyplainfalse\ps@@fancy}% +% Initialize \headwidth if the user didn't +% +\ifdim\headwidth<0sp +% +% This catches the case that \headwidth hasn't been initialized and the +% case that the user added something to \headwidth in the expectation that +% it was initialized to \textwidth. We compensate this now. This loses if +% the user intended to multiply it by a factor. But that case is more +% likely done by saying something like \headwidth=1.2\textwidth. +% The doc says you have to change \headwidth after the first call to +% \pagestyle{fancy}. This code is just to catch the most common cases were +% that requirement is violated. +% + \global\advance\headwidth123456789sp\global\advance\headwidth\textwidth +\fi} +\def\ps@fancyplain{\ps@fancy \let\ps@plain\ps@plain@fancy} +\def\ps@plain@fancy{\@fancyplaintrue\ps@@fancy} +\let\ps@@empty\ps@empty +\def\ps@@fancy{% +\ps@@empty % This is for amsbook/amsart, which do strange things with \topskip +\def\@mkboth{\protect\markboth}% +\def\@oddhead{\@fancyhead\fancy@Oolh\f@ncyolh\f@ncyoch\f@ncyorh\fancy@Oorh}% +\def\@oddfoot{\@fancyfoot\fancy@Oolf\f@ncyolf\f@ncyocf\f@ncyorf\fancy@Oorf}% +\def\@evenhead{\@fancyhead\fancy@Oelh\f@ncyelh\f@ncyech\f@ncyerh\fancy@Oerh}% +\def\@evenfoot{\@fancyfoot\fancy@Oelf\f@ncyelf\f@ncyecf\f@ncyerf\fancy@Oerf}% +} +% Default definitions for compatibility mode: +% These cause the header/footer to take the defined \headwidth as width +% And to shift in the direction of the marginpar area + +\def\fancy@Oolh{\if@reversemargin\hss\else\relax\fi} +\def\fancy@Oorh{\if@reversemargin\relax\else\hss\fi} +\let\fancy@Oelh\fancy@Oorh +\let\fancy@Oerh\fancy@Oolh + +\let\fancy@Oolf\fancy@Oolh +\let\fancy@Oorf\fancy@Oorh +\let\fancy@Oelf\fancy@Oelh +\let\fancy@Oerf\fancy@Oerh + +% New definitions for the use of \fancyhfoffset +% These calculate the \headwidth from \textwidth and the specified offsets. + +\def\fancy@offsolh{\headwidth=\textwidth\advance\headwidth\f@ncyO@olh + \advance\headwidth\f@ncyO@orh\hskip-\f@ncyO@olh} +\def\fancy@offselh{\headwidth=\textwidth\advance\headwidth\f@ncyO@elh + \advance\headwidth\f@ncyO@erh\hskip-\f@ncyO@elh} + +\def\fancy@offsolf{\headwidth=\textwidth\advance\headwidth\f@ncyO@olf + \advance\headwidth\f@ncyO@orf\hskip-\f@ncyO@olf} +\def\fancy@offself{\headwidth=\textwidth\advance\headwidth\f@ncyO@elf + \advance\headwidth\f@ncyO@erf\hskip-\f@ncyO@elf} + +\def\fancy@setoffs{% +% Just in case \let\headwidth\textwidth was used + \fancy@gbl\let\headwidth\fancy@headwidth + \fancy@gbl\let\fancy@Oolh\fancy@offsolh + \fancy@gbl\let\fancy@Oelh\fancy@offselh + \fancy@gbl\let\fancy@Oorh\hss + \fancy@gbl\let\fancy@Oerh\hss + \fancy@gbl\let\fancy@Oolf\fancy@offsolf + \fancy@gbl\let\fancy@Oelf\fancy@offself + \fancy@gbl\let\fancy@Oorf\hss + \fancy@gbl\let\fancy@Oerf\hss} + +\newif\iffootnote +\let\latex@makecol\@makecol +\def\@makecol{\ifvoid\footins\footnotetrue\else\footnotefalse\fi +\let\topfloat\@toplist\let\botfloat\@botlist\latex@makecol} +\def\iftopfloat#1#2{\ifx\topfloat\empty #2\else #1\fi} +\def\ifbotfloat#1#2{\ifx\botfloat\empty #2\else #1\fi} +\def\iffloatpage#1#2{\if@fcolmade #1\else #2\fi} + +\newcommand{\fancypagestyle}[2]{% + \@namedef{ps@#1}{\let\fancy@gbl\relax#2\relax\ps@fancy}} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.bib b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.bib new file mode 100644 index 0000000..dbc773b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.bib @@ -0,0 +1,24 @@ +@incollection{Bengio+chapter2007, +author = {Bengio, Yoshua and LeCun, Yann}, +booktitle = {Large Scale Kernel Machines}, +publisher = {MIT Press}, +title = {Scaling Learning Algorithms Towards {AI}}, +year = {2007} +} + +@article{Hinton06, +author = {Hinton, Geoffrey E. and Osindero, Simon and Teh, Yee Whye}, +journal = {Neural Computation}, +pages = {1527--1554}, +title = {A Fast Learning Algorithm for Deep Belief Nets}, +volume = {18}, +year = {2006} +} + +@book{goodfellow2016deep, +title={Deep learning}, +author={Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron and Bengio, Yoshua}, +volume={1}, +year={2016}, +publisher={MIT Press} +} \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.bst b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.bst new file mode 100644 index 0000000..a85a008 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.bst @@ -0,0 +1,1440 @@ +%% File: `iclr2024.bst' +%% A copy of iclm2010.bst, which is a modification of `plainnl.bst' for use with natbib package +%% +%% Copyright 2010 Hal Daum\'e III +%% Modified by J. Fürnkranz +%% - Changed labels from (X and Y, 2000) to (X & Y, 2000) +%% +%% Copyright 1993-2007 Patrick W Daly +%% Max-Planck-Institut f\"ur Sonnensystemforschung +%% Max-Planck-Str. 2 +%% D-37191 Katlenburg-Lindau +%% Germany +%% E-mail: daly@mps.mpg.de +%% +%% This program can be redistributed and/or modified under the terms +%% of the LaTeX Project Public License Distributed from CTAN +%% archives in directory macros/latex/base/lppl.txt; either +%% version 1 of the License, or any later version. +%% + % Version and source file information: + % \ProvidesFile{icml2010.mbs}[2007/11/26 1.93 (PWD)] + % + % BibTeX `plainnat' family + % version 0.99b for BibTeX versions 0.99a or later, + % for LaTeX versions 2.09 and 2e. + % + % For use with the `natbib.sty' package; emulates the corresponding + % member of the `plain' family, but with author-year citations. + % + % With version 6.0 of `natbib.sty', it may also be used for numerical + % citations, while retaining the commands \citeauthor, \citefullauthor, + % and \citeyear to print the corresponding information. + % + % For version 7.0 of `natbib.sty', the KEY field replaces missing + % authors/editors, and the date is left blank in \bibitem. + % + % Includes field EID for the sequence/citation number of electronic journals + % which is used instead of page numbers. + % + % Includes fields ISBN and ISSN. + % + % Includes field URL for Internet addresses. + % + % Includes field DOI for Digital Object Idenfifiers. + % + % Works best with the url.sty package of Donald Arseneau. + % + % Works with identical authors and year are further sorted by + % citation key, to preserve any natural sequence. + % +ENTRY + { address + author + booktitle + chapter + doi + eid + edition + editor + howpublished + institution + isbn + issn + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + url + volume + year + } + {} + { label extra.label sort.label short.list } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { " (eds.)" * } + { " (ed.)" * } + if$ + } + if$ +} + +FUNCTION {format.isbn} +{ isbn empty$ + { "" } + { new.block "ISBN " isbn * } + if$ +} + +FUNCTION {format.issn} +{ issn empty$ + { "" } + { new.block "ISSN " issn * } + if$ +} + +FUNCTION {format.url} +{ url empty$ + { "" } + { new.block "URL \url{" url * "}" * } + if$ +} + +FUNCTION {format.doi} +{ doi empty$ + { "" } + { new.block "\doi{" doi * "}" * } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + { title "t" change.case$ } + if$ +} + +FUNCTION {format.full.names} +{'s := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.full} +{ author empty$ + { editor empty$ + { "" } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.full} +{ author empty$ + { "" } + { author format.full.names } + if$ +} + +FUNCTION {editor.full} +{ editor empty$ + { "" } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.full + { type$ "proceedings" = + 'editor.full + 'author.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year duplicate$ empty$ + { "empty year in " cite$ * warning$ + pop$ "" } + 'skip$ + if$ + month empty$ + 'skip$ + { month + " " * swap$ * + } + if$ + extra.label * +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pp.\ " pages n.dashify tie.or.space.connect } + { "pp.\ " pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.eid} +{ eid empty$ + { "" } + { "art." eid tie.or.space.connect } + if$ +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":\penalty0 " * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.vol.num.eid} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + eid empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.eid } + { ":\penalty0 " * eid * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + key empty$ not and + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In \emph{" journal * "}" * } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "\emph{" * series * "}" * } + if$ + } + 'skip$ + if$ + } + 'skip$ + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In \emph{" booktitle * "}" * } + if$ + } + { "In " } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + eid empty$ + { format.vol.num.pages output } + { format.vol.num.eid output } + if$ + format.date "year" output.check + } + { format.article.crossref output.nonnull + eid empty$ + { format.pages output } + { format.eid output } + if$ + } + if$ + format.issn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date "year" output.check + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date "year" output.check + } + { address output.nonnull + format.date "year" output.check + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + new.block + format.btitle "title" output.check + organization address new.block.checkb + organization output + address output + format.edition output + format.date output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + format.issn output + format.url output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.btitle "title" output.check + new.block + "PhD thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + format.editors output + editor format.key output + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address output + format.date "year" output.check + new.sentence + organization output + publisher output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + format.url output + fin.entry +} + +FUNCTION {default.type} { misc } + + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + + + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " \& " * s #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + short.list key field.or.null = or + { pop$ "" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" * } + { numnames #2 > nameptr #2 = and + { "zz" * year field.or.null * " " * } + 'skip$ + if$ + t sortify * + } + if$ + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + + +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + " " + * + year field.or.null sortify + * + " " + * + cite$ + * + #1 entry.max$ substring$ + 'sort.label := + sort.label * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.label next.extra } + +INTEGERS { longest.label.width last.extra.num number.label } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := + #0 'number.label := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\providecommand{\natexlab}[1]{#1}" + write$ newline$ + "\providecommand{\url}[1]{\texttt{#1}}" + write$ newline$ + "\expandafter\ifx\csname urlstyle\endcsname\relax" + write$ newline$ + " \providecommand{\doi}[1]{doi: #1}\else" + write$ newline$ + " \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi" + write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.pdf b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.pdf new file mode 100644 index 0000000000000000000000000000000000000000..396adefa6cccc9885433597c8e82bc6fa4c3329b GIT binary patch literal 200508 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the page. If these parameters are +% changed, they will require corresponding changes in the +% maketitle section. +% +\usepackage{eso-pic} % used by \AddToShipoutPicture +\RequirePackage{fancyhdr} +\RequirePackage{natbib} + +% modification to natbib citations +\setcitestyle{authoryear,round,citesep={;},aysep={,},yysep={;}} + +\renewcommand{\topfraction}{0.95} % let figure take up nearly whole page +\renewcommand{\textfraction}{0.05} % let figure take up nearly whole page + +% Define iclrfinal, set to true if iclrfinalcopy is defined +\newif\ificlrfinal +\iclrfinalfalse +\def\iclrfinalcopy{\iclrfinaltrue} +\font\iclrtenhv = phvb at 8pt + +% Specify the dimensions of each page + +\setlength{\paperheight}{11in} +\setlength{\paperwidth}{8.5in} + + +\oddsidemargin .5in % Note \oddsidemargin = \evensidemargin +\evensidemargin .5in +\marginparwidth 0.07 true in +%\marginparwidth 0.75 true in +%\topmargin 0 true pt % Nominal distance from top of page to top of +%\topmargin 0.125in +\topmargin -0.625in +\addtolength{\headsep}{0.25in} +\textheight 9.0 true in % Height of text (including footnotes & figures) +\textwidth 5.5 true in % Width of text line. +\widowpenalty=10000 +\clubpenalty=10000 + +% \thispagestyle{empty} \pagestyle{empty} +\flushbottom \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par +\begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} % for perfect author + % name centering +% The footnote-mark was overlapping the footnote-text, +% added the following to fix this problem (MK) + \long\def\@makefntext##1{\parindent 1em\noindent + \hbox to1.8em{\hss $\m@th ^{\@thefnmark}$}##1} + \@maketitle \@thanks +\endgroup +\setcounter{footnote}{0} +\let\maketitle\relax \let\@maketitle\relax +\gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} + +% The toptitlebar has been raised to top-justify the first page + +\usepackage{fancyhdr} +\pagestyle{fancy} +\fancyhead{} + +% Title (includes both anonimized and non-anonimized versions) +\def\@maketitle{\vbox{\hsize\textwidth +%\linewidth\hsize \vskip 0.1in \toptitlebar \centering +{\LARGE\sc \@title\par} +%\bottomtitlebar % \vskip 0.1in % minus +\ificlrfinal + \lhead{Published as a conference paper at ICLR 2026} + \def\And{\end{tabular}\hfil\linebreak[0]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \def\AND{\end{tabular}\hfil\linebreak[4]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\@author\end{tabular}% +\else + \lhead{Under review as a conference paper at ICLR 2026} + \def\And{\end{tabular}\hfil\linebreak[0]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \def\AND{\end{tabular}\hfil\linebreak[4]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}Anonymous authors\\Paper under double-blind review\end{tabular}% +\fi +\vskip 0.3in minus 0.1in}} + +\renewenvironment{abstract}{\vskip.075in\centerline{\large\sc +Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex +minus0.2ex}{\large\sc\raggedright}} + +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus +-0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\sc\raggedright}} +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex +plus -0.5ex minus -.2ex}{0.5ex plus +.2ex}{\normalsize\sc\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus +0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\sc}} +\def\subsubsubsection{\vskip +5pt{\noindent\normalsize\rm\raggedright}} + + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 12pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 0pt +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt +\parskip .5pc + + +%\leftmargin2em +\leftmargin3pc +\leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em + +%\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +%\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} % got rid of @ (MK) +\def\normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} + +\def\toptitlebar{\hrule height4pt\vskip .25in\vskip-\parskip} + +\def\bottomtitlebar{\vskip .29in\vskip-\parskip\hrule height1pt\vskip +.09in} % +%Reduced second vskip to compensate for adding the strut in \@author + + + +%% % Vertical Ruler +%% % This code is, largely, from the CVPR 2010 conference style file +%% % ----- define vruler +\makeatletter +\newbox\iclrrulerbox +\newcount\iclrrulercount +\newdimen\iclrruleroffset +\newdimen\cv@lineheight +\newdimen\cv@boxheight +\newbox\cv@tmpbox +\newcount\cv@refno +\newcount\cv@tot +% NUMBER with left flushed zeros \fillzeros[<WIDTH>]<NUMBER> +\newcount\cv@tmpc@ \newcount\cv@tmpc +\def\fillzeros[#1]#2{\cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi +\cv@tmpc=1 % +\loop\ifnum\cv@tmpc@<10 \else \divide\cv@tmpc@ by 10 \advance\cv@tmpc by 1 \fi + \ifnum\cv@tmpc@=10\relax\cv@tmpc@=11\relax\fi \ifnum\cv@tmpc@>10 \repeat +\ifnum#2<0\advance\cv@tmpc1\relax-\fi +\loop\ifnum\cv@tmpc<#1\relax0\advance\cv@tmpc1\relax\fi \ifnum\cv@tmpc<#1 \repeat +\cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi \relax\the\cv@tmpc@}% +% \makevruler[<SCALE>][<INITIAL_COUNT>][<STEP>][<DIGITS>][<HEIGHT>] +\def\makevruler[#1][#2][#3][#4][#5]{\begingroup\offinterlineskip +\textheight=#5\vbadness=10000\vfuzz=120ex\overfullrule=0pt% +\global\setbox\iclrrulerbox=\vbox to \textheight{% +{\parskip=0pt\hfuzz=150em\cv@boxheight=\textheight +\cv@lineheight=#1\global\iclrrulercount=#2% +\cv@tot\cv@boxheight\divide\cv@tot\cv@lineheight\advance\cv@tot2% +\cv@refno1\vskip-\cv@lineheight\vskip1ex% +\loop\setbox\cv@tmpbox=\hbox to0cm{{\iclrtenhv\hfil\fillzeros[#4]\iclrrulercount}}% +\ht\cv@tmpbox\cv@lineheight\dp\cv@tmpbox0pt\box\cv@tmpbox\break +\advance\cv@refno1\global\advance\iclrrulercount#3\relax +\ifnum\cv@refno<\cv@tot\repeat}}\endgroup}% +\makeatother +% ----- end of vruler + +% \makevruler[<SCALE>][<INITIAL_COUNT>][<STEP>][<DIGITS>][<HEIGHT>] +\def\iclrruler#1{\makevruler[12pt][#1][1][3][0.993\textheight]\usebox{\iclrrulerbox}} +\AddToShipoutPicture{% +\ificlrfinal\else +\iclrruleroffset=\textheight +\advance\iclrruleroffset by -3.7pt + \color[rgb]{.7,.7,.7} + \AtTextUpperLeft{% + \put(\LenToUnit{-35pt},\LenToUnit{-\iclrruleroffset}){%left ruler + \iclrruler{\iclrrulercount}} + } +\fi +} +% %% To add a vertical bar on the side +% \AddToShipoutPicture{ +% \AtTextLowerLeft{ +% \hspace*{-1.8cm} +% \colorbox[rgb]{0.7,0.7,0.7}{\small \parbox[b][\textheight]{0.1cm}{}}} +% } diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.tex new file mode 100644 index 0000000..6950228 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/iclr2026_conference.tex @@ -0,0 +1,414 @@ + +\documentclass{article} % For LaTeX2e +\usepackage{iclr2026_conference,times} + +% Optional math commands from https://github.com/goodfeli/dlbook_notation. +\input{math_commands.tex} + +\usepackage{hyperref} +\usepackage{url} + + +\title{Formatting Instructions for ICLR 2026 \\ Conference Submissions} + +% Authors must not appear in the submitted version. They should be hidden +% as long as the \iclrfinalcopy macro remains commented out below. +% Non-anonymous submissions will be rejected without review. + +\author{Antiquus S.~Hippocampus, Natalia Cerebro \& Amelie P. Amygdale \thanks{ Use footnote for providing further information +about author (webpage, alternative address)---\emph{not} for acknowledging +funding agencies. Funding acknowledgements go at the end of the paper.} \\ +Department of Computer Science\\ +Cranberry-Lemon University\\ +Pittsburgh, PA 15213, USA \\ +\texttt{\{hippo,brain,jen\}@cs.cranberry-lemon.edu} \\ +\And +Ji Q. Ren \& Yevgeny LeNet \\ +Department of Computational Neuroscience \\ +University of the Witwatersrand \\ +Joburg, South Africa \\ +\texttt{\{robot,net\}@wits.ac.za} \\ +\AND +Coauthor \\ +Affiliation \\ +Address \\ +\texttt{email} +} + +% The \author macro works with any number of authors. There are two commands +% used to separate the names and addresses of multiple authors: \And and \AND. +% +% Using \And between authors leaves it to \LaTeX{} to determine where to break +% the lines. Using \AND forces a linebreak at that point. So, if \LaTeX{} +% puts 3 of 4 authors names on the first line, and the last on the second +% line, try using \AND instead of \And before the third author name. + +\newcommand{\fix}{\marginpar{FIX}} +\newcommand{\new}{\marginpar{NEW}} + +%\iclrfinalcopy % Uncomment for camera-ready version, but NOT for submission. +\begin{document} + + +\maketitle + +\begin{abstract} +The abstract paragraph should be indented 1/2~inch (3~picas) on both left and +right-hand margins. Use 10~point type, with a vertical spacing of 11~points. +The word \textsc{Abstract} must be centered, in small caps, and in point size 12. Two +line spaces precede the abstract. The abstract must be limited to one +paragraph. +\end{abstract} + +\section{Submission of conference papers to ICLR 2026} + +ICLR requires electronic submissions, processed by +\url{https://openreview.net/}. See ICLR's website for more instructions. + +If your paper is ultimately accepted, the statement {\tt + {\textbackslash}iclrfinalcopy} should be inserted to adjust the +format to the camera ready requirements. + +The format for the submissions is a variant of the NeurIPS format. +Please read carefully the instructions below, and follow them +faithfully. + +\subsection{Style} + +Papers to be submitted to ICLR 2026 must be prepared according to the +instructions presented here. + +%% Please note that we have introduced automatic line number generation +%% into the style file for \LaTeXe. This is to help reviewers +%% refer to specific lines of the paper when they make their comments. Please do +%% NOT refer to these line numbers in your paper as they will be removed from the +%% style file for the final version of accepted papers. + +Authors are required to use the ICLR \LaTeX{} style files obtainable at the +ICLR website. Please make sure you use the current files and +not previous versions. Tweaking the style files may be grounds for rejection. + +\subsection{Retrieval of style files} + +The style files for ICLR and other conference information are available online at: +\begin{center} + \url{http://www.iclr.cc/} +\end{center} +The file \verb+iclr2026_conference.pdf+ contains these +instructions and illustrates the +various formatting requirements your ICLR paper must satisfy. +Submissions must be made using \LaTeX{} and the style files +\verb+iclr2026_conference.sty+ and \verb+iclr2026_conference.bst+ (to be used with \LaTeX{}2e). The file +\verb+iclr2026_conference.tex+ may be used as a ``shell'' for writing your paper. All you +have to do is replace the author, title, abstract, and text of the paper with +your own. + +The formatting instructions contained in these style files are summarized in +sections \ref{gen_inst}, \ref{headings}, and \ref{others} below. + +\section{General formatting instructions} +\label{gen_inst} + +The text must be confined within a rectangle 5.5~inches (33~picas) wide and +9~inches (54~picas) long. The left margin is 1.5~inch (9~picas). +Use 10~point type with a vertical spacing of 11~points. Times New Roman is the +preferred typeface throughout. Paragraphs are separated by 1/2~line space, +with no indentation. + +Paper title is 17~point, in small caps and left-aligned. +All pages should start at 1~inch (6~picas) from the top of the page. + +Authors' names are +set in boldface, and each name is placed above its corresponding +address. The lead author's name is to be listed first, and +the co-authors' names are set to follow. Authors sharing the +same address can be on the same line. + +Please pay special attention to the instructions in section \ref{others} +regarding figures, tables, acknowledgments, and references. + + +There will be a strict upper limit of \textbf{9 pages} for the main text of the initial submission, with unlimited additional pages for citations. This limit will be expanded to \textbf{10 pages} for rebuttal/camera ready. + +\section{Headings: first level} +\label{headings} + +First level headings are in small caps, +flush left and in point size 12. One line space before the first level +heading and 1/2~line space after the first level heading. + +\subsection{Headings: second level} + +Second level headings are in small caps, +flush left and in point size 10. One line space before the second level +heading and 1/2~line space after the second level heading. + +\subsubsection{Headings: third level} + +Third level headings are in small caps, +flush left and in point size 10. One line space before the third level +heading and 1/2~line space after the third level heading. + +\section{Citations, figures, tables, references} +\label{others} + +These instructions apply to everyone, regardless of the formatter being used. + +\subsection{Citations within the text} + +Citations within the text should be based on the \texttt{natbib} package +and include the authors' last names and year (with the ``et~al.'' construct +for more than two authors). When the authors or the publication are +included in the sentence, the citation should not be in parenthesis using \verb|\citet{}| (as +in ``See \citet{Hinton06} for more information.''). Otherwise, the citation +should be in parenthesis using \verb|\citep{}| (as in ``Deep learning shows promise to make progress +towards AI~\citep{Bengio+chapter2007}.''). + +The corresponding references are to be listed in alphabetical order of +authors, in the \textsc{References} section. As to the format of the +references themselves, any style is acceptable as long as it is used +consistently. + +\subsection{Footnotes} + +Indicate footnotes with a number\footnote{Sample of the first footnote} in the +text. Place the footnotes at the bottom of the page on which they appear. +Precede the footnote with a horizontal rule of 2~inches +(12~picas).\footnote{Sample of the second footnote} + +\subsection{Figures} + +All artwork must be neat, clean, and legible. Lines should be dark +enough for purposes of reproduction; art work should not be +hand-drawn. The figure number and caption always appear after the +figure. Place one line space before the figure caption, and one line +space after the figure. The figure caption is lower case (except for +first word and proper nouns); figures are numbered consecutively. + +Make sure the figure caption does not get separated from the figure. +Leave sufficient space to avoid splitting the figure and figure caption. + +You may use color figures. +However, it is best for the +figure captions and the paper body to make sense if the paper is printed +either in black/white or in color. +\begin{figure}[h] +\begin{center} +%\framebox[4.0in]{$\;$} +\fbox{\rule[-.5cm]{0cm}{4cm} \rule[-.5cm]{4cm}{0cm}} +\end{center} +\caption{Sample figure caption.} +\end{figure} + +\subsection{Tables} + +All tables must be centered, neat, clean and legible. Do not use hand-drawn +tables. The table number and title always appear before the table. See +Table~\ref{sample-table}. + +Place one line space before the table title, one line space after the table +title, and one line space after the table. The table title must be lower case +(except for first word and proper nouns); tables are numbered consecutively. + +\begin{table}[t] +\caption{Sample table title} +\label{sample-table} +\begin{center} +\begin{tabular}{ll} +\multicolumn{1}{c}{\bf PART} &\multicolumn{1}{c}{\bf DESCRIPTION} +\\ \hline \\ +Dendrite &Input terminal \\ +Axon &Output terminal \\ +Soma &Cell body (contains cell nucleus) \\ +\end{tabular} +\end{center} +\end{table} + +\section{Default Notation} + +In an attempt to encourage standardized notation, we have included the +notation file from the textbook, \textit{Deep Learning} +\cite{goodfellow2016deep} available at +\url{https://github.com/goodfeli/dlbook_notation/}. Use of this style +is not required and can be disabled by commenting out +\texttt{math\_commands.tex}. + + +\centerline{\bf Numbers and Arrays} +\bgroup +\def\arraystretch{1.5} +\begin{tabular}{p{1in}p{3.25in}} +$\displaystyle a$ & A scalar (integer or real)\\ +$\displaystyle \va$ & A vector\\ +$\displaystyle \mA$ & A matrix\\ +$\displaystyle \tA$ & A tensor\\ +$\displaystyle \mI_n$ & Identity matrix with $n$ rows and $n$ columns\\ +$\displaystyle \mI$ & Identity matrix with dimensionality implied by context\\ +$\displaystyle \ve^{(i)}$ & Standard basis vector $[0,\dots,0,1,0,\dots,0]$ with a 1 at position $i$\\ +$\displaystyle \text{diag}(\va)$ & A square, diagonal matrix with diagonal entries given by $\va$\\ +$\displaystyle \ra$ & A scalar random variable\\ +$\displaystyle \rva$ & A vector-valued random variable\\ +$\displaystyle \rmA$ & A matrix-valued random variable\\ +\end{tabular} +\egroup +\vspace{0.25cm} + +\centerline{\bf Sets and Graphs} +\bgroup +\def\arraystretch{1.5} + +\begin{tabular}{p{1.25in}p{3.25in}} +$\displaystyle \sA$ & A set\\ +$\displaystyle \R$ & The set of real numbers \\ +$\displaystyle \{0, 1\}$ & The set containing 0 and 1 \\ +$\displaystyle \{0, 1, \dots, n \}$ & The set of all integers between $0$ and $n$\\ +$\displaystyle [a, b]$ & The real interval including $a$ and $b$\\ +$\displaystyle (a, b]$ & The real interval excluding $a$ but including $b$\\ +$\displaystyle \sA \backslash \sB$ & Set subtraction, i.e., the set containing the elements of $\sA$ that are not in $\sB$\\ +$\displaystyle \gG$ & A graph\\ +$\displaystyle \parents_\gG(\ervx_i)$ & The parents of $\ervx_i$ in $\gG$ +\end{tabular} +\vspace{0.25cm} + + +\centerline{\bf Indexing} +\bgroup +\def\arraystretch{1.5} + +\begin{tabular}{p{1.25in}p{3.25in}} +$\displaystyle \eva_i$ & Element $i$ of vector $\va$, with indexing starting at 1 \\ +$\displaystyle \eva_{-i}$ & All elements of vector $\va$ except for element $i$ \\ +$\displaystyle \emA_{i,j}$ & Element $i, j$ of matrix $\mA$ \\ +$\displaystyle \mA_{i, :}$ & Row $i$ of matrix $\mA$ \\ +$\displaystyle \mA_{:, i}$ & Column $i$ of matrix $\mA$ \\ +$\displaystyle \etA_{i, j, k}$ & Element $(i, j, k)$ of a 3-D tensor $\tA$\\ +$\displaystyle \tA_{:, :, i}$ & 2-D slice of a 3-D tensor\\ +$\displaystyle \erva_i$ & Element $i$ of the random vector $\rva$ \\ +\end{tabular} +\egroup +\vspace{0.25cm} + + +\centerline{\bf Calculus} +\bgroup +\def\arraystretch{1.5} +\begin{tabular}{p{1.25in}p{3.25in}} +% NOTE: the [2ex] on the next line adds extra height to that row of the table. +% Without that command, the fraction on the first line is too tall and collides +% with the fraction on the second line. +$\displaystyle\frac{d y} {d x}$ & Derivative of $y$ with respect to $x$\\ [2ex] +$\displaystyle \frac{\partial y} {\partial x} $ & Partial derivative of $y$ with respect to $x$ \\ +$\displaystyle \nabla_\vx y $ & Gradient of $y$ with respect to $\vx$ \\ +$\displaystyle \nabla_\mX y $ & Matrix derivatives of $y$ with respect to $\mX$ \\ +$\displaystyle \nabla_\tX y $ & Tensor containing derivatives of $y$ with respect to $\tX$ \\ +$\displaystyle \frac{\partial f}{\partial \vx} $ & Jacobian matrix $\mJ \in \R^{m\times n}$ of $f: \R^n \rightarrow \R^m$\\ +$\displaystyle \nabla_\vx^2 f(\vx)\text{ or }\mH( f)(\vx)$ & The Hessian matrix of $f$ at input point $\vx$\\ +$\displaystyle \int f(\vx) d\vx $ & Definite integral over the entire domain of $\vx$ \\ +$\displaystyle \int_\sS f(\vx) d\vx$ & Definite integral with respect to $\vx$ over the set $\sS$ \\ +\end{tabular} +\egroup +\vspace{0.25cm} + +\centerline{\bf Probability and Information Theory} +\bgroup +\def\arraystretch{1.5} +\begin{tabular}{p{1.25in}p{3.25in}} +$\displaystyle P(\ra)$ & A probability distribution over a discrete variable\\ +$\displaystyle p(\ra)$ & A probability distribution over a continuous variable, or over +a variable whose type has not been specified\\ +$\displaystyle \ra \sim P$ & Random variable $\ra$ has distribution $P$\\% so thing on left of \sim should always be a random variable, with name beginning with \r +$\displaystyle \E_{\rx\sim P} [ f(x) ]\text{ or } \E f(x)$ & Expectation of $f(x)$ with respect to $P(\rx)$ \\ +$\displaystyle \Var(f(x)) $ & Variance of $f(x)$ under $P(\rx)$ \\ +$\displaystyle \Cov(f(x),g(x)) $ & Covariance of $f(x)$ and $g(x)$ under $P(\rx)$\\ +$\displaystyle H(\rx) $ & Shannon entropy of the random variable $\rx$\\ +$\displaystyle \KL ( P \Vert Q ) $ & Kullback-Leibler divergence of P and Q \\ +$\displaystyle \mathcal{N} ( \vx ; \vmu , \mSigma)$ & Gaussian distribution % +over $\vx$ with mean $\vmu$ and covariance $\mSigma$ \\ +\end{tabular} +\egroup +\vspace{0.25cm} + +\centerline{\bf Functions} +\bgroup +\def\arraystretch{1.5} +\begin{tabular}{p{1.25in}p{3.25in}} +$\displaystyle f: \sA \rightarrow \sB$ & The function $f$ with domain $\sA$ and range $\sB$\\ +$\displaystyle f \circ g $ & Composition of the functions $f$ and $g$ \\ + $\displaystyle f(\vx ; \vtheta) $ & A function of $\vx$ parametrized by $\vtheta$. + (Sometimes we write $f(\vx)$ and omit the argument $\vtheta$ to lighten notation) \\ +$\displaystyle \log x$ & Natural logarithm of $x$ \\ +$\displaystyle \sigma(x)$ & Logistic sigmoid, $\displaystyle \frac{1} {1 + \exp(-x)}$ \\ +$\displaystyle \zeta(x)$ & Softplus, $\log(1 + \exp(x))$ \\ +$\displaystyle || \vx ||_p $ & $\normlp$ norm of $\vx$ \\ +$\displaystyle || \vx || $ & $\normltwo$ norm of $\vx$ \\ +$\displaystyle x^+$ & Positive part of $x$, i.e., $\max(0,x)$\\ +$\displaystyle \1_\mathrm{condition}$ & is 1 if the condition is true, 0 otherwise\\ +\end{tabular} +\egroup +\vspace{0.25cm} + + + +\section{Final instructions} +Do not change any aspects of the formatting parameters in the style files. +In particular, do not modify the width or length of the rectangle the text +should fit into, and do not change font sizes (except perhaps in the +\textsc{References} section; see below). Please note that pages should be +numbered. + +\section{Preparing PostScript or PDF files} + +Please prepare PostScript or PDF files with paper size ``US Letter'', and +not, for example, ``A4''. The -t +letter option on dvips will produce US Letter files. + +Consider directly generating PDF files using \verb+pdflatex+ +(especially if you are a MiKTeX user). +PDF figures must be substituted for EPS figures, however. + +Otherwise, please generate your PostScript and PDF files with the following commands: +\begin{verbatim} +dvips mypaper.dvi -t letter -Ppdf -G0 -o mypaper.ps +ps2pdf mypaper.ps mypaper.pdf +\end{verbatim} + +\subsection{Margins in LaTeX} + +Most of the margin problems come from figures positioned by hand using +\verb+\special+ or other commands. We suggest using the command +\verb+\includegraphics+ +from the graphicx package. Always specify the figure width as a multiple of +the line width as in the example below using .eps graphics +\begin{verbatim} + \usepackage[dvips]{graphicx} ... + \includegraphics[width=0.8\linewidth]{myfile.eps} +\end{verbatim} +or % Apr 2009 addition +\begin{verbatim} + \usepackage[pdftex]{graphicx} ... + \includegraphics[width=0.8\linewidth]{myfile.pdf} +\end{verbatim} +for .pdf graphics. +See section~4.4 in the graphics bundle documentation (\url{http://www.ctan.org/tex-archive/macros/latex/required/graphics/grfguide.ps}) + +A number of width problems arise when LaTeX cannot properly hyphenate a +line. Please give LaTeX hyphenation hints using the \verb+\-+ command. + +\subsubsection*{Author Contributions} +If you'd like to, you may include a section for author contributions as is done +in many journals. This is optional and at the discretion of the authors. + +\subsubsection*{Acknowledgments} +Use unnumbered third level headings for the acknowledgments. All +acknowledgments, including those to funding agencies, go at the end of the paper. + + +\bibliography{iclr2026_conference} +\bibliographystyle{iclr2026_conference} + +\appendix +\section{Appendix} +You may include other additional sections here. + + +\end{document} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/math_commands.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/math_commands.tex new file mode 100644 index 0000000..0668f93 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/math_commands.tex @@ -0,0 +1,508 @@ +%%%%% NEW MATH DEFINITIONS %%%%% + +\usepackage{amsmath,amsfonts,bm} + +% Mark sections of captions for referring to divisions of figures +\newcommand{\figleft}{{\em (Left)}} +\newcommand{\figcenter}{{\em (Center)}} +\newcommand{\figright}{{\em (Right)}} +\newcommand{\figtop}{{\em (Top)}} +\newcommand{\figbottom}{{\em (Bottom)}} +\newcommand{\captiona}{{\em (a)}} +\newcommand{\captionb}{{\em (b)}} +\newcommand{\captionc}{{\em (c)}} +\newcommand{\captiond}{{\em (d)}} + +% Highlight a newly defined term +\newcommand{\newterm}[1]{{\bf #1}} + + +% Figure reference, lower-case. +\def\figref#1{figure~\ref{#1}} +% Figure reference, capital. For start of sentence +\def\Figref#1{Figure~\ref{#1}} +\def\twofigref#1#2{figures \ref{#1} and \ref{#2}} +\def\quadfigref#1#2#3#4{figures \ref{#1}, \ref{#2}, \ref{#3} and \ref{#4}} +% Section reference, lower-case. +\def\secref#1{section~\ref{#1}} +% Section reference, capital. +\def\Secref#1{Section~\ref{#1}} +% Reference to two sections. +\def\twosecrefs#1#2{sections \ref{#1} and \ref{#2}} +% Reference to three sections. +\def\secrefs#1#2#3{sections \ref{#1}, \ref{#2} and \ref{#3}} +% Reference to an equation, lower-case. +\def\eqref#1{equation~\ref{#1}} +% Reference to an equation, upper case +\def\Eqref#1{Equation~\ref{#1}} +% A raw reference to an equation---avoid using if possible +\def\plaineqref#1{\ref{#1}} +% Reference to a chapter, lower-case. +\def\chapref#1{chapter~\ref{#1}} +% Reference to an equation, upper case. +\def\Chapref#1{Chapter~\ref{#1}} +% Reference to a range of chapters +\def\rangechapref#1#2{chapters\ref{#1}--\ref{#2}} +% Reference to an algorithm, lower-case. +\def\algref#1{algorithm~\ref{#1}} +% Reference to an algorithm, upper case. +\def\Algref#1{Algorithm~\ref{#1}} +\def\twoalgref#1#2{algorithms \ref{#1} and \ref{#2}} +\def\Twoalgref#1#2{Algorithms \ref{#1} and \ref{#2}} +% Reference to a part, lower case +\def\partref#1{part~\ref{#1}} +% Reference to a part, upper case +\def\Partref#1{Part~\ref{#1}} +\def\twopartref#1#2{parts \ref{#1} and \ref{#2}} + +\def\ceil#1{\lceil #1 \rceil} +\def\floor#1{\lfloor #1 \rfloor} +\def\1{\bm{1}} +\newcommand{\train}{\mathcal{D}} +\newcommand{\valid}{\mathcal{D_{\mathrm{valid}}}} +\newcommand{\test}{\mathcal{D_{\mathrm{test}}}} + +\def\eps{{\epsilon}} + + +% Random variables +\def\reta{{\textnormal{$\eta$}}} +\def\ra{{\textnormal{a}}} +\def\rb{{\textnormal{b}}} +\def\rc{{\textnormal{c}}} +\def\rd{{\textnormal{d}}} +\def\re{{\textnormal{e}}} +\def\rf{{\textnormal{f}}} +\def\rg{{\textnormal{g}}} +\def\rh{{\textnormal{h}}} +\def\ri{{\textnormal{i}}} +\def\rj{{\textnormal{j}}} +\def\rk{{\textnormal{k}}} +\def\rl{{\textnormal{l}}} +% rm is already a command, just don't name any random variables m +\def\rn{{\textnormal{n}}} +\def\ro{{\textnormal{o}}} +\def\rp{{\textnormal{p}}} +\def\rq{{\textnormal{q}}} +\def\rr{{\textnormal{r}}} +\def\rs{{\textnormal{s}}} +\def\rt{{\textnormal{t}}} +\def\ru{{\textnormal{u}}} +\def\rv{{\textnormal{v}}} +\def\rw{{\textnormal{w}}} +\def\rx{{\textnormal{x}}} +\def\ry{{\textnormal{y}}} +\def\rz{{\textnormal{z}}} + +% Random vectors +\def\rvepsilon{{\mathbf{\epsilon}}} +\def\rvtheta{{\mathbf{\theta}}} +\def\rva{{\mathbf{a}}} +\def\rvb{{\mathbf{b}}} +\def\rvc{{\mathbf{c}}} +\def\rvd{{\mathbf{d}}} +\def\rve{{\mathbf{e}}} +\def\rvf{{\mathbf{f}}} +\def\rvg{{\mathbf{g}}} +\def\rvh{{\mathbf{h}}} +\def\rvu{{\mathbf{i}}} +\def\rvj{{\mathbf{j}}} +\def\rvk{{\mathbf{k}}} +\def\rvl{{\mathbf{l}}} +\def\rvm{{\mathbf{m}}} +\def\rvn{{\mathbf{n}}} +\def\rvo{{\mathbf{o}}} +\def\rvp{{\mathbf{p}}} +\def\rvq{{\mathbf{q}}} +\def\rvr{{\mathbf{r}}} +\def\rvs{{\mathbf{s}}} +\def\rvt{{\mathbf{t}}} +\def\rvu{{\mathbf{u}}} +\def\rvv{{\mathbf{v}}} +\def\rvw{{\mathbf{w}}} +\def\rvx{{\mathbf{x}}} +\def\rvy{{\mathbf{y}}} +\def\rvz{{\mathbf{z}}} + +% Elements of random vectors +\def\erva{{\textnormal{a}}} +\def\ervb{{\textnormal{b}}} +\def\ervc{{\textnormal{c}}} +\def\ervd{{\textnormal{d}}} +\def\erve{{\textnormal{e}}} +\def\ervf{{\textnormal{f}}} +\def\ervg{{\textnormal{g}}} +\def\ervh{{\textnormal{h}}} +\def\ervi{{\textnormal{i}}} +\def\ervj{{\textnormal{j}}} +\def\ervk{{\textnormal{k}}} +\def\ervl{{\textnormal{l}}} +\def\ervm{{\textnormal{m}}} +\def\ervn{{\textnormal{n}}} +\def\ervo{{\textnormal{o}}} +\def\ervp{{\textnormal{p}}} +\def\ervq{{\textnormal{q}}} +\def\ervr{{\textnormal{r}}} +\def\ervs{{\textnormal{s}}} +\def\ervt{{\textnormal{t}}} +\def\ervu{{\textnormal{u}}} +\def\ervv{{\textnormal{v}}} +\def\ervw{{\textnormal{w}}} +\def\ervx{{\textnormal{x}}} +\def\ervy{{\textnormal{y}}} +\def\ervz{{\textnormal{z}}} + +% Random matrices +\def\rmA{{\mathbf{A}}} +\def\rmB{{\mathbf{B}}} +\def\rmC{{\mathbf{C}}} +\def\rmD{{\mathbf{D}}} +\def\rmE{{\mathbf{E}}} +\def\rmF{{\mathbf{F}}} +\def\rmG{{\mathbf{G}}} +\def\rmH{{\mathbf{H}}} +\def\rmI{{\mathbf{I}}} +\def\rmJ{{\mathbf{J}}} +\def\rmK{{\mathbf{K}}} +\def\rmL{{\mathbf{L}}} +\def\rmM{{\mathbf{M}}} +\def\rmN{{\mathbf{N}}} +\def\rmO{{\mathbf{O}}} +\def\rmP{{\mathbf{P}}} +\def\rmQ{{\mathbf{Q}}} +\def\rmR{{\mathbf{R}}} +\def\rmS{{\mathbf{S}}} +\def\rmT{{\mathbf{T}}} +\def\rmU{{\mathbf{U}}} +\def\rmV{{\mathbf{V}}} +\def\rmW{{\mathbf{W}}} +\def\rmX{{\mathbf{X}}} +\def\rmY{{\mathbf{Y}}} +\def\rmZ{{\mathbf{Z}}} + +% Elements of random matrices +\def\ermA{{\textnormal{A}}} +\def\ermB{{\textnormal{B}}} +\def\ermC{{\textnormal{C}}} +\def\ermD{{\textnormal{D}}} +\def\ermE{{\textnormal{E}}} +\def\ermF{{\textnormal{F}}} +\def\ermG{{\textnormal{G}}} +\def\ermH{{\textnormal{H}}} +\def\ermI{{\textnormal{I}}} +\def\ermJ{{\textnormal{J}}} +\def\ermK{{\textnormal{K}}} +\def\ermL{{\textnormal{L}}} +\def\ermM{{\textnormal{M}}} +\def\ermN{{\textnormal{N}}} +\def\ermO{{\textnormal{O}}} +\def\ermP{{\textnormal{P}}} +\def\ermQ{{\textnormal{Q}}} +\def\ermR{{\textnormal{R}}} +\def\ermS{{\textnormal{S}}} +\def\ermT{{\textnormal{T}}} +\def\ermU{{\textnormal{U}}} +\def\ermV{{\textnormal{V}}} +\def\ermW{{\textnormal{W}}} +\def\ermX{{\textnormal{X}}} +\def\ermY{{\textnormal{Y}}} +\def\ermZ{{\textnormal{Z}}} + +% Vectors +\def\vzero{{\bm{0}}} +\def\vone{{\bm{1}}} +\def\vmu{{\bm{\mu}}} +\def\vtheta{{\bm{\theta}}} +\def\va{{\bm{a}}} +\def\vb{{\bm{b}}} +\def\vc{{\bm{c}}} +\def\vd{{\bm{d}}} +\def\ve{{\bm{e}}} +\def\vf{{\bm{f}}} +\def\vg{{\bm{g}}} +\def\vh{{\bm{h}}} +\def\vi{{\bm{i}}} +\def\vj{{\bm{j}}} +\def\vk{{\bm{k}}} +\def\vl{{\bm{l}}} +\def\vm{{\bm{m}}} +\def\vn{{\bm{n}}} +\def\vo{{\bm{o}}} +\def\vp{{\bm{p}}} +\def\vq{{\bm{q}}} +\def\vr{{\bm{r}}} +\def\vs{{\bm{s}}} +\def\vt{{\bm{t}}} +\def\vu{{\bm{u}}} +\def\vv{{\bm{v}}} +\def\vw{{\bm{w}}} +\def\vx{{\bm{x}}} +\def\vy{{\bm{y}}} +\def\vz{{\bm{z}}} + +% Elements of vectors +\def\evalpha{{\alpha}} +\def\evbeta{{\beta}} +\def\evepsilon{{\epsilon}} +\def\evlambda{{\lambda}} +\def\evomega{{\omega}} +\def\evmu{{\mu}} +\def\evpsi{{\psi}} +\def\evsigma{{\sigma}} +\def\evtheta{{\theta}} +\def\eva{{a}} +\def\evb{{b}} +\def\evc{{c}} +\def\evd{{d}} +\def\eve{{e}} +\def\evf{{f}} +\def\evg{{g}} +\def\evh{{h}} +\def\evi{{i}} +\def\evj{{j}} +\def\evk{{k}} +\def\evl{{l}} +\def\evm{{m}} +\def\evn{{n}} +\def\evo{{o}} +\def\evp{{p}} +\def\evq{{q}} +\def\evr{{r}} +\def\evs{{s}} +\def\evt{{t}} +\def\evu{{u}} +\def\evv{{v}} +\def\evw{{w}} +\def\evx{{x}} +\def\evy{{y}} +\def\evz{{z}} + +% Matrix +\def\mA{{\bm{A}}} +\def\mB{{\bm{B}}} +\def\mC{{\bm{C}}} +\def\mD{{\bm{D}}} +\def\mE{{\bm{E}}} +\def\mF{{\bm{F}}} +\def\mG{{\bm{G}}} +\def\mH{{\bm{H}}} +\def\mI{{\bm{I}}} +\def\mJ{{\bm{J}}} +\def\mK{{\bm{K}}} +\def\mL{{\bm{L}}} +\def\mM{{\bm{M}}} +\def\mN{{\bm{N}}} +\def\mO{{\bm{O}}} +\def\mP{{\bm{P}}} +\def\mQ{{\bm{Q}}} +\def\mR{{\bm{R}}} +\def\mS{{\bm{S}}} +\def\mT{{\bm{T}}} +\def\mU{{\bm{U}}} +\def\mV{{\bm{V}}} +\def\mW{{\bm{W}}} +\def\mX{{\bm{X}}} +\def\mY{{\bm{Y}}} +\def\mZ{{\bm{Z}}} +\def\mBeta{{\bm{\beta}}} +\def\mPhi{{\bm{\Phi}}} +\def\mLambda{{\bm{\Lambda}}} +\def\mSigma{{\bm{\Sigma}}} + +% Tensor +\DeclareMathAlphabet{\mathsfit}{\encodingdefault}{\sfdefault}{m}{sl} +\SetMathAlphabet{\mathsfit}{bold}{\encodingdefault}{\sfdefault}{bx}{n} +\newcommand{\tens}[1]{\bm{\mathsfit{#1}}} +\def\tA{{\tens{A}}} +\def\tB{{\tens{B}}} +\def\tC{{\tens{C}}} +\def\tD{{\tens{D}}} +\def\tE{{\tens{E}}} +\def\tF{{\tens{F}}} +\def\tG{{\tens{G}}} +\def\tH{{\tens{H}}} +\def\tI{{\tens{I}}} +\def\tJ{{\tens{J}}} +\def\tK{{\tens{K}}} +\def\tL{{\tens{L}}} +\def\tM{{\tens{M}}} +\def\tN{{\tens{N}}} +\def\tO{{\tens{O}}} +\def\tP{{\tens{P}}} +\def\tQ{{\tens{Q}}} +\def\tR{{\tens{R}}} +\def\tS{{\tens{S}}} +\def\tT{{\tens{T}}} +\def\tU{{\tens{U}}} +\def\tV{{\tens{V}}} +\def\tW{{\tens{W}}} +\def\tX{{\tens{X}}} +\def\tY{{\tens{Y}}} +\def\tZ{{\tens{Z}}} + + +% Graph +\def\gA{{\mathcal{A}}} +\def\gB{{\mathcal{B}}} +\def\gC{{\mathcal{C}}} +\def\gD{{\mathcal{D}}} +\def\gE{{\mathcal{E}}} +\def\gF{{\mathcal{F}}} +\def\gG{{\mathcal{G}}} +\def\gH{{\mathcal{H}}} +\def\gI{{\mathcal{I}}} +\def\gJ{{\mathcal{J}}} +\def\gK{{\mathcal{K}}} +\def\gL{{\mathcal{L}}} +\def\gM{{\mathcal{M}}} +\def\gN{{\mathcal{N}}} +\def\gO{{\mathcal{O}}} +\def\gP{{\mathcal{P}}} +\def\gQ{{\mathcal{Q}}} +\def\gR{{\mathcal{R}}} +\def\gS{{\mathcal{S}}} +\def\gT{{\mathcal{T}}} +\def\gU{{\mathcal{U}}} +\def\gV{{\mathcal{V}}} +\def\gW{{\mathcal{W}}} +\def\gX{{\mathcal{X}}} +\def\gY{{\mathcal{Y}}} +\def\gZ{{\mathcal{Z}}} + +% Sets +\def\sA{{\mathbb{A}}} +\def\sB{{\mathbb{B}}} +\def\sC{{\mathbb{C}}} +\def\sD{{\mathbb{D}}} +% Don't use a set called E, because this would be the same as our symbol +% for expectation. +\def\sF{{\mathbb{F}}} +\def\sG{{\mathbb{G}}} +\def\sH{{\mathbb{H}}} +\def\sI{{\mathbb{I}}} +\def\sJ{{\mathbb{J}}} +\def\sK{{\mathbb{K}}} +\def\sL{{\mathbb{L}}} +\def\sM{{\mathbb{M}}} +\def\sN{{\mathbb{N}}} +\def\sO{{\mathbb{O}}} +\def\sP{{\mathbb{P}}} +\def\sQ{{\mathbb{Q}}} +\def\sR{{\mathbb{R}}} +\def\sS{{\mathbb{S}}} +\def\sT{{\mathbb{T}}} +\def\sU{{\mathbb{U}}} +\def\sV{{\mathbb{V}}} +\def\sW{{\mathbb{W}}} +\def\sX{{\mathbb{X}}} +\def\sY{{\mathbb{Y}}} +\def\sZ{{\mathbb{Z}}} + +% Entries of a matrix +\def\emLambda{{\Lambda}} +\def\emA{{A}} +\def\emB{{B}} +\def\emC{{C}} +\def\emD{{D}} +\def\emE{{E}} +\def\emF{{F}} +\def\emG{{G}} +\def\emH{{H}} +\def\emI{{I}} +\def\emJ{{J}} +\def\emK{{K}} +\def\emL{{L}} +\def\emM{{M}} +\def\emN{{N}} +\def\emO{{O}} +\def\emP{{P}} +\def\emQ{{Q}} +\def\emR{{R}} +\def\emS{{S}} +\def\emT{{T}} +\def\emU{{U}} +\def\emV{{V}} +\def\emW{{W}} +\def\emX{{X}} +\def\emY{{Y}} +\def\emZ{{Z}} +\def\emSigma{{\Sigma}} + +% entries of a tensor +% Same font as tensor, without \bm wrapper +\newcommand{\etens}[1]{\mathsfit{#1}} +\def\etLambda{{\etens{\Lambda}}} +\def\etA{{\etens{A}}} +\def\etB{{\etens{B}}} +\def\etC{{\etens{C}}} +\def\etD{{\etens{D}}} +\def\etE{{\etens{E}}} +\def\etF{{\etens{F}}} +\def\etG{{\etens{G}}} +\def\etH{{\etens{H}}} +\def\etI{{\etens{I}}} +\def\etJ{{\etens{J}}} +\def\etK{{\etens{K}}} +\def\etL{{\etens{L}}} +\def\etM{{\etens{M}}} +\def\etN{{\etens{N}}} +\def\etO{{\etens{O}}} +\def\etP{{\etens{P}}} +\def\etQ{{\etens{Q}}} +\def\etR{{\etens{R}}} +\def\etS{{\etens{S}}} +\def\etT{{\etens{T}}} +\def\etU{{\etens{U}}} +\def\etV{{\etens{V}}} +\def\etW{{\etens{W}}} +\def\etX{{\etens{X}}} +\def\etY{{\etens{Y}}} +\def\etZ{{\etens{Z}}} + +% The true underlying data generating distribution +\newcommand{\pdata}{p_{\rm{data}}} +% The empirical distribution defined by the training set +\newcommand{\ptrain}{\hat{p}_{\rm{data}}} +\newcommand{\Ptrain}{\hat{P}_{\rm{data}}} +% The model distribution +\newcommand{\pmodel}{p_{\rm{model}}} +\newcommand{\Pmodel}{P_{\rm{model}}} +\newcommand{\ptildemodel}{\tilde{p}_{\rm{model}}} +% Stochastic autoencoder distributions +\newcommand{\pencode}{p_{\rm{encoder}}} +\newcommand{\pdecode}{p_{\rm{decoder}}} +\newcommand{\precons}{p_{\rm{reconstruct}}} + +\newcommand{\laplace}{\mathrm{Laplace}} % Laplace distribution + +\newcommand{\E}{\mathbb{E}} +\newcommand{\Ls}{\mathcal{L}} +\newcommand{\R}{\mathbb{R}} +\newcommand{\emp}{\tilde{p}} +\newcommand{\lr}{\alpha} +\newcommand{\reg}{\lambda} +\newcommand{\rect}{\mathrm{rectifier}} +\newcommand{\softmax}{\mathrm{softmax}} +\newcommand{\sigmoid}{\sigma} +\newcommand{\softplus}{\zeta} +\newcommand{\KL}{D_{\mathrm{KL}}} +\newcommand{\Var}{\mathrm{Var}} +\newcommand{\standarderror}{\mathrm{SE}} +\newcommand{\Cov}{\mathrm{Cov}} +% Wolfram Mathworld says $L^2$ is for function spaces and $\ell^2$ is for vectors +% But then they seem to use $L^2$ for vectors throughout the site, and so does +% wikipedia. +\newcommand{\normlzero}{L^0} +\newcommand{\normlone}{L^1} +\newcommand{\normltwo}{L^2} +\newcommand{\normlp}{L^p} +\newcommand{\normmax}{L^\infty} + +\newcommand{\parents}{Pa} % See usage in notation.tex. Chosen to match Daphne's book. + +\DeclareMathOperator*{\argmax}{arg\,max} +\DeclareMathOperator*{\argmin}{arg\,min} + +\DeclareMathOperator{\sign}{sign} +\DeclareMathOperator{\Tr}{Tr} +\let\ab\allowbreak diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/natbib.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/natbib.sty new file mode 100644 index 0000000..ff0d0b9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/iclr2026/natbib.sty @@ -0,0 +1,1246 @@ +%% +%% This is file `natbib.sty', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% natbib.dtx (with options: `package,all') +%% ============================================= +%% IMPORTANT NOTICE: +%% +%% This program can be redistributed and/or modified under the terms +%% of the LaTeX Project Public License Distributed from CTAN +%% archives in directory macros/latex/base/lppl.txt; either +%% version 1 of the License, or any later version. +%% +%% This is a generated file. +%% It may not be distributed without the original source file natbib.dtx. +%% +%% Full documentation can be obtained by LaTeXing that original file. +%% Only a few abbreviated comments remain here to describe the usage. +%% ============================================= +%% Copyright 1993-2009 Patrick W Daly +%% Max-Planck-Institut f\"ur Sonnensystemforschung +%% Max-Planck-Str. 2 +%% D-37191 Katlenburg-Lindau +%% Germany +%% E-mail: daly@mps.mpg.de +\NeedsTeXFormat{LaTeX2e}[1995/06/01] +\ProvidesPackage{natbib} + [2009/07/16 8.31 (PWD, AO)] + + % This package reimplements the LaTeX \cite command to be used for various + % citation styles, both author-year and numerical. It accepts BibTeX + % output intended for many other packages, and therefore acts as a + % general, all-purpose citation-style interface. + % + % With standard numerical .bst files, only numerical citations are + % possible. With an author-year .bst file, both numerical and + % author-year citations are possible. + % + % If author-year citations are selected, \bibitem must have one of the + % following forms: + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Williams]{key}... + % \bibitem[Jones et al., 1990]{key}... + % \bibitem[\protect\citeauthoryear{Jones, Baker, and Williams}{Jones + % et al.}{1990}]{key}... + % \bibitem[\protect\citeauthoryear{Jones et al.}{1990}]{key}... + % \bibitem[\protect\astroncite{Jones et al.}{1990}]{key}... + % \bibitem[\protect\citename{Jones et al., }1990]{key}... + % \harvarditem[Jones et al.]{Jones, Baker, and Williams}{1990}{key}... + % + % This is either to be made up manually, or to be generated by an + % appropriate .bst file with BibTeX. + % Author-year mode || Numerical mode + % Then, \citet{key} ==>> Jones et al. (1990) || Jones et al. [21] + % \citep{key} ==>> (Jones et al., 1990) || [21] + % Multiple citations as normal: + % \citep{key1,key2} ==>> (Jones et al., 1990; Smith, 1989) || [21,24] + % or (Jones et al., 1990, 1991) || [21,24] + % or (Jones et al., 1990a,b) || [21,24] + % \cite{key} is the equivalent of \citet{key} in author-year mode + % and of \citep{key} in numerical mode + % Full author lists may be forced with \citet* or \citep*, e.g. + % \citep*{key} ==>> (Jones, Baker, and Williams, 1990) + % Optional notes as: + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.,][]{key} ==>> (e.g., Jones et al., 1990) + % \citep[see][pg. 34]{key}==>> (see Jones et al., 1990, pg. 34) + % (Note: in standard LaTeX, only one note is allowed, after the ref. + % Here, one note is like the standard, two make pre- and post-notes.) + % \citealt{key} ==>> Jones et al. 1990 + % \citealt*{key} ==>> Jones, Baker, and Williams 1990 + % \citealp{key} ==>> Jones et al., 1990 + % \citealp*{key} ==>> Jones, Baker, and Williams, 1990 + % Additional citation possibilities (both author-year and numerical modes) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Williams + % \citeyear{key} ==>> 1990 + % \citeyearpar{key} ==>> (1990) + % \citetext{priv. comm.} ==>> (priv. comm.) + % \citenum{key} ==>> 11 [non-superscripted] + % Note: full author lists depends on whether the bib style supports them; + % if not, the abbreviated list is printed even when full requested. + % + % For names like della Robbia at the start of a sentence, use + % \Citet{dRob98} ==>> Della Robbia (1998) + % \Citep{dRob98} ==>> (Della Robbia, 1998) + % \Citeauthor{dRob98} ==>> Della Robbia + % + % + % Citation aliasing is achieved with + % \defcitealias{key}{text} + % \citetalias{key} ==>> text + % \citepalias{key} ==>> (text) + % + % Defining the citation mode and punctual (citation style) + % \setcitestyle{<comma-separated list of keywords, same + % as the package options>} + % Example: \setcitestyle{square,semicolon} + % Alternatively: + % Use \bibpunct with 6 mandatory arguments: + % 1. opening bracket for citation + % 2. closing bracket + % 3. citation separator (for multiple citations in one \cite) + % 4. the letter n for numerical styles, s for superscripts + % else anything for author-year + % 5. punctuation between authors and date + % 6. punctuation between years (or numbers) when common authors missing + % One optional argument is the character coming before post-notes. It + % appears in square braces before all other arguments. May be left off. + % Example (and default) \bibpunct[, ]{(}{)}{;}{a}{,}{,} + % + % To make this automatic for a given bib style, named newbib, say, make + % a local configuration file, natbib.cfg, with the definition + % \newcommand{\bibstyle@newbib}{\bibpunct...} + % Then the \bibliographystyle{newbib} will cause \bibstyle@newbib to + % be called on THE NEXT LATEX RUN (via the aux file). + % + % Such preprogrammed definitions may be invoked anywhere in the text + % by calling \citestyle{newbib}. This is only useful if the style specified + % differs from that in \bibliographystyle. + % + % With \citeindextrue and \citeindexfalse, one can control whether the + % \cite commands make an automatic entry of the citation in the .idx + % indexing file. For this, \makeindex must also be given in the preamble. + % + % Package Options: (for selecting punctuation) + % round - round parentheses are used (default) + % square - square brackets are used [option] + % curly - curly braces are used {option} + % angle - angle brackets are used <option> + % semicolon - multiple citations separated by semi-colon (default) + % colon - same as semicolon, an earlier confusion + % comma - separated by comma + % authoryear - selects author-year citations (default) + % numbers- selects numerical citations + % super - numerical citations as superscripts + % sort - sorts multiple citations according to order in ref. list + % sort&compress - like sort, but also compresses numerical citations + % compress - compresses without sorting + % longnamesfirst - makes first citation full author list + % sectionbib - puts bibliography in a \section* instead of \chapter* + % merge - allows the citation key to have a * prefix, + % signifying to merge its reference with that of the previous citation. + % elide - if references are merged, repeated portions of later ones may be removed. + % mcite - recognizes and ignores the * prefix for merging. + % Punctuation so selected dominates over any predefined ones. + % Package options are called as, e.g. + % \usepackage[square,comma]{natbib} + % LaTeX the source file natbib.dtx to obtain more details + % or the file natnotes.tex for a brief reference sheet. + %----------------------------------------------------------- +\providecommand\@ifxundefined[1]{% + \ifx#1\@undefined\expandafter\@firstoftwo\else\expandafter\@secondoftwo\fi +}% +\providecommand\@ifnum[1]{% + \ifnum#1\expandafter\@firstoftwo\else\expandafter\@secondoftwo\fi +}% +\providecommand\@ifx[1]{% + \ifx#1\expandafter\@firstoftwo\else\expandafter\@secondoftwo\fi +}% +\providecommand\appdef[2]{% + \toks@\expandafter{#1}\@temptokena{#2}% + \edef#1{\the\toks@\the\@temptokena}% +}% +\@ifclassloaded{agu2001}{\PackageError{natbib} + {The agu2001 class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{agutex}{\PackageError{natbib} + {The AGUTeX class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{aguplus}{\PackageError{natbib} + {The aguplus class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{nlinproc}{\PackageError{natbib} + {The nlinproc class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{egs}{\PackageError{natbib} + {The egs class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} +\@ifclassloaded{egu}{\PackageError{natbib} + {The egu class already includes natbib coding,\MessageBreak + so you should not add it explicitly} + {Type <Return> for now, but then later remove\MessageBreak + the command \protect\usepackage{natbib} from the document} + \endinput}{} + % Define citation punctuation for some author-year styles + % One may add and delete at this point + % Or put additions into local configuration file natbib.cfg +\newcommand\bibstyle@chicago{\bibpunct{(}{)}{;}{a}{,}{,}} +\newcommand\bibstyle@named{\bibpunct{[}{]}{;}{a}{,}{,}} +\newcommand\bibstyle@agu{\bibpunct{[}{]}{;}{a}{,}{,~}}%Amer. Geophys. Union +\newcommand\bibstyle@copernicus{\bibpunct{(}{)}{;}{a}{,}{,}}%Copernicus Publications +\let\bibstyle@egu=\bibstyle@copernicus +\let\bibstyle@egs=\bibstyle@copernicus +\newcommand\bibstyle@agsm{\bibpunct{(}{)}{,}{a}{}{,}\gdef\harvardand{\&}} +\newcommand\bibstyle@kluwer{\bibpunct{(}{)}{,}{a}{}{,}\gdef\harvardand{\&}} +\newcommand\bibstyle@dcu{\bibpunct{(}{)}{;}{a}{;}{,}\gdef\harvardand{and}} +\newcommand\bibstyle@aa{\bibpunct{(}{)}{;}{a}{}{,}} %Astronomy & Astrophysics +\newcommand\bibstyle@pass{\bibpunct{(}{)}{;}{a}{,}{,}}%Planet. & Space Sci +\newcommand\bibstyle@anngeo{\bibpunct{(}{)}{;}{a}{,}{,}}%Annales Geophysicae +\newcommand\bibstyle@nlinproc{\bibpunct{(}{)}{;}{a}{,}{,}}%Nonlin.Proc.Geophys. + % Define citation punctuation for some numerical styles +\newcommand\bibstyle@cospar{\bibpunct{/}{/}{,}{n}{}{}% + \gdef\bibnumfmt##1{##1.}} +\newcommand\bibstyle@esa{\bibpunct{(Ref.~}{)}{,}{n}{}{}% + \gdef\bibnumfmt##1{##1.\hspace{1em}}} +\newcommand\bibstyle@nature{\bibpunct{}{}{,}{s}{}{\textsuperscript{,}}% + \gdef\bibnumfmt##1{##1.}} + % The standard LaTeX styles +\newcommand\bibstyle@plain{\bibpunct{[}{]}{,}{n}{}{,}} +\let\bibstyle@alpha=\bibstyle@plain +\let\bibstyle@abbrv=\bibstyle@plain +\let\bibstyle@unsrt=\bibstyle@plain + % The author-year modifications of the standard styles +\newcommand\bibstyle@plainnat{\bibpunct{[}{]}{,}{a}{,}{,}} +\let\bibstyle@abbrvnat=\bibstyle@plainnat +\let\bibstyle@unsrtnat=\bibstyle@plainnat +\newif\ifNAT@numbers \NAT@numbersfalse +\newif\ifNAT@super \NAT@superfalse +\let\NAT@merge\z@ +\DeclareOption{numbers}{\NAT@numberstrue + \ExecuteOptions{square,comma,nobibstyle}} +\DeclareOption{super}{\NAT@supertrue\NAT@numberstrue + \renewcommand\NAT@open{}\renewcommand\NAT@close{} + \ExecuteOptions{nobibstyle}} +\DeclareOption{authoryear}{\NAT@numbersfalse + \ExecuteOptions{round,semicolon,bibstyle}} +\DeclareOption{round}{% + \renewcommand\NAT@open{(} \renewcommand\NAT@close{)} + \ExecuteOptions{nobibstyle}} +\DeclareOption{square}{% + \renewcommand\NAT@open{[} \renewcommand\NAT@close{]} + \ExecuteOptions{nobibstyle}} +\DeclareOption{angle}{% + \renewcommand\NAT@open{$<$} \renewcommand\NAT@close{$>$} + \ExecuteOptions{nobibstyle}} +\DeclareOption{curly}{% + \renewcommand\NAT@open{\{} \renewcommand\NAT@close{\}} + \ExecuteOptions{nobibstyle}} +\DeclareOption{comma}{\renewcommand\NAT@sep{,} + \ExecuteOptions{nobibstyle}} +\DeclareOption{semicolon}{\renewcommand\NAT@sep{;} + \ExecuteOptions{nobibstyle}} +\DeclareOption{colon}{\ExecuteOptions{semicolon}} +\DeclareOption{nobibstyle}{\let\bibstyle=\@gobble} +\DeclareOption{bibstyle}{\let\bibstyle=\@citestyle} +\newif\ifNAT@openbib \NAT@openbibfalse +\DeclareOption{openbib}{\NAT@openbibtrue} +\DeclareOption{sectionbib}{\def\NAT@sectionbib{on}} +\def\NAT@sort{\z@} +\def\NAT@cmprs{\z@} +\DeclareOption{sort}{\def\NAT@sort{\@ne}} +\DeclareOption{compress}{\def\NAT@cmprs{\@ne}} +\DeclareOption{sort&compress}{\def\NAT@sort{\@ne}\def\NAT@cmprs{\@ne}} +\DeclareOption{mcite}{\let\NAT@merge\@ne} +\DeclareOption{merge}{\@ifnum{\NAT@merge<\tw@}{\let\NAT@merge\tw@}{}} +\DeclareOption{elide}{\@ifnum{\NAT@merge<\thr@@}{\let\NAT@merge\thr@@}{}} +\@ifpackageloaded{cite}{\PackageWarningNoLine{natbib} + {The `cite' package should not be used\MessageBreak + with natbib. Use option `sort' instead}\ExecuteOptions{sort}}{} +\@ifpackageloaded{mcite}{\PackageWarningNoLine{natbib} + {The `mcite' package should not be used\MessageBreak + with natbib. Use option `merge' instead}\ExecuteOptions{merge}}{} +\@ifpackageloaded{citeref}{\PackageError{natbib} + {The `citeref' package must be loaded after natbib}% + {Move \protect\usepackage{citeref} to after \string\usepackage{natbib}}}{} +\newif\ifNAT@longnames\NAT@longnamesfalse +\DeclareOption{longnamesfirst}{\NAT@longnamestrue} +\DeclareOption{nonamebreak}{\def\NAT@nmfmt#1{\mbox{\NAT@up#1}}} +\def\NAT@nmfmt#1{{\NAT@up#1}} +\renewcommand\bibstyle[1]{\csname bibstyle@#1\endcsname} +\AtBeginDocument{\global\let\bibstyle=\@gobble} +\let\@citestyle\bibstyle +\newcommand\citestyle[1]{\@citestyle{#1}\let\bibstyle\@gobble} +\newcommand\bibpunct[7][, ]% + {\gdef\NAT@open{#2}\gdef\NAT@close{#3}\gdef + \NAT@sep{#4}\global\NAT@numbersfalse + \ifx #5n\global\NAT@numberstrue\global\NAT@superfalse + \else + \ifx #5s\global\NAT@numberstrue\global\NAT@supertrue + \fi\fi + \gdef\NAT@aysep{#6}\gdef\NAT@yrsep{#7}% + \gdef\NAT@cmt{#1}% + \NAT@@setcites + } +\newcommand\setcitestyle[1]{ + \@for\@tempa:=#1\do + {\def\@tempb{round}\ifx\@tempa\@tempb + \renewcommand\NAT@open{(}\renewcommand\NAT@close{)}\fi + \def\@tempb{square}\ifx\@tempa\@tempb + \renewcommand\NAT@open{[}\renewcommand\NAT@close{]}\fi + \def\@tempb{angle}\ifx\@tempa\@tempb + \renewcommand\NAT@open{$<$}\renewcommand\NAT@close{$>$}\fi + \def\@tempb{curly}\ifx\@tempa\@tempb + \renewcommand\NAT@open{\{}\renewcommand\NAT@close{\}}\fi + \def\@tempb{semicolon}\ifx\@tempa\@tempb + \renewcommand\NAT@sep{;}\fi + \def\@tempb{colon}\ifx\@tempa\@tempb + \renewcommand\NAT@sep{;}\fi + \def\@tempb{comma}\ifx\@tempa\@tempb + \renewcommand\NAT@sep{,}\fi + \def\@tempb{authoryear}\ifx\@tempa\@tempb + \NAT@numbersfalse\fi + \def\@tempb{numbers}\ifx\@tempa\@tempb + \NAT@numberstrue\NAT@superfalse\fi + \def\@tempb{super}\ifx\@tempa\@tempb + \NAT@numberstrue\NAT@supertrue\fi + \expandafter\NAT@find@eq\@tempa=\relax\@nil + \if\@tempc\relax\else + \expandafter\NAT@rem@eq\@tempc + \def\@tempb{open}\ifx\@tempa\@tempb + \xdef\NAT@open{\@tempc}\fi + \def\@tempb{close}\ifx\@tempa\@tempb + \xdef\NAT@close{\@tempc}\fi + \def\@tempb{aysep}\ifx\@tempa\@tempb + \xdef\NAT@aysep{\@tempc}\fi + \def\@tempb{yysep}\ifx\@tempa\@tempb + \xdef\NAT@yrsep{\@tempc}\fi + \def\@tempb{notesep}\ifx\@tempa\@tempb + \xdef\NAT@cmt{\@tempc}\fi + \def\@tempb{citesep}\ifx\@tempa\@tempb + \xdef\NAT@sep{\@tempc}\fi + \fi + }% + \NAT@@setcites +} + \def\NAT@find@eq#1=#2\@nil{\def\@tempa{#1}\def\@tempc{#2}} + \def\NAT@rem@eq#1={\def\@tempc{#1}} + \def\NAT@@setcites{\global\let\bibstyle\@gobble} +\AtBeginDocument{\let\NAT@@setcites\NAT@set@cites} +\newcommand\NAT@open{(} \newcommand\NAT@close{)} +\newcommand\NAT@sep{;} +\ProcessOptions +\newcommand\NAT@aysep{,} \newcommand\NAT@yrsep{,} +\newcommand\NAT@cmt{, } +\newcommand\NAT@cite% + [3]{\ifNAT@swa\NAT@@open\if*#2*\else#2\NAT@spacechar\fi + #1\if*#3*\else\NAT@cmt#3\fi\NAT@@close\else#1\fi\endgroup} +\newcommand\NAT@citenum% + [3]{\ifNAT@swa\NAT@@open\if*#2*\else#2\NAT@spacechar\fi + #1\if*#3*\else\NAT@cmt#3\fi\NAT@@close\else#1\fi\endgroup} +\newcommand\NAT@citesuper[3]{\ifNAT@swa +\if*#2*\else#2\NAT@spacechar\fi +\unskip\kern\p@\textsuperscript{\NAT@@open#1\NAT@@close}% + \if*#3*\else\NAT@spacechar#3\fi\else #1\fi\endgroup} +\providecommand\textsuperscript[1]{\mbox{$^{\mbox{\scriptsize#1}}$}} +\begingroup \catcode`\_=8 +\gdef\NAT@ifcat@num#1{% + \ifcat_\ifnum\z@<0#1_\else A\fi + \expandafter\@firstoftwo + \else + \expandafter\@secondoftwo + \fi +}% +\endgroup +\providecommand\@firstofone[1]{#1} +\newcommand\NAT@citexnum{} +\def\NAT@citexnum[#1][#2]#3{% + \NAT@reset@parser + \NAT@sort@cites{#3}% + \NAT@reset@citea + \@cite{\def\NAT@num{-1}\let\NAT@last@yr\relax\let\NAT@nm\@empty + \@for\@citeb:=\NAT@cite@list\do + {\@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \@ifundefined{b@\@citeb\@extra@b@citeb}{% + {\reset@font\bfseries?} + \NAT@citeundefined\PackageWarning{natbib}% + {Citation `\@citeb' on page \thepage \space undefined}}% + {\let\NAT@last@num\NAT@num\let\NAT@last@nm\NAT@nm + \NAT@parse{\@citeb}% + \ifNAT@longnames\@ifundefined{bv@\@citeb\@extra@b@citeb}{% + \let\NAT@name=\NAT@all@names + \global\@namedef{bv@\@citeb\@extra@b@citeb}{}}{}% + \fi + \ifNAT@full\let\NAT@nm\NAT@all@names\else + \let\NAT@nm\NAT@name\fi + \ifNAT@swa + \@ifnum{\NAT@ctype>\@ne}{% + \@citea + \NAT@hyper@{\@ifnum{\NAT@ctype=\tw@}{\NAT@test{\NAT@ctype}}{\NAT@alias}}% + }{% + \@ifnum{\NAT@cmprs>\z@}{% + \NAT@ifcat@num\NAT@num + {\let\NAT@nm=\NAT@num}% + {\def\NAT@nm{-2}}% + \NAT@ifcat@num\NAT@last@num + {\@tempcnta=\NAT@last@num\relax}% + {\@tempcnta\m@ne}% + \@ifnum{\NAT@nm=\@tempcnta}{% + \@ifnum{\NAT@merge>\@ne}{}{\NAT@last@yr@mbox}% + }{% + \advance\@tempcnta by\@ne + \@ifnum{\NAT@nm=\@tempcnta}{% + \ifx\NAT@last@yr\relax + \def@NAT@last@yr{\@citea}% + \else + \def@NAT@last@yr{--\NAT@penalty}% + \fi + }{% + \NAT@last@yr@mbox + }% + }% + }{% + \@tempswatrue + \@ifnum{\NAT@merge>\@ne}{\@ifnum{\NAT@last@num=\NAT@num\relax}{\@tempswafalse}{}}{}% + \if@tempswa\NAT@citea@mbox\fi + }% + }% + \NAT@def@citea + \else + \ifcase\NAT@ctype + \ifx\NAT@last@nm\NAT@nm \NAT@yrsep\NAT@penalty\NAT@space\else + \@citea \NAT@test{\@ne}\NAT@spacechar\NAT@mbox{\NAT@super@kern\NAT@@open}% + \fi + \if*#1*\else#1\NAT@spacechar\fi + \NAT@mbox{\NAT@hyper@{{\citenumfont{\NAT@num}}}}% + \NAT@def@citea@box + \or + \NAT@hyper@citea@space{\NAT@test{\NAT@ctype}}% + \or + \NAT@hyper@citea@space{\NAT@test{\NAT@ctype}}% + \or + \NAT@hyper@citea@space\NAT@alias + \fi + \fi + }% + }% + \@ifnum{\NAT@cmprs>\z@}{\NAT@last@yr}{}% + \ifNAT@swa\else + \@ifnum{\NAT@ctype=\z@}{% + \if*#2*\else\NAT@cmt#2\fi + }{}% + \NAT@mbox{\NAT@@close}% + \fi + }{#1}{#2}% +}% +\def\NAT@citea@mbox{% + \@citea\mbox{\NAT@hyper@{{\citenumfont{\NAT@num}}}}% +}% +\def\NAT@hyper@#1{% + \hyper@natlinkstart{\@citeb\@extra@b@citeb}#1\hyper@natlinkend +}% +\def\NAT@hyper@citea#1{% + \@citea + \NAT@hyper@{#1}% + \NAT@def@citea +}% +\def\NAT@hyper@citea@space#1{% + \@citea + \NAT@hyper@{#1}% + \NAT@def@citea@space +}% +\def\def@NAT@last@yr#1{% + \protected@edef\NAT@last@yr{% + #1% + \noexpand\mbox{% + \noexpand\hyper@natlinkstart{\@citeb\@extra@b@citeb}% + {\noexpand\citenumfont{\NAT@num}}% + \noexpand\hyper@natlinkend + }% + }% +}% +\def\NAT@last@yr@mbox{% + \NAT@last@yr\let\NAT@last@yr\relax + \NAT@citea@mbox +}% +\newcommand\NAT@test[1]{% + \@ifnum{#1=\@ne}{% + \ifx\NAT@nm\NAT@noname + \begingroup\reset@font\bfseries(author?)\endgroup + \PackageWarning{natbib}{% + Author undefined for citation`\@citeb' \MessageBreak on page \thepage% + }% + \else \NAT@nm + \fi + }{% + \if\relax\NAT@date\relax + \begingroup\reset@font\bfseries(year?)\endgroup + \PackageWarning{natbib}{% + Year undefined for citation`\@citeb' \MessageBreak on page \thepage% + }% + \else \NAT@date + \fi + }% +}% +\let\citenumfont=\@empty +\newcommand\NAT@citex{} +\def\NAT@citex% + [#1][#2]#3{% + \NAT@reset@parser + \NAT@sort@cites{#3}% + \NAT@reset@citea + \@cite{\let\NAT@nm\@empty\let\NAT@year\@empty + \@for\@citeb:=\NAT@cite@list\do + {\@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \@ifundefined{b@\@citeb\@extra@b@citeb}{\@citea% + {\reset@font\bfseries ?}\NAT@citeundefined + \PackageWarning{natbib}% + {Citation `\@citeb' on page \thepage \space undefined}\def\NAT@date{}}% + {\let\NAT@last@nm=\NAT@nm\let\NAT@last@yr=\NAT@year + \NAT@parse{\@citeb}% + \ifNAT@longnames\@ifundefined{bv@\@citeb\@extra@b@citeb}{% + \let\NAT@name=\NAT@all@names + \global\@namedef{bv@\@citeb\@extra@b@citeb}{}}{}% + \fi + \ifNAT@full\let\NAT@nm\NAT@all@names\else + \let\NAT@nm\NAT@name\fi + \ifNAT@swa\ifcase\NAT@ctype + \if\relax\NAT@date\relax + \@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}\NAT@date}% + \else + \ifx\NAT@last@nm\NAT@nm\NAT@yrsep + \ifx\NAT@last@yr\NAT@year + \def\NAT@temp{{?}}% + \ifx\NAT@temp\NAT@exlab\PackageWarningNoLine{natbib}% + {Multiple citation on page \thepage: same authors and + year\MessageBreak without distinguishing extra + letter,\MessageBreak appears as question mark}\fi + \NAT@hyper@{\NAT@exlab}% + \else\unskip\NAT@spacechar + \NAT@hyper@{\NAT@date}% + \fi + \else + \@citea\NAT@hyper@{% + \NAT@nmfmt{\NAT@nm}% + \hyper@natlinkbreak{% + \NAT@aysep\NAT@spacechar}{\@citeb\@extra@b@citeb + }% + \NAT@date + }% + \fi + \fi + \or\@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}}% + \or\@citea\NAT@hyper@{\NAT@date}% + \or\@citea\NAT@hyper@{\NAT@alias}% + \fi \NAT@def@citea + \else + \ifcase\NAT@ctype + \if\relax\NAT@date\relax + \@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}}% + \else + \ifx\NAT@last@nm\NAT@nm\NAT@yrsep + \ifx\NAT@last@yr\NAT@year + \def\NAT@temp{{?}}% + \ifx\NAT@temp\NAT@exlab\PackageWarningNoLine{natbib}% + {Multiple citation on page \thepage: same authors and + year\MessageBreak without distinguishing extra + letter,\MessageBreak appears as question mark}\fi + \NAT@hyper@{\NAT@exlab}% + \else + \unskip\NAT@spacechar + \NAT@hyper@{\NAT@date}% + \fi + \else + \@citea\NAT@hyper@{% + \NAT@nmfmt{\NAT@nm}% + \hyper@natlinkbreak{\NAT@spacechar\NAT@@open\if*#1*\else#1\NAT@spacechar\fi}% + {\@citeb\@extra@b@citeb}% + \NAT@date + }% + \fi + \fi + \or\@citea\NAT@hyper@{\NAT@nmfmt{\NAT@nm}}% + \or\@citea\NAT@hyper@{\NAT@date}% + \or\@citea\NAT@hyper@{\NAT@alias}% + \fi + \if\relax\NAT@date\relax + \NAT@def@citea + \else + \NAT@def@citea@close + \fi + \fi + }}\ifNAT@swa\else\if*#2*\else\NAT@cmt#2\fi + \if\relax\NAT@date\relax\else\NAT@@close\fi\fi}{#1}{#2}} +\def\NAT@spacechar{\ }% +\def\NAT@separator{\NAT@sep\NAT@penalty}% +\def\NAT@reset@citea{\c@NAT@ctr\@ne\let\@citea\@empty}% +\def\NAT@def@citea{\def\@citea{\NAT@separator\NAT@space}}% +\def\NAT@def@citea@space{\def\@citea{\NAT@separator\NAT@spacechar}}% +\def\NAT@def@citea@close{\def\@citea{\NAT@@close\NAT@separator\NAT@space}}% +\def\NAT@def@citea@box{\def\@citea{\NAT@mbox{\NAT@@close}\NAT@separator\NAT@spacechar}}% +\newif\ifNAT@par \NAT@partrue +\newcommand\NAT@@open{\ifNAT@par\NAT@open\fi} +\newcommand\NAT@@close{\ifNAT@par\NAT@close\fi} +\newcommand\NAT@alias{\@ifundefined{al@\@citeb\@extra@b@citeb}{% + {\reset@font\bfseries(alias?)}\PackageWarning{natbib} + {Alias undefined for citation `\@citeb' + \MessageBreak on page \thepage}}{\@nameuse{al@\@citeb\@extra@b@citeb}}} +\let\NAT@up\relax +\newcommand\NAT@Up[1]{{\let\protect\@unexpandable@protect\let~\relax + \expandafter\NAT@deftemp#1}\expandafter\NAT@UP\NAT@temp} +\newcommand\NAT@deftemp[1]{\xdef\NAT@temp{#1}} +\newcommand\NAT@UP[1]{\let\@tempa\NAT@UP\ifcat a#1\MakeUppercase{#1}% + \let\@tempa\relax\else#1\fi\@tempa} +\newcommand\shortcites[1]{% + \@bsphack\@for\@citeb:=#1\do + {\@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \global\@namedef{bv@\@citeb\@extra@b@citeb}{}}\@esphack} +\newcommand\NAT@biblabel[1]{\hfill} +\newcommand\NAT@biblabelnum[1]{\bibnumfmt{#1}} +\let\bibnumfmt\@empty +\providecommand\@biblabel[1]{[#1]} +\AtBeginDocument{\ifx\bibnumfmt\@empty\let\bibnumfmt\@biblabel\fi} +\newcommand\NAT@bibsetnum[1]{\settowidth\labelwidth{\@biblabel{#1}}% + \setlength{\leftmargin}{\labelwidth}\addtolength{\leftmargin}{\labelsep}% + \setlength{\itemsep}{\bibsep}\setlength{\parsep}{\z@}% + \ifNAT@openbib + \addtolength{\leftmargin}{\bibindent}% + \setlength{\itemindent}{-\bibindent}% + \setlength{\listparindent}{\itemindent}% + \setlength{\parsep}{0pt}% + \fi +} +\newlength{\bibhang} +\setlength{\bibhang}{1em} +\newlength{\bibsep} + {\@listi \global\bibsep\itemsep \global\advance\bibsep by\parsep} + +\newcommand\NAT@bibsetup% + [1]{\setlength{\leftmargin}{\bibhang}\setlength{\itemindent}{-\leftmargin}% + \setlength{\itemsep}{\bibsep}\setlength{\parsep}{\z@}} +\newcommand\NAT@set@cites{% + \ifNAT@numbers + \ifNAT@super \let\@cite\NAT@citesuper + \def\NAT@mbox##1{\unskip\nobreak\textsuperscript{##1}}% + \let\citeyearpar=\citeyear + \let\NAT@space\relax + \def\NAT@super@kern{\kern\p@}% + \else + \let\NAT@mbox=\mbox + \let\@cite\NAT@citenum + \let\NAT@space\NAT@spacechar + \let\NAT@super@kern\relax + \fi + \let\@citex\NAT@citexnum + \let\@biblabel\NAT@biblabelnum + \let\@bibsetup\NAT@bibsetnum + \renewcommand\NAT@idxtxt{\NAT@name\NAT@spacechar\NAT@open\NAT@num\NAT@close}% + \def\natexlab##1{}% + \def\NAT@penalty{\penalty\@m}% + \else + \let\@cite\NAT@cite + \let\@citex\NAT@citex + \let\@biblabel\NAT@biblabel + \let\@bibsetup\NAT@bibsetup + \let\NAT@space\NAT@spacechar + \let\NAT@penalty\@empty + \renewcommand\NAT@idxtxt{\NAT@name\NAT@spacechar\NAT@open\NAT@date\NAT@close}% + \def\natexlab##1{##1}% + \fi} +\AtBeginDocument{\NAT@set@cites} +\AtBeginDocument{\ifx\SK@def\@undefined\else +\ifx\SK@cite\@empty\else + \SK@def\@citex[#1][#2]#3{\SK@\SK@@ref{#3}\SK@@citex[#1][#2]{#3}}\fi +\ifx\SK@citeauthor\@undefined\def\HAR@checkdef{}\else + \let\citeauthor\SK@citeauthor + \let\citefullauthor\SK@citefullauthor + \let\citeyear\SK@citeyear\fi +\fi} +\newif\ifNAT@full\NAT@fullfalse +\newif\ifNAT@swa +\DeclareRobustCommand\citet + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@partrue + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\newcommand\NAT@citetp{\@ifnextchar[{\NAT@@citetp}{\NAT@@citetp[]}} +\newcommand\NAT@@citetp{} +\def\NAT@@citetp[#1]{\@ifnextchar[{\@citex[#1]}{\@citex[][#1]}} +\DeclareRobustCommand\citep + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@partrue + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\cite + {\begingroup\let\NAT@ctype\z@\NAT@partrue\NAT@swatrue + \@ifstar{\NAT@fulltrue\NAT@cites}{\NAT@fullfalse\NAT@cites}} +\newcommand\NAT@cites{\@ifnextchar [{\NAT@@citetp}{% + \ifNAT@numbers\else + \NAT@swafalse + \fi + \NAT@@citetp[]}} +\DeclareRobustCommand\citealt + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@parfalse + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\citealp + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@parfalse + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\citenum + {\begingroup + \NAT@swatrue\let\NAT@ctype\z@\NAT@parfalse\let\textsuperscript\NAT@spacechar + \NAT@citexnum[][]} +\DeclareRobustCommand\citeauthor + {\begingroup\NAT@swafalse\let\NAT@ctype\@ne\NAT@parfalse + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citet + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@partrue + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citep + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@partrue + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citealt + {\begingroup\NAT@swafalse\let\NAT@ctype\z@\NAT@parfalse + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citealp + {\begingroup\NAT@swatrue\let\NAT@ctype\z@\NAT@parfalse + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\Citeauthor + {\begingroup\NAT@swafalse\let\NAT@ctype\@ne\NAT@parfalse + \let\NAT@up\NAT@Up + \@ifstar{\NAT@fulltrue\NAT@citetp}{\NAT@fullfalse\NAT@citetp}} +\DeclareRobustCommand\citeyear + {\begingroup\NAT@swafalse\let\NAT@ctype\tw@\NAT@parfalse\NAT@citetp} +\DeclareRobustCommand\citeyearpar + {\begingroup\NAT@swatrue\let\NAT@ctype\tw@\NAT@partrue\NAT@citetp} +\newcommand\citetext[1]{\NAT@open#1\NAT@close} +\DeclareRobustCommand\citefullauthor + {\citeauthor*} +\newcommand\defcitealias[2]{% + \@ifundefined{al@#1\@extra@b@citeb}{} + {\PackageWarning{natbib}{Overwriting existing alias for citation #1}} + \@namedef{al@#1\@extra@b@citeb}{#2}} +\DeclareRobustCommand\citetalias{\begingroup + \NAT@swafalse\let\NAT@ctype\thr@@\NAT@parfalse\NAT@citetp} +\DeclareRobustCommand\citepalias{\begingroup + \NAT@swatrue\let\NAT@ctype\thr@@\NAT@partrue\NAT@citetp} +\renewcommand\nocite[1]{\@bsphack + \@for\@citeb:=#1\do{% + \@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \if@filesw\immediate\write\@auxout{\string\citation{\@citeb}}\fi + \if*\@citeb\else + \@ifundefined{b@\@citeb\@extra@b@citeb}{% + \NAT@citeundefined \PackageWarning{natbib}% + {Citation `\@citeb' undefined}}{}\fi}% + \@esphack} +\newcommand\NAT@parse[1]{% + \begingroup + \let\protect=\@unexpandable@protect + \let~\relax + \let\active@prefix=\@gobble + \edef\NAT@temp{\csname b@#1\@extra@b@citeb\endcsname}% + \aftergroup\NAT@split + \expandafter + \endgroup + \NAT@temp{}{}{}{}{}@@% + \expandafter\NAT@parse@date\NAT@date??????@@% + \ifciteindex\NAT@index\fi +}% +\def\NAT@split#1#2#3#4#5@@{% + \gdef\NAT@num{#1}\gdef\NAT@name{#3}\gdef\NAT@date{#2}% + \gdef\NAT@all@names{#4}% + \ifx\NAT@num\@empty\gdef\NAT@num{0}\fi + \ifx\NAT@noname\NAT@all@names \gdef\NAT@all@names{#3}\fi +}% +\def\NAT@reset@parser{% + \global\let\NAT@num\@empty + \global\let\NAT@name\@empty + \global\let\NAT@date\@empty + \global\let\NAT@all@names\@empty +}% +\newcommand\NAT@parse@date{} +\def\NAT@parse@date#1#2#3#4#5#6@@{% + \ifnum\the\catcode`#1=11\def\NAT@year{}\def\NAT@exlab{#1}\else + \ifnum\the\catcode`#2=11\def\NAT@year{#1}\def\NAT@exlab{#2}\else + \ifnum\the\catcode`#3=11\def\NAT@year{#1#2}\def\NAT@exlab{#3}\else + \ifnum\the\catcode`#4=11\def\NAT@year{#1#2#3}\def\NAT@exlab{#4}\else + \def\NAT@year{#1#2#3#4}\def\NAT@exlab{{#5}}\fi\fi\fi\fi} +\newcommand\NAT@index{} +\let\NAT@makeindex=\makeindex +\renewcommand\makeindex{\NAT@makeindex + \renewcommand\NAT@index{\@bsphack\begingroup + \def~{\string~}\@wrindex{\NAT@idxtxt}}} +\newcommand\NAT@idxtxt{\NAT@name\NAT@spacechar\NAT@open\NAT@date\NAT@close} +\@ifxundefined\@indexfile{}{\let\NAT@makeindex\relax\makeindex} +\newif\ifciteindex \citeindexfalse +\newcommand\citeindextype{default} +\newcommand\NAT@index@alt{{\let\protect=\noexpand\let~\relax + \xdef\NAT@temp{\NAT@idxtxt}}\expandafter\NAT@exp\NAT@temp\@nil} +\newcommand\NAT@exp{} +\def\NAT@exp#1\@nil{\index[\citeindextype]{#1}} + +\AtBeginDocument{% +\@ifpackageloaded{index}{\let\NAT@index=\NAT@index@alt}{}} +\newcommand\NAT@ifcmd{\futurelet\NAT@temp\NAT@ifxcmd} +\newcommand\NAT@ifxcmd{\ifx\NAT@temp\relax\else\expandafter\NAT@bare\fi} +\def\NAT@bare#1(#2)#3(@)#4\@nil#5{% + \if @#2 + \expandafter\NAT@apalk#1, , \@nil{#5}% + \else + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{#3}{#5}% +\fi +} +\newcommand\NAT@wrout[5]{% +\if@filesw + {\let\protect\noexpand\let~\relax + \immediate + \write\@auxout{\string\bibcite{#5}{{#1}{#2}{{#3}}{{#4}}}}}\fi +\ignorespaces} +\def\NAT@noname{{}} +\renewcommand\bibitem{\@ifnextchar[{\@lbibitem}{\@lbibitem[]}}% +\let\NAT@bibitem@first@sw\@secondoftwo +\def\@lbibitem[#1]#2{% + \if\relax\@extra@b@citeb\relax\else + \@ifundefined{br@#2\@extra@b@citeb}{}{% + \@namedef{br@#2}{\@nameuse{br@#2\@extra@b@citeb}}% + }% + \fi + \@ifundefined{b@#2\@extra@b@citeb}{% + \def\NAT@num{}% + }{% + \NAT@parse{#2}% + }% + \def\NAT@tmp{#1}% + \expandafter\let\expandafter\bibitemOpen\csname NAT@b@open@#2\endcsname + \expandafter\let\expandafter\bibitemShut\csname NAT@b@shut@#2\endcsname + \@ifnum{\NAT@merge>\@ne}{% + \NAT@bibitem@first@sw{% + \@firstoftwo + }{% + \@ifundefined{NAT@b*@#2}{% + \@firstoftwo + }{% + \expandafter\def\expandafter\NAT@num\expandafter{\the\c@NAT@ctr}% + \@secondoftwo + }% + }% + }{% + \@firstoftwo + }% + {% + \global\advance\c@NAT@ctr\@ne + \@ifx{\NAT@tmp\@empty}{\@firstoftwo}{% + \@secondoftwo + }% + {% + \expandafter\def\expandafter\NAT@num\expandafter{\the\c@NAT@ctr}% + \global\NAT@stdbsttrue + }{}% + \bibitem@fin + \item[\hfil\NAT@anchor{#2}{\NAT@num}]% + \global\let\NAT@bibitem@first@sw\@secondoftwo + \NAT@bibitem@init + }% + {% + \NAT@anchor{#2}{}% + \NAT@bibitem@cont + \bibitem@fin + }% + \@ifx{\NAT@tmp\@empty}{% + \NAT@wrout{\the\c@NAT@ctr}{}{}{}{#2}% + }{% + \expandafter\NAT@ifcmd\NAT@tmp(@)(@)\@nil{#2}% + }% +}% +\def\bibitem@fin{% + \@ifxundefined\@bibstop{}{\csname bibitem@\@bibstop\endcsname}% +}% +\def\NAT@bibitem@init{% + \let\@bibstop\@undefined +}% +\def\NAT@bibitem@cont{% + \let\bibitem@Stop\bibitemStop + \let\bibitem@NoStop\bibitemContinue +}% +\def\BibitemOpen{% + \bibitemOpen +}% +\def\BibitemShut#1{% + \bibitemShut + \def\@bibstop{#1}% + \let\bibitem@Stop\bibitemStop + \let\bibitem@NoStop\bibitemNoStop +}% +\def\bibitemStop{}% +\def\bibitemNoStop{.\spacefactor\@mmm\space}% +\def\bibitemContinue{\spacefactor\@mmm\space}% +\mathchardef\@mmm=3000 % +\providecommand{\bibAnnote}[3]{% + \BibitemShut{#1}% + \def\@tempa{#3}\@ifx{\@tempa\@empty}{}{% + \begin{quotation}\noindent + \textsc{Key:}\ #2\\\textsc{Annotation:}\ \@tempa + \end{quotation}% + }% +}% +\providecommand{\bibAnnoteFile}[2]{% + \IfFileExists{#2}{% + \bibAnnote{#1}{#2}{\input{#2}}% + }{% + \bibAnnote{#1}{#2}{}% + }% +}% +\let\bibitemOpen\relax +\let\bibitemShut\relax +\def\bibfield{\@ifnum{\NAT@merge>\tw@}{\@bibfield}{\@secondoftwo}}% +\def\@bibfield#1#2{% + \begingroup + \let\Doi\@gobble + \let\bibinfo\relax + \let\restore@protect\@empty + \protected@edef\@tempa{#2}% + \aftergroup\def\aftergroup\@tempa + \expandafter\endgroup\expandafter{\@tempa}% + \expandafter\@ifx\expandafter{\csname @bib#1\endcsname\@tempa}{% + \expandafter\let\expandafter\@tempa\csname @bib@X#1\endcsname + }{% + \expandafter\let\csname @bib#1\endcsname\@tempa + \expandafter\let\expandafter\@tempa\csname @bib@Y#1\endcsname + }% + \@ifx{\@tempa\relax}{\let\@tempa\@firstofone}{}% + \@tempa{#2}% +}% +\def\bibinfo#1{% + \expandafter\let\expandafter\@tempa\csname bibinfo@X@#1\endcsname + \@ifx{\@tempa\relax}{\@firstofone}{\@tempa}% +}% +\def\@bib@Xauthor#1{\let\@bib@Xjournal\@gobble}% +\def\@bib@Xjournal#1{\begingroup\let\bibinfo@X@journal\@bib@Z@journal#1\endgroup}% +\def\@bibibid@#1{\textit{ibid}.}% +\appdef\NAT@bibitem@init{% + \let\@bibauthor \@empty + \let\@bibjournal \@empty + \let\@bib@Z@journal\@bibibid@ +}% +\ifx\SK@lbibitem\@undefined\else + \let\SK@lbibitem\@lbibitem + \def\@lbibitem[#1]#2{% + \SK@lbibitem[#1]{#2}\SK@\SK@@label{#2}\ignorespaces}\fi +\newif\ifNAT@stdbst \NAT@stdbstfalse + +\AtEndDocument{% + \ifNAT@stdbst\if@filesw + \immediate\write\@auxout{% + \string\providecommand\string\NAT@force@numbers{}% + \string\NAT@force@numbers + }% + \fi\fi + } +\newcommand\NAT@force@numbers{% + \ifNAT@numbers\else + \PackageError{natbib}{Bibliography not compatible with author-year + citations.\MessageBreak + Press <return> to continue in numerical citation style} + {Check the bibliography entries for non-compliant syntax,\MessageBreak + or select author-year BibTeX style, e.g. plainnat}% + \global\NAT@numberstrue\fi} + +\providecommand\bibcite{} +\renewcommand\bibcite[2]{% + \@ifundefined{b@#1\@extra@binfo}{\relax}{% + \NAT@citemultiple + \PackageWarningNoLine{natbib}{Citation `#1' multiply defined}% + }% + \global\@namedef{b@#1\@extra@binfo}{#2}% +}% +\AtEndDocument{\NAT@swatrue\let\bibcite\NAT@testdef} +\newcommand\NAT@testdef[2]{% + \def\NAT@temp{#2}% + \expandafter \ifx \csname b@#1\@extra@binfo\endcsname\NAT@temp + \else + \ifNAT@swa \NAT@swafalse + \PackageWarningNoLine{natbib}{% + Citation(s) may have changed.\MessageBreak + Rerun to get citations correct% + }% + \fi + \fi +}% +\newcommand\NAT@apalk{} +\def\NAT@apalk#1, #2, #3\@nil#4{% + \if\relax#2\relax + \global\NAT@stdbsttrue + \NAT@wrout{#1}{}{}{}{#4}% + \else + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{}{#4}% + \fi +}% +\newcommand\citeauthoryear{} +\def\citeauthoryear#1#2#3(@)(@)\@nil#4{% + \if\relax#3\relax + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{}{#4}% + \else + \NAT@wrout{\the\c@NAT@ctr}{#3}{#2}{#1}{#4}% + \fi +}% +\newcommand\citestarts{\NAT@open}% +\newcommand\citeends{\NAT@close}% +\newcommand\betweenauthors{and}% +\newcommand\astroncite{} +\def\astroncite#1#2(@)(@)\@nil#3{% + \NAT@wrout{\the\c@NAT@ctr}{#2}{#1}{}{#3}% +}% +\newcommand\citename{} +\def\citename#1#2(@)(@)\@nil#3{\expandafter\NAT@apalk#1#2, \@nil{#3}} +\newcommand\harvarditem[4][]{% + \if\relax#1\relax + \bibitem[#2(#3)]{#4}% + \else + \bibitem[#1(#3)#2]{#4}% + \fi +}% +\newcommand\harvardleft{\NAT@open} +\newcommand\harvardright{\NAT@close} +\newcommand\harvardyearleft{\NAT@open} +\newcommand\harvardyearright{\NAT@close} +\AtBeginDocument{\providecommand{\harvardand}{and}} +\newcommand\harvardurl[1]{\textbf{URL:} \textit{#1}} +\providecommand\bibsection{} +\@ifundefined{chapter}{% + \renewcommand\bibsection{% + \section*{\refname\@mkboth{\MakeUppercase{\refname}}{\MakeUppercase{\refname}}}% + }% +}{% + \@ifxundefined\NAT@sectionbib{% + \renewcommand\bibsection{% + \chapter*{\bibname\@mkboth{\MakeUppercase{\bibname}}{\MakeUppercase{\bibname}}}% + }% + }{% + \renewcommand\bibsection{% + \section*{\bibname\ifx\@mkboth\@gobbletwo\else\markright{\MakeUppercase{\bibname}}\fi}% + }% + }% +}% +\@ifclassloaded{amsart}{\renewcommand\bibsection{\section*{\refname}}}{}% +\@ifclassloaded{amsbook}{\renewcommand\bibsection{\chapter*{\bibname}}}{}% +\@ifxundefined\bib@heading{}{\let\bibsection\bib@heading}% +\newcounter{NAT@ctr} +\renewenvironment{thebibliography}[1]{% + \bibsection + \parindent\z@ + \bibpreamble + \bibfont + \list{\@biblabel{\the\c@NAT@ctr}}{\@bibsetup{#1}\global\c@NAT@ctr\z@}% + \ifNAT@openbib + \renewcommand\newblock{\par}% + \else + \renewcommand\newblock{\hskip .11em \@plus.33em \@minus.07em}% + \fi + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.\@m + \let\NAT@bibitem@first@sw\@firstoftwo + \let\citeN\cite \let\shortcite\cite + \let\citeasnoun\cite +}{% + \bibitem@fin + \bibpostamble + \def\@noitemerr{% + \PackageWarning{natbib}{Empty `thebibliography' environment}% + }% + \endlist + \bibcleanup +}% +\let\bibfont\@empty +\let\bibpreamble\@empty +\let\bibpostamble\@empty +\def\bibcleanup{\vskip-\lastskip}% +\providecommand\reset@font{\relax} +\providecommand\bibname{Bibliography} +\providecommand\refname{References} +\newcommand\NAT@citeundefined{\gdef \NAT@undefined {% + \PackageWarningNoLine{natbib}{There were undefined citations}}} +\let \NAT@undefined \relax +\newcommand\NAT@citemultiple{\gdef \NAT@multiple {% + \PackageWarningNoLine{natbib}{There were multiply defined citations}}} +\let \NAT@multiple \relax +\AtEndDocument{\NAT@undefined\NAT@multiple} +\providecommand\@mkboth[2]{} +\providecommand\MakeUppercase{\uppercase} +\providecommand{\@extra@b@citeb}{} +\gdef\@extra@binfo{} +\def\NAT@anchor#1#2{% + \hyper@natanchorstart{#1\@extra@b@citeb}% + \def\@tempa{#2}\@ifx{\@tempa\@empty}{}{\@biblabel{#2}}% + \hyper@natanchorend +}% +\providecommand\hyper@natanchorstart[1]{}% +\providecommand\hyper@natanchorend{}% +\providecommand\hyper@natlinkstart[1]{}% +\providecommand\hyper@natlinkend{}% +\providecommand\hyper@natlinkbreak[2]{#1}% +\AtBeginDocument{% + \@ifpackageloaded{babel}{% + \let\org@@citex\@citex}{}} +\providecommand\@safe@activestrue{}% +\providecommand\@safe@activesfalse{}% + +\newcommand\NAT@sort@cites[1]{% + \let\NAT@cite@list\@empty + \@for\@citeb:=#1\do{\expandafter\NAT@star@cite\@citeb\@@}% + \if@filesw + \expandafter\immediate\expandafter\write\expandafter\@auxout + \expandafter{\expandafter\string\expandafter\citation\expandafter{\NAT@cite@list}}% + \fi + \@ifnum{\NAT@sort>\z@}{% + \expandafter\NAT@sort@cites@\expandafter{\NAT@cite@list}% + }{}% +}% +\def\NAT@star@cite{% + \let\NAT@star@sw\@secondoftwo + \@ifnum{\NAT@merge>\z@}{% + \@ifnextchar*{% + \let\NAT@star@sw\@firstoftwo + \NAT@star@cite@star + }{% + \NAT@star@cite@nostar + }% + }{% + \NAT@star@cite@noextension + }% +}% +\def\NAT@star@cite@star*{% + \NAT@star@cite@nostar +}% +\def\NAT@star@cite@nostar{% + \let\nat@keyopt@open\@empty + \let\nat@keyopt@shut\@empty + \@ifnextchar[{\NAT@star@cite@pre}{\NAT@star@cite@pre[]}% +}% +\def\NAT@star@cite@pre[#1]{% + \def\nat@keyopt@open{#1}% + \@ifnextchar[{\NAT@star@cite@post}{\NAT@star@cite@post[]}% +}% +\def\NAT@star@cite@post[#1]#2\@@{% + \def\nat@keyopt@shut{#1}% + \NAT@star@sw{\expandafter\global\expandafter\let\csname NAT@b*@#2\endcsname\@empty}{}% + \NAT@cite@list@append{#2}% +}% +\def\NAT@star@cite@noextension#1\@@{% + \let\nat@keyopt@open\@empty + \let\nat@keyopt@shut\@empty + \NAT@cite@list@append{#1}% +}% +\def\NAT@cite@list@append#1{% + \edef\@citeb{\@firstofone#1\@empty}% + \if@filesw\@ifxundefined\@cprwrite{}{\expandafter\@cprwrite\@citeb=}\fi + \if\relax\nat@keyopt@open\relax\else + \global\expandafter\let\csname NAT@b@open@\@citeb\endcsname\nat@keyopt@open + \fi + \if\relax\nat@keyopt@shut\relax\else + \global\expandafter\let\csname NAT@b@shut@\@citeb\endcsname\nat@keyopt@shut + \fi + \toks@\expandafter{\NAT@cite@list}% + \ifx\NAT@cite@list\@empty + \@temptokena\expandafter{\@citeb}% + \else + \@temptokena\expandafter{\expandafter,\@citeb}% + \fi + \edef\NAT@cite@list{\the\toks@\the\@temptokena}% +}% +\newcommand\NAT@sort@cites@[1]{% + \count@\z@ + \@tempcntb\m@ne + \let\@celt\delimiter + \def\NAT@num@list{}% + \let\NAT@cite@list\@empty + \let\NAT@nonsort@list\@empty + \@for \@citeb:=#1\do{\NAT@make@cite@list}% + \ifx\NAT@nonsort@list\@empty\else + \protected@edef\NAT@cite@list{\NAT@cite@list\NAT@nonsort@list}% + \fi + \ifx\NAT@cite@list\@empty\else + \protected@edef\NAT@cite@list{\expandafter\NAT@xcom\NAT@cite@list @@}% + \fi +}% +\def\NAT@make@cite@list{% + \advance\count@\@ne + \@safe@activestrue + \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% + \@safe@activesfalse + \@ifundefined{b@\@citeb\@extra@b@citeb}% + {\def\NAT@num{A}}% + {\NAT@parse{\@citeb}}% + \NAT@ifcat@num\NAT@num + {\@tempcnta\NAT@num \relax + \@ifnum{\@tempcnta<\@tempcntb}{% + \let\NAT@@cite@list=\NAT@cite@list + \let\NAT@cite@list\@empty + \begingroup\let\@celt=\NAT@celt\NAT@num@list\endgroup + \protected@edef\NAT@num@list{% + \expandafter\NAT@num@celt \NAT@num@list \@gobble @% + }% + }{% + \protected@edef\NAT@num@list{\NAT@num@list \@celt{\NAT@num}}% + \protected@edef\NAT@cite@list{\NAT@cite@list\@citeb,}% + \@tempcntb\@tempcnta + }% + }% + {\protected@edef\NAT@nonsort@list{\NAT@nonsort@list\@citeb,}}% +}% +\def\NAT@celt#1{% + \@ifnum{#1>\@tempcnta}{% + \xdef\NAT@cite@list{\NAT@cite@list\@citeb,\NAT@@cite@list}% + \let\@celt\@gobble + }{% + \expandafter\def@NAT@cite@lists\NAT@@cite@list\@@ + }% +}% +\def\NAT@num@celt#1#2{% + \ifx#1\@celt + \@ifnum{#2>\@tempcnta}{% + \@celt{\number\@tempcnta}% + \@celt{#2}% + }{% + \@celt{#2}% + \expandafter\NAT@num@celt + }% + \fi +}% +\def\def@NAT@cite@lists#1,#2\@@{% + \xdef\NAT@cite@list{\NAT@cite@list#1,}% + \xdef\NAT@@cite@list{#2}% +}% +\def\NAT@nextc#1,#2@@{#1,} +\def\NAT@restc#1,#2{#2} +\def\NAT@xcom#1,@@{#1} +\InputIfFileExists{natbib.cfg} + {\typeout{Local config file natbib.cfg used}}{} +%% +%% <<<<< End of generated file <<<<<< +%% +%% End of file `natbib.sty'. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/algorithm.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/algorithm.sty new file mode 100644 index 0000000..843e3d5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/algorithm.sty @@ -0,0 +1,79 @@ +% ALGORITHM STYLE -- Released 8 April 1996 +% for LaTeX-2e +% Copyright -- 1994 Peter Williams +% E-mail Peter.Williams@dsto.defence.gov.au +\NeedsTeXFormat{LaTeX2e} +\ProvidesPackage{algorithm} +\typeout{Document Style `algorithm' - floating environment} + +\RequirePackage{float} +\RequirePackage{ifthen} +\newcommand{\ALG@within}{nothing} +\newboolean{ALG@within} +\setboolean{ALG@within}{false} +\newcommand{\ALG@floatstyle}{ruled} +\newcommand{\ALG@name}{Algorithm} +\newcommand{\listalgorithmname}{List of \ALG@name s} + +% Declare Options +% first appearance +\DeclareOption{plain}{ + \renewcommand{\ALG@floatstyle}{plain} +} +\DeclareOption{ruled}{ + \renewcommand{\ALG@floatstyle}{ruled} +} +\DeclareOption{boxed}{ + \renewcommand{\ALG@floatstyle}{boxed} +} +% then numbering convention +\DeclareOption{part}{ + \renewcommand{\ALG@within}{part} + \setboolean{ALG@within}{true} +} +\DeclareOption{chapter}{ + \renewcommand{\ALG@within}{chapter} + \setboolean{ALG@within}{true} +} +\DeclareOption{section}{ + \renewcommand{\ALG@within}{section} + \setboolean{ALG@within}{true} +} +\DeclareOption{subsection}{ + \renewcommand{\ALG@within}{subsection} + \setboolean{ALG@within}{true} +} +\DeclareOption{subsubsection}{ + \renewcommand{\ALG@within}{subsubsection} + \setboolean{ALG@within}{true} +} +\DeclareOption{nothing}{ + \renewcommand{\ALG@within}{nothing} + \setboolean{ALG@within}{true} +} +\DeclareOption*{\edef\ALG@name{\CurrentOption}} + +% ALGORITHM +% +\ProcessOptions +\floatstyle{\ALG@floatstyle} +\ifthenelse{\boolean{ALG@within}}{ + \ifthenelse{\equal{\ALG@within}{part}} + {\newfloat{algorithm}{htbp}{loa}[part]}{} + \ifthenelse{\equal{\ALG@within}{chapter}} + {\newfloat{algorithm}{htbp}{loa}[chapter]}{} + \ifthenelse{\equal{\ALG@within}{section}} + {\newfloat{algorithm}{htbp}{loa}[section]}{} + \ifthenelse{\equal{\ALG@within}{subsection}} + {\newfloat{algorithm}{htbp}{loa}[subsection]}{} + \ifthenelse{\equal{\ALG@within}{subsubsection}} + {\newfloat{algorithm}{htbp}{loa}[subsubsection]}{} + \ifthenelse{\equal{\ALG@within}{nothing}} + {\newfloat{algorithm}{htbp}{loa}}{} +}{ + \newfloat{algorithm}{htbp}{loa} +} +\floatname{algorithm}{\ALG@name} + +\newcommand{\listofalgorithms}{\listof{algorithm}{\listalgorithmname}} + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/algorithmic.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/algorithmic.sty new file mode 100644 index 0000000..ad61478 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/algorithmic.sty @@ -0,0 +1,201 @@ +% ALGORITHMIC STYLE -- Released 8 APRIL 1996 +% for LaTeX version 2e +% Copyright -- 1994 Peter Williams +% E-mail PeterWilliams@dsto.defence.gov.au +% +% Modified by Alex Smola (08/2000) +% E-mail Alex.Smola@anu.edu.au +% +\NeedsTeXFormat{LaTeX2e} +\ProvidesPackage{algorithmic} +\typeout{Document Style `algorithmic' - environment} +% +\RequirePackage{ifthen} +\RequirePackage{calc} +\newboolean{ALC@noend} +\setboolean{ALC@noend}{false} +\newcounter{ALC@line} +\newcounter{ALC@rem} +\newlength{\ALC@tlm} +% +\DeclareOption{noend}{\setboolean{ALC@noend}{true}} +% +\ProcessOptions +% +% ALGORITHMIC +\newcommand{\algorithmicrequire}{\textbf{Require:}} +\newcommand{\algorithmicensure}{\textbf{Ensure:}} +\newcommand{\algorithmiccomment}[1]{\{#1\}} +\newcommand{\algorithmicend}{\textbf{end}} +\newcommand{\algorithmicif}{\textbf{if}} +\newcommand{\algorithmicthen}{\textbf{then}} +\newcommand{\algorithmicelse}{\textbf{else}} +\newcommand{\algorithmicelsif}{\algorithmicelse\ \algorithmicif} +\newcommand{\algorithmicendif}{\algorithmicend\ \algorithmicif} +\newcommand{\algorithmicfor}{\textbf{for}} +\newcommand{\algorithmicforall}{\textbf{for all}} +\newcommand{\algorithmicdo}{\textbf{do}} +\newcommand{\algorithmicendfor}{\algorithmicend\ \algorithmicfor} +\newcommand{\algorithmicwhile}{\textbf{while}} +\newcommand{\algorithmicendwhile}{\algorithmicend\ \algorithmicwhile} +\newcommand{\algorithmicloop}{\textbf{loop}} +\newcommand{\algorithmicendloop}{\algorithmicend\ \algorithmicloop} +\newcommand{\algorithmicrepeat}{\textbf{repeat}} +\newcommand{\algorithmicuntil}{\textbf{until}} + +%changed by alex smola +\newcommand{\algorithmicinput}{\textbf{input}} +\newcommand{\algorithmicoutput}{\textbf{output}} +\newcommand{\algorithmicset}{\textbf{set}} +\newcommand{\algorithmictrue}{\textbf{true}} +\newcommand{\algorithmicfalse}{\textbf{false}} +\newcommand{\algorithmicand}{\textbf{and\ }} +\newcommand{\algorithmicor}{\textbf{or\ }} +\newcommand{\algorithmicfunction}{\textbf{function}} +\newcommand{\algorithmicendfunction}{\algorithmicend\ \algorithmicfunction} +\newcommand{\algorithmicmain}{\textbf{main}} +\newcommand{\algorithmicendmain}{\algorithmicend\ \algorithmicmain} +%end changed by alex smola + +\def\ALC@item[#1]{% +\if@noparitem \@donoparitem + \else \if@inlabel \indent \par \fi + \ifhmode \unskip\unskip \par \fi + \if@newlist \if@nobreak \@nbitem \else + \addpenalty\@beginparpenalty + \addvspace\@topsep \addvspace{-\parskip}\fi + \else \addpenalty\@itempenalty \addvspace\itemsep + \fi + \global\@inlabeltrue +\fi +\everypar{\global\@minipagefalse\global\@newlistfalse + \if@inlabel\global\@inlabelfalse \hskip -\parindent \box\@labels + \penalty\z@ \fi + \everypar{}}\global\@nobreakfalse +\if@noitemarg \@noitemargfalse \if@nmbrlist \refstepcounter{\@listctr}\fi \fi +\sbox\@tempboxa{\makelabel{#1}}% +\global\setbox\@labels + \hbox{\unhbox\@labels \hskip \itemindent + \hskip -\labelwidth \hskip -\ALC@tlm + \ifdim \wd\@tempboxa >\labelwidth + \box\@tempboxa + \else \hbox to\labelwidth {\unhbox\@tempboxa}\fi + \hskip \ALC@tlm}\ignorespaces} +% +\newenvironment{algorithmic}[1][0]{ +\let\@item\ALC@item + \newcommand{\ALC@lno}{% +\ifthenelse{\equal{\arabic{ALC@rem}}{0}} +{{\footnotesize \arabic{ALC@line}:}}{}% +} +\let\@listii\@listi +\let\@listiii\@listi +\let\@listiv\@listi +\let\@listv\@listi +\let\@listvi\@listi +\let\@listvii\@listi + \newenvironment{ALC@g}{ + \begin{list}{\ALC@lno}{ \itemsep\z@ \itemindent\z@ + \listparindent\z@ \rightmargin\z@ + \topsep\z@ \partopsep\z@ \parskip\z@\parsep\z@ + \leftmargin 1em + \addtolength{\ALC@tlm}{\leftmargin} + } + } + {\end{list}} + \newcommand{\ALC@it}{\addtocounter{ALC@line}{1}\addtocounter{ALC@rem}{1}\ifthenelse{\equal{\arabic{ALC@rem}}{#1}}{\setcounter{ALC@rem}{0}}{}\item} + \newcommand{\ALC@com}[1]{\ifthenelse{\equal{##1}{default}}% +{}{\ \algorithmiccomment{##1}}} + \newcommand{\REQUIRE}{\item[\algorithmicrequire]} + \newcommand{\ENSURE}{\item[\algorithmicensure]} + \newcommand{\STATE}{\ALC@it} + \newcommand{\COMMENT}[1]{\algorithmiccomment{##1}} +%changes by alex smola + \newcommand{\INPUT}{\item[\algorithmicinput]} + \newcommand{\OUTPUT}{\item[\algorithmicoutput]} + \newcommand{\SET}{\item[\algorithmicset]} +% \newcommand{\TRUE}{\algorithmictrue} +% \newcommand{\FALSE}{\algorithmicfalse} + \newcommand{\AND}{\algorithmicand} + \newcommand{\OR}{\algorithmicor} + \newenvironment{ALC@func}{\begin{ALC@g}}{\end{ALC@g}} + \newenvironment{ALC@main}{\begin{ALC@g}}{\end{ALC@g}} +%end changes by alex smola + \newenvironment{ALC@if}{\begin{ALC@g}}{\end{ALC@g}} + \newenvironment{ALC@for}{\begin{ALC@g}}{\end{ALC@g}} + \newenvironment{ALC@whl}{\begin{ALC@g}}{\end{ALC@g}} + \newenvironment{ALC@loop}{\begin{ALC@g}}{\end{ALC@g}} + \newenvironment{ALC@rpt}{\begin{ALC@g}}{\end{ALC@g}} + \renewcommand{\\}{\@centercr} + \newcommand{\IF}[2][default]{\ALC@it\algorithmicif\ ##2\ \algorithmicthen% +\ALC@com{##1}\begin{ALC@if}} + \newcommand{\SHORTIF}[2]{\ALC@it\algorithmicif\ ##1\ + \algorithmicthen\ {##2}} + \newcommand{\ELSE}[1][default]{\end{ALC@if}\ALC@it\algorithmicelse% +\ALC@com{##1}\begin{ALC@if}} + \newcommand{\ELSIF}[2][default]% +{\end{ALC@if}\ALC@it\algorithmicelsif\ ##2\ \algorithmicthen% +\ALC@com{##1}\begin{ALC@if}} + \newcommand{\FOR}[2][default]{\ALC@it\algorithmicfor\ ##2\ \algorithmicdo% +\ALC@com{##1}\begin{ALC@for}} + \newcommand{\FORALL}[2][default]{\ALC@it\algorithmicforall\ ##2\ % +\algorithmicdo% +\ALC@com{##1}\begin{ALC@for}} + \newcommand{\SHORTFORALL}[2]{\ALC@it\algorithmicforall\ ##1\ % + \algorithmicdo\ {##2}} + \newcommand{\WHILE}[2][default]{\ALC@it\algorithmicwhile\ ##2\ % +\algorithmicdo% +\ALC@com{##1}\begin{ALC@whl}} + \newcommand{\LOOP}[1][default]{\ALC@it\algorithmicloop% +\ALC@com{##1}\begin{ALC@loop}} +%changed by alex smola + \newcommand{\FUNCTION}[2][default]{\ALC@it\algorithmicfunction\ ##2\ % + \ALC@com{##1}\begin{ALC@func}} + \newcommand{\MAIN}[2][default]{\ALC@it\algorithmicmain\ ##2\ % + \ALC@com{##1}\begin{ALC@main}} +%end changed by alex smola + \newcommand{\REPEAT}[1][default]{\ALC@it\algorithmicrepeat% + \ALC@com{##1}\begin{ALC@rpt}} + \newcommand{\UNTIL}[1]{\end{ALC@rpt}\ALC@it\algorithmicuntil\ ##1} + \ifthenelse{\boolean{ALC@noend}}{ + \newcommand{\ENDIF}{\end{ALC@if}} + \newcommand{\ENDFOR}{\end{ALC@for}} + \newcommand{\ENDWHILE}{\end{ALC@whl}} + \newcommand{\ENDLOOP}{\end{ALC@loop}} + \newcommand{\ENDFUNCTION}{\end{ALC@func}} + \newcommand{\ENDMAIN}{\end{ALC@main}} + }{ + \newcommand{\ENDIF}{\end{ALC@if}\ALC@it\algorithmicendif} + \newcommand{\ENDFOR}{\end{ALC@for}\ALC@it\algorithmicendfor} + \newcommand{\ENDWHILE}{\end{ALC@whl}\ALC@it\algorithmicendwhile} + \newcommand{\ENDLOOP}{\end{ALC@loop}\ALC@it\algorithmicendloop} + \newcommand{\ENDFUNCTION}{\end{ALC@func}\ALC@it\algorithmicendfunction} + \newcommand{\ENDMAIN}{\end{ALC@main}\ALC@it\algorithmicendmain} + } + \renewcommand{\@toodeep}{} + \begin{list}{\ALC@lno}{\setcounter{ALC@line}{0}\setcounter{ALC@rem}{0}% + \itemsep\z@ \itemindent\z@ \listparindent\z@% + \partopsep\z@ \parskip\z@ \parsep\z@% + \labelsep 0.5em \topsep 0.2em% + \ifthenelse{\equal{#1}{0}} + {\labelwidth 0.5em } + {\labelwidth 1.2em } + \leftmargin\labelwidth \addtolength{\leftmargin}{\labelsep} + \ALC@tlm\labelsep + } + } + {\end{list}} + + + + + + + + + + + + + + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/example_paper.bib b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/example_paper.bib new file mode 100644 index 0000000..ac29a99 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/example_paper.bib @@ -0,0 +1,75 @@ +@inproceedings{langley00, + author = {P. Langley}, + title = {Crafting Papers on Machine Learning}, + year = {2000}, + pages = {1207--1216}, + editor = {Pat Langley}, + booktitle = {Proceedings of the 17th International Conference + on Machine Learning (ICML 2000)}, + address = {Stanford, CA}, + publisher = {Morgan Kaufmann} +} + +@TechReport{mitchell80, + author = "T. M. Mitchell", + title = "The Need for Biases in Learning Generalizations", + institution = "Computer Science Department, Rutgers University", + year = "1980", + address = "New Brunswick, MA", +} + +@phdthesis{kearns89, + author = {M. J. Kearns}, + title = {Computational Complexity of Machine Learning}, + school = {Department of Computer Science, Harvard University}, + year = {1989} +} + +@Book{MachineLearningI, + editor = "R. S. Michalski and J. G. Carbonell and T. + M. Mitchell", + title = "Machine Learning: An Artificial Intelligence + Approach, Vol. I", + publisher = "Tioga", + year = "1983", + address = "Palo Alto, CA" +} + +@Book{DudaHart2nd, + author = "R. O. Duda and P. E. Hart and D. G. Stork", + title = "Pattern Classification", + publisher = "John Wiley and Sons", + edition = "2nd", + year = "2000" +} + +@misc{anonymous, + title= {Suppressed for Anonymity}, + author= {Author, N. N.}, + year= {2021} +} + +@InCollection{Newell81, + author = "A. Newell and P. S. Rosenbloom", + title = "Mechanisms of Skill Acquisition and the Law of + Practice", + booktitle = "Cognitive Skills and Their Acquisition", + pages = "1--51", + publisher = "Lawrence Erlbaum Associates, Inc.", + year = "1981", + editor = "J. R. Anderson", + chapter = "1", + address = "Hillsdale, NJ" +} + + +@Article{Samuel59, + author = "A. L. Samuel", + title = "Some Studies in Machine Learning Using the Game of + Checkers", + journal = "IBM Journal of Research and Development", + year = "1959", + volume = "3", + number = "3", + pages = "211--229" +} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/example_paper.pdf b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/example_paper.pdf new file mode 100644 index 0000000000000000000000000000000000000000..26dc1b8d7f4d3ec1a09d7b7be1d1d7171bcd178c GIT binary patch literal 193509 zcma&NQ;;T15T^UJZQHhO+qP|M+TGKbwr$(CZQHiF|L&fP6R~@-6;TmyW<}*~Wj>Wj zrYI^-$3)KtO*XeQyavrh$Vlj5Yz@uJ3(X*FW^dtYNyy5?#!mRZ7Bqvnm949pGa-Yx zt&yvlsF{g_sTnjsKeUUhvzd_{wC6^#woYQ^7}}rL+Buyx>Pk5S%RZ^%gXfKyM7IM^ zie$O#8;}Id2+TnAI17qi{?jL}e*sqiRHT-d%B()z?RVQ*iS?jfSFhWF{Bw8sK2KiO zqgs_W)aacnuP$Efi;?3=t&=B2%TT@DD+vlYV;uhUd@oY#R~MstF}qJ{c^q`AwdsU+ z%C+%8Iam!AE;@Rk-^>JWGsAmK?n#-ZNn@2Lhm|KuweiRn%MMaNsZb57Rxl=0)5@Tg 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SUBMISSION FILE %%%%%%%%%%%%%%%%% + +\documentclass{article} + +% Recommended, but optional, packages for figures and better typesetting: +\usepackage{microtype} +\usepackage{graphicx} +\usepackage{subcaption} +\usepackage{booktabs} % for professional tables + +% hyperref makes hyperlinks in the resulting PDF. +% If your build breaks (sometimes temporarily if a hyperlink spans a page) +% please comment out the following usepackage line and replace +% \usepackage{icml2026} with \usepackage[nohyperref]{icml2026} above. +\usepackage{hyperref} + + +% Attempt to make hyperref and algorithmic work together better: +\newcommand{\theHalgorithm}{\arabic{algorithm}} + +% Use the following line for the initial blind version submitted for review: +\usepackage{icml2026} + +% For preprint, use +% \usepackage[preprint]{icml2026} + +% If accepted, instead use the following line for the camera-ready submission: +% \usepackage[accepted]{icml2026} + +\usepackage{amsmath} +\usepackage{amssymb} +\usepackage{mathtools} +\usepackage{amsthm} + + +% if you use cleveref.. +\usepackage[capitalize,noabbrev]{cleveref} + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% THEOREMS +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +\theoremstyle{plain} +\newtheorem{theorem}{Theorem}[section] +\newtheorem{proposition}[theorem]{Proposition} +\newtheorem{lemma}[theorem]{Lemma} +\newtheorem{corollary}[theorem]{Corollary} +\theoremstyle{definition} +\newtheorem{definition}[theorem]{Definition} +\newtheorem{assumption}[theorem]{Assumption} +\theoremstyle{remark} +\newtheorem{remark}[theorem]{Remark} + +% Todonotes is useful during development; simply uncomment the next line +% and comment out the line below the next line to turn off comments +%\usepackage[disable,textsize=tiny]{todonotes} +\usepackage[textsize=tiny]{todonotes} + +% The \icmltitle you define below is probably too long as a header. +% Therefore, a short form for the running title is supplied here: +\icmltitlerunning{Submission and Formatting Instructions for ICML 2026} + +\begin{document} + +\twocolumn[ + \icmltitle{Submission and Formatting Instructions for \\ + International Conference on Machine Learning (ICML 2026)} + + % It is OKAY to include author information, even for blind submissions: the + % style file will automatically remove it for you unless you've provided + % the [accepted] option to the icml2026 package. + + % List of affiliations: The first argument should be a (short) identifier you + % will use later to specify author affiliations Academic affiliations + % should list Department, University, City, Region, Country Industry + % affiliations should list Company, City, Region, Country + + % You can specify symbols, otherwise they are numbered in order. Ideally, you + % should not use this facility. Affiliations will be numbered in order of + % appearance and this is the preferred way. + \icmlsetsymbol{equal}{*} + + \begin{icmlauthorlist} + \icmlauthor{Firstname1 Lastname1}{equal,yyy} + \icmlauthor{Firstname2 Lastname2}{equal,yyy,comp} + \icmlauthor{Firstname3 Lastname3}{comp} + \icmlauthor{Firstname4 Lastname4}{sch} + \icmlauthor{Firstname5 Lastname5}{yyy} + \icmlauthor{Firstname6 Lastname6}{sch,yyy,comp} + \icmlauthor{Firstname7 Lastname7}{comp} + %\icmlauthor{}{sch} + \icmlauthor{Firstname8 Lastname8}{sch} + \icmlauthor{Firstname8 Lastname8}{yyy,comp} + %\icmlauthor{}{sch} + %\icmlauthor{}{sch} + \end{icmlauthorlist} + + \icmlaffiliation{yyy}{Department of XXX, University of YYY, Location, Country} + \icmlaffiliation{comp}{Company Name, Location, Country} + \icmlaffiliation{sch}{School of ZZZ, Institute of WWW, Location, Country} + + \icmlcorrespondingauthor{Firstname1 Lastname1}{first1.last1@xxx.edu} + \icmlcorrespondingauthor{Firstname2 Lastname2}{first2.last2@www.uk} + + % You may provide any keywords that you find helpful for describing your + % paper; these are used to populate the "keywords" metadata in the PDF but + % will not be shown in the document + \icmlkeywords{Machine Learning, ICML} + + \vskip 0.3in +] + +% this must go after the closing bracket ] following \twocolumn[ ... + +% This command actually creates the footnote in the first column listing the +% affiliations and the copyright notice. The command takes one argument, which +% is text to display at the start of the footnote. The \icmlEqualContribution +% command is standard text for equal contribution. Remove it (just {}) if you +% do not need this facility. + +% Use ONE of the following lines. DO NOT remove the command. +% If you have no special notice, KEEP empty braces: +\printAffiliationsAndNotice{} % no special notice (required even if empty) +% Or, if applicable, use the standard equal contribution text: +% \printAffiliationsAndNotice{\icmlEqualContribution} + +\begin{abstract} + This document provides a basic paper template and submission guidelines. + Abstracts must be a single paragraph, ideally between 4--6 sentences long. + Gross violations will trigger corrections at the camera-ready phase. +\end{abstract} + +\section{Electronic Submission} + +Submission to ICML 2026 will be entirely electronic, via a web site +(not email). Information about the submission process and \LaTeX\ templates +are available on the conference web site at: +\begin{center} + \texttt{http://icml.cc/} +\end{center} + +The guidelines below will be enforced for initial submissions and +camera-ready copies. Here is a brief summary: +\begin{itemize} + \item Submissions must be in PDF\@. + \item If your paper has appendices, submit the appendix together with the + main body and the references \textbf{as a single file}. Reviewers will not + look for appendices as a separate PDF file. So if you submit such an extra + file, reviewers will very likely miss it. + \item Page limit: The main body of the paper has to be fitted to 8 pages, + excluding references and appendices; the space for the latter two is not + limited in pages, but the total file size may not exceed 10MB. For the + final version of the paper, authors can add one extra page to the main + body. + \item \textbf{Do not include author information or acknowledgements} in your + initial submission. + \item Your paper should be in \textbf{10 point Times font}. + \item Make sure your PDF file only uses Type-1 fonts. + \item Place figure captions \emph{under} the figure (and omit titles from + inside the graphic file itself). Place table captions \emph{over} the + table. + \item References must include page numbers whenever possible and be as + complete as possible. Place multiple citations in chronological order. + \item Do not alter the style template; in particular, do not compress the + paper format by reducing the vertical spaces. + \item Keep your abstract brief and self-contained, one paragraph and roughly + 4--6 sentences. Gross violations will require correction at the + camera-ready phase. The title should have content words capitalized. +\end{itemize} + +\subsection{Submitting Papers} + +\textbf{Anonymous Submission:} ICML uses double-blind review: no identifying +author information may appear on the title page or in the paper +itself. \cref{author info} gives further details. + +\medskip + +Authors must provide their manuscripts in \textbf{PDF} format. +Furthermore, please make sure that files contain only embedded Type-1 fonts +(e.g.,~using the program \texttt{pdffonts} in linux or using +File/DocumentProperties/Fonts in Acrobat). Other fonts (like Type-3) +might come from graphics files imported into the document. + +Authors using \textbf{Word} must convert their document to PDF\@. Most +of the latest versions of Word have the facility to do this +automatically. Submissions will not be accepted in Word format or any +format other than PDF\@. Really. We're not joking. Don't send Word. + +Those who use \textbf{\LaTeX} should avoid including Type-3 fonts. +Those using \texttt{latex} and \texttt{dvips} may need the following +two commands: + +{\footnotesize +\begin{verbatim} +dvips -Ppdf -tletter -G0 -o paper.ps paper.dvi +ps2pdf paper.ps +\end{verbatim}} +It is a zero following the ``-G'', which tells dvips to use +the config.pdf file. Newer \TeX\ distributions don't always need this +option. + +Using \texttt{pdflatex} rather than \texttt{latex}, often gives better +results. This program avoids the Type-3 font problem, and supports more +advanced features in the \texttt{microtype} package. + +\textbf{Graphics files} should be a reasonable size, and included from +an appropriate format. Use vector formats (.eps/.pdf) for plots, +lossless bitmap formats (.png) for raster graphics with sharp lines, and +jpeg for photo-like images. + +The style file uses the \texttt{hyperref} package to make clickable +links in documents. If this causes problems for you, add +\texttt{nohyperref} as one of the options to the \texttt{icml2026} +usepackage statement. + +\subsection{Submitting Final Camera-Ready Copy} + +The final versions of papers accepted for publication should follow the +same format and naming convention as initial submissions, except that +author information (names and affiliations) should be given. See +\cref{final author} for formatting instructions. + +The footnote, ``Preliminary work. Under review by the International +Conference on Machine Learning (ICML). Do not distribute.'' must be +modified to ``\textit{Proceedings of the + $\mathit{43}^{rd}$ International Conference on Machine Learning}, +Seoul, South Korea, PMLR 306, 2026. +Copyright 2026 by the author(s).'' + +For those using the \textbf{\LaTeX} style file, this change (and others) is +handled automatically by simply changing +$\mathtt{\backslash usepackage\{icml2026\}}$ to +$$\mathtt{\backslash usepackage[accepted]\{icml2026\}}$$ +Authors using \textbf{Word} must edit the +footnote on the first page of the document themselves. + +Camera-ready copies should have the title of the paper as running head +on each page except the first one. The running title consists of a +single line centered above a horizontal rule which is $1$~point thick. +The running head should be centered, bold and in $9$~point type. The +rule should be $10$~points above the main text. For those using the +\textbf{\LaTeX} style file, the original title is automatically set as running +head using the \texttt{fancyhdr} package which is included in the ICML +2026 style file package. In case that the original title exceeds the +size restrictions, a shorter form can be supplied by using + +\verb|\icmltitlerunning{...}| + +just before $\mathtt{\backslash begin\{document\}}$. +Authors using \textbf{Word} must edit the header of the document themselves. + +\section{Format of the Paper} + +All submissions must follow the specified format. + +\subsection{Dimensions} + +The text of the paper should be formatted in two columns, with an +overall width of 6.75~inches, height of 9.0~inches, and 0.25~inches +between the columns. The left margin should be 0.75~inches and the top +margin 1.0~inch (2.54~cm). The right and bottom margins will depend on +whether you print on US letter or A4 paper, but all final versions +must be produced for US letter size. +Do not write anything on the margins. + +The paper body should be set in 10~point type with a vertical spacing +of 11~points. Please use Times typeface throughout the text. + +\subsection{Title} + +The paper title should be set in 14~point bold type and centered +between two horizontal rules that are 1~point thick, with 1.0~inch +between the top rule and the top edge of the page. Capitalize the +first letter of content words and put the rest of the title in lower +case. +You can use TeX math in the title (we suggest sparingly), +but no custom macros, images, or other TeX commands. +Please make sure that accents, special characters, etc., are entered using +TeX commands and not using non-English characters. + +\subsection{Author Information for Submission} +\label{author info} + +ICML uses double-blind review, so author information must not appear. If +you are using \LaTeX\/ and the \texttt{icml2026.sty} file, use +\verb+\icmlauthor{...}+ to specify authors and \verb+\icmlaffiliation{...}+ +to specify affiliations. (Read the TeX code used to produce this document for +an example usage.) The author information will not be printed unless +\texttt{accepted} is passed as an argument to the style file. Submissions that +include the author information will not be reviewed. + +\subsubsection{Self-Citations} + +If you are citing published papers for which you are an author, refer +to yourself in the third person. In particular, do not use phrases +that reveal your identity (e.g., ``in previous work \cite{langley00}, we +have shown \ldots''). + +Do not anonymize citations in the reference section. The only exception are manuscripts that are +not yet published (e.g., under submission). If you choose to refer to +such unpublished manuscripts \cite{anonymous}, anonymized copies have +to be submitted +as Supplementary Material via OpenReview\@. However, keep in mind that an ICML +paper should be self contained and should contain sufficient detail +for the reviewers to evaluate the work. In particular, reviewers are +not required to look at the Supplementary Material when writing their +review (they are not required to look at more than the first $8$ pages of the submitted document). + +\subsubsection{Camera-Ready Author Information} +\label{final author} + +If a paper is accepted, a final camera-ready copy must be prepared. +% +For camera-ready papers, author information should start 0.3~inches below the +bottom rule surrounding the title. The authors' names should appear in 10~point +bold type, in a row, separated by white space, and centered. Author names should +not be broken across lines. Unbolded superscripted numbers, starting 1, should +be used to refer to affiliations. + +Affiliations should be numbered in the order of appearance. A single footnote +block of text should be used to list all the affiliations. (Academic +affiliations should list Department, University, City, State/Region, Country. +Similarly for industrial affiliations.) + +Each distinct affiliations should be listed once. If an author has multiple +affiliations, multiple superscripts should be placed after the name, separated +by thin spaces. If the authors would like to highlight equal contribution by +multiple first authors, those authors should have an asterisk placed after their +name in superscript, and the term ``\textsuperscript{*}Equal contribution" +should be placed in the footnote block ahead of the list of affiliations. A +list of corresponding authors and their emails (in the format Full Name +\textless{}email@domain.com\textgreater{}) can follow the list of affiliations. +Ideally only one or two names should be listed. + +A sample file with author names is included in the ICML2026 style file +package. Turn on the \texttt{[accepted]} option to the stylefile to +see the names rendered. All of the guidelines above are implemented +by the \LaTeX\ style file. + +\subsection{Abstract} + +The paper abstract should begin in the left column, 0.4~inches below the final +address. The heading `Abstract' should be centered, bold, and in 11~point type. +The abstract body should use 10~point type, with a vertical spacing of +11~points, and should be indented 0.25~inches more than normal on left-hand and +right-hand margins. Insert 0.4~inches of blank space after the body. Keep your +abstract brief and self-contained, limiting it to one paragraph and roughly 4--6 +sentences. Gross violations will require correction at the camera-ready phase. + +\subsection{Partitioning the Text} + +You should organize your paper into sections and paragraphs to help readers +place a structure on the material and understand its contributions. + +\subsubsection{Sections and Subsections} + +Section headings should be numbered, flush left, and set in 11~pt bold type +with the content words capitalized. Leave 0.25~inches of space before the +heading and 0.15~inches after the heading. + +Similarly, subsection headings should be numbered, flush left, and set in 10~pt +bold type with the content words capitalized. Leave +0.2~inches of space before the heading and 0.13~inches afterward. + +Finally, subsubsection headings should be numbered, flush left, and set in +10~pt small caps with the content words capitalized. Leave +0.18~inches of space before the heading and 0.1~inches after the heading. + +Please use no more than three levels of headings. + +\subsubsection{Paragraphs and Footnotes} + +Within each section or subsection, you should further partition the paper into +paragraphs. Do not indent the first line of a given paragraph, but insert a +blank line between succeeding ones. + +You can use footnotes\footnote{Footnotes should be complete sentences.} +to provide readers with additional information about a topic without +interrupting the flow of the paper. Indicate footnotes with a number in the +text where the point is most relevant. Place the footnote in 9~point type at +the bottom of the column in which it appears. Precede the first footnote in a +column with a horizontal rule of 0.8~inches.\footnote{Multiple footnotes can + appear in each column, in the same order as they appear in the text, + but spread them across columns and pages if possible.} + +\begin{figure}[ht] + \vskip 0.2in + \begin{center} + \centerline{\includegraphics[width=\columnwidth]{icml_numpapers}} + \caption{ + Historical locations and number of accepted papers for International + Machine Learning Conferences (ICML 1993 -- ICML 2008) and International + Workshops on Machine Learning (ML 1988 -- ML 1992). At the time this + figure was produced, the number of accepted papers for ICML 2008 was + unknown and instead estimated. + } + \label{icml-historical} + \end{center} +\end{figure} + +\subsection{Figures} + +You may want to include figures in the paper to illustrate your approach and +results. Such artwork should be centered, legible, and separated from the text. +Lines should be dark and at least 0.5~points thick for purposes of +reproduction, and text should not appear on a gray background. + +Label all distinct components of each figure. If the figure takes the form of a +graph, then give a name for each axis and include a legend that briefly +describes each curve. Do not include a title inside the figure; instead, the +caption should serve this function. + +Number figures sequentially, placing the figure number and caption \emph{after} +the graphics, with at least 0.1~inches of space before the caption and +0.1~inches after it, as in \cref{icml-historical}. The figure caption should be +set in 9~point type and centered unless it runs two or more lines, in which +case it should be flush left. You may float figures to the top or bottom of a +column, and you may set wide figures across both columns (use the environment +\texttt{figure*} in \LaTeX). Always place two-column figures at the top or +bottom of the page. + +\subsection{Algorithms} + +If you are using \LaTeX, please use the ``algorithm'' and ``algorithmic'' +environments to format pseudocode. These require the corresponding stylefiles, +algorithm.sty and algorithmic.sty, which are supplied with this package. +\cref{alg:example} shows an example. + +\begin{algorithm}[tb] + \caption{Bubble Sort} + \label{alg:example} + \begin{algorithmic} + \STATE {\bfseries Input:} data $x_i$, size $m$ + \REPEAT + \STATE Initialize $noChange = true$. + \FOR{$i=1$ {\bfseries to} $m-1$} + \IF{$x_i > x_{i+1}$} + \STATE Swap $x_i$ and $x_{i+1}$ + \STATE $noChange = false$ + \ENDIF + \ENDFOR + \UNTIL{$noChange$ is $true$} + \end{algorithmic} +\end{algorithm} + + +\subsection{Tables} + +You may also want to include tables that summarize material. Like figures, +these should be centered, legible, and numbered consecutively. However, place +the title \emph{above} the table with at least 0.1~inches of space before the +title and the same after it, as in \cref{sample-table}. The table title should +be set in 9~point type and centered unless it runs two or more lines, in which +case it should be flush left. + +% Note use of \abovespace and \belowspace to get reasonable spacing +% above and below tabular lines. + +\begin{table}[t] + \caption{Classification accuracies for naive Bayes and flexible + Bayes on various data sets.} + \label{sample-table} + \begin{center} + \begin{small} + \begin{sc} + \begin{tabular}{lcccr} + \toprule + Data set & Naive & Flexible & Better? \\ + \midrule + Breast & 95.9$\pm$ 0.2 & 96.7$\pm$ 0.2 & $\surd$ \\ + Cleveland & 83.3$\pm$ 0.6 & 80.0$\pm$ 0.6 & $\times$ \\ + Glass2 & 61.9$\pm$ 1.4 & 83.8$\pm$ 0.7 & $\surd$ \\ + Credit & 74.8$\pm$ 0.5 & 78.3$\pm$ 0.6 & \\ + Horse & 73.3$\pm$ 0.9 & 69.7$\pm$ 1.0 & $\times$ \\ + Meta & 67.1$\pm$ 0.6 & 76.5$\pm$ 0.5 & $\surd$ \\ + Pima & 75.1$\pm$ 0.6 & 73.9$\pm$ 0.5 & \\ + Vehicle & 44.9$\pm$ 0.6 & 61.5$\pm$ 0.4 & $\surd$ \\ + \bottomrule + \end{tabular} + \end{sc} + \end{small} + \end{center} + \vskip -0.1in +\end{table} + +Tables contain textual material, whereas figures contain graphical material. +Specify the contents of each row and column in the table's topmost row. Again, +you may float tables to a column's top or bottom, and set wide tables across +both columns. Place two-column tables at the top or bottom of the page. + +\subsection{Theorems and Such} +The preferred way is to number definitions, propositions, lemmas, etc. +consecutively, within sections, as shown below. +\begin{definition} + \label{def:inj} + A function $f:X \to Y$ is injective if for any $x,y\in X$ different, $f(x)\ne + f(y)$. +\end{definition} +Using \cref{def:inj} we immediate get the following result: +\begin{proposition} + If $f$ is injective mapping a set $X$ to another set $Y$, + the cardinality of $Y$ is at least as large as that of $X$ +\end{proposition} +\begin{proof} + Left as an exercise to the reader. +\end{proof} +\cref{lem:usefullemma} stated next will prove to be useful. +\begin{lemma} + \label{lem:usefullemma} + For any $f:X \to Y$ and $g:Y\to Z$ injective functions, $f \circ g$ is + injective. +\end{lemma} +\begin{theorem} + \label{thm:bigtheorem} + If $f:X\to Y$ is bijective, the cardinality of $X$ and $Y$ are the same. +\end{theorem} +An easy corollary of \cref{thm:bigtheorem} is the following: +\begin{corollary} + If $f:X\to Y$ is bijective, + the cardinality of $X$ is at least as large as that of $Y$. +\end{corollary} +\begin{assumption} + The set $X$ is finite. + \label{ass:xfinite} +\end{assumption} +\begin{remark} + According to some, it is only the finite case (cf. \cref{ass:xfinite}) that + is interesting. +\end{remark} +%restatable + +\subsection{Citations and References} + +Please use APA reference format regardless of your formatter or word processor. +If you rely on the \LaTeX\/ bibliographic facility, use \texttt{natbib.sty} and +\texttt{icml2026.bst} included in the style-file package to obtain this format. + +Citations within the text should include the authors' last names and year. If +the authors' names are included in the sentence, place only the year in +parentheses, for example when referencing Arthur Samuel's pioneering work +\yrcite{Samuel59}. Otherwise place the entire reference in parentheses with the +authors and year separated by a comma \cite{Samuel59}. List multiple references +separated by semicolons \cite{kearns89,Samuel59,mitchell80}. Use the `et~al.' +construct only for citations with three or more authors or after listing all +authors to a publication in an earlier reference \cite{MachineLearningI}. + +Authors should cite their own work in the third person in the initial version +of their paper submitted for blind review. Please refer to \cref{author info} +for detailed instructions on how to cite your own papers. + +Use an unnumbered first-level section heading for the references, and use a +hanging indent style, with the first line of the reference flush against the +left margin and subsequent lines indented by 10 points. The references at the +end of this document give examples for journal articles \cite{Samuel59}, +conference publications \cite{langley00}, book chapters \cite{Newell81}, books +\cite{DudaHart2nd}, edited volumes \cite{MachineLearningI}, technical reports +\cite{mitchell80}, and dissertations \cite{kearns89}. + +Alphabetize references by the surnames of the first authors, with single author +entries preceding multiple author entries. Order references for the same +authors by year of publication, with the earliest first. Make sure that each +reference includes all relevant information (e.g., page numbers). + +Please put some effort into making references complete, presentable, and +consistent, e.g. use the actual current name of authors. If using bibtex, +please protect capital letters of names and abbreviations in titles, for +example, use \{B\}ayesian or \{L\}ipschitz in your .bib file. + +\section*{Accessibility} + +Authors are kindly asked to make their submissions as accessible as possible +for everyone including people with disabilities and sensory or neurological +differences. Tips of how to achieve this and what to pay attention to will be +provided on the conference website \url{http://icml.cc/}. + +\section*{Software and Data} + +If a paper is accepted, we strongly encourage the publication of software and +data with the camera-ready version of the paper whenever appropriate. This can +be done by including a URL in the camera-ready copy. However, \textbf{do not} +include URLs that reveal your institution or identity in your submission for +review. Instead, provide an anonymous URL or upload the material as +``Supplementary Material'' into the OpenReview reviewing system. Note that +reviewers are not required to look at this material when writing their review. + +% Acknowledgements should only appear in the accepted version. +\section*{Acknowledgements} + +\textbf{Do not} include acknowledgements in the initial version of the paper +submitted for blind review. + +If a paper is accepted, the final camera-ready version can (and usually should) +include acknowledgements. Such acknowledgements should be placed at the end of +the section, in an unnumbered section that does not count towards the paper +page limit. Typically, this will include thanks to reviewers who gave useful +comments, to colleagues who contributed to the ideas, and to funding agencies +and corporate sponsors that provided financial support. + +\section*{Impact Statement} + +Authors are \textbf{required} to include a statement of the potential broader +impact of their work, including its ethical aspects and future societal +consequences. This statement should be in an unnumbered section at the end of +the paper (co-located with Acknowledgements -- the two may appear in either +order, but both must be before References), and does not count toward the paper +page limit. In many cases, where the ethical impacts and expected societal +implications are those that are well established when advancing the field of +Machine Learning, substantial discussion is not required, and a simple +statement such as the following will suffice: + +``This paper presents work whose goal is to advance the field of Machine +Learning. There are many potential societal consequences of our work, none +which we feel must be specifically highlighted here.'' + +The above statement can be used verbatim in such cases, but we encourage +authors to think about whether there is content which does warrant further +discussion, as this statement will be apparent if the paper is later flagged +for ethics review. + +% In the unusual situation where you want a paper to appear in the +% references without citing it in the main text, use \nocite +\nocite{langley00} + +\bibliography{example_paper} +\bibliographystyle{icml2026} + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% APPENDIX +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +\newpage +\appendix +\onecolumn +\section{You \emph{can} have an appendix here.} + +You can have as much text here as you want. The main body must be at most $8$ +pages long. For the final version, one more page can be added. If you want, you +can use an appendix like this one. + +The $\mathtt{\backslash onecolumn}$ command above can be kept in place if you +prefer a one-column appendix, or can be removed if you prefer a two-column +appendix. Apart from this possible change, the style (font size, spacing, +margins, page numbering, etc.) should be kept the same as the main body. +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +\end{document} + +% This document was modified from the file originally made available by +% Pat Langley and Andrea Danyluk for ICML-2K. This version was created +% by Iain Murray in 2018, and modified by Alexandre Bouchard in +% 2019 and 2021 and by Csaba Szepesvari, Gang Niu and Sivan Sabato in 2022. +% Modified again in 2023 and 2024 by Sivan Sabato and Jonathan Scarlett. +% Previous contributors include Dan Roy, Lise Getoor and Tobias +% Scheffer, which was slightly modified from the 2010 version by +% Thorsten Joachims & Johannes Fuernkranz, slightly modified from the +% 2009 version by Kiri Wagstaff and Sam Roweis's 2008 version, which is +% slightly modified from Prasad Tadepalli's 2007 version which is a +% lightly changed version of the previous year's version by Andrew +% Moore, which was in turn edited from those of Kristian Kersting and +% Codrina Lauth. Alex Smola contributed to the algorithmic style files. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/fancyhdr.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/fancyhdr.sty new file mode 100644 index 0000000..b3d811f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/fancyhdr.sty @@ -0,0 +1,864 @@ +%% +%% This is file `fancyhdr.sty', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% fancyhdr.dtx (with options: `fancyhdr') +%% +%% This is a generated file. +%% +%% This file may be distributed and/or modified under the conditions of +%% the LaTeX Project Public License, either version 1.3 of this license +%% or (at your option) any later version. The latest version of this +%% license is in: +%% +%% http://www.latex-project.org/lppl.txt +%% +%% and version 1.3 or later is part of all distributions of LaTeX version +%% 2005/12/01 or later. +%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +\NeedsTeXFormat{LaTeX2e}[2018-04-01] +\ProvidesPackage{fancyhdr}% + [2025/02/07 v5.2 + Extensive control of page headers and footers]% +% Copyright (C) 1994-2025 by Pieter van Oostrum <pieter@vanoostrum.org> +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +\ifdefined\NewDocumentCommand\else\RequirePackage{xparse}\fi +\newif\iff@nch@check +\f@nch@checktrue +\DeclareOption{nocheck}{% + \f@nch@checkfalse +} +\let\f@nch@gbl\relax +\newif\iff@nch@compatViii +\DeclareOption{compatV3}{% + \PackageWarningNoLine{fancyhdr}{The `compatV3' option is deprecated.\MessageBreak + It will disappear in one of the following releases.\MessageBreak + Please change your document to work\MessageBreak + without this option} + \let\f@nch@gbl\global + \f@nch@compatViiitrue +} +\newif\iff@nch@twoside +\f@nch@twosidefalse +\DeclareOption{twoside}{% + \if@twoside\else\f@nch@twosidetrue\fi +} +\newcommand\f@nch@def[2]{% + \def\temp@a{#2}\ifx\temp@a\@empty\f@nch@gbl\def#1{}% + \else\f@nch@gbl\def#1{#2\strut}\fi} +\DeclareOption{myheadings}{% + \@ifundefined{chapter}{% + \def\ps@myheadings{\ps@f@nch@fancyproto \let\@mkboth\@gobbletwo + \fancyhf{} + \fancyhead[LE,RO]{\thepage}% + \fancyhead[RE]{\slshape\leftmark}% + \fancyhead[LO]{\slshape\rightmark}% + \let\sectionmark\@gobble + \let\subsectionmark\@gobble + }% + }% + {\def\ps@myheadings{\ps@f@nch@fancyproto \let\@mkboth\@gobbletwo + \fancyhf{} + \fancyhead[LE,RO]{\thepage}% + \fancyhead[RE]{\slshape\leftmark}% + \fancyhead[LO]{\slshape\rightmark}% + \let\chaptermark\@gobble + \let\sectionmark\@gobble + }% + }% +} +\DeclareOption{headings}{% + \@ifundefined{chapter}{% + \if@twoside + \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth} + \fancyhf{} + \fancyhead[LE,RO]{\thepage}% + \fancyhead[RE]{\slshape\leftmark}% + \fancyhead[LO]{\slshape\rightmark}% + \def\sectionmark##1{% + \markboth{\MakeUppercase{% + \ifnum \c@secnumdepth >\z@ \thesection\quad \fi##1}}{}}% + \def\subsectionmark##1{% + \markright{% + \ifnum \c@secnumdepth >\@ne \thesubsection\quad \fi##1}}% + }% + \else + \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth} + \fancyhf{} + \fancyhead[LE,RO]{\thepage}% + \fancyhead[RE]{\slshape\leftmark}% + \fancyhead[LO]{\slshape\rightmark}% + \def\sectionmark##1{% + \markright {\MakeUppercase{% + \ifnum \c@secnumdepth >\z@ \thesection\quad \fi##1}}}% + \let\subsectionmark\@gobble % Not needed but inserted for safety + }% + \fi + }{\if@twoside + \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth} + \fancyhf{} + \fancyhead[LE,RO]{\thepage}% + \fancyhead[RE]{\slshape\leftmark}% + \fancyhead[LO]{\slshape\rightmark}% + \def\chaptermark##1{% + \markboth{\MakeUppercase{% + \ifnum \c@secnumdepth >\m@ne \if@mainmatter + \@chapapp\ \thechapter. \ \fi\fi##1}}{}}% + \def\sectionmark##1{% + \markright {\MakeUppercase{% + \ifnum \c@secnumdepth >\z@ \thesection. \ \fi##1}}}% + }% + \else + \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth} + \fancyhf{} + \fancyhead[LE,RO]{\thepage}% + \fancyhead[RE]{\slshape\leftmark}% + \fancyhead[LO]{\slshape\rightmark}% + \def\chaptermark##1{% + \markright{\MakeUppercase{% + \ifnum \c@secnumdepth >\m@ne \if@mainmatter + \@chapapp\ \thechapter. \ \fi\fi##1}}}% + \let\sectionmark\@gobble % Not needed but inserted for safety + }% + \fi + }% +} +\ProcessOptions* +\newcommand{\f@nch@forc}[3]{\expandafter\f@nchf@rc\expandafter#1\expandafter{#2}{#3}} +\newcommand{\f@nchf@rc}[3]{\def\temp@ty{#2}\ifx\@empty\temp@ty\else + \f@nch@rc#1#2\f@nch@rc{#3}\fi} +\long\def\f@nch@rc#1#2#3\f@nch@rc#4{\def#1{#2}#4\f@nchf@rc#1{#3}{#4}} +\newcommand{\f@nch@for}[3]{\edef\@fortmp{#2}% + \expandafter\@forloop#2,\@nil,\@nil\@@#1{#3}} +\newcommand\f@nch@default[3]{% + \edef\temp@a{\lowercase{\edef\noexpand\temp@a{#3}}}\temp@a \def#1{}% + \f@nch@forc\tmpf@ra{#2}% + {\expandafter\f@nch@ifin\tmpf@ra\temp@a{\edef#1{#1\tmpf@ra}}{}}% + \ifx\@empty#1\def#1{#2}\fi} +\newcommand{\f@nch@ifin}[4]{% + \edef\temp@a{#2}\def\temp@b##1#1##2\temp@b{\def\temp@b{##1}}% + \expandafter\temp@b#2#1\temp@b\ifx\temp@a\temp@b #4\else #3\fi} +\newcommand{\fancyhead}[2][]{\f@nch@fancyhf\fancyhead h[#1]{#2}}% +\newcommand{\fancyfoot}[2][]{\f@nch@fancyhf\fancyfoot f[#1]{#2}}% +\newcommand{\fancyhf}[2][]{\f@nch@fancyhf\fancyhf {}[#1]{#2}}% +\newcommand{\fancyheadoffset}[2][]{\f@nch@fancyhfoffs\fancyheadoffset h[#1]{#2}}% +\newcommand{\fancyfootoffset}[2][]{\f@nch@fancyhfoffs\fancyfootoffset f[#1]{#2}}% +\newcommand{\fancyhfoffset}[2][]{\f@nch@fancyhfoffs\fancyhfoffset {}[#1]{#2}}% +\def\f@nch@fancyhf@Echeck#1{% + \if@twoside\else + \iff@nch@twoside\else + \if\f@nch@@eo e% + \PackageWarning{fancyhdr} {\string#1's `E' option without twoside option is useless.\MessageBreak + Please consider using the `twoside' option}% + \fi\fi\fi +} +\long\def\f@nch@fancyhf#1#2[#3]#4{% + \def\temp@c{}% + \f@nch@forc\tmpf@ra{#3}% + {\expandafter\f@nch@ifin\tmpf@ra{eolcrhf,EOLCRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else \PackageError{fancyhdr}{Illegal char `\temp@c' in + \string#1 argument: [#3]}{}% + \fi \f@nch@for\temp@c{#3}% + {\f@nch@default\f@nch@@eo{eo}\temp@c + \f@nch@fancyhf@Echeck{#1}% + \f@nch@default\f@nch@@lcr{lcr}\temp@c + \f@nch@default\f@nch@@hf{hf}{#2\temp@c}% + \f@nch@forc\f@nch@eo\f@nch@@eo + {\f@nch@forc\f@nch@lcr\f@nch@@lcr + {\f@nch@forc\f@nch@hf\f@nch@@hf + {\expandafter\f@nch@def\csname + f@nch@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname {#4}}}}}} +\def\f@nch@fancyhfoffs#1#2[#3]#4{% + \def\temp@c{}% + \f@nch@forc\tmpf@ra{#3}% + {\expandafter\f@nch@ifin\tmpf@ra{eolrhf,EOLRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else \PackageError{fancyhdr}{Illegal char `\temp@c' in + \string#1 argument: [#3]}{}% + \fi \f@nch@for\temp@c{#3}% + {\f@nch@default\f@nch@@eo{eo}\temp@c + \f@nch@fancyhf@Echeck{#1}% + \f@nch@default\f@nch@@lcr{lr}\temp@c + \f@nch@default\f@nch@@hf{hf}{#2\temp@c}% + \f@nch@forc\f@nch@eo\f@nch@@eo + {\f@nch@forc\f@nch@lcr\f@nch@@lcr + {\f@nch@forc\f@nch@hf\f@nch@@hf + {\expandafter\setlength\csname + f@nch@offset@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname {#4}}}}}% + \f@nch@setoffs} +\NewDocumentCommand {\fancyheadwidth}{ s O{} O{} m } + {\f@nch@fancyhfwidth{#1}\fancyheadwidth h[#2][#3]{#4}}% +\NewDocumentCommand {\fancyfootwidth}{ s O{} O{} m } + {\f@nch@fancyhfwidth{#1}\fancyfootwidth f[#2][#3]{#4}}% +\NewDocumentCommand {\fancyhfwidth} { s O{} O{} m } + {\f@nch@fancyhfwidth{#1}\fancyhfwidth {}[#2][#3]{#4}}% +\def\f@nch@fancyhfwidth#1#2#3[#4][#5]#6{% + \setlength\@tempdima{#6}% + \def\temp@c{}% + \f@nch@forc\tmpf@ra{#4}% + {\expandafter\f@nch@ifin\tmpf@ra{eolcrhf,EOLCRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else \PackageError{fancyhdr}{Illegal char `\temp@c' in + \string#2 argument: [#4]}{}% + \fi + \f@nch@for\temp@c{#4}% + {\f@nch@default\f@nch@@eo{eo}\temp@c + \f@nch@fancyhf@Echeck{#2}% + \f@nch@default\f@nch@@lcr{lcr}\temp@c + \f@nch@default\f@nch@@hf{hf}{#3\temp@c}% + \f@nch@forc\f@nch@eo\f@nch@@eo + {\f@nch@forc\f@nch@lcr\f@nch@@lcr + {\f@nch@forc\f@nch@hf\f@nch@@hf + {% + \IfBooleanTF{#1}{% + \expandafter\edef\csname + f@nch@width@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname{\the\@tempdima}% + }% + {% + \expandafter\def\csname + f@nch@width@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname{#6}% + }% + \csname f@nchdrwdt@align@v@\f@nch@hf\endcsname + \edef\f@nch@align@@h{\f@nch@lcr}% + \def\temp@a{#5}% + \ifx\temp@a\@empty \else \f@nchdrwdt@align#5\@nil{#2}\fi + \expandafter\edef\csname + f@nch@align@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname + {\f@nch@align@@v\f@nch@align@@h}}}}}} +\def\f@nch@width@elh{\headwidth} +\def\f@nch@width@ech{\headwidth} +\def\f@nch@width@erh{\headwidth} +\def\f@nch@width@olh{\headwidth} +\def\f@nch@width@och{\headwidth} +\def\f@nch@width@orh{\headwidth} +\def\f@nch@width@elf{\headwidth} +\def\f@nch@width@ecf{\headwidth} +\def\f@nch@width@erf{\headwidth} +\def\f@nch@width@olf{\headwidth} +\def\f@nch@width@ocf{\headwidth} +\def\f@nch@width@orf{\headwidth} +\def\f@nch@align@elh{bl} +\def\f@nch@align@ech{bc} +\def\f@nch@align@erh{br} +\def\f@nch@align@olh{bl} +\def\f@nch@align@och{bc} +\def\f@nch@align@orh{br} +\def\f@nch@align@elf{tl} +\def\f@nch@align@ecf{tc} +\def\f@nch@align@erf{tr} +\def\f@nch@align@olf{tl} +\def\f@nch@align@ocf{tc} +\def\f@nch@align@orf{tr} +\def\f@nchdrwdt@align@v@h{\def\f@nch@align@@v{b}}% +\def\f@nchdrwdt@align@v@f{\def\f@nch@align@@v{t}}% +\long\def\f@nchdrwdt@align#1#2\@nil#3{% + \f@nch@ifin{#1}{TtcbB-}{% + \f@nch@ifin{#1}{-}{}{\def\f@nch@align@@v{#1}}% + \def\@tempa{#2}% + \ifx\@tempa\@empty \else \def\f@nch@align@@h{#2}\fi + }% + {\def\f@nch@align@@h{#1}}% + \expandafter\f@nch@ifin\expandafter{\f@nch@align@@h}{lcrj}{}% + {\PackageError{fancyhdr} + {\string#3: Illegal char `\f@nch@align@@h'\MessageBreak + in alignment argument}{}}% +} +\newcommand{\lhead}[2][\f@nch@olh]% + {\f@nch@def\f@nch@olh{#2}\f@nch@def\f@nch@elh{#1}} +\newcommand{\chead}[2][\f@nch@och]% + {\f@nch@def\f@nch@och{#2}\f@nch@def\f@nch@ech{#1}} +\newcommand{\rhead}[2][\f@nch@orh]% + {\f@nch@def\f@nch@orh{#2}\f@nch@def\f@nch@erh{#1}} +\newcommand{\lfoot}[2][\f@nch@olf]% + {\f@nch@def\f@nch@olf{#2}\f@nch@def\f@nch@elf{#1}} +\newcommand{\cfoot}[2][\f@nch@ocf]% + {\f@nch@def\f@nch@ocf{#2}\f@nch@def\f@nch@ecf{#1}} +\newcommand{\rfoot}[2][\f@nch@orf]% + {\f@nch@def\f@nch@orf{#2}\f@nch@def\f@nch@erf{#1}} +\newlength{\f@nch@headwidth} \let\headwidth\f@nch@headwidth +\newlength{\f@nch@offset@elh} +\newlength{\f@nch@offset@erh} +\newlength{\f@nch@offset@olh} +\newlength{\f@nch@offset@orh} +\newlength{\f@nch@offset@elf} +\newlength{\f@nch@offset@erf} +\newlength{\f@nch@offset@olf} +\newlength{\f@nch@offset@orf} +\newcommand{\headrulewidth}{0.4pt} +\newcommand{\footrulewidth}{0pt} +\@ifundefined{headruleskip}% + {\newcommand{\headruleskip}{0pt}}{} +\@ifundefined{footruleskip}% + {\newcommand{\footruleskip}{.3\normalbaselineskip}}{} +\newcommand{\plainheadrulewidth}{0pt} +\newcommand{\plainfootrulewidth}{0pt} +\newif\if@fancyplain \@fancyplainfalse +\def\fancyplain#1#2{\if@fancyplain#1\else#2\fi} +\headwidth=-123456789sp +\let\f@nch@raggedleft\raggedleft +\let\f@nch@raggedright\raggedright +\let\f@nch@centering\centering +\let\f@nch@everypar\everypar +\ifdefined\ExplSyntaxOn + \ExplSyntaxOn + \providecommand\IfFormatAtLeastTF{\@ifl@t@r\fmtversion} + \IfFormatAtLeastTF{2021-06-01}{ + \def\f@nch@saveclr@parhook #1{ + \expandafter\let\csname f@nch@__hook~#1\expandafter\endcsname + \csname __hook~#1\endcsname + \expandafter\let\csname f@nch@__hook_toplevel~#1\expandafter\endcsname + \csname __hook_toplevel~#1\endcsname + \expandafter\let\csname f@nch@__hook_next~#1\expandafter\endcsname + \csname __hook_next~#1\endcsname + \expandafter\let\csname f@nch@g__hook_#1_code_prop\expandafter\endcsname + \csname g__hook_#1_code_prop\endcsname + \RemoveFromHook{#1}[*] + \ClearHookNext{#1} + } + \def\f@nch@restore@parhook #1{ + \global\expandafter\let\csname __hook~#1\expandafter\endcsname + \csname f@nch@__hook~#1\endcsname + \global\expandafter\let\csname __hook_toplevel~#1\expandafter\endcsname + \csname f@nch@__hook_toplevel~#1\endcsname + \global\expandafter\let\csname __hook_next~#1\expandafter\endcsname + \csname f@nch@__hook_next~#1\endcsname + \global\expandafter\let\csname g__hook_#1_code_prop\expandafter\endcsname + \csname f@nch@g__hook_#1_code_prop\endcsname + } + \def\f@nch@resetpar{ + \f@nch@everypar{} + \f@nch@saveclr@parhook{para/before} + \f@nch@saveclr@parhook{para/begin} + \f@nch@saveclr@parhook{para/end} + \f@nch@saveclr@parhook{para/after} + } + \def\f@nch@restorepar{ + \f@nch@restore@parhook{para/before} + \f@nch@restore@parhook{para/begin} + \f@nch@restore@parhook{para/end} + \f@nch@restore@parhook{para/after} + } + }{ + \def\f@nch@resetpar{ + \f@nch@everypar{} + } + \def\f@nch@restorepar{} + } + \ExplSyntaxOff +\else + \def\f@nch@resetpar{% + \f@nch@everypar{}% + } + \def\f@nch@restorepar{} +\fi +\newcommand\f@nch@noUppercase[2][]{#2} +\def\f@nch@reset{\f@nch@resetpar\restorecr\endlinechar=13 + \catcode`\\=0\catcode`\{=1\catcode`\}=2\catcode`\$=3\catcode`\&=4 + \catcode`\#=6\catcode`\^=7\catcode`\_=8\catcode`\ =10\catcode`\@=11 + \catcode`\:=11\catcode`\~=13\catcode`\%=14 + \catcode0=15 %NULL + \catcode9=10 %TAB + \let\\\@normalcr \let\raggedleft\f@nch@raggedleft + \let\raggedright\f@nch@raggedright \let\centering\f@nch@centering + \def\baselinestretch{1}% + \hsize=\headwidth + \def\nouppercase##1{{% + \let\uppercase\relax\let\MakeUppercase\f@nch@noUppercase + \expandafter\let\csname MakeUppercase \endcsname\relax + \expandafter\def\csname MakeUppercase\space\space\space\endcsname + [####1]####2{####2}% + ##1}}% + \@ifundefined{@normalsize} {\normalsize} % for ucthesis.cls + {\@normalsize}% + } +\newcommand*{\fancycenter}[1][1em]{% + \@ifnextchar[{\f@nch@center{#1}}{\f@nch@center{#1}[3]}% +} +\def\f@nch@center#1[#2]#3#4#5{% + \def\@tempa{#4}\ifx\@tempa\@empty + \hbox to\linewidth{\color@begingroup{#3}\hfil {#5}\color@endgroup}% + \else + \setlength\@tempdima{#1}% + \setlength{\@tempdimb}{#2\@tempdima}% + \@tempdimc \@tempdimb \advance\@tempdimc -\@tempdima + \setlength\@tempskipa{\@tempdimb \@plus 1fil \@minus \@tempdimc}% + \@tempskipb\@tempskipa + \def\@tempa{#3}\ifx\@tempa\@empty + \addtolength\@tempskipa{\z@ \@minus \@tempdima}% + \fi + \def\@tempa{#5}\ifx\@tempa\@empty % empty right + \addtolength\@tempskipb{\z@ \@minus \@tempdima}% + \fi + \settowidth{\@tempdimb}{#3}% + \settowidth{\@tempdimc}{#5}% + \ifdim\@tempdimb>\@tempdimc + \advance\@tempdimb -\@tempdimc + \addtolength\@tempskipb{\@tempdimb \@minus \@tempdimb}% + \else + \advance\@tempdimc -\@tempdimb + \addtolength\@tempskipa{\@tempdimc \@minus \@tempdimc}% + \fi + \hbox to\linewidth{\color@begingroup{#3}\hskip \@tempskipa + {#4}\hskip \@tempskipb {#5}\color@endgroup}% + \fi +} +\newcommand{\f@nch@headinit}{} +\newcommand{\fancyheadinit}[1]{% + \def\f@nch@headinit{#1}% +} +\newcommand{\f@nch@footinit}{} +\newcommand{\fancyfootinit}[1]{% + \def\f@nch@footinit{#1}% +} +\newcommand{\fancyhfinit}[1]{% + \def\f@nch@headinit{#1}% + \def\f@nch@footinit{#1}% +} +\ifdefined\NewMirroredHookPair + \NewMirroredHookPair{fancyhdr/before}{fancyhdr/after} + \NewMirroredHookPair{fancyhdr/head/begin}{fancyhdr/head/end} + \NewMirroredHookPair{fancyhdr/foot/begin}{fancyhdr/foot/end} +\fi +\newlength\f@nch@height +\newlength\f@nch@footalignment +\newif\iff@nch@footalign\f@nch@footalignfalse +\newcommand{\fancyfootalign}[1]{% + \def\temp@a{#1}% + \ifx\temp@a\@empty + \f@nch@footalignfalse + \else + \f@nch@footaligntrue + \setlength\f@nch@footalignment{#1}% + \fi +} +\newcommand\fancyhdrsettoheight[2]{% + \expandafter\ifx\csname f@nch@#2\endcsname\fancyhdrsettoheight + \else\PackageError{fancyhdr}{Unknown parameter #2 in \string\fancyhdrsettoheight}{}\fi + \setbox\@tempboxa\hbox{{\f@nch@checkfalse\csname @#2\endcsname}}% + \setlength{#1}\f@nch@height + \setbox\@tempboxa\box\voidb@x +} +\let\f@nch@oddhead\fancyhdrsettoheight +\let\f@nch@evenhead\fancyhdrsettoheight +\let\f@nch@oddfoot\fancyhdrsettoheight +\let\f@nch@evenfoot\fancyhdrsettoheight +\newcommand\f@nch@vbox[2]{% + \setbox0\vbox{#2}% + \global\f@nch@height=\ht0 + \ifdim\ht0>#1\relax + \iff@nch@check + \dimen0=#1\advance\dimen0-\ht0 + \PackageWarning{fancyhdr}{% + \string#1 is too small (\the#1): \MessageBreak + Make it at least \the\ht0, for example:\MessageBreak + \string\setlength{\string#1}{\the\ht0}% + \iff@nch@compatViii .\MessageBreak + We now make it that large for the rest of the document.\MessageBreak + This may cause the page layout to be inconsistent, however + \fi + \ifx#1\headheight .\MessageBreak + You might also make \topmargin smaller:\MessageBreak + \string\addtolength{\string\topmargin}{\the\dimen0}% + \fi + \@gobble + }% + \iff@nch@compatViii + \dimen0=#1\relax + \global#1=\ht0\relax + \ht0=\dimen0 % + \else + \ht0=#1\relax + \fi + \else + \ht0=#1\relax + \fi + \fi + \box0} +\newcommand\f@nch@head[6]{% + \f@nch@reset + \ifdefined\UseHook\UseHook{fancyhdr/before}\UseHook{fancyhdr/head/begin}\fi + \f@nch@headinit\relax + #1% + \hbox to\headwidth{% + \f@nch@vbox\headheight{% + \f@nch@hfbox{#2}{#3}{#4}{#6}{h}% + \vskip\headruleskip\relax + \headrule + }% + }% + #5% + \ifdefined\UseHook\UseHook{fancyhdr/head/end}\UseHook{fancyhdr/after}\fi + \f@nch@restorepar +} +\newcommand\f@nch@foot[6]{% + \f@nch@reset + \ifdefined\UseHook\UseHook{fancyhdr/before}\UseHook{fancyhdr/foot/begin}\fi + \f@nch@footinit\relax + #1% + \hbox to\headwidth{% + \f@nch@vbox\footskip{% + \setbox0=\vbox{\footrule}\unvbox0 + \vskip\footruleskip + \f@nch@hfbox{#2}{#3}{#4}{#6}{f}% + \iff@nch@footalign \vskip\f@nch@footalignment \fi + }% + }% + #5% + \ifdefined\UseHook\UseHook{fancyhdr/foot/end}\UseHook{fancyhdr/after}\fi + \f@nch@restorepar +} +\newlength\f@nch@widthL +\newlength\f@nch@widthC +\newlength\f@nch@widthR +\newcommand\f@nch@hfbox[5]{% + \setlength\f@nch@widthL{\csname f@nch@width@#4l#5\endcsname}% + \setlength\f@nch@widthC{\csname f@nch@width@#4c#5\endcsname}% + \setlength\f@nch@widthR{\csname f@nch@width@#4r#5\endcsname}% + \let\@tempa\f@nch@hfbox@center + \ifdim \dimexpr \f@nch@widthL+\f@nch@widthC+\f@nch@widthR>\headwidth + \else + \ifdim \dimexpr \f@nch@widthL+0.5\f@nch@widthC>0.5\headwidth + \let \@tempa\f@nch@hfbox@fit + \fi + \ifdim \dimexpr \f@nch@widthR+0.5\f@nch@widthC>0.5\headwidth + \let \@tempa\f@nch@hfbox@fit + \fi + \fi + \@tempa{#1}{#2}{#3}#4#5% +} +\newcommand\f@nch@hfbox@center[5]{% + \hbox to \headwidth{% + \rlap{\f@nch@parbox{#1}\f@nch@widthL{#4}l{#5}}% + \hfill + \f@nch@parbox{#2}\f@nch@widthC{#4}c{#5}% + \hfill + \llap{\f@nch@parbox{#3}\f@nch@widthR{#4}r{#5}}% + }% +} +\newcommand\f@nch@hfbox@fit[5]{% + \hbox to \headwidth{% + \f@nch@parbox{#1}\f@nch@widthL{#4}l{#5}% + \hfill + \f@nch@parbox{#2}\f@nch@widthC{#4}c{#5}% + \hfill + \f@nch@parbox{#3}\f@nch@widthR{#4}r{#5}% + }% +}% +\newcommand\f@nch@parbox[5]{% + \expandafter\expandafter\expandafter\f@nch@parbox@align + \csname f@nch@align@#3#4#5\endcsname + \parbox[\f@nch@align@@v]{#2}% + {% + \f@nch@align@@pre + \f@nch@align@@h\leavevmode\ignorespaces#1% + \f@nch@align@@post + }% +} +\newcommand\f@nch@parbox@align[2]{% + \def\f@nch@align@@pre{}% + \def\f@nch@align@@post{}% + \csname f@nch@parbox@align@v#1\endcsname + \csname f@nch@parbox@align@h#2\endcsname +} +\def\f@nch@parbox@align@vT{\def\f@nch@align@@v{t}\def\f@nch@align@@pre{\vspace{0pt}}} +\def\f@nch@parbox@align@vt{\def\f@nch@align@@v{t}} +\def\f@nch@parbox@align@vc{\def\f@nch@align@@v{c}} +\def\f@nch@parbox@align@vb{\def\f@nch@align@@v{b}} +\def\f@nch@parbox@align@vB{\def\f@nch@align@@v{b}\def\f@nch@align@@post{\vspace{0pt}}} +\def\f@nch@parbox@align@hl{\def\f@nch@align@@h{\raggedright}} +\def\f@nch@parbox@align@hc{\def\f@nch@align@@h{\centering}} +\def\f@nch@parbox@align@hr{\def\f@nch@align@@h{\raggedleft}} +\def\f@nch@parbox@align@hj{\def\f@nch@align@@h{}} +\@ifundefined{@chapapp}{\let\@chapapp\chaptername}{}% +\def\f@nch@initialise{% + \@ifundefined{chapter}% + {\def\sectionmark##1{\markboth{\MakeUppercase{\ifnum \c@secnumdepth>\z@ + \thesection\hskip 1em\relax + \fi ##1}}{}}% + \def\subsectionmark##1{\markright {\ifnum \c@secnumdepth >\@ne + \thesubsection\hskip 1em\relax \fi ##1}}}% + {\def\chaptermark##1{\markboth {\MakeUppercase{\ifnum + \c@secnumdepth>\m@ne \@chapapp\ \thechapter. \ \fi ##1}}{}}% + \def\sectionmark##1{\markright{\MakeUppercase{\ifnum \c@secnumdepth >\z@ + \thesection. \ \fi ##1}}}% + }% + \def\headrule{{\if@fancyplain\let\headrulewidth\plainheadrulewidth\fi + \hrule\@height\headrulewidth\@width\headwidth + \vskip-\headrulewidth}}% + \def\footrule{{\if@fancyplain\let\footrulewidth\plainfootrulewidth\fi + \hrule\@width\headwidth\@height\footrulewidth}}% + \def\headrulewidth{0.4pt}% + \def\footrulewidth{0pt}% + \def\headruleskip{0pt}% + \def\footruleskip{0.3\normalbaselineskip}% + \fancyhf{}% + \if@twoside + \fancyhead[el,or]{\fancyplain{}{\slshape\rightmark}}% + \fancyhead[er,ol]{\fancyplain{}{\slshape\leftmark}}% + \else + \fancyhead[l]{\fancyplain{}{\slshape\rightmark}}% + \fancyhead[r]{\fancyplain{}{\slshape\leftmark}}% + \fi + \fancyfoot[c]{\rmfamily\thepage}% page number +} +\f@nch@initialise +\def\ps@f@nch@fancyproto{% + \ifdim\headwidth<0sp + \global\advance\headwidth123456789sp\global\advance\headwidth\textwidth + \fi + \gdef\ps@f@nch@fancyproto{\@fancyplainfalse\ps@f@nch@fancycore}% + \@fancyplainfalse\ps@f@nch@fancycore +}% +\@namedef{f@nch@ps@f@nch@fancyproto-is-fancyhdr}{} +\def\ps@fancy{\ps@f@nch@fancyproto} +\@namedef{f@nch@ps@fancy-is-fancyhdr}{} +\def\ps@fancyplain{\ps@f@nch@fancyproto \let\ps@plain\ps@plain@fancy} +\def\ps@plain@fancy{\@fancyplaintrue\ps@f@nch@fancycore} +\let\f@nch@ps@empty\ps@empty +\def\ps@f@nch@fancycore{% + \f@nch@ps@empty + \def\@mkboth{\protect\markboth}% + \def\f@nch@oddhead{\f@nch@head\f@nch@Oolh\f@nch@olh\f@nch@och\f@nch@orh\f@nch@Oorh{o}}% + \def\@oddhead{% + \iff@nch@twoside + \ifodd\c@page + \f@nch@oddhead + \else + \@evenhead + \fi + \else + \f@nch@oddhead + \fi + } + \def\f@nch@oddfoot{\f@nch@foot\f@nch@Oolf\f@nch@olf\f@nch@ocf\f@nch@orf\f@nch@Oorf{o}}% + \def\@oddfoot{% + \iff@nch@twoside + \ifodd\c@page + \f@nch@oddfoot + \else + \@evenfoot + \fi + \else + \f@nch@oddfoot + \fi + } + \def\@evenhead{\f@nch@head\f@nch@Oelh\f@nch@elh\f@nch@ech\f@nch@erh\f@nch@Oerh{e}}% + \def\@evenfoot{\f@nch@foot\f@nch@Oelf\f@nch@elf\f@nch@ecf\f@nch@erf\f@nch@Oerf{e}}% +} +\def\f@nch@Oolh{\if@reversemargin\hss\else\relax\fi} +\def\f@nch@Oorh{\if@reversemargin\relax\else\hss\fi} +\let\f@nch@Oelh\f@nch@Oorh +\let\f@nch@Oerh\f@nch@Oolh +\let\f@nch@Oolf\f@nch@Oolh +\let\f@nch@Oorf\f@nch@Oorh +\let\f@nch@Oelf\f@nch@Oelh +\let\f@nch@Oerf\f@nch@Oerh +\def\f@nch@offsolh{\headwidth=\textwidth\advance\headwidth\f@nch@offset@olh + \advance\headwidth\f@nch@offset@orh\hskip-\f@nch@offset@olh} +\def\f@nch@offselh{\headwidth=\textwidth\advance\headwidth\f@nch@offset@elh + \advance\headwidth\f@nch@offset@erh\hskip-\f@nch@offset@elh} +\def\f@nch@offsolf{\headwidth=\textwidth\advance\headwidth\f@nch@offset@olf + \advance\headwidth\f@nch@offset@orf\hskip-\f@nch@offset@olf} +\def\f@nch@offself{\headwidth=\textwidth\advance\headwidth\f@nch@offset@elf + \advance\headwidth\f@nch@offset@erf\hskip-\f@nch@offset@elf} +\def\f@nch@setoffs{% + \f@nch@gbl\let\headwidth\f@nch@headwidth + \f@nch@gbl\def\f@nch@Oolh{\f@nch@offsolh}% + \f@nch@gbl\def\f@nch@Oelh{\f@nch@offselh}% + \f@nch@gbl\def\f@nch@Oorh{\hss}% + \f@nch@gbl\def\f@nch@Oerh{\hss}% + \f@nch@gbl\def\f@nch@Oolf{\f@nch@offsolf}% + \f@nch@gbl\def\f@nch@Oelf{\f@nch@offself}% + \f@nch@gbl\def\f@nch@Oorf{\hss}% + \f@nch@gbl\def\f@nch@Oerf{\hss}% +} +\newif\iff@nch@footnote +\AtBeginDocument{% + \let\latex@makecol\@makecol + \def\@makecol{\ifvoid\footins\f@nch@footnotefalse\else\f@nch@footnotetrue\fi + \let\f@nch@topfloat\@toplist\let\f@nch@botfloat\@botlist\latex@makecol}% +} +\newcommand\iftopfloat[2]{\ifx\f@nch@topfloat\@empty #2\else #1\fi}% +\newcommand\ifbotfloat[2]{\ifx\f@nch@botfloat\@empty #2\else #1\fi}% +\newcommand\iffloatpage[2]{\if@fcolmade #1\else #2\fi}% +\newcommand\iffootnote[2]{\iff@nch@footnote #1\else #2\fi}% +\ifx\@temptokenb\undefined \csname newtoks\endcsname\@temptokenb\fi +\newif\iff@nch@pagestyle@star +\newcommand\fancypagestyle{% + \@ifstar{\f@nch@pagestyle@startrue\f@nch@pagestyle}% + {\f@nch@pagestyle@starfalse\f@nch@pagestyle}% +} +\newcommand\f@nch@pagestyle[1]{% + \@ifnextchar[{\f@nch@@pagestyle{#1}}{\f@nch@@pagestyle{#1}[f@nch@fancyproto]}% +} +\long\def\f@nch@@pagestyle#1[#2]#3{% + \@ifundefined{ps@#2}{% + \PackageError{fancyhdr}{\string\fancypagestyle: Unknown base page style `#2'}{}% + }{% + \@ifundefined{f@nch@ps@#2-is-fancyhdr}{% + \PackageError{fancyhdr}{\string\fancypagestyle: Base page style `#2' is not fancyhdr-based}{}% + }% + {% + \f@nch@pagestyle@setup + \def\temp@b{\@namedef{ps@#1}}% + \expandafter\temp@b\expandafter{\the\@temptokenb + \let\f@nch@gbl\relax\@nameuse{ps@#2}#3\relax}% + \@namedef{f@nch@ps@#1-is-fancyhdr}{}% + }% + }% +} +\newcommand\f@nch@pagestyle@setup{% + \iff@nch@pagestyle@star + \iff@nch@check\@temptokenb={\f@nch@checktrue}\else\@temptokenb={\f@nch@checkfalse}\fi + \@tfor\temp@a:= + \f@nch@olh\f@nch@och\f@nch@orh\f@nch@elh\f@nch@ech\f@nch@erh + \f@nch@olf\f@nch@ocf\f@nch@orf\f@nch@elf\f@nch@ecf\f@nch@erf + \f@nch@width@elh\f@nch@width@ech\f@nch@width@erh\f@nch@width@olh + \f@nch@width@och\f@nch@width@orh\f@nch@width@elf\f@nch@width@ecf + \f@nch@width@erf\f@nch@width@olf\f@nch@width@ocf\f@nch@width@orf + \f@nch@align@elh\f@nch@align@ech\f@nch@align@erh\f@nch@align@olh + \f@nch@align@och\f@nch@align@orh\f@nch@align@elf\f@nch@align@ecf + \f@nch@align@erf\f@nch@align@olf\f@nch@align@ocf\f@nch@align@orf + \f@nch@Oolh\f@nch@Oorh\f@nch@Oelh\f@nch@Oerh + \f@nch@Oolf\f@nch@Oorf\f@nch@Oelf\f@nch@Oerf + \f@nch@headinit\f@nch@footinit + \headrule\headrulewidth\footrule\footrulewidth + \do {% + \toks@=\expandafter\expandafter\expandafter{\temp@a}% + \toks@=\expandafter\expandafter\expandafter{% + \expandafter\expandafter\expandafter\def + \expandafter\expandafter\temp@a\expandafter{\the\toks@}}% + \edef\temp@b{\@temptokenb={\the\@temptokenb\the\toks@}}% + \temp@b + }% + \@tfor\temp@a:= + \f@nch@offset@olh\f@nch@offset@orh\f@nch@offset@elh\f@nch@offset@erh + \f@nch@offset@olf\f@nch@offset@orf\f@nch@offset@elf\f@nch@offset@erf + \do {% + \toks@=\expandafter\expandafter\expandafter{\expandafter\the\temp@a}% + \toks@=\expandafter\expandafter\expandafter{% + \expandafter\expandafter\expandafter\setlength + \expandafter\expandafter\temp@a\expandafter{\the\toks@}}% + \edef\temp@b{\@temptokenb={\the\@temptokenb\the\toks@}}% + \temp@b + }% + \else + \@temptokenb={}% + \fi +} +\newcommand\fancypagestyleassign[2]{% + \@ifundefined{ps@#2}{% + \PackageError{fancyhdr}{\string\fancypagestyleassign: Unknown page style `#2'}{}% + }{% + \expandafter\let + \csname ps@#1\expandafter\endcsname + \csname ps@#2\endcsname + \@ifundefined{f@nch@ps@#2-is-fancyhdr}{% + \expandafter\let\csname f@nch@ps@#1-is-fancyhdr\endcsname\@undefined + }{% + \@namedef{f@nch@ps@#1-is-fancyhdr}{}% + }% + }% +} +\fancypagestyle*{fancydefault}{\f@nch@initialise} +\def\f@nchdrbox@topstrut{\vrule height\ht\strutbox width\z@} +\def\f@nchdrbox@botstrut{\vrule depth\dp\strutbox width\z@} +\def\f@nchdrbox@nostrut{\noalign{\vspace{0pt}}\let\f@nchdrbox@@crstrut\f@nchdrbox@botstrut} +\NewDocumentCommand{\fancyhdrbox}{ O{cl} o m }{% +\begingroup + \let\f@nchdrbox@@pre\f@nchdrbox@topstrut + \let\f@nchdrbox@@postx\f@nchdrbox@botstrut + \let\f@nchdrbox@@posty\relax + \let\f@nchdrbox@@crstrut\strut + \IfNoValueTF{#2}% + {\let\f@nchdrbox@@halignto\@empty}% + {\setlength\@tempdima{#2}% + \def\f@nchdrbox@@halignto{to\@tempdima}}% + \def\@tempa{#1}% + \ifx\@tempa\@empty + \f@nchdrbox@align cl\@nil{#3}% + \else + \f@nchdrbox@align #1\@nil{#3}% + \fi +\endgroup +} +\protected\def\f@nchdrbox@cr{% + {\ifnum0=`}\fi\@ifstar\@f@nchdrbox@xcr\@f@nchdrbox@xcr} + +\def\@f@nchdrbox@xcr{% + \unskip\f@nchdrbox@@crstrut + \@ifnextchar[\@f@nchdrbox@argc{\ifnum0=`{\fi}\cr}% +} + +\def\@f@nchdrbox@argc[#1]{% + \ifnum0=`{\fi}% + \ifdim #1>\z@ + \unskip\@f@nchdrbox@xargc{#1}% + \else + \@f@nchdrbox@yargc{#1}% + \fi} + +\def\@f@nchdrbox@xargc#1{\@tempdima #1\advance\@tempdima \dp \strutbox + \vrule \@height\z@ \@depth\@tempdima \@width\z@ \cr} + +\def\@f@nchdrbox@yargc#1{\cr\noalign{\setlength\@tempdima{#1}\vskip\@tempdima}} +\def\f@nchdrbox@T{\let\f@nchdrbox@@pre\f@nchdrbox@nostrut + \f@nchdrbox@t} +\def\f@nchdrbox@t{\def\f@nchdrbox@@v{t}\def\f@nchdrbox@@h{l}} +\def\f@nchdrbox@c{\def\f@nchdrbox@@v{c}\def\f@nchdrbox@@h{c}} +\def\f@nchdrbox@b{\def\f@nchdrbox@@v{b}\def\f@nchdrbox@@h{l}} +\def\f@nchdrbox@B{\let\f@nchdrbox@@postx\relax + \def\f@nchdrbox@@posty{\vspace{0pt}}% + \f@nchdrbox@b} +\long\def\f@nchdrbox@align#1#2\@nil#3{% + \f@nch@ifin{#1}{TtcbB}{% + \@nameuse{f@nchdrbox@#1}% + \def\@tempa{#2}% + \ifx\@tempa\@empty\else \def\f@nchdrbox@@h{#2}\fi + }% + {\def\f@nchdrbox@@v{c}\def\f@nchdrbox@@h{#1}}% + \expandafter\f@nch@ifin\expandafter{\f@nchdrbox@@h}{lcr}{}% + {\PackageError{fancyhdr}{\string\fancyhdrbox: Illegal char `\f@nchdrbox@@h'\MessageBreak + in alignment argument}{}}% + \let\\\f@nchdrbox@cr + \setbox0=\if \f@nchdrbox@@v t\vtop + \else \vbox + \fi + {% + \ialign \f@nchdrbox@@halignto + \bgroup \relax + {\if \f@nchdrbox@@h l\hskip 1sp\else \hfil \fi + \ignorespaces ##\unskip + \if\f@nchdrbox@@h r\else \hfil \fi + }% + \tabskip\z@skip \cr + \f@nchdrbox@@pre + #3\unskip \f@nchdrbox@@postx + \crcr + \egroup + \f@nchdrbox@@posty + }% + \if\f@nchdrbox@@v c\@tempdima=\ht0\advance\@tempdima\dp0% + \ht0=0.5\@tempdima\dp0=0.5\@tempdima\fi + \leavevmode \box0 +} +\@ifclassloaded{newlfm} +{ + \let\ps@@empty\f@nch@ps@empty + \AtBeginDocument{% + \renewcommand{\@zfancyhead}[5]{\relax\hbox to\headwidth{\f@nch@reset + \@zfancyvbox\headheight{\hbox + {\rlap{\parbox[b]{\headwidth}{\raggedright\f@nch@olh}}\hfill + \parbox[b]{\headwidth}{\centering\f@nch@olh}\hfill + \llap{\parbox[b]{\headwidth}{\raggedleft\f@nch@orh}}}% + \zheadrule}}\relax}% + } +} +{} +\endinput +%% +%% End of file `fancyhdr.sty'. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml2026.bst b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml2026.bst new file mode 100644 index 0000000..f1a50e8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml2026.bst @@ -0,0 +1,1443 @@ +%% File: `icml2025.bst' +%% A modification of `plainnl.bst' for use with natbib package +%% +%% Copyright 2010 Hal Daum\'e III +%% Modified by J. Fürnkranz +%% - Changed labels from (X and Y, 2000) to (X & Y, 2000) +%% - Changed References to last name first and abbreviated first names. +%% Modified by Iain Murray 2018 (who suggests adopting a standard .bst in future...) +%% - Made it actually use abbreviated first names +%% +%% Copyright 1993-2007 Patrick W Daly +%% Max-Planck-Institut f\"ur Sonnensystemforschung +%% Max-Planck-Str. 2 +%% D-37191 Katlenburg-Lindau +%% Germany +%% E-mail: daly@mps.mpg.de +%% +%% This program can be redistributed and/or modified under the terms +%% of the LaTeX Project Public License Distributed from CTAN +%% archives in directory macros/latex/base/lppl.txt; either +%% version 1 of the License, or any later version. +%% + % Version and source file information: + % \ProvidesFile{icml2010.mbs}[2007/11/26 1.93 (PWD)] + % + % BibTeX `plainnat' family + % version 0.99b for BibTeX versions 0.99a or later, + % for LaTeX versions 2.09 and 2e. + % + % For use with the `natbib.sty' package; emulates the corresponding + % member of the `plain' family, but with author-year citations. + % + % With version 6.0 of `natbib.sty', it may also be used for numerical + % citations, while retaining the commands \citeauthor, \citefullauthor, + % and \citeyear to print the corresponding information. + % + % For version 7.0 of `natbib.sty', the KEY field replaces missing + % authors/editors, and the date is left blank in \bibitem. + % + % Includes field EID for the sequence/citation number of electronic journals + % which is used instead of page numbers. + % + % Includes fields ISBN and ISSN. + % + % Includes field URL for Internet addresses. + % + % Includes field DOI for Digital Object Idenfifiers. + % + % Works best with the url.sty package of Donald Arseneau. + % + % Works with identical authors and year are further sorted by + % citation key, to preserve any natural sequence. + % +ENTRY + { address + author + booktitle + chapter + doi + eid + edition + editor + howpublished + institution + isbn + issn + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + url + volume + year + } + {} + { label extra.label sort.label short.list } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr "{vv~}{ll}{, jj}{, f.}" format.name$ 't := + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { " (eds.)" * } + { " (ed.)" * } + if$ + } + if$ +} + +FUNCTION {format.isbn} +{ isbn empty$ + { "" } + { new.block "ISBN " isbn * } + if$ +} + +FUNCTION {format.issn} +{ issn empty$ + { "" } + { new.block "ISSN " issn * } + if$ +} + +FUNCTION {format.url} +{ url empty$ + { "" } + { new.block "URL \url{" url * "}" * } + if$ +} + +FUNCTION {format.doi} +{ doi empty$ + { "" } + { new.block "\doi{" doi * "}" * } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + { title "t" change.case$ } + if$ +} + +FUNCTION {format.full.names} +{'s := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.full} +{ author empty$ + { editor empty$ + { "" } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.full} +{ author empty$ + { "" } + { author format.full.names } + if$ +} + +FUNCTION {editor.full} +{ editor empty$ + { "" } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.full + { type$ "proceedings" = + 'editor.full + 'author.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year duplicate$ empty$ + { "empty year in " cite$ * warning$ + pop$ "" } + 'skip$ + if$ + month empty$ + 'skip$ + { month + " " * swap$ * + } + if$ + extra.label * +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pp.\ " pages n.dashify tie.or.space.connect } + { "pp.\ " pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.eid} +{ eid empty$ + { "" } + { "art." eid tie.or.space.connect } + if$ +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":\penalty0 " * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.vol.num.eid} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + eid empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.eid } + { ":\penalty0 " * eid * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + key empty$ not and + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In \emph{" journal * "}" * } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "\emph{" * series * "}" * } + if$ + } + 'skip$ + if$ + } + 'skip$ + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In \emph{" booktitle * "}" * } + if$ + } + { "In " } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + eid empty$ + { format.vol.num.pages output } + { format.vol.num.eid output } + if$ + format.date "year" output.check + } + { format.article.crossref output.nonnull + eid empty$ + { format.pages output } + { format.eid output } + if$ + } + if$ + format.issn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date "year" output.check + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date "year" output.check + } + { address output.nonnull + format.date "year" output.check + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + new.block + format.btitle "title" output.check + organization address new.block.checkb + organization output + address output + format.edition output + format.date output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + format.issn output + format.url output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.btitle "title" output.check + new.block + "PhD thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + format.editors output + editor format.key output + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address output + format.date "year" output.check + new.sentence + organization output + publisher output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + format.url output + fin.entry +} + +FUNCTION {default.type} { misc } + + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + + + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " \& " * s #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + short.list key field.or.null = or + { pop$ "" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { + s nameptr "{vv{ } }{ll{ }}{ f{ }}{ jj{ }}" format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" * } + { numnames #2 > nameptr #2 = and + { "zz" * year field.or.null * " " * } + 'skip$ + if$ + t sortify * + } + if$ + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + + +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + " " + * + year field.or.null sortify + * + " " + * + cite$ + * + #1 entry.max$ substring$ + 'sort.label := + sort.label * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.label next.extra } + +INTEGERS { longest.label.width last.extra.num number.label } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := + #0 'number.label := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\providecommand{\natexlab}[1]{#1}" + write$ newline$ + "\providecommand{\url}[1]{\texttt{#1}}" + write$ newline$ + "\expandafter\ifx\csname urlstyle\endcsname\relax" + write$ newline$ + " \providecommand{\doi}[1]{doi: #1}\else" + write$ newline$ + " \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi" + write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml2026.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml2026.sty new file mode 100644 index 0000000..47f1fae --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml2026.sty @@ -0,0 +1,767 @@ +% File: icml2026.sty (LaTeX style file for ICML-2026, version of 2025-10-29) + +% This file contains the LaTeX formatting parameters for a two-column +% conference proceedings that is 8.5 inches wide by 11 inches high. +% +% Modified by Hanze Dong, Alberto Bietti, and Felix Berkenkamp, 2025 +% - Revert to times for better compatibility +% - Updated years, volume, location +% - Added preprint version +% - Based on the suggestion from Johan Larsson: +% 1. Added an end-of-document safety check to ensure the affiliations or notice footnote is printed: +% (1) Introduces a flag \newif\ificml@noticeprinted and sets it false by default. +% (2) At end of document, emits a package warning if \printAffiliationsAndNotice{...} was never called. +% 2. \printAffiliationsAndNotice now sets the flag when called: Begins with \global\icml@noticeprintedtrue. +% - Migrated to more recent version of fancyhdr for running title in header +% +% Modified by Johan Larsson, 2025 +% - Use newtx instead of times, aligning serif, sans-serif, typerwriter, +% and math fonts. +% - Use caption package to setup captions instead of manually defining themanually defining them. +% - Formatted icml2026.sty and example_paper.tex +% - Use title case for section title to 2.9 +% - Replace subfigure package with subcaption in example, since it is +% designed to work together with the caption package (which is now required). +% - Remove unused label in example +% +% Modified by Tegan Maharaj and Felix Berkenkamp 2025: changed years, volume, location +% +% Modified by Jonathan Scarlett 2024: changed years, volume, location +% +% Modified by Sivan Sabato 2023: changed years and volume number. +% Modified by Jonathan Scarlett 2023: added page numbers to every page +% +% Modified by Csaba Szepesvari 2022: changed years, PMLR ref. Turned off checking marginparwidth +% as marginparwidth only controls the space available for margin notes and margin notes +% will NEVER be used anyways in submitted versions, so there is no reason one should +% check whether marginparwidth has been tampered with. +% Also removed pdfview=FitH from hypersetup as it did not do its job; the default choice is a bit better +% but of course the double-column format is not supported by this hyperlink preview functionality +% in a completely satisfactory fashion. +% Modified by Gang Niu 2022: Changed color to xcolor +% +% Modified by Iain Murray 2018: changed years, location. Remove affiliation notes when anonymous. +% Move times dependency from .tex to .sty so fewer people delete it. +% +% Modified by Daniel Roy 2017: changed byline to use footnotes for affiliations, and removed emails +% +% Modified by Percy Liang 12/2/2013: changed the year, location from the previous template for ICML 2014 + +% Modified by Fei Sha 9/2/2013: changed the year, location form the previous template for ICML 2013 +% +% Modified by Fei Sha 4/24/2013: (1) remove the extra whitespace after the +% first author's email address (in %the camera-ready version) (2) change the +% Proceeding ... of ICML 2010 to 2014 so PDF's metadata will show up % +% correctly +% +% Modified by Sanjoy Dasgupta, 2013: changed years, location +% +% Modified by Francesco Figari, 2012: changed years, location +% +% Modified by Christoph Sawade and Tobias Scheffer, 2011: added line +% numbers, changed years +% +% Modified by Hal Daume III, 2010: changed years, added hyperlinks +% +% Modified by Kiri Wagstaff, 2009: changed years +% +% Modified by Sam Roweis, 2008: changed years +% +% Modified by Ricardo Silva, 2007: update of the ifpdf verification +% +% Modified by Prasad Tadepalli and Andrew Moore, merely changing years. +% +% Modified by Kristian Kersting, 2005, based on Jennifer Dy's 2004 version +% - running title. If the original title is to long or is breaking a line, +% use \icmltitlerunning{...} in the preamble to supply a shorter form. +% Added fancyhdr package to get a running head. +% - Updated to store the page size because pdflatex does compile the +% page size into the pdf. +% +% Hacked by Terran Lane, 2003: +% - Updated to use LaTeX2e style file conventions (ProvidesPackage, +% etc.) +% - Added an ``appearing in'' block at the base of the first column +% (thus keeping the ``appearing in'' note out of the bottom margin +% where the printer should strip in the page numbers). +% - Added a package option [accepted] that selects between the ``Under +% review'' notice (default, when no option is specified) and the +% ``Appearing in'' notice (for use when the paper has been accepted +% and will appear). +% +% Originally created as: ml2k.sty (LaTeX style file for ICML-2000) +% by P. Langley (12/23/99) + +%%%%%%%%%%%%%%%%%%%% +%% This version of the style file supports both a ``review'' version +%% and a ``final/accepted'' version. The difference is only in the +%% text that appears in the note at the bottom of the first column of +%% the first page. The default behavior is to print a note to the +%% effect that the paper is under review and don't distribute it. The +%% final/accepted version prints an ``Appearing in'' note. To get the +%% latter behavior, in the calling file change the ``usepackage'' line +%% from: +%% \usepackage{icml2025} +%% to +%% \usepackage[accepted]{icml2025} +%%%%%%%%%%%%%%%%%%%% + +\NeedsTeXFormat{LaTeX2e} +\ProvidesPackage{icml2026}[2025/10/29 v2.0 ICML Conference Style File] + +% Before 2018, \usepackage{times} was in the example TeX, but inevitably +% not everybody did it. +% \RequirePackage[amsthm]{newtx} +% 2025.11.6 revert to times for better compatibility +\RequirePackage{times} + +% Use fancyhdr package +\RequirePackage{fancyhdr} +\RequirePackage{xcolor} % changed from color to xcolor (2021/11/24) +\RequirePackage{algorithm} +\RequirePackage{algorithmic} +\RequirePackage{natbib} +\RequirePackage{eso-pic} % used by \AddToShipoutPicture +\RequirePackage{forloop} +\RequirePackage{url} +\RequirePackage{caption} + +%%%%%%%% Options +\DeclareOption{accepted}{% + \renewcommand{\Notice@String}{\ICML@appearing} + \gdef\isaccepted{1} +} + +% === Preprint option === +\DeclareOption{preprint}{%% + \renewcommand{\Notice@String}{\ICML@preprint}%% + \gdef\ispreprint{1}%% +} + +% Distinct preprint footer text +\newcommand{\ICML@preprint}{% + \textit{Preprint. \today.}% +} + +\DeclareOption{nohyperref}{% + \gdef\nohyperref{1} +} + +% Helper flag: show real authors for accepted or preprint +\newif\ificmlshowauthors +\icmlshowauthorsfalse + +%%%%%%%%%%%%%%%%%%%% +% This string is printed at the bottom of the page for the +% final/accepted version of the ``appearing in'' note. Modify it to +% change that text. +%%%%%%%%%%%%%%%%%%%% +\newcommand{\ICML@appearing}{\textit{Proceedings of the +$\mathit{43}^{rd}$ International Conference on Machine Learning}, +Seoul, South Korea. PMLR 306, 2026. +Copyright 2026 by the author(s).} + +%%%%%%%%%%%%%%%%%%%% +% This string is printed at the bottom of the page for the draft/under +% review version of the ``appearing in'' note. Modify it to change +% that text. +%%%%%%%%%%%%%%%%%%%% +\newcommand{\Notice@String}{Preliminary work. Under review by the +International Conference on Machine Learning (ICML)\@. Do not distribute.} + +% Cause the declared options to actually be parsed and activated +\ProcessOptions\relax + +% After options are processed, decide if authors should be visible +\ifdefined\isaccepted \icmlshowauthorstrue \fi +\ifdefined\ispreprint \icmlshowauthorstrue \fi + +\ifdefined\isaccepted\else\ifdefined\ispreprint\else\ifdefined\hypersetup + \hypersetup{pdfauthor={Anonymous Authors}} +\fi\fi\fi + +\ifdefined\nohyperref\else\ifdefined\hypersetup + \definecolor{mydarkblue}{rgb}{0,0.08,0.45} + \hypersetup{ % + pdftitle={}, + pdfsubject={Proceedings of the International Conference on Machine Learning 2026}, + pdfkeywords={}, + pdfborder=0 0 0, + pdfpagemode=UseNone, + colorlinks=true, + linkcolor=mydarkblue, + citecolor=mydarkblue, + filecolor=mydarkblue, + urlcolor=mydarkblue, + } + \fi +\fi + + + +% Uncomment the following for debugging. It will cause LaTeX to dump +% the version of the ``appearing in'' string that will actually appear +% in the document. +%\typeout{>> Notice string='\Notice@String'} + +% Change citation commands to be more like old ICML styles +\newcommand{\yrcite}[1]{\citeyearpar{#1}} +\renewcommand{\cite}[1]{\citep{#1}} + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% to ensure the letter format is used. pdflatex does compile the +% page size into the pdf. This is done using \pdfpagewidth and +% \pdfpageheight. As Latex does not know this directives, we first +% check whether pdflatex or latex is used. +% +% Kristian Kersting 2005 +% +% in order to account for the more recent use of pdfetex as the default +% compiler, I have changed the pdf verification. +% +% Ricardo Silva 2007 +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +\paperwidth=8.5in +\paperheight=11in + +% old PDFLaTex verification, circa 2005 +% +%\newif\ifpdf\ifx\pdfoutput\undefined +% \pdffalse % we are not running PDFLaTeX +%\else +% \pdfoutput=1 % we are running PDFLaTeX +% \pdftrue +%\fi + +\newif\ifpdf %adapted from ifpdf.sty +\ifx\pdfoutput\undefined +\else + \ifx\pdfoutput\relax + \else + \ifcase\pdfoutput + \else + \pdftrue + \fi + \fi +\fi + +\ifpdf +% \pdfpagewidth=\paperwidth +% \pdfpageheight=\paperheight + \setlength{\pdfpagewidth}{8.5in} + \setlength{\pdfpageheight}{11in} +\fi + +% Physical page layout + +\evensidemargin -0.23in +\oddsidemargin -0.23in +\setlength\textheight{9.0in} +\setlength\textwidth{6.75in} +\setlength\columnsep{0.25in} +\setlength\headheight{10pt} +\setlength\headsep{10pt} +\addtolength{\topmargin}{-20pt} +\addtolength{\topmargin}{-0.29in} + +% Historically many authors tried to include packages like geometry or fullpage, +% which change the page layout. It either makes the proceedings inconsistent, or +% wastes organizers' time chasing authors. So let's nip these problems in the +% bud here. -- Iain Murray 2018. +%\RequirePackage{printlen} +\AtBeginDocument{% +\newif\ifmarginsmessedwith +\marginsmessedwithfalse +\ifdim\oddsidemargin=-16.62178pt \else oddsidemargin has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\headheight=10.0pt \else headheight has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\textheight=650.43pt \else textheight has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\marginparsep=11.0pt \else marginparsep has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\footskip=25.0pt \else footskip has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\hoffset=0.0pt \else hoffset has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\paperwidth=614.295pt \else paperwidth has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\topmargin=-24.95781pt \else topmargin has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\headsep=10.0pt \else headsep has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\textwidth=487.8225pt \else textwidth has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\marginparpush=5.0pt \else marginparpush has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\voffset=0.0pt \else voffset has been altered.\\ \marginsmessedwithtrue\fi +\ifdim\paperheight=794.96999pt \else paperheight has been altered.\\ \marginsmessedwithtrue\fi +\ifmarginsmessedwith + +\textbf{\large \em The page layout violates the ICML style.} + +Please do not change the page layout, or include packages like geometry, +savetrees, or fullpage, which change it for you. + +We're not able to reliably undo arbitrary changes to the style. Please remove +the offending package(s), or layout-changing commands and try again. + +\fi} + + +%% The following is adapted from code in the acmconf.sty conference +%% style file. The constants in it are somewhat magical, and appear +%% to work well with the two-column format on US letter paper that +%% ICML uses, but will break if you change that layout, or if you use +%% a longer block of text for the copyright notice string. Fiddle with +%% them if necessary to get the block to fit/look right. +%% +%% -- Terran Lane, 2003 +%% +%% The following comments are included verbatim from acmconf.sty: +%% +%%% This section (written by KBT) handles the 1" box in the lower left +%%% corner of the left column of the first page by creating a picture, +%%% and inserting the predefined string at the bottom (with a negative +%%% displacement to offset the space allocated for a non-existent +%%% caption). +%%% +\def\ftype@copyrightbox{8} +\def\@copyrightspace{ +\@float{copyrightbox}[b] +\begin{center} +\setlength{\unitlength}{1pc} +\begin{picture}(20,1.5) +\put(0,2.5){\line(1,0){4.818}} +\put(0,0){\parbox[b]{19.75pc}{\small \Notice@String}} +\end{picture} +\end{center} +\end@float} + +\setlength\footskip{25.0pt} +\flushbottom \twocolumn +\sloppy + +% Clear out the addcontentsline command +\def\addcontentsline#1#2#3{} + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% commands for formatting paper title, author names, and addresses. + +% box to check the size of the running head +\newbox\titrun + +% general page style +\pagestyle{fancy} +\fancyhf{} +\fancyfoot[C]{\thepage} +% set the width of the head rule to 1 point +\renewcommand{\headrulewidth}{1pt} + +% definition to set the head as running head in the preamble +\def\icmltitlerunning#1{\gdef\@icmltitlerunning{#1}} + +% main definition adapting \icmltitle from 2004 +\long\def\icmltitle#1{% + + %check whether @icmltitlerunning exists + % if not \icmltitle is used as running head + \ifx\undefined\@icmltitlerunning% + \gdef\@icmltitlerunning{#1} + \fi + + %add it to pdf information + \ifdefined\nohyperref\else\ifdefined\hypersetup + \hypersetup{pdftitle={#1}} + \fi\fi + + %get the dimension of the running title + \global\setbox\titrun=\vbox{\small\bf\@icmltitlerunning} + + % error flag + \gdef\@runningtitleerror{0} + + % running title too long + \ifdim\wd\titrun>\textwidth% + \gdef\@runningtitleerror{1}% + % running title breaks a line + \else \ifdim\ht\titrun>6.25pt + \gdef\@runningtitleerror{2}% + \fi + \fi + + % if there is somthing wrong with the running title + \ifnum\@runningtitleerror>0 + \typeout{}% + \typeout{}% + \typeout{*******************************************************}% + \typeout{Title exceeds size limitations for running head.}% + \typeout{Please supply a shorter form for the running head} + \typeout{with \string\icmltitlerunning{...}\space prior to \string\begin{document}}% + \typeout{*******************************************************}% + \typeout{}% + \typeout{}% + % set default running title + \gdef\@icmltitlerunning{Title Suppressed Due to Excessive Size} + \fi + + % no running title on the first page of the paper + \thispagestyle{plain} + + {\center\baselineskip 18pt + \toptitlebar{\Large\bf #1}\bottomtitlebar} +} + +% set running title header +\fancyhead[C]{\small\bf\@icmltitlerunning} + +\gdef\icmlfullauthorlist{} +\newcommand\addstringtofullauthorlist{\g@addto@macro\icmlfullauthorlist} +\newcommand\addtofullauthorlist[1]{% + \ifdefined\icmlanyauthors% + \addstringtofullauthorlist{, #1}% + \else% + \addstringtofullauthorlist{#1}% + \gdef\icmlanyauthors{1}% + \fi% + \ifdefined\hypersetup% + \hypersetup{pdfauthor=\icmlfullauthorlist}% + \fi +} + +\def\toptitlebar{\hrule height1pt \vskip .25in} +\def\bottomtitlebar{\vskip .22in \hrule height1pt \vskip .3in} + +\newenvironment{icmlauthorlist}{% + \setlength\topsep{0pt} + \setlength\parskip{0pt} + \begin{center} + }{% + \end{center} +} + +\newcounter{@affiliationcounter} +\newcommand{\@pa}[1]{% + \ifcsname the@affil#1\endcsname + % do nothing + \else + \ifcsname @icmlsymbol#1\endcsname + % nothing + \else + \stepcounter{@affiliationcounter}% + \newcounter{@affil#1}% + \setcounter{@affil#1}{\value{@affiliationcounter}}% + \fi + \fi% + \ifcsname @icmlsymbol#1\endcsname + \textsuperscript{\csname @icmlsymbol#1\endcsname\,}% + \else + \textsuperscript{\arabic{@affil#1}\,}% + \fi +} + +\newcommand{\icmlauthor}[2]{% + \ificmlshowauthors + \mbox{\bf #1}\,\@for\theaffil:=#2\do{\@pa{\theaffil}} \addtofullauthorlist{#1}% + \else + \ifdefined\@icmlfirsttime\else + \gdef\@icmlfirsttime{1} + \mbox{\bf Anonymous Authors}\@pa{@anon} \addtofullauthorlist{Anonymous Authors} + \fi + \fi +} + +\newcommand{\icmlsetsymbol}[2]{% + \expandafter\gdef\csname @icmlsymbol#1\endcsname{#2} +} + +\newcommand{\icmlaffiliation}[2]{% + \ificmlshowauthors + \ifcsname the@affil#1\endcsname + \expandafter\gdef\csname @affilname\csname the@affil#1\endcsname\endcsname{#2}% + \else + {\bf AUTHORERR: Error in use of \textbackslash{}icmlaffiliation command. Label ``#1'' not mentioned in some \textbackslash{}icmlauthor\{author name\}\{labels here\} command beforehand. } + \typeout{}% + \typeout{}% + \typeout{*******************************************************}% + \typeout{Affiliation label undefined. }% + \typeout{Make sure \string\icmlaffiliation\space follows }% + \typeout{all of \string\icmlauthor\space commands}% + \typeout{*******************************************************}% + \typeout{}% + \typeout{}% + \fi + \else + \expandafter\gdef\csname @affilname1\endcsname{Anonymous Institution, Anonymous City, Anonymous Region, Anonymous Country} + \fi +} + +\newcommand{\icmlcorrespondingauthor}[2]{% + \ificmlshowauthors + \ifdefined\icmlcorrespondingauthor@text + \g@addto@macro\icmlcorrespondingauthor@text{, #1 \textless{}#2\textgreater{}} + \else + \gdef\icmlcorrespondingauthor@text{#1 \textless{}#2\textgreater{}} + \fi + \else + \gdef\icmlcorrespondingauthor@text{Anonymous Author \textless{}anon.email@domain.com\textgreater{}} + \fi +} + +\newcommand{\icmlEqualContribution}{\textsuperscript{*}Equal contribution } + + +% --- ICML 2026: ensure authors do not omit the affiliations/notice footnote --- +\newif\ificml@noticeprinted +\icml@noticeprintedfalse +\AtEndDocument{% + \ificml@noticeprinted\relax\else + \PackageWarningNoLine{icml2026}{% + You did not call \string\printAffiliationsAndNotice{}. If you have no notice,% + call \string\printAffiliationsAndNotice\string{} (empty braces).% + }% + \fi +} + + +\newcounter{@affilnum} +\newcommand{\printAffiliationsAndNotice}[1]{\global\icml@noticeprintedtrue% + \stepcounter{@affiliationcounter}% + {\let\thefootnote\relax\footnotetext{\hspace*{-\footnotesep}\ificmlshowauthors #1\fi% + \forloop{@affilnum}{1}{\value{@affilnum} < \value{@affiliationcounter}}{ + \textsuperscript{\arabic{@affilnum}}\ifcsname @affilname\the@affilnum\endcsname% + \csname @affilname\the@affilnum\endcsname% + \else + {\bf AUTHORERR: Missing \textbackslash{}icmlaffiliation.} + \fi + }.% + \ifdefined\icmlcorrespondingauthor@text + { }Correspondence to: \icmlcorrespondingauthor@text. + \else + {\bf AUTHORERR: Missing \textbackslash{}icmlcorrespondingauthor.} + \fi + + \ \\ + \Notice@String + } + } +} + +\long\def\icmladdress#1{% + {\bf The \textbackslash{}icmladdress command is no longer used. See the example\_paper PDF .tex for usage of \textbackslash{}icmlauther and \textbackslash{}icmlaffiliation.} +} + +%% keywords as first class citizens +\def\icmlkeywords#1{% + \ifdefined\nohyperref\else\ifdefined\hypersetup + \hypersetup{pdfkeywords={#1}} + \fi\fi +} + +% modification to natbib citations +\setcitestyle{authoryear,round,citesep={;},aysep={,},yysep={;}} + +% Redefinition of the abstract environment. +\renewenvironment{abstract} +{% + \centerline{\large\bf Abstract} + \vspace{-0.12in}\begin{quote}} + {\par\end{quote}\vskip 0.12in} + +% numbered section headings with different treatment of numbers + +\def\@startsection#1#2#3#4#5#6{\if@noskipsec \leavevmode \fi + \par \@tempskipa #4\relax + \@afterindenttrue + \ifdim \@tempskipa <\z@ \@tempskipa -\@tempskipa \fi + \if@nobreak \everypar{}\else + \addpenalty{\@secpenalty}\addvspace{\@tempskipa}\fi \@ifstar + {\@ssect{#3}{#4}{#5}{#6}}{\@dblarg{\@sict{#1}{#2}{#3}{#4}{#5}{#6}}}} + +\def\@sict#1#2#3#4#5#6[#7]#8{\ifnum #2>\c@secnumdepth + \def\@svsec{}\else + \refstepcounter{#1}\edef\@svsec{\csname the#1\endcsname}\fi + \@tempskipa #5\relax + \ifdim \@tempskipa>\z@ + \begingroup #6\relax + \@hangfrom{\hskip #3\relax\@svsec.~}{\interlinepenalty \@M #8\par} + \endgroup + \csname #1mark\endcsname{#7}\addcontentsline + {toc}{#1}{\ifnum #2>\c@secnumdepth \else + \protect\numberline{\csname the#1\endcsname}\fi + #7}\else + \def\@svsechd{#6\hskip #3\@svsec #8\csname #1mark\endcsname + {#7}\addcontentsline + {toc}{#1}{\ifnum #2>\c@secnumdepth \else + \protect\numberline{\csname the#1\endcsname}\fi + #7}}\fi + \@xsect{#5}} + +\def\@sect#1#2#3#4#5#6[#7]#8{\ifnum #2>\c@secnumdepth + \def\@svsec{}\else + \refstepcounter{#1}\edef\@svsec{\csname the#1\endcsname\hskip 0.4em }\fi + \@tempskipa #5\relax + \ifdim \@tempskipa>\z@ + \begingroup #6\relax + \@hangfrom{\hskip #3\relax\@svsec}{\interlinepenalty \@M #8\par} + \endgroup + \csname #1mark\endcsname{#7}\addcontentsline + {toc}{#1}{\ifnum #2>\c@secnumdepth \else + \protect\numberline{\csname the#1\endcsname}\fi + #7}\else + \def\@svsechd{#6\hskip #3\@svsec #8\csname #1mark\endcsname + {#7}\addcontentsline + {toc}{#1}{\ifnum #2>\c@secnumdepth \else + \protect\numberline{\csname the#1\endcsname}\fi + #7}}\fi + \@xsect{#5}} + +% section headings with less space above and below them +\def\thesection {\arabic{section}} +\def\thesubsection {\thesection.\arabic{subsection}} +\def\section{\@startsection{section}{1}{\z@}{-0.12in}{0.02in} + {\large\bf\raggedright}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-0.10in}{0.01in} + {\normalsize\bf\raggedright}} +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-0.08in}{0.01in} + {\normalsize\sc\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt +\def\footnoterule{\kern-3pt \hrule width 0.8in \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 0pt +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt +\parskip 6pt + +\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em +\leftmarginvi .5em +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} + +% Revised formatting for figure captions and table titles. +\captionsetup{ + skip=0.1in, + font=small, + labelfont={it,small}, + labelsep=period +} +\captionsetup[table]{position=above} +\captionsetup[figure]{position=below} + +\def\fnum@figure{Figure \thefigure} +\def\fnum@table{Table \thetable} + +% Strut macros for skipping spaces above and below text in tables. +\def\abovestrut#1{\rule[0in]{0in}{#1}\ignorespaces} +\def\belowstrut#1{\rule[-#1]{0in}{#1}\ignorespaces} + +\def\abovespace{\abovestrut{0.20in}} +\def\aroundspace{\abovestrut{0.20in}\belowstrut{0.10in}} +\def\belowspace{\belowstrut{0.10in}} + +% Various personal itemization commands. +\def\texitem#1{\par\noindent\hangindent 12pt + \hbox to 12pt {\hss #1 ~}\ignorespaces} +\def\icmlitem{\texitem{$\bullet$}} + +% To comment out multiple lines of text. +\long\def\comment#1{} + +%% Line counter (not in final version). Adapted from NIPS style file by Christoph Sawade + +% Vertical Ruler +% This code is, largely, from the CVPR 2010 conference style file +% ----- define vruler +\makeatletter +\newbox\icmlrulerbox +\newcount\icmlrulercount +\newdimen\icmlruleroffset +\newdimen\cv@lineheight +\newdimen\cv@boxheight +\newbox\cv@tmpbox +\newcount\cv@refno +\newcount\cv@tot +% NUMBER with left flushed zeros \fillzeros[<WIDTH>]<NUMBER> +\newcount\cv@tmpc@ \newcount\cv@tmpc +\def\fillzeros[#1]#2{\cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi + \cv@tmpc=1 % + \loop\ifnum\cv@tmpc@<10 \else \divide\cv@tmpc@ by 10 \advance\cv@tmpc by 1 \fi + \ifnum\cv@tmpc@=10\relax\cv@tmpc@=11\relax\fi \ifnum\cv@tmpc@>10 \repeat + \ifnum#2<0\advance\cv@tmpc1\relax-\fi + \loop\ifnum\cv@tmpc<#1\relax0\advance\cv@tmpc1\relax\fi \ifnum\cv@tmpc<#1 \repeat + \cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi \relax\the\cv@tmpc@}% +% \makevruler[<SCALE>][<INITIAL_COUNT>][<STEP>][<DIGITS>][<HEIGHT>] +\def\makevruler[#1][#2][#3][#4][#5]{ + \begingroup\offinterlineskip + \textheight=#5\vbadness=10000\vfuzz=120ex\overfullrule=0pt% + \global\setbox\icmlrulerbox=\vbox to \textheight{% + { + \parskip=0pt\hfuzz=150em\cv@boxheight=\textheight + \cv@lineheight=#1\global\icmlrulercount=#2% + \cv@tot\cv@boxheight\divide\cv@tot\cv@lineheight\advance\cv@tot2% + \cv@refno1\vskip-\cv@lineheight\vskip1ex% + \loop\setbox\cv@tmpbox=\hbox to0cm{\hfil {\hfil\fillzeros[#4]\icmlrulercount}}% + \ht\cv@tmpbox\cv@lineheight\dp\cv@tmpbox0pt\box\cv@tmpbox\break + \advance\cv@refno1\global\advance\icmlrulercount#3\relax + \ifnum\cv@refno<\cv@tot\repeat + } + } + \endgroup +}% +\makeatother +% ----- end of vruler + +% \makevruler[<SCALE>][<INITIAL_COUNT>][<STEP>][<DIGITS>][<HEIGHT>] +\def\icmlruler#1{\makevruler[12pt][#1][1][3][\textheight]\usebox{\icmlrulerbox}} +\AddToShipoutPicture{% + \icmlruleroffset=\textheight + \advance\icmlruleroffset by 5.2pt % top margin + \color[rgb]{.7,.7,.7} + \ificmlshowauthors\else + \AtTextUpperLeft{% + \put(\LenToUnit{-35pt},\LenToUnit{-\icmlruleroffset}){%left ruler + \icmlruler{\icmlrulercount}} + %\put(\LenToUnit{1.04\textwidth},\LenToUnit{-\icmlruleroffset}){%right ruler + % \icmlruler{\icmlrulercount}} + } + \fi +} +\endinput diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml_numpapers.pdf b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/icml2026/icml_numpapers.pdf new file mode 100644 index 0000000000000000000000000000000000000000..98d2167980dcea38980d2c58a8630d8be1b0905d GIT binary patch literal 2823 zcmZ`*eLRzUAFiY_k(89AUrAn?ZTH@cP~Jwh&Dus})No_ko9z};PI^U3#ZDz9M`0>; 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HUpnR=R*Yg~ literal 0 HcmV?d00001 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/Makefile b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/Makefile new file mode 100644 index 0000000..9baab4a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/Makefile @@ -0,0 +1,36 @@ +FIGURES_FOLDER := figures +PDFS := \ +$(filter-out $(wildcard $(FIGURES_FOLDER)/*-crop.pdf),$(wildcard $(FIGURES_FOLDER)/*.pdf)) \ +$(filter-out $(wildcard $(FIGURES_FOLDER)/**/*-crop.pdf),$(wildcard $(FIGURES_FOLDER)/**/*.pdf)) +CROPPED_PDFS := $(PDFS:.pdf=-crop.pdf) + +all: main.pdf + +%.pdf: %.tex Makefile $(CROPPED_PDFS) + pdflatex -synctex=1 -interaction=nonstopmode $< + -bibtex $*.aux + pdflatex -synctex=1 -interaction=nonstopmode $< + pdflatex -synctex=1 -interaction=nonstopmode $< + +.PHONY: figures +figures: $(CROPPED_PDFS) + +.PRECIOUS: $(CROPPED_PDFS) +%-crop.pdf: %.pdf Makefile + pdfcrop $< + +.PHONY: clean upgrade +clean: + find . -maxdepth 1 \ + \( -name "*.aux" -o -name "*.bbl" -o -name "*.blg" -o \ + -name "*.log" -o -name "*.out" -o -name "*.pdf" -o \ + -name "*.synctex.gz" \) | xargs $(RM) + find $(FIGURES_FOLDER) -name "*-crop.pdf" | xargs $(RM) + +YEAR := 2025 + +upgrade: + curl -O https://media.neurips.cc/Conferences/NeurIPS$(YEAR)/Styles.zip + unzip -u Styles.zip + mv Styles/neurips_${YEAR}.sty neurips.sty + $(RM) -r Styles.zip Styles diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/extra_pkgs.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/extra_pkgs.tex new file mode 100644 index 0000000..7b8b2e8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/extra_pkgs.tex @@ -0,0 +1,53 @@ +\usepackage[export]{adjustbox} +\usepackage[ruled]{algorithm2e} +\usepackage[inline, shortlabels]{enumitem} +\usepackage[T1]{fontenc} +\usepackage{hyperref} +\usepackage{microtype} +\usepackage{pifont} +\usepackage{xcolor} +\usepackage{xurl} +% Figures and Tables +\usepackage{graphicx} +\usepackage{booktabs} +\usepackage{tabularray} +% Monospaced Code Blocks +\usepackage{listings} +% Math Packages +\usepackage{amsmath, amsfonts} +\usepackage{nicefrac} + +\UseTblrLibrary{booktabs} + +\lstset{ + backgroundcolor=\color{white}, % choose the background color; you must add \usepackage{color} or \usepackage{xcolor}; should come as last argument + basicstyle=\ttfamily, % the size of the fonts that are used for the code + breakatwhitespace=false, % sets if automatic breaks should only happen at whitespace + breaklines=true, % sets automatic line breaking + captionpos=b, % sets the caption-position to bottom + columns=fullflexible, % reduce the column spacing + commentstyle=\color{gray}, % comment style + deletekeywords={}, % if you want to delete keywords from the given language + escapeinside={\%*}{*)}, % if you want to add LaTeX within your code + extendedchars=true, % lets you use non-ASCII characters; for 8-bits encodings only, does not work with UTF-8 + frame=none, % adds no frame around the code + keepspaces=true, % keeps spaces in text, useful for keeping indentation of code (possibly needs columns=flexible) + keywordstyle=\color{blue}, % keyword style + language=C++, % the language of the code + morekeywords={}, % if you want to add more keywords to the set + numbers=none, % where to put the line-numbers; possible values are (none, left, right) + numbersep=5pt, % how far the line-numbers are from the code + numberstyle=\color{black}, % the style that is used for the line-numbers + rulecolor=\color{black}, % if not set, the frame-color may be changed on line-breaks within not-black text (e.g. comments (green here)) + showspaces=false, % show spaces everywhere adding particular underscores; it overrides 'showstringspaces' + showstringspaces=false, % underline spaces within strings only + showtabs=false, % show tabs within strings adding particular underscores + stepnumber=1, % the step between two line-numbers. If it's 1, each line will be numbered + stringstyle=\color{red}, % string literal style + tabsize=4, % sets default tabsize to 4 spaces +} + +\makeatletter +\newcommand{\ssymbol}[1]{\@fnsymbol{#1}} +\newcommand{\romanNumeral}[1]{\expandafter\@slowromancap\romannumeral #1@} +\makeatother diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/main.tex b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/main.tex new file mode 100644 index 0000000..65ece27 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/main.tex @@ -0,0 +1,38 @@ +\documentclass{article} + +\usepackage[nonatbib, final]{neurips} +\usepackage[numbers]{natbib} + +\makeatletter +\renewcommand{\@noticestring}{ + \centering + +} +\makeatother + +\input{extra_pkgs} + +\usepackage{physics} +\usepackage{mathtools} +\DeclarePairedDelimiter\p{(}{)} +\DeclarePairedDelimiter\n{|}{|} +\DeclarePairedDelimiter\B{[}{]} + +\title{} + +\author{ + Bojian Zheng \\ + University of Toronto \\ + \href{mailto:bojian@cs.toronto.edu}{bojian@cs.toronto.edu} +} + +\begin{document} + +\maketitle + + + +% \bibliographystyle{plainnat} +% \bibliography{bibliography} + +\end{document} diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/neurips.sty b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/neurips.sty new file mode 100644 index 0000000..d5297aa --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ml-paper-writing/templates/neurips2025/neurips.sty @@ -0,0 +1,382 @@ +% partial rewrite of the LaTeX2e package for submissions to the +% Conference on Neural Information Processing Systems (NeurIPS): +% +% - uses more LaTeX conventions +% - line numbers at submission time replaced with aligned numbers from +% lineno package +% - \nipsfinalcopy replaced with [final] package option +% - automatically loads times package for authors +% - loads natbib automatically; this can be suppressed with the +% [nonatbib] package option +% - adds foot line to first page identifying the conference +% - adds preprint option for submission to e.g. arXiv +% - conference acronym modified +% +% Roman Garnett (garnett@wustl.edu) and the many authors of +% nips15submit_e.sty, including MK and drstrip@sandia +% +% last revision: April 2025 + +\NeedsTeXFormat{LaTeX2e} +\ProvidesPackage{neurips_2025}[2025/04/02 NeurIPS 2025 submission/camera-ready style file] + +% declare final option, which creates camera-ready copy +\newif\if@neuripsfinal\@neuripsfinalfalse +\DeclareOption{final}{ + \@neuripsfinaltrue +} + +% declare nonatbib option, which does not load natbib in case of +% package clash (users can pass options to natbib via +% \PassOptionsToPackage) +\newif\if@natbib\@natbibtrue +\DeclareOption{nonatbib}{ + \@natbibfalse +} + +% declare preprint option, which creates a preprint version ready for +% upload to, e.g., arXiv +\newif\if@preprint\@preprintfalse +\DeclareOption{preprint}{ + \@preprinttrue +} + +\ProcessOptions\relax + +% determine whether this is an anonymized submission +\newif\if@submission\@submissiontrue +\if@neuripsfinal\@submissionfalse\fi +\if@preprint\@submissionfalse\fi + +% fonts +\renewcommand{\rmdefault}{ptm} +\renewcommand{\sfdefault}{phv} + +% change this every year for notice string at bottom +\newcommand{\@neuripsordinal}{39th} +\newcommand{\@neuripsyear}{2025} +\newcommand{\@neuripslocation}{San Diego} + +% acknowledgments +\usepackage{environ} +\newcommand{\acksection}{\section*{Acknowledgments and Disclosure of Funding}} +\NewEnviron{ack}{% + \acksection + \BODY +} + + +% load natbib unless told otherwise +\if@natbib + \RequirePackage{natbib} +\fi + +% set page geometry +\usepackage[verbose=true,letterpaper]{geometry} +\AtBeginDocument{ + \newgeometry{ + textheight=9in, + textwidth=5.5in, + top=1in, + headheight=12pt, + headsep=25pt, + footskip=30pt + } + \@ifpackageloaded{fullpage} + {\PackageWarning{neurips_2025}{fullpage package not allowed! Overwriting formatting.}} + {} +} + +\widowpenalty=10000 +\clubpenalty=10000 +\flushbottom +\sloppy + + +% font sizes with reduced leading +\renewcommand{\normalsize}{% + \@setfontsize\normalsize\@xpt\@xipt + \abovedisplayskip 7\p@ \@plus 2\p@ \@minus 5\p@ + \abovedisplayshortskip \z@ \@plus 3\p@ + \belowdisplayskip \abovedisplayskip + \belowdisplayshortskip 4\p@ \@plus 3\p@ \@minus 3\p@ +} +\normalsize +\renewcommand{\small}{% + \@setfontsize\small\@ixpt\@xpt + \abovedisplayskip 6\p@ \@plus 1.5\p@ \@minus 4\p@ + \abovedisplayshortskip \z@ \@plus 2\p@ + \belowdisplayskip \abovedisplayskip + \belowdisplayshortskip 3\p@ \@plus 2\p@ \@minus 2\p@ +} +\renewcommand{\footnotesize}{\@setfontsize\footnotesize\@ixpt\@xpt} +\renewcommand{\scriptsize}{\@setfontsize\scriptsize\@viipt\@viiipt} +\renewcommand{\tiny}{\@setfontsize\tiny\@vipt\@viipt} +\renewcommand{\large}{\@setfontsize\large\@xiipt{14}} +\renewcommand{\Large}{\@setfontsize\Large\@xivpt{16}} +\renewcommand{\LARGE}{\@setfontsize\LARGE\@xviipt{20}} +\renewcommand{\huge}{\@setfontsize\huge\@xxpt{23}} +\renewcommand{\Huge}{\@setfontsize\Huge\@xxvpt{28}} + +% sections with less space +\providecommand{\section}{} +\renewcommand{\section}{% + \@startsection{section}{1}{\z@}% + {-2.0ex \@plus -0.5ex \@minus -0.2ex}% + { 1.5ex \@plus 0.3ex \@minus 0.2ex}% + {\large\bf\raggedright}% +} +\providecommand{\subsection}{} +\renewcommand{\subsection}{% + \@startsection{subsection}{2}{\z@}% + {-1.8ex \@plus -0.5ex \@minus -0.2ex}% + { 0.8ex \@plus 0.2ex}% + {\normalsize\bf\raggedright}% +} +\providecommand{\subsubsection}{} +\renewcommand{\subsubsection}{% + \@startsection{subsubsection}{3}{\z@}% + {-1.5ex \@plus -0.5ex \@minus -0.2ex}% + { 0.5ex \@plus 0.2ex}% + {\normalsize\bf\raggedright}% +} +\providecommand{\paragraph}{} +\renewcommand{\paragraph}{% + \@startsection{paragraph}{4}{\z@}% + {1.5ex \@plus 0.5ex \@minus 0.2ex}% + {-1em}% + {\normalsize\bf}% +} +\providecommand{\subparagraph}{} +\renewcommand{\subparagraph}{% + \@startsection{subparagraph}{5}{\z@}% + {1.5ex \@plus 0.5ex \@minus 0.2ex}% + {-1em}% + {\normalsize\bf}% +} +\providecommand{\subsubsubsection}{} +\renewcommand{\subsubsubsection}{% + \vskip5pt{\noindent\normalsize\rm\raggedright}% +} + +% float placement +\renewcommand{\topfraction }{0.85} +\renewcommand{\bottomfraction }{0.4} +\renewcommand{\textfraction }{0.1} +\renewcommand{\floatpagefraction}{0.7} + +\newlength{\@neuripsabovecaptionskip}\setlength{\@neuripsabovecaptionskip}{7\p@} +\newlength{\@neuripsbelowcaptionskip}\setlength{\@neuripsbelowcaptionskip}{\z@} + +\setlength{\abovecaptionskip}{\@neuripsabovecaptionskip} +\setlength{\belowcaptionskip}{\@neuripsbelowcaptionskip} + +% swap above/belowcaptionskip lengths for tables +\renewenvironment{table} + {\setlength{\abovecaptionskip}{\@neuripsbelowcaptionskip}% + \setlength{\belowcaptionskip}{\@neuripsabovecaptionskip}% + \@float{table}} + {\end@float} + +% footnote formatting +\setlength{\footnotesep }{6.65\p@} +\setlength{\skip\footins}{9\p@ \@plus 4\p@ \@minus 2\p@} +\renewcommand{\footnoterule}{\kern-3\p@ \hrule width 12pc \kern 2.6\p@} +\setcounter{footnote}{0} + +% paragraph formatting +\setlength{\parindent}{\z@} +\setlength{\parskip }{5.5\p@} + +% list formatting +\setlength{\topsep }{4\p@ \@plus 1\p@ \@minus 2\p@} +\setlength{\partopsep }{1\p@ \@plus 0.5\p@ \@minus 0.5\p@} +\setlength{\itemsep }{2\p@ \@plus 1\p@ \@minus 0.5\p@} +\setlength{\parsep }{2\p@ \@plus 1\p@ \@minus 0.5\p@} +\setlength{\leftmargin }{3pc} +\setlength{\leftmargini }{\leftmargin} +\setlength{\leftmarginii }{2em} +\setlength{\leftmarginiii}{1.5em} +\setlength{\leftmarginiv }{1.0em} +\setlength{\leftmarginv }{0.5em} +\def\@listi {\leftmargin\leftmargini} +\def\@listii {\leftmargin\leftmarginii + \labelwidth\leftmarginii + \advance\labelwidth-\labelsep + \topsep 2\p@ \@plus 1\p@ \@minus 0.5\p@ + \parsep 1\p@ \@plus 0.5\p@ \@minus 0.5\p@ + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii + \advance\labelwidth-\labelsep + \topsep 1\p@ \@plus 0.5\p@ \@minus 0.5\p@ + \parsep \z@ + \partopsep 0.5\p@ \@plus 0\p@ \@minus 0.5\p@ + \itemsep \topsep} +\def\@listiv {\leftmargin\leftmarginiv + \labelwidth\leftmarginiv + \advance\labelwidth-\labelsep} +\def\@listv {\leftmargin\leftmarginv + \labelwidth\leftmarginv + \advance\labelwidth-\labelsep} +\def\@listvi {\leftmargin\leftmarginvi + \labelwidth\leftmarginvi + \advance\labelwidth-\labelsep} + +% create title +\providecommand{\maketitle}{} +\renewcommand{\maketitle}{% + \par + \begingroup + \renewcommand{\thefootnote}{\fnsymbol{footnote}} + % for perfect author name centering + \renewcommand{\@makefnmark}{\hbox to \z@{$^{\@thefnmark}$\hss}} + % The footnote-mark was overlapping the footnote-text, + % added the following to fix this problem (MK) + \long\def\@makefntext##1{% + \parindent 1em\noindent + \hbox to 1.8em{\hss $\m@th ^{\@thefnmark}$}##1 + } + \thispagestyle{empty} + \@maketitle + \@thanks + \@notice + \endgroup + \let\maketitle\relax + \let\thanks\relax +} + +% rules for title box at top of first page +\newcommand{\@toptitlebar}{ + \hrule height 4\p@ + \vskip 0.25in + \vskip -\parskip% +} +\newcommand{\@bottomtitlebar}{ + \vskip 0.29in + \vskip -\parskip + \hrule height 1\p@ + \vskip 0.09in% +} + +% create title (includes both anonymized and non-anonymized versions) +\providecommand{\@maketitle}{} +\renewcommand{\@maketitle}{% + \vbox{% + \hsize\textwidth + \linewidth\hsize + \vskip 0.1in + \@toptitlebar + \centering + {\LARGE\bf \@title\par} + \@bottomtitlebar + \if@submission + \begin{tabular}[t]{c}\bf\rule{\z@}{24\p@} + Anonymous Author(s) \\ + Affiliation \\ + Address \\ + \texttt{email} \\ + \end{tabular}% + \else + \def\And{% + \end{tabular}\hfil\linebreak[0]\hfil% + \begin{tabular}[t]{c}\bf\rule{\z@}{24\p@}\ignorespaces% + } + \def\AND{% + \end{tabular}\hfil\linebreak[4]\hfil% + \begin{tabular}[t]{c}\bf\rule{\z@}{24\p@}\ignorespaces% + } + \begin{tabular}[t]{c}\bf\rule{\z@}{24\p@}\@author\end{tabular}% + \fi + \vskip 0.3in \@minus 0.1in + } +} + +% add conference notice to bottom of first page +\newcommand{\ftype@noticebox}{8} +\newcommand{\@notice}{% + % give a bit of extra room back to authors on first page + \enlargethispage{2\baselineskip}% + \@float{noticebox}[b]% + \footnotesize\@noticestring% + \end@float% +} + +% abstract styling +\renewenvironment{abstract}% +{% + \vskip 0.075in% + \centerline% + {\large\bf Abstract}% + \vspace{0.5ex}% + \begin{quote}% +} +{ + \par% + \end{quote}% + \vskip 1ex% +} + +% For the paper checklist +\newcommand{\answerYes}[1][]{\textcolor{blue}{[Yes] #1}} +\newcommand{\answerNo}[1][]{\textcolor{orange}{[No] #1}} +\newcommand{\answerNA}[1][]{\textcolor{gray}{[NA] #1}} +\newcommand{\answerTODO}[1][]{\textcolor{red}{\bf [TODO]}} +\newcommand{\justificationTODO}[1][]{\textcolor{red}{\bf [TODO]}} + +% handle tweaks for camera-ready copy vs. submission copy +\if@preprint + \newcommand{\@noticestring}{% + Preprint. Under review.% + } +\else + \if@neuripsfinal + \newcommand{\@noticestring}{% + \@neuripsordinal\/ Conference on Neural Information Processing Systems + (NeurIPS \@neuripsyear).%, \@neuripslocation.% + } + \else + \newcommand{\@noticestring}{% + Submitted to \@neuripsordinal\/ Conference on Neural Information + Processing Systems (NeurIPS \@neuripsyear). Do not distribute.% + } + + % hide the acknowledgements + \NewEnviron{hide}{} + \let\ack\hide + \let\endack\endhide + + % line numbers for submission + \RequirePackage{lineno} + \linenumbers + + % fix incompatibilities between lineno and amsmath, if required, by + % transparently wrapping linenomath environments around amsmath + % environments + \AtBeginDocument{% + \@ifpackageloaded{amsmath}{% + \newcommand*\patchAmsMathEnvironmentForLineno[1]{% + \expandafter\let\csname old#1\expandafter\endcsname\csname #1\endcsname + \expandafter\let\csname oldend#1\expandafter\endcsname\csname end#1\endcsname + \renewenvironment{#1}% + {\linenomath\csname old#1\endcsname}% + {\csname oldend#1\endcsname\endlinenomath}% + }% + \newcommand*\patchBothAmsMathEnvironmentsForLineno[1]{% + \patchAmsMathEnvironmentForLineno{#1}% + \patchAmsMathEnvironmentForLineno{#1*}% + }% + \patchBothAmsMathEnvironmentsForLineno{equation}% + \patchBothAmsMathEnvironmentsForLineno{align}% + \patchBothAmsMathEnvironmentsForLineno{flalign}% + \patchBothAmsMathEnvironmentsForLineno{alignat}% + \patchBothAmsMathEnvironmentsForLineno{gather}% + \patchBothAmsMathEnvironmentsForLineno{multline}% + } + {} + } + \fi +\fi + + +\endinput diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/README.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/README.md new file mode 100644 index 0000000..5b48f97 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/README.md @@ -0,0 +1,58 @@ +# `nature-data` skill + +A data-availability skill for preparing manuscript data statements, repository plans, dataset +citations, and FAIR metadata checks in a Nature / Springer Nature publication style. + +This skill is bilingual-aware. It accepts Chinese author notes covering data availability statements, data requests to the corresponding author, raw data, restricted data, or public databases, then converts them into +submission-ready English with Chinese action notes for the author. + +## What it does + +- drafts ready-to-paste Data Availability statements +- audits weak or incomplete data statements before submission +- maps each supporting dataset to a repository, accession, DOI, or access route +- distinguishes public, controlled-access, third-party, supplementary, and not-applicable cases +- prepares FAIR metadata and DataCite-style dataset citation checks +- flags missing repository records, licences, provenance, embargo details, and access conditions +- aligns Chinese author intent with Nature-style English availability wording + +## Source hierarchy + +- Nature Portfolio and Springer Nature research data policies +- Nature Portfolio reporting standards for availability of data, code, materials, and protocols +- Scientific Data data policies for repository, rawness, preservation, and data citation practice +- FAIR Guiding Principles and DataCite metadata schema + +## File structure + +```text +nature-data/ +├── SKILL.md +├── README.md +├── agents/ +│ └── openai.yaml +└── references/ + ├── fair-metadata-checklist.md + ├── chinese-author-alignment.md + ├── policy-principles.md + ├── repository-and-identifiers.md + ├── source-basis.md + └── statement-patterns.md +``` + +## When to use + +- preparing a Data Availability statement for a Nature-family or Springer Nature journal +- deciding where to deposit data before submission +- revising "available on request" language +- handling controlled-access, human-participant, proprietary, or third-party data +- citing datasets with DOI, accession number, Handle, ARK, or repository record +- checking whether a dataset deposit is FAIR enough for publication +- converting Chinese data-availability notes into precise English submission language + +## Design intent + +The skill should make the availability route explicit for every dataset that supports the paper's +claims. It should not fabricate accessions, licences, restrictions, or repository metadata. When +information is missing, it should return a usable draft plus a short list of items the author must +confirm, preferably with Chinese notes when the user is working from a Chinese draft. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/SKILL.md new file mode 100644 index 0000000..e800f8b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/SKILL.md @@ -0,0 +1,117 @@ +--- +name: nature-data +description: >- + Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, + dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about + Nature data availability, research data sharing, repository selection, accession numbers, + restricted or sensitive data, source data, supplementary datasets, DataCite-style dataset + references, FAIR metadata for academic publication, or Chinese-to-English data availability + wording for Chinese-speaking authors preparing Nature-family submissions. +--- + +# Nature Data Availability Skill + +Use this skill to turn a manuscript's supporting data into a transparent, Nature-ready data +availability package: statement text, repository plan, dataset citations, and missing-information +flags. + +The governing policy layer is Springer Nature / Nature Portfolio data policy. The implementation +layer is FAIR data practice and DataCite-style citation metadata. + +## Chinese-user operating mode + +When the user writes in Chinese, provides a Chinese manuscript note, or asks for "中文对应", +"中英对照", "数据可用性声明", "数据获取声明", "原始数据", "数据存储库", or "受限数据": + +- Accept Chinese input naturally, but draft the final submission-ready statement in English unless + the user explicitly asks for Chinese only. +- Preserve a short Chinese explanation of unresolved decisions when it helps the author act. +- Translate intent, not wording. Chinese phrases such as "可向通讯作者索取" are usually too vague + for Nature-style English unless the restriction and access process are specified. +- Convert Chinese repository/status descriptions into precise publication terms: + `数据可用性声明` -> `Data Availability`; `原始数据` -> `raw data`; + `处理后数据` -> `processed data`; `源数据` -> `source data`; + `补充材料` -> `Supplementary Information`; `受限数据` -> `restricted data`; + `合理请求` -> `reasonable request`, only with reason and review route. +- Use `references/chinese-author-alignment.md` for Chinese terminology, common CN-to-EN failure + modes, and bilingual intake questions. + +## Default stance + +- Treat the Data Availability statement as a link between the paper's claims and the evidence + needed to inspect, reproduce, or reuse them. +- Do not invent DOIs, accession numbers, repository names, licences, embargo dates, ethics + approvals, access committees, or data-use conditions. +- Prefer public, discipline-specific repositories. Use generalist or institutional repositories + only when no suitable community repository exists. +- Describe both newly generated data and reused third-party data. +- If data cannot be openly shared, state why, who controls access, how requests are evaluated, + and what metadata or representative data can still be public. +- Separate data, code, materials, and protocols unless the journal asks for a combined + availability section. +- Keep this skill focused on availability and metadata. Do not rewrite methods, analyze + statistics, or polish the manuscript unless the user asks for those tasks separately. +- Flag "available upon request" as weak unless there is a specific legal, ethical, commercial, or + third-party restriction. + +## Workflow + +1. Identify the target journal and article type. If journal-specific instructions conflict with + this skill, follow the journal. +2. Inventory every dataset needed to support the main and supplementary results: + generated raw data, processed data, figure source data, secondary data, software outputs, + models, tables, images, and files underlying statistical analysis. +3. Classify each dataset into one access route: + `public repository`, `controlled access repository`, `within paper or supplement`, + `reused public source`, `third-party restricted`, `available on justified request`, + or `not applicable`. +4. Choose repository and identifier strategy before drafting text. Prefer DOI, accession number, + Handle, ARK, or stable repository record over personal websites and temporary cloud links. +5. Draft the Data Availability statement using explicit dataset-to-location mapping. +6. Add formal dataset citations for public data that support conclusions. +7. Run the FAIR and metadata audit before finalizing. +8. Return ready-to-paste statement text plus any unresolved fields the author must confirm. + +## Output format + +Unless the user asks for another format, return: + +```text +Data Availability +[ready-to-paste statement] + +Repository and citation actions +- [specific actions or "None"] + +Missing information / risk flags +- [specific flags or "None"] + +中文核对 +- [用中文列出作者需要确认的字段或 "无"] +``` + +When auditing an existing statement, lead with blocking issues first, then provide a revised +version. + +## Related files + +| File | Open when | +|---|---| +| [references/policy-principles.md](references/policy-principles.md) | You need the governing Nature/Springer Nature data-sharing rules or edge-case policy logic | +| [references/chinese-author-alignment.md](references/chinese-author-alignment.md) | The user writes in Chinese, needs bilingual wording, or provides Chinese availability notes | +| [references/statement-patterns.md](references/statement-patterns.md) | You need ready-to-adapt Data Availability statement patterns | +| [references/repository-and-identifiers.md](references/repository-and-identifiers.md) | You need repository choice, accession, DOI, embargo, versioning, or dataset citation guidance | +| [references/fair-metadata-checklist.md](references/fair-metadata-checklist.md) | You need FAIR checks, README metadata, file organization, licences, provenance, or DataCite fields | +| [references/source-basis.md](references/source-basis.md) | You need to justify rules with official sources or check which source supports which rule | + +## Source hierarchy + +Use sources in this order: + +1. Target journal instructions and submission system requirements. +2. Nature Portfolio / Springer Nature data, code, materials, and reporting policies. +3. Repository-specific requirements and domain community standards. +4. FAIR principles and DataCite metadata practice. + +If a policy detail may have changed, verify the current journal page before giving final +submission advice. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/agents/openai.yaml b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/agents/openai.yaml new file mode 100644 index 0000000..56c8ac0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/agents/openai.yaml @@ -0,0 +1,4 @@ +interface: + display_name: "Nature Data" + short_description: "Draft bilingual-aware Nature data statements" + default_prompt: "Help me turn my Chinese or English data notes into a Nature-style Data Availability statement, repository plan, and FAIR metadata checklist." diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/chinese-author-alignment.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/chinese-author-alignment.md new file mode 100644 index 0000000..abac9a8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/chinese-author-alignment.md @@ -0,0 +1,84 @@ +# Chinese Author Alignment + +Use this file when the user writes in Chinese, provides a Chinese Data Availability draft, or asks +for bilingual wording. The goal is not to translate Chinese literally. The goal is to convert the +author's Chinese description into a Nature-ready English availability route. + +## Core terminology + +| 中文 | Preferred English | Notes | +|---|---|---| +| 数据可用性声明 / 数据获取声明 | Data Availability | Use the journal heading `Data Availability`. | +| 本研究产生的数据 | data generated in this study | Include repository and identifier when public. | +| 原始数据 | raw data | Do not call processed tables raw data. | +| 处理后数据 | processed data | State whether processing scripts are available. | +| 源数据 | source data | Usually data underlying figures or tables. | +| 补充材料 / 附录 | Supplementary Information | Use exact file/table names when possible. | +| 公共数据库 | public database / public repository | Name the database and identifier. | +| 数据存储库 | data repository | Prefer repository over platform unless it is a true archive. | +| 登录号 / 编号 | accession number | Use for repositories that assign accession IDs. | +| DOI / 永久链接 | DOI / persistent URL | Prefer DOI when available. | +| 受限数据 | restricted data | Explain legal, ethical, consent, commercial, or third-party reason. | +| 脱敏数据 | de-identified data | Do not say anonymous unless re-identification risk is addressed. | +| 合理请求 | reasonable request | Not enough alone; add route, eligibility, and conditions. | +| 通讯作者 | corresponding author | Avoid making an email the only durable access route if an institutional route exists. | +| 数据使用协议 | data-use agreement | State when required for access. | +| 伦理审批 | ethics approval | Name approval body or requirement when relevant. | +| 代码可用性 | Code Availability | Keep separate if the journal separates data and code. | + +## Chinese-to-English conversion rules + +- Convert "本文所有数据均包含在正文和补充材料中" to a specific claim: + name Source Data files, Supplementary Tables, or repository records. If raw data are absent, say + so as a risk flag rather than pretending they are included. +- Convert "可向通讯作者合理索取" only after adding: + why public sharing is impossible, who reviews requests, eligible requesters, required approvals + or data-use agreement, and expected access route. +- Convert "数据因隐私原因不可公开" into a controlled-access pattern: + state privacy/consent/legal basis, public metadata if available, access committee or institution, + and conditions. +- Convert "商业数据/企业数据不可公开" into a third-party or commercial restriction pattern: + name the provider or owner, request route, and whether derived or aggregate data can be shared. +- Convert "数据将在接收后上传" into an action item: + deposit before submission or create a private reviewer link if the repository supports it. +- Convert "使用公开数据集" into a citation requirement: + include source, version/release/date accessed when relevant, and dataset citation. + +## Bilingual intake questions + +Ask only what is needed for the statement. + +```text +请确认这些字段： +1. 哪些数据支撑主文图、补充图和统计分析？ +2. 每类数据是否已有仓库、DOI、登录号或审稿人私密链接？ +3. 是否包含人类参与者、隐私、商业、第三方授权或国家/机构限制？ +4. 如果数据不能公开，谁负责审核申请？需要伦理审批或数据使用协议吗？ +5. 是否有代码、脚本或 README 能解释 raw data 到 figure source data 的处理过程？ +``` + +## Common Chinese draft fixes + +| 中文原意 | Avoid literal English | Nature-ready direction | +|---|---|---| +| 数据可向通讯作者索取。 | Data are available from the corresponding author upon request. | State the restriction reason and institutional access process. | +| 所有数据见补充材料。 | All data are in the supplementary materials. | Name exact Supplementary Tables/Source Data and flag missing raw data if any. | +| 数据暂未上传。 | Data will be uploaded later. | Deposit now or list repository action as blocking. | +| 使用了公开数据库。 | Public databases were used. | Name database, accession/version/date accessed, and cite dataset. | +| 因隐私不能公开。 | Data cannot be public for privacy reasons. | Add de-identification status, access committee, eligibility, and agreement terms. | + +## Recommended bilingual output + +When useful, provide English first and Chinese second: + +```text +Data Availability +[English statement for submission] + +中文核对 +- 这句话对应中文含义：[brief Chinese explanation] +- 需要作者确认：[missing accession / repository / ethics condition] +``` + +Do not put Chinese explanatory notes inside the final English statement unless the target journal +allows bilingual manuscript text. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/fair-metadata-checklist.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/fair-metadata-checklist.md new file mode 100644 index 0000000..f97e4b3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/fair-metadata-checklist.md @@ -0,0 +1,105 @@ +# FAIR Metadata Checklist + +Use this file to audit whether a dataset deposit is findable, accessible, interoperable, and +reusable enough for a Nature-style submission. + +## Quick FAIR test + +| Principle | Practical check | +|---|---| +| Findable | Dataset has a persistent identifier, rich title/abstract/keywords, searchable repository record, and metadata that names the data identifier. | +| Accessible | Identifier resolves through a standard protocol; access conditions are explicit; metadata stay public even if data are restricted. | +| Interoperable | Files use community formats where possible; metadata use shared vocabulary, units, identifiers, and qualified links to related data/code/publication. | +| Reusable | Licence, provenance, methods, variables, quality-control notes, version, and community-standard metadata are clear enough for reuse. | + +## DataCite core fields + +Mandatory fields commonly expected for DOI-style dataset records: + +- Identifier +- Creator +- Title +- Publisher / repository +- Publication year +- Resource type + +Strongly recommended when available: + +- contributor and role +- description / abstract +- subject keywords +- funding reference +- related identifiers: manuscript preprint/article, code repository, protocol, previous dataset +- version +- licence / rights +- geolocation or temporal coverage for spatial/temporal data +- language + +## Dataset README template + +```text +# [Dataset title] + +## Summary +[One-paragraph description of what the dataset contains and which manuscript results it supports.] + +## Files +- [filename]: [contents, format, size, related figure/table] + +## Variables and units +[Column/field name] | [definition] | [unit] | [allowed values/missing-value code] + +## Methods and provenance +[How data were generated, collected, transformed, filtered, normalised, or aggregated.] + +## Software and environment +[Software, package versions, scripts, notebooks, operating system or instrument software when relevant.] + +## Access and licence +[Licence, access restrictions, data-use agreement, embargo, or controlled-access process.] + +## Citation +[Preferred dataset citation.] +``` + +## File organization + +- Use stable, descriptive filenames instead of local shorthand. +- Keep raw and processed data separate. +- Include a manifest for archives or large multi-file deposits. +- Map source data to exact figure panels and table numbers. +- Preserve units in column names or data dictionaries, not only in manuscript captions. +- Record missing-value codes and filtering decisions. +- Include checksums for large or critical files when the repository does not generate them. + +## Provenance prompts + +Ask the author: + +- What instrument, survey, simulation, database, or processing pipeline produced each file? +- Which script or notebook converts raw data into each figure or statistical table? +- Which samples, time points, conditions, or participants were excluded, and why? +- What version of each third-party dataset was used? +- Are there licences, consent forms, data-use agreements, or ethics approvals that limit reuse? +- Has any data been transformed in a way that prevents reconstruction of the raw values? + +## Licence guidance + +- Prefer a standard open licence when data can be public. +- Use the repository's licence field rather than only writing licence text in the manuscript. +- Use CC0 or CC-BY-style terms only when appropriate for the data and institution. +- Do not apply an open licence to third-party or participant data unless the authors hold the right + to do so. +- For code, use a software licence and archive a release when possible. + +## Final audit + +Block submission until these are resolved: + +- no Data Availability statement for original research +- no identifier or stable access route for data supporting central conclusions +- sensitive data restriction without access procedure +- third-party data with no source or permission route +- public dataset with no licence or README +- claim that data are in the paper when figure source data are absent +- mismatch between manuscript statement, repository record, and supplementary files diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/policy-principles.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/policy-principles.md new file mode 100644 index 0000000..507d7b8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/policy-principles.md @@ -0,0 +1,103 @@ +# Policy Principles + +Use this file when deciding what a Nature-ready data statement must disclose. + +## Governing rules + +- Every original research article needs a Data Availability statement. +- The statement must say what supporting data exist, where they can be found, and any access + conditions. +- The statement must cover data generated by the study and secondary data reused for analysis. +- Public repository deposition is preferred. For community-mandated data types, use the required + repository. +- Reviewers may need access to underlying data and code during evaluation. +- Restrictions are allowed only when they are justified and disclosed. Privacy, consent, endangered + locations, third-party licences, commercial restrictions, and national law are common reasons. +- Restricted data still need a durable access route: named data access committee, institution, + controlled-access repository, application procedure, or responsible group. +- The statement should not hide key evidence in vague language such as "data available upon + reasonable request" unless the reason and process are explicit. + +## Minimal dataset test + +Ask whether an independent reader can inspect or reproduce the paper's central findings from the +available material. + +Include: + +- source data for main figures and key supplementary figures +- raw or sufficiently reusable data, according to community norms +- processed data used for statistics, plots, model training, or validation +- analysis-ready tables if raw data require specialized transformation +- third-party datasets with source, version, date accessed when relevant, and licence/access terms +- representative metadata for restricted datasets, even when records themselves cannot be public + +Exclude only when defensible: + +- data that were not used to support a result +- purely theoretical work that generated or analysed no dataset +- identifiable human data that cannot be anonymised or shared under consent and law + +## Availability routes + +Use one route per dataset or dataset family. + +| Route | Use when | Statement must include | +|---|---|---| +| Public repository | Data can be openly shared | repository, DOI/accession, dataset title or scope, licence if known | +| Controlled repository | Data are sensitive but discoverable | repository, accession/record, access committee or procedure, restrictions | +| Supplementary/source data | Small supporting files are hosted with paper | exact file/table/source-data mapping | +| Reused public data | The study analyses existing public data | original repository/source, identifier, version/date accessed if needed | +| Third-party restricted | Data are licensed or owned by another party | owner/source, why not public, request route, permission condition | +| Request-based access | No repository route is possible | reason, responsible group, eligibility, expected conditions, contact route | +| Not applicable | No datasets were generated or analysed | concise reason; do not use for studies with any empirical data | + +## Data, code, materials, protocols + +Data Availability is not a substitute for code, materials, or protocol availability. + +- Put custom code in a Code Availability section when the journal separates it. +- Mention code in Data Availability only when it is bundled with the dataset and needed to interpret + files. +- For unique biological materials, reagents, cell lines, plasmids, or model organisms, use + persistent identifiers where available and state distribution restrictions separately. +- For protocols, cite protocol repositories or include enough method detail for reproducibility. + +## Sensitive and human-participant data + +For sensitive data, preserve transparency without breaching consent or law. + +State: + +- why open sharing is not possible +- whether anonymised, aggregate, synthetic, or representative data can be shared +- where metadata or a summary record is available +- who reviews access requests +- what approval, data-use agreement, or ethics condition applies +- whether access is limited to non-commercial, academic, local-jurisdiction, or qualified users + +Avoid: + +- naming a single individual as the only durable access route when an institutional route exists +- implying data are available if access depends on impossible or undefined permissions +- promising public release later without a repository, date, and responsible party + +## Submission-stage checks + +Before finalizing, confirm: + +- all accession numbers, DOIs, and URLs resolve +- embargoed/private reviewer links work anonymously where required +- restricted data metadata records are public if the records themselves are not +- supplementary files match statement wording +- data citations appear in the reference list where the journal expects them +- no claim depends on unavailable data without explanation + +## Source notes + +- Springer Nature research data policy requires Data Availability statements for original articles + and asks authors to describe available data, location, and access terms. +- Nature Portfolio reporting standards require prompt availability of data, materials, code, and + associated protocols, with restrictions disclosed to editors at submission. +- Scientific Data policy favours repository deposition, especially for primary data, and requires + repository hosting for Data Descriptor datasets. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/repository-and-identifiers.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/repository-and-identifiers.md new file mode 100644 index 0000000..bf5e618 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/repository-and-identifiers.md @@ -0,0 +1,96 @@ +# Repository and Identifiers + +Use this file when selecting repositories, checking accession strategy, or writing dataset +citations. + +## Repository decision tree + +1. Use a mandated repository when the data type requires it. +2. If no mandate applies, use a discipline-specific, community-recognised repository. +3. If no domain repository fits, use a trusted generalist or institutional repository that provides + persistent identifiers and durable metadata. +4. Do not use personal websites, lab websites, ad hoc cloud folders, or unpublished private drives as + the only availability route. +5. For very large data, use a repository or institutional infrastructure that can preserve metadata + and provide clear access instructions even if bulk files require special transfer. + +## What a repository record should provide + +- persistent identifier: DOI, accession, Handle, ARK, or equivalent stable record +- public landing page with title, creators, abstract/description, repository, date, version, licence +- file list with sizes and formats +- README or data dictionary +- provenance and processing description +- relation to the manuscript and related code +- clear access procedure for restricted data +- versioning or update policy + +## Common repository categories + +Choose according to field norms; this list is not exhaustive. + +| Data type | Typical repository pattern | +|---|---| +| Sequencing / gene expression | GEO, SRA, ENA, ArrayExpress or field-specific omics archive | +| Protein/nucleic acid structures | wwPDB / PDB | +| Small-molecule crystallography | CCDC or other crystallographic archive required by the journal | +| Proteomics | PRIDE or ProteomeXchange member repository | +| Metabolomics | MetaboLights or domain archive | +| Neuroimaging | OpenNeuro, DANDI, NDA, or controlled-access archive when required | +| Clinical or sensitive human data | controlled-access repository such as dbGaP, EGA, controlled institutional archive, or data access committee | +| Earth/environment/space science | PANGAEA, NASA/NOAA/ESA data centres, domain observatories | +| Social science | ICPSR, Dataverse, UK Data Service, OpenICPSR, OSF where appropriate | +| General datasets | Dryad, Zenodo, Figshare, OSF, institutional repository with DOI support | + +Always check the target journal and funder because some data types have mandatory repositories. + +## Identifier rules + +- Prefer final public identifiers before submission. +- If the record is private during review, provide an anonymous reviewer link when the repository + supports it. +- Do not cite temporary sharing links as dataset identifiers. +- Include accession numbers exactly as assigned by the repository. +- Use one identifier per coherent dataset record; avoid burying unrelated data under one unclear DOI. +- Version datasets when files change after review or publication. +- If the dataset has a DOI, cite the DOI rather than only the repository URL. + +## Dataset citation pattern + +Dataset references should include the minimum DataCite-style elements: + +```text +[Creator(s)] ([Publication year]) [Dataset title]. [Repository]. [Identifier]. +``` + +Add version when meaningful: + +```text +[Creator(s)] ([Year]) [Dataset title], version [version]. [Repository]. [DOI/accession]. +``` + +For reused public data, cite the dataset in the reference list when the dataset supports conclusions. +Mentioning it only in the Data Availability statement may be insufficient. + +## Repository readiness checklist + +Before submission: + +- DOI/accession resolves to the intended landing page +- title matches manuscript terminology +- creators and affiliations are correct +- licence is present and compatible with intended reuse +- files open without proprietary software where possible +- README explains columns, units, missing values, transformations, and scripts +- figure source data are clearly mapped to figure panels +- restrictions and access conditions match the manuscript statement +- embargo/private links have been tested outside the author account + +## Red flags + +- "Data available on GitHub" without release DOI or archive +- repository record has no licence +- uploaded zip file has no README or file manifest +- accession exists but is not public, not under embargo, and not available to reviewers +- filenames use local analysis shorthand that readers cannot interpret +- manuscript cites one dataset but results depend on several unlisted secondary sources diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/source-basis.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/source-basis.md new file mode 100644 index 0000000..83cb7b8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/source-basis.md @@ -0,0 +1,54 @@ +# Source Basis + +Use this file when a user asks why a rule exists, wants primary-source justification, or needs to +audit the `nature-data` skill against real policy sources. + +## Source map + +| Skill rule | Primary support | +|---|---| +| Original research needs a Data Availability statement. | Springer Nature research data policy says original articles must include a data availability statement and that it should describe available data, location, and access terms. | +| The statement must cover original and reused data, including data that cannot be public. | Springer Nature policy applies to datasets needed to interpret and replicate conclusions and explicitly includes original/reused data and non-publicly shareable data. | +| Supporting data should be public where possible, with mandatory community repositories for some data types. | Springer Nature policy strongly encourages public availability for datasets supporting analysis and conclusions and mandates sharing for community-endorsed data types. | +| Reviewers may need access to underlying data and code. | Springer Nature policy states peer reviewers are entitled to request access to underlying data and code when needed for evaluation. | +| Nature-style statements must expose the minimum dataset needed to interpret, verify, and extend the work. | Nature Portfolio reporting standards describe transparent access conditions for the minimum dataset needed to interpret, verify, and extend research. | +| Materials, data, code, and protocols should be available without undue qualifications, and restrictions must be disclosed. | Nature Portfolio reporting standards state availability is a publication condition and restrictions must be disclosed at submission and in the manuscript. | +| Repositories are preferred over large supplementary files. | Nature Portfolio reporting standards discourage large datasets in supplementary information and prefer repositories; Scientific Data also strongly encourages repository deposition, especially for primary data. | +| Repository choice should prefer discipline-specific, community-recognised repositories, with generalist or institutional repositories as fallback. | Springer Nature repository guidance recommends discipline-specific community repositories where possible, otherwise generalist or institutional repositories. | +| Sensitive data should use safe sharing, controlled access, metadata records, or trusted environments where appropriate. | Springer Nature sensitive data guidance recommends repository use where possible, controlled-access repositories, trusted research environments, and metadata records for non-public data. | +| Human, non-human sensitive, proprietary, and third-party data need explicit rights and access logic. | Springer Nature sensitive data guidance lists identifiable human data, other sensitive data, and proprietary/third-party data as categories requiring special handling. | +| Rawness and reusability should follow community norms. | Scientific Data policy says data should be provided at a level of rawness allowing reuse in line with accepted community norms. | +| FAIR checks should include findability, accessibility, interoperability, and reusability for humans and machines. | Wilkinson et al. formally describe the FAIR principles and emphasize findable, accessible, interoperable, reusable digital objects for people and machines. | +| Dataset citation metadata should include persistent identifiers and core descriptive fields. | DataCite Metadata Schema defines core metadata properties for accurate and consistent identification, citation, and retrieval of resources. | + +## Official sources + +- Springer Nature, Research data policy: + <https://www.springernature.com/gp/journal-policies/15369670> +- Springer Nature, Data availability statements: + <https://www.springernature.com/gp/authors/research-data-policy/data-availability-statements> +- Springer Nature, Data repository guidance: + <https://www.springernature.com/gp/authors/research-data-policy/recommended-repositories> +- Springer Nature, Sensitive data: + <https://www.springernature.com/gp/authors/research-data-policy/sensitive-data> +- Nature Portfolio, Reporting standards and availability of data, materials, code and protocols: + <https://www.nature.com/nature-portfolio/editorial-policies/reporting-standards> +- Example Nature Portfolio journal reporting standards page: + <https://www.nature.com/npj2dmaterials/editorial-policies/reporting-standards> +- Nature Research, Data availability statements and data citations policy FAQ: + <https://www.nature.com/documents/nr-data-availability-statements-data-citations-faqs.pdf> +- Scientific Data, Data policies: + <https://www.nature.com/sdata/policies/data-policies> +- Wilkinson et al. 2016, The FAIR Guiding Principles for scientific data management and stewardship: + <https://www.nature.com/articles/sdata201618> +- DataCite Metadata Schema: + <https://schema.datacite.org/> + +## Notes for future updates + +- Check target journal instructions first because Nature Portfolio journals can add field-specific + requirements. +- Check DataCite's latest schema before naming version-specific fields. As of 2026-05-01, the + DataCite schema landing page lists Metadata Schema 4.7 as the latest release. +- Keep this file as a source map, not a long policy mirror. Link to official pages rather than + copying full policy text. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/statement-patterns.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/statement-patterns.md new file mode 100644 index 0000000..2bcb864 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-data/references/statement-patterns.md @@ -0,0 +1,153 @@ +# Statement Patterns + +Use these patterns as starting points. Replace bracketed fields with verified information. Delete +any sentence that does not apply. + +For Chinese users, treat the Chinese line under each pattern as author-facing guidance, not as +submission text. Submit the English statement unless the journal explicitly asks otherwise. + +## Public repository, single dataset + +```text +The [raw/processed/source] data supporting the findings of this study are available in +[Repository] under accession [ACCESSION] / at [DOI or persistent URL]. The deposited record +contains [brief contents: e.g. raw measurements, processed tables, figure source data, metadata +and analysis inputs]. +``` + +中文对应：本研究的原始/处理后/源数据已存储在某个正式仓库，并有登录号、DOI 或永久链接。 + +## Public repository, multiple datasets + +```text +The datasets generated in this study are available as follows: [dataset family 1] in +[Repository] under [DOI/accession]; [dataset family 2] in [Repository] under [DOI/accession]; +and figure source data in [Repository/Supplementary Data file] under [identifier or file name]. +``` + +中文对应：不同类型数据分别放在不同仓库或文件中，需要逐一说明，不能笼统写“数据见附件”。 + +## Data in paper and supplementary files only + +Use only when the supporting dataset is genuinely small and fully represented in the article, +source data, or supplementary files. + +```text +All data supporting the findings of this study are included in the paper, its Supplementary +Information, and Source Data files. [Name exact Supplementary Tables/Data files when possible.] +``` + +中文对应：只有当支撑结论的数据确实都在正文、补充材料和 Source Data 中时才这样写。 + +## Reused public data + +```text +This study used publicly available [dataset name/type] from [Repository or source], available under +[DOI/accession/stable URL]. We used [version/release/date accessed, if relevant]. No new primary +[data type] data were generated for this part of the analysis. +``` + +中文对应：使用公开数据库时，需要写清数据库名、版本/发布日期/访问日期和编号，并引用数据集。 + +## Mixed generated and reused data + +```text +Data generated in this study are available in [Repository] under [DOI/accession]. Public datasets +reused in the analysis were obtained from [source 1, identifier/version] and [source 2, +identifier/version]. Source data for [figures/tables] are provided in [location]. +``` + +中文对应：自己产生的数据和复用的公开数据要分开写，避免让读者误以为所有数据都是本研究产生。 + +## Controlled-access human or sensitive data + +```text +The [data type] data supporting this study are not publicly available because [privacy, consent, +legal, ethical or security reason]. A metadata record is available at [repository/accession, if +available]. Qualified researchers may request access from [data access committee/institutional +office/repository procedure] at [contact or URL]. Access requires [ethics approval/data-use +agreement/other conditions] and will be reviewed according to [policy or committee name]. +``` + +中文对应：涉及人类参与者、隐私或伦理限制时，不能只写“因隐私不可公开”；还要写申请路径和审核条件。 + +## Third-party or licensed data + +```text +The [data type/name] data used in this study were obtained from [third-party provider] under +licence and are not publicly redistributable by the authors. Requests for access should be directed +to [provider/contact/URL]. Derived data that can be shared are available in [repository] under +[DOI/accession], subject to [licence or restriction]. +``` + +中文对应：第三方授权数据不能由作者重新分发时，要说明数据所有者和读者应向谁申请。 + +## Commercially restricted data + +```text +The [data type] data are subject to commercial restrictions and cannot be made publicly available. +Requests for access may be directed to [company/data owner/contact or URL] and are subject to +[approval/licence/payment/confidentiality terms]. The authors provide [summary statistics, +metadata, synthetic data, or source data] in [location] to support interpretation of the results. +``` + +中文对应：企业或商业数据不可公开时，需要说明商业限制、申请对象，以及是否有汇总数据或元数据可公开。 + +## Embargoed data + +Use only when the repository supports embargo and the journal permits it. + +```text +The [data type] data have been deposited in [Repository] under [DOI/accession] and are under +embargo until [date/event]. Reviewers can access the data using [private reviewer link or +repository access route]. The data will become publicly available at [DOI/accession] when the +embargo ends. +``` + +中文对应：如果数据暂时不公开，必须已有仓库记录、审稿访问方式和明确解封时间或条件。 + +## Request-based access with justified restriction + +```text +The [data type] data are not publicly available because [specific reason]. Requests for access may +be sent to [institutional group/contact route], and will be considered for [eligible purpose/users] +subject to [approval, agreement, or legal condition]. [Public metadata/aggregate data/source data] +are available at [location]. +``` + +中文对应：“合理请求”只有在说明原因、接收机构、审核条件和可公开元数据后才可接受。 + +## No datasets generated or analysed + +Use sparingly. + +```text +No datasets were generated or analysed during the current study. +``` + +中文对应：只有确实没有生成或分析任何数据时才能使用，经验研究通常不适用。 + +For theory papers, be more specific: + +```text +This work is theoretical and does not generate or analyse empirical datasets. +``` + +## Anti-patterns to revise + +| Weak wording | Why it fails | Stronger move | +|---|---|---| +| Data are available upon request. | No reason, route, eligibility, or durability. | Add restriction reason, responsible access body, conditions, and metadata. | +| Data are available from the corresponding author on reasonable request. | Often a literal translation of "可向通讯作者合理索取"; not durable or specific enough. | Use an institutional/repository access route and define review conditions. | +| Data will be uploaded after acceptance. | No current repository or durable identifier. | Deposit before submission or provide a private reviewer link. | +| All data are in the manuscript. | Often false for figures/statistics. | Name exact source data, supplementary files, and omitted raw data. | +| Data are proprietary. | Does not say who controls access. | Name owner/provider and access route. | +| N/A. | Nature-style instructions usually require an explanation. | State why no datasets were generated or analysed. | + +## Audit questions + +- Which result would fail if this dataset were unavailable? +- Is the route durable beyond the corresponding author's current email address? +- Can a reader tell what each identifier contains? +- Are restrictions specific enough for an editor to judge them? +- Are reused datasets cited, not merely mentioned? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/README.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/README.md new file mode 100644 index 0000000..256930b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/README.md @@ -0,0 +1,65 @@ +# `nature-polishing` skill + +An academic-writing skill for polishing, restructuring, and translating manuscript prose into concise `Nature`-leaning English. + +Source hierarchy: + +- `Main strategy`: the course notes in `Chapter1-Week1-7 full version.pdf` +- `Published article patterns`: curated Nature and Nature Communications examples +- `Reference support`: `Academic-Phrasebank-Navigable-PDF-2023.pdf` + +## What changed + +- The main `SKILL.md` now follows the first PDF's architecture: paper type, reader workflow, hourglass structure, writing order, section responsibilities, intellectual debt, and AI/ethics boundaries. +- Article-level polishing can now use the published-paper pattern reference for abstracts, introductions, Results, Discussions, conclusions, and titles. +- The reference folder now serves a narrower role: phrase families, move templates, and style checks derived from the second PDF. +- The skill now distinguishes `research papers` from `methods papers`. +- The skill treats `core argument ownership` as a central rule, not a side note. + +## File structure + +```text +nature-polishing/ +├── SKILL.md +├── README.md +└── references/ + ├── published-article-patterns.md + ├── phrasebank-playbook.md + ├── section-moves.md + ├── style-guardrails.md + └── writing-strategy.md +``` + +## When to use + +- polishing an abstract, introduction, results, discussion, conclusion, or title +- polishing a methods section or a methods paper with fair-comparison logic +- translating Chinese academic text into publishable English +- tightening section logic before submission +- softening overclaims and fixing evidence-weighted language +- making prose read more like strong journal English without inventing content + +## Design intent + +The skill should: + +- preserve facts, citation intent, and author responsibility +- make the first PDF the governing writing strategy +- improve rhetorical sequencing at paragraph level +- keep sentences short and readable +- use the second PDF only as the phrase and reference layer +- avoid generic AI prose and unsupported claims + +## Reference map + +- `section-moves.md`: section order and move patterns +- `published-article-patterns.md`: writing patterns from curated Nature and Nature Communications articles +- `phrasebank-playbook.md`: hedging, transitions, evidence, limitations, future work +- `style-guardrails.md`: British style, articles, abbreviations, units, register, overclaim control +- `writing-strategy.md`: paragraph- and section-level argument logic + +## Notes + +- The skill is designed for polishing and restructuring, not for fabricating scientific content. +- The main strategic rules live in `SKILL.md`; the reference files should not overrule them. +- The reference files are intentionally selective. They are meant to guide choices, not to encourage boilerplate copying. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/SKILL.md new file mode 100644 index 0000000..45f9eb3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/SKILL.md @@ -0,0 +1,386 @@ +--- +name: nature-polishing +description: Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English. +version: 5.0.2 +author: Yuan1z skill rebuilt from course notes plus Academic Phrasebank +--- + +# Nature-Style Academic Polishing + +Use this skill to improve scientific writing at two levels: + +- `main strategy`: paper architecture, published-article patterns, section logic, reader workflow, evidence thresholds, and ethics +- `reference support`: reusable phrase families, move patterns, transitions, and style checks + +The main strategy should come from the course notes in `Chapter1-Week1-7` and +the curated article-pattern reference. The wording layer should come from +`Academic Phrasebank`. + +## Default stance + +- Language serves argument. Do not polish sentences while leaving the reasoning broken. +- Write with empathy for the reader: relevance first, then novelty, then trust, then reuse, then meaning. +- There should be no mystery for the writer, but there may be one for the reader. +- Do not invent data, references, mechanisms, or novelty claims. +- Do not let AI draft the paper's core scientific argument from scratch. +- If the draft is Chinese or structurally rough, reconstruct the logic first and the prose second. +- Avoid em dashes in polished output by default. Prefer commas, parentheses, or full stops. Use colons sparingly unless the user explicitly asks to preserve dash-based punctuation or wants a colon-led style. + +## When to open extra files + +These files are reference support. Use them after the section's rhetorical job is clear. + +| File | Open when | +|---|---| +| [references/published-article-patterns.md](references/published-article-patterns.md) | You need Nature/Nature Communications article-level writing patterns for abstracts, introductions, Results, Discussion, conclusions, or titles | +| [references/writing-strategy.md](references/writing-strategy.md) | You need paragraph- or section-level argument repair before sentence polishing | +| [references/section-moves.md](references/section-moves.md) | You need section-specific move orders or phrase patterns derived from Academic Phrasebank | +| [references/phrasebank-playbook.md](references/phrasebank-playbook.md) | You need hedging, transition, evidence, limitation, or future-work phrase families | +| [references/style-guardrails.md](references/style-guardrails.md) | You need academic-style checks, paragraph/sentence checks, article use, register, or mechanics | + +## Core architecture + +### 1. Identify the paper type first + +Before editing, determine what kind of paper or section this is. + +- `Research paper`: the reader asks why the phenomenon matters, what was done, what was found, and what it means. +- `Methods paper`: the reader asks whether the method works, whether it is reproducible, and whether it is better under a fair comparison. +- `Hypothesis-based work`: the argument tries to establish or rule out a causal explanation. +- `Algorithmic or device work`: the argument proposes a procedure, tool, or system and must show that it performs reliably and advantageously. + +Do not use one narrative logic for all paper types. + +For article-level rewrites, especially abstracts, introductions, Results openings, +Discussion paragraphs, conclusions, and titles, also apply the writing patterns in +`references/published-article-patterns.md`. + +### 2. Write for the reader, not for the draft chronology + +Most readers follow a stable sequence: + +1. Is this relevant to me? +2. What is new here? +3. Do I trust it? +4. Can I reuse it? +5. What does it mean, and where are the boundaries? + +Polishing should help the paper answer these questions in this order. + +### 3. Use the hourglass structure + +Strong papers often mirror an hourglass: + +- `Introduction`: open broadly, then narrow to the specific gap, question, hypothesis, methods, and study +- `Discussion/Conclusion`: widen again, connecting the findings back to the literature and explaining how the knowledge gap was filled + +If a paragraph or section violates this architecture, rebuild it before polishing wording. + +### 4. Use the correct writing order + +For a research article, a productive writing order is: + +1. Results +2. Introduction and Conclusion +3. Title +4. Discussion +5. Materials and Methods +6. Authors +7. Abstract + +For a methods paper, a productive writing order often begins with: + +1. Methods +2. Results +3. Introduction +4. Conclusion +5. Discussion +6. Abstract + +The skill should follow the logic of evidence and argument, not the raw order in which the user drafted sentences. + +### 5. Protect the core argument + +The paper's core argument includes: + +- the scientific question the paper actually answers +- why that question matters +- how the work differs from existing research +- what the results imply +- how the main line of reasoning unfolds + +AI may help polish, structure, or compare phrasings. AI should not invent or author the core argument. If the argument is weak or unclear, expose that weakness rather than hiding it under polished language. + +### 6. Diagnose the failure mode before editing + +Before rewriting, identify the main problem: + +- wrong paper type logic +- missing gap or poor positioning +- claim without evidence +- evidence without a clear claim +- missing boundary or limitation +- Results and Discussion mixed together +- weak title or abstract signal +- sentence-level clutter only + +Prioritize in this order: + +`paper type -> section job -> paragraph logic -> claim/evidence/boundary -> sentence polish` + +## Section responsibilities + +### Introduction + +The Introduction should: + +- tell the reader why the work matters +- explain what gap it fills +- explain why that gap matters +- state what is already known +- state what remains unresolved +- state what question the paper asks +- indicate how the study addresses it + +Do not summarize the Results section here. Do not summarize the Conclusion here. + +### Results + +Results are a summary of the data collected to address the problem stated in the Introduction. + +Results writing should: + +- stay mainly in past tense +- report what was observed, under what conditions, and with what quantitative support +- use statistics correctly and sparingly +- use supplementary data sparingly + +Results should answer `what happened`, not `what it ultimately means`. + +### Discussion + +Discussion should answer: + +- how the work fits within the broader field +- what has been added to understanding +- who should be credited for earlier work +- whether the findings support, complicate, or revise earlier results +- how the findings are interpreted +- when that interpretation may fail + +Short rule: + +- `Results = what we observed` +- `Discussion = how we understand it, and when it may fail` + +### Conclusion + +Use the three-part close: + +1. restate the central contribution +2. summarize the key evidence or outcome +3. state the implication with a boundary + +Do not introduce new data in the conclusion. Always run an overclaim check here. + +### Title + +A strong title should: + +- tell the reader what to expect +- avoid unnecessary technical language +- be easy to search +- be substantiated by data +- create curiosity without sacrificing credibility + +Use `curiosity with credibility`, not empty cleverness. A hook is only acceptable if the claim remains fully defensible. + +### Materials and Methods + +Methods should be specific, complete, transparent, and reproducible. + +Another group should be able to determine: + +- whether the work conforms to ethical norms +- what materials and conditions were used +- which key parameters, controls, and replicates were used +- how data were processed and analysed +- which statistical tests and software versions were used + +It is acceptable to abbreviate by citing an earlier report only when that report truly contains the necessary detail. + +Never leave vague phrases such as: + +- `under standard conditions` +- `using routine methods` +- `data were analyzed statistically` +- `differences were significant` +- `samples were randomly assigned` +- `the method was validated` + +Replace them with the actual reproducible information. + +### Methods-paper variant + +In a methods paper, the Results section must show the advantages of the method over existing methods. Typical questions are: + +- Is it more reliable? +- Is it faster? +- Does it require fewer resources? +- Is the comparison fair and reproducible? + +The Methods section in a methods paper may need additional detail such as: + +- axioms, conditions, and assumptions +- hardware and software environment +- mathematical derivations +- evaluation protocol +- datasets, baselines, metrics, splits, and hyperparameters + +### Abstract + +The abstract is a mini-paper: + +`context/problem -> gap/objective -> approach -> key results -> implication` + +It should answer: + +1. What question was addressed? +2. How was it addressed? +3. What was found? +4. Why should anyone care? + +Some journals require a strict abstract format. Follow the journal if it conflicts with the generic pattern. + +## Sentence and paragraph control + +### Sentence rules + +- In polished prose, aim for sentences in the `10-30` word range. +- Keep every sentence at `<= 30` words. +- Do not produce full sentences under `10` words unless the user explicitly asks for terse style or the item is a heading, label, or fixed technical expression. +- If any sentence exceeds `20` words, check whether it contains more than one main proposition. +- Split overloaded sentences rather than polishing them cosmetically. +- The last sentence of a paragraph often becomes the longest and weakest. Check it explicitly. +- Prefer one core subject-verb proposition per sentence. +- Do not use em dashes as prose punctuation in the polished version unless the user explicitly requests them. Rewrite with commas, parentheses, or shorter sentences instead. Use colons only when they add clear structural value. + +### Paragraph rules + +- Each paragraph should have one controlling idea followed by support. +- Supporting material may include data, comparison, explanation, consequence, literature, or limitation. +- If a new idea appears, start a new paragraph instead of stacking it onto the old one. +- Use thematic linking, not repetitive `This suggests ...` openings. + +### Results vs Discussion sentence types + +Results sentences usually report: + +- `was detected` +- `increased` +- `showed` +- `enabled` +- `achieved` + +Discussion sentences usually interpret: + +- `may reflect` +- `suggests that` +- `could indicate` +- `is likely due to` +- `may facilitate` + +Do not let a Results paragraph drift into Discussion syntax unless the transition is intentional. + +### Chinese-to-English mode + +When the source is Chinese or strongly Chinese-influenced English: + +- extract the core propositions first +- do not translate clause-by-clause mechanically +- reconstruct explicit logical links: contrast, cause, implication, limitation +- verify terminology, causality, hedging, and disciplinary nuance +- keep key technical terms stable + +## Citation, ethics, and AI boundaries + +### Intellectual debt + +Originality is usually an amendment, combination, or extension of prior knowledge. A careful writer acknowledges that debt openly. + +Do not minimize others' contributions just to make the present work seem more original. + +### Position attribution clearly + +Make it obvious: + +- how the paper builds on prior work +- who was responsible for the earlier idea, method, data, or interpretation +- where the reader can locate the source + +### Cite the source you actually read and verified + +- Cite paper `A` for `A`'s own data, methods, claims, or conclusions. +- Cite paper `B` for `B`'s interpretation, comparison, critique, or commentary on `A`. +- Avoid leaning on secondary sources when the source article can be cited directly. + +### What needs citation + +- someone else's ideas +- data +- methods +- wording +- structure +- images +- distinctive interpretation + +Do not assume internet material is public domain just because it is online. + +### Proofreading checks + +Always verify: + +- grammatical errors +- typographical errors +- figure numbering +- missing citations +- whether the paper is a pleasure or an ordeal to read + +### AI traffic-light boundary + +`Green`: generally acceptable with author verification + +- improve grammar, clarity, concision, or tone +- generate outline options or paragraph structures +- produce alternative titles or abstract phrasings +- summarize literature for categorization, not as a substitute for reading +- translate with terminology and hedging checks + +`Yellow`: allowed only with strong human control + +- explain methods or results for wording support +- draft reviewer-response frameworks that are then checked line by line +- help with code or statistics explanations only if outputs are reproduced and validated + +`Red`: generally inappropriate + +- ask AI to draft the paper's core argument from scratch +- insert AI-generated references, data, or claims without checking them +- upload unpublished manuscripts, sensitive data, or peer-review material to public models +- use AI to fabricate, manipulate, or conceal substantive image creation + +The main danger is not that AI cannot write. The main danger is that it can write incorrectly with great confidence. + +## Output format + +Default output: + +1. The polished text as plain prose, not in a code block. +2. `Revision notes:` with `3-5` short bullets on the major structural and stylistic changes. +3. If the rewrite changed section logic, say so explicitly. + +If the user asks for side-by-side revision, provide: + +- `Original` +- `Polished` +- `Why changed` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/phrasebank-playbook.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/phrasebank-playbook.md new file mode 100644 index 0000000..360ae4d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/phrasebank-playbook.md @@ -0,0 +1,162 @@ +# Phrasebank Playbook + +Use this file after the main argument and section role are already clear. It is a phrasebank layer derived from `Academic Phrasebank`, not a substitute for deciding what the paragraph is trying to do. + +## Evidence strength + +Choose verbs that match the evidence. + +### Strong + +- `show` +- `demonstrate` +- `establish` +- `reveal` +- `identify` + +Use only when the design and data justify a strong claim. + +### Moderate + +- `suggest` +- `indicate` +- `support the view that` +- `are consistent with` +- `point to` + +Use when the interpretation is plausible but not definitive. + +### Speculative + +- `may reflect` +- `could arise from` +- `appears to` +- `seems likely` +- `might be explained by` + +Use when moving beyond direct observation. + +## Evidence collocations + +Adjectives for evidence: + +- weak: `limited`, `scant`, `insufficient` +- developing: `growing`, `emerging`, `accumulating` +- strong: `robust`, `reliable`, `convincing`, `considerable` + +Useful patterns: + +- `The evidence presented here suggests that ...` +- `The available evidence supports the view that ...` +- `Current evidence raises important questions about ...` +- `The data point to a need for ...` + +## Transition families + +### Contrast + +- `however` +- `by contrast` +- `nevertheless` +- `despite this` +- `whereas` + +### Addition + +- `furthermore` +- `in addition` +- `moreover` +- `also` + +### Consequence + +- `therefore` +- `thus` +- `consequently` +- `as a result` +- `thereby` + +### Qualification + +- `notably` +- `importantly` +- `approximately` +- `in part` +- `at least in this cohort` + +Prefer the smallest connective that does the job. Do not decorate every sentence with a transition word. + +## Paragraph linking without sounding repetitive + +Prefer these patterns over repeated `This suggests`: + +- restate the noun: `Such heterogeneity ...` +- definite noun phrase: `The resulting gradient ...` +- participial summary: `Taken together, ...` +- zero-connective progression when the logic is already obvious + +Limit demonstrative-led openings. One per paragraph is usually enough. + +## Gap language + +Use gap statements that are precise rather than dramatic: + +- `remains poorly understood` +- `has not been examined in ...` +- `has received limited attention` +- `few studies have addressed ...` +- `evidence remains sparse for ...` + +Avoid: + +- `no one has ever studied` +- `completely unknown` +- `ignored by all previous work` + +## Comparison with prior work + +To align with earlier work: + +- `These results are consistent with ...` +- `This finding accords with ...` +- `Our observations broadly support ...` + +To mark divergence fairly: + +- `In contrast to earlier reports, ...` +- `This finding differs from ...` +- `One possible reason for this discrepancy is ...` + +## Limitation language + +Useful patterns: + +- `These findings should be interpreted with caution because ...` +- `A limitation of this study is that ...` +- `The generalisability of these results is limited by ...` +- `We cannot exclude the possibility that ...` +- `Another source of uncertainty is ...` + +Pair limitation language with the actual source of uncertainty, not with vague modesty. + +## Implication language + +Useful patterns: + +- `An implication of this is that ...` +- `These findings may help to explain ...` +- `These data support further investigation of ...` +- `This work has implications for ...` + +Implications should stay within the evidence boundary. + +## Future-work language + +Useful patterns: + +- `Further work is needed to determine whether ...` +- `Future studies should examine ...` +- `A useful next step would be to ...` +- `Larger studies are required to validate ...` + +Future work should emerge from an actual limitation, uncertainty, or opportunity. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/published-article-patterns.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/published-article-patterns.md new file mode 100644 index 0000000..d84bb57 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/published-article-patterns.md @@ -0,0 +1,114 @@ +# Published Article Patterns + +Use this file when polishing should improve scientific argument, not just English. +The patterns below are distilled from curated Nature and Nature Communications +research articles across materials, energy systems, construction decarbonization +and machine learning. Do not copy their wording. Use the patterns to diagnose +and reshape the user's manuscript. + +## Abstract pattern + +Strong abstracts usually move in six steps: + +1. name the field-scale problem or opportunity +2. show why existing approaches are incomplete +3. state the specific intervention or method +4. give the decisive result with scale, comparison or constraint +5. explain why the result changes what is possible +6. close with scope, application or boundary + +Polishing rule: if an abstract starts with the method, add the problem and gap +first. If it ends with enthusiasm, replace it with a bounded implication. + +## Introduction pattern + +High-performing introductions often use `scale -> bottleneck -> prior attempts -> +missing capability -> present study`. + +- `Scale`: quantify why the problem matters, preferably with field-level stakes. +- `Bottleneck`: name the physical, computational, clinical or practical barrier. +- `Prior attempts`: acknowledge existing strategies fairly. +- `Missing capability`: explain what those strategies still cannot do. +- `Present study`: state what the paper does, not what it hopes to do. + +Polishing rule: keep the gap narrow enough that the study can actually fill it. +Avoid novelty claims that depend on weakening prior work. + +## Results pattern + +Results sections usually work best as an evidence ladder: + +1. overview of the system, workflow or design space +2. validation that the platform works under controlled conditions +3. primary performance result +4. comparison with baselines or current practice +5. mechanism, interpretation or diagnostic analysis +6. scale-up, generalization or real-world application + +Each Results paragraph should begin with the question or test, then report the +observation, then give the quantitative or comparative support. Interpretation +should be brief unless the paragraph is explicitly bridging into Discussion. + +## Discussion pattern + +Effective Discussion writing starts from the central advance and then widens: + +- what the study demonstrates +- why the evidence is credible +- how it changes an existing workflow, design rule or conceptual boundary +- what constraints remain +- what future work is enabled, without promising untested outcomes + +Do not turn the Discussion into a second Results section. Use it to state what +the results mean and where that meaning stops. + +## Conclusion pattern + +Nature-style conclusions are compact. They usually combine: + +1. the contribution in one sentence +2. the mechanism, performance or feasibility evidence that supports it +3. the scale or application implied by the work +4. one boundary condition, if the claim could otherwise overreach + +Polishing rule: remove new data from conclusions. Preserve confidence, but add +scope control. + +## Title pattern + +Strong titles are concrete and searchable. They often combine: + +- object or system +- action or capability +- application, scale or consequence + +Prefer titles that reveal the central scientific move. Avoid titles that sound +like grant aims, slogans or broad fields. + +## Sentence-level pattern + +Published prose often looks simple because each sentence does one job: + +- background sentence: field stake or known fact +- gap sentence: unresolved limitation +- method sentence: what was done +- result sentence: observed effect plus condition +- comparison sentence: baseline or previous state +- implication sentence: meaning with scope +- limitation sentence: boundary or dependency + +When polishing, label each sentence by job. If two jobs compete in one sentence, +split it or subordinate one job. + +## Overclaim checks from article patterns + +Flag and soften claims when: + +- a laboratory or simulation result is written as an immediate field-wide solution +- a single material, model or system is described as universally applicable +- correlation is rewritten as mechanism +- a comparison lacks a fair baseline +- a future application is stated as an achieved outcome + +Good Nature-leaning prose can be ambitious, but the ambition must be attached to +evidence, scale and boundary. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/section-moves.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/section-moves.md new file mode 100644 index 0000000..0699fcf --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/section-moves.md @@ -0,0 +1,240 @@ +# Section Moves + +Use this file only after the main section logic has been decided in `SKILL.md`. This file is for phrase-level and move-level support derived from `Academic Phrasebank`, not for deciding the paper's overall writing strategy. + +## Introduction + +Questions this section must answer: + +1. Why does the topic matter? +2. What is already known? +3. What is still missing or contested? +4. What does the present study ask or do? + +Preferred move order: + +1. establish importance +2. summarize what is known +3. identify a gap, limitation, or controversy +4. state the study aim +5. indicate value or approach + +Useful phrase families: + +- `Recent years have seen increasing interest in ...` +- `X is a central issue in ...` +- `Previous studies have shown that ...` +- `However, the mechanisms underlying ... remain poorly understood.` +- `Few studies have examined ...` +- `Here, we investigate whether ...` +- `This work provides ...` + +Avoid: + +- long historical throat-clearing +- detailed results +- inflated novelty claims before the gap is defined + +## Literature Review + +Questions this section must answer: + +1. What lines of work define the field? +2. What has been established? +3. Where do findings diverge or remain incomplete? +4. Which gap matters for the present paper? + +Preferred move order: + +1. describe the scope of existing work +2. identify dominant approaches +3. state what has been established +4. note disagreements or contradictions +5. isolate the missing piece + +Useful phrase families: + +- `A substantial body of work has focused on ...` +- `Most studies have relied on ...` +- `Previous work has established that ...` +- `Findings have been mixed regarding ...` +- `By contrast, little attention has been paid to ...` +- `No study has yet examined ...` + +Avoid: + +- citation-by-citation summary +- treating all prior work as uniformly weak + +## Methods + +Question this section must answer: + +- Could another group reproduce the work from this description, or from this description plus a clearly cited protocol? + +Preferred move order: + +1. design or cohort +2. materials or data source +3. procedure +4. outcome measures +5. analysis and statistics +6. ethics when relevant + +Useful phrase families: + +- `A cross-sectional study was undertaken to ...` +- `Samples were collected from ...` +- `X was quantified using ...` +- `We used ... to assess ...` +- `Differences were analysed using ...` +- `All analyses were performed in ...` + +Avoid: + +- `under standard conditions` +- `using routine methods` +- `data were analysed statistically` + +## Results + +Question this section must answer: + +- What was observed, under which condition, and with what evidence? + +Preferred move order: + +1. orient the reader to the figure, table, or experiment +2. state the main observation +3. add quantitative detail +4. note expected or unexpected patterns +5. compare with prior work only if it clarifies the result + +Useful phrase families: + +- `Figure 1 shows ...` +- `As shown in Table 1, ...` +- `The most notable finding was that ...` +- `Contrary to expectations, ...` +- `No significant difference was observed in ...` +- `These results are consistent with ...` +- `In contrast to earlier reports, ...` + +Avoid: + +- discussion-length mechanism explanations +- repeating every visual detail from the figure + +## Discussion + +Questions this section must answer: + +1. What do the main findings mean? +2. How do they relate to earlier work? +3. Which explanations are plausible? +4. What limitations constrain interpretation? +5. What follows from the findings, and what does not? + +Preferred move order: + +1. restate the main finding +2. explain plausible reasons +3. compare with earlier work +4. note limitations +5. state implications +6. point to future work if needed + +Useful phrase families: + +- `Taken together, these findings suggest that ...` +- `A possible explanation is that ...` +- `This discrepancy may reflect ...` +- `These results should be interpreted with caution because ...` +- `An implication of this is that ...` +- `Further work is needed to determine whether ...` + +Avoid: + +- repeating the Results section in new words +- claiming mechanism when only association was shown + +## Conclusion + +Questions this section must answer: + +1. What was the central contribution? +2. Which finding matters most? +3. What implication follows, with what boundary? + +Preferred move order: + +1. return to the aim +2. summarize the decisive finding +3. state contribution or significance +4. give a boundary or forward look + +Useful phrase families: + +- `This study set out to ...` +- `The present findings indicate that ...` +- `These results extend our understanding of ...` +- `Notwithstanding these limitations, ...` +- `Further studies are required to ...` + +Avoid: + +- introducing new experiments +- ending on vague praise of the work + +## Abstract + +Questions this section must answer: + +1. What problem or gap is being addressed? +2. What was done? +3. What was found? +4. Why should the reader care? + +Preferred move order: + +1. broad context +2. concrete gap +3. approach +4. key result with numbers if available +5. implication + +Useful phrase families: + +- `X remains challenging because ...` +- `Here, we ...` +- `Using ... , we found that ...` +- `We show that ...` +- `These findings suggest ...` + +Keep the abstract selective. If a detail does not affect editorial triage, it probably does not belong. + +## Title + +Question this section must answer: + +- Which few words make the paper searchable, accurate, and interesting without overclaiming? + +Target properties: + +- searchable +- specific +- restrained +- defensible + +Useful patterns: + +- `[Core entity] in/through/by [mechanism or context]` +- `[Process] shapes [outcome] in [system]` +- `[Signature/pattern/framework] of [phenomenon]` + +Avoid: + +- `A study of ...` +- vague hooks +- unverified `first` +- stacked jargon diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/style-guardrails.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/style-guardrails.md new file mode 100644 index 0000000..b93d1dc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/style-guardrails.md @@ -0,0 +1,94 @@ +# Style Guardrails + +Use this file for mechanical and stylistic checks after the main rewrite. This file should refine prose and correctness, not override the main writing strategy in `SKILL.md`. + +## Academic style + +- prefer cautious, precise prose over conversational confidence +- avoid contractions +- avoid rhetorical questions in polished manuscript prose +- define abbreviations on first use +- use British spelling by default if the target is Nature-style prose +- keep figure legends concise; if aiming for Nature style, `<= 300` words is a good upper bound +- if aiming for Nature style, keep titles at `<= 75` characters including spaces + +## Articles + +Common checks: + +- first mention of a singular count noun: `a` or `an` +- later mention of the same item: `the` +- generic plural: usually no article +- unique entity: often `the` +- abstract nouns used generally: often no article + +Typical repair: + +- bad: `The hypoxia induces ...` +- better: `Hypoxia induces ...` + +## Numbers and units + +- use numerals for measurements +- leave a space between the value and the unit: `25 cm`, `3.2 s` +- keep statistical symbols and mathematical notation consistent +- use en dashes for ranges where appropriate + +Do not rewrite numbers into words unless the surrounding house style demands it. + +## Academic register + +- avoid spoken fillers and weak evaluative language +- use `we` only when it suits the discipline and document type +- keep nominalisation useful, not excessive +- keep the prose impersonal where appropriate, but do not force lifelessness + +## Sentence and paragraph checks + +- each sentence should express one main proposition +- dependent clauses must stay attached to a main clause +- do not join two independent clauses with only a comma +- each paragraph needs a controlling idea and supporting material +- avoid common structure errors such as sentence fragments introduced by `although` or `whereas` + +## Overclaim checklist + +Flag and soften: + +- `prove` +- `conclusively` +- `unprecedented` +- `best` +- `superior` +- `first` + +Safer replacements: + +- `show` +- `suggest` +- `to our knowledge` +- `among the strongest` +- `in this cohort` + +## Integrity rules + +- do not invent references +- do not alter quantitative values unless correcting an obvious typo requested by the user +- do not upgrade association to causation +- do not imply broader generalisability than the study supports + +## AI boundary + +Use AI for language control, not for scientific fabrication. + +Allowed: + +- grammar and clarity +- restructuring and hedging +- translation with terminology checking + +Not allowed: + +- fabricated citations or datasets +- invented mechanisms presented as fact +- unsupported claims of novelty diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/writing-strategy.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/writing-strategy.md new file mode 100644 index 0000000..a2a5543 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-polishing/references/writing-strategy.md @@ -0,0 +1,148 @@ +# Writing Strategy + +Use this file when the user is not just asking for cleaner English, but for better scientific writing logic. This is the layer that should govern all paragraph- and section-level rewriting. + +## Core stance + +Academic polishing is not only about style. It is also about making the reasoning legible. A polished paragraph that still performs the wrong rhetorical job is a failed edit. + +## Hourglass structure + +Most strong research writing follows a `broad -> narrow -> broad` pattern: + +- `Introduction`: open the territory, narrow to the gap, then state the study +- `Discussion/Conclusion`: start from the specific findings, then widen to implications and limits + +Use this pattern when deciding paragraph order and section scope. If a draft jumps between background, results, and implications without control, rebuild the progression first. + +## Writing order is not reading order + +The author may draft in one order and the reader may consume in another. A useful planning sequence is: + +1. results +2. introduction and conclusion +3. title +4. discussion +5. methods +6. abstract + +The practical rule for this skill is simple: organize around evidence and argumentative function, not around the chronology of the raw draft. + +## Claim, evidence, boundary + +Every important scientific statement should have three parts: + +1. `claim`: what is being said +2. `evidence`: what supports it +3. `boundary`: where the claim stops, or what uncertainty remains + +Typical failures: + +- claim without evidence +- data without an explicit point +- implication without a scope condition +- correlation rewritten as mechanism + +When polishing, repair these failures before polishing rhythm. + +## Section responsibilities + +### Introduction + +The Introduction should answer four questions: + +1. What is already known? +2. What remains unresolved? +3. What exact question does this study ask? +4. How does the study address it? + +Do not summarize results or conclusions here. + +### Results + +Results state what was observed. They should provide: + +- object or system +- condition +- quantitative support +- direct result + +Do not turn Results into a Discussion section by adding long mechanistic interpretation. + +### Discussion + +Discussion explains what the findings mean. It should address: + +- how the work fits the broader field +- what has been added to understanding +- which earlier work is being supported, revised, or complicated +- which explanations are plausible +- which limitations constrain the interpretation + +Discussion is the natural home for hedging. + +### Methods + +Methods should pass a reproducibility test: could another group repeat the work from this description, or from this description plus a clearly cited prior protocol? + +Reject vague writing such as: + +- `under standard conditions` +- `using routine methods` +- `data were analysed statistically` + +### Conclusion + +Conclusion is not a mini-discussion. A strong closing usually does three things: + +1. restates the central contribution +2. identifies the decisive evidence +3. states the implication with a boundary + +Do not introduce new data here. + +### Abstract + +The abstract is a mini-paper: + +1. context or problem +2. gap +3. approach +4. key result +5. implication + +It should help the reader decide whether the paper is relevant, credible, and potentially important. + +## Citation as positioning + +Citation is not just a formatting issue. It tells the reader how the current work stands relative to earlier work. + +Useful categories: + +- `support`: prior work supports the premise +- `borrow`: current work adopts a method, framework, or protocol +- `contrast`: current work differs in result, setting, or interpretation +- `reuse/adaptation`: material, data, code, or images come from elsewhere + +Always cite the source actually read and verified. Do not cite a paper as direct support if you only know it through another paper's summary. + +## Fairness to earlier work + +Do not manufacture novelty by flattening previous studies into a weak baseline. Prefer language like: + +- `Although previous studies showed ..., their performance in ... remains unclear.` +- `Earlier work established ..., but did not address ...` + +This preserves intellectual honesty while still making the gap explicit. + +## Overclaim control + +Watch for: + +- `prove` +- `conclusively` +- `unprecedented` +- `best` +- unqualified `first` + +Replace or qualify them unless the evidence is unusually strong and the scope is tightly defined. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/README.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/README.md new file mode 100644 index 0000000..82efcbe --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/README.md @@ -0,0 +1,94 @@ +# `nature-response` skill + +A reviewer-response skill for drafting, auditing, and revising point-by-point response +letters for Nature-family and high-impact journal manuscript revisions. + +This skill is bilingual-aware. It accepts Chinese or English reviewer comments, editor +letters, author notes, and draft rebuttals, then prepares an English response package with +Chinese author confirmation notes when useful. + +## What it does + +- splits reviewer comments into stable IDs such as `R1.1`, `R1.2`, and `R2.1` +- classifies each concern by type, severity, action, evidence need, and risk +- creates a response strategy summary before drafting prose +- routes requests into drafting, auditing, revising, triage-only, or appeal-like handling +- assigns editor instruction IDs such as `E.1` before reviewer IDs when the decision letter includes editor instructions +- drafts an editor-readable point-by-point response letter +- maps each response to a manuscript action, location, or missing-information flag +- rewrites defensive or vague author notes into professional response language +- handles difficult cases such as out-of-scope experiments, factual reviewer errors, conflicting reviewers, statistical critiques, and compliance concerns +- flags missing experiments, analyses, line numbers, citations, figure panels, and manuscript changes instead of inventing them + +## When to use + +- preparing a Nature, Nature Portfolio, Springer Nature, or similar high-impact journal revision +- responding to major or minor revision comments +- turning reviewer comments into a manuscript change checklist +- auditing a draft rebuttal for missing responses, tone problems, or unsupported claims +- converting Chinese author notes into submission-ready English point-by-point replies +- deciding how to respectfully disagree with a reviewer or explain a scope boundary + +## What it returns + +Unless the user asks for another format, the skill returns: + +1. response strategy summary +2. comment-response tracker +3. draft point-by-point response letter +4. manuscript change checklist +5. missing information / risk flags +6. Chinese confirmation notes when the user writes in Chinese + +## Core rules + +- Preserve reviewer comments faithfully before responding. +- Answer every concern, cross-reference it, or mark it unresolved. +- Map every response to a concrete action such as `ACCEPT_TEXT`, `ACCEPT_ANALYSIS`, `SOFTEN_CLAIM`, `DISAGREE`, or `AUTHOR_INPUT_NEEDED`. +- Do not invent experiments, analyses, citations, line numbers, figure panels, supplementary items, reviewer identities, editor instructions, or manuscript changes. +- Use cooperative, evidence-forward, non-defensive language. +- Treat the response letter as an editor-facing verification document, not a politeness exercise. + +## Source hierarchy + +- Target journal instructions and decision-letter requirements. +- Nature / Nature Portfolio / Springer Nature revision and peer-review process guidance. +- Springer Nature editorial advice on rebuttal letters. +- Local manuscript facts supplied by the author. + +The source basis is summarized in `references/source-basis.md` with URLs, rule summaries, and source-type labels. + +## File structure + +```text +nature-response/ +├── README.md +├── SKILL.md +├── references/ +│ ├── source-basis.md +│ ├── response-structure.md +│ ├── comment-taxonomy.md +│ ├── action-mapping.md +│ ├── tone-and-stance.md +│ ├── chinese-author-alignment.md +│ ├── difficult-cases.md +│ ├── intake-and-routing.md +│ └── qa-checklist.md +├── tests/ + ├── conflicting-reviewers.md + ├── defensive-draft-audit.md + ├── evaluation-summary.md + ├── minor-revision.md + ├── major-revision-missing-evidence.md + ├── impossible-experiment.md + └── rubric.md +└── examples/ + ├── conflicting-reviewers.md + ├── major-revision-with-missing-evidence.md + └── minor-revision.md +``` + +## Status + +Beta. The behavior is defined by synthetic Markdown fixtures and examples. The skill should remain +below Stable until it has been validated on real anonymized revision packages with author permission. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/SKILL.md new file mode 100644 index 0000000..009a1df --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/SKILL.md @@ -0,0 +1,127 @@ +--- +name: nature-response +description: >- + Draft, audit, or revise point-by-point reviewer response letters for Nature-family + manuscript revisions. Use when the user provides reviewer comments, editor decision + letters, revision notes, response drafts, or asks how to respond to major/minor + revision requests, rebuttal letters, response to reviewers, peer-review reports, + 审稿意见回复, 逐点回复, 修回信, 大修回复, 小修回复, or 如何回复 reviewer. +version: 0.1.0 +status: Beta +--- + +# Nature Reviewer Response Skill + +Use this skill to convert editor decision letters, reviewer comments, author notes, or +draft rebuttals into an auditable point-by-point response package for manuscript revisions. + +The response letter is an editor-facing verification document. The goal is to show that every +reviewer concern has been understood, addressed, and mapped to a concrete manuscript change, +justified scientific response, or unresolved author action. + +## Default stance + +- Preserve each reviewer comment faithfully before responding. +- Every reviewer concern must be answered, cross-referenced, or explicitly marked as unresolved. +- Map every response to manuscript evidence, a revision location, a justified disagreement, or `AUTHOR_INPUT_NEEDED`. +- Do not invent experiments, analyses, citations, line numbers, figure panels, supplementary materials, editor instructions, reviewer identities, or manuscript changes. +- Prefer concise, evidence-linked replies over long defensive explanations. +- When disagreeing, acknowledge the concern first, then give a scientific or scope-based reason. +- When a reviewer misunderstood the manuscript, first consider whether the manuscript presentation caused the misunderstanding. +- Treat rebuttal letters as potentially public review artifacts; write with professional tone and traceability. + +## Accepted inputs + +The skill may receive: + +- editor decision letter +- reviewer comments +- previous response draft +- manuscript change notes +- tracked-change summary +- line or page numbers +- figure, table, and supplement list +- author notes in Chinese or English +- journal name and article type + +If reviewer boundaries or comment segmentation are ambiguous, flag the ambiguity instead of +inventing reviewer structure. + +## Workflow + +1. Identify task mode and input readiness: `draft`, `audit`, `revise`, `triage-only`, or `appeal-like`. +2. Identify decision type: minor revision, major revision, revise-and-resubmit, transfer after review, or unclear. +3. Extract editor instructions first and assign IDs such as `E.1`, then split reviewer comments with IDs such as `R1.1`, `R1.2`, and `R2.1`. +4. Classify each item by category, severity, action label, missing input, readiness state, and risk. +5. Create a response strategy summary before drafting prose. +6. Draft responses using preserved reviewer comments unless the mode is `triage-only` or `appeal-like`. +7. Map each claimed change to manuscript location, figure, table, supplement, citation, or explicit placeholder. +8. Flag missing author input rather than fabricating details. +9. Run QA for completeness, traceability, factuality, tone, and unresolved risk. +10. Return the response package with package readiness: `ready_to_submit`, `draft_with_placeholders`, `needs_author_input`, or `blocked`. + +## Output format + +Unless the user asks for another format, return: + +```text +Response strategy summary +- Decision type: +- Overall posture: +- Major risks: +- Suggested ordering: + +Comment-response tracker +| ID | Reviewer concern | Type | Severity | Proposed action | Missing author input | +|---|---|---|---|---|---| + +Draft point-by-point response letter +[editor-readable English response] + +Manuscript change checklist +- [specific manuscript changes or placeholders] + +Missing information / risk flags +- [specific unresolved items or "None"] + +中文核对 +- [when the user writes in Chinese; otherwise omit unless useful] +``` + +## Red lines + +- Do not ignore any reviewer comment. +- Do not rephrase reviewer comments in a way that changes their meaning. +- Do not claim a revision was made unless the user supplied it. +- Do not invent line numbers, figure panels, citations, statistical results, or supplementary items. +- Do not use hostile or accusatory language. +- Do not cite time, money, or convenience as the primary reason for not doing a requested experiment. +- Do not hide limitations. +- Do not generate an appeal letter as the default path. Route appeal-like cases separately. +- Do not generate a cover letter in the MVP. Mention it only as adjacent revision-package material when relevant. + +## Related files + +| File | Open when | +|---|---| +| [references/intake-and-routing.md](references/intake-and-routing.md) | Before drafting, to identify task mode, minimum inputs, editor IDs, readiness state, and clarifying-question need | +| [references/source-basis.md](references/source-basis.md) | You need source hierarchy, rule provenance, or policy-vs-advice boundaries | +| [references/response-structure.md](references/response-structure.md) | You need the response package format or point-by-point letter anatomy | +| [references/comment-taxonomy.md](references/comment-taxonomy.md) | You need to classify reviewer comments by category and severity | +| [references/action-mapping.md](references/action-mapping.md) | You need action labels, tracker fields, and missing-input states | +| [references/tone-and-stance.md](references/tone-and-stance.md) | You need recommended language, forbidden phrasing, or disagreement tone | +| [references/chinese-author-alignment.md](references/chinese-author-alignment.md) | The user writes in Chinese or provides Chinese author notes | +| [references/difficult-cases.md](references/difficult-cases.md) | The comments involve impossible experiments, factual errors, conflicting reviewers, citations, statistics, compliance, transfer, or appeal-like cases | +| [references/qa-checklist.md](references/qa-checklist.md) | Before finalizing an output or auditing a draft response | + +## Source hierarchy + +Use sources in this order: + +1. Target journal instructions and the editor decision letter. +2. Nature / Nature Portfolio / Springer Nature revision and peer-review process guidance. +3. Springer Nature editorial advice on rebuttal letters. +4. Local manuscript facts supplied by the author. + +If a policy detail may have changed, verify the current journal page before giving final +submission advice. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/conflicting-reviewers.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/conflicting-reviewers.md new file mode 100644 index 0000000..79e1ac1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/conflicting-reviewers.md @@ -0,0 +1,42 @@ +# Example: conflicting reviewers + +This synthetic example shows how editor instructions and evidence limits control the response when +reviewers request incompatible claim strength. + +## Input + +```text +Editor: +Please avoid expanding the manuscript substantially and focus on clarifying the central claim. + +Reviewer 1: +1. The abstract should make a stronger causal claim that X drives Y. + +Reviewer 2: +1. The causal language is not supported by the observational design and should be softened. + +Author notes: +- The study is observational. +- We can soften the abstract and discussion. +- We can state that the findings support an association, not causality. +``` + +## Expected handling + +- Assign the editor instruction `E.1`. +- Assign reviewer comments `R1.1` and `R2.1`. +- Surface the conflict in the strategy summary. +- Prioritize the editor instruction and the observational design. +- Use `SOFTEN_CLAIM` for `R2.1`. +- Use `PARTIAL` or `DISAGREE` for `R1.1`, with respectful reasoning. + +## Response style + +```text +We appreciate the reviewer's suggestion to sharpen the abstract. However, because the study is +observational, we agree with the editor's instruction to clarify the central claim without +overstating causality. We have therefore revised the abstract and Discussion to state that the +findings support an association between X and Y, rather than a causal relationship. +``` + +The response must not promise both stronger causal language and softened causal language. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/major-revision-with-missing-evidence.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/major-revision-with-missing-evidence.md new file mode 100644 index 0000000..294bb02 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/major-revision-with-missing-evidence.md @@ -0,0 +1,52 @@ +# Example: major revision with missing evidence + +This synthetic example shows how to avoid fabricated compliance when an author note is incomplete. + +## Input + +```text +Editor decision: Major revision. + +Reviewer 1: +1. The manuscript requires validation in an independent cohort. +2. The replicate definition in the statistical analysis is unclear. + +Author notes: +- We added validation using dataset GSEXXXX in Fig. 5. +- We fixed the statistics description. +``` + +## Expected handling + +```text +Response strategy summary +- Decision type: Major revision +- Task mode: draft +- Package readiness: needs_author_input +- Major risks: validation results and statistical details are missing +``` + +The response may mention `GSEXXXX` and `Fig. 5` because they were supplied. It must not invent: + +- validation performance; +- sample size; +- p-values; +- confidence intervals; +- statistical test names; +- Methods or Results line numbers. + +## Required author questions + +```text +Missing information / risk flags +- R1.1: Please provide the validation result summary, cohort size or dataset scale, and Results/Fig. 5 location. +- R1.2: Please provide the statistical test name, replicate unit, sample size, correction method, and Methods location. +``` + +## Response style + +```text +To address this concern, we added an independent validation analysis using dataset GSEXXXX, +which is presented in Fig. 5. The final response requires the validation result summary and +manuscript location before it can be marked ready_to_submit. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/minor-revision.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/minor-revision.md new file mode 100644 index 0000000..20bf3a0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/examples/minor-revision.md @@ -0,0 +1,51 @@ +# Example: minor revision response package + +This synthetic example shows the expected output shape for a minor revision. It is not based on +real reviewer comments. + +## Input + +```text +Editor decision: Minor revision. + +Reviewer 1: +1. Please define cross-domain calibration in the Introduction. +2. Figure 2 legend does not explain the colour scale. + +Author notes: +- Cross-domain calibration means adjusting the model output across datasets with different feature distributions. +- We added a definition in the Introduction. +- We revised the Figure 2 legend to define the colour scale. +- No line numbers are available. +``` + +## Expected response strategy summary + +```text +Response strategy summary +- Decision type: Minor revision +- Task mode: draft +- Package readiness: draft_with_placeholders +- Overall posture: Cooperative and concise +- Major risks: line numbers are not available +- Suggested ordering: Reviewer 1 comments in order +``` + +## Expected tracker + +```markdown +| ID | Reviewer concern | Type | Severity | Proposed action | Readiness | Missing author input | +|---|---|---|---|---|---|---| +| R1.1 | Define cross-domain calibration | Editorial / presentation | Minor | ACCEPT_TEXT | draft_with_placeholders | Line or section location | +| R1.2 | Explain Figure 2 colour scale | Editorial / figure | Minor | ACCEPT_FIGURE | draft_with_placeholders | Line or legend location | +``` + +## Response style + +```text +We agree that the original Introduction did not define this term clearly. We have revised the +Introduction to define cross-domain calibration as adjustment of model output across datasets with +different feature distributions. This change appears in the Introduction [location]. +``` + +Do not invent line numbers. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/action-mapping.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/action-mapping.md new file mode 100644 index 0000000..d22f6ab --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/action-mapping.md @@ -0,0 +1,63 @@ +# Action mapping + +Use this file to map every reviewer concern to a concrete response action. + +## Action labels + +| Action label | Meaning | Use when | +|---|---|---| +| `ACCEPT_TEXT` | Revised wording, structure, title, abstract, Methods detail, Discussion, or legend | The author supplied or can supply a text change | +| `ACCEPT_ANALYSIS` | Added or revised analysis | The response depends on real analysis output | +| `ACCEPT_EXPERIMENT` | Added experimental data | The author performed a real experiment and supplied enough detail | +| `ACCEPT_FIGURE` | Added or modified figure, table, panel, legend, or supplement | A visual or tabular item addresses the concern | +| `CLARIFY_EXISTING` | Existing data already address the concern, but manuscript presentation needed clarification | The evidence exists and location can be cited | +| `ADD_CITATION` | Added verified citation | The citation is genuinely relevant and metadata is supplied or flagged | +| `SOFTEN_CLAIM` | Reduced claim strength or added boundary | The original claim was too broad, causal, novel, clinical, or mechanistic | +| `PARTIAL` | Partly addressed with explicit remaining limitation | A valid concern cannot be fully resolved in the revision | +| `DISAGREE` | Respectfully disagree with evidence or scope-based reasoning | The reviewer interpretation is not supported by the manuscript facts | +| `OUT_OF_SCOPE` | Valid suggestion but outside current manuscript scope | The request requires a new cohort, system, longitudinal design, or different study | +| `AUTHOR_INPUT_NEEDED` | Cannot draft final answer without real details | The author note is vague, missing, or unsupported | +| `BLOCKING` | Revision cannot be credible until author action occurs | Missing ethics, compliance, central evidence, integrity explanation, or required data | + +## Internal tracker fields + +Use this shape internally when organizing a response: + +```yaml +comment_id: R1.3 +reviewer: Reviewer 1 +severity: major +category: methodological +action: ACCEPT_ANALYSIS +author_input_needed: true +readiness: draft_with_placeholders +risk_level: high +manuscript_location: Methods; Results; Supplementary Fig. S2 +``` + +## Readiness state + +| State | Meaning | +|---|---| +| `ready_to_submit` | Enough facts are supplied to draft final text with traceable manuscript location | +| `draft_with_placeholders` | Draft can proceed, but placeholders must remain visible | +| `needs_author_input` | Do not draft final wording until author supplies facts | +| `blocked` | Revision response would be misleading or non-credible without author action | + +## Risk level + +| Risk | Use when | +|---|---| +| `low` | Wording, format, or straightforward clarification | +| `medium` | Citation, figure, method detail, or presentation issue requiring verification | +| `high` | Evidence, statistics, validation, claim strength, or out-of-scope request | +| `blocking` | Ethics, compliance, data integrity, missing central evidence, or unsupported response | + +## Mapping rules + +- If the author says only "we revised it", use `AUTHOR_INPUT_NEEDED` until the location and nature of the revision are known. +- If the author says "we added an experiment", request experiment name, condition, sample size or replicate unit, result summary, and figure/table location. +- If the author says "we added a citation", request verified bibliographic detail unless already supplied. +- If a reviewer asks for impossible or out-of-scope work, use `PARTIAL` or `OUT_OF_SCOPE` plus claim softening or limitation. +- If a reviewer is factually wrong, usually combine `CLARIFY_EXISTING` with a small text clarification. +- If a central claim remains unsupported, use `SOFTEN_CLAIM` or `BLOCKING`, not confident compliance language. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/chinese-author-alignment.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/chinese-author-alignment.md new file mode 100644 index 0000000..8b71c63 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/chinese-author-alignment.md @@ -0,0 +1,75 @@ +# Chinese author alignment + +Use this file when the user writes in Chinese, provides Chinese author notes, or asks for +`中文核对`, `中英对照`, `审稿意见回复`, `逐点回复`, `修回信`, `大修回复`, or `小修回复`. + +## Default behavior + +- Accept Chinese reviewer summaries, author notes, manuscript-change notes, and mixed Chinese-English inputs. +- Draft the final point-by-point response letter in English unless the user explicitly asks for Chinese only. +- Keep a short `中文核对` section for unresolved author actions when it helps the author act. +- Translate intent, not literal wording. +- Convert vague Chinese notes into concrete response evidence requirements. + +## Common Chinese note conversions + +| Chinese note | Problem | Better handling | +|---|---|---| +| `我们已经改了` | Too vague | Ask what changed, where it appears, and whether revised text is available | +| `按审稿人意见修改` | No action mapping | Convert to `AUTHOR_INPUT_NEEDED` until action and location are known | +| `我们补了实验` | Missing evidence | Request experiment name, conditions, replicate/sample details, result summary, and figure/table location | +| `我们补了分析` | Missing analysis detail | Request analysis method, data source, key result, statistical output, and manuscript location | +| `这个问题不重要` | Defensive and unsupported | Reframe as scope, evidence, or claim-boundary reasoning if scientifically justified | +| `由于时间原因没做` | High-risk excuse | Replace with study-design or scope boundary only if true; otherwise flag risk | +| `审稿人误解了` | Accusatory | Reframe as manuscript clarity issue and add clarification | +| `详见正文` | Not traceable | Require section, page, line, figure, table, or supplement | +| `我们认为足够了` | Unsupported sufficiency claim | Explain what evidence addresses the concern or mark remaining limitation | + +## Chinese confirmation section + +Use concise Chinese action notes: + +```text +中文核对 +- R1.1: 请补充验证分析的主要结果、样本量或数据集规模，以及 Fig. 5 对应的正文位置。 +- R1.2: 请确认统计检验名称、重复单位、样本量和多重检验校正方法。 +- R2.1: 目前不能声称已完成动物验证；建议改为范围说明 + Discussion limitation。 +``` + +## Bilingual drafting pattern + +When the user supplies Chinese notes: + +1. Preserve reviewer comments in their supplied language unless asked to translate. +2. Build the tracker using English action labels. +3. Draft the response letter in polished English. +4. Add `中文核对` only for decisions, missing facts, and high-risk issues. + +## Tone correction examples + +Chinese author note: + +```text +审稿人没有理解我们的方法。 +``` + +Response stance: + +```text +We agree that the original Methods description did not make this distinction sufficiently clear. +We have revised the Methods to clarify [specific distinction and location]. +``` + +Chinese author note: + +```text +这个实验超出了我们的能力。 +``` + +Response stance: + +```text +We agree that this experiment would provide an additional test of [claim]. However, it would require +[new cohort/system/longitudinal design], which is outside the scope of the present study. We have +therefore softened the claim and added a limitation in [location]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/comment-taxonomy.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/comment-taxonomy.md new file mode 100644 index 0000000..ce8c44b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/comment-taxonomy.md @@ -0,0 +1,95 @@ +# Comment taxonomy + +Use this file to classify reviewer comments before drafting responses. + +## Severity + +| Severity | Meaning | Default handling | +|---|---|---| +| `minor` | Presentation, clarity, formatting, citation, or small method-detail issue that does not alter the main evidence chain | Usually draftable with text change or citation placeholder | +| `major` | Evidence, validation, method, statistics, interpretation, or scope issue that may affect claims or editorial confidence | Requires explicit action, evidence, or author input | +| `blocking` | Ethics, compliance, data integrity, missing required approval, unsupported central claim, or unresolved fatal methodological issue | Do not draft a confident response without author action | +| `unclear` | Insufficient information to judge severity | Flag for author confirmation | + +## Categories + +### Editorial / presentation + +Includes unclear writing, structure problems, missing definitions, figure readability, title/abstract mismatch, or confusing terminology. + +Default strategy: + +- Usually `ACCEPT_TEXT` or `ACCEPT_FIGURE`. +- Revise wording, structure, legend, definition, or abstract-title alignment. +- Give section, page, line, figure, or placeholder. + +### Evidence / interpretation + +Includes unsupported claims, overinterpretation, missing control, causal claim not justified, clinical relevance not shown, or alternative explanation. + +Default strategy: + +- Use `ACCEPT_EXPERIMENT`, `ACCEPT_ANALYSIS`, `SOFTEN_CLAIM`, `CLARIFY_EXISTING`, `PARTIAL`, or `DISAGREE`. +- Do not invent results. +- If evidence is absent, soften the claim and add a limitation. + +### Methodological + +Includes missing method detail, reproducibility issue, missing baseline, missing validation, unclear sample size, software/model/version not stated. + +Default strategy: + +- Use `ACCEPT_TEXT`, `ACCEPT_ANALYSIS`, or `AUTHOR_INPUT_NEEDED`. +- Request exact method details when author notes are vague. +- Map to Methods, Supplementary Methods, protocol, code, or figure/table. + +### Statistical + +Includes inappropriate test, missing effect size, multiple testing issue, insufficient power, missing confidence interval, unclear replicate definition. + +Default strategy: + +- Treat major statistical critiques as high risk until details are supplied. +- Ask for test name, replicate unit, sample size, correction method, effect size, confidence interval, and exact results where relevant. +- Do not invent p-values, confidence intervals, sample sizes, or effect sizes. + +### Data / code / materials + +Includes missing accession number, source data unavailable, code not provided, restricted data not justified, FAIR metadata incomplete, materials availability. + +Default strategy: + +- Use `ACCEPT_TEXT`, `CLARIFY_EXISTING`, `AUTHOR_INPUT_NEEDED`, or `BLOCKING`. +- Request repository, accession, DOI, license, access route, or restriction reason. +- Coordinate with `nature-data` if the user asks for full data-availability wording. + +### Citation / positioning + +Includes missing prior work, inaccurate novelty claim, wrong comparison, field context incomplete, reviewer-requested citation. + +Default strategy: + +- Use `ADD_CITATION`, `SOFTEN_CLAIM`, `CLARIFY_EXISTING`, or `DISAGREE`. +- Add citations only when genuinely relevant and verified. +- Do not fabricate DOI, publication year, title, journal, or authors. + +### Scope / feasibility + +Includes requested experiments beyond scope, future-work suggestions, journal-fit concerns, transfer-related concerns. + +Default strategy: + +- Use `PARTIAL`, `OUT_OF_SCOPE`, `SOFTEN_CLAIM`, or `DISAGREE`. +- Acknowledge scientific value. +- Give a study-design or scope reason, offer alternative evidence, and add a limitation. +- Avoid time, funding, or convenience as the primary reason. + +### Ethics / compliance + +Includes ethics approval missing, consent missing, animal/human-subject reporting, competing interests, image/data integrity, or permissions. + +Default strategy: + +- Usually `BLOCKING` or `AUTHOR_INPUT_NEEDED`. +- Request exact approval number, institution, consent statement, reporting checklist, image-processing details, or data-integrity explanation. +- Do not draft around missing required compliance. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/difficult-cases.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/difficult-cases.md new file mode 100644 index 0000000..df784ae --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/difficult-cases.md @@ -0,0 +1,131 @@ +# Difficult cases + +Use this file when comments cannot be handled with straightforward acceptance and revision. + +## Impossible or out-of-scope experiment + +Use when the requested work requires a new cohort, long follow-up, new animal model, new clinical +trial, new platform, or different study design. + +Strategy: + +1. Acknowledge scientific value. +2. Explain the study-design or scope boundary. +3. Offer alternative evidence if supplied. +4. Soften the claim or add a limitation. +5. Avoid time, budget, convenience, or ability excuses. + +Template: + +```text +We agree that [experiment] would provide an additional test of [claim]. However, the central +conclusion of the present study is based on [existing evidence], and the requested experiment +would require [new system/cohort/longitudinal design] beyond the scope of this revision. +To avoid overstatement, we have revised [location] to acknowledge this limitation and now state +that [revised text or placeholder]. +``` + +## Reviewer factual error + +Use when the reviewer appears to have missed existing data or made a factually incorrect statement. + +Strategy: + +1. Do not accuse the reviewer. +2. Cite the existing manuscript location or supplied evidence. +3. Clarify wording if the manuscript invited confusion. +4. Consider a small revision even when the reviewer is wrong. + +Template: + +```text +We appreciate the reviewer raising this point. The relevant data are provided in [location], +where we show [supplied evidence]. We have revised [location] to make this clearer. +``` + +## Conflicting reviewer requests + +Use when two reviewers ask for incompatible changes. + +Strategy: + +1. Surface the conflict internally in the strategy summary. +2. Prioritize explicit editor instructions if supplied. +3. Find the minimal revision that satisfies both concerns. +4. Avoid making incompatible promises. +5. If necessary, explain the balancing choice in the relevant responses. + +## Reviewer-requested citation + +Use when a reviewer asks for a specific citation or broader literature coverage. + +Strategy: + +1. Evaluate relevance. +2. Add only genuinely relevant and verified citations. +3. Do not imply coercion or reviewer self-citation. +4. Use neutral positioning language. +5. If citation metadata is missing, use `AUTHOR_INPUT_NEEDED`. + +## Major statistical critique + +Treat as high risk or blocking until details are supplied. + +Request: + +- statistical test name +- replicate unit +- sample size or replicate count +- effect size or estimate when relevant +- confidence interval when relevant +- p-value only when supplied and appropriate +- multiple-testing correction +- software and version if relevant +- Methods and Results locations + +Do not invent statistical output. + +## Ethics, compliance, or data-integrity critique + +Usually `BLOCKING` until author provides exact facts. + +Request: + +- ethics approval body and approval number +- consent statement +- animal or human-subject reporting details +- competing-interest correction +- image-processing or data-integrity explanation +- data, code, materials, or accession information + +Do not write around missing required compliance. + +## Transfer after review + +Use when a manuscript is transferred with reviewer reports. + +Strategy: + +1. Identify whether the receiving journal expects a response to transferred reports. +2. Preserve reviewer IDs from the transferred review package when possible. +3. Address comments as normal revision concerns unless the new editor gives different instructions. +4. Flag journal-specific formatting or scope differences. + +## Appeal-like case + +Appeals are not ordinary revision responses. + +Route separately when: + +- the user wants to challenge rejection rather than revise; +- the decision letter invites an appeal path; +- the author alleges major factual error, bias, or process failure; +- no revised manuscript is being prepared. + +Default action: + +```text +This appears to be an appeal-like case rather than a revision response. `nature-response` +can identify the disputed points, but a full appeal letter should be handled as a separate task +with journal-specific appeal rules. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/intake-and-routing.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/intake-and-routing.md new file mode 100644 index 0000000..633241e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/intake-and-routing.md @@ -0,0 +1,107 @@ +# Intake and routing + +Use this file before splitting comments or drafting prose. Its job is to decide what task the +user is asking for, whether the supplied information is enough, and what output state is honest. + +## Task modes + +| Mode | Use when | Minimum useful input | Default output | +|---|---|---|---| +| `draft` | User wants a new point-by-point response package | Reviewer comments plus any author actions or manuscript-change notes | Full response package with placeholders where needed | +| `audit` | User provides an existing response draft and asks whether it is good enough | Response draft; reviewer comments when available | Findings first, then revised or annotated response sections | +| `revise` | User wants a draft rewritten for tone, traceability, or Nature-style response | Existing draft plus target change request | Revised response text plus changed-risk notes | +| `triage-only` | User wants strategy, action list, or missing inputs before writing prose | Reviewer comments or editor letter | Tracker, action map, missing-input list, no final letter | +| `appeal-like` | User wants to challenge rejection or process rather than revise | Decision letter and disputed points | Route out of default workflow and explain separate appeal handling | + +If the mode is unclear, infer the safest useful mode. Prefer `triage-only` when drafting would +require many unsupported facts. + +## Readiness states + +Use one readiness state for each comment and one package-level state: + +| State | Meaning | Allowed output | +|---|---|---| +| `ready_to_submit` | Direct answer, supplied action, and traceable manuscript location are all present | Final response wording without unresolved placeholders | +| `draft_with_placeholders` | A useful draft can be written, but visible placeholders remain | Draft wording with bracketed placeholders and risk flags | +| `needs_author_input` | Final text would require facts the user has not supplied | Tracker, questions, partial draft only if placeholders are explicit | +| `blocked` | Ethics, compliance, data integrity, missing central evidence, or appeal-like routing prevents credible revision response | Blocking issue first; do not produce confident final wording | + +Do not call a package `ready_to_submit` if any comment remains `draft_with_placeholders`, +`needs_author_input`, or `blocked`. + +## Editor instruction handling + +When editor instructions are supplied: + +- Assign editor-level IDs before reviewer IDs: `E.1`, `E.2`, `E.3`. +- Address editor instructions before Reviewer 1, Reviewer 2, etc. +- If editor instructions conflict with reviewer suggestions, surface the conflict in the strategy summary. +- Treat explicit editor constraints as higher priority than reviewer-level preference. + +Example: + +```text +E.1: Focus on clarifying the central claim without substantial manuscript expansion. +R1.1: Make the causal claim stronger. +R2.1: Soften unsupported causal language. +``` + +The response strategy should explain that the editor's constraint and the observational design +support claim softening rather than stronger causal language. + +## Minimum information by output type + +### Full draft response + +Requires: + +- reviewer comments or editor comments; +- enough author notes to know which actions were taken; +- manuscript locations or placeholders for claimed changes. + +If locations are missing, use section names or bracketed placeholders. Do not invent line numbers. + +### Final submission-ready response + +Requires: + +- all reviewer and editor comments identified; +- all claimed actions supplied by the author; +- traceable locations for every manuscript change; +- real details for experiments, analyses, statistics, citations, figures, tables, supplements, ethics, and data availability. + +If any required fact is missing, the output is not `ready_to_submit`. + +### Audit + +Requires: + +- user draft; +- reviewer comments when available. + +If reviewer comments are absent, audit only the visible draft and flag that completeness cannot be verified. + +## Clarifying question rules + +Usually proceed with placeholders and risk flags. Ask concise questions only when: + +- the user explicitly asks for final submission-ready text and required facts are missing; +- the draft would otherwise fabricate data, locations, approvals, statistics, citations, or figure panels; +- reviewer boundaries are too ambiguous to assign stable IDs; +- the case appears appeal-like or outside normal revision response. + +When asking, keep questions specific: + +```text +I need three facts before final wording: the validation result summary, the Methods/Results location, +and whether Fig. 5 is a main or supplementary figure. +``` + +## Routing shortcuts + +- Vague author note such as "we fixed it" -> `needs_author_input`. +- Existing response with hostile language -> `audit` or `revise`. +- Reviewer asks for impossible new work -> normal revision mode with `PARTIAL` or `OUT_OF_SCOPE`, not appeal. +- Rejection challenge -> `appeal-like`. +- User asks only "what should we do?" -> `triage-only`. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/qa-checklist.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/qa-checklist.md new file mode 100644 index 0000000..b09ea8f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/qa-checklist.md @@ -0,0 +1,64 @@ +# QA checklist + +Use this checklist before finalizing a response package or when auditing an existing draft. + +## Completeness + +- Every reviewer comment has a stable ID. +- Every ID has a response or an explicit unresolved flag. +- No reviewer comment is paraphrased in a way that changes meaning. +- Repeated concerns are cross-referenced rather than ignored. +- No major concern is answered only with thanks. +- Editor-specific instructions are addressed before reviewer comments when supplied. + +## Traceability + +- Every claimed revision has a manuscript location or visible placeholder. +- Every new figure, table, panel, supplement, or citation is named only if supplied. +- Every new experiment or analysis has enough supplied description to be credible. +- Line numbers are not invented; use section names if line numbers are unavailable. +- Reviewer comments and response IDs match throughout tracker, letter, and checklist. + +## Factuality + +- No invented data. +- No invented p-values, confidence intervals, effect sizes, sample sizes, or replicate counts. +- No invented DOI, citation metadata, accession number, repository record, or figure panel. +- No invented reviewer identity or editor instruction. +- No unsupported claim that an experiment, analysis, or manuscript revision was performed. +- Unsupported claims are softened or flagged. + +## Tone + +- No accusations of reviewer incompetence, bias, or misunderstanding unless the user is explicitly preparing an appeal and supplies evidence. +- No excessive apologies. +- No repetitive empty thanks. +- Disagreement is evidence-based and narrow. +- Study limitations are acknowledged cleanly. +- Time, money, convenience, or ability is not the primary stated reason for not doing requested work. + +## Actionability + +- Missing author inputs are concrete. +- High-risk and blocking items appear before the final letter or in a visible risk section. +- The manuscript change checklist tells the author which section, figure, table, supplement, or claim needs attention. +- Partial responses state what was addressed and what remains unresolved. + +## Final output gate + +Before returning final text, ask: + +- Can an editor verify every response against a manuscript change, supplied evidence, or explicit limitation? +- Would the response remain professional if included in a transparent peer review file? +- Are all placeholders visible enough that the author cannot accidentally submit fabricated compliance? +- Is the package readiness honestly labelled as `ready_to_submit`, `draft_with_placeholders`, `needs_author_input`, or `blocked`? +- If any item is `draft_with_placeholders`, `needs_author_input`, or `blocked`, the package must not be labelled `ready_to_submit`. + +## Readiness gate + +Use these labels consistently: + +- `ready_to_submit`: all comments are answered with supplied actions and traceable locations. +- `draft_with_placeholders`: draft text exists, but visible placeholders or missing locations remain. +- `needs_author_input`: the author must provide facts before final response wording is credible. +- `blocked`: a compliance, integrity, central-evidence, or appeal-like issue prevents normal final response drafting. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/response-structure.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/response-structure.md new file mode 100644 index 0000000..ba1ddbd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/response-structure.md @@ -0,0 +1,114 @@ +# Response structure + +Use this file when drafting or auditing the output shape of a reviewer response package. + +## Default package + +Return the response in this order unless the user asks for another format: + +1. Response strategy summary. +2. Comment-response tracker. +3. Draft point-by-point response letter. +4. Manuscript change checklist. +5. Missing information / risk flags. +6. Chinese confirmation notes when the user writes in Chinese. + +## Response strategy summary + +Keep this short and editor-readable: + +```text +Response strategy summary +- Decision type: Major revision +- Task mode: draft +- Package readiness: draft_with_placeholders +- Overall posture: Cooperative, evidence-forward, non-defensive +- Major risks: missing validation results; unclear replicate definition +- Suggested ordering: address editor first, then Reviewer 1 and Reviewer 2 in full +``` + +Decision types: + +- `minor revision` +- `major revision` +- `revise-and-resubmit` +- `transfer after review` +- `appeal-like case` routed outside the default workflow +- `unclear` when the decision type is not supplied + +Task modes: + +- `draft` +- `audit` +- `revise` +- `triage-only` +- `appeal-like` + +Package readiness: + +- `ready_to_submit`: no unresolved placeholders or missing facts remain. +- `draft_with_placeholders`: usable draft, but visible placeholders remain. +- `needs_author_input`: final text depends on facts the author has not supplied. +- `blocked`: credible revision response is blocked by ethics, compliance, data integrity, central evidence, or appeal-like routing. + +## Comment-response tracker + +Use a compact table: + +```markdown +| ID | Reviewer concern | Type | Severity | Proposed action | Readiness | Missing author input | +|---|---|---|---|---|---|---| +| R1.1 | Missing validation cohort | Evidence / validation | Major | ACCEPT_ANALYSIS | needs_author_input | Need result summary and manuscript location | +``` + +Keep reviewer concern text short in the tracker. Preserve the full wording in the letter when available. +Use `E.1`, `E.2`, etc. for editor instructions and list them before reviewer comments. + +## Point-by-point letter anatomy + +Use this default structure: + +```markdown +Dear Editor and Reviewers, + +We thank the editor and reviewers for their careful evaluation of our manuscript. +We have revised the manuscript to address the concerns raised and provide a point-by-point response below. + +## Response to Reviewer 1 + +**Reviewer comment R1.1** +[Full reviewer comment preserved here.] + +**Response** +We thank the reviewer for raising this point. [Direct answer.] +To address this concern, we have [specific action]. This change appears in [section/page/line/figure]. +[If needed: The remaining limitation is now stated in [location].] +``` + +## Manuscript change checklist + +List manuscript actions, not polite intentions: + +```text +Manuscript change checklist +- R1.1: Add validation result summary to Results and cite Fig. 5. +- R1.2: Clarify replicate definition in Methods. +- R2.1: Soften causal claim in Abstract and Discussion. +``` + +## Missing information / risk flags + +Use specific requests: + +```text +Missing information / risk flags +- R1.1: Need validation result direction and effect/performance summary before final wording. +- R1.2: Need test name, replicate unit, sample size, and correction method. +- R2.1: No line numbers supplied; using section names for now. +``` + +## Cover letter boundary + +Some journals ask for a revised manuscript, response to reviewers, and cover letter. This MVP does +not generate cover letters. If the user asks for one, state that it is adjacent to the response +package and should be handled as a separate task. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/source-basis.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/source-basis.md new file mode 100644 index 0000000..7357563 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/source-basis.md @@ -0,0 +1,33 @@ +# Source basis + +Use this file to keep `nature-response` grounded in primary or near-primary publication +process sources. Source labels distinguish formal policy from journal instructions and editorial +advice. + +## Source hierarchy + +1. Target journal instructions and the specific editor decision letter. +2. Nature / Nature Portfolio / Springer Nature peer-review and editorial-process pages. +3. Springer Nature editorial advice on rebuttal letters. +4. Local manuscript facts supplied by the author. + +If a current journal page conflicts with this file, follow the current journal page. + +## Sources and rules + +| Source | URL | Source type | Local rule summary | +|---|---|---|---| +| Nature editorial criteria and processes | https://www.nature.com/nature/for-authors/editorial-criteria-and-processes | Formal journal process | Revised papers that need technical work should be accompanied by a point-by-point response to referee comments. Resubmitted manuscripts must seriously address referee criticisms unless the editor says otherwise. | +| Nature transparent peer review information | https://www.nature.com/nature/for-authors/editorial-criteria-and-processes | Formal journal process | For some published original research articles, reviewer comments and author rebuttal material may be available as transparent peer review files. Write response letters as potentially auditable public documents without assuming every rebuttal is published. | +| Nature Electronics editorial process | https://www.nature.com/natelectron/submission-guidelines/editorial-process | Journal instruction | A revision package commonly includes the revised manuscript, a response to each reviewer, and a cover letter. `nature-response` handles the reviewer response; cover-letter generation is out of MVP scope. | +| Springer Nature rebuttal guidance | https://communities.springernature.com/posts/how-to-write-a-rebuttal-letter | Editorial advice | Preserve reviewer comments, respond immediately after each concern, number or clearly separate replies, state where changes appear, and avoid venting, accusations, ignored requests, or distorted paraphrases. | +| Scientific Reviews peer-review policies | https://www.nature.com/scirev/journal-policies/peer-review | Journal policy | Revisions should include point-by-point responses explaining manuscript changes. Appeals and revision responses follow different logic, so appeal-like cases should be routed separately instead of treated as ordinary point-by-point revision responses. | + +## Implementation implications + +- Point-by-point response is the default structure for revision cases. +- Every referee criticism must be answered, justified, cross-referenced, or flagged as unresolved. +- A cover letter can be mentioned as adjacent revision-package material, but this skill does not draft it by default. +- The skill should copy or preserve reviewer wording supplied by the user unless the user asks for anonymization or summarization. +- Tone, accuracy, and traceability should meet the standard of material that may later be reviewed by editors, reviewers, or public readers. +- Do not overstate source authority: Springer Nature advice is useful writing guidance, not journal-specific binding policy. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/tone-and-stance.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/tone-and-stance.md new file mode 100644 index 0000000..02fbcca --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/references/tone-and-stance.md @@ -0,0 +1,95 @@ +# Tone and stance + +Use this file when drafting response prose, rewriting defensive author notes, or deciding how to disagree. + +## Core posture + +- Cooperative but not submissive. +- Evidence-forward rather than personality-forward. +- Concise enough for editors to audit quickly. +- Respectful to reviewers without hiding scientific limits. +- Transparent about missing information and unresolved risks. + +## Recommended sentence patterns + +Use these patterns only when the facts support them: + +```text +We thank the reviewer for this constructive suggestion. +We agree that the original wording did not make this point sufficiently clear. +We have revised the manuscript to clarify... +To address this concern, we performed... +The new analysis shows... +We have therefore softened the claim from ... to ... +We respectfully disagree with this interpretation because... +Although we agree that this experiment would be valuable, it is outside the scope of the present study because... +We now explicitly acknowledge this limitation in the Discussion. +``` + +## Weak or forbidden patterns + +Do not present these as acceptable final responses: + +```text +The reviewer misunderstood... +The reviewer is wrong... +Due to lack of funding, we cannot... +This is beyond our ability... +As everyone knows... +We believe this is sufficient. +We have revised accordingly. +Thank you for the comment. +``` + +It is acceptable to thank reviewers, but thanks cannot be the response. Each reply still needs a +direct answer, action, location, or unresolved flag. + +## Disagreement pattern + +Use this order: + +1. Acknowledge the concern. +2. State the point of disagreement narrowly. +3. Give manuscript evidence, external evidence, or scope logic. +4. Make a small clarification if the manuscript may have invited confusion. +5. Avoid personalizing the disagreement. + +Template: + +```text +We appreciate the reviewer raising this issue. We respectfully disagree that [narrow point], +because [evidence or scope reason]. To make this clearer, we have revised [location] to state +that [revised text or placeholder]. +``` + +## Reviewer misunderstanding pattern + +Do not write that the reviewer misunderstood. Treat the misunderstanding as a presentation signal: + +```text +We agree that the original text did not make this distinction sufficiently clear. We have revised +the [section] to clarify that [specific distinction]. +``` + +## Out-of-scope pattern + +When declining a requested experiment or analysis: + +```text +We agree that [requested work] would provide an additional test of [claim]. However, the central +conclusion of the present study is based on [existing evidence], and [requested work] would require +[new cohort/system/longitudinal design] beyond the scope of this revision. To avoid overstatement, +we have revised [location] to acknowledge this limitation and now state that [text or placeholder]. +``` + +Use study design, available evidence, and claim boundaries. Do not lead with time, money, or convenience. + +## Claim-strength verbs + +Prefer calibrated verbs: + +- Strong evidence: `demonstrate`, `show`, `establish` +- Moderate evidence: `indicate`, `suggest`, `support` +- Limited or associative evidence: `are consistent with`, `may reflect`, `raise the possibility` + +If the reviewer challenges causality and the evidence is associative, soften causal verbs before drafting the response. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/conflicting-reviewers.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/conflicting-reviewers.md new file mode 100644 index 0000000..afb6882 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/conflicting-reviewers.md @@ -0,0 +1,49 @@ +# Test: conflicting reviewers + +## Input + +```text +Editor decision: Major revision. + +Editor: +Please avoid expanding the manuscript substantially; focus on clarifying the central claim and +addressing the reviewers' concerns with existing data where possible. + +Reviewer 1: +1. The abstract should make a stronger causal claim that X drives Y. + +Reviewer 2: +1. The causal language is not supported by the current observational design and should be softened. + +Author notes: +- The study is observational. +- We can soften the abstract and discussion. +- We can add a sentence explaining that the findings support an association, not causality. +``` + +## Expected behavior + +- Assign editor instruction ID `E.1` and address it before reviewer comments. +- Assign reviewer IDs `R1.1` and `R2.1`. +- Detect a conflict between Reviewer 1 and Reviewer 2. +- Prioritize the editor instruction and the evidentiary limit of the observational design. +- Use `SOFTEN_CLAIM` for `R2.1`. +- Use `PARTIAL` or `DISAGREE` for the stronger causal-claim request in `R1.1`, with respectful reasoning. +- Avoid incompatible promises. +- Mark readiness as `draft_with_placeholders` unless exact revised abstract/discussion wording or locations are supplied. + +## Forbidden behavior + +- Do not promise both stronger causal language and softened causal language. +- Do not ignore the editor instruction. +- Do not claim causality from an observational design. +- Do not accuse either reviewer of being wrong. +- Do not invent revised abstract or discussion line numbers. + +## Pass/fail checklist + +- [ ] `E.1` appears in the tracker or strategy summary. +- [ ] The conflict is surfaced explicitly. +- [ ] The chosen response is consistent with the observational design. +- [ ] `R1.1` and `R2.1` are both answered. +- [ ] No incompatible manuscript-change promises appear. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/defensive-draft-audit.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/defensive-draft-audit.md new file mode 100644 index 0000000..c02e5c8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/defensive-draft-audit.md @@ -0,0 +1,47 @@ +# Test: defensive draft audit + +## Input + +```text +Mode requested: audit and revise this draft response. + +Reviewer 1: +1. The method description is unclear and does not explain how model calibration was performed. +2. The authors should report the software version. + +Author draft: +The reviewer clearly misunderstood our method. We already explained the calibration in the paper. +We have revised accordingly. The software version is now included. + +Author notes: +- Calibration is described in Methods, but the exact paragraph may not be clear. +- Software version: v2.3.1. +- No line numbers are available yet. +``` + +## Expected behavior + +- Detect task mode as `audit` or `revise`. +- Assign stable IDs `R1.1` and `R1.2`. +- Flag the author draft as defensive and insufficiently traceable. +- Rewrite the misunderstanding sentence as manuscript-clarity framing. +- Treat `R1.1` as `CLARIFY_EXISTING` plus possible `ACCEPT_TEXT`. +- Treat `R1.2` as `ACCEPT_TEXT` with supplied version `v2.3.1`. +- Use section names rather than invented line numbers. +- Mark package readiness as `draft_with_placeholders` or `needs_author_input` until exact Methods location or revised text is supplied. + +## Forbidden behavior + +- Do not retain "The reviewer clearly misunderstood our method." +- Do not retain bare "We have revised accordingly." +- Do not invent line numbers or a Methods paragraph. +- Do not claim the calibration explanation was already sufficient without clarifying the manuscript. +- Do not remove the supplied software version. + +## Pass/fail checklist + +- [ ] Defensive language is removed. +- [ ] Each reviewer comment receives its own ID. +- [ ] Revised response includes manuscript-clarity framing. +- [ ] `v2.3.1` is preserved exactly. +- [ ] Missing location details remain visible. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/evaluation-summary.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/evaluation-summary.md new file mode 100644 index 0000000..b92d7b0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/evaluation-summary.md @@ -0,0 +1,43 @@ +# Evaluation summary + +`nature-response` is evaluated with synthetic Markdown fixtures. These tests are not executable +unit tests; they are behavior contracts for manual and agent review. + +## Status rationale + +Recommended status: `Beta`. + +Rationale: + +- The core rules are defined in `SKILL.md` and modular references. +- The skill has synthetic fixtures covering minor revision, major revision with missing evidence, + impossible experiment, defensive draft audit, and conflicting reviewers. +- Each fixture includes expected behavior, forbidden behavior, and pass/fail criteria. +- The examples show expected output shape without using real confidential reviewer comments. +- The skill has not yet been validated on real anonymized revision packages, so `Stable` would be premature. + +## Fixture coverage + +| Fixture | Coverage | Key failure prevented | +|---|---|---| +| `minor-revision.md` | stable IDs, minor comments, missing citation metadata | fabricated citation or line numbers | +| `major-revision-missing-evidence.md` | validation request, statistical details, missing evidence | invented results or p-values | +| `impossible-experiment.md` | out-of-scope longitudinal evidence | time/funding excuse or fabricated survival data | +| `defensive-draft-audit.md` | hostile draft language, vague compliance | accusatory reviewer language | +| `conflicting-reviewers.md` | editor priority and incompatible reviewer requests | contradictory manuscript promises | + +## Manual evaluation checklist + +- [x] Every fixture has input, expected behavior, forbidden behavior, and pass/fail checklist. +- [x] No fixture uses real reviewer comments. +- [x] Examples are synthetic and do not contain confidential review content. +- [x] Status remains below `Stable` until real anonymized cases are reviewed. + +## Promotion path to Stable + +Promote from `Beta` to `Stable` only after: + +- at least two real anonymized revision packages are tested with author permission; +- no fabricated actions, line numbers, statistics, or citations are observed; +- Chinese-note workflows produce usable English response drafts and Chinese confirmation notes; +- edge cases such as conflicting reviewers and impossible experiments remain traceable. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/impossible-experiment.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/impossible-experiment.md new file mode 100644 index 0000000..e43af45 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/impossible-experiment.md @@ -0,0 +1,42 @@ +# Test: impossible experiment + +## Input + +```text +Editor decision: Major revision. + +Reviewer 2: +1. Please add 2-year survival outcomes to support the clinical relevance of the biomarker. + +Author notes: +- The study is cross-sectional. +- We do not have longitudinal follow-up. +- We can soften the claim and add a limitation in the Discussion. +- We can point to the existing association analysis in Figure 3. +``` + +## Expected behavior + +- Assign stable ID `R2.1`. +- Classify the request as evidence / interpretation plus scope / feasibility. +- Use `PARTIAL` or `OUT_OF_SCOPE` with a high-risk flag, not simple refusal. +- Acknowledge the scientific value of longitudinal survival data. +- Explain that 2-year survival requires longitudinal follow-up beyond the present cross-sectional design. +- Offer the supplied alternative evidence: existing association analysis in `Figure 3`. +- Add a limitation / softened claim action in the Discussion. + +## Forbidden behavior + +- Do not cite time, money, convenience, or lack of funding as the primary reason. +- Do not say the experiment is impossible without explaining the study-design boundary. +- Do not imply survival data were collected. +- Do not accuse the reviewer of asking for an unreasonable experiment. +- Do not leave the central claim unchanged if the requested evidence is absent. + +## Pass/fail checklist + +- [ ] The response acknowledges the value of the requested survival evidence. +- [ ] The scope boundary is scientific and design-based. +- [ ] The response includes alternative evidence from `Figure 3`. +- [ ] The manuscript checklist includes claim softening or limitation text. +- [ ] No fabricated survival results appear. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/major-revision-missing-evidence.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/major-revision-missing-evidence.md new file mode 100644 index 0000000..8e09987 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/major-revision-missing-evidence.md @@ -0,0 +1,40 @@ +# Test: major revision with missing evidence + +## Input + +```text +Editor decision: Major revision. + +Reviewer 1: +1. The manuscript requires validation in an independent cohort. +2. The statistical replicate definition is unclear. + +Author notes: +- We added validation using dataset GSEXXXX and placed it in new Fig. 5. +- We fixed the statistics description. +- Please write the reply in Nature style. +``` + +## Expected behavior + +- Assign stable IDs: `R1.1`, `R1.2`. +- Classify `R1.1` as major evidence / validation with `ACCEPT_ANALYSIS` or `ACCEPT_EXPERIMENT`, depending on whether dataset validation is presented as analysis or experiment. +- Mention dataset `GSEXXXX` and `Fig. 5` because the author supplied them. +- Flag missing result details for `R1.1`, such as outcome direction, performance/effect summary, sample count if relevant, and manuscript section or line location. +- Classify `R1.2` as statistical / methodological and flag missing exact details. +- Request the statistical test name, replicate unit, sample size or replicate count, correction method when relevant, and Methods location. + +## Forbidden behavior + +- Do not invent validation results, performance numbers, p-values, confidence intervals, sample sizes, or effect sizes. +- Do not claim "the revised Methods now states" unless revised text or location is supplied. +- Do not treat "We fixed the statistics description" as enough evidence for a final confident response. +- Do not downgrade a major validation request to minor wording. + +## Pass/fail checklist + +- [ ] Major risks are surfaced in the strategy summary. +- [ ] `GSEXXXX` and `Fig. 5` are preserved exactly. +- [ ] Missing evidence is marked as `AUTHOR_INPUT_NEEDED`. +- [ ] Statistical details are requested explicitly. +- [ ] No fabricated quantitative results or manuscript locations appear. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/minor-revision.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/minor-revision.md new file mode 100644 index 0000000..94bc504 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/minor-revision.md @@ -0,0 +1,44 @@ +# Test: minor revision + +## Input + +```text +Editor decision: Minor revision. + +Reviewer 1: +1. Please define X in the Introduction. +2. Figure 2 legend is unclear. + +Reviewer 2: +1. Please cite recent work on Y. + +Author notes: +- X means cross-domain calibration. +- We revised the Introduction definition. +- We clarified the Figure 2 legend. +- We know one relevant citation but have not provided DOI or full bibliographic details yet. +``` + +## Expected behavior + +- Assign stable IDs: `R1.1`, `R1.2`, `R2.1`. +- Classify `R1.1` and `R1.2` as minor editorial / presentation comments. +- Classify `R2.1` as citation / positioning with missing citation metadata. +- Draft concise English responses for `R1.1` and `R1.2`. +- Mark `R2.1` as `ADD_CITATION` with `AUTHOR_INPUT_NEEDED` until the citation is verified. +- Use section names when line numbers are absent. + +## Forbidden behavior + +- Do not invent a citation, DOI, journal, year, or title for work on Y. +- Do not claim exact line numbers. +- Do not answer any comment only with thanks. +- Do not merge the two Reviewer 1 comments into one untraceable response. + +## Pass/fail checklist + +- [ ] Every reviewer comment receives an ID. +- [ ] Every ID appears in the tracker and the draft letter. +- [ ] Citation metadata is requested or placeholder-flagged. +- [ ] Responses are concise and non-defensive. +- [ ] No fabricated line numbers or citation details appear. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/rubric.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/rubric.md new file mode 100644 index 0000000..c2a1633 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-response/tests/rubric.md @@ -0,0 +1,84 @@ +# nature-response test rubric + +Use this rubric to manually evaluate `nature-response` outputs against the Markdown fixtures. + +## Completeness + +Pass when: + +- Every reviewer comment receives a stable ID. +- Every ID appears in the tracker and response letter. +- Repeated concerns are cross-referenced rather than ignored. +- Ambiguous reviewer boundaries are flagged. + +Fail when: + +- A comment is skipped. +- Two concerns are merged without traceability. +- A major concern receives only a polite acknowledgement. + +## Traceability + +Pass when: + +- Every claimed manuscript change has a section, page, line, figure, table, supplement, or explicit placeholder. +- New analyses, experiments, figures, citations, and limitations are mapped to action labels. +- Missing locations are flagged rather than invented. + +Fail when: + +- The response claims a change without location or evidence. +- The response invents line numbers, figure panels, supplementary items, or citation metadata. + +## Factuality + +Pass when: + +- Missing evidence is marked `AUTHOR_INPUT_NEEDED`. +- Quantitative details are used only when supplied by the author. +- Reviewer wording is preserved unless the user asks for anonymization or summarization. + +Fail when: + +- The response invents data, p-values, confidence intervals, sample sizes, accession details, reviewer identities, or editor instructions. +- The response overstates unsupported causal or clinical claims. + +## Tone + +Pass when: + +- The response is cooperative, concise, and evidence-forward. +- Disagreement is respectful and scientifically justified. +- Reviewer misunderstanding is framed as manuscript clarification when appropriate. + +Fail when: + +- The response accuses the reviewer of error, incompetence, or misunderstanding. +- The response is excessively apologetic, defensive, or repetitive. +- The response uses time, money, or convenience as the primary reason for not doing requested work. + +## Actionability + +Pass when: + +- The author can see what to change in the manuscript. +- Missing information is listed as concrete author questions. +- Blocking or high-risk issues are visible before the draft letter. + +Fail when: + +- The output only produces prose and no action checklist. +- The author cannot identify what evidence is still needed. + +## Nature-fit + +Pass when: + +- The output is organized as editor-readable point-by-point response material. +- All referee criticisms are seriously addressed, justified, or flagged. +- The response letter could be audited if it became part of transparent peer review. + +Fail when: + +- The output reads like generic language polishing. +- The response hides limitations or makes compliance appear stronger than the evidence provided. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/README.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/README.md new file mode 100644 index 0000000..153d4f6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/README.md @@ -0,0 +1,66 @@ +# `nature-writing` skill + +A Nature-style manuscript writing skill for drafting or rebuilding sections from +author-provided claims, figures, results, notes, or Chinese drafts. + +## What it does + +`nature-writing` helps write: + +- titles +- abstracts +- introductions +- results narratives +- discussions +- conclusions +- significance paragraphs +- manuscript outlines + +It is for argument construction and section drafting. For sentence-level polish +of an existing draft, use `nature-polishing`. + +## Built from + +Close reading of curated Nature and Nature Communications research articles +across materials, energy systems, construction decarbonization and machine +learning, combined with the existing writing-strategy rules in this repository. + +Section-level writing and reviewer-facing self-review guidance is also adapted +from Prof. Peng Sida's open research-writing notes: + +- https://pengsida.notion.site/c1a22465a0fa4b15a12985223916048e +- https://github.com/pengsida/learning_research + +## File structure + +```text +nature-writing/ +├── README.md +├── SKILL.md +└── references/ + ├── abstract.md + ├── article-architecture.md + ├── chinese-author-workflow.md + ├── conclusion.md + ├── experiments.md + ├── introduction.md + ├── method.md + ├── paper-review.md + ├── paragraph-flow.md + ├── related-work.md + └── examples/ +``` + +## Key rules + +| Domain | Core rule | +|---|---| +| Evidence first | Do not invent data, mechanisms, statistics, sample sizes or novelty | +| Abstract | Context, gap, approach, key result, implication, boundary | +| Introduction | Field scale, bottleneck, prior attempts, unresolved gap, present study | +| Method | Explain module motivation, design, forward process, and technical advantage | +| Results | Build an evidence ladder, not a chronological lab diary | +| Experiments | Tie every major claim to comparison, ablation, metric, or stress-test evidence | +| Discussion | Explain meaning, prior-work relation, constraints and future use | +| Review | Run adversarial self-review before submission | +| Chinese notes | Translate intent and argument, not clause order | diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/SKILL.md new file mode 100644 index 0000000..8f257bb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/SKILL.md @@ -0,0 +1,159 @@ +--- +name: nature-writing +description: Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose. +version: 0.2.0 +author: Community contribution based on curated Nature/Nature Communications writing patterns and open research-writing notes +--- + +# Nature-Style Scientific Writing + +Use this skill when the user needs help creating or rebuilding manuscript prose, +not merely polishing existing sentences. + +## Core stance + +- Author evidence comes first. Do not invent results, mechanisms, references, + methods, novelty, sample sizes, statistics or limitations. +- Write the argument before writing the sentences. +- Make the paper easy to judge: relevance, novelty, trust, reuse and meaning. +- Use ambitious but bounded claims. +- If essential evidence is missing, write a placeholder or ask for the missing + input instead of filling the gap. + +## When to open extra files + +| File | Open when | +|---|---| +| [references/article-architecture.md](references/article-architecture.md) | You need section-level structure, argument order, or published-article writing patterns | +| [references/abstract.md](references/abstract.md) | Drafting or revising an abstract, especially challenge-contribution and challenge-insight-contribution forms | +| [references/introduction.md](references/introduction.md) | Drafting or revising an Introduction, task framing, technical challenge, contribution framing, or teaser/pipeline logic | +| [references/related-work.md](references/related-work.md) | Rebuilding Related Work as topic synthesis instead of a paper-by-paper list | +| [references/method.md](references/method.md) | Writing Method sections, pipeline modules, module motivation, technical advantages, or implementation details | +| [references/experiments.md](references/experiments.md) | Planning or writing Experiments/Results around baselines, ablations, metrics, tables, figures, and claim support | +| [references/conclusion.md](references/conclusion.md) | Writing a bounded conclusion with contribution, evidence, impact, limitation, and future direction | +| [references/paragraph-flow.md](references/paragraph-flow.md) | User asks whether a paragraph flows, makes sense, or is clear; use reverse outlining and paragraph-message checks | +| [references/paper-review.md](references/paper-review.md) | Final manuscript self-review, rejection-risk audit, claim-evidence alignment, or reviewer-facing critique | +| [references/chinese-author-workflow.md](references/chinese-author-workflow.md) | The user's notes are Chinese, mixed Chinese-English, or organized as lab notes rather than manuscript prose | +| [references/examples/index.md](references/examples/index.md) | You need concrete abstract, introduction, or method examples after choosing the relevant guide | + +## Intake + +Before drafting, identify: + +- manuscript section: title, abstract, introduction, results, discussion, + conclusion, significance paragraph or full outline +- paper type: mechanism, method, resource, device, model, clinical, materials, + computational or interdisciplinary +- core claim: what the paper actually demonstrates +- evidence: figures, measurements, comparisons, datasets, statistics or examples +- boundary: where the claim stops +- target journal or word limit, if provided + +If any of `core claim`, `evidence` or `boundary` is absent, expose the gap before +drafting. You may still produce a scaffold with explicit placeholders. + +## Writing workflow + +1. Build a one-sentence argument: `In [system/problem], we show [advance] using + [approach], supported by [evidence], with [boundary].` +2. Choose the section architecture from `references/article-architecture.md`. +3. Map each paragraph to one job: context, gap, approach, result, comparison, + mechanism, implication or limitation. +4. Draft from evidence outward. Keep claims near the data that support them. +5. Calibrate verbs: `show`, `demonstrate`, `suggest`, `indicate`, `enable`, + `may`, `could`. +6. Remove unsupported novelty and universal claims. +7. Run a paragraph-flow check: one paragraph, one message, with a clear first + sentence and explicit sentence-to-sentence relation. +8. Return prose plus concise notes on assumptions and missing inputs. + +## Section defaults + +### Abstract + +Default Nature pattern: + +`context/problem -> gap -> approach -> key result -> implication -> boundary` + +For technical AI, ML, CV or method-heavy manuscripts, open +`references/abstract.md` and choose one of: + +- `challenge -> contribution` +- `challenge -> insight -> contribution` +- `multiple contributions` + +Keep it compact. Include quantitative or comparative detail when the user +provided it. End with what the work enables, not generic importance. + +### Introduction + +Use: + +`field scale -> bottleneck -> prior attempts -> unresolved gap -> present study` + +For method-heavy papers, open `references/introduction.md` and reason backward +from the technical challenge and contribution before drafting forward. + +Do not summarize all results. The final paragraph should state what this paper +does and how it addresses the gap. + +### Results narrative + +Use an evidence ladder: + +`system/workflow -> validation -> main result -> baseline comparison -> +mechanism/diagnostic analysis -> application or generalization` + +Each subsection should have a claim-first opening and then data support. + +For ML/conference-style experiment sections, open `references/experiments.md` +and make sure each major claim is backed by comparison, ablation, or stress-test +evidence. + +### Related Work + +Use: + +`topic scope -> representative methods -> limitation tied to this paper -> +distinction` + +Group prior work by technical topic and mechanism, not by publication year. + +### Discussion + +Use: + +`central advance -> evidence meaning -> relation to prior work -> constraints -> +future use` + +This is where interpretation and limitations belong. Do not repeat the Results +section figure by figure. + +### Conclusion + +Use: + +`contribution -> decisive evidence -> implication -> boundary` + +No new data. No unsupported promises. + +### Title + +Prefer concrete titles that combine: + +`system/object + action/capability + application or consequence` + +Avoid slogan titles, grant-style aims and overbroad field claims. + +## Output format + +Default output: + +1. `Draft:` with the requested prose. +2. `Section outline:` with `3-7` compact bullets when the task involves a full section. +3. `Assumptions or missing inputs:` with only material issues. +4. `Claim-evidence map:` for major claims, using `Claim: ... | Evidence: ... | Status: supported/needs evidence`. +5. `Why this structure:` with `2-4` short bullets. + +For Chinese author notes, provide polished English first, then brief Chinese +notes explaining major structural choices. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/agents/openai.yaml b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/agents/openai.yaml new file mode 100644 index 0000000..14b8743 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/agents/openai.yaml @@ -0,0 +1,4 @@ +interface: + display_name: "Nature Writing" + short_description: "Draft Nature-style manuscript sections" + default_prompt: "Help me turn my claims, results, figures, or Chinese notes into a Nature-style manuscript section with a clear argument and claim-evidence map." diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/abstract.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/abstract.md new file mode 100644 index 0000000..73f687e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/abstract.md @@ -0,0 +1,102 @@ +# Abstract Writing Guide + +## Goal + +Write a strong abstract by doing three things repeatedly: + +1. Think through the abstract logic first. +2. Follow one template (Version 1/2/3 below). +3. Revise the abstract many times. + +## Pre-Writing Questions (Important) + +Answer these before writing: + +1. What technical problem do we solve, and why is there no well-established solution? (important) +2. What is our technical contribution? +3. Why can our method work in essence? +4. What technical advantage and new insight do we provide? (important) + +## Version 1: Challenge -> Contribution + +Introduce the technical challenge, then use one to two sentences to present the technical contribution that solves the challenge. + +### Structure + +1. Task. +2. Technical challenge for previous methods. +3. One to two sentences introducing the technical contribution for solving the challenge. +4. Benefits of the technical contribution. +5. Experiment summary. + +### Expert Notes + +1. Discuss previous work around the technical challenge that we actually solve. +2. For the contribution sentence(s), usually mention the technical term/name only; do not explain every detailed step. +3. The technical term must be easy to understand; readers should not feel a jump. +4. This ability is very important for writing a good abstract. + +Version 1 local cite: + +1. `references/examples/abstract/template-a.md` + +## Version 2: Challenge -> Insight -> Contribution + +Introduce the technical challenge, then use one to two sentences to present the insight for solving the challenge, and then one sentence to present the technical contribution that implements this insight. + +### Structure + +1. Task. +2. Technical challenge for previous methods. +3. One sentence introducing the insight for solving the challenge. +4. One to two sentences introducing the technical contribution that implements the insight. +5. Benefits of technical novelty. +6. Experiment summary. + +### Expert Notes + +1. Discuss previous work around the technical challenge that we actually solve. +2. Introduce the insight in one clear sentence. +3. For the implementation sentence(s), usually mention the technical term/name only; do not explain every detailed step. +4. The technical term must be easy to understand; do not create a jump in reading. +5. This ability is very important for writing a good abstract. + +Version 2 local cite: + +1. `references/examples/abstract/template-b.md` + +## Version 3: Multiple Contributions + +Version 3: When there are multiple technical contributions, describe each contribution together with its technical advantage. + +### Structure + +1. Task. +2. If needed, one contrast sentence about prior methods. +3. Contribution sentence 1 + technical advantage. +4. Contribution sentence 2 + technical advantage. +5. Contribution sentence 3 + technical advantage. +6. Experiment summary. + +### Expert Notes + +1. When there are multiple technical contributions, describe each contribution together with its technical advantage. +2. The ability to express "contribution + advantage" in one sentence is very important for writing a good abstract. + +Version 3 local cite: + +1. `references/examples/abstract/template-c.md` + +## Example Bank + +1. `references/examples/abstract-examples.md` +2. `references/examples/abstract/template-a.md` +3. `references/examples/abstract/template-b.md` +4. `references/examples/abstract/template-c.md` + +## Abstract Quality Checklist + +1. Can a reader identify task, challenge, insight/contribution, and results in one pass? +2. Are all major claims supported by experiments? +3. Are technical names self-contained and readable? +4. Is there any sentence that mixes too many messages? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/article-architecture.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/article-architecture.md new file mode 100644 index 0000000..97de242 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/article-architecture.md @@ -0,0 +1,107 @@ +# Article Architecture + +Use this reference when writing or rebuilding manuscript sections. The patterns +come from curated Nature and Nature Communications examples across materials, +energy, construction decarbonization and machine learning. They are structural +patterns, not wording templates. + +## Full-paper argument + +A strong paper can usually be reduced to: + +`field-scale need -> unresolved bottleneck -> proposed move -> decisive evidence +-> broader implication -> boundary` + +Before drafting, force the user's material into this chain. If one link is +missing, mark it as missing rather than writing around it. + +## Abstract + +Recommended paragraph movement: + +1. Field-scale context or problem. +2. Why current routes do not fully solve it. +3. What this paper introduces or demonstrates. +4. The strongest result, preferably with quantitative or comparative support. +5. The mechanism, workflow or practical consequence. +6. Bounded implication. + +Useful diagnostics: + +- If the abstract begins with `Here, we`, it may be missing context. +- If it ends with a broad promise, it may need scope control. +- If it contains no number, comparison or concrete test, it may feel ungrounded. + +## Introduction + +Use a controlled funnel: + +1. Establish the field stake. +2. Explain the bottleneck in existing practice. +3. Treat prior work fairly and specifically. +4. Identify the remaining capability gap. +5. State the present study as a direct response to that gap. + +Avoid: + +- a literature list without a narrowing logic +- claiming novelty by dismissing prior work +- announcing results before the reader understands the question + +## Results + +Arrange Results as an evidence ladder: + +1. system, workflow or design space overview +2. validation that the platform or assay is credible +3. primary performance or discovery result +4. fair comparison with baseline, standard practice or prior method +5. mechanism, diagnostic analysis or interpretability +6. scale-up, application, generalization or stress test + +Subsection opening rule: + +`To test [question], we [action].` + +Then report the result and evidence. Keep interpretation short unless the +paragraph explicitly transitions toward Discussion. + +## Discussion + +Discussion should widen from finding to meaning: + +1. central advance +2. why the evidence supports it +3. how it changes a workflow, design rule or conceptual boundary +4. how it relates to previous studies +5. what limits or dependencies remain +6. what future work is now plausible + +Do not restate every figure. Select the evidence that changes interpretation. + +## Conclusion + +Use a compact four-part close: + +1. This work demonstrates or establishes the main contribution. +2. The decisive evidence is named. +3. The broader implication is stated. +4. The boundary condition is clear. + +Conclusions should not introduce new data, new citations or new mechanisms. + +## Title + +Good titles are concrete and searchable: + +`system/object + capability/action + application/consequence` + +Examples of title logic: + +- material plus function +- method plus task +- process plus scale +- model plus data regime + +Avoid vague prestige words such as `novel`, `advanced`, `powerful`, `green`, +`efficient` unless they are made concrete by the rest of the title. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/chinese-author-workflow.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/chinese-author-workflow.md new file mode 100644 index 0000000..5c44ea8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/chinese-author-workflow.md @@ -0,0 +1,42 @@ +# Chinese Author Workflow + +Use this reference when the user's input is Chinese, mixed Chinese-English, or +written as lab notes. + +## Translate intent, not syntax + +Chinese academic notes often place background, motivation, method and implication +in one long sentence. Before drafting English, split the note into: + +- claim +- evidence +- condition +- comparison +- implication +- limitation + +Then write English in the order required by the section, not in the order of the +Chinese sentence. + +## Common repairs + +| Chinese-draft pattern | Repair | +|---|---| +| Broad importance before a clear object | Name the system or problem earlier | +| Method list before research gap | Move the gap before the method | +| `显著提高/明显改善` without baseline | Add the comparator or soften the verb | +| `首次/创新性` without scope | Replace with a bounded novelty claim | +| Mechanism inferred from correlation | Use `suggests`, `is consistent with`, or ask for mechanistic evidence | +| Results mixed with implications | Put observation in Results and meaning in Discussion | + +## Drafting from author notes + +Use this sequence: + +1. Summarize the author's intended claim in Chinese. +2. Identify missing evidence or boundary. +3. Draft the English paragraph. +4. Add short Chinese notes explaining any structural changes. + +Do not make the English sound like a literal translation. Make it sound like a +Nature-style manuscript paragraph supported by the user's facts. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/conclusion.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/conclusion.md new file mode 100644 index 0000000..60209f9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/conclusion.md @@ -0,0 +1,35 @@ +# Conclusion Writing Guide + +## Goal + +Close the paper with clear takeaways and credible limitations. + +## Structure + +1. Restate solved problem and core technical idea. +2. Summarize strongest evidence from experiments. +3. State practical impact or new insight. +4. Add limitation paragraph. +5. End with concrete future direction. + +## Limitation Guidance + +Prefer limitations tied to task goal/setting boundaries, for example: + +1. Data regime limitation (e.g., only short sequences). +2. Assumption limitation (e.g., controlled viewpoints only). +3. Deployment scope limitation (e.g., specific sensor setup). + +Avoid framing conclusion around fixable implementation flaws unless they critically define your method's scope. + +## Distinguish Limitation Types + +1. Technical defect: underperforms strong baselines on key metrics or causes unacceptable tradeoff. +2. Scope limitation: bounded by current task setting and still competitive vs. current SOTA. + +## Template + +1. This paper addresses [problem] by proposing [method]. +2. The key idea is [core insight], which enables [main benefit]. +3. Experiments show [main gains] across [datasets/settings]. +4. A current limitation is [scope boundary], and extending to [future setting] is an important next step. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract-examples.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract-examples.md new file mode 100644 index 0000000..ccc112a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract-examples.md @@ -0,0 +1,13 @@ +# Abstract Examples Index + +All abstract example cites should point to the local files below. + +1. Version 1 (Challenge -> Contribution) +`Version 1: Introduce the technical challenge, then use one to two sentences to present the technical contribution that solves the challenge.` +`references/examples/abstract/template-a.md` +2. Version 2 (Challenge -> Insight -> Contribution) +`Version 2: Introduce the technical challenge, then use one to two sentences to present the insight for solving the challenge, and then one sentence to present the technical contribution that implements this insight. (Personally recommended.)` +`references/examples/abstract/template-b.md` +3. Version 3 (Multiple Contributions) +`Version 3: When there are multiple technical contributions, describe each contribution together with its technical advantage.` +`references/examples/abstract/template-c.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-a.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-a.md new file mode 100644 index 0000000..8b58534 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-a.md @@ -0,0 +1,21 @@ +# Abstract Template A Examples (Challenge -> Contribution) + +Source scope: your original notes, "Version 1". + +```latex +\section{Abstract} +% Task +% Technical challenge for previous methods (discuss around the technical challenge that we solved) +% Introduce the technical contribution for solving the challenge in one to two sentences (usually mention the technical term/name only, without describing every detailed step. The term should be easy to understand and should not create a jump in reading. This ability is very important for writing a good abstract.) +% Introduce the benefits of the technical contribution +% Experiment +``` + +## Reusable skeleton + +1. `[Task sentence]` +2. `However, previous methods suffer from [technical challenge].` +3. `To solve this challenge, we propose [technical contribution name].` +4. `[One more contribution sentence if needed].` +5. `This contribution brings [technical benefit].` +6. `Experiments show [main result].` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-b.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-b.md new file mode 100644 index 0000000..ae7ee9d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-b.md @@ -0,0 +1,34 @@ +# Abstract Template B Examples (Challenge -> Insight -> Contribution) + +```latex +\section{Abstract} +% Task +%% Example 1: In recent years, generative models have undergone significant advancement due to the success of diffusion models. +%% Example 2: This paper addresses the challenge of novel view synthesis for a human performer from a very sparse set of camera views. + +% Technical challenge for previous methods (discuss around the technical challenge that we solved) +%% Example 1: The success of these models is often attributed to their use of guidance techniques, such as classifier and classifier-free methods, which provides effective mechanisms to tradeoff between fidelity and diversity. However, these methods are not capable of guiding a generated image to be aware of its geometric configuration, e.g., depth, which hinders the application of diffusion models to areas that require a certain level of depth awareness. +%% Example 2: Some recent works have shown that learning implicit neural representations of 3D scenes achieves remarkable view synthesis quality given dense input views. However, the representation learning will be ill-posed if the views are highly sparse. + +% Introduce the insight for solving the challenge in one sentence +%% Example 1: To address this limitation, we propose a novel guidance approach for diffusion models that uses estimated depth information derived from the rich intermediate representations of diffusion models. +%% Example 2: To solve this ill-posed problem, our key idea is to integrate observations over video frames. + +% Introduce the technical contribution that implements the insight in one to two sentences (usually mention the technical term/name only, without describing every detailed step. The term should be easy to understand and should not create a jump in reading. This ability is very important for writing a good abstract.) +%% Example 1: To do this, we first present a label-efficient depth estimation framework using the internal representations of diffusion models. At the sampling phase, we utilize two guidance techniques to self-condition the generated image using the estimated depth map, the first of which uses pseudo-labeling, and the subsequent one uses a depth-domain diffusion prior. +%% Example 2: To this end, we propose Neural Body, a new human body representation which assumes that the learned neural representations at different frames share the same set of latent codes anchored to a deformable mesh + +% Introduce the benefits of technical novelty +%% Example 2: so that the observations across frames can be naturally integrated. The deformable mesh also provides geometric guidance for the network to learn 3D representations more efficiently. + +% Experiment +``` + +## Given example pattern 2 + +1. `This paper addresses the challenge of novel view synthesis for a human performer from a very sparse set of camera views.` +2. `... representation learning will be ill-posed if the views are highly sparse.` +3. `To solve this ill-posed problem, our key idea is to integrate observations over video frames.` +4. `To this end, we propose Neural Body ...` +5. `... observations across frames can be naturally integrated ... provides geometric guidance ...` +6. `Experiments show [main result].` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-c.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-c.md new file mode 100644 index 0000000..3865325 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/abstract/template-c.md @@ -0,0 +1,28 @@ +# Abstract Template C Examples (Multiple Contributions) + +```latex +% Task +%% This paper introduces a novel contour-based approach named deep snake for real-time instance segmentation. + +%% Unlike some recent methods that directly regress the coordinates of the object boundary points from an image + +% Introduce technical contribution and technical advantage in one sentence (this ability is very important for writing a good abstract.) +%% deep snake uses a neural network to iteratively deform an initial contour to match the object boundary, which implements the classic idea of snake algorithms with a learning-based approach. + +% Introduce technical contribution and technical advantage in one sentence +%% For structured feature learning on the contour, we propose to use circular convolution in deep snake, which better exploits the cycle-graph structure of a contour compared against generic graph convolution. + +% Introduce technical contribution and technical advantage in one sentence +%% Based on deep snake, we develop a two-stage pipeline for instance segmentation: initial contour proposal and contour deformation, which can handle errors in object localization. + +% Experiment +``` + +## Given example pattern (Deep Snake style from your text) + +1. `This paper introduces a novel contour-based approach named deep snake for real-time instance segmentation.` +2. `Unlike some recent methods that directly regress the coordinates of the object boundary points from an image ...` +3. `deep snake uses a neural network to iteratively deform an initial contour ...` +4. `For structured feature learning on the contour, we propose circular convolution ...` +5. `Based on deep snake, we develop a two-stage pipeline ...` +6. `Experiments show [main result].` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/index.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/index.md new file mode 100644 index 0000000..3babc90 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/index.md @@ -0,0 +1,21 @@ +# Example Bank Index + +Use this folder for concrete writing patterns and locally organized cite targets. + +## Files + +1. Abstract examples index: `references/examples/abstract-examples.md` +2. Introduction examples index: `references/examples/introduction-examples.md` +3. Abstract template files: `references/examples/abstract/template-a.md`, `references/examples/abstract/template-b.md`, `references/examples/abstract/template-c.md` +4. Introduction task/application files: `references/examples/introduction/version-1-task-then-application.md`, `references/examples/introduction/version-2-application-first.md`, `references/examples/introduction/version-3-general-to-specific-setting.md`, `references/examples/introduction/version-4-open-with-challenge.md` +5. Introduction technical-challenge files: `references/examples/introduction/technical-challenge-version-1-existing-task.md`, `references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md`, `references/examples/introduction/technical-challenge-version-3-novel-task.md`, `references/examples/introduction/novel-task-challenge-decomposition.md` +6. Introduction pipeline files: `references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md`, `references/examples/introduction/pipeline-version-2-two-contributions.md`, `references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md`, `references/examples/introduction/pipeline-version-4-observation-driven.md`, `references/examples/introduction/pipeline-not-recommended-abstract-only.md` +7. Method examples index: `references/examples/method-examples.md` +8. Method detail files: `references/examples/method/pre-writing-questions.md`, `references/examples/method/module-triad-neural-body.md`, `references/examples/method/neural-body-annotated-figure-text.md`, `references/examples/method/module-design-instant-ngp.md`, `references/examples/method/module-motivation-patterns.md`, `references/examples/method/section-skeleton.md`, `references/examples/method/overview-template.md`, `references/examples/method/example-of-the-three-elements.md`, `references/examples/method/method-writing-common-issues-note.md` + +## Usage + +1. Pick one template from a section guide. +2. Open the matching examples file. +3. Reuse the sentence logic, not exact wording. +4. Keep citation links in your notes for traceability. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction-examples.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction-examples.md new file mode 100644 index 0000000..d3aed2e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction-examples.md @@ -0,0 +1,25 @@ +# Introduction Examples Index + +All introduction example cites should point to the local files below. + +## A. Task and Application Versions + +1. Version 1: `references/examples/introduction/version-1-task-then-application.md` +2. Version 2: `references/examples/introduction/version-2-application-first.md` +3. Version 3: `references/examples/introduction/version-3-general-to-specific-setting.md` +4. Version 4: `references/examples/introduction/version-4-open-with-challenge.md` + +## B. Technical Challenge Versions + +1. Version 1 (existing task): `references/examples/introduction/technical-challenge-version-1-existing-task.md` +2. Version 2 (existing task + traditional insight backing): `references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md` +3. Version 3 (novel task): `references/examples/introduction/technical-challenge-version-3-novel-task.md` +4. Novel-task decomposition examples: `references/examples/introduction/novel-task-challenge-decomposition.md` + +## C. Pipeline-Introduction Versions + +1. Version 1: `references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md` +2. Version 2: `references/examples/introduction/pipeline-version-2-two-contributions.md` +3. Version 3: `references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md` +4. Version 4: `references/examples/introduction/pipeline-version-4-observation-driven.md` +5. Not recommended pattern: `references/examples/introduction/pipeline-not-recommended-abstract-only.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/novel-task-challenge-decomposition.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/novel-task-challenge-decomposition.md new file mode 100644 index 0000000..de15962 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/novel-task-challenge-decomposition.md @@ -0,0 +1,18 @@ +# Introduction Novel-Task Challenge Decomposition + + +`For novel tasks without direct methods, decompose the challenge into clear requirement/challenge points.` + +```latex +% To achieve xx goal, several requirements must be satisfied (or several challenges must be handled). +%% Example: In this work, our goal is to build a model that captures such object intrinsics from a single image. This problem is challenging for three reasons. + +% Describe point 1 +%% Example: First, we only have a single image. This makes our work fundamentally different from existing works on 3D-aware image generation models [8, 9, 27, 28], which typically require a large dataset of thousands of instances for training. In comparison, the single image contains at most a few dozen instances, making the inference problem highly under-constrained. + +% Describe point 2 +%% Example: Second, these already limited instances may vary significantly in pixel values. This is because they have different poses and illumination conditions, but neither of these factors are annotated or known. We also cannot resort to existing tools for pose estimation based on structure from motion, such as COLMAP [35], because the appearance variations violate the assumptions of epipolar geometry. + +% Describe point 3 +%% Example: Finally, the object intrinsics we aim to infer are probabilistic, not deterministic: no two roses in the natural world are identical, and we want to capture a distribution of their geometry, texture, and material to exploit the underlying multi-view information. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-not-recommended-abstract-only.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-not-recommended-abstract-only.md new file mode 100644 index 0000000..e508e53 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-not-recommended-abstract-only.md @@ -0,0 +1,30 @@ +# Not Recommended: Abstract-Only Method Description in Introduction + + +`Not recommended: If the method is simple, do not avoid concrete method details in Introduction and only discuss abstract insight to make it look novel.` + +Expert note (faithful translation): + +1. The craft of this writing template is how to make a simple pipeline look novel. +2. Note: this is not about making the insight look novel, but about making the pipeline steps look novel. +3. In most cases this is not recommended. +4. The better target is to clearly explain how the core contribution is implemented in Introduction. + +```latex +% To tackle this problem, we propose a novel 3D GAN training method to generate photo-realistic images irrespective of the viewing angle. + +% Introduce key idea +% Our key idea is as follows. To ease the challenging problem of learning photorealistic and multi-view consistent image synthesis, we cast the problem into two subproblems, each of which can be solved more easily. + +% Explain why the key idea works, but without concretely discussing the full pipeline (or only discuss abstract benefit) +%% Example: Specifically, we formulate the problem as a combination of two simple discrimination problems, one of which learns to discriminate whether a synthesized image looks real or not, and the other learns to discriminate whether a synthesized image agrees with the camera pose. Unlike the formulations of the previous methods, which try to learn the real image distribution for each pose, or to learn pose estimation, our subproblems are much easier as each of them is analogous to a basic binary classification problem. + +% Introduce pipeline modules with new terms but without clearly explaining the full pipeline (or skip concrete pipeline details) +%% Example: Based on this key idea, we propose a dual-branched discriminator, which has two branches for learning photorealism and pose consistency, respectively. As these branches are supervised explicitly for their respective purposes, high-quality images with pose consistency can be produced at each viewing angle, and consequently, the generator creates high-quality images and shapes. (This paragraph does not clearly explain how the pipeline works.) + +% Introduce another contribution +%% Example: In addition, we propose a pose-matching loss to give supervision to the discriminator for the pose consistency, by considering a positive pose (i.e., rendering pose or ground truth pose) and a negative pose (i.e., irrelevant pose) for a given image. (This paragraph does not clearly explain how the pipeline works.) + +% Explain expected benefit over prior methods +%% Example: For example, the frontal viewpoint is one of the irrelevant poses for a side-view image. As reported in the experiments, this loss helps improve image and shape quality. This can be interpreted as a simplification of a classification problem from a large number of classes into binary, which is composed of positive and negative pairs. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md new file mode 100644 index 0000000..a5ce72d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md @@ -0,0 +1,30 @@ +# Pipeline Version 1 (One Contribution, Multiple Advantages) + + +`Version 1: One contribution with multiple advantages, and one teaser figure to present the basic idea.` + +```latex +% In this paper, we propose a novel framework … +%% Example: In this paper, we introduce a novel implicit neural representation for dynamic humans, named Neural Body, to solve the challenge of novel view synthesis from sparse views. +In this paper, we propose a novel framework/representation, named [method name] for [xxx task]. + +% Teaser for basic idea +%% Example: The basic idea is illustrated in Figure 2. +The basic idea is illustrated in [xxx Figure]. + +% One-sentence key novelty/contribution (very important ability) +%% Example: For the implicit fields at different frames, instead of learning them separately, Neural Body generates them from the same set of latent codes. +Our innovation is in [one sentence for key novelty]. + +% Method details +%% Example: Specifically, we anchor a set of latent codes to the vertices of a deformable human model (SMPL in this work), namely that their spatial locations vary with the human pose. To obtain the 3D representation at a frame, we first transform the code locations based on the human pose, which can be reliably estimated from sparse camera views. Then, a network is designed to regress the density and color for any 3D point based on these latent codes. Both the latent codes and the network are jointly learned from images of all video frames during the reconstruction. +Specifically, [how it works in detail]. + +% Advantage 1 +%% Example: This model is inspired by the latent variable model in statistics, which enables us to effectively integrate observations at different frames. +In contrast to previous methods, [our advantage]. + +% Advantage 2 +%% Example: Another advantage of the proposed method is that the deformable model provides a geometric prior (rough surface location) to enable more efficient learning of implicit fields. +Another advantage of the proposed method is that [another advantage]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-2-two-contributions.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-2-two-contributions.md new file mode 100644 index 0000000..aeff8fc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-2-two-contributions.md @@ -0,0 +1,34 @@ +# Pipeline Version 2 (Two Contributions) + + +`Version 2: Two contributions, and one teaser figure to present the basic idea.` + +```latex +% In this paper, we propose a novel framework … +%% Example: In this paper, we introduce a novel implicit neural representation for dynamic humans, named Neural Body, to solve the challenge of novel view synthesis from sparse views. +In this paper, we propose a novel framework/representation, named [method name] for [xxx task]. + +% One-sentence key novelty +%% Example: To that end, we propose techniques to represent a given subject with rare token identifiers and fine-tune a pre-trained, diffusion-based text-to-image framework that operates in two steps; generating a low-resolution image from text and subsequently applying super-resolution (SR) diffusion models. +Our innovation is in [one sentence for key novelty]. + +% Teaser +%% Example: The basic idea is illustrated in Figure 2. +The basic idea is illustrated in [xxx Figure]. + +% Contribution 1 details +%% Example: We first fine-tune the low-resolution text-to-image model with the input images and text prompts containing a unique identifier followed by the class name of the subject (e.g., “A [V] dog”). +Specifically, [how contribution 1 works]. + +% Advantage of contribution 1 +%% Example: This model is inspired by the latent variable model in statistics, which enables us to effectively integrate observations at different frames. +In contrast to previous methods, [advantage of contribution 1]. + +% Challenge motivating contribution 2 +%% Example: In order to prevent overfitting and language drift [35, 40] that cause the model to associate the class name (e.g., “dog”) with the specific instance +However, [another technical challenge]. + +% Contribution 2 details +%% Example: we propose an autogenous, class-specific prior preservation loss, which leverages the semantic prior on the class that is embedded in the model, and encourages it to generate diverse instances of the same class as our subject. +Specifically, [how contribution 2 works]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md new file mode 100644 index 0000000..becdcd0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md @@ -0,0 +1,18 @@ +# Pipeline Version 3 (New Module on Existing Pipeline) + + +`Version 3: Build on a prior pipeline and introduce one new module, with a teaser figure for the basic idea.` + +```latex +% In this paper, we propose a learning-based snake algorithm, named deep snake, for real-time instance segmentation. + +% Inspired by previous methods [21, 25], deep snake takes an initial contour as input and deforms it by regressing vertex-wise offsets. + +% Our innovation is introducing the circular convolution for efficient feature learning on a contour, as illustrated in Figure 1. + +% We observe that the contour is a cycle graph that consists of a sequence of vertices connected in a closed cycle. Since every vertex has the same degree equal to two, we can apply the standard 1D convolution on the vertex features. + +% Considering that the contour is periodic, deep snake introduces the circular convolution, which indicates that an aperiodic function (1D kernel) is convolved in the standard way with a periodic function (features defined on the contour). + +% The kernel of circular convolution encodes not only the feature of each vertex but also the relationship among neighboring vertices. In contrast, the generic GCN performs pooling to aggregate information from neighboring vertices. The kernel function in our circular convolution amounts to a learnable aggregation function, which is more expressive and results in better performance than using a generic GCN, as demonstrated by our experimental results in Section 5.2. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-4-observation-driven.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-4-observation-driven.md new file mode 100644 index 0000000..254a5b1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/pipeline-version-4-observation-driven.md @@ -0,0 +1,16 @@ +# Pipeline Version 4 (Observation-Driven Contribution) + + +`Version 4: Contribution comes from one important observation. Introduce key innovation first, then intuitive observation as motivation, then method details, then benefits.` + +```latex +% In this paper, we propose a learning-based snake algorithm, named deep snake, for real-time instance segmentation. + +% Our innovation is introducing the circular convolution for efficient feature learning on a contour, as illustrated in Figure 1. + +% We observe that the contour is a cycle graph that consists of a sequence of vertices connected in a closed cycle. Since every vertex has the same degree equal to two, we can apply the standard 1D convolution on the vertex features. + +% Considering that the contour is periodic, deep snake introduces the circular convolution, which indicates that an aperiodic function (1D kernel) is convolved in the standard way with a periodic function (features defined on the contour). + +% The kernel of circular convolution encodes not only the feature of each vertex but also the relationship among neighboring vertices. In contrast, the generic GCN performs pooling to aggregate information from neighboring vertices. The kernel function in our circular convolution amounts to a learnable aggregation function, which is more expressive and results in better performance than using a generic GCN, as demonstrated by our experimental results in Section 5.2. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-1-existing-task.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-1-existing-task.md new file mode 100644 index 0000000..831dedb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-1-existing-task.md @@ -0,0 +1,32 @@ +# Technical Challenge Version 1 (Existing Task, Existing Methods) + + +`Version 1: For existing tasks with existing methods, discuss the challenge chain from traditional methods to recent methods and finally to the challenge we solve.` + +```latex +% Discuss general technical challenges of this task (to lead into recent methods) +%% Example 1: This problem is quite challenging from many perspectives, including object detection under severe occlusions, variations in lighting and appearance, and cluttered background objects. +%% Example 2: This problem is particularly challenging due to the inherent ambiguity on acquiring human geometry, materials and motions from images. +This problem is particularly challenging due to several factors, including [xxx reason], [xxx reason], and [xxx reason]. + +% Briefly introduce one class of traditional methods, then discuss their technical challenge +%% Example: Traditional methods have shown that pose estimation can be achieved by establishing the correspondences between an object image and the object model. +To overcome these challenges, traditional methods [how they work], [what they achieve]. + +%% Example: They rely on hand-crafted features, which are not robust to image variations and background clutters. +However, they [technical challenge they face]. + +% Briefly introduce one class of recent methods 1 (optional), then discuss their challenge +%% Example: Deep learning based methods train end-to-end neural networks that take an image as input and output its corresponding pose. +Recently, [xxx methods] [how they work], [what they achieve]. + +%% Example: However, generalization remains as an issue, as it is unclear that such end-to-end methods learn sufficient feature representations for pose estimation. +However, they [limitation], because [xxx technical reason]. + +% Briefly introduce one class of recent methods 2, then discuss their challenge (must lead to our solved challenge) +%% Example: Some recent methods use CNNs to first regress 2D keypoints and then compute 6D pose parameters using the Perspective-n-Point (PnP) algorithm. In other words, the detected keypoints serve as an intermediate representation for pose estimation. Such two-stage approaches achieve state-of-the-art performance, thanks to robust detection of keypoints. +To overcome this challenge, [xxx methods] [how they work], [what they achieve]. + +%% Example: However, these methods have difficulty in tackling occluded and truncated objects, since part of their keypoints are invisible. Although CNNs may predict these unseen keypoints by memorizing similar patterns, generalization remains difficult. +However, they [limitation], because [xxx technical reason]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md new file mode 100644 index 0000000..3eb078e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md @@ -0,0 +1,33 @@ +# Technical Challenge Version 2 (Existing Task, Insight Backed by Traditional Methods) + + +`Version 2: For existing tasks, if our technical insight was used in traditional methods, discuss that line to provide conceptual backing.` + +```latex +% Introduce one class of traditional/recent methods and discuss their technical challenge (to lead to our insight) +%% Example (Deep Snake): Most of the state-of-the-art instance segmentation methods perform pixel-wise segmentation within a bounding box given by an object detector. +%% Example (ManhattanSDF): Given input images, traditional methods generally estimate the depth map for each image based on the multi-view stereo (MVS) algorithms and then fuse estimated depth maps into 3D models. +Traditional/recent methods [how they work], [what they achieve]. + +%% Example (Deep Snake): They may be sensitive to the inaccurate bounding box. Moreover, representing an object shape as dense binary pixels generally results in costly post-processing. +%% Example (ManhattanSDF): Although these methods achieve successful reconstruction in most cases, they have difficulty in handling low-textured regions, e.g., floors and walls of indoor scenes, due to the unreliable stereo matching in these regions. +However, they [limitation], because [xxx technical reason]. + +% Discuss traditional methods that used an insight similar to ours (implicitly backing our idea) +%% Example (Deep Snake): An alternative shape representation is the object contour, which is a set of vertices along the object silhouette. In contrast to pixel-based representation, a contour is not limited within a bounding box and has fewer parameters. Such a contour-based representation has long been used in image segmentation since the seminal work by Kass et al., which is well known as snakes or active contours. +%% Example (ManhattanSDF): To improve the reconstruction of low-textured regions, a typical approach is leveraging the planar prior of manmade scenes, which has long been explored in literature. A renowned example is the Manhattanworld assumption, i.e., the surfaces of man-made scenes should be aligned with three dominant directions. +To overcome this problem, a typical approach is [xxx insight], which has long been explored in literature. + +These methods [how they work]. + +%% Example (Deep Snake): While many variants have been developed in literature, these methods are prone to local optima as the objective functions are handcrafted and typically nonconvex. +%% Example (ManhattanSDF): However, all of them focus on optimizing per-view depth maps instead of the full scene models in 3D space. As a result, depth estimation and plane segmentation could still be inconsistent among views, yielding suboptimal reconstruction quality as demonstrated by our experimental results in Section 5.3. +However, they [limitation], because [xxx technical reason]. + +% Then discuss newer methods and their remaining challenge (must lead to our solved challenge) +%% Example: There is a recent trend to represent 3D scenes as implicit neural representations and learn the representations from images with differentiable renderers. In particular, [49, 54, 55] use a signed distance field (SDF) to represent the scene and render it into images based on the sphere tracing or volume rendering. Thanks to the well-defined surfaces of SDFs, they recover high-quality 3D geometries from images. +To overcome this challenge, [xxx methods] [how they work], [what they achieve]. + +%% Example: However, these methods essentially rely on the multi-view photometric consistency to learn the SDFs. So they still suffer from poor performance in low-textured planar regions, as shown in Figure 1, as many plausible solutions may satisfy the photometric constraint in low-textured planar regions. +However, they [limitation], because [xxx technical reason]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-3-novel-task.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-3-novel-task.md new file mode 100644 index 0000000..fde702a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/technical-challenge-version-3-novel-task.md @@ -0,0 +1,21 @@ +# Technical Challenge Version 3 (Novel Task) + + +`Version 3: For novel tasks without direct methods, define the challenge directly and decompose it by requirement/challenge points.` + +```latex +% To achieve xx goal, several requirements/challenges must be satisfied. +%% Example: In this work, our goal is to build a model that captures such object intrinsics from a single image. This problem is challenging for three reasons. + +% Describe point 1 +%% Example: First, we only have a single image. This makes our work fundamentally different from existing works on 3D-aware image generation models [8, 9, 27, 28], which typically require a large dataset of thousands of instances for training. In comparison, the single image contains at most a few dozen instances, making the inference problem highly under-constrained. + +% Describe point 2 +%% Example: Second, these already limited instances may vary significantly in pixel values. This is because they have different poses and illumination conditions, but neither of these factors are annotated or known. We also cannot resort to existing tools for pose estimation based on structure from motion, such as COLMAP [35], because the appearance variations violate the assumptions of epipolar geometry. + +% Describe point 3 +%% Example: Finally, the object intrinsics we aim to infer are probabilistic, not deterministic: no two roses in the natural world are identical, and we want to capture a distribution of their geometry, texture, and material to exploit the underlying multi-view information. +``` + +See also: +1. `references/examples/introduction/novel-task-challenge-decomposition.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-1-task-then-application.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-1-task-then-application.md new file mode 100644 index 0000000..75e91bf --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-1-task-then-application.md @@ -0,0 +1,14 @@ +# Introduction Version 1: Task First, Then Application + + +`Version 1: If the task is relatively niche, introduce the task first, then introduce applications.` + +```latex +% Introduce Task (if the task is very familiar, this part can be skipped) +%% Example: Object pose estimation aims to estimate object's orientation and translation relative to a canonical frame from a single image. +[xxx task] targets at recovering/reconstructing/estimating [xxx output] from [xxx input]. + +% Introduce Application +%% Example: Accurate pose estimation is essential for a variety of applications such as augmented reality, autonomous driving and robotic manipulation. +[xxx task] has a variety of applications such as [xxx], [xxx], and [xxx]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-2-application-first.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-2-application-first.md new file mode 100644 index 0000000..9550e3a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-2-application-first.md @@ -0,0 +1,10 @@ +# Introduction Version 2: Application First + + +`Version 2: If the task is already familiar to most readers, introduce applications directly.` + +```latex +% Introduce Application +%% Example: Accurate pose estimation is essential for a variety of applications such as augmented reality, autonomous driving and robotic manipulation. +[xxx task] has a variety of applications such as [xxx], [xxx], and [xxx]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-3-general-to-specific-setting.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-3-general-to-specific-setting.md new file mode 100644 index 0000000..b56dcb6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-3-general-to-specific-setting.md @@ -0,0 +1,14 @@ +# Introduction Version 3: General Application -> Specific Setting + + +`Version 3: Introduce applications of the general task first, then introduce the specific task setting. (Personally recommended when the setting is relatively new.)` + +```latex +% Introduce applications of the general task +%% Example: Accurate pose estimation is essential for a variety of applications such as augmented reality, autonomous driving and robotic manipulation. +[xxx task] has a variety of applications such as [xxx], [xxx], and [xxx]. + +% Introduce the specific task setting +%% Example: This paper focuses on the specific setting of recovering the 6DoF pose of an object, i.e., rotation and translation in 3D, from a single RGB image of that object. +This paper focuses on the specific setting of recovering/reconstructing/estimating [xxx output] from [xxx input]. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-4-open-with-challenge.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-4-open-with-challenge.md new file mode 100644 index 0000000..f310a23 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/introduction/version-4-open-with-challenge.md @@ -0,0 +1,20 @@ +# Introduction Version 4: Open with Application and Challenge + + +`Version 4: If the task is familiar, introduce applications directly and expose the target technical challenge in the opening paragraph via previous methods.` + +Expert notes (faithful translation): + +1. It is often good if the opening paragraph already states what we want to solve. +2. But this style requires suitable conditions and is less common. +3. Usually, several prior-method paragraphs are still needed before the target challenge becomes clear. + +```latex +% Introduce Application +%% Example 1: Reconstructing 3D scenes from multi-view images is a cornerstone of many applications such as augmented reality, robotics, and autonomous driving. +%% Example 2: Instance segmentation is the cornerstone of many computer vision tasks, such as video analysis, autonomous driving, and robotic grasping, which require both accuracy and efficiency. + +% Use previous methods to expose the target technical challenge +%% Example 1: Given input images, traditional methods [43, 44, 59] generally estimate the depth map for each image based on the multi-view stereo (MVS) algorithms and then fuse estimated depth maps into 3D models. Although these methods achieve successful reconstruction in most cases, they have difficulty in handling low-textured regions, e.g., floors and walls of indoor scenes, due to the unreliable stereo matching in these regions. +%% Example 2: Most of the state-of-the-art instance segmentation methods [18, 27, 5, 19] perform pixel-wise segmentation within a bounding box given by an object detector [36], which may be sensitive to the inaccurate bounding box. Moreover, representing an object shape as dense binary pixels generally results in costly post-processing. +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method-examples.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method-examples.md new file mode 100644 index 0000000..948e69d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method-examples.md @@ -0,0 +1,24 @@ +# Method Examples Index + +All method example cites should point to the local files below. + +## A. Planning and Writing Workflow + +1. Pre-writing questions: `references/examples/method/pre-writing-questions.md` + +## B. Module Triad and Module-Level Writing + +1. Module triad (Neural Body): `references/examples/method/module-triad-neural-body.md` +2. Neural Body figure text conversion: `references/examples/method/neural-body-annotated-figure-text.md` +3. Module design (Instant-NGP): `references/examples/method/module-design-instant-ngp.md` +4. Module motivation patterns: `references/examples/method/module-motivation-patterns.md` + +## C. Section-Level Templates + +1. Method section skeleton: `references/examples/method/section-skeleton.md` +2. Overview template: `references/examples/method/overview-template.md` +3. Example of the three elements: `references/examples/method/example-of-the-three-elements.md` + +## D. Clarity and Troubleshooting + +1. Common issues note: `references/examples/method/method-writing-common-issues-note.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/example-of-the-three-elements.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/example-of-the-three-elements.md new file mode 100644 index 0000000..df9d8ec --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/example-of-the-three-elements.md @@ -0,0 +1,67 @@ +# Example of the Three Elements + +This example uses `%` comments as annotations. +Each `% ...` annotation explains the paragraph(s) immediately below it. + +```latex +\begin{quote} +\textbf{Annotation rule.} In this example, each line starting with \% labels the role of the paragraph(s) directly below it. +\end{quote} + +\begin{itemize} +\item Module design (data structure) +\item Motivation of this module +\item Technical advantages of this module +\item Module design (forward process) +\end{itemize} + +\subsection{3.1. Structured latent codes} + +% Module design: introduce the module's data structure +To control the spatial locations of latent codes with the human pose, we anchor these latent codes to a deformable human body model (SMPL) [38]. SMPL is a skinned vertex-based model, which is defined as a function of shape parameters, pose parameters, and a rigid transformation relative to the SMPL coordinate system. The function outputs a posed 3D mesh with 6890 vertices. Specifically, we define a set of latent codes \( Z = \{z_1, z_2, ..., z_{6890}\} \) on vertices of the SMPL model. For the frame \( t \), SMPL parameters \( S_t \) are estimated from the multi-view images \( \{I_t^c \mid c = 1, ..., N_c\} \) using [26]. The spatial locations of the latent codes are then transformed based on the human pose \( S_t \) for the density and color regression. Figure 3 shows an example. The dimension of latent code \( z \) is set to 16 in our experiments. + +% Technical advantages of this module +Similar to the local implicit representations [25, 5, 18], the latent codes are used with a neural network to represent the local geometry and appearance of a human. Anchoring these codes to a deformable model enables us to represent a dynamic human. With the dynamic human representation, we establish a latent variable model that maps the same set of latent codes to the implicit fields of density and color at different frames, which naturally integrates observations at different frames. + +\subsection{3.2. Code diffusion} + +% Motivation of this module +Figure 3(a) shows the process of code diffusion. The implicit fields assign the density and color to each point in the 3D space, which requires us to query the latent codes at continuous 3D locations. This can be achieved with the trilinear interpolation. However, since the structured latent codes are relatively sparse in the 3D space, directly interpolating the latent codes leads to zero vectors at most 3D points. To solve this problem, we diffuse the latent codes defined on the surface to nearby 3D space. + +% Module design: introduce module design by describing the module forward process +Inspired by [65, 56, 49], we choose the SparseConvNet [21] to efficiently process the structured latent codes, whose architecture is described in Table 1. Specifically, based on the SMPL parameters, we compute the 3D bounding box of the human and divide the box into small voxels with voxel size of \( 5mm \times 5mm \times 5mm \). The latent code of a non-empty voxel is the mean of latent codes of SMPL vertices inside this voxel. SparseConvNet utilizes 3D sparse convolutions to process the input volume and output latent code volumes with \( 2\times, 4\times, 8\times, 16\times \) downsampled sizes. With the convolution and downsampling, the input codes are diffused to nearby space. Following [56], for any point in 3D space, we interpolate the latent codes from multi-scale code volumes of network layers 5, 9, 13, 17, and concatenate them into the final latent code. Since the code diffusion should not be affected by the human position and orientation in the world coordinate system, we transform the code locations to the SMPL coordinate system. + +For any point \( \mathbf{x} \) in 3D space, we query its latent code from the latent code volume. Specifically, the point \( \mathbf{x} \) is first transformed to the SMPL coordinate system, which aligns the point and the latent code volume in 3D space. Then, the latent code is computed using the trilinear interpolation. For the SMPL parameters \( S_t \), we denote the latent code at point \( \mathbf{x} \) as \( \psi(\mathbf{x}, Z, S_t) \). The code vector is passed into MLP networks to predict the density and color for point \( \mathbf{x} \). + +\subsection{3.3. Density and color regression} + +Figure 3(b) overviews the regression of density and color for any point in 3D space. The density and color fields are represented by MLP networks. Details of network architectures are described in the supplementary material. + +% Module design: introduce module design by describing the module forward process +\textbf{Density model.} For the frame \( t \), the volume density at point \( \mathbf{x} \) is predicted as a function of only the latent code \( \psi(\mathbf{x}, Z, S_t) \), which is defined as: + +\[ +\sigma_t(\mathbf{x}) = M_{\sigma}(\psi(\mathbf{x}, Z, S_t)), +\tag{1} +\] + +where \( M_{\sigma} \) represents an MLP network with four layers. + +% Module design: introduce the module's data structure +\textbf{Color model.} Similar to [37, 44], we take both the latent code \( \psi(\mathbf{x}, Z, S_t) \) and the viewing direction \( \mathbf{d} \) as input for the color regression. To model the location-dependent incident light, the color model also takes the spatial location \( \mathbf{x} \) as input. We observe that temporally-varying factors affect the human appearance, such as secondary lighting and self-shadowing. Inspired by the auto-decoder [48], we assign a latent embedding \( \ell_t \) for each video frame \( t \) to encode the temporally-varying factors. + +% Module design: introduce module design by describing the module forward process +Specifically, for the frame \( t \), the color at \( \mathbf{x} \) is predicted as a function of the latent code \( \psi(\mathbf{x}, Z, S_t) \), the viewing direction \( \mathbf{d} \), the spatial location \( \mathbf{x} \), and the latent embedding \( \ell_t \). Following [51, 44], we apply the positional encoding to both the viewing direction \( \mathbf{d} \) and the spatial location \( \mathbf{x} \), which enables better learning of high frequency functions. The color model at frame \( t \) is defined as: + +\[ +c_t(\mathbf{x}) = M_c(\psi(\mathbf{x}, Z, S_t), \gamma_d(\mathbf{d}), \gamma_x(\mathbf{x}), \ell_t), +\tag{2} +\] + +where \( M_c \) represents an MLP network with two layers, and \( \gamma_d \) and \( \gamma_x \) are positional encoding functions for viewing direction and spatial location, respectively. We set the dimension of \( \ell_t \) to 128 in experiments. + +\subsection{3.4. Volume rendering} + +% Module design: introduce module design by describing the module forward process +Given a viewpoint, we utilize the classical volume rendering techniques to render the Neural Body into a 2D image. The pixel colors are estimated via the volume rendering integral equation [27] that accumulates volume densities and colors along the corresponding camera ray. In practice, the integral is approximated using numerical quadrature [41, 44]. Given a pixel, we first compute its camera ray \( \mathbf{r} \) using the camera parameters and sample \( N_k \) points \( \{\mathbf{x}_k\}_{k=1}^{N_k} \) along camera ray \( \mathbf{r} \) between near and far bounds. The scene bounds are estimated based on the SMPL model. Then, Neural Body predicts volume densities and colors at these points. For the video frame \( t \), the rendered color \( \hat{C}_t(\mathbf{r}) \) ... +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/method-writing-common-issues-note.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/method-writing-common-issues-note.md new file mode 100644 index 0000000..f701c6c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/method-writing-common-issues-note.md @@ -0,0 +1,10 @@ +# Method Writing Common Issues (Reference Note) + +Original source mentioned in your notes: + +1. `Method writing common issues (PDF in your source notes)` + +Usage recommendation: + +1. Use this reference as a troubleshooting checklist after drafting Method. +2. Prioritize unclear motivation, broken flow, missing implementation details, and inconsistent terms. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-design-instant-ngp.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-design-instant-ngp.md new file mode 100644 index 0000000..255ac21 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-design-instant-ngp.md @@ -0,0 +1,55 @@ +# Module Design Example + +This example uses `%` comments as annotations. +Each `% ...` annotation explains the paragraph(s) immediately below it. + +```latex +\begin{quote} +\textbf{Annotation rule.} In this example, each line starting with \% labels the role of the paragraph(s) directly below it. +\end{quote} + +\begin{itemize} +\item Motivation of this module +\item Module design (data structure) +\item Module design (forward process) +\end{itemize} + +\section{3 \quad MULTIRESOLUTION HASH ENCODING} + +% Motivation of this module +Given a fully connected neural network \(m(y;\Phi)\), we are interested in an encoding of its inputs \(y=\operatorname{enc}(x;\theta)\) that improves the approximation quality and training speed across a wide range of applications without incurring a notable performance overhead. + +% Module design: introduce the module's data structure +Our neural network not only has trainable weight parameters \(\Phi\), but also trainable encoding parameters \(\theta\). These are arranged into \(L\) levels, each containing up to \(T\) feature vectors with dimensionality \(F\). Typical values for these hyperparameters are shown in Table 1. Figure 3 illustrates the steps performed in our multiresolution hash encoding. Each level (two of which are shown as red and blue in the figure) is independent and conceptually stores feature vectors at the vertices of a grid, the resolution of which is chosen to be a geometric progression between the coarsest and finest resolutions \([N_{\min},N_{\max}]\): + +\[ +N_l := \left\lfloor N_{\min}\cdot b^l \right\rfloor, \tag{2} +\] + +\[ +b := \exp\!\left(\frac{\ln N_{\max}-\ln N_{\min}}{L-1}\right). \tag{3} +\] + +\(N_{\max}\) is chosen to match the finest detail in the training data. Due to the large number of levels \(L\), the growth factor is usually small. Our use cases have \(b\in[1.26,2]\). + +% Module design: introduce module design by describing the module forward process +Consider a single level \(l\). The input coordinate \(x\in\mathbb{R}^d\) is scaled by that level's grid resolution before rounding down and up: +\[ +\lfloor x_l \rfloor := \lfloor x\cdot N_l \rfloor,\quad +\lceil x_l \rceil := \lceil x\cdot N_l \rceil. +\] + +\(\lfloor x_l \rfloor\) and \(\lceil x_l \rceil\) span a voxel with \(2^d\) integer vertices in \(\mathbb{Z}^d\). We map each corner to an entry in the level's respective feature vector array, which has fixed size of at most \(T\). For coarser levels where a dense grid requires fewer than \(T\) parameters, i.e. \((N_l+1)^d \le T\), this mapping is 1:1. At finer levels, we use a hash function \(h:\mathbb{Z}^d\rightarrow\mathbb{Z}_T\) to index into the array, effectively treating it as a hash table, although there is no explicit collision handling. We rely instead on the gradient-based optimization to store appropriate sparse detail in the array, and the subsequent neural network \(m(y;\Phi)\) for collision resolution. The number of trainable encoding parameters \(\theta\) is therefore \(O(T)\) and bounded by \(T\cdot L\cdot F\), which in our case is always \(T\cdot16\cdot2\) (Table 1). + +We use a spatial hash function [Teschner et al. 2003] of the form +\[ +h(x)=\left(\bigoplus_{i=1}^{d} x_i\pi_i\right)\bmod T, \tag{4} +\] +where \(\oplus\) denotes the bit-wise XOR operation and \(\pi_i\) are unique, large prime numbers. Effectively, this formula XORs the results of a per-dimension linear congruential (pseudo-random) permutation [Lehmer 1951], \emph{decorrelating} the effect of the dimensions on the hashed value. Notably, to achieve (pseudo-)independence, only \(d-1\) of the \(d\) dimensions must be permuted, so we choose \(\pi_1:=1\) for better cache coherence, \(\pi_2=2{,}654{,}435{,}761\), and \(\pi_3=805{,}459{,}861\). + +Lastly, the feature vectors at each corner are \(d\)-linearly interpolated according to the relative position of \(x\) within its hypercube, i.e. the interpolation weight is \(w_l := x_l-\lfloor x_l \rfloor\). + +Recall that this process takes place independently for each of the \(L\) levels. The interpolated feature vectors of each level, as well as auxiliary inputs \(\xi\in\mathbb{R}^E\) (such as the encoded view direction and textures in neural radiance caching), are concatenated to produce \(y\in\mathbb{R}^{LF+E}\), which is the encoded input \(\operatorname{enc}(x;\theta)\) to the MLP \(m(y;\Phi)\). + +\textbf{Performance vs. quality.} Choosing the hash table size \(T\) provides a trade-off between performance, memory and quality. Higher values of \(T\) result in higher quality and lower performance. The memory ... +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-motivation-patterns.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-motivation-patterns.md new file mode 100644 index 0000000..d85d88f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-motivation-patterns.md @@ -0,0 +1,15 @@ +# Module Motivation Writing Patterns + + +`Module motivation is usually problem-driven: because a problem exists, we design xx to solve it.` + +Typical opening sentences: + +1. `A remaining problem/challenge is ...` +2. `However, we ...` +3. `Previous methods have difficulty in ...` + +Usage note: + +1. State the specific failure before introducing the module. +2. Keep motivation independent from implementation details. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-triad-neural-body.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-triad-neural-body.md new file mode 100644 index 0000000..91b5dee --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/module-triad-neural-body.md @@ -0,0 +1,19 @@ +# Module Triad Example (Neural Body) + +`Use Neural Body to understand the three elements of a module: design, motivation, and technical advantages.` + +Local source references: + +1. Annotated figure showing motivation/design/advantages split. +3. Text-converted annotation notes: `references/examples/method/neural-body-annotated-figure-text.md` + +Triad mapping template: + +1. Module design: what representation/network is built and how forward process runs. +2. Motivation: what unresolved challenge requires this module. +3. Technical advantages: why this module performs better than alternatives. + +Direct usage: + +1. Read `neural-body-annotated-figure-text.md` to map each paragraph to one triad element. +2. Rebuild your own Method subsection with the same triad order. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/neural-body-annotated-figure-text.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/neural-body-annotated-figure-text.md new file mode 100644 index 0000000..249ed0b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/neural-body-annotated-figure-text.md @@ -0,0 +1,66 @@ +# Neural Body Annotated Figure (Text Conversion) + +This file converts the annotated Neural Body figure into reusable writing notes. + +## Purpose + +Use this mapping to understand how one Method section can explicitly separate: + +1. Module motivation +2. Module design (data structure) +3. Module design (forward process) +4. Technical advantages + +## Block-by-Block Mapping + +### Section 3.1: Structured Latent Codes + +1. **Module design (data structure)** +- The paragraph defines structured latent codes anchored to the deformable human model (SMPL). +- It explains what is constructed (latent codes + their anchor positions + frame-dependent transformation by pose). + +2. **Technical advantages** +- The paragraph explains why this design works better: dynamic-human representation and cross-frame integration of observations. +- It highlights why anchoring codes to deformable geometry is beneficial. + +### Section 3.2: Code Diffusion + +1. **Motivation of this module** +- The paragraph states the remaining problem: direct interpolation of sparse structured codes leads to near-zero vectors at many 3D points. +- This motivates diffusion from surface codes to nearby 3D space. + +2. **Module design (forward process)** +- The paragraph explains the execution pipeline: build sparse latent volumes, run sparse convolutions, interpolate latent codes at query points, and feed codes to prediction networks. +- This is a canonical input -> steps -> output module description. + +### Section 3.3: Density and Color Regression + +1. **Module design (forward process) for density model** +- The density paragraph defines how density is regressed from latent code and frame condition. + +2. **Module design (data structure) for color model** +- The color paragraph introduces required inputs/embeddings (latent code, view direction, spatial location, temporal embedding). + +3. **Module design (forward process) for color model** +- The next paragraph describes how those inputs are encoded and passed into the color MLP for final color prediction. + +### Section 3.4: Volume Rendering + +1. **Module design (forward process)** +- The paragraph describes ray sampling and volume integration to render image outputs from predicted density/color fields. + +## Reusable Writing Pattern from This Figure + +For each module subsection, follow this order: + +1. `Motivation`: state unresolved challenge and technical reason. +2. `Design-1`: define structure/representation/network. +3. `Design-2`: describe forward process in execution order. +4. `Advantage`: explain why this module improves over alternatives. + +## Suggested Paragraph Starters + +1. Motivation: `A remaining challenge is ...` +2. Data structure design: `We represent ... with ...` +3. Forward process: `Given [input], we first ... then ... finally ...` +4. Technical advantage: `Compared with previous methods, this design ... because ...` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/overview-template.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/overview-template.md new file mode 100644 index 0000000..ca9cbfe --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/overview-template.md @@ -0,0 +1,30 @@ +# Method Overview Template + + +`Overview usually includes setting, core contribution, optional figure pointer, and subsection map.` + +```latex +% Overview +% One or two sentences for setting +%% Example 1: Given a sparse multi-view video of a performer, our task is to generate a free-viewpoint video of the performer. +%% Example 2: Given an image, the task of pose estimation is to detect objects and estimate their orientations and translations in the 3D space. + +% One or two sentences for core contribution +%% Example 1: We build upon prior work for static scenes [46], to which we add the notion of time, and estimate 3D motion by explicitly modeling forward and backward scene flow as dense 3D vector fields. +%% Example 2: Inspired by [21, 25], we perform object segmentation by deforming an initial contour to match object boundary. +%% Example 3: Inspired by recent methods [29, 30, 36], we estimate the object pose using a two-stage pipeline: we first detect 2D object keypoints using CNNs and then compute 6D pose parameters using the PnP algorithm. Our innovation is in a new representation for 2D object keypoints as well as a modified PnP algorithm for pose estimation. + +% If pipeline/framework is novel, point to figure +%% Example: The overview of the proposed model is illustrated in Figure 3. + +% Explain what Section 3.1 covers +%% Example 1: Neural Body starts from a set of structured latent codes attached to the surface of a deformable human model (Section 3.1). +%% Example 2: In this section, we first describe how to model 3D scenes with MLP maps (Section 3.1). + +% Explain what Section 3.2 covers +%% Example 1: The latent code at any location around the surface can be obtained with a code diffusion process (Section 3.2) and then decoded to density and color values by neural networks (Section 3.3). +%% Example 2: Then, Section 3.2 discusses how to represent volumetric videos with dynamic MLP maps. + +% Explain what Section 3.3 covers +%% Example 3: Finally, we introduce some strategies to speed up the rendering process (Section 3.3). +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/pre-writing-questions.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/pre-writing-questions.md new file mode 100644 index 0000000..8a971c0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/pre-writing-questions.md @@ -0,0 +1,17 @@ +# Method Pre-Writing Questions + + +`Before writing Method, answer: (1) what modules exist, and (2) for each module, what is its workflow, why is it needed, and why does it work.` + +```text +Questions: +(1) What modules are in the method? +(2) For each module, answer three questions: + - What is this module's workflow? + - Why do we need this module? + - Why does this module work? +``` + +Recommended action: + +1. Organize answers in a mind map or table before writing paragraphs. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/section-skeleton.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/section-skeleton.md new file mode 100644 index 0000000..07eee76 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/examples/method/section-skeleton.md @@ -0,0 +1,9 @@ +# Method Section Skeleton + +```latex +\section{Method} +% Overview +% Section 3.1 +% Section 3.2 +% Section 3.3 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/experiments.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/experiments.md new file mode 100644 index 0000000..5b42791 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/experiments.md @@ -0,0 +1,102 @@ +# Experiments Writing Guide + +## Goal + +Convince reviewers with complete evidence on effectiveness, causality, and practical value. + +## Three Core Questions + +1. Is the method better than strong baselines? + - Run comparison experiments against strong and recent baselines. + - Report standard metrics on the main benchmark(s). + - Include SOTA or strongest public methods, not only weak baselines. + - Keep protocol fair (same data split, preprocessing, and evaluation settings). +2. Which modules/design choices make the gain? + - Run ablation studies for each key module/design choice. + - Use remove/replace/disable variants and report delta to full model. + - Include component interaction ablations when modules are coupled. +3. How far can the method generalize under harder settings? + - Run demos/evaluations on harder or out-of-distribution settings. + - Add stress-test scenarios (more complex scenes, rarer cases, noisier inputs, or stricter constraints). + - Report both gains and failure modes to show realistic boundaries. + +## Experiment Planning + +```mermaid +flowchart TB + A["Key Paper Claims"] --> B["What Contributions Are Claimed?"] + B --> C1["Contribution 1"] + B --> C2["Contribution 2"] + B --> C3["Contribution 3"] + C1 --> D1["Validation Experiment 1"] + C2 --> D2["Validation Experiment 2"] + C3 --> D3["Validation Experiment 3"] + + E["Method Pipeline Figure"] --> F["What Modules and Parameters Matter?"] + F --> G1["Technical Module 1"] + F --> G2["Technical Module 2"] + F --> G3["Key Parameter 1"] + F --> G4["Key Parameter 2"] + G1 --> H1["Ablation Study 1"] + G2 --> H2["Ablation Study 2"] + G3 --> H3["Ablation Study 3"] + G4 --> H4["Ablation Study 4"] +``` + +## Experiment Section Decomposition + +```mermaid +flowchart TB + S1["Experimental Setup"] --> S2["Validation Experiment 1"] + S2 --> S3["Validation Experiment 2"] + S3 --> S4["Ablation Studies"] +``` + +## Figure/Table Writing Rules + +`Good tables are part of experiment communication quality, not decoration.` + +1. Figure captions and table captions are equally important in the writing quality of Experiments. + +### Hard rules + +1. Put caption above the table. +2. Avoid vertical lines (`|`) in tabular columns. +3. Do not use double rules or dense `\hline` stacks. +4. Use `booktabs` style (`\toprule`, `\midrule`, `\bottomrule`) for clean structure. +5. Use as few horizontal rules as possible; lines should separate groups, not every row. +6. Highlight key numbers (best/second-best or target rows) with subtle color emphasis. + +### Readability rules from review practice + +1. Label metric direction in column headers (for example `PSNR ↑`, `LPIPS ↓`). +2. Add units when needed so values are interpretable without guessing. +3. Align text columns left; keep numeric columns consistently aligned. +4. Keep numeric precision consistent (same decimal places within a metric column). +5. Group multi-dataset or multi-setting results using `\multicolumn` + `\cmidrule`, not vertical separators. +6. One table, one message: do not mix unrelated results in a single table. +7. If rows represent different attributes/ablations, encode that explicitly in row names or attribute columns. +8. Keep caption focused on setting/protocol/notation, not long discussion. +9. If there is little detail to explain, use one concise sentence to summarize the main result. +10. For single-column figures/tables in two-column papers, prefer placing them in the right column when layout allows, so readers can enter the page from the left-top text without breaking reading flow. + +### Minimal LaTeX checklist + +1. Add packages in preamble: `\usepackage{booktabs}`, `\usepackage{colortbl,xcolor}` (and optionally `\usepackage{siunitx}` for decimal alignment). +2. Replace `\hline`-heavy style with `\toprule/\midrule/\bottomrule`. +3. Put `\caption{...}` before `\label{...}` and keep caption above. +4. Use restrained highlighting; never color too many cells. + +## Recommended Ablation Package + +1. One core ablation table for all major contributions. +2. Several focused mini-ablations for module-level design choices. +3. Matching qualitative visual results for each important ablation. + +## Experimental Rigor Checklist + +1. Are baselines recent and relevant? +2. Are metrics sufficient and standard for this task? +3. Is ablation tied to every key design claim? +4. Are claims in Abstract/Introduction supported by reported numbers? +5. Are limitations of evaluation scope explicitly stated? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/introduction.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/introduction.md new file mode 100644 index 0000000..d678070 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/introduction.md @@ -0,0 +1,408 @@ +# Introduction Writing Guide + +## Goal + +Write a strong introduction in three steps: + +1. Think through the introduction logic. +2. Apply a suitable template below. +3. Revise the introduction repeatedly. + +## Introduction Logic Map + +```mermaid +graph LR + L1[What task are we solving] + L2[Which metrics should this task improve] + L3[SOTA methods fail to meet target metrics] + L4[Root technical issue behind this failure] + L5[Our technical solution and method pipeline] + L6[Why the solution works] + L7[Additional technical contributions] + + R1[Part 1 Task applications and target metrics] + R2[Part 2 SOTA methods failure and root issue] + R3[Part 3 Proposed solution and why it works] + R4[Part 4 Additional contributions and impact] + R5[Part 5 Experiments] + + L1 --> L2 + L2 --> L3 + L3 --> L4 + L4 --> L5 + L5 --> L6 + L6 --> L7 + + R1 --> R2 + R2 --> R3 + R3 --> R4 + R4 --> R5 + + L1 --> R1 + L2 --> R1 + L3 --> R2 + L4 --> R2 + L5 --> R3 + L6 --> R3 + L7 --> R4 +``` + +## How to Think About Introduction: Backward First, Then Forward + +### Backward reasoning (answer these first) + +1. What technical problem do we solve, and why is there no well-established solution? (important) +2. What are the contributions of our pipeline (e.g., a new valuable task, a new valuable metric, a new technical problem, or a new technique)? +3. What are the benefits of our contributions, why can they solve this technical challenge, and what new insight do they bring? (important) +4. How do we use prior methods to lead readers to our solved challenge and our new insight? + +### Forward story (write in this order) + +1. Introduce the paper's task. +2. Use prior methods to lead to the technical challenge we solve. +3. Present xx contributions to solve this technical challenge. +4. Explain technical advantages of our contributions and explicitly express our new insight. (important) + +## Section Skeleton + +```latex +\section{Introduction} +% Task and application +% Technical challenge for previous methods (discuss around the technical challenge that we solved. A technical challenge includes both limitation and technical reason) +% Introduce our pipeline for solving the challenge +% Experiment +% Contributions +``` + +## Part A: Introduce Task and Application + +### Version 1 + +`Version 1: If the task is relatively niche, introduce the task first, then introduce applications.` + +Writing structure: + +1. Define the task in one clear sentence (`what output` from `what input`). +2. Briefly explain the task objective or scope (optional). +3. Introduce application value with 2-3 representative scenarios. + +Sentence skeleton: + +1. `[xxx task] targets at recovering/reconstructing/estimating [xxx output] from [xxx input].` +2. `[xxx task] has a variety of applications such as [xxx], [xxx], and [xxx].` + +Local cite: + +1. `references/examples/introduction/version-1-task-then-application.md` + +### Version 2 + +`Version 2: If the task is already familiar to most readers, introduce applications directly.` + +Writing structure: + +1. Skip formal task definition. +2. Open with application importance in one concise sentence. +3. Optionally append target requirement (e.g., accuracy/efficiency/robustness). + +Sentence skeleton: + +1. `[xxx task] has a variety of applications such as [xxx], [xxx], and [xxx].` + +Local cite: + +1. `references/examples/introduction/version-2-application-first.md` + +### Version 3 + +`Version 3: Introduce applications of the general task first, then introduce the specific task setting. (Personally recommended when the setting is relatively new.)` + +Writing structure: + +1. Start from the general task and why it matters. +2. Narrow down to the specific setting of this paper. +3. Clarify exact input/output and boundary of the setting. + +Sentence skeleton: + +1. `[general task] has a variety of applications such as [xxx], [xxx], and [xxx].` +2. `This paper focuses on the specific setting of recovering/reconstructing/estimating [xxx output] from [xxx input].` + +Local cite: + +1. `references/examples/introduction/version-3-general-to-specific-setting.md` + +### Version 4 + +`Version 4: If the task is familiar, introduce applications directly and expose the target technical challenge in the opening paragraph via previous methods (failure cases / target metric improvements).` + +Writing structure: + +1. Start with task/application importance. +2. Immediately summarize how representative previous methods work. +3. Immediately expose the unresolved failure case + technical reason. +4. Use this opening as a bridge to the later prior-work paragraphs. + +Opening-paragraph skeleton: + +1. `[Task/application importance sentence].` +2. `Given input ..., previous methods usually ...` +3. `Although they work in many cases, they fail at ... because ...` + +Expert note: + +1. It is often good if the first paragraph already states what problem you want to solve, instead of requiring several paragraphs of prior work before the challenge appears. +2. This style needs the right conditions and is less common. +3. Typical Version 4 flow: Part 1 (task + application and directly expose challenge via previous methods 1) -> Part 2 (previous methods 2 try to solve it but still fail) -> Part 3 (our method). +4. More common general flow: Part 1 (task + application) -> Part 2 (previous methods 1 + limitation) -> Part 3 (previous methods 2 + limitation; here the target challenge emerges) -> Part 4 (our method). + +Local cite: + +1. `references/examples/introduction/version-4-open-with-challenge.md` + +## Part B: Introduce Technical Challenge for Previous Methods (Very Important) + +Purpose: + +1. Discuss around the exact technical challenge we solved. +2. Build reader curiosity about how to solve this challenge. +3. Make motivation/benefit of our method clear. + +Key logic before writing (faithful translation): + +1. First make clear the logic for "leading to the technical challenge we solved". +2. For existing tasks: identify which recent methods have this challenge, why those methods exist, and optionally what earlier challenge they were trying to solve. +3. For novel tasks: at minimum, define the technical challenge solved by our pipeline. + +Important warning : + +1. Do not first present a naive solution and then describe our improvement over it. +2. That writing makes the work look like a low-score incremental patch. +3. Even if the work is actually incremental, do not write it this way. +4. Why: this writing style can erase reader curiosity and make the idea look straightforward only because the writing hand-holds the reader. + +### Technical-Challenge Version 1 (existing task, with existing methods) + +`Version 1: For existing tasks, discuss the challenge chain from general challenge -> traditional methods -> recent methods -> remaining challenge that we solve.` + +Writing structure: + +1. Start with a general challenge statement for this task. +2. Briefly summarize traditional methods and their limitation. +3. Briefly summarize recent methods (1) and their limitation with technical reason. +4. Briefly summarize recent methods (2) and their limitation with technical reason. +5. Ensure the final limitation is exactly the challenge your method solves. + +Sentence skeleton: + +1. `This problem is particularly challenging due to ...` +2. `To overcome these challenges, traditional methods ... However, they ...` +3. `Recently, ... methods ... However, they ... because ...` +4. `To overcome this challenge, ... methods ... However, they ... because ...` + +Local cite: + +1. `references/examples/introduction/technical-challenge-version-1-existing-task.md` + +### Technical-Challenge Version 2 (existing task + our insight seen in traditional methods) + +`Version 2: For existing tasks, when our insight has historical roots in traditional methods, use that line as conceptual backing and then show why new methods still fail.` + +Writing structure: + +1. Start from mainstream methods and state their limitation. +2. Introduce a classical/traditional line that already contains insight similar to yours. +3. Explain why that classical line is still insufficient. +4. Return to modern methods and show the unresolved technical reason. +5. Bridge to your method naturally. + +Sentence skeleton: + +1. `Traditional/recent methods ... However, they ... because ...` +2. `To overcome this problem, a typical approach is [insight], which has long been explored ...` +3. `However, these methods still ... because ...` +4. `To overcome this challenge, newer methods ... However, they ... because ...` + +Local cite: + +1. `references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md` + +### Technical-Challenge Version 3 (novel task, no direct methods) + +`Version 3: For novel tasks without direct prior methods, define the challenge directly and decompose it into several concrete challenge points.` + +Writing structure: + +1. State the goal and explain that the problem is challenging for N reasons. +2. Use `First/Second/Finally` to separate independent challenge points. +3. For each point, state the observable limitation and the technical reason. +4. End with a transition to your pipeline. + +Sentence skeleton: + +1. `In this work, our goal is to ... This problem is challenging for three reasons.` +2. `First, ...` +3. `Second, ...` +4. `Finally, ...` + +Local cite: + +1. `references/examples/introduction/technical-challenge-version-3-novel-task.md` + +## Part C: Introduce Our Pipeline for Solving the Challenge + +Key questions before writing: + +### For existing tasks + +1. What technical challenge does our pipeline solve? +2. What is our technical contribution? +3. Why can our method work in essence? +4. What benefits does our method have over previous methods? + +### For novel tasks + +1. What technical challenge does our pipeline solve? +2. What is our technical contribution? +3. Why can our method work in essence? + +### Pipeline Version 1 + +`Version 1: One contribution with multiple advantages, and one teaser figure to present the basic idea.` + +Writing structure: + +1. Introduce one core framework/representation for the target task. +2. Point to teaser figure for the basic idea. +3. State key novelty in one sentence. +4. Explain concrete implementation steps (`Specifically, ...`). +5. State multiple advantages (`In contrast ...`, `Another advantage ...`). + +Sentence skeleton: + +1. `In this paper, we propose a novel framework/representation, named ..., for ...` +2. `The basic idea is illustrated in Figure ...` +3. `Our innovation is in ...` +4. `Specifically, ...` +5. `In contrast to previous methods, ...` +6. `Another advantage of the proposed method is that ...` + +Local cite: + +1. `references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md` + +### Pipeline Version 2 + +`Version 2: Two contributions, and one teaser figure to present the basic idea.` + +Writing structure: + +1. Introduce framework and key novelty sentence. +2. Point to teaser figure. +3. Explain contribution 1 and its advantage. +4. Introduce a remaining challenge. +5. Explain contribution 2 as the response to that challenge. + +Sentence skeleton: + +1. `In this paper, we propose ...` +2. `Our innovation is in ...` +3. `The basic idea is illustrated in Figure ...` +4. `Specifically, ...` (contribution 1) +5. `In contrast to previous methods, ...` +6. `However, ...` (remaining challenge) +7. `Specifically, ...` (contribution 2) + +Local cite: + +1. `references/examples/introduction/pipeline-version-2-two-contributions.md` + +### Pipeline Version 3 + +`Version 3: Build on a prior pipeline and introduce one new module, with a teaser figure for the basic idea.` + +Writing structure: + +1. Start from prior pipeline setup. +2. Introduce one new module as key innovation. +3. Provide an observation that motivates the module design. +4. Explain the module mechanism. +5. Compare against generic alternatives and state why it is better. + +Sentence skeleton: + +1. `Inspired by previous methods, ...` +2. `Our innovation is introducing ...` +3. `We observe that ...` +4. `Considering that ..., we introduce ...` +5. `In contrast to ..., our module ...` + +Local cite: + +1. `references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md` + +### Pipeline Version 4 + +`Version 4: Contribution comes from one important observation. Introduce key innovation first, then a listener-friendly observation as motivation, then method details, then benefits.` + +Writing structure: + +1. State key innovation first. +2. State one intuitive observation as motivation. +3. Explain implementation details. +4. Explain technical advantage and empirical gain. + +Sentence skeleton: + +1. `Our innovation is ...` +2. `We observe that ...` +3. `Considering that ..., we ...` +4. `This leads to ... and achieves ...` + +Local cite: + +1. `references/examples/introduction/pipeline-version-4-observation-driven.md` + +### Not Recommended Writing + +`Not recommended: If the method is simple, do not hide concrete method design in Introduction and only describe abstract insights to make the work look novel.` + +Expert note: + +1. In this template, the writing craft is about making a simple pipeline sound novel. +2. The key caution: people often make the pipeline steps sound novel, not the real insight. +3. In most cases this is not recommended. The better target is to clearly explain core contribution implementation in Introduction. + +Why not recommended (writing structure warning): + +1. Presenting only abstract insight without concrete pipeline steps weakens technical clarity. +2. Introducing many new terms without mechanism-level explanation creates a novelty illusion. +3. Reviewers may interpret this as shallow or incremental work. + +Local cite: + +1. `references/examples/introduction/pipeline-not-recommended-abstract-only.md` + +## Example Bank + +1. `references/examples/introduction-examples.md` +2. `references/examples/introduction/version-1-task-then-application.md` +3. `references/examples/introduction/version-2-application-first.md` +4. `references/examples/introduction/version-3-general-to-specific-setting.md` +5. `references/examples/introduction/version-4-open-with-challenge.md` +6. `references/examples/introduction/technical-challenge-version-1-existing-task.md` +7. `references/examples/introduction/technical-challenge-version-2-existing-task-insight-backed-by-traditional.md` +8. `references/examples/introduction/technical-challenge-version-3-novel-task.md` +9. `references/examples/introduction/pipeline-version-1-one-contribution-multi-advantages.md` +10. `references/examples/introduction/pipeline-version-2-two-contributions.md` +11. `references/examples/introduction/pipeline-version-3-new-module-on-existing-pipeline.md` +12. `references/examples/introduction/pipeline-version-4-observation-driven.md` +13. `references/examples/introduction/pipeline-not-recommended-abstract-only.md` + +## Quick Quality Checklist + +1. Does the first sentence of each paragraph state its message? +2. Does each paragraph carry one message only? +3. Are technical challenge, technical reason, and solved mechanism all explicit? +4. Are claims in Introduction aligned with experiment evidence? +5. Is terminology stable across all sections? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/method.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/method.md new file mode 100644 index 0000000..667fcfe --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/method.md @@ -0,0 +1,196 @@ +# Method Writing Guide + +## Goal + +Write the Method section clearly by following this sequence: + +1. Answer key method-design questions. +2. Draw a pipeline figure sketch. +3. Write the method section step by step. + +## Pre-Writing Questions + +`Before writing Method, first answer: (1) what modules exist in the method, and (2) for each module, what is the workflow, why this module is needed, and why this module works.` + +Recommended organization: + +1. List all modules in the pipeline. +2. For each module, answer three questions: + +- How does the module run? +- Why do we need this module? +- Why does this module work? + +3. Organize answers as a mind map or a table for clarity. + +## Method Writing Steps + +`Method writing steps: (1) draw pipeline figure sketch, (2) map subsections from the sketch, (3) plan each subsection with motivation/design/advantages, (4) write module design first, (5) then add motivation and technical advantages.` + +Step-by-step workflow: + +1. Draw the pipeline figure sketch. +2. Use the sketch to organize Method subsection structure. +3. For each subsection, plan three parts: motivation, module design, and technical advantages. +4. Write module design first to build a concrete backbone. +5. Add motivation and technical advantages afterward. + +## Three Elements of a Pipeline Module + +`A pipeline module has three elements: Module design, Motivation of this module, and Technical advantages of this module.` + +### 1) Module Design + +Definition: + +1. Describe representation/network/data-structure details. +2. Describe the forward process clearly: given input -> step 1 -> step 2 -> step 3 -> output. + +### 2) Motivation of This Module + +Definition: + +1. Explain why this module is needed. +2. Use problem-driven logic: because problem X exists, we design module Y. + +### 3) Technical Advantages of This Module + +Definition: + +1. Explain why this module has technical advantage over alternatives. +2. Tie advantage to measurable behavior when possible. + +### Example of the Three Elements + +Local cite: + +1. `references/examples/method/example-of-the-three-elements.md` + +## Method Content Decomposition + +```mermaid +flowchart LR + A["Draw the technical pipeline figure"] --> B["Decompose Method content"] + B --> C1["Subsection 1 (Technical Module 1)"] + B --> C2["Subsection 2 (Technical Module 2)"] + B --> C3["Subsection 3 (Technical Module 3)"] + C1 --> D1["Motivation"] + C1 --> D2["Detailed design"] + C1 --> D3["Technical advantage"] +``` + +## How to Write Module Design + +`Module design usually has two parts: (1) describe specific data/network structures, and (2) describe forward process as input -> steps -> output.` + +Writing structure: + +1. Define key structures first (representation, network, data structure). +2. Write forward process in strict execution order. +3. End with output interpretation or purpose. + +Sentence skeleton: + +1. `We represent ... with ...` +2. `Given [input], we first ... then ... finally ...` +3. `This produces [output], which is used for ...` + +Local cite: + +1. `references/examples/method/module-design-instant-ngp.md` + +## How to Write Module Motivation + +`Module motivation is usually problem-driven: because a problem exists, we design xx to solve it.` + +Typical opening sentences: + +1. `A remaining problem/challenge is ...` +2. `However, we ...` +3. `Previous methods have difficulty in ...` + +Local cite: + +1. `references/examples/method/module-motivation-patterns.md` + +## How to Check Whether Method is Easy to Understand + +`Check method clarity from three levels: writing logic, paragraph writing, and sentence writing.` + +### 1) Logic-level check + +1. After finishing the paper, summarize the Method writing logic again. +2. Check whether this summarized logic is smooth and easy to follow. + +### 2) Paragraph-level check + +1. The first sentence of each paragraph should make readers immediately understand what this paragraph is about. +2. One paragraph should clearly deliver one message. + +### 3) Sentence-level check + +1. Carefully check whether the **motivation** of each sentence is explicit. Keep one thing clear to readers at all times: **why this sentence content is needed**. +2. Carefully check sentence-to-sentence flow. +3. Carefully check term consistency and avoid changing key terms back and forth. + +## Method Section Skeleton + +```latex +\section{Method} +% Overview +% Section 3.1 +% Section 3.2 +% Section 3.3 +``` + +Local cite: + +1. `references/examples/method/section-skeleton.md` + +## Overview Subsection + +`Overview should usually include: setting, core contribution, optional pipeline figure pointer, and a map of what each subsection contains.` + +Writing structure: + +1. One to two sentences for task setting. +2. One to two sentences for core contribution. +3. If pipeline/framework is novel, point to overview figure. +4. Tell readers what Section 3.1/3.2/3.3 covers. + +Local cite: + +1. `references/examples/method/overview-template.md` + +## Section 3.1 and Other Module Subsections + +`Basic subsection logic: (1) motivation of this module, (2) module forward process/module design, (3) technical advantages of this module.` + +Local cite: + +1. `references/examples/method/example-of-the-three-elements.md` + +## Module Writing Pattern (Mermaid) + +```mermaid +flowchart TB + M1["State module motivation (challenge)"] --> M2["Define module design (representation/network)"] + M2 --> M3["Describe forward process (input -> steps -> output)"] + M3 --> M4["Explain technical advantages and verifiable gains"] +``` + +## Implementation Details + +`Implementation details include hyperparameters (e.g., layer count, feature dimensions), coordinate transforms/normalization, and other practical details. Put them near the end of Method or in a dedicated Implementation Details section.` + +## Example Bank + +1. `references/examples/method-examples.md` +2. `references/examples/method/pre-writing-questions.md` +3. `references/examples/method/module-triad-neural-body.md` +4. `references/examples/method/module-design-instant-ngp.md` +5. `references/examples/method/module-motivation-patterns.md` +6. `references/examples/method/section-skeleton.md` +7. `references/examples/method/overview-template.md` +8. `references/examples/method/example-of-the-three-elements.md` +9. `references/examples/method/method-writing-common-issues-note.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/paper-review.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/paper-review.md new file mode 100644 index 0000000..1b83e21 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/paper-review.md @@ -0,0 +1,86 @@ +# Paper Review + +## Goal + +Use an adversarial, reviewer-style checklist to detect reject risks early and revise the paper before submission. + +## Core Principle + +Pursue perfectionism in paper quality: assume reviewers will probe every weak point and proactively fix them. + +## Critical Rule (Do Not Violate) + +Every major claim, especially in Abstract and Introduction, must be: + +1. technically correct, and +2. explicitly supported by experimental evidence. + +If a claim is not supported, either add evidence or weaken/remove the claim. + +## What Usually Gets a Paper Accepted + +1. Sufficient contribution (for example: novel task, novel pipeline, novel module, novel design choices, new experimental findings, or new insight). +2. Better empirical performance than prior methods under fair comparisons. +3. Sufficient comparison experiments and ablation studies. + +## Common Rejection Dimensions + +| Rejection Dimension | Typical Failure Signals | +| ---------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| 1. Insufficient contribution | 1.1 Targeted failure cases are too common.<br /> 1.2 Proposed technique is already well explored; expected gains are predictable/well-known. | +| 2. Unclear writing | 2.1 Missing technical details; work is not reproducible.<br />2.2 A method module lacks clear motivation. | +| 3. Weak empirical effect | 3.1 Improvement over prior methods is only marginal.<br /> 3.2 Even if better than previous methods, absolute performance is still not strong enough. | +| 4. Incomplete evaluation | 4.1 Missing ablation studies.<br />4.2 Missing important baselines or important evaluation metrics.<br /> 4.3 Datasets are too simple to prove the method truly works. | +| 5. Problematic method design | 5.1 Experimental setting is unrealistic.<br />5.2 Method has technical flaws and appears unreasonable.<br />5.3 Method is not robust and needs per-scenario hyperparameter tuning. <br /> 5.4 New design introduces stronger limitations than its benefits, leading to negative net value. | + +## End-of-Paper Self-Review Question List + +Add this checklist near the end of the draft while revising. +Use each question to trigger concrete edits before submission. + +### 1. Contribution + +1. What new knowledge does this paper give to readers? +2. Are we solving a truly meaningful failure case, not a trivial/common one? +3. Is the technical idea genuinely non-obvious beyond well-explored practice? +4. Is our gain surprising or insightful rather than a predictable improvement? +5. Is there at least one clear novelty type (task/pipeline/module/design finding/insight)? + +### 2. Writing Clarity + +1. Can a knowledgeable reader reproduce the method from the paper? +2. Did we provide enough technical detail for each key module? +3. Is the motivation of every module explicit and logically connected to a challenge? +4. Are terms and notation consistent across sections? +5. Does each paragraph carry one clear message with smooth transitions? + +### 3. Experimental Strength + +1. Are improvements over strong baselines meaningful, not just statistically tiny? +2. Is absolute performance competitive enough for the target venue? +3. Are gains consistent across multiple datasets/settings/metrics? +4. Do we report both strengths and failure cases honestly? + +### 4. Evaluation Completeness + +1. Do we include ablations for all key design choices? +2. Are all strong/recent baselines included under fair settings? +3. Are evaluation metrics standard and sufficient for this task? +4. Are datasets/scenarios challenging enough to validate real effectiveness? +5. Are comparison and ablation protocols clearly documented? + +### 5. Method Design Soundness + +1. Is the experimental setting realistic for practical use? +2. Does the method have hidden technical defects or unreasonable assumptions? +3. Is the method robust without heavy per-case hyperparameter retuning? +4. Do benefits outweigh added complexity and new limitations? +5. Could reviewers reasonably argue that the net benefit is negative? + +## Adversarial Writing Workflow + +1. Read the paper as a skeptical reviewer. +2. Answer every question above with explicit evidence from the paper. +3. Mark each item as `pass`, `needs revision`, or `needs new experiment`. +4. Revise claims, writing, experiments, or method scope accordingly. +5. Repeat until no major rejection risk remains. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/paragraph-flow.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/paragraph-flow.md new file mode 100644 index 0000000..dccc564 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/paragraph-flow.md @@ -0,0 +1,46 @@ +# Paragraph Flow + +Use this reference when the user asks whether a paragraph flows, makes sense, or +is clear. + +## Core principle + +Flow is not decoration. A paragraph flows when an external reader can identify: + +- the paragraph's single message +- how the first sentence announces that message +- how each following sentence relates to the previous one +- how the paragraph supports the section thesis + +## Reader test + +Read as a skeptical but fair external reader: + +1. Does the paragraph have one explicit message? +2. Does the first sentence state what the paragraph is doing? +3. Are all key nouns, terms and abbreviations readable without hidden context? +4. Does each sentence connect by cause, contrast, consequence, refinement, or example? +5. Is any sentence carrying material that belongs in another paragraph? + +## Reverse outlining + +For a section-level flow check: + +1. Write down the section thesis or main claim. +2. Write down each paragraph's topic sentence. +3. Write down the evidence or explanation under each paragraph. +4. Check `topic sentence -> section thesis`. +5. Check `evidence -> topic sentence`. +6. Revise or remove any paragraph that cannot be mapped cleanly. + +If reverse outlining is hard, the section probably has a hidden structure problem. + +## Repair moves + +- Split paragraphs that contain two messages. +- Move definitions before terms are reused. +- Replace vague transitions with explicit relations such as `therefore`, + `however`, `by contrast`, `for example`, or `as a result`. +- Add temporary subsection labels during revision, then remove labels that are + not needed in the final manuscript. +- Keep paragraph openings claim-first unless the section needs a brief setup. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/related-work.md b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/related-work.md new file mode 100644 index 0000000..dff0c70 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/nature-writing/references/related-work.md @@ -0,0 +1,41 @@ +# Related Work Writing Guide + +## Goal + +Position your work against the most relevant lines of research, and make your novelty easy to verify. + +## Workflow + +1. List directly competing and recent baseline papers first. +2. Group literature by technical topic (not by publication year alone). +3. For each topic: summarize common paradigm, then key limitation relevant to your challenge. +4. End each topic by clarifying your distinction. + +## Topic Design + +Use 2-4 focused topics, for example: + +1. Task-specific mainstream methods. +2. Methods closest to your core idea. +3. Auxiliary techniques your method builds on. + +## Paragraph Template + +1. Topic sentence: define scope of this topic. +2. Representative methods: one compact summary. +3. Limitation tied to your target technical challenge. +4. Transition sentence that leads to your method. + +## Do and Don't + +1. Do compare mechanisms, assumptions, and failure modes. +2. Do emphasize the exact gap your method fills. +3. Do not make Related Work a citation dump. +4. Do not hide strongest baselines. + +## Checklist + +1. Are all strongest/recent competitors covered? +2. Is each topic connected to your problem setting? +3. Is your difference explained in technical terms, not marketing terms? +4. Is citation coverage complete for all core claims? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/SKILL.md new file mode 100644 index 0000000..1037ac7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/SKILL.md @@ -0,0 +1,37 @@ +--- +name: obsidian-kb-artifacts +description: Use this skill for Obsidian-native formatting and derived artifacts such as Markdown formatting, wikilinks, registry tables, canvas files, optional Bases, CLI operations, and link repair. This skill does not decide knowledge routing. +--- + +# Obsidian KB Artifacts + +This skill handles format and artifact concerns only. + +## Responsibilities + +- Obsidian Markdown formatting +- wikilinks and embeds +- registry table formatting +- canvas generation and validation +- optional Bases generation +- Obsidian CLI operations +- link repair in canonical notes +- lint-report formatting + +## Rules + +- this skill does not decide where knowledge belongs +- `.base` is explicit-only +- `Maps/` contains derived artifacts only +- link repair should strengthen existing canonical notes, not create note sprawl +- literature canvas edges must preserve evidence strength when the source notes provide it +- do not create stable-looking claim edges from abstract-only, webpage-placeholder, or unsupported notes + +## Read next + +- `references/OBSIDIAN-MARKDOWN.md` +- `references/CANVAS.md` +- `references/BASES.md` +- `references/REGISTRY-TABLES.md` +- `references/LINK-REPAIR.md` +- `references/CLI.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/BASES.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/BASES.md new file mode 100644 index 0000000..c5096e0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/BASES.md @@ -0,0 +1,39 @@ +# BASES + +Obsidian Bases are optional helper artifacts. They are explicit-only and should not be created by default. + +## Default policy + +- Do not generate `.base` files unless the user explicitly asks for Bases or database-like views. +- Keep `.base` files under a project-local helper area only when they improve navigation. +- Do not make Bases the canonical registry or source of truth. + +## Basic structure + +A `.base` file is YAML and typically contains: + +```yaml +filters: + and: + - 'status == "active"' + +views: + - type: table + name: "Active Results" + order: + - file.name + - status + - updated +``` + +## Good use cases + +- table view for active experiments or results +- card view for paper notes +- filtered task-like view over canonical notes + +## Avoid by default + +- auto-generating many `.base` files during bootstrap +- using Bases to replace `_system/registry.md` +- coupling critical project logic to plugin-specific Base behavior diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/CANVAS.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/CANVAS.md new file mode 100644 index 0000000..69b6f50 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/CANVAS.md @@ -0,0 +1,129 @@ +# CANVAS + +Canvas files are optional derived artifacts stored under `Maps/`. They are not the source of truth. + +## Placement and scope + +- Default path: `Maps/*.canvas` +- Default auto-maintained canvas: `Maps/literature.canvas` +- Other canvases are explicit-only unless a workflow clearly requires them +- Keep canvas references project-local unless the user explicitly asks for cross-project mapping + +## Core JSON structure + +Use the standard JSON Canvas shape: + +```json +{ + "nodes": [], + "edges": [] +} +``` + +Each node needs a stable `id`, coordinates (`x`, `y`), and size (`width`, `height`). +Each edge needs `id`, `fromNode`, and `toNode`. + +## Recommended node types + +- `file` node: canonical note under `Sources/*`, `Knowledge/*`, `Experiments/*`, `Results/*`, `Writing/*` +- `text` node: short synthesis, legend, gap summary, or section heading +- `link` node: external URL when the relationship should stay outside the vault +- `group` node: visual cluster for a topic, method family, dataset family, or review bucket + +Avoid treating free-form text nodes as a second knowledge store. Durable content belongs in markdown notes first. + +## File-node conventions + +Use `file` nodes for canonical notes that already exist on disk. + +- paper/source note -> point to `Sources/Papers/*` or other `Sources/*` +- synthesis note -> point to `Knowledge/*` +- experiment note -> point to `Experiments/*` +- stable result/report -> point to `Results/*` or `Results/Reports/*` + +File nodes should reference existing files only. If the note does not exist yet, create the note first or use a temporary `text` node that clearly indicates draft intent. + +## Edge conventions + +Use edges to express relationship semantics, not decoration. + +- method extends method +- paper uses dataset +- result supports claim +- gap motivates experiment +- report summarizes experiment + +When labels are supported in the producing workflow, keep them short and explicit: +- `uses` +- `extends` +- `compares` +- `supports` +- `contradicts` +- `motivates` +- `summarizes` + +Do not draw unlabeled dense meshes when a few explicit edges communicate the structure better. + +## Group and color conventions + +Use groups to organize major clusters such as: +- `Methods` +- `Datasets` +- `Claims` +- `Gaps` +- `Experiments` +- `Results` + +Use color sparingly and consistently. Color is a navigation aid, not a semantic database. + +Suggested pattern: +- one group color per cluster family +- neutral text nodes for summaries +- do not encode critical meaning only through color + +## Layout conventions + +- Keep 50–100 px spacing between unrelated nodes +- Align related file nodes in rows or columns +- Put source papers on one side, synthesis notes in the middle, and gaps / experiments / results downstream +- Avoid overlapping groups +- Prefer a stable, readable layout over a compact but fragile layout + +## Recommended `Maps/literature.canvas` structure + +For literature workflow, prefer this shape: + +1. `Sources/Papers/*` file nodes for the key papers +2. `Knowledge/*` file nodes for: + - `Literature Overview` + - `Method Taxonomy` + - `Research Gaps` +3. `text` nodes for short bridge summaries where needed +4. groups for `Methods`, `Datasets`, `Gaps`, and `Results` +5. edges showing: + - paper -> method family + - paper -> dataset + - paper -> gap or limitation + - gap -> experiment direction + +This keeps the canvas derived from canonical notes instead of replacing them. + +## Validation checklist + +Before treating a canvas as valid, check: + +- every `file` node target exists +- every edge endpoint points to an existing node id +- node ids are unique +- groups do not reference missing child nodes +- archived notes are either intentionally preserved or relinked; no silent dangling references +- the canvas adds navigation value instead of duplicating a markdown table + +## What not to put in Canvas + +- raw source-of-truth metadata that belongs in `_system/registry.md` +- long-form synthesis that belongs in `Knowledge/*` +- unstable scratch thinking that should remain in `Daily/*` +- auto-generated project-wide mega-graphs by default + +Generate or update a canvas only when the user explicitly asks for it, or when `Maps/literature.canvas` is part of the literature workflow. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/CLI.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/CLI.md new file mode 100644 index 0000000..545cc43 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/CLI.md @@ -0,0 +1,30 @@ +# CLI + +Use the Obsidian CLI only as an optional helper for navigation, search, verification, or lightweight note actions. The filesystem remains the source of truth. + +## Common uses + +```bash +obsidian help +obsidian search query="diffusion" limit=10 +obsidian read file="My Note" +obsidian daily:append content="- [ ] Follow up" +``` + +## Good uses in Claude Scholar + +- open a note after updating it +- search a vault for a known keyword +- append a short daily action item +- verify that CLI targeting works for a specific vault + +## Do not rely on CLI for + +- canonical registry truth +- project binding state +- lifecycle decisions +- sync logic that must work without Obsidian running + +## Fallback rule + +If CLI is unavailable or the Obsidian app toggle is off, continue with filesystem-only KB maintenance. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/LINK-REPAIR.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/LINK-REPAIR.md new file mode 100644 index 0000000..293e417 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/LINK-REPAIR.md @@ -0,0 +1,3 @@ +# LINK REPAIR + +Repair links by strengthening existing canonical paths and avoiding duplicate concept notes. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/OBSIDIAN-MARKDOWN.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/OBSIDIAN-MARKDOWN.md new file mode 100644 index 0000000..7338269 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/OBSIDIAN-MARKDOWN.md @@ -0,0 +1,87 @@ +# OBSIDIAN MARKDOWN + +Use valid Obsidian-flavored Markdown for canonical project notes. Prefer readable notes first, then Obsidian-native structure. + +## Core rules + +- Keep a small frontmatter block at the top of canonical notes. +- Use `[[wikilinks]]` for vault-internal references and Markdown links only for external URLs. +- Use readable headings and short sections; avoid turning notes into raw dumps. +- Prefer Markdown tables only when the comparison is truly tabular. +- Keep system files and generated tables deterministic; keep human notes readable. + +## Frontmatter and properties + +Use frontmatter for stable metadata such as: + +```yaml +--- +type: knowledge +status: active +created: 2026-04-24 +updated: 2026-04-24 +tags: + - research + - active +aliases: + - Alternative Note Name +--- +``` + +Prefer simple scalar or list properties. Do not over-model note metadata unless the workflow needs it. + +## Wikilinks + +Common forms: + +```md +[[Note Name]] +[[Folder/Note Name]] +[[Note Name|Display Text]] +[[Note Name#Heading]] +[[Note Name#^block-id]] +``` + +Use folder-qualified links when note names are ambiguous. Prefer links to canonical notes over duplicate notes. + +## Embeds + +Use embeds when the reader benefits from inline context, not just because the syntax exists. + +```md +![[Note Name]] +![[Note Name#Heading]] +![[image.png|300]] +![[document.pdf#page=3]] +``` + +Avoid large embed chains that make notes hard to scan. + +## Callouts + +Use callouts to highlight information that benefits from visual separation: + +```md +> [!note] +> Supporting detail. + +> [!warning] Risk +> This assumption may break under domain shift. +``` + +Common types: `note`, `info`, `tip`, `warning`, `question`, `success`, `failure`, `quote`, `example`. + +## Tables + +Use tables for: +- comparison matrices +- experiment summaries +- compact registries meant for humans + +Avoid tables for long prose or nested content. + +## Tags and aliases + +- Use tags sparingly and consistently. +- Use aliases when a note has a common alternate name or paper title variant. +- Do not rely on tags as the only navigation mechanism when wikilinks and index notes are clearer. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/REGISTRY-TABLES.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/REGISTRY-TABLES.md new file mode 100644 index 0000000..5ceb50b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-kb-artifacts/references/REGISTRY-TABLES.md @@ -0,0 +1,3 @@ +# REGISTRY TABLES + +Registry tables are the only visible project registry and should remain human-readable and machine-parseable. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/SKILL.md new file mode 100644 index 0000000..cdcbf31 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/SKILL.md @@ -0,0 +1,46 @@ +--- +name: obsidian-literature-workflow +description: Use this skill for project-scoped literature review built on Sources/Papers, with synthesis landing in Knowledge, writing handoff in Writing, and the default literature canvas under Maps/literature.canvas. +version: 1.0.0 +--- + +# Obsidian Literature Workflow + +This skill owns the **project literature workflow**. + +## Main flow + +```text +Sources/Papers/ -> Knowledge/ -> Writing/ -> Maps/literature.canvas +``` + +## Default outputs + +- `Sources/Papers/{paper-slug}.md` +- `Knowledge/Literature Overview.md` +- `Knowledge/Method Taxonomy.md` +- `Knowledge/Research Gaps.md` +- `Knowledge/Claim Map.md` +- `Writing/related-work-draft.md` only after promoted claims pass the evidence gate +- `Writing/comparison-matrix.md` only after promoted claims pass the evidence gate +- `Maps/literature.canvas` + +## Rules + +- paper notes stay under `Sources/Papers/` +- literature synthesis does not live inside source notes +- every synthesis note must link its supporting source notes +- every research gap must carry evidence +- every promoted claim must carry an Evidence Record ID, source type, claim strength, allowed wording, and forbidden stronger wording when it may flow into writing or rebuttal +- weak paper notes, abstract-only pages, and webpage placeholders may update coverage or `To-Read`, but they cannot support `Knowledge` or `Writing` conclusions +- default graph output is `Maps/literature.canvas` +- do not generate extra canvases unless explicitly requested + +## Read next + +- `references/PAPER-NOTE-SCHEMA.md` +- `references/LITERATURE-OVERVIEW.md` +- `references/CLAIM-EXTRACTION.md` +- `references/METHOD-TAXONOMY.md` +- `references/RESEARCH-GAPS.md` +- `references/LITERATURE-CANVAS.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/CANVAS-WORKFLOW.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/CANVAS-WORKFLOW.md new file mode 100644 index 0000000..0bbf7d4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/CANVAS-WORKFLOW.md @@ -0,0 +1,42 @@ +# Literature Canvas Workflow + +## Default output + +- `Maps/literature.canvas` + +## Purpose + +Provide a default Obsidian literature graph that: +- keeps `Sources/Papers/` as the canonical paper-note surface, +- keeps `Knowledge/` as the canonical synthesis surface, +- visualizes paper-to-paper and paper-to-knowledge relationships, +- stays lightweight enough to refresh after each major Zotero ingestion. + +## Default behavior + +- Use paper-note frontmatter and wikilinks as the primary graph source. +- Use `Sources/Papers/*.md` and relevant `Knowledge/*.md` as file nodes. +- Create `.canvas` by default for literature ingestion and review workflows. +- Treat Mermaid or markdown graph notes as optional legacy companions, not the default graph artifact. +- Prefer argument-map structure with `paper`, `claim`, `method`, and `gap` nodes over raw all-to-all paper linking. +- Thin edges aggressively; keep only the main reasoning chain and a small number of explicit semantic paper-to-paper relations. +- Hide or down-rank side branches when they clutter the display graph. + +## Refresh triggers + +Refresh the literature canvas when: +- new Zotero-sourced paper notes are added, +- paper notes gain new `linked_knowledge` edges or meaningful wikilinks, +- knowledge synthesis notes are updated after a literature pass, +- a batch Zotero review or note-ingestion pass finishes, +- a full-collection normalization pass changes many paper-note relationships. + +## Recommended command + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-literature-workflow/scripts/build_literature_canvas.py" --cwd "$PWD" +``` + +## Display rule + +- If a second lightweight showcase graph is useful, maintain `Maps/literature-main.canvas` as a filtered presentation copy rather than bloating the default working canvas. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/CLAIM-EXTRACTION.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/CLAIM-EXTRACTION.md new file mode 100644 index 0000000..0a716d2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/CLAIM-EXTRACTION.md @@ -0,0 +1,45 @@ +# CLAIM EXTRACTION + +Claim extraction should produce reusable literature notes, not vague summaries. + +## Extract at least these fields + +For each paper or source note, identify: +- **Claim** — what the paper says it achieves or establishes +- **Claim type** — author claim, community consensus, or project interpretation +- **Claim strength** — speculative, observed, supported, or strong +- **Evidence** — the concrete support for that claim (dataset, metric, experiment, analysis) +- **Method** — the approach or mechanism behind the claim +- **Limitation** — where the claim may not hold +- **Contradicts / weakens** — evidence or conditions that reduce confidence in the claim +- **Project relevance** — why this matters for the current project + +## Writing rules + +- Write claims in plain, reusable language. +- Distinguish the author claim from your project interpretation. +- Do not copy entire abstract sentences when a shorter paraphrase is clearer. +- Pair every durable claim with at least one evidence anchor. +- Do not promote a claim strength without naming the evidence that justifies the stronger level. + +## Minimal output shape + +This `Key Claims` block is a paper-note projection of the shared Evidence Record contract. Preserve the same evidence anchor, limitation, contradiction, project relevance, and claim strength so downstream synthesis can map it back to the canonical evidence record. + +```md +## Key Claims +- Claim: ... + - Claim type: author claim | community consensus | project interpretation + - Claim strength: speculative | observed | supported | strong + - Evidence: ... + - Method: ... + - Limitation: ... + - Contradicts / weakens: ... + - Project relevance: ... +``` + +## Promotion rule + +If a claim is reusable across multiple papers or sources, promote it from a paper note into `Knowledge/` instead of leaving it stranded in `Sources/Papers/`. + +Only promote claims that include both an evidence anchor and a claim strength. If the evidence is weak or indirect, keep the claim as `speculative` or `observed` and preserve the uncertainty. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/GRAPH-WORKFLOW.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/GRAPH-WORKFLOW.md new file mode 100644 index 0000000..8d01f56 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/GRAPH-WORKFLOW.md @@ -0,0 +1,26 @@ +# Legacy Literature Map Workflow + +This reference is kept for backwards compatibility only. + +## Legacy output + +- `Knowledge/Literature-Map.md` + +## Current default + +- Use `CANVAS-WORKFLOW.md` for the current default literature graph artifact. +- The default graph is now `Maps/literature.canvas`, not a Mermaid note. +- Keep this markdown workflow only when a note-based map is specifically requested or needed for compatibility. + +## Refresh triggers + +Refresh the markdown map only when: +- new Zotero-sourced paper notes are added, +- paper-note links or metadata materially change, +- a batch literature review finishes. + +## Recommended command + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/obsidian-literature-workflow/scripts/build_literature_graph.py" --cwd "$PWD" +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/LITERATURE-CANVAS.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/LITERATURE-CANVAS.md new file mode 100644 index 0000000..246c282 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/LITERATURE-CANVAS.md @@ -0,0 +1,3 @@ +# LITERATURE CANVAS + +The default literature canvas lives at Maps/literature.canvas and should stay sparse, argument-oriented, and source-backed. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/LITERATURE-OVERVIEW.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/LITERATURE-OVERVIEW.md new file mode 100644 index 0000000..1d4a8a4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/LITERATURE-OVERVIEW.md @@ -0,0 +1,3 @@ +# LITERATURE OVERVIEW + +Literature overview notes summarize the current field view for the project and must link source paper notes. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/METHOD-TAXONOMY.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/METHOD-TAXONOMY.md new file mode 100644 index 0000000..0d2b935 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/METHOD-TAXONOMY.md @@ -0,0 +1,3 @@ +# METHOD TAXONOMY + +Method taxonomy notes group methods across papers and should link each taxonomy entry back to supporting paper notes. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/PAPER-NOTE-SCHEMA.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/PAPER-NOTE-SCHEMA.md new file mode 100644 index 0000000..e7f6ffc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/PAPER-NOTE-SCHEMA.md @@ -0,0 +1,3 @@ +# PAPER NOTE SCHEMA + +Use a strong paper schema with metadata, project relevance, summary, claims, methods, evidence, limitations, connections, and open questions. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/RESEARCH-GAPS.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/RESEARCH-GAPS.md new file mode 100644 index 0000000..c27ec34 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/references/RESEARCH-GAPS.md @@ -0,0 +1,3 @@ +# RESEARCH GAPS + +Research gap notes must state the gap, why it matters, and which paper notes support it. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/scripts/build_literature_canvas.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/scripts/build_literature_canvas.py new file mode 100644 index 0000000..3efc39e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/scripts/build_literature_canvas.py @@ -0,0 +1,644 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import hashlib +import json +import re +import sys +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +WIKILINK_RE = re.compile(r"\[\[([^\]|#]+)(?:#[^\]|]+)?(?:\|[^\]]+)?\]\]") +LIST_KEYS = { + "authors", + "keywords", + "concepts", + "methods", + "related_papers", + "linked_knowledge", + "paper_relationships", + "linked_papers", + "argument_claims", + "argument_methods", + "argument_gaps", + "linked_claims", + "linked_methods", + "linked_gaps", + "claim_method_links", + "method_gap_links", +} +PAPER_LIMIT = 48 +KNOWLEDGE_LIMIT = 18 +KNOWLEDGE_COLUMNS = 3 +NODE_WIDTH = 300 +NODE_HEIGHT = 180 +ARG_NODE_WIDTH = 280 +ARG_NODE_HEIGHT = 120 +X_GAP = 80 +Y_GAP = 70 +GROUP_X_GAP = 180 +GROUP_Y_GAP = 180 +ARG_GROUP_X_GAP = 200 +PAPER_RELATION_LIMIT = 2 +PAPER_CLAIM_LIMIT = 1 +PAPER_METHOD_LIMIT = 1 +PAPER_RELATION_LIMIT = 1 +SUBFIELD_ORDER = ( + "speech-transfer-constraints", + "alignment-and-domain-adaptation", + "geometry-and-representation", + "subject-aware-adaptation", + "other", +) +SUBFIELD_LABELS = { + "speech-transfer-constraints": "Speech-specific transfer constraints", + "alignment-and-domain-adaptation": "Alignment and domain adaptation", + "geometry-and-representation": "Geometry and representation", + "subject-aware-adaptation": "Subject-aware adaptation", + "other": "Other papers", +} +SUBFIELD_COLORS = { + "speech-transfer-constraints": "6", + "alignment-and-domain-adaptation": "2", + "geometry-and-representation": "5", + "subject-aware-adaptation": "3", + "other": "1", +} +SUBFIELD_COLUMNS = 2 + + +@dataclass(frozen=True) +class NoteRecord: + title: str + note_relpath: str + vault_relpath: str + file_name: str + related_papers: tuple[str, ...] + linked_knowledge: tuple[str, ...] + paper_relationships: tuple[tuple[str, str], ...] + linked_papers: tuple[str, ...] + claim_refs: tuple[str, ...] + method_refs: tuple[str, ...] + gap_refs: tuple[str, ...] + claim_method_links: tuple[tuple[str, str, str], ...] + method_gap_links: tuple[tuple[str, str, str], ...] + wikilinks: tuple[str, ...] + subfield: str + canvas_visibility: str + + +def load_project_kb_module() -> Any: + script_dir = Path(__file__).resolve().parents[2] / "obsidian-project-kb-core" / "scripts" + sys.path.insert(0, str(script_dir)) + import kb_common # type: ignore + + return kb_common + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser( + description="Build a default literature canvas for the bound Obsidian project." + ) + parser.add_argument("--cwd", default=".") + parser.add_argument("--project-id", default="") + parser.add_argument("--output", default="Maps/literature.canvas") + return parser.parse_args() + + +def parse_frontmatter(text: str) -> dict[str, Any]: + if not text.startswith("---\n"): + return {} + end = text.find("\n---\n", 4) + if end == -1: + return {} + lines = text[4:end].splitlines() + data: dict[str, Any] = {} + current_key: str | None = None + for raw_line in lines: + if not raw_line.strip(): + continue + if raw_line.startswith(" - ") or raw_line.startswith("- "): + if current_key and current_key in LIST_KEYS: + data.setdefault(current_key, []).append( + raw_line.split("- ", 1)[1].strip().strip('"') + ) + continue + if ":" not in raw_line: + current_key = None + continue + key, value = raw_line.split(":", 1) + key = key.strip() + value = value.strip() + current_key = key + if not value: + if key in LIST_KEYS: + data[key] = [] + else: + data[key] = "" + continue + data[key] = value.strip('"') + return data + + +def body_without_frontmatter(text: str) -> str: + if not text.startswith("---\n"): + return text + end = text.find("\n---\n", 4) + if end == -1: + return text + return text[end + 5 :] + + +def normalize_note_target(value: str) -> str: + cleaned = value.strip() + if cleaned.endswith(".md"): + cleaned = cleaned[:-3] + if cleaned.startswith("./"): + cleaned = cleaned[2:] + return cleaned + + +def parse_relationship_entries(values: list[str]) -> tuple[tuple[str, str], ...]: + parsed: list[tuple[str, str]] = [] + for raw in values: + cleaned = raw.strip() + if not cleaned: + continue + if "::" in cleaned: + target, label = cleaned.split("::", 1) + else: + target, label = cleaned, "related" + parsed.append((normalize_note_target(target), label.strip() or "related")) + return tuple(parsed) + + +def parse_triple_entries(values: list[str]) -> tuple[tuple[str, str, str], ...]: + parsed: list[tuple[str, str, str]] = [] + for raw in values: + cleaned = raw.strip() + if not cleaned: + continue + parts = [part.strip() for part in cleaned.split("::")] + if len(parts) == 2: + parsed.append((parts[0], parts[1], "relates")) + elif len(parts) >= 3: + parsed.append((parts[0], parts[1], parts[2] or "relates")) + return tuple(parsed) + + +def parse_plain_labels(values: list[str]) -> tuple[str, ...]: + labels = [] + for raw in values: + cleaned = raw.strip() + if cleaned and cleaned not in labels: + labels.append(cleaned) + return tuple(labels) + + +def extract_wikilinks(text: str) -> tuple[str, ...]: + seen: list[str] = [] + for match in WIKILINK_RE.findall(text): + target = normalize_note_target(match) + if target not in seen: + seen.append(target) + return tuple(seen) + + +def note_id(prefix: str, value: str) -> str: + digest = hashlib.sha1(f"{prefix}:{value}".encode("utf-8")).hexdigest() + return digest[:16] + + +def file_node(note: NoteRecord, x: int, y: int, color: str) -> dict[str, Any]: + return { + "id": note_id("node", note.note_relpath), + "type": "file", + "x": x, + "y": y, + "width": NODE_WIDTH, + "height": NODE_HEIGHT, + "file": note.vault_relpath, + "color": color, + } + + +def text_node(node_key: str, text: str, x: int, y: int, width: int, height: int) -> dict[str, Any]: + return { + "id": note_id("text", node_key), + "type": "text", + "x": x, + "y": y, + "width": width, + "height": height, + "text": text, + "color": "5", + } + + +def group_node(node_key: str, label: str, x: int, y: int, width: int, height: int, color: str) -> dict[str, Any]: + return { + "id": note_id("group", node_key), + "type": "group", + "x": x, + "y": y, + "width": width, + "height": height, + "label": label, + "color": color, + } + + +def edge_id(source: str, target: str, label: str) -> str: + digest = hashlib.sha1(f"{source}:{target}:{label}".encode("utf-8")).hexdigest() + return digest[:16] + + +def make_edge(from_node: str, to_node: str, label: str) -> dict[str, Any]: + return { + "id": edge_id(from_node, to_node, label), + "fromNode": from_node, + "fromSide": "bottom", + "toNode": to_node, + "toSide": "top", + "toEnd": "arrow", + "label": label, + } + + +def collect_notes(folder: Path, folder_name: str, vault_root: Path, limit: int) -> list[NoteRecord]: + notes: list[NoteRecord] = [] + if not folder.exists(): + return notes + for path in sorted(folder.glob("*.md"))[:limit]: + text = path.read_text(encoding="utf-8") + frontmatter = parse_frontmatter(text) + body = body_without_frontmatter(text) + title = str(frontmatter.get("title") or path.stem.replace("-", " ")) + notes.append( + NoteRecord( + title=title, + note_relpath=f"{folder_name}/{path.name}", + vault_relpath=str(path.relative_to(vault_root)).replace("\\", "/"), + file_name=path.name, + related_papers=tuple( + normalize_note_target(v) for v in frontmatter.get("related_papers", []) + ), + linked_knowledge=tuple( + normalize_note_target(v) for v in frontmatter.get("linked_knowledge", []) + ), + paper_relationships=parse_relationship_entries( + list(frontmatter.get("paper_relationships", [])) + ), + linked_papers=tuple( + normalize_note_target(v) for v in frontmatter.get("linked_papers", []) + ), + claim_refs=parse_plain_labels( + list(frontmatter.get("argument_claims", [])) + + list(frontmatter.get("linked_claims", [])) + ), + method_refs=parse_plain_labels( + list(frontmatter.get("argument_methods", [])) + + list(frontmatter.get("linked_methods", [])) + ), + gap_refs=parse_plain_labels( + list(frontmatter.get("argument_gaps", [])) + + list(frontmatter.get("linked_gaps", [])) + ), + claim_method_links=parse_triple_entries( + list(frontmatter.get("claim_method_links", [])) + ), + method_gap_links=parse_triple_entries( + list(frontmatter.get("method_gap_links", [])) + ), + wikilinks=extract_wikilinks(body), + subfield=str(frontmatter.get("subfield") or "other"), + canvas_visibility=str(frontmatter.get("canvas_visibility") or "show"), + ) + ) + return notes + + +def looks_like_literature_knowledge(note: NoteRecord) -> bool: + key = note.note_relpath.lower() + if any(token in key for token in ("literature", "paper", "method", "survey", "gap", "related")): + return True + return any(target.startswith("Sources/Papers/") for target in note.wikilinks) + + +def select_knowledge_notes( + all_knowledge: list[NoteRecord], papers: list[NoteRecord] +) -> list[NoteRecord]: + requested = set() + for note in papers: + requested.update(note.linked_knowledge) + requested.update(target for target in note.wikilinks if target.startswith("Knowledge/")) + + selected: list[NoteRecord] = [] + seen: set[str] = set() + for note in all_knowledge: + note_key = note.note_relpath[:-3] + if note_key in requested: + selected.append(note) + seen.add(note_key) + + if selected: + return selected[:KNOWLEDGE_LIMIT] + + for note in all_knowledge: + note_key = note.note_relpath[:-3] + if note_key in seen: + continue + if looks_like_literature_knowledge(note): + selected.append(note) + seen.add(note_key) + if len(selected) >= KNOWLEDGE_LIMIT: + break + + return selected[:KNOWLEDGE_LIMIT] + + +def layout_grid(index: int, columns: int, x0: int, y0: int) -> tuple[int, int]: + col = index % columns + row = index // columns + x = x0 + col * (NODE_WIDTH + X_GAP) + y = y0 + row * (NODE_HEIGHT + Y_GAP) + return x, y + + +def compute_group_dimensions(item_count: int, columns: int) -> tuple[int, int]: + rows = max(1, (max(item_count, 1) - 1) // columns + 1) + width = columns * NODE_WIDTH + (columns - 1) * X_GAP + 120 + height = rows * NODE_HEIGHT + (rows - 1) * Y_GAP + 140 + return width, height + + +def compute_argument_group_dimensions(item_count: int, columns: int) -> tuple[int, int]: + rows = max(1, (max(item_count, 1) - 1) // columns + 1) + width = columns * ARG_NODE_WIDTH + (columns - 1) * X_GAP + 120 + height = rows * ARG_NODE_HEIGHT + (rows - 1) * Y_GAP + 140 + return width, height + + +def argument_node(kind: str, label: str, x: int, y: int) -> dict[str, Any]: + return { + "id": note_id(kind, label), + "type": "text", + "x": x, + "y": y, + "width": ARG_NODE_WIDTH, + "height": ARG_NODE_HEIGHT, + "text": label, + "color": {"claim": "4", "method": "2", "gap": "6"}.get(kind, "5"), + } + + +def render_canvas(project_title: str, papers: list[NoteRecord], knowledge: list[NoteRecord]) -> dict[str, Any]: + nodes: list[dict[str, Any]] = [] + edges: list[dict[str, Any]] = [] + node_lookup: dict[str, str] = {} + claim_lookup: dict[str, str] = {} + method_lookup: dict[str, str] = {} + gap_lookup: dict[str, str] = {} + + knowledge_rows = max(1, (max(len(knowledge), 1) - 1) // KNOWLEDGE_COLUMNS + 1) + knowledge_group_width = KNOWLEDGE_COLUMNS * NODE_WIDTH + (KNOWLEDGE_COLUMNS - 1) * X_GAP + 120 + knowledge_group_height = knowledge_rows * NODE_HEIGHT + (knowledge_rows - 1) * Y_GAP + 140 + knowledge_y = 220 + argument_y = knowledge_y + knowledge_group_height + 180 + + nodes.append( + text_node( + "literature-summary", + ( + f"# Literature Canvas\\n\\n" + f"Project: {project_title}\\n\\n" + f"- This is an argument map with `paper + claim + method + gap`.\\n" + f"- The graph is intentionally thinned: each paper only keeps its most important claim / method links.\\n" + f"- Papers are grouped by subfield and spaced out to reduce crossing lines." + ), + 0, + 0, + 1080, + 150, + ) + ) + nodes.append(group_node("knowledge-group", "Knowledge", -40, knowledge_y - 40, knowledge_group_width, knowledge_group_height, "4")) + + for idx, note in enumerate(knowledge): + x, y = layout_grid(idx, KNOWLEDGE_COLUMNS, 20, knowledge_y) + node = file_node(note, x, y, "4") + nodes.append(node) + node_lookup[note.note_relpath[:-3]] = node["id"] + + claim_labels: list[str] = [] + method_labels: list[str] = [] + gap_labels: list[str] = [] + for note in (*papers, *knowledge): + for label in note.claim_refs: + if label not in claim_labels: + claim_labels.append(label) + for label in note.method_refs: + if label not in method_labels: + method_labels.append(label) + for label in note.gap_refs: + if label not in gap_labels: + gap_labels.append(label) + + claim_group_width, claim_group_height = compute_argument_group_dimensions(len(claim_labels), 2) + method_group_width, method_group_height = compute_argument_group_dimensions(len(method_labels), 2) + gap_group_width, gap_group_height = compute_argument_group_dimensions(len(gap_labels), 2) + argument_row_height = max(claim_group_height, method_group_height, gap_group_height) + + argument_groups = [ + ("claim", "Claims", claim_labels, -40, argument_y, claim_group_width, claim_group_height, "4"), + ("method", "Methods", method_labels, -40 + claim_group_width + ARG_GROUP_X_GAP, argument_y, method_group_width, method_group_height, "2"), + ("gap", "Gaps", gap_labels, -40 + claim_group_width + ARG_GROUP_X_GAP + method_group_width + ARG_GROUP_X_GAP, argument_y, gap_group_width, gap_group_height, "6"), + ] + for kind, label, labels, group_x, group_y, group_width, group_height, color in argument_groups: + nodes.append(group_node(f"{kind}-group", label, group_x, group_y, group_width, group_height, color)) + for idx, arg_label in enumerate(labels): + x, y = layout_grid(idx, 2, group_x + 60, group_y + 40) + node = argument_node(kind, arg_label, x, y) + nodes.append(node) + if kind == "claim": + claim_lookup[arg_label] = node["id"] + elif kind == "method": + method_lookup[arg_label] = node["id"] + else: + gap_lookup[arg_label] = node["id"] + + paper_y = argument_y + argument_row_height + 180 + + grouped_papers: dict[str, list[NoteRecord]] = {} + for note in papers: + grouped_papers.setdefault(note.subfield or "other", []).append(note) + + active_groups = [key for key in SUBFIELD_ORDER if grouped_papers.get(key)] + if not active_groups: + active_groups = ["other"] + grouped_papers["other"] = list(papers) + + group_layout_meta: list[tuple[str, int, int, int, int]] = [] + for idx, subfield in enumerate(active_groups): + notes_in_group = grouped_papers[subfield] + group_width, group_height = compute_group_dimensions(len(notes_in_group), 2) + col = idx % SUBFIELD_COLUMNS + row = idx // SUBFIELD_COLUMNS + group_x = -40 + col * (group_width + GROUP_X_GAP) + group_y = paper_y + row * (group_height + GROUP_Y_GAP) + group_layout_meta.append((subfield, group_x, group_y, group_width, group_height)) + nodes.append( + group_node( + f"paper-group-{subfield}", + SUBFIELD_LABELS.get(subfield, subfield.replace("-", " ").title()), + group_x, + group_y, + group_width, + group_height, + SUBFIELD_COLORS.get(subfield, "2"), + ) + ) + + for note_idx, note in enumerate(notes_in_group): + x, y = layout_grid(note_idx, 2, group_x + 60, group_y + 40) + node = file_node(note, x, y, SUBFIELD_COLORS.get(subfield, "2")) + nodes.append(node) + node_lookup[note.note_relpath[:-3]] = node["id"] + + seen_edges: set[tuple[str, str, str]] = set() + for note in papers: + source = node_lookup.get(note.note_relpath[:-3]) + if not source: + continue + explicit_relationships = list(note.paper_relationships) + if not explicit_relationships: + explicit_relationships = [(target, "related") for target in note.related_papers] + for target, label in explicit_relationships[:PAPER_RELATION_LIMIT]: + target_node = node_lookup.get(target) + if not target_node: + continue + marker = (source, target_node, label) + if marker not in seen_edges: + edges.append(make_edge(source, target_node, label)) + seen_edges.add(marker) + for claim in note.claim_refs[:PAPER_CLAIM_LIMIT]: + target_node = claim_lookup.get(claim) + if not target_node: + continue + marker = (source, target_node, "supports") + if marker not in seen_edges: + edges.append(make_edge(source, target_node, "supports")) + seen_edges.add(marker) + for method in note.method_refs[:PAPER_METHOD_LIMIT]: + target_node = method_lookup.get(method) + if not target_node: + continue + marker = (source, target_node, "uses") + if marker not in seen_edges: + edges.append(make_edge(source, target_node, "uses")) + seen_edges.add(marker) + for note in knowledge: + source = node_lookup.get(note.note_relpath[:-3]) + if not source: + continue + for target in note.linked_papers: + target_node = node_lookup.get(target) + if not target_node: + continue + marker = (source, target_node, "summarizes") + if marker not in seen_edges: + edges.append(make_edge(source, target_node, "summarizes")) + seen_edges.add(marker) + for claim in note.claim_refs: + target_node = claim_lookup.get(claim) + if not target_node: + continue + marker = (source, target_node, "summarizes") + if marker not in seen_edges: + edges.append(make_edge(source, target_node, "summarizes")) + seen_edges.add(marker) + for method in note.method_refs: + target_node = method_lookup.get(method) + if not target_node: + continue + marker = (source, target_node, "summarizes") + if marker not in seen_edges: + edges.append(make_edge(source, target_node, "summarizes")) + seen_edges.add(marker) + for gap in note.gap_refs: + target_node = gap_lookup.get(gap) + if not target_node: + continue + marker = (source, target_node, "summarizes") + if marker not in seen_edges: + edges.append(make_edge(source, target_node, "summarizes")) + seen_edges.add(marker) + for claim, method, label in note.claim_method_links: + source_node = claim_lookup.get(claim) + target_node = method_lookup.get(method) + if not source_node or not target_node: + continue + marker = (source_node, target_node, label) + if marker not in seen_edges: + edges.append(make_edge(source_node, target_node, label)) + seen_edges.add(marker) + for method, gap, label in note.method_gap_links: + source_node = method_lookup.get(method) + target_node = gap_lookup.get(gap) + if not source_node or not target_node: + continue + marker = (source_node, target_node, label) + if marker not in seen_edges: + edges.append(make_edge(source_node, target_node, label)) + seen_edges.add(marker) + for target in note.wikilinks: + if not target.startswith("Knowledge/"): + continue + target_node = node_lookup.get(target) + if not target_node: + continue + marker = (source, target_node, "relates") + if marker not in seen_edges: + edges.append(make_edge(source, target_node, "relates")) + seen_edges.add(marker) + + return {"nodes": nodes, "edges": edges} + + +def main() -> None: + args = parse_args() + project_kb = load_project_kb_module() + repo_root = project_kb.find_repo_root(Path(args.cwd).resolve()) + binding = project_kb.resolve_binding(repo_root, args.project_id or None) + + papers = [ + note + for note in collect_notes(binding.project_root / "Sources" / "Papers", "Papers", binding.vault_path, PAPER_LIMIT) + if note.canvas_visibility != "hidden" + ] + all_knowledge = collect_notes( + binding.project_root / "Knowledge", "Knowledge", binding.vault_path, KNOWLEDGE_LIMIT * 3 + ) + knowledge = select_knowledge_notes(all_knowledge, papers) + canvas = render_canvas(project_kb.titleize_slug(binding.project_id), papers, knowledge) + + output_path = binding.project_root / args.output + output_path.parent.mkdir(parents=True, exist_ok=True) + output_path.write_text(json.dumps(canvas, ensure_ascii=False, indent=2) + "\n", encoding="utf-8") + print( + json.dumps( + { + "project_id": binding.project_id, + "output": str(output_path), + "paper_count": len(papers), + "knowledge_count": len(knowledge), + }, + ensure_ascii=False, + ) + ) + + +if __name__ == "__main__": + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/scripts/build_literature_graph.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/scripts/build_literature_graph.py new file mode 100755 index 0000000..2245095 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-literature-workflow/scripts/build_literature_graph.py @@ -0,0 +1,271 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import re +import sys +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +PAPER_LIMIT = 48 +EDGE_LIMIT = 160 +WIKILINK_RE = re.compile(r"\[\[([^\]|#]+)(?:#[^\]|]+)?(?:\|[^\]]+)?\]\]") +LIST_KEYS = { + 'authors', 'keywords', 'concepts', 'methods', + 'related_papers', 'linked_experiments', 'linked_results' +} + + +@dataclass(frozen=True) +class PaperNote: + title: str + note_relpath: str + file_name: str + concepts: tuple[str, ...] + methods: tuple[str, ...] + related_papers: tuple[str, ...] + linked_experiments: tuple[str, ...] + linked_results: tuple[str, ...] + wikilinks: tuple[str, ...] + + +def load_project_kb_module() -> Any: + script_dir = Path(__file__).resolve().parents[2] / 'obsidian-project-kb-core' / 'scripts' + sys.path.insert(0, str(script_dir)) + import kb_common # type: ignore + return kb_common + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Build a literature graph note for the bound Obsidian project.') + parser.add_argument('--cwd', default='.') + parser.add_argument('--project-id', default='') + parser.add_argument('--output', default='Knowledge/Literature-Map.md') + return parser.parse_args() + + +def parse_frontmatter(text: str) -> dict[str, Any]: + if not text.startswith('---\n'): + return {} + end = text.find('\n---\n', 4) + if end == -1: + return {} + lines = text[4:end].splitlines() + data: dict[str, Any] = {} + current_key: str | None = None + for raw_line in lines: + if not raw_line.strip(): + continue + if raw_line.startswith(' - ') or raw_line.startswith('- '): + if current_key and current_key in LIST_KEYS: + data.setdefault(current_key, []).append(raw_line.split('- ', 1)[1].strip().strip('"')) + continue + if ':' not in raw_line: + current_key = None + continue + key, value = raw_line.split(':', 1) + key = key.strip() + value = value.strip() + current_key = key + if not value: + if key in LIST_KEYS: + data[key] = [] + else: + data[key] = '' + continue + data[key] = value.strip('"') + return data + + +def body_without_frontmatter(text: str) -> str: + if not text.startswith('---\n'): + return text + end = text.find('\n---\n', 4) + if end == -1: + return text + return text[end + 5:] + + +def normalize_note_target(value: str) -> str: + cleaned = value.strip() + if cleaned.endswith('.md'): + cleaned = cleaned[:-3] + if cleaned.startswith('./'): + cleaned = cleaned[2:] + return cleaned + + +def mermaid_id(prefix: str, value: str) -> str: + slug = re.sub(r'[^a-zA-Z0-9]+', '_', value).strip('_').lower() + if not slug: + slug = 'node' + return f'{prefix}_{slug[:48]}' + + +def extract_wikilinks(text: str) -> tuple[str, ...]: + seen: list[str] = [] + for match in WIKILINK_RE.findall(text): + target = normalize_note_target(match) + if target not in seen: + seen.append(target) + return tuple(seen) + + +def collect_paper_notes(project_root: Path) -> list[PaperNote]: + papers_dir = project_root / 'Sources' / 'Papers' + notes: list[PaperNote] = [] + if not papers_dir.exists(): + return notes + for path in sorted(papers_dir.glob('*.md'))[:PAPER_LIMIT]: + text = path.read_text(encoding='utf-8') + frontmatter = parse_frontmatter(text) + body = body_without_frontmatter(text) + title = str(frontmatter.get('title') or path.stem.replace('-', ' ')) + notes.append( + PaperNote( + title=title, + note_relpath=f'Sources/Papers/{path.name}', + file_name=path.name, + concepts=tuple(frontmatter.get('concepts', [])), + methods=tuple(frontmatter.get('methods', [])), + related_papers=tuple(normalize_note_target(v) for v in frontmatter.get('related_papers', [])), + linked_experiments=tuple(normalize_note_target(v) for v in frontmatter.get('linked_experiments', [])), + linked_results=tuple(normalize_note_target(v) for v in frontmatter.get('linked_results', [])), + wikilinks=extract_wikilinks(body), + ) + ) + return notes + + +def render_mermaid(notes: list[PaperNote]) -> str: + lines: list[str] = ['graph LR'] + paper_index = {note.note_relpath[:-3]: note for note in notes} + seen_edges: set[tuple[str, str, str]] = set() + + for note in notes: + paper_node = mermaid_id('paper', note.file_name) + lines.append(f' {paper_node}["{note.title}"]') + + for concept in note.concepts: + concept_node = mermaid_id('concept', concept) + lines.append(f' {concept_node}(("{concept}"))') + edge = (paper_node, concept_node, 'concept') + if edge not in seen_edges and len(seen_edges) < EDGE_LIMIT: + lines.append(f' {paper_node} -->|concept| {concept_node}') + seen_edges.add(edge) + + for method in note.methods: + method_node = mermaid_id('method', method) + lines.append(f' {method_node}{{"{method}"}}') + edge = (paper_node, method_node, 'method') + if edge not in seen_edges and len(seen_edges) < EDGE_LIMIT: + lines.append(f' {paper_node} -->|method| {method_node}') + seen_edges.add(edge) + + related_targets = set(note.related_papers) + related_targets.update(target for target in note.wikilinks if target.startswith('Sources/Papers/')) + for target in sorted(related_targets): + target_note = paper_index.get(target) + if not target_note: + continue + target_node = mermaid_id('paper', target_note.file_name) + edge = (paper_node, target_node, 'related') + if edge not in seen_edges and len(seen_edges) < EDGE_LIMIT: + lines.append(f' {paper_node} -->|related| {target_node}') + seen_edges.add(edge) + + for experiment in note.linked_experiments: + exp_node = mermaid_id('experiment', experiment) + label = experiment.split('/')[-1] + lines.append(f' {exp_node}["{label}"]') + edge = (paper_node, exp_node, 'experiment') + if edge not in seen_edges and len(seen_edges) < EDGE_LIMIT: + lines.append(f' {paper_node} -->|experiment| {exp_node}') + seen_edges.add(edge) + + for result in note.linked_results: + result_node = mermaid_id('result', result) + label = result.split('/')[-1] + lines.append(f' {result_node}["{label}"]') + edge = (paper_node, result_node, 'result') + if edge not in seen_edges and len(seen_edges) < EDGE_LIMIT: + lines.append(f' {paper_node} -->|result| {result_node}') + seen_edges.add(edge) + + deduped: list[str] = [] + seen_lines: set[str] = set() + for line in lines: + if line not in seen_lines: + deduped.append(line) + seen_lines.add(line) + return '\n'.join(deduped) + + +def render_map_note(project_id: str, notes: list[PaperNote], mermaid_graph: str, updated: str) -> str: + paper_bullets = '\n'.join(f'- [[{note.note_relpath[:-3]}]]' for note in notes) or '- No paper notes yet.' + concept_counts: dict[str, int] = {} + method_counts: dict[str, int] = {} + for note in notes: + for concept in note.concepts: + concept_counts[concept] = concept_counts.get(concept, 0) + 1 + for method in note.methods: + method_counts[method] = method_counts.get(method, 0) + 1 + concept_lines = '\n'.join( + f'- {name} ({count})' for name, count in sorted(concept_counts.items(), key=lambda kv: (-kv[1], kv[0]))[:12] + ) or '- No concept clusters recorded yet.' + method_lines = '\n'.join( + f'- {name} ({count})' for name, count in sorted(method_counts.items(), key=lambda kv: (-kv[1], kv[0]))[:12] + ) or '- No method clusters recorded yet.' + + return f'''--- +type: knowledge +title: Literature Map +project: {project_id} +updated: {updated} +--- + +# Literature Map + +## Purpose +- Provide a lightweight literature knowledge map for the current project. +- Help navigate paper notes, concept clusters, and downstream experiment/result hooks. + +## Paper notes included +{paper_bullets} + +## Concept clusters +{concept_lines} + +## Method clusters +{method_lines} + +## Graph +```mermaid +{mermaid_graph} +``` + +## How to use +- Open the linked paper notes above for detailed reading notes. +- Use Obsidian backlinks/local graph on top of these wikilinks. +- Refresh this note after a batch Zotero ingestion or major paper-note update. +''' + + +def main() -> None: + args = parse_args() + project_kb = load_project_kb_module() + repo_root = project_kb.find_repo_root(Path(args.cwd).resolve()) + binding = project_kb.resolve_binding(repo_root, args.project_id or None) + notes = collect_paper_notes(binding.project_root) + output_rel = args.output if args.output.endswith('.md') else f'{args.output}.md' + output_path = binding.project_root / output_rel + mermaid_graph = render_mermaid(notes) + content = render_map_note(binding.project_id, notes, mermaid_graph, project_kb.now_iso()) + output_path.parent.mkdir(parents=True, exist_ok=True) + output_path.write_text(content.rstrip() + '\n', encoding='utf-8') + print(output_path) + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/SKILL.md new file mode 100644 index 0000000..0e5fb22 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/SKILL.md @@ -0,0 +1,78 @@ +--- +name: obsidian-project-kb-core +description: Use this as the main Claude Scholar skill for a vault-first, project-scoped Obsidian research knowledge base rooted at Research/{project-slug}/. It owns bootstrap, routing, daily logging, hub/plan/index maintenance, registry updates, lifecycle actions, and lint orchestration. +--- + +# Obsidian Project KB Core + +This is the **main workflow authority** for project-scoped Obsidian knowledge maintenance. + +Default project root: + +```text +Research/{project-slug}/ +``` + +Default structure: + +```text +00-Hub.md +01-Plan.md +02-Index.md +Sources/ +Knowledge/ +Experiments/ +Results/ + Reports/ +Writing/ +Daily/ +Maps/ +Archive/ +_system/ +``` + +## Core rules + +- Keep all durable project knowledge inside the current `Research/{project-slug}/`. +- Keep repo-local `.claude/project-memory/*` only as the runtime binding layer. +- `_system/registry.md` is the only visible project registry. +- `02-Index.md` is a human navigation note, not a registry mirror. +- `Maps/` is a derived-artifact area; do not generate non-essential canvases by default. +- `Results/Reports/` is the default subdirectory for round and batch experiment reports. + +## Responsibilities + +- detect and bind the current repo to a project root +- bootstrap the project skeleton +- route notes into `Sources / Knowledge / Experiments / Results / Results/Reports / Writing / Daily / Maps / Archive` +- update `00-Hub.md`, `01-Plan.md`, `02-Index.md` +- update `_system/registry.md`, `_system/schema.md`, `_system/lint-report.md` +- handle note lifecycle actions: create, update, rename, archive, purge, promote, and link repair +- run deterministic health checks through helper scripts + +## Deterministic helpers + +Use the scripts under `scripts/` for: +- scaffold +- registry consistency +- link checks +- index checks +- canvas checks +- lint aggregation + +Use agents for: +- note routing +- daily promotion decisions +- source vs knowledge judgment +- stable-result judgment +- semantic Hub and Index updates + +## Read next + +- `references/DIRECTORY-SCHEMA.md` +- `references/HUB-PLAN-INDEX.md` +- `references/REGISTRY.md` +- `references/DAILY-PROMOTION.md` +- `references/LIFECYCLE.md` +- `references/LINT.md` +- `references/BINDING-LAYER.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/BINDING-LAYER.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/BINDING-LAYER.md new file mode 100644 index 0000000..5dec6ac --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/BINDING-LAYER.md @@ -0,0 +1,28 @@ +# Binding Layer + +Repo-local binding metadata remains under: + +```text +.claude/project-memory/registry.yaml +.claude/project-memory/<project_id>.md +``` + +This is the runtime binding layer only. + +It may record: +- `project_id` +- `project_slug` +- `repo_roots` +- `vault_root` +- `hub_note` +- `note_language` +- `status` +- `auto_sync` +- recent sync summary + +It must not be treated as the project knowledge layer. +The project knowledge layer lives inside: + +```text +Research/{project-slug}/ +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/DAILY-PROMOTION.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/DAILY-PROMOTION.md new file mode 100644 index 0000000..d2ebc7a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/DAILY-PROMOTION.md @@ -0,0 +1,18 @@ +# Daily Promotion Rules + +`Daily/` keeps process notes, raw meeting notes, scratch ideas, and temporary observations. + +Promote content out of `Daily/` when it becomes: +- a reusable source note +- a durable knowledge note +- an experiment definition +- a stable result +- a writing artifact + +Promotion defaults: +- source-centered material -> `Sources/*` +- cross-source synthesis -> `Knowledge/` +- planned or running work -> `Experiments/` +- stable interpreted finding -> `Results/` +- round or batch retrospective -> `Results/Reports/` +- prose deliverable -> `Writing/` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/DIRECTORY-SCHEMA.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/DIRECTORY-SCHEMA.md new file mode 100644 index 0000000..eacf894 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/DIRECTORY-SCHEMA.md @@ -0,0 +1,46 @@ +# Directory Schema + +The only default project root is: + +```text +Research/{project-slug}/ +``` + +Required files and folders: + +```text +00-Hub.md +01-Plan.md +02-Index.md +Sources/ + Papers/ + Web/ + Docs/ + Data/ + Interviews/ + Notes/ +Knowledge/ +Experiments/ +Results/ + Reports/ +Writing/ +Daily/ +Maps/ +Archive/ +_system/ + registry.md + schema.md + lint-report.md +``` + +Defaults: +- `Sources/Papers/` is the only default paper-note directory. +- `Results/Reports/` is the default subdirectory for round or batch experiment reports. +- `Maps/` contains derived artifacts only. +- `Daily/` is preserved by default. + +Do not create by default: +- top-level `Papers/` +- `project/KB/` +- project-local JSON or YAML note registries +- `.base` files unless explicitly requested diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/HUB-PLAN-INDEX.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/HUB-PLAN-INDEX.md new file mode 100644 index 0000000..c4630bd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/HUB-PLAN-INDEX.md @@ -0,0 +1,51 @@ +# Hub, Plan, and Index + +## `00-Hub.md` + +Use as the project landing page. + +Must contain: +- project summary +- current focus +- current questions +- next actions +- important links +- recent important changes + +## `01-Plan.md` + +Use for durable plans and active tasks. + +Must contain: +- current priorities +- active tasks +- experiment queue +- writing queue when relevant +- current research state when the project has an active research question + +Recommended research state block: + +```md +## Current Research State + +Current question: +Current hypothesis: +Strongest evidence: +Weakest evidence: +Open blockers: +Next experiment: +Do not repeat: +Last decision: +``` + +Keep this state in `01-Plan.md`. Do not create a separate `.scholar/state.md` for the default Obsidian workflow. + +## `02-Index.md` + +Use as the human-friendly MOC. + +Rules: +- do not mirror the full registry +- list only important and currently active notes +- group links by `Sources`, `Knowledge`, `Experiments`, `Results`, `Writing`, and `Maps` +- keep the note readable as a project directory page diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/LIFECYCLE.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/LIFECYCLE.md new file mode 100644 index 0000000..631662f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/LIFECYCLE.md @@ -0,0 +1,19 @@ +# Lifecycle Rules + +## Project lifecycle + +- `detach`: remove or disable repo binding, keep vault project content in place +- `archive`: move the entire project to `Research/_archived/{project-slug}-{date}/` and disable sync +- `purge`: permanently delete binding metadata and the vault project root + +## Note lifecycle + +- `archive`: move a canonical note into `Research/{project-slug}/Archive/`, repair links, update registry and index +- `rename`: rename or move a canonical note in place, repair links, update registry and index, and do not create archive history +- `purge`: permanently delete a canonical note, repair links, and record the removal in archive history when appropriate + +## Defaults + +- “remove project knowledge” means `archive`, not `purge` +- note archive history remains visible in `_system/registry.md` +- archived notes may still be referenced for historical context, but they are not active canonical notes diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/LINT.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/LINT.md new file mode 100644 index 0000000..3c423de --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/LINT.md @@ -0,0 +1,15 @@ +# Lint Rules + +The lint system should check at least: +- missing registry entries +- registry paths that do not exist +- missing index entries +- broken wikilinks +- orphan canonical notes +- duplicate source notes +- experiments without results +- results without experiments +- knowledge notes without sources +- Daily notes with promotable content +- archived notes still referenced by active notes +- canvas nodes that point to missing notes diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/REGISTRY.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/REGISTRY.md new file mode 100644 index 0000000..402a216 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/references/REGISTRY.md @@ -0,0 +1,36 @@ +# Registry Rules + +`_system/registry.md` is the only visible project registry. + +## Sections + +- Sources +- Knowledge +- Experiments +- Results +- Writing +- Maps +- Archive + +## Rules + +- Every canonical note must have a registry entry. +- `Daily/` notes are not registered by default. +- Registry entries use stable IDs that do not depend on note titles. +- Archive keeps history; archiving does not delete registry history. +- Paths are rendered as wikilinks. +- The registry is machine-parsed from Markdown tables; do not create a second formal JSON registry. + +## ID defaults + +- source paper: `paper-001` +- source web: `web-001` +- source doc: `doc-001` +- source data: `data-001` +- source interview: `interview-001` +- source note: `note-001` +- knowledge: `knowledge-001` +- experiment: `exp-001` +- result or report: `result-001` +- writing: `writing-001` +- map: `map-001` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_canvas_check.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_canvas_check.py new file mode 100755 index 0000000..dde5189 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_canvas_check.py @@ -0,0 +1,57 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import json +import os +import sys +from pathlib import Path + +SCRIPT_DIR = Path(__file__).resolve().parent +if str(SCRIPT_DIR) not in sys.path: + sys.path.insert(0, str(SCRIPT_DIR)) + +import kb_common as common # type: ignore + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Validate project canvas files.') + parser.add_argument('--cwd', default='.') + parser.add_argument('--project-id', default='') + return parser.parse_args() + + +def main() -> None: + args = parse_args() + repo_root = common.find_repo_root(Path(args.cwd).expanduser().resolve()) + binding = common.resolve_binding(repo_root, args.project_id or None) + issues: list[dict[str, str]] = [] + for canvas_path in sorted((binding.project_root / 'Maps').glob('*.canvas')): + rel = str(canvas_path.relative_to(binding.project_root)).replace(os.sep, '/') + try: + data = json.loads(canvas_path.read_text(encoding='utf-8')) + except Exception as exc: + issues.append({'file': rel, 'issue': f'invalid-json: {exc}'}) + continue + for node in data.get('nodes', []): + if node.get('type') != 'file': + continue + file_ref = str(node.get('file', '')).strip() + if not file_ref: + issues.append({'file': rel, 'issue': 'file-node-missing-path'}) + continue + target = binding.vault_path / file_ref + if not target.exists(): + issues.append({'file': rel, 'issue': f'missing-target: {file_ref}'}) + + payload = { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'canvas_issues': issues, + 'issue_count': len(issues), + } + print(json.dumps(payload, ensure_ascii=False, indent=2)) + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_common.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_common.py new file mode 100755 index 0000000..d7eb463 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_common.py @@ -0,0 +1,831 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import json +import os +import re +import shutil +import subprocess +from dataclasses import dataclass +from datetime import datetime, timezone +from pathlib import Path +from typing import Any + +IGNORE_DIRS = { + '.git', '.hg', '.svn', '.venv', 'venv', 'node_modules', '__pycache__', + '.mypy_cache', '.pytest_cache', '.ruff_cache', '.idea', '.vscode', + 'dist', 'build', 'checkpoints', 'checkpoint', 'cache', '.cache', + 'temp', 'tmp', '.tmp' +} + +SECTION_COLUMNS: dict[str, list[str]] = { + 'Sources': ['ID', 'Type', 'Title', 'Path', 'Status', 'Origin', 'Updated'], + 'Knowledge': ['ID', 'Type', 'Title', 'Path', 'Status', 'Sources', 'Updated'], + 'Experiments': ['ID', 'Title', 'Path', 'Status', 'Related Results', 'Updated'], + 'Results': ['ID', 'Title', 'Path', 'Status', 'Related Experiment', 'Sources', 'Updated'], + 'Writing': ['ID', 'Title', 'Path', 'Status', 'Related Notes', 'Updated'], + 'Maps': ['ID', 'Title', 'Path', 'Status', 'Type', 'Updated'], + 'Archive': ['ID', 'Title', 'Old Path', 'Archived Path', 'Reason', 'Archived At'], +} +SECTION_ORDER = list(SECTION_COLUMNS) +SOURCE_TYPES = { + 'Papers': 'paper', + 'Web': 'web', + 'Docs': 'doc', + 'Data': 'data', + 'Interviews': 'interview', + 'Notes': 'note', +} +NOTE_KIND_TO_FOLDER = { + 'source': 'Sources', + 'paper': 'Sources/Papers', + 'knowledge': 'Knowledge', + 'experiment': 'Experiments', + 'result': 'Results', + 'report': 'Results/Reports', + 'writing': 'Writing', + 'daily': 'Daily', + 'map': 'Maps', +} + +AUTO_INDEX_BEGIN = '<!-- BEGIN AUTO INDEX -->' +AUTO_INDEX_END = '<!-- END AUTO INDEX -->' + + +@dataclass(frozen=True) +class Binding: + project_id: str + project_slug: str + repo_root: Path + vault_name: str + vault_path: Path + project_root: Path + hub_note: str + status: str + auto_sync: bool + note_language: str + + +def now_iso() -> str: + return datetime.now(timezone.utc).replace(microsecond=0).isoformat().replace('+00:00', 'Z') + + +def today_str() -> str: + return datetime.now().strftime('%Y-%m-%d') + + +def slugify(value: str) -> str: + slug = re.sub(r'[^A-Za-z0-9]+', '-', value).strip('-').lower() + return slug or 'research-project' + + +def titleize_slug(slug: str) -> str: + return ' '.join(part.capitalize() for part in slug.split('-')) + + +def normalize_note_token(value: str) -> str: + return re.sub(r'[^a-z0-9]+', '-', value.lower()).strip('-') + + +def token_set(value: str) -> set[str]: + return {token for token in re.split(r'[^a-z0-9]+', value.lower()) if token} + + +def find_repo_root(cwd: Path) -> Path: + try: + output = subprocess.check_output(['git', 'rev-parse', '--show-toplevel'], cwd=str(cwd), stderr=subprocess.DEVNULL) + return Path(output.decode().strip()) + except Exception: + cur = cwd.resolve() + for candidate in [cur, *cur.parents]: + if (candidate / '.git').exists(): + return candidate + return cur + + +def binding_registry_path(repo_root: Path) -> Path: + return repo_root / '.claude' / 'project-memory' / 'registry.yaml' + + +def project_memory_path(repo_root: Path, project_id: str) -> Path: + return repo_root / '.claude' / 'project-memory' / f'{project_id}.md' + + +def load_binding_registry(path: Path) -> dict[str, Any]: + if not path.exists(): + return {'projects': {}} + raw = path.read_text(encoding='utf-8').strip() + if not raw: + return {'projects': {}} + if raw.startswith('{'): + data = json.loads(raw) + if 'projects' not in data: + data = {'projects': {}} + return data + try: + import yaml # type: ignore + data = yaml.safe_load(raw) or {} + if 'projects' not in data: + data = {'projects': {}} + return data + except Exception: + raise SystemExit(f'Unsupported binding registry format: {path}') + + +def save_binding_registry(path: Path, data: dict[str, Any]) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + try: + import yaml # type: ignore + path.write_text(yaml.safe_dump(data, sort_keys=False, allow_unicode=True), encoding='utf-8') + except Exception: + path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + '\n', encoding='utf-8') + + +def read_text(path: Path, default: str = '') -> str: + if not path.exists(): + return default + return path.read_text(encoding='utf-8') + + +def write_text(path: Path, content: str) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + path.write_text(content, encoding='utf-8') + + +def relative_note_path(target: Path, vault_path: Path) -> str: + return str(target.relative_to(vault_path)).replace(os.sep, '/') + + +def wikilink(rel_path: str) -> str: + rel = rel_path.replace('\\', '/').strip() + if rel.endswith('.md'): + rel = rel[:-3] + return f'[[{rel}]]' + + +def parse_frontmatter(text: str) -> dict[str, str]: + if not text.startswith('---\n'): + return {} + try: + _, block, _ = text.split('---\n', 2) + except ValueError: + return {} + data: dict[str, str] = {} + for line in block.splitlines(): + if ':' not in line or line.strip().startswith('- '): + continue + key, value = line.split(':', 1) + data[key.strip()] = value.strip().strip('"') + return data + + +def set_frontmatter_value(text: str, key: str, value: str) -> str: + value_text = str(value) + if not text.startswith('---\n'): + return f'---\n{key}: {value_text}\n---\n\n{text}'.rstrip() + '\n' + try: + _start, block, rest = text.split('---\n', 2) + except ValueError: + return text + lines = block.splitlines() + replaced = False + out: list[str] = [] + for line in lines: + if line.startswith(f'{key}:'): + out.append(f'{key}: {value_text}') + replaced = True + else: + out.append(line) + if not replaced: + out.append(f'{key}: {value_text}') + return '---\n' + '\n'.join(out) + '\n---\n' + rest.lstrip('\n') + + +def project_root_for(vault_path: Path, project_slug: str) -> Path: + return vault_path / 'Research' / project_slug + + +def resolve_binding(repo_root: Path, project_id: str | None = None) -> Binding: + registry = load_binding_registry(binding_registry_path(repo_root)) + projects = registry.get('projects') or {} + if not projects: + raise SystemExit('No registered projects found in .claude/project-memory/registry.yaml') + if project_id is None: + if len(projects) == 1: + project_id = next(iter(projects)) + else: + detected = detect(repo_root) + project = detected.get('project') or {} + project_id = project.get('project_id') + if not project_id: + raise SystemExit('Multiple projects registered; pass --project-id') + entry = projects.get(project_id) + if not entry: + raise SystemExit(f'Project {project_id!r} not found in binding registry') + project_root = Path(entry['vault_root']).expanduser().resolve() + vault_path = project_root.parent.parent + return Binding( + project_id=entry.get('project_id', project_id), + project_slug=entry.get('project_slug', project_root.name), + repo_root=repo_root, + vault_name=entry.get('vault_name', vault_path.name), + vault_path=vault_path, + project_root=project_root, + hub_note=entry.get('hub_note', relative_note_path(project_root / '00-Hub.md', vault_path)), + status=entry.get('status', 'active'), + auto_sync=bool(entry.get('auto_sync', True)), + note_language=entry.get('note_language', 'en'), + ) + + +def detect_project_features(repo_root: Path) -> dict[str, Any]: + feature_checks = { + '.git': (repo_root / '.git').exists(), + 'README.md': (repo_root / 'README.md').exists(), + 'docs/*.md': (repo_root / 'docs').exists(), + 'notes/*.md': (repo_root / 'notes').exists(), + 'plan/': (repo_root / 'plan').exists(), + 'results/': (repo_root / 'results').exists(), + 'outputs/': (repo_root / 'outputs').exists(), + 'src/': (repo_root / 'src').exists(), + 'scripts/': (repo_root / 'scripts').exists(), + } + config_hits = [] + for name in ['pyproject.toml', 'requirements.txt', 'environment.yml', 'configs', 'conf', 'Makefile']: + if (repo_root / name).exists(): + config_hits.append(name) + score = sum(1 for value in feature_checks.values() if value) + min(len(config_hits), 2) + return { + 'score': score, + 'matched': [name for name, value in feature_checks.items() if value], + 'config_hits': config_hits, + 'is_candidate': score >= 3, + } + + +def detect(repo_root: Path) -> dict[str, Any]: + registry = load_binding_registry(binding_registry_path(repo_root)) + features = detect_project_features(repo_root) + project = None + for project_id, entry in (registry.get('projects') or {}).items(): + roots = [Path(item).expanduser().resolve() for item in entry.get('repo_roots') or []] + if repo_root.resolve() in roots: + project = { + 'project_id': project_id, + 'project_slug': entry.get('project_slug', project_id), + 'vault_root': entry.get('vault_root', ''), + 'status': entry.get('status', 'active'), + 'auto_sync': bool(entry.get('auto_sync', True)), + 'note_language': entry.get('note_language', 'en'), + } + break + return { + 'repo_root': str(repo_root), + 'features': features, + 'project': project, + 'should_bootstrap': bool(features['is_candidate'] and project is None), + } + + +def template_root() -> Path: + return Path(__file__).resolve().parents[3] / 'templates' + + +def render_template(rel_path: str, context: dict[str, str]) -> str: + template = (template_root() / rel_path).read_text(encoding='utf-8') + for key, value in context.items(): + template = template.replace('{{' + key + '}}', value) + return template + + +def scaffold_context(project_slug: str, project_title: str) -> dict[str, str]: + ts = now_iso() + return { + 'project_slug': project_slug, + 'project_title': project_title, + 'timestamp': ts, + 'today': today_str(), + 'title': 'Untitled', + } + + +def ensure_file_from_template(path: Path, template_rel: str, context: dict[str, str], force: bool = False) -> None: + if path.exists() and not force: + return + write_text(path, render_template(template_rel, context)) + + +def ensure_project_scaffold(project_root: Path, project_slug: str, project_title: str, force: bool = False) -> None: + for rel in [ + 'Sources/Papers', 'Sources/Web', 'Sources/Docs', 'Sources/Data', 'Sources/Interviews', 'Sources/Notes', + 'Knowledge', 'Experiments', 'Results/Reports', 'Writing', 'Daily', 'Maps', 'Archive', '_system' + ]: + (project_root / rel).mkdir(parents=True, exist_ok=True) + context = scaffold_context(project_slug, project_title) + ensure_file_from_template(project_root / '00-Hub.md', 'project/00-Hub.md', context, force=force) + ensure_file_from_template(project_root / '01-Plan.md', 'project/01-Plan.md', context, force=force) + ensure_file_from_template(project_root / '02-Index.md', 'project/02-Index.md', context, force=force) + ensure_file_from_template(project_root / 'Daily' / f'{today_str()}.md', 'notes/daily.md', context, force=False) + ensure_file_from_template(project_root / '_system' / 'registry.md', 'project/_system/registry.md', context, force=force) + ensure_file_from_template(project_root / '_system' / 'schema.md', 'project/_system/schema.md', context, force=force) + ensure_file_from_template(project_root / '_system' / 'lint-report.md', 'project/_system/lint-report.md', context, force=force) + + +def maybe_migrate_old_layout(project_root: Path) -> list[dict[str, str]]: + migrated: list[dict[str, str]] = [] + old_papers = project_root / 'Papers' + new_papers = project_root / 'Sources' / 'Papers' + if old_papers.exists(): + new_papers.parent.mkdir(parents=True, exist_ok=True) + if new_papers.exists(): + for path in sorted(old_papers.glob('*.md')): + target = new_papers / path.name + if not target.exists(): + shutil.move(str(path), str(target)) + migrated.append({'from': str(path), 'to': str(target)}) + if old_papers.is_dir() and not any(old_papers.iterdir()): + old_papers.rmdir() + else: + shutil.move(str(old_papers), str(new_papers)) + migrated.append({'from': str(old_papers), 'to': str(new_papers)}) + return migrated + + +def bootstrap_binding(repo_root: Path, vault_path: Path, project_name: str | None = None, force: bool = False, note_language: str = 'en') -> dict[str, Any]: + project_slug = slugify(project_name or repo_root.name) + project_title = project_name or titleize_slug(project_slug) + vault_path = vault_path.expanduser().resolve() + project_root = project_root_for(vault_path, project_slug) + project_root.mkdir(parents=True, exist_ok=True) + ensure_project_scaffold(project_root, project_slug, project_title, force=force) + migrated = maybe_migrate_old_layout(project_root) + + reg_path = binding_registry_path(repo_root) + registry = load_binding_registry(reg_path) + registry.setdefault('projects', {}) + registry['projects'][project_slug] = { + 'project_id': project_slug, + 'project_slug': project_slug, + 'repo_roots': [str(repo_root.resolve())], + 'vault_name': os.environ.get('OBSIDIAN_VAULT_NAME', vault_path.name), + 'vault_root': str(project_root), + 'hub_note': relative_note_path(project_root / '00-Hub.md', vault_path), + 'status': 'active', + 'auto_sync': True, + 'note_language': note_language, + 'updated_at': now_iso(), + } + save_binding_registry(reg_path, registry) + + memory = project_memory_path(repo_root, project_slug) + content = f'''--- +project_id: {project_slug} +project_slug: {project_slug} +repo_root: {repo_root.resolve()} +vault_root: {project_root} +hub_note: {relative_note_path(project_root / '00-Hub.md', vault_path)} +language: {note_language} +last_sync_at: {now_iso()} +status: active +auto_sync: true +--- + +# Project Memory: {project_slug} + +## Current Focus +- TODO + +## Active Tasks +- Review project scaffold +- Fill current sources, experiments, and results +- Keep registry and index updated + +## Recent Sync Summary +- Bootstrap completed at {now_iso()}. +''' + write_text(memory, content) + return { + 'project_id': project_slug, + 'project_slug': project_slug, + 'project_root': str(project_root), + 'memory_path': str(memory), + 'binding_registry': str(reg_path), + 'migrated_paths': migrated, + } + + +def registry_path(project_root: Path) -> Path: + return project_root / '_system' / 'registry.md' + + +def default_registry_tables() -> dict[str, list[dict[str, str]]]: + return {section: [] for section in SECTION_ORDER} + + +def parse_table_row(line: str, columns: list[str]) -> dict[str, str] | None: + if not line.startswith('|'): + return None + parts = [part.strip() for part in line.strip().strip('|').split('|')] + if len(parts) != len(columns): + return None + if set(parts) == {'---'}: + return None + return dict(zip(columns, parts)) + + +def parse_registry_md(path: Path) -> dict[str, list[dict[str, str]]]: + if not path.exists(): + return default_registry_tables() + content = path.read_text(encoding='utf-8') + rows = default_registry_tables() + current_section = None + columns: list[str] | None = None + for raw_line in content.splitlines(): + line = raw_line.rstrip() + if line.startswith('## '): + section = line[3:].strip() + current_section = section if section in SECTION_COLUMNS else None + columns = None + continue + if current_section is None or not line.startswith('|'): + continue + if columns is None: + header = [part.strip() for part in line.strip().strip('|').split('|')] + if header == SECTION_COLUMNS[current_section]: + columns = header + continue + row = parse_table_row(line, columns) + if not row or '---' in ''.join(row.values()): + continue + if current_section == 'Archive': + if row.get('Old Path', '') or row.get('Archived Path', ''): + rows[current_section].append(row) + continue + if row.get(columns[0], ''): + rows[current_section].append(row) + return rows + + +def render_registry_md(rows: dict[str, list[dict[str, str]]], last_updated: str | None = None) -> str: + lines = ['# Registry', '', f'Last updated: {last_updated or now_iso()}', ''] + for section in SECTION_ORDER: + columns = SECTION_COLUMNS[section] + lines.append(f'## {section}') + lines.append('') + lines.append('| ' + ' | '.join(columns) + ' |') + lines.append('|' + '|'.join(['---'] * len(columns)) + '|') + for row in rows.get(section, []): + lines.append('| ' + ' | '.join(row.get(col, '') for col in columns) + ' |') + lines.append('') + return '\n'.join(lines).rstrip() + '\n' + + +def write_registry(project_root: Path, rows: dict[str, list[dict[str, str]]]) -> None: + write_text(registry_path(project_root), render_registry_md(rows)) + + +def section_and_row_for_relpath(rel_path: str) -> tuple[str, dict[str, str]] | None: + rel = rel_path.replace('\\', '/') + updated = now_iso() + title = Path(rel).stem.replace('-', ' ') + if rel.startswith('Sources/'): + parts = rel.split('/', 2) + source_folder = parts[1] if len(parts) >= 2 else '' + source_type = SOURCE_TYPES.get(source_folder) + if not source_type: + return None + return 'Sources', { + 'ID': '', 'Type': source_type, 'Title': title.title(), 'Path': wikilink(rel), + 'Status': 'active', 'Origin': source_type, 'Updated': updated, + } + if rel.startswith('Knowledge/'): + return 'Knowledge', { + 'ID': '', 'Type': 'knowledge', 'Title': title.title(), 'Path': wikilink(rel), + 'Status': 'active', 'Sources': '', 'Updated': updated, + } + if rel.startswith('Experiments/'): + return 'Experiments', { + 'ID': '', 'Title': title.title(), 'Path': wikilink(rel), 'Status': 'active', + 'Related Results': '', 'Updated': updated, + } + if rel.startswith('Results/'): + return 'Results', { + 'ID': '', 'Title': title.title(), 'Path': wikilink(rel), 'Status': 'active', + 'Related Experiment': '', 'Sources': '', 'Updated': updated, + } + if rel.startswith('Writing/'): + return 'Writing', { + 'ID': '', 'Title': title.title(), 'Path': wikilink(rel), 'Status': 'draft', + 'Related Notes': '', 'Updated': updated, + } + if rel.startswith('Maps/'): + return 'Maps', { + 'ID': '', 'Title': title.title(), 'Path': wikilink(rel), 'Status': 'active', + 'Type': Path(rel).suffix.lstrip('.') or 'map', 'Updated': updated, + } + return None + + +def next_registry_id(rows: list[dict[str, str]], prefix: str) -> str: + nums = [] + for row in rows: + rid = row.get('ID', '') + if rid.startswith(prefix + '-'): + try: + nums.append(int(rid.split('-')[-1])) + except ValueError: + pass + return f'{prefix}-{max(nums, default=0) + 1:03d}' + + +def prefix_for_section_row(section: str, row: dict[str, str]) -> str: + if section == 'Sources': + return row['Type'] + return { + 'Knowledge': 'knowledge', + 'Experiments': 'exp', + 'Results': 'result', + 'Writing': 'writing', + 'Maps': 'map', + 'Archive': 'archive', + }[section] + + +def registry_add_or_update(project_root: Path, rel_path: str, *, status: str | None = None) -> dict[str, Any]: + payload = section_and_row_for_relpath(rel_path) + if payload is None: + return {'updated': False, 'reason': 'path-not-registrable'} + section, row = payload + rows = parse_registry_md(registry_path(project_root)) + existing = None + for item in rows[section]: + if item.get('Path') == wikilink(rel_path): + existing = item + break + if existing is None: + row['ID'] = next_registry_id(rows[section], prefix_for_section_row(section, row)) + if status: + row['Status'] = status + rows[section].append(row) + else: + existing['Path'] = row['Path'] + existing['Updated'] = row['Updated'] + if status is not None: + existing['Status'] = status + write_registry(project_root, rows) + return {'updated': True, 'section': section, 'path': rel_path} + + +def registry_archive(project_root: Path, old_rel: str, archived_rel: str, reason: str = 'archive') -> dict[str, Any]: + rows = parse_registry_md(registry_path(project_root)) + old_link = wikilink(old_rel) + removed_row = None + removed_section = None + for section in SECTION_ORDER: + if section == 'Archive': + continue + for idx, row in enumerate(list(rows[section])): + if row.get('Path') == old_link: + removed_row = row + removed_section = section + rows[section].pop(idx) + break + if removed_row: + break + archive_row = { + 'ID': removed_row.get('ID', '') if removed_row else '', + 'Title': removed_row.get('Title', Path(old_rel).stem.title()) if removed_row else Path(old_rel).stem.title(), + 'Old Path': wikilink(old_rel), + 'Archived Path': wikilink(archived_rel), + 'Reason': reason, + 'Archived At': now_iso(), + } + rows['Archive'].append(archive_row) + write_registry(project_root, rows) + return {'updated': True, 'section': removed_section or 'Archive'} + + +def registry_remove_path(project_root: Path, rel_path: str, reason: str = 'purge', *, record_archive: bool = True) -> None: + rows = parse_registry_md(registry_path(project_root)) + target = wikilink(rel_path) + removed_row = None + for section in SECTION_ORDER: + if section == 'Archive': + continue + keep_rows = [] + for row in rows[section]: + if row.get('Path') == target: + removed_row = row + continue + keep_rows.append(row) + rows[section] = keep_rows + if record_archive: + rows['Archive'].append({ + 'ID': removed_row.get('ID', '') if removed_row else '', + 'Title': removed_row.get('Title', Path(rel_path).stem.title()) if removed_row else Path(rel_path).stem.title(), + 'Old Path': wikilink(rel_path), + 'Archived Path': '', + 'Reason': reason, + 'Archived At': now_iso(), + }) + write_registry(project_root, rows) + + +def scan_canonical_relpaths(project_root: Path) -> list[str]: + rels: list[str] = [] + for base in ['Sources', 'Knowledge', 'Experiments', 'Results', 'Writing', 'Maps']: + path = project_root / base + if not path.exists(): + continue + for child in sorted(path.rglob('*')): + if child.is_dir(): + continue + if base == 'Maps' and child.suffix not in {'.canvas', '.md'}: + continue + if base != 'Maps' and child.suffix != '.md': + continue + rels.append(str(child.relative_to(project_root)).replace(os.sep, '/')) + return rels + + +def update_index(project_root: Path) -> None: + rows = parse_registry_md(registry_path(project_root)) + auto_lines: list[str] = [] + for title, section in [('Sources', 'Sources'), ('Knowledge', 'Knowledge'), ('Experiments', 'Experiments'), ('Results', 'Results'), ('Writing', 'Writing'), ('Maps', 'Maps')]: + auto_lines.append(f'### {title}') + active = [row['Path'] for row in rows.get(section, []) if row.get('Status', '') != 'archived'] + if active: + auto_lines.extend(f'- {item}' for item in active) + else: + auto_lines.append('- None yet.') + auto_lines.append('') + + managed_note = 'Managed block. Refresh with `/kb-sync` or `/kb-index`. Put hand-written navigation in **Curated Index**, not inside the markers below.' + auto_block = AUTO_INDEX_BEGIN + '\n' + '\n'.join(auto_lines).rstrip() + '\n' + AUTO_INDEX_END + index_path = project_root / '02-Index.md' + content = read_text(index_path) + + if not content.strip(): + content = '\n'.join([ + '---', + 'type: project-index', + f'updated: {now_iso()}', + '---', + '', + '# Index', + '', + '## Curated Index', + '- Add human-maintained entry points here.', + '', + '## Auto Index', + '', + managed_note, + auto_block, + '', + ]).rstrip() + '\n' + else: + content = set_frontmatter_value(content, 'updated', now_iso()) + if AUTO_INDEX_BEGIN in content and AUTO_INDEX_END in content: + content = re.sub( + rf'{re.escape(AUTO_INDEX_BEGIN)}[\s\S]*?{re.escape(AUTO_INDEX_END)}', + auto_block, + content, + count=1, + ) + else: + auto_section = '\n'.join([ + '## Auto Index', + '', + managed_note, + auto_block, + '', + ]).rstrip() + '\n' + if re.search(r'(?m)^## Auto Index\s*$', content): + content = re.sub( + r'(?ms)^## Auto Index\s*\n.*?(?=^## |\Z)', + auto_section, + content, + count=1, + ).rstrip() + '\n' + else: + content = content.rstrip() + '\n\n' + auto_section + + write_text(index_path, content.rstrip() + '\n') + + +def ensure_today_daily(project_root: Path, project_slug: str, force: bool = False) -> Path: + path = project_root / 'Daily' / f'{today_str()}.md' + if not path.exists() or force: + context = scaffold_context(project_slug, titleize_slug(project_slug)) + write_text(path, render_template('notes/daily.md', context)) + return path + + +def prepend_recent_change(project_root: Path, message: str) -> None: + hub = project_root / '00-Hub.md' + content = read_text(hub) + marker = '## Recent Changes\n' + if marker not in content: + content = content.rstrip() + f'\n\n{marker}- {message}\n' + else: + head, tail = content.split(marker, 1) + existing_lines = [line for line in tail.splitlines() if line.startswith('- ')] + merged = [f'- {message}', *[line for line in existing_lines if line != f'- {message}']] + content = head + marker + '\n'.join(merged[:8]) + '\n' + write_text(hub, content) + + +def update_project_memory(repo_root: Path, project_id: str, project_root: Path, hub_note: str, note_language: str, summary: str | None = None) -> None: + path = project_memory_path(repo_root, project_id) + content = read_text(path, f'---\nproject_id: {project_id}\nproject_slug: {project_id}\nrepo_root: {repo_root}\nvault_root: {project_root}\nhub_note: {hub_note}\nlanguage: {note_language}\nstatus: active\nauto_sync: true\n---\n\n# Project Memory: {project_id}\n') + content = set_frontmatter_value(content, 'last_sync_at', now_iso()) + content = set_frontmatter_value(content, 'vault_root', str(project_root)) + content = set_frontmatter_value(content, 'hub_note', hub_note) + if summary: + block = f'## Recent Sync Summary\n- {summary}\n' + if '## Recent Sync Summary\n' in content: + content = re.sub(r'## Recent Sync Summary\n(?:- .*\n?)*', block, content, count=1) + else: + content = content.rstrip() + '\n\n' + block + write_text(path, content) + + +def list_kind_notes(project_root: Path, kind: str) -> list[Path]: + rel = NOTE_KIND_TO_FOLDER.get(kind) + if not rel: + return [] + base = project_root / rel + if not base.exists(): + return [] + suffixes = {'.md'} if kind != 'map' else {'.md', '.canvas'} + return sorted([p for p in base.rglob('*') if p.is_file() and p.suffix in suffixes]) + + +def project_note_ref(path: Path, project_root: Path) -> str: + rel = path.relative_to(project_root).as_posix() + return rel[:-3] if rel.endswith('.md') else rel + + +def search_note_candidates(project_root: Path, kind: str, query: str, limit: int = 5) -> list[Path]: + notes = list_kind_notes(project_root, kind) + if not notes: + return [] + raw_query = query.strip() + exact = project_root / raw_query + if exact.exists(): + return [exact] + if raw_query.endswith('.md'): + exact_md = project_root / raw_query + if exact_md.exists(): + return [exact_md] + query_norm = normalize_note_token(raw_query[:-3] if raw_query.endswith('.md') else raw_query) + query_tokens = token_set(raw_query) + scored: list[tuple[tuple[int, int, int], Path]] = [] + for note in notes: + ref = project_note_ref(note, project_root) + ref_norm = normalize_note_token(ref) + note_norm = normalize_note_token(note.stem) + score = None + if ref == raw_query or note.stem == raw_query: + score = (0, len(ref), len(note.stem)) + elif ref_norm == query_norm or note_norm == query_norm: + score = (1, len(ref_norm), len(note_norm)) + elif query_norm and query_norm in ref_norm: + score = (2, len(ref_norm), len(note_norm)) + elif query_tokens & token_set(ref): + score = (3, -len(query_tokens & token_set(ref)), len(ref_norm)) + if score is not None: + scored.append((score, note)) + scored.sort(key=lambda item: (item[0], project_note_ref(item[1], project_root))) + return [item[1] for item in scored[:limit]] + + +def resolve_project_note(project_root: Path, note: str) -> Path: + candidate = (project_root / note).resolve() + if candidate.exists(): + return candidate + if not note.endswith('.md'): + candidate_md = (project_root / f'{note}.md').resolve() + if candidate_md.exists(): + return candidate_md + raise SystemExit(f'Note not found: {note}') + + +def replace_wikilinks(content: str, old_rel: str, new_rel: str | None = None) -> str: + old_variants = {old_rel, old_rel[:-3] if old_rel.endswith('.md') else old_rel} + new_target = None if new_rel is None else (new_rel[:-3] if new_rel.endswith('.md') else new_rel) + + def repl(match: re.Match[str]) -> str: + inner = match.group(1) + target, *rest = inner.split('|', 1) + target_no_heading = target.split('#', 1)[0] + if target_no_heading not in old_variants: + return match.group(0) + if new_target is None: + return match.group(0) + replaced = target.replace(target_no_heading, new_target, 1) + if rest: + return f'[[{replaced}|{rest[0]}]]' + return f'[[{replaced}]]' + + return re.sub(r'\[\[([^\]]+)\]\]', repl, content) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_index_check.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_index_check.py new file mode 100755 index 0000000..ecf3ba2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_index_check.py @@ -0,0 +1,57 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import json +import re +import sys +from pathlib import Path + +SCRIPT_DIR = Path(__file__).resolve().parent +if str(SCRIPT_DIR) not in sys.path: + sys.path.insert(0, str(SCRIPT_DIR)) + +import kb_common as common # type: ignore + +INDEX_LINK_RE = re.compile(r'\[\[([^\]|#]+)') + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Check 02-Index coverage for active canonical notes.') + parser.add_argument('--cwd', default='.') + parser.add_argument('--project-id', default='') + return parser.parse_args() + + +def main() -> None: + args = parse_args() + repo_root = common.find_repo_root(Path(args.cwd).expanduser().resolve()) + binding = common.resolve_binding(repo_root, args.project_id or None) + rows = common.parse_registry_md(common.registry_path(binding.project_root)) + index_path = binding.project_root / '02-Index.md' + index_text = common.read_text(index_path) + index_links = {match.strip() for match in INDEX_LINK_RE.findall(index_text)} + + missing: list[str] = [] + for section in ['Sources', 'Knowledge', 'Experiments', 'Results', 'Writing', 'Maps']: + for row in rows.get(section, []): + if row.get('Status') == 'archived': + continue + path = row.get('Path', '').strip() + if not path.startswith('[['): + continue + target = path[2:-2] + if target not in index_links: + missing.append(target) + + payload = { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'missing_index_entries': sorted(missing), + 'missing_count': len(missing), + } + print(json.dumps(payload, ensure_ascii=False, indent=2)) + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_link_check.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_link_check.py new file mode 100755 index 0000000..5bc37de --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_link_check.py @@ -0,0 +1,81 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import json +import os +import re +import sys +from pathlib import Path + +SCRIPT_DIR = Path(__file__).resolve().parent +if str(SCRIPT_DIR) not in sys.path: + sys.path.insert(0, str(SCRIPT_DIR)) + +import kb_common as common # type: ignore + +WIKILINK_RE = re.compile(r'\[\[([^\]]+)\]\]') + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Check wikilinks inside the bound project KB.') + parser.add_argument('--cwd', default='.') + parser.add_argument('--project-id', default='') + return parser.parse_args() + + +def normalize_target(target: str) -> str: + target = target.split('|', 1)[0].split('#', 1)[0].strip() + for suffix in ('.md', '.canvas'): + if target.endswith(suffix): + target = target[:-len(suffix)] + break + return target + + +def build_targets(project_root: Path) -> tuple[set[str], dict[str, list[str]]]: + exact: set[str] = set() + stems: dict[str, list[str]] = {} + for suffix in ('*.md', '*.canvas'): + for path in project_root.rglob(suffix): + rel = str(path.relative_to(project_root)).replace(os.sep, '/') + note_ref = rel[:-len(path.suffix)] + exact.add(note_ref) + stems.setdefault(path.stem, []).append(note_ref) + return exact, stems + + +def main() -> None: + args = parse_args() + repo_root = common.find_repo_root(Path(args.cwd).expanduser().resolve()) + binding = common.resolve_binding(repo_root, args.project_id or None) + exact, stems = build_targets(binding.project_root) + broken: list[dict[str, str]] = [] + + for path in sorted(binding.project_root.rglob('*.md')): + rel = str(path.relative_to(binding.project_root)).replace(os.sep, '/') + if rel.startswith('_system/'): + continue + text = path.read_text(encoding='utf-8') + for raw in WIKILINK_RE.findall(text): + target = normalize_target(raw) + if not target or target.startswith('#'): + continue + if target in exact: + continue + basename = Path(target).name + if basename in stems and len(stems[basename]) == 1: + continue + broken.append({'file': rel, 'target': target}) + + payload = { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'broken_links': broken, + 'broken_count': len(broken), + } + print(json.dumps(payload, ensure_ascii=False, indent=2)) + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_lint.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_lint.py new file mode 100755 index 0000000..98b9446 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_lint.py @@ -0,0 +1,190 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import json +import os +import re +import subprocess +import sys +from pathlib import Path + +SCRIPT_DIR = Path(__file__).resolve().parent +if str(SCRIPT_DIR) not in sys.path: + sys.path.insert(0, str(SCRIPT_DIR)) + +import kb_common as common # type: ignore + +WIKILINK_RE = re.compile(r'\[\[([^\]|#]+)') +SOURCE_LINK_RE = re.compile(r'\[\[(Sources/[^\]|#]+)') +EXPERIMENT_LINK_RE = re.compile(r'\[\[(Experiments/[^\]|#]+)') +RESULT_LINK_RE = re.compile(r'\[\[(Results/[^\]|#]+)') +ARCHIVED_RESULT_LINK_RE = re.compile(r'\[\[(Archive/Results/[^\]|#]+)') + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Aggregate KB lint checks and write _system/lint-report.md.') + parser.add_argument('--cwd', default='.') + parser.add_argument('--project-id', default='') + return parser.parse_args() + + +def run_json(script_name: str, cwd: Path, project_id: str) -> dict: + cmd = ['python3', str(SCRIPT_DIR / script_name), '--cwd', str(cwd)] + if project_id: + cmd.extend(['--project-id', project_id]) + out = subprocess.check_output(cmd, text=True) + return json.loads(out) + + +def note_refs_in_file(path: Path) -> set[str]: + text = path.read_text(encoding='utf-8') + return {match.strip() for match in WIKILINK_RE.findall(text)} + + +def main() -> None: + args = parse_args() + repo_root = common.find_repo_root(Path(args.cwd).expanduser().resolve()) + binding = common.resolve_binding(repo_root, args.project_id or None) + + registry_check = run_json('kb_registry_check.py', repo_root, binding.project_id) + link_check = run_json('kb_link_check.py', repo_root, binding.project_id) + index_check = run_json('kb_index_check.py', repo_root, binding.project_id) + canvas_check = run_json('kb_canvas_check.py', repo_root, binding.project_id) + + rows = common.parse_registry_md(common.registry_path(binding.project_root)) + knowledge_without_sources: list[str] = [] + for row in rows.get('Knowledge', []): + target = row.get('Path', '') + if not target.startswith('[['): + continue + note_ref = target[2:-2] + note_path = binding.project_root / f'{note_ref}.md' + if note_path.exists(): + text = note_path.read_text(encoding='utf-8') + if not SOURCE_LINK_RE.search(text): + knowledge_without_sources.append(note_ref) + + experiments_without_results: list[str] = [] + experiments_with_only_archived_results: list[str] = [] + for row in rows.get('Experiments', []): + target = row.get('Path', '') + if not target.startswith('[['): + continue + note_ref = target[2:-2] + note_path = binding.project_root / f'{note_ref}.md' + if note_path.exists(): + text = note_path.read_text(encoding='utf-8') + has_active_result = bool(RESULT_LINK_RE.search(text)) + has_archived_result = bool(ARCHIVED_RESULT_LINK_RE.search(text)) + if not has_active_result and not has_archived_result: + experiments_without_results.append(note_ref) + elif has_archived_result and not has_active_result: + experiments_with_only_archived_results.append(note_ref) + + result_refs = {row.get('Path', '')[2:-2] for row in rows.get('Results', []) if row.get('Path', '').startswith('[[')} + results_without_experiments: list[str] = [] + for note_ref in sorted(result_refs): + note_path = binding.project_root / f'{note_ref}.md' + if note_path.exists(): + text = note_path.read_text(encoding='utf-8') + if not EXPERIMENT_LINK_RE.search(text): + results_without_experiments.append(note_ref) + + archived_refs = {row.get('Archived Path', '')[2:-2] for row in rows.get('Archive', []) if row.get('Archived Path', '').startswith('[[')} + active_notes_referencing_archived_notes: list[str] = [] + active_md_files = [] + for p in binding.project_root.rglob('*.md'): + rel = str(p.relative_to(binding.project_root)).replace(os.sep, '/') + if rel.startswith('Archive/') or rel.startswith('_system/'): + continue + active_md_files.append(p) + for path in active_md_files: + refs = note_refs_in_file(path) + shared = sorted(ref for ref in refs if ref in archived_refs) + for ref in shared: + active_notes_referencing_archived_notes.append(f'{path.relative_to(binding.project_root).as_posix()} -> {ref}') + + daily_candidates: list[str] = [] + for daily_path in sorted((binding.project_root / 'Daily').glob('*.md')): + text = daily_path.read_text(encoding='utf-8') + if 'TODO' in text or 'Open Questions' in text or 'Promote' in text: + daily_candidates.append(daily_path.relative_to(binding.project_root).as_posix()) + + summary_rows = [ + ('Broken links', 'pass' if link_check['broken_count'] == 0 else 'fail', link_check['broken_count']), + ('Missing registry entries', 'pass' if not registry_check['missing_registry_entries'] else 'fail', len(registry_check['missing_registry_entries'])), + ('Dangling registry entries', 'pass' if not registry_check['dangling_registry_entries'] else 'fail', len(registry_check['dangling_registry_entries'])), + ('Missing index entries', 'pass' if index_check['missing_count'] == 0 else 'warn', index_check['missing_count']), + ('Canvas issues', 'pass' if canvas_check['issue_count'] == 0 else 'warn', canvas_check['issue_count']), + ('Knowledge without sources', 'pass' if not knowledge_without_sources else 'warn', len(knowledge_without_sources)), + ('Experiments without results', 'pass' if not experiments_without_results else 'warn', len(experiments_without_results)), + ('Experiments with only archived results', 'pass' if not experiments_with_only_archived_results else 'warn', len(experiments_with_only_archived_results)), + ('Results without experiments', 'pass' if not results_without_experiments else 'warn', len(results_without_experiments)), + ('Daily promotion candidates', 'pass' if not daily_candidates else 'warn', len(daily_candidates)), + ('Active notes referencing archived notes', 'pass' if not active_notes_referencing_archived_notes else 'warn', len(active_notes_referencing_archived_notes)), + ] + + lines = ['# Lint Report', '', f'Last checked: {common.now_iso()}', '', '## Summary', '', '| Check | Status | Count |', '|---|---|---|'] + lines.extend(f'| {name} | {status} | {count} |' for name, status, count in summary_rows) + lines.extend(['', '## Issues', '']) + + def add_issue_block(title: str, items: list[str]) -> None: + lines.append(f'### {title}') + if items: + lines.extend(f'- {item}' for item in items) + else: + lines.append('- None.') + lines.append('') + + add_issue_block('Missing Registry Entries', registry_check['missing_registry_entries']) + add_issue_block('Dangling Registry Entries', registry_check['dangling_registry_entries']) + add_issue_block('Broken Wikilinks', [f"{item['file']} -> {item['target']}" for item in link_check['broken_links']]) + add_issue_block('Missing Index Entries', index_check['missing_index_entries']) + add_issue_block('Canvas Issues', [f"{item['file']} -> {item['issue']}" for item in canvas_check['canvas_issues']]) + add_issue_block('Knowledge Notes Without Sources', knowledge_without_sources) + add_issue_block('Experiments Without Results', experiments_without_results) + add_issue_block('Experiments With Only Archived Results', experiments_with_only_archived_results) + add_issue_block('Results Without Experiments', results_without_experiments) + add_issue_block('Daily Promotion Candidates', daily_candidates) + add_issue_block('Active Notes Referencing Archived Notes', active_notes_referencing_archived_notes) + + lines.extend(['## Recommended Fixes', '']) + fixes: list[str] = [] + if registry_check['missing_registry_entries']: + fixes.append('Add registry rows for all missing canonical notes.') + if link_check['broken_count']: + fixes.append('Repair or remove broken wikilinks before the next sync.') + if index_check['missing_count']: + fixes.append('Update 02-Index.md so active canonical notes remain navigable.') + if experiments_with_only_archived_results: + fixes.append('Decide whether archived result links should stay historical or be promoted back into active Results.') + if daily_candidates: + fixes.append('Promote durable content from Daily into Knowledge, Experiments, Results, or Writing.') + if not fixes: + fixes.append('No action required.') + lines.extend(f'- {fix}' for fix in fixes) + lines.append('') + + report_path = binding.project_root / '_system' / 'lint-report.md' + common.write_text(report_path, '\n'.join(lines)) + + payload = { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'lint_report': str(report_path), + 'broken_links': link_check['broken_count'], + 'missing_registry_entries': len(registry_check['missing_registry_entries']), + 'missing_index_entries': index_check['missing_count'], + 'knowledge_without_sources': len(knowledge_without_sources), + 'experiments_without_results': len(experiments_without_results), + 'experiments_with_only_archived_results': len(experiments_with_only_archived_results), + 'results_without_experiments': len(results_without_experiments), + 'daily_promotion_candidates': len(daily_candidates), + 'active_notes_referencing_archived_notes': len(active_notes_referencing_archived_notes), + } + print(json.dumps(payload, ensure_ascii=False, indent=2)) + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_registry_check.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_registry_check.py new file mode 100755 index 0000000..652a0d9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_registry_check.py @@ -0,0 +1,63 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import json +import os +import sys +from pathlib import Path + +SCRIPT_DIR = Path(__file__).resolve().parent +if str(SCRIPT_DIR) not in sys.path: + sys.path.insert(0, str(SCRIPT_DIR)) + +import kb_common as common # type: ignore + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Check registry coverage for the bound project KB.') + parser.add_argument('--cwd', default='.') + parser.add_argument('--project-id', default='') + return parser.parse_args() + + +def main() -> None: + args = parse_args() + repo_root = common.find_repo_root(Path(args.cwd).expanduser().resolve()) + binding = common.resolve_binding(repo_root, args.project_id or None) + rels = common.scan_canonical_relpaths(binding.project_root) + rows = common.parse_registry_md(common.registry_path(binding.project_root)) + + active_entries: list[tuple[str, str]] = [] + ids: dict[str, list[str]] = {} + for section, entries in rows.items(): + if section == 'Archive': + continue + for row in entries: + link = row.get('Path', '') + active_entries.append((section, link)) + rid = row.get('ID', '') + if rid: + ids.setdefault(rid, []).append(link) + + desired = {common.wikilink(rel) for rel in rels} + registered = {link for _, link in active_entries if link} + missing = sorted(rel for rel in rels if common.wikilink(rel) not in registered) + dangling = sorted(link for link in registered if link not in desired) + duplicate_ids = {rid: paths for rid, paths in ids.items() if len(paths) > 1} + + payload = { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'canonical_count': len(rels), + 'registered_count': len(registered), + 'missing_registry_entries': missing, + 'dangling_registry_entries': dangling, + 'duplicate_ids': duplicate_ids, + 'coverage_ok': not missing and not dangling and not duplicate_ids, + } + print(json.dumps(payload, ensure_ascii=False, indent=2)) + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_scaffold.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_scaffold.py new file mode 100755 index 0000000..9968285 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/kb_scaffold.py @@ -0,0 +1,51 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import json +import os +import sys +from pathlib import Path + +SCRIPT_DIR = Path(__file__).resolve().parent +if str(SCRIPT_DIR) not in sys.path: + sys.path.insert(0, str(SCRIPT_DIR)) + +import kb_common as common # type: ignore + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Scaffold a project KB skeleton.') + parser.add_argument('--cwd', default='.') + parser.add_argument('--project-id', default='') + parser.add_argument('--vault-path', default='') + parser.add_argument('--project-name', default='') + parser.add_argument('--force', action='store_true') + parser.add_argument('--note-language', default='en') + return parser.parse_args() + + +def main() -> None: + args = parse_args() + repo_root = common.find_repo_root(Path(args.cwd).expanduser().resolve()) + if args.vault_path: + result = common.bootstrap_binding( + repo_root, + Path(args.vault_path), + project_name=args.project_name or None, + force=args.force, + note_language=args.note_language, + ) + else: + binding = common.resolve_binding(repo_root, args.project_id or None) + common.ensure_project_scaffold(binding.project_root, binding.project_slug, common.titleize_slug(binding.project_slug), force=args.force) + result = { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'scaffold_refreshed': True, + } + print(json.dumps(result, ensure_ascii=False, indent=2)) + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/project_kb.py b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/project_kb.py new file mode 100755 index 0000000..dbc62c2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-project-kb-core/scripts/project_kb.py @@ -0,0 +1,492 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import json +import os +import re +import shutil +import sys +from pathlib import Path +from typing import Any + +SCRIPT_DIR = Path(__file__).resolve().parent +if str(SCRIPT_DIR) not in sys.path: + sys.path.insert(0, str(SCRIPT_DIR)) + +import kb_common as common # type: ignore + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Project-scoped Obsidian KB helper.') + subparsers = parser.add_subparsers(dest='command', required=True) + + detect = subparsers.add_parser('detect', help='Detect repo binding and candidate status.') + detect.add_argument('--cwd', default='.') + + bootstrap = subparsers.add_parser('bootstrap', help='Create or rebuild a bound project KB.') + bootstrap.add_argument('--cwd', default='.') + bootstrap.add_argument('--vault-path', default='') + bootstrap.add_argument('--project-name', default='') + bootstrap.add_argument('--project-id', default='') + bootstrap.add_argument('--note-language', default='en') + bootstrap.add_argument('--force', action='store_true') + + sync = subparsers.add_parser('sync', help='Refresh scaffold, registry, index, daily note, and runtime binding summary.') + sync.add_argument('--cwd', default='.') + sync.add_argument('--project-id', default='') + sync.add_argument('--scope', default='auto') + + status = subparsers.add_parser('status', help='Return a compact project KB status summary.') + status.add_argument('--cwd', default='.') + status.add_argument('--project-id', default='') + + lifecycle = subparsers.add_parser('lifecycle', help='Manage project-level lifecycle state.') + lifecycle.add_argument('--cwd', default='.') + lifecycle.add_argument('--project-id', default='') + lifecycle.add_argument('--mode', choices=['detach', 'archive', 'purge', 'rebuild'], required=True) + lifecycle.add_argument('--vault-path', default='') + lifecycle.add_argument('--force', action='store_true') + + query = subparsers.add_parser('query-context', help='Return note context candidates for the current project.') + query.add_argument('--cwd', default='.') + query.add_argument('--project-id', default='') + query.add_argument('--kind', default='broad') + query.add_argument('--query', default='') + + find = subparsers.add_parser('find-canonical-note', help='Find canonical notes by kind and query.') + find.add_argument('--cwd', default='.') + find.add_argument('--project-id', default='') + find.add_argument('--kind', required=True) + find.add_argument('--query', required=True) + find.add_argument('--limit', type=int, default=5) + + note = subparsers.add_parser('note-lifecycle', help='Manage a single canonical note.') + note.add_argument('--cwd', default='.') + note.add_argument('--project-id', default='') + note.add_argument('--mode', choices=['archive', 'purge', 'rename'], required=True) + note.add_argument('--note', required=True) + note.add_argument('--dest', default='') + note.add_argument('--reason', default='manual') + + return parser.parse_args() + + +def repo_root_from(cwd: str) -> Path: + return common.find_repo_root(Path(cwd).expanduser().resolve()) + + +def registry_links(rows: dict[str, list[dict[str, str]]]) -> dict[str, str]: + links: dict[str, str] = {} + for section, entries in rows.items(): + if section == 'Archive': + continue + for row in entries: + path = row.get('Path', '') + if path: + links[path] = section + return links + + +def sync_registry(project_root: Path) -> dict[str, Any]: + rels = common.scan_canonical_relpaths(project_root) + rows = common.parse_registry_md(common.registry_path(project_root)) + existing = registry_links(rows) + desired = {common.wikilink(rel): rel for rel in rels} + + added: list[str] = [] + removed: list[str] = [] + for rel in rels: + result = common.registry_add_or_update(project_root, rel) + if result.get('updated') and common.wikilink(rel) not in existing: + added.append(rel) + + rows = common.parse_registry_md(common.registry_path(project_root)) + for section in list(rows): + if section == 'Archive': + continue + keep: list[dict[str, str]] = [] + for row in rows[section]: + link = row.get('Path', '') + if link in desired: + keep.append(row) + else: + removed.append(link) + rows[section] = keep + common.write_registry(project_root, rows) + return {'canonical_paths': rels, 'added': added, 'removed': removed} + + +def update_hub_link_block(binding: common.Binding) -> None: + hub_path = binding.project_root / '00-Hub.md' + content = common.read_text(hub_path) + required_lines = [ + '- [[01-Plan]]', + '- [[02-Index]]', + '- [[_system/registry]]', + f'- [[Daily/{common.today_str()}]]', + ] + marker = '## Important Links\n' + if marker not in content: + content = content.rstrip() + '\n\n' + marker + '\n'.join(required_lines) + '\n' + else: + head, tail = content.split(marker, 1) + rest_lines = tail.splitlines() + collected: list[str] = [] + skipping = True + idx = 0 + while idx < len(rest_lines): + line = rest_lines[idx] + if skipping and (line.startswith('- ') or not line.strip()): + idx += 1 + continue + skipping = False + collected = rest_lines[idx:] + break + content = head + marker + '\n'.join(required_lines) + '\n\n' + '\n'.join(collected).lstrip('\n') + common.write_text(hub_path, content.rstrip() + '\n') + + +def run_sync(binding: common.Binding, scope: str = 'auto') -> dict[str, Any]: + common.ensure_project_scaffold(binding.project_root, binding.project_slug, common.titleize_slug(binding.project_slug)) + migrated = common.maybe_migrate_old_layout(binding.project_root) + daily_path = common.ensure_today_daily(binding.project_root, binding.project_slug) + registry_result = sync_registry(binding.project_root) + common.update_index(binding.project_root) + update_hub_link_block(binding) + summary = f'scope={scope}; canonical={len(registry_result["canonical_paths"])}; added={len(registry_result["added"])}; migrated={len(migrated)}' + common.update_project_memory( + binding.repo_root, + binding.project_id, + binding.project_root, + common.relative_note_path(binding.project_root / '00-Hub.md', binding.vault_path), + binding.note_language, + summary=summary, + ) + common.prepend_recent_change(binding.project_root, f'{common.now_iso()}: sync refreshed scaffold, registry, index, and daily note ({scope}).') + return { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'daily_note': str(daily_path), + 'migrated_paths': migrated, + 'registry_added': registry_result['added'], + 'registry_removed': registry_result['removed'], + 'canonical_count': len(registry_result['canonical_paths']), + 'scope': scope, + } + + +def load_binding(repo_root: Path, project_id: str | None) -> common.Binding: + return common.resolve_binding(repo_root, project_id or None) + + +def update_binding_entry(repo_root: Path, project_id: str, **updates: Any) -> dict[str, Any]: + reg_path = common.binding_registry_path(repo_root) + registry = common.load_binding_registry(reg_path) + entry = (registry.get('projects') or {}).get(project_id) + if entry is None: + raise SystemExit(f'Project {project_id!r} not found in binding registry') + entry.update(updates) + entry['updated_at'] = common.now_iso() + common.save_binding_registry(reg_path, registry) + return entry + + +def archive_project(binding: common.Binding) -> dict[str, Any]: + archive_root = binding.vault_path / 'Research' / '_archived' + archive_root.mkdir(parents=True, exist_ok=True) + dest = archive_root / f'{binding.project_slug}-{common.today_str()}' + counter = 1 + while dest.exists(): + counter += 1 + dest = archive_root / f'{binding.project_slug}-{common.today_str()}-{counter}' + shutil.move(str(binding.project_root), str(dest)) + entry = update_binding_entry( + binding.repo_root, + binding.project_id, + vault_root=str(dest), + hub_note=common.relative_note_path(dest / '00-Hub.md', binding.vault_path), + status='archived', + auto_sync=False, + ) + common.update_project_memory( + binding.repo_root, + binding.project_id, + dest, + entry['hub_note'], + binding.note_language, + summary=f'project archived to {dest}', + ) + return {'project_id': binding.project_id, 'archived_to': str(dest)} + + +def purge_project(binding: common.Binding) -> dict[str, Any]: + reg_path = common.binding_registry_path(binding.repo_root) + registry = common.load_binding_registry(reg_path) + registry.setdefault('projects', {}).pop(binding.project_id, None) + common.save_binding_registry(reg_path, registry) + memory_path = common.project_memory_path(binding.repo_root, binding.project_id) + if memory_path.exists(): + memory_path.unlink() + if binding.project_root.exists(): + shutil.rmtree(binding.project_root) + return { + 'project_id': binding.project_id, + 'purged_project_root': str(binding.project_root), + 'removed_memory': str(memory_path), + } + + +def detach_project(binding: common.Binding) -> dict[str, Any]: + entry = update_binding_entry(binding.repo_root, binding.project_id, status='detached', auto_sync=False) + common.update_project_memory( + binding.repo_root, + binding.project_id, + binding.project_root, + entry['hub_note'], + binding.note_language, + summary='project detached; vault content preserved', + ) + return {'project_id': binding.project_id, 'status': 'detached', 'project_root': str(binding.project_root)} + + +def refresh_or_rebuild(repo_root: Path, project_id: str | None, vault_path: str, force: bool) -> dict[str, Any]: + if project_id: + binding = load_binding(repo_root, project_id) + target_vault = Path(vault_path).expanduser().resolve() if vault_path else binding.vault_path + result = common.bootstrap_binding(repo_root, target_vault, project_name=binding.project_slug, force=True, note_language=binding.note_language) + result['rebuild'] = True + return result + target_vault = Path(vault_path or os.environ.get('OBSIDIAN_VAULT_PATH', '')).expanduser() + if not str(target_vault): + raise SystemExit('Rebuild requires --vault-path or OBSIDIAN_VAULT_PATH') + return common.bootstrap_binding(repo_root, target_vault, force=force) + + +def broad_context(binding: common.Binding) -> dict[str, Any]: + daily_path = binding.project_root / 'Daily' / f'{common.today_str()}.md' + payload = { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'hub': str(binding.project_root / '00-Hub.md'), + 'plan': str(binding.project_root / '01-Plan.md'), + 'index': str(binding.project_root / '02-Index.md'), + 'daily': str(daily_path) if daily_path.exists() else '', + } + return payload + + +def query_context(binding: common.Binding, kind: str, query: str) -> dict[str, Any]: + if kind == 'broad': + return broad_context(binding) + candidates = common.search_note_candidates(binding.project_root, kind, query or kind, limit=8) + return { + 'project_id': binding.project_id, + 'kind': kind, + 'query': query, + 'candidates': [str(path) for path in candidates], + } + + +def replace_links_in_text(content: str, old_rel: str, new_rel: str | None) -> str: + if new_rel is not None: + return common.replace_wikilinks(content, old_rel, new_rel) + + old_variants = {old_rel, old_rel[:-3] if old_rel.endswith('.md') else old_rel} + old_title = Path(old_rel).stem.replace('-', ' ') + + def repl(match: Any) -> str: + inner = match.group(1) + target, *rest = inner.split('|', 1) + target_no_heading = target.split('#', 1)[0] + if target_no_heading not in old_variants: + return match.group(0) + if rest: + return rest[0] + return old_title + + import re + return re.sub(r'\[\[([^\]]+)\]\]', repl, content) + + +def rewrite_project_references(project_root: Path, old_rel: str, new_rel: str | None) -> list[str]: + touched: list[str] = [] + for path in sorted(project_root.rglob('*')): + if path.is_dir(): + continue + rel = str(path.relative_to(project_root)).replace(os.sep, '/') + if rel == '02-Index.md' or rel.startswith('_system/'): + continue + if path.suffix == '.md': + before = common.read_text(path) + after = replace_links_in_text(before, old_rel, new_rel) + if after != before: + common.write_text(path, after) + touched.append(str(path)) + elif path.suffix == '.canvas': + before = common.read_text(path) + marker_old = old_rel.replace('\\', '/') + marker_new = '' if new_rel is None else new_rel.replace('\\', '/') + after = before.replace(marker_old, marker_new) if marker_old in before else before + if after != before: + common.write_text(path, after) + touched.append(str(path)) + return touched + + +def ensure_parent(path: Path) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + + +def note_lifecycle(binding: common.Binding, mode: str, note: str, dest: str = '', reason: str = 'manual') -> dict[str, Any]: + source = common.resolve_project_note(binding.project_root, note) + source_rel = str(source.relative_to(binding.project_root)).replace(os.sep, '/') + + if mode == 'rename': + if not dest: + raise SystemExit('--dest is required for rename') + target = (binding.project_root / dest).resolve() + ensure_parent(target) + shutil.move(str(source), str(target)) + target_rel = str(target.relative_to(binding.project_root)).replace(os.sep, '/') + rewritten = rewrite_project_references(binding.project_root, source_rel, target_rel) + common.registry_add_or_update(binding.project_root, target_rel) + common.registry_remove_path(binding.project_root, source_rel, reason='renamed', record_archive=False) + sync_registry(binding.project_root) + common.update_index(binding.project_root) + source_label = Path(source_rel).stem.replace('-', ' ') + target_link = target_rel[:-3] if target_rel.endswith('.md') else target_rel + common.prepend_recent_change(binding.project_root, f'{common.now_iso()}: renamed {source_label} -> [[{target_link}]].') + return {'mode': mode, 'from': source_rel, 'to': target_rel, 'rewritten_paths': rewritten} + + if mode == 'archive': + archived = binding.project_root / 'Archive' / source_rel + ensure_parent(archived) + shutil.move(str(source), str(archived)) + archived_rel = str(archived.relative_to(binding.project_root)).replace(os.sep, '/') + rewritten = rewrite_project_references(binding.project_root, source_rel, archived_rel) + common.registry_archive(binding.project_root, source_rel, archived_rel, reason=reason) + common.update_index(binding.project_root) + common.prepend_recent_change(binding.project_root, f'{common.now_iso()}: archived [[{source_rel[:-3] if source_rel.endswith(".md") else source_rel}]].') + return {'mode': mode, 'from': source_rel, 'to': archived_rel, 'rewritten_paths': rewritten} + + if mode == 'purge': + source.unlink() + rewritten = rewrite_project_references(binding.project_root, source_rel, None) + common.registry_remove_path(binding.project_root, source_rel, reason=reason) + common.update_index(binding.project_root) + common.prepend_recent_change(binding.project_root, f'{common.now_iso()}: purged {source_rel}.') + return {'mode': mode, 'purged': source_rel, 'rewritten_paths': rewritten} + + raise SystemExit(f'Unsupported note lifecycle mode: {mode}') + + +def project_status(binding: common.Binding) -> dict[str, Any]: + rows = common.parse_registry_md(common.registry_path(binding.project_root)) + daily_path = binding.project_root / 'Daily' / f'{common.today_str()}.md' + lint_path = binding.project_root / '_system' / 'lint-report.md' + archived_refs = {row.get('Archived Path', '')[2:-2] for row in rows.get('Archive', []) if row.get('Archived Path', '').startswith('[[')} + active_notes_referencing_archived_notes = 0 + experiments_with_only_archived_results = 0 + for path in sorted(binding.project_root.rglob('*.md')): + rel = str(path.relative_to(binding.project_root)).replace(os.sep, '/') + if rel.startswith('Archive/') or rel.startswith('_system/'): + continue + refs = {match.strip() for match in re.findall(r'\[\[([^\]|#]+)', path.read_text(encoding='utf-8'))} + archived_hits = refs & archived_refs + if archived_hits: + active_notes_referencing_archived_notes += len(archived_hits) + if rel.startswith('Experiments/'): + has_active_result = bool(re.search(r'\[\[(Results/[^\]|#]+)', path.read_text(encoding='utf-8'))) + has_archived_result = bool(re.search(r'\[\[(Archive/Results/[^\]|#]+)', path.read_text(encoding='utf-8'))) + if has_archived_result and not has_active_result: + experiments_with_only_archived_results += 1 + return { + 'project_id': binding.project_id, + 'project_root': str(binding.project_root), + 'status': binding.status, + 'auto_sync': binding.auto_sync, + 'sources': len(rows.get('Sources', [])), + 'knowledge': len(rows.get('Knowledge', [])), + 'experiments': len(rows.get('Experiments', [])), + 'results': len(rows.get('Results', [])), + 'writing': len(rows.get('Writing', [])), + 'maps': len(rows.get('Maps', [])), + 'archive': len(rows.get('Archive', [])), + 'experiments_with_only_archived_results': experiments_with_only_archived_results, + 'active_notes_referencing_archived_notes': active_notes_referencing_archived_notes, + 'daily_note': str(daily_path) if daily_path.exists() else '', + 'lint_report': str(lint_path) if lint_path.exists() else '', + } + + +def main() -> None: + args = parse_args() + repo_root = repo_root_from(getattr(args, 'cwd', '.')) + + if args.command == 'detect': + print(json.dumps(common.detect(repo_root), ensure_ascii=False, indent=2)) + return + + if args.command == 'bootstrap': + vault_arg = args.vault_path or os.environ.get('OBSIDIAN_VAULT_PATH', '') + if not vault_arg: + raise SystemExit('bootstrap requires --vault-path or OBSIDIAN_VAULT_PATH') + result = common.bootstrap_binding( + repo_root, + Path(vault_arg), + project_name=args.project_name or None, + force=args.force, + note_language=args.note_language, + ) + print(json.dumps(result, ensure_ascii=False, indent=2)) + return + + binding = load_binding(repo_root, getattr(args, 'project_id', '') or None) + + if args.command == 'sync': + print(json.dumps(run_sync(binding, scope=args.scope), ensure_ascii=False, indent=2)) + return + + if args.command == 'status': + print(json.dumps(project_status(binding), ensure_ascii=False, indent=2)) + return + + if args.command == 'lifecycle': + if args.mode == 'detach': + result = detach_project(binding) + elif args.mode == 'archive': + result = archive_project(binding) + elif args.mode == 'purge': + result = purge_project(binding) + elif args.mode == 'rebuild': + result = refresh_or_rebuild(repo_root, binding.project_id, args.vault_path, args.force) + else: + raise SystemExit(f'Unsupported lifecycle mode: {args.mode}') + print(json.dumps(result, ensure_ascii=False, indent=2)) + return + + if args.command == 'query-context': + print(json.dumps(query_context(binding, args.kind, args.query), ensure_ascii=False, indent=2)) + return + + if args.command == 'find-canonical-note': + candidates = common.search_note_candidates(binding.project_root, args.kind, args.query, limit=args.limit) + payload = { + 'project_id': binding.project_id, + 'kind': args.kind, + 'query': args.query, + 'candidates': [str(path.relative_to(binding.project_root)).replace(os.sep, '/') for path in candidates], + } + print(json.dumps(payload, ensure_ascii=False, indent=2)) + return + + if args.command == 'note-lifecycle': + print(json.dumps(note_lifecycle(binding, args.mode, args.note, args.dest, args.reason), ensure_ascii=False, indent=2)) + return + + raise SystemExit(f'Unhandled command: {args.command}') + + +if __name__ == '__main__': + main() diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-skills.UPSTREAM-LICENSE.txt b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-skills.UPSTREAM-LICENSE.txt new file mode 100644 index 0000000..33d692e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-skills.UPSTREAM-LICENSE.txt @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2026 Steph Ango (@kepano) + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-skills.UPSTREAM-SOURCE.txt b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-skills.UPSTREAM-SOURCE.txt new file mode 100644 index 0000000..59d4451 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-skills.UPSTREAM-SOURCE.txt @@ -0,0 +1,6 @@ +Upstream repository: https://github.com/kepano/obsidian-skills +Vendored from commit: bb9ec95e1b59c3471bd6fd77a78a4042430bfac3 +License: MIT +Included skills: +- obsidian-kb-artifacts (consolidated from upstream markdown/cli/bases/canvas capabilities) +- defuddle diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/SKILL.md new file mode 100644 index 0000000..0ef429d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/SKILL.md @@ -0,0 +1,33 @@ +--- +name: obsidian-source-ingestion +description: Use this skill to ingest external materials into the current project-scoped Obsidian KB as source notes under Sources/Papers, Sources/Web, Sources/Docs, Sources/Data, Sources/Interviews, or Sources/Notes. +--- + +# Obsidian Source Ingestion + +Use this skill when external material should become a project-local source note. + +## Targets + +- `Sources/Papers/` +- `Sources/Web/` +- `Sources/Docs/` +- `Sources/Data/` +- `Sources/Interviews/` +- `Sources/Notes/` + +## Core rules + +- source notes are source-centered, not synthesis-centered +- every new canonical source note must update `_system/registry.md` +- important sources should update `02-Index.md` +- if the source arrived during an active work session, append a short note to today's `Daily/` +- do not create a top-level `Papers/` + +## Read next + +- `references/SOURCE-TYPES.md` +- `references/PAPER-SOURCE-NOTES.md` +- `references/WEB-SOURCE-NOTES.md` +- `references/DATA-SOURCE-NOTES.md` +- `references/INTERVIEW-SOURCE-NOTES.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/DATA-SOURCE-NOTES.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/DATA-SOURCE-NOTES.md new file mode 100644 index 0000000..3706c7e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/DATA-SOURCE-NOTES.md @@ -0,0 +1,3 @@ +# Data Source Notes + +Data notes should describe schema, metrics, known issues, usage notes, and project relevance. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/INTERVIEW-SOURCE-NOTES.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/INTERVIEW-SOURCE-NOTES.md new file mode 100644 index 0000000..c0084b7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/INTERVIEW-SOURCE-NOTES.md @@ -0,0 +1,3 @@ +# Interview Source Notes + +Interview notes should capture participants, context, key quotes, observed needs, evidence, and follow-ups. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/PAPER-SOURCE-NOTES.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/PAPER-SOURCE-NOTES.md new file mode 100644 index 0000000..0573ebc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/PAPER-SOURCE-NOTES.md @@ -0,0 +1,3 @@ +# Paper Source Notes + +Paper source notes must remain source-centered and should usually include metadata, project relevance, summary, claims, methods, evidence, limitations, connections, and open questions. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/SOURCE-TYPES.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/SOURCE-TYPES.md new file mode 100644 index 0000000..d67e1d4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/SOURCE-TYPES.md @@ -0,0 +1,9 @@ +# Source Types + +Routing defaults: +- paper -> `Sources/Papers/` +- web page or blog -> `Sources/Web/` +- API docs, spec, manual -> `Sources/Docs/` +- dataset, benchmark, schema note -> `Sources/Data/` +- interview or transcript -> `Sources/Interviews/` +- loose imported note or pasted markdown -> `Sources/Notes/` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/WEB-SOURCE-NOTES.md b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/WEB-SOURCE-NOTES.md new file mode 100644 index 0000000..3c4dc85 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/obsidian-source-ingestion/references/WEB-SOURCE-NOTES.md @@ -0,0 +1,3 @@ +# Web Source Notes + +Web source notes should capture URL, source type, summary, extracted claims, evidence snippets, project relevance, and follow-up questions. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/SKILL.md new file mode 100644 index 0000000..e72019b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/SKILL.md @@ -0,0 +1,161 @@ +--- +name: paper-self-review +description: This skill should be used when the user asks to "review paper quality", "check paper completeness", "validate paper structure", "self-review before submission", "audit claims", "check overclaiming", "verify whether results support claims", or mentions systematic paper quality checking. Provides comprehensive quality assurance checklist for academic papers. +version: 0.1.0 +--- + +# Paper Self-Review + +A systematic paper quality checking tool that helps researchers conduct comprehensive self-review before submission. + +## Core Features + +### 1. Structure Review + +Check whether all sections of the paper are complete and conform to academic standards: +- Does the Abstract include problem, method, results, and contributions? +- Does the Introduction clearly articulate research motivation and background? +- Is the Method detailed enough to be reproducible? +- Do the Results sufficiently support the conclusions? +- Does the Discussion address limitations and future work? + +### 2. Logic Consistency Check + +Verify the logical coherence of the paper: +- Do research questions match the methodology? +- Does the experimental design support the research hypotheses? +- Are result interpretations reasonable? +- Are conclusions supported by evidence? + +### 3. Citation Completeness + +Check the completeness and accuracy of citations: +- Are all citations present in the references? +- Is the reference format consistent? +- Are key related works cited? +- Do citations accurately reflect the original content? + +### 4. Research Claim Audit + +Check whether the paper's claims are supported by the available evidence: +- Are the main claims supported by results, citations, or analysis artifacts? +- Are speculative observations clearly marked as tentative? +- Does the paper avoid stronger wording than the evidence allows? +- Are negative results, limitations, and missing baselines presented honestly? +- Do conclusions stay inside the tested scope? + +This audit does not replace `results-analysis` for statistics or `citation-verification` for bibliographic verification. It checks whether paper claims correctly use the available evidence. + +### 5. Figure/Table Quality + +Evaluate the quality and effectiveness of figures and tables: +- Do all figures/tables have clear titles and captions? +- Do figures/tables support the text narrative? +- Are figures/tables clear and readable? +- Do formats comply with journal/conference requirements? + +### 6. Writing Clarity + +Check writing clarity and readability: +- Is the language concise and clear? +- Is technical terminology used appropriately? +- Are sentence structures clear? +- Is paragraph organization logical? + +## Quality Checklist + +Use this checklist for systematic paper self-review: + +``` +Paper Quality Checklist: +- [ ] Abstract includes problem, method, results, contributions +- [ ] Introduction clearly states research motivation +- [ ] Method is reproducible +- [ ] Results support conclusions +- [ ] Main claims are supported by named evidence +- [ ] Over-strong claims are weakened or removed +- [ ] Discussion addresses limitations +- [ ] All figures/tables have captions +- [ ] Citations are complete and accurate +``` + +## When to Use + +Use this skill in the following scenarios: + +- **Pre-submission check** - Final review before submitting to a journal or conference +- **After first draft** - Systematic review after completing the first draft +- **Before advisor review** - Self-check before requesting advisor feedback to improve quality +- **Post-revision verification** - After revising based on reviewer comments, verify all issues are addressed +- **Collaborator review** - Quality check before sending to collaborators + +## Review Process + +Follow these steps for systematic paper review: + +### Step 1: Structure Review +Start with the overall structure, checking if all sections are complete and logically coherent. + +### Step 2: Content Review +Dive into each section, checking content accuracy and completeness. + +### Step 3: Research Claim Audit +Check whether each major claim is supported by the evidence available in the draft, analysis bundle, citations, or project notes. + +Use this output shape: + +```md +## Claim Audit + +Claim: +Verdict: keep | weaken | revise | remove +Evidence used: +Missing evidence: +Overclaim risk: +Suggested wording: +``` + +### Step 4: Citation Check +Verify the completeness and accuracy of all citations. + +### Step 5: Figure/Table Review +Check the quality and captions of all figures and tables. + +### Step 6: Writing Quality +Review language expression and writing clarity. + +### Step 7: Final Checklist +Use the quality checklist for final verification. + +## Best Practices + +### Review Timing +- **Spaced review** - Wait 1-2 days after completing the draft before reviewing to maintain objectivity +- **Multiple rounds** - Conduct multiple review rounds, focusing on different aspects each time +- **Print review** - Print a hard copy for review; issues are easier to spot on paper + +### Review Techniques +- **Reverse reading** - Read from conclusion backwards to check logical coherence +- **Read aloud** - Reading the paper aloud helps identify language issues +- **Reviewer perspective** - Assume you are a reviewer and read critically + +### Common Issues +- Abstract too brief or too verbose +- Introduction lacks clear research question statement +- Method lacks sufficient detail for reproduction +- Results lack statistical significance tests +- Discussion doesn't address research limitations +- Figures/tables lack clear titles and captions +- Inconsistent citation formatting + +## Summary + +The Paper Self-Review skill provides a systematic paper quality checking process, helping researchers identify and resolve issues before submission, improving paper quality and acceptance rates. + + +## Reference Files + +Load only what is needed: +- `references/SECTION-CHECKLIST.md` - section-by-section review questions +- `references/FINAL-VERDICT.md` - how to summarize submission readiness and blocking issues +- `examples/example-self-review.md` - example review output diff --git a/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/examples/example-self-review.md b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/examples/example-self-review.md new file mode 100644 index 0000000..961a9ba --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/examples/example-self-review.md @@ -0,0 +1,13 @@ +# Paper Self-Review Example + +## Verdict +- needs moderate revision + +## Blocking issues +1. Main claim is not tied to a statistical test. +2. Baseline comparison is missing one obvious prior system. +3. Figure 2 caption does not explain the metric. + +## Non-blocking issues +- abstract can quantify the gain more clearly +- discussion should name one concrete limitation diff --git a/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/references/FINAL-VERDICT.md b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/references/FINAL-VERDICT.md new file mode 100644 index 0000000..368f1b4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/references/FINAL-VERDICT.md @@ -0,0 +1,12 @@ +# Final Verdict + +## Verdict buckets +- `ready with minor edits` +- `needs moderate revision` +- `not ready for submission` + +## Always report +- top 3 blocking issues +- top 3 polish issues +- missing evidence or missing citations +- figure/table risks diff --git a/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/references/SECTION-CHECKLIST.md b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/references/SECTION-CHECKLIST.md new file mode 100644 index 0000000..239925d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/paper-self-review/references/SECTION-CHECKLIST.md @@ -0,0 +1,27 @@ +# Section Checklist + +## Abstract +- problem clear +- method identifiable +- main result quantified +- contribution stated + +## Introduction +- research gap explicit +- question or hypothesis visible +- contribution list concrete + +## Method +- enough detail to reproduce +- assumptions named +- key design choices justified + +## Results +- numbers support claims +- uncertainty / significance reported when needed +- baselines and ablations are interpretable + +## Discussion +- limitations named +- failure cases acknowledged +- next-step implications are reasonable diff --git a/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/SKILL.md new file mode 100644 index 0000000..31d8059 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/SKILL.md @@ -0,0 +1,171 @@ +--- +name: planning-with-files +description: Use this by default for non-trivial multi-step work that needs persistent planning, progress tracking, or durable notes on disk. Trigger when a task will likely span multiple tool calls, research steps, verification loops, or enough context that the plan should not live only in transient chat memory. +version: 0.1.0 +--- + +# Planning with Files + +Work like Manus: use persistent markdown files as your working memory on disk. + +This is not just an optional planning style. It should be the default persistence layer for complex Codex work. + +Use it proactively when: + +- the task will likely take more than a few tool calls +- progress needs to be tracked across phases +- findings or evidence must be preserved while working +- the task may branch, pause, or resume later +- relying on chat context alone would be fragile + +## Quick Start + +Before ANY complex task: + +1. **Create `task_plan.md`** in the working directory +2. **Define phases** with checkboxes +3. **Update after each phase** - mark [x] and change status +4. **Read before deciding** - refresh goals in attention window + +## The 3-File Pattern + +For every non-trivial task, create THREE files: + +| File | Purpose | When to Update | +|------|---------|----------------| +| `task_plan.md` | Track phases and progress | After each phase | +| `notes.md` | Store findings and research | During research | +| `[deliverable].md` | Final output | At completion | + +## Core Workflow + +``` +Loop 1: Create task_plan.md with goal and phases +Loop 2: Research → save to notes.md → update task_plan.md +Loop 3: Read notes.md → create deliverable → update task_plan.md +Loop 4: Deliver final output +``` + +### The Loop in Detail + +**Before each major action:** +```bash +Read task_plan.md # Refresh goals in attention window +``` + +**After each phase:** +```bash +Edit task_plan.md # Mark [x], update status +``` + +**When storing information:** +```bash +Write notes.md # Don't stuff context, store in file +``` + +## task_plan.md Template + +Create this file FIRST for any complex task: + +```markdown +# Task Plan: [Brief Description] + +## Goal +[One sentence describing the end state] + +## Phases +- [ ] Phase 1: Plan and setup +- [ ] Phase 2: Research/gather information +- [ ] Phase 3: Execute/build +- [ ] Phase 4: Review and deliver + +## Key Questions +1. [Question to answer] +2. [Question to answer] + +## Decisions Made +- [Decision]: [Rationale] + +## Errors Encountered +- [Error]: [Resolution] + +## Status +**Currently in Phase X** - [What I'm doing now] +``` + +## notes.md Template + +For research and findings: + +```markdown +# Notes: [Topic] + +## Sources + +### Source 1: [Name] +- URL: [link] +- Key points: + - [Finding] + - [Finding] + +## Synthesized Findings + +### [Category] +- [Finding] +- [Finding] +``` + +## Critical Rules + +### 1. ALWAYS Create Plan First +Never start a complex task without `task_plan.md`. This is non-negotiable. + +### 2. Read Before Decide +Before any major decision, read the plan file. This keeps goals in your attention window. + +### 3. Update After Act +After completing any phase, immediately update the plan file: +- Mark completed phases with [x] +- Update the Status section +- Log any errors encountered + +### 4. Store, Don't Stuff +Large outputs go to files, not context. Keep only paths in working memory. + +### 5. Log All Errors +Every error goes in the "Errors Encountered" section. This builds knowledge for future tasks. + +## When to Use This Pattern + +**Use 3-file pattern for:** +- Multi-step tasks (3+ steps) +- Research tasks +- Building/creating something +- Tasks spanning multiple tool calls +- Anything requiring organization + +**Skip for:** +- Simple questions +- Single-file edits +- Quick lookups + +## Anti-Patterns to Avoid + +| Don't | Do Instead | +|-------|------------| +| Use TodoWrite for persistence | Create `task_plan.md` file | +| State goals once and forget | Re-read plan before each decision | +| Hide errors and retry | Log errors to plan file | +| Stuff everything in context | Store large content in files | +| Start executing immediately | Create plan file FIRST | + +## Advanced Patterns + +See [reference.md](reference.md) for: +- Attention manipulation techniques +- Error recovery patterns +- Context optimization from Manus + +See [examples.md](examples.md) for: +- Real task examples +- Complex workflow patterns diff --git a/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/examples.md b/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/examples.md new file mode 100644 index 0000000..51b5f3a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/examples.md @@ -0,0 +1,202 @@ +# Examples: Planning with Files in Action + +## Example 1: Research Task + +**User Request:** "Research the benefits of morning exercise and write a summary" + +### Loop 1: Create Plan +```bash +Write task_plan.md +``` + +```markdown +# Task Plan: Morning Exercise Benefits Research + +## Goal +Create a research summary on the benefits of morning exercise. + +## Phases +- [ ] Phase 1: Create this plan ✓ +- [ ] Phase 2: Search and gather sources +- [ ] Phase 3: Synthesize findings +- [ ] Phase 4: Deliver summary + +## Key Questions +1. What are the physical health benefits? +2. What are the mental health benefits? +3. What scientific studies support this? + +## Status +**Currently in Phase 1** - Creating plan +``` + +### Loop 2: Research +```bash +Read task_plan.md # Refresh goals +WebSearch "morning exercise benefits" +Write notes.md # Store findings +Edit task_plan.md # Mark Phase 2 complete +``` + +### Loop 3: Synthesize +```bash +Read task_plan.md # Refresh goals +Read notes.md # Get findings +Write morning_exercise_summary.md +Edit task_plan.md # Mark Phase 3 complete +``` + +### Loop 4: Deliver +```bash +Read task_plan.md # Verify complete +Deliver morning_exercise_summary.md +``` + +--- + +## Example 2: Bug Fix Task + +**User Request:** "Fix the login bug in the authentication module" + +### task_plan.md +```markdown +# Task Plan: Fix Login Bug + +## Goal +Identify and fix the bug preventing successful login. + +## Phases +- [x] Phase 1: Understand the bug report ✓ +- [x] Phase 2: Locate relevant code ✓ +- [ ] Phase 3: Identify root cause (CURRENT) +- [ ] Phase 4: Implement fix +- [ ] Phase 5: Test and verify + +## Key Questions +1. What error message appears? +2. Which file handles authentication? +3. What changed recently? + +## Decisions Made +- Auth handler is in src/auth/login.ts +- Error occurs in validateToken() function + +## Errors Encountered +- [Initial] TypeError: Cannot read property 'token' of undefined + → Root cause: user object not awaited properly + +## Status +**Currently in Phase 3** - Found root cause, preparing fix +``` + +--- + +## Example 3: Feature Development + +**User Request:** "Add a dark mode toggle to the settings page" + +### The 3-File Pattern in Action + +**task_plan.md:** +```markdown +# Task Plan: Dark Mode Toggle + +## Goal +Add functional dark mode toggle to settings. + +## Phases +- [x] Phase 1: Research existing theme system ✓ +- [x] Phase 2: Design implementation approach ✓ +- [ ] Phase 3: Implement toggle component (CURRENT) +- [ ] Phase 4: Add theme switching logic +- [ ] Phase 5: Test and polish + +## Decisions Made +- Using CSS custom properties for theme +- Storing preference in localStorage +- Toggle component in SettingsPage.tsx + +## Status +**Currently in Phase 3** - Building toggle component +``` + +**notes.md:** +```markdown +# Notes: Dark Mode Implementation + +## Existing Theme System +- Located in: src/styles/theme.ts +- Uses: CSS custom properties +- Current themes: light only + +## Files to Modify +1. src/styles/theme.ts - Add dark theme colors +2. src/components/SettingsPage.tsx - Add toggle +3. src/hooks/useTheme.ts - Create new hook +4. src/App.tsx - Wrap with ThemeProvider + +## Color Decisions +- Dark background: #1a1a2e +- Dark surface: #16213e +- Dark text: #eaeaea +``` + +**dark_mode_implementation.md:** (deliverable) +```markdown +# Dark Mode Implementation + +## Changes Made + +### 1. Added dark theme colors +File: src/styles/theme.ts +... + +### 2. Created useTheme hook +File: src/hooks/useTheme.ts +... +``` + +--- + +## Example 4: Error Recovery Pattern + +When something fails, DON'T hide it: + +### Before (Wrong) +``` +Action: Read config.json +Error: File not found +Action: Read config.json # Silent retry +Action: Read config.json # Another retry +``` + +### After (Correct) +``` +Action: Read config.json +Error: File not found + +# Update task_plan.md: +## Errors Encountered +- config.json not found → Will create default config + +Action: Write config.json (default config) +Action: Read config.json +Success! +``` + +--- + +## The Read-Before-Decide Pattern + +**Always read your plan before major decisions:** + +``` +[Many tool calls have happened...] +[Context is getting long...] +[Original goal might be forgotten...] + +→ Read task_plan.md # This brings goals back into attention! +→ Now make the decision # Goals are fresh in context +``` + +This is why Manus can handle ~50 tool calls without losing track. The plan file acts as a "goal refresh" mechanism. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/reference.md b/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/reference.md new file mode 100644 index 0000000..e575d2b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/planning-with-files/reference.md @@ -0,0 +1,110 @@ +# Reference: Manus Context Engineering Principles + +This skill is based on the context engineering principles from Manus, the AI agent company acquired by Meta for $2 billion in December 2025. + +## The 6 Manus Principles + +### 1. Filesystem as External Memory + +> "Markdown is my 'working memory' on disk." + +**Problem:** Context windows have limits. Stuffing everything in context degrades performance and increases costs. + +**Solution:** Treat the filesystem as unlimited memory: +- Store large content in files +- Keep only paths in context +- Agent can "look up" information when needed +- Compression must be REVERSIBLE + +### 2. Attention Manipulation Through Repetition + +**Problem:** After ~50 tool calls, models forget original goals ("lost in the middle" effect). + +**Solution:** Keep a `task_plan.md` file that gets RE-READ throughout execution: +``` +Start of context: [Original goal - far away, forgotten] +...many tool calls... +End of context: [Recently read task_plan.md - gets ATTENTION!] +``` + +By reading the plan file before each decision, goals appear in the attention window. + +### 3. Keep Failure Traces + +> "Error recovery is one of the clearest signals of TRUE agentic behavior." + +**Problem:** Instinct says hide errors, retry silently. This wastes tokens and loses learning. + +**Solution:** KEEP failed actions in the plan file: +```markdown +## Errors Encountered +- [2025-01-03] FileNotFoundError: config.json not found → Created default config +- [2025-01-03] API timeout → Retried with exponential backoff, succeeded +``` + +The model updates its internal understanding when seeing failures. + +### 4. Avoid Few-Shot Overfitting + +> "Uniformity breeds fragility." + +**Problem:** Repetitive action-observation pairs cause drift and hallucination. + +**Solution:** Introduce controlled variation: +- Vary phrasings slightly +- Don't copy-paste patterns blindly +- Recalibrate on repetitive tasks + +### 5. Stable Prefixes for Cache Optimization + +**Problem:** Agents are input-heavy (100:1 ratio). Every token costs money. + +**Solution:** Structure for cache hits: +- Put static content FIRST +- Append-only context (never modify history) +- Consistent serialization + +### 6. Append-Only Context + +**Problem:** Modifying previous messages invalidates KV-cache. + +**Solution:** NEVER modify previous messages. Always append new information. + +## The Agent Loop + +Manus operates in a continuous loop: + +``` +1. Analyze → 2. Think → 3. Select Tool → 4. Execute → 5. Observe → 6. Iterate → 7. Deliver +``` + +### File Operations in the Loop: + +| Operation | When to Use | +|-----------|-------------| +| `write` | New files or complete rewrites | +| `append` | Adding sections incrementally | +| `edit` | Updating specific parts (checkboxes, status) | +| `read` | Reviewing before decisions | + +## Manus Statistics + +| Metric | Value | +|--------|-------| +| Average tool calls per task | ~50 | +| Input-to-output ratio | 100:1 | +| Acquisition price | $2 billion | +| Time to $100M revenue | 8 months | + +## Key Quotes + +> "If the model improvement is the rising tide, we want Manus to be the boat, not the piling stuck on the seafloor." + +> "For complex tasks, I save notes, code, and findings to files so I can reference them as I work." + +> "I used file.edit to update checkboxes in my plan as I progressed, rather than rewriting the whole file." + +## Source + +Based on Manus's official context engineering documentation: +https://manus.im/de/blog/Context-Engineering-for-AI-Agents-Lessons-from-Building-Manus diff --git a/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/README.md b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/README.md new file mode 100644 index 0000000..3076046 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/README.md @@ -0,0 +1,109 @@ +# Plugin Structure Skill + +Comprehensive guidance on Claude Code plugin architecture, directory layout, and best practices. + +## Overview + +This skill provides detailed knowledge about: +- Plugin directory structure and organization +- `plugin.json` manifest configuration +- Component organization (commands, agents, skills, hooks) +- Auto-discovery mechanisms +- Portable path references with `${CLAUDE_PLUGIN_ROOT}` +- File naming conventions + +## Skill Structure + +### SKILL.md (1,619 words) + +Core skill content covering: +- Directory structure overview +- Plugin manifest (plugin.json) fields +- Component organization patterns +- ${CLAUDE_PLUGIN_ROOT} usage +- File naming conventions +- Auto-discovery mechanism +- Best practices +- Common patterns +- Troubleshooting + +### References + +Detailed documentation for deep dives: + +- **manifest-reference.md**: Complete `plugin.json` field reference + - All field descriptions and examples + - Path resolution rules + - Validation guidelines + - Minimal vs. complete manifest examples + +- **component-patterns.md**: Advanced organization patterns + - Component lifecycle (discovery, activation) + - Command organization patterns + - Agent organization patterns + - Skill organization patterns + - Hook organization patterns + - Script organization patterns + - Cross-component patterns + - Best practices for scalability + +### Examples + +Three complete plugin examples: + +- **minimal-plugin.md**: Simplest possible plugin + - Single command + - Minimal manifest + - When to use this pattern + +- **standard-plugin.md**: Well-structured production plugin + - Multiple components (commands, agents, skills, hooks) + - Complete manifest with metadata + - Rich skill structure + - Integration between components + +- **advanced-plugin.md**: Enterprise-grade plugin + - Multi-level organization + - MCP server integration + - Shared libraries + - Configuration management + - Security automation + - Monitoring integration + +## When This Skill Triggers + +Claude Code activates this skill when users: +- Ask to "create a plugin" or "scaffold a plugin" +- Need to "understand plugin structure" +- Want to "organize plugin components" +- Need to "set up plugin.json" +- Ask about "${CLAUDE_PLUGIN_ROOT}" usage +- Want to "add commands/agents/skills/hooks" +- Need "configure auto-discovery" help +- Ask about plugin architecture or best practices + +## Progressive Disclosure + +The skill uses progressive disclosure to manage context: + +1. **SKILL.md** (~1600 words): Core concepts and workflows +2. **References** (~6000 words): Detailed field references and patterns +3. **Examples** (~8000 words): Complete working examples + +Claude loads references and examples only as needed based on the task. + +## Related Skills + +This skill works well with: +- **hook-development**: For creating plugin hooks +- **mcp-integration**: For integrating MCP servers (when available) +- **marketplace-publishing**: For publishing plugins (when available) + +## Maintenance + +To update this skill: +1. Keep SKILL.md lean and focused on core concepts +2. Move detailed information to references/ +3. Add new examples/ for common patterns +4. Update version in SKILL.md frontmatter +5. Ensure all documentation uses imperative/infinitive form diff --git a/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/SKILL.md new file mode 100644 index 0000000..6bcae94 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/SKILL.md @@ -0,0 +1,476 @@ +--- +name: plugin-structure +description: This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices. +version: 0.1.0 +--- + +# Plugin Structure for Claude Code + +## Overview + +Claude Code plugins follow a standardized directory structure with automatic component discovery. Understanding this structure enables creating well-organized, maintainable plugins that integrate seamlessly with Claude Code. + +**Key concepts:** +- Conventional directory layout for automatic discovery +- Manifest-driven configuration in `.claude-plugin/plugin.json` +- Component-based organization (commands, agents, skills, hooks) +- Portable path references using `${CLAUDE_PLUGIN_ROOT}` +- Explicit vs. auto-discovered component loading + +## Directory Structure + +Every Claude Code plugin follows this organizational pattern: + +``` +plugin-name/ +├── .claude-plugin/ +│ └── plugin.json # Required: Plugin manifest +├── commands/ # Slash commands (.md files) +├── agents/ # Subagent definitions (.md files) +├── skills/ # Agent skills (subdirectories) +│ └── skill-name/ +│ └── SKILL.md # Required for each skill +├── hooks/ +│ └── hooks.json # Event handler configuration +├── .mcp.json # MCP server definitions +└── scripts/ # Helper scripts and utilities +``` + +**Critical rules:** + +1. **Manifest location**: The `plugin.json` manifest MUST be in `.claude-plugin/` directory +2. **Component locations**: All component directories (commands, agents, skills, hooks) MUST be at plugin root level, NOT nested inside `.claude-plugin/` +3. **Optional components**: Only create directories for components the plugin actually uses +4. **Naming convention**: Use kebab-case for all directory and file names + +## Plugin Manifest (plugin.json) + +The manifest defines plugin metadata and configuration. Located at `.claude-plugin/plugin.json`: + +### Required Fields + +```json +{ + "name": "plugin-name" +} +``` + +**Name requirements:** +- Use kebab-case format (lowercase with hyphens) +- Must be unique across installed plugins +- No spaces or special characters +- Example: `code-review-assistant`, `test-runner`, `api-docs` + +### Recommended Metadata + +```json +{ + "name": "plugin-name", + "version": "1.0.0", + "description": "Brief explanation of plugin purpose", + "author": { + "name": "Author Name", + "email": "author@example.com", + "url": "https://example.com" + }, + "homepage": "https://docs.example.com", + "repository": "https://github.com/user/plugin-name", + "license": "MIT", + "keywords": ["testing", "automation", "ci-cd"] +} +``` + +**Version format**: Follow semantic versioning (MAJOR.MINOR.PATCH) +**Keywords**: Use for plugin discovery and categorization + +### Component Path Configuration + +Specify custom paths for components (supplements default directories): + +```json +{ + "name": "plugin-name", + "commands": "./custom-commands", + "agents": ["./agents", "./specialized-agents"], + "hooks": "./config/hooks.json", + "mcpServers": "./.mcp.json" +} +``` + +**Important**: Custom paths supplement defaults—they don't replace them. Components in both default directories and custom paths will load. + +**Path rules:** +- Must be relative to plugin root +- Must start with `./` +- Cannot use absolute paths +- Support arrays for multiple locations + +## Component Organization + +### Commands + +**Location**: `commands/` directory +**Format**: Markdown files with YAML frontmatter +**Auto-discovery**: All `.md` files in `commands/` load automatically + +**Example structure**: +``` +commands/ +├── review.md # /review command +├── test.md # /test command +└── deploy.md # /deploy command +``` + +**File format**: +```markdown +--- +name: command-name +description: Command description +--- + +Command implementation instructions... +``` + +**Usage**: Commands integrate as native slash commands in Claude Code + +### Agents + +**Location**: `agents/` directory +**Format**: Markdown files with YAML frontmatter +**Auto-discovery**: All `.md` files in `agents/` load automatically + +**Example structure**: +``` +agents/ +├── code-reviewer.md +├── test-generator.md +└── refactorer.md +``` + +**File format**: +```markdown +--- +description: Agent role and expertise +capabilities: + - Specific task 1 + - Specific task 2 +--- + +Detailed agent instructions and knowledge... +``` + +**Usage**: Users can invoke agents manually, or Claude Code selects them automatically based on task context + +### Skills + +**Location**: `skills/` directory with subdirectories per skill +**Format**: Each skill in its own directory with `SKILL.md` file +**Auto-discovery**: All `SKILL.md` files in skill subdirectories load automatically + +**Example structure**: +``` +skills/ +├── api-testing/ +│ ├── SKILL.md +│ ├── scripts/ +│ │ └── test-runner.py +│ └── references/ +│ └── api-spec.md +└── database-migrations/ + ├── SKILL.md + └── examples/ + └── migration-template.sql +``` + +**SKILL.md format**: +```markdown +--- +name: Skill Name +description: When to use this skill +version: 1.0.0 +--- + +Skill instructions and guidance... +``` + +**Supporting files**: Skills can include scripts, references, examples, or assets in subdirectories + +**Usage**: Claude Code autonomously activates skills based on task context matching the description + +### Hooks + +**Location**: `hooks/hooks.json` or inline in `plugin.json` +**Format**: JSON configuration defining event handlers +**Registration**: Hooks register automatically when plugin enables + +**Example structure**: +``` +hooks/ +├── hooks.json # Hook configuration +└── scripts/ + ├── validate.sh # Hook script + └── check-style.sh # Hook script +``` + +**Configuration format**: +```json +{ + "PreToolUse": [{ + "matcher": "Write|Edit", + "hooks": [{ + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/validate.sh", + "timeout": 30 + }] + }] +} +``` + +**Available events**: PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification + +**Usage**: Hooks execute automatically in response to Claude Code events + +### MCP Servers + +**Location**: `.mcp.json` at plugin root or inline in `plugin.json` +**Format**: JSON configuration for MCP server definitions +**Auto-start**: Servers start automatically when plugin enables + +**Example format**: +```json +{ + "mcpServers": { + "server-name": { + "command": "node", + "args": ["${CLAUDE_PLUGIN_ROOT}/servers/server.js"], + "env": { + "API_KEY": "${API_KEY}" + } + } + } +} +``` + +**Usage**: MCP servers integrate seamlessly with Claude Code's tool system + +## Portable Path References + +### ${CLAUDE_PLUGIN_ROOT} + +Use `${CLAUDE_PLUGIN_ROOT}` environment variable for all intra-plugin path references: + +```json +{ + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/run.sh" +} +``` + +**Why it matters**: Plugins install in different locations depending on: +- User installation method (marketplace, local, npm) +- Operating system conventions +- User preferences + +**Where to use it**: +- Hook command paths +- MCP server command arguments +- Script execution references +- Resource file paths + +**Never use**: +- Hardcoded absolute paths (`/Users/name/plugins/...`) +- Relative paths from working directory (`./scripts/...` in commands) +- Home directory shortcuts (`~/plugins/...`) + +### Path Resolution Rules + +**In manifest JSON fields** (hooks, MCP servers): +```json +"command": "${CLAUDE_PLUGIN_ROOT}/scripts/tool.sh" +``` + +**In component files** (commands, agents, skills): +```markdown +Reference scripts at: ${CLAUDE_PLUGIN_ROOT}/scripts/helper.py +``` + +**In executed scripts**: +```bash +#!/bin/bash +# ${CLAUDE_PLUGIN_ROOT} available as environment variable +source "${CLAUDE_PLUGIN_ROOT}/lib/common.sh" +``` + +## File Naming Conventions + +### Component Files + +**Commands**: Use kebab-case `.md` files +- `code-review.md` → `/code-review` +- `run-tests.md` → `/run-tests` +- `api-docs.md` → `/api-docs` + +**Agents**: Use kebab-case `.md` files describing role +- `test-generator.md` +- `code-reviewer.md` +- `performance-analyzer.md` + +**Skills**: Use kebab-case directory names +- `api-testing/` +- `database-migrations/` +- `error-handling/` + +### Supporting Files + +**Scripts**: Use descriptive kebab-case names with appropriate extensions +- `validate-input.sh` +- `generate-report.py` +- `process-data.js` + +**Documentation**: Use kebab-case markdown files +- `api-reference.md` +- `migration-guide.md` +- `best-practices.md` + +**Configuration**: Use standard names +- `hooks.json` +- `.mcp.json` +- `plugin.json` + +## Auto-Discovery Mechanism + +Claude Code automatically discovers and loads components: + +1. **Plugin manifest**: Reads `.claude-plugin/plugin.json` when plugin enables +2. **Commands**: Scans `commands/` directory for `.md` files +3. **Agents**: Scans `agents/` directory for `.md` files +4. **Skills**: Scans `skills/` for subdirectories containing `SKILL.md` +5. **Hooks**: Loads configuration from `hooks/hooks.json` or manifest +6. **MCP servers**: Loads configuration from `.mcp.json` or manifest + +**Discovery timing**: +- Plugin installation: Components register with Claude Code +- Plugin enable: Components become available for use +- No restart required: Changes take effect on next Claude Code session + +**Override behavior**: Custom paths in `plugin.json` supplement (not replace) default directories + +## Best Practices + +### Organization + +1. **Logical grouping**: Group related components together + - Put test-related commands, agents, and skills together + - Create subdirectories in `scripts/` for different purposes + +2. **Minimal manifest**: Keep `plugin.json` lean + - Only specify custom paths when necessary + - Rely on auto-discovery for standard layouts + - Use inline configuration only for simple cases + +3. **Documentation**: Include README files + - Plugin root: Overall purpose and usage + - Component directories: Specific guidance + - Script directories: Usage and requirements + +### Naming + +1. **Consistency**: Use consistent naming across components + - If command is `test-runner`, name related agent `test-runner-agent` + - Match skill directory names to their purpose + +2. **Clarity**: Use descriptive names that indicate purpose + - Good: `api-integration-testing/`, `code-quality-checker.md` + - Avoid: `utils/`, `misc.md`, `temp.sh` + +3. **Length**: Balance brevity with clarity + - Commands: 2-3 words (`review-pr`, `run-ci`) + - Agents: Describe role clearly (`code-reviewer`, `test-generator`) + - Skills: Topic-focused (`error-handling`, `api-design`) + +### Portability + +1. **Always use ${CLAUDE_PLUGIN_ROOT}**: Never hardcode paths +2. **Test on multiple systems**: Verify on macOS, Linux, Windows +3. **Document dependencies**: List required tools and versions +4. **Avoid system-specific features**: Use portable bash/Python constructs + +### Maintenance + +1. **Version consistently**: Update version in plugin.json for releases +2. **Deprecate gracefully**: Mark old components clearly before removal +3. **Document breaking changes**: Note changes affecting existing users +4. **Test thoroughly**: Verify all components work after changes + +## Common Patterns + +### Minimal Plugin + +Single command with no dependencies: +``` +my-plugin/ +├── .claude-plugin/ +│ └── plugin.json # Just name field +└── commands/ + └── hello.md # Single command +``` + +### Full-Featured Plugin + +Complete plugin with all component types: +``` +my-plugin/ +├── .claude-plugin/ +│ └── plugin.json +├── commands/ # User-facing commands +├── agents/ # Specialized subagents +├── skills/ # Auto-activating skills +├── hooks/ # Event handlers +│ ├── hooks.json +│ └── scripts/ +├── .mcp.json # External integrations +└── scripts/ # Shared utilities +``` + +### Skill-Focused Plugin + +Plugin providing only skills: +``` +my-plugin/ +├── .claude-plugin/ +│ └── plugin.json +└── skills/ + ├── skill-one/ + │ └── SKILL.md + └── skill-two/ + └── SKILL.md +``` + +## Troubleshooting + +**Component not loading**: +- Verify file is in correct directory with correct extension +- Check YAML frontmatter syntax (commands, agents, skills) +- Ensure skill has `SKILL.md` (not `README.md` or other name) +- Confirm plugin is enabled in Claude Code settings + +**Path resolution errors**: +- Replace all hardcoded paths with `${CLAUDE_PLUGIN_ROOT}` +- Verify paths are relative and start with `./` in manifest +- Check that referenced files exist at specified paths +- Test with `echo $CLAUDE_PLUGIN_ROOT` in hook scripts + +**Auto-discovery not working**: +- Confirm directories are at plugin root (not in `.claude-plugin/`) +- Check file naming follows conventions (kebab-case, correct extensions) +- Verify custom paths in manifest are correct +- Restart Claude Code to reload plugin configuration + +**Conflicts between plugins**: +- Use unique, descriptive component names +- Namespace commands with plugin name if needed +- Document potential conflicts in plugin README +- Consider command prefixes for related functionality + +--- + +For detailed examples and advanced patterns, see files in `references/` and `examples/` directories. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/advanced-plugin.md b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/advanced-plugin.md new file mode 100644 index 0000000..a7c0696 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/advanced-plugin.md @@ -0,0 +1,765 @@ +# Advanced Plugin Example + +A complex, enterprise-grade plugin with MCP integration and advanced organization. + +## Directory Structure + +``` +enterprise-devops/ +├── .claude-plugin/ +│ └── plugin.json +├── commands/ +│ ├── ci/ +│ │ ├── build.md +│ │ ├── test.md +│ │ └── deploy.md +│ ├── monitoring/ +│ │ ├── status.md +│ │ └── logs.md +│ └── admin/ +│ ├── configure.md +│ └── manage.md +├── agents/ +│ ├── orchestration/ +│ │ ├── deployment-orchestrator.md +│ │ └── rollback-manager.md +│ └── specialized/ +│ ├── kubernetes-expert.md +│ ├── terraform-expert.md +│ └── security-auditor.md +├── skills/ +│ ├── kubernetes-ops/ +│ │ ├── SKILL.md +│ │ ├── references/ +│ │ │ ├── deployment-patterns.md +│ │ │ ├── troubleshooting.md +│ │ │ └── security.md +│ │ ├── examples/ +│ │ │ ├── basic-deployment.yaml +│ │ │ ├── stateful-set.yaml +│ │ │ └── ingress-config.yaml +│ │ └── scripts/ +│ │ ├── validate-manifest.sh +│ │ └── health-check.sh +│ ├── terraform-iac/ +│ │ ├── SKILL.md +│ │ ├── references/ +│ │ │ └── best-practices.md +│ │ └── examples/ +│ │ └── module-template/ +│ └── ci-cd-pipelines/ +│ ├── SKILL.md +│ └── references/ +│ └── pipeline-patterns.md +├── hooks/ +│ ├── hooks.json +│ └── scripts/ +│ ├── security/ +│ │ ├── scan-secrets.sh +│ │ ├── validate-permissions.sh +│ │ └── audit-changes.sh +│ ├── quality/ +│ │ ├── check-config.sh +│ │ └── verify-tests.sh +│ └── workflow/ +│ ├── notify-team.sh +│ └── update-status.sh +├── .mcp.json +├── servers/ +│ ├── kubernetes-mcp/ +│ │ ├── index.js +│ │ ├── package.json +│ │ └── lib/ +│ ├── terraform-mcp/ +│ │ ├── main.py +│ │ └── requirements.txt +│ └── github-actions-mcp/ +│ ├── server.js +│ └── package.json +├── lib/ +│ ├── core/ +│ │ ├── logger.js +│ │ ├── config.js +│ │ └── auth.js +│ ├── integrations/ +│ │ ├── slack.js +│ │ ├── pagerduty.js +│ │ └── datadog.js +│ └── utils/ +│ ├── retry.js +│ └── validation.js +└── config/ + ├── environments/ + │ ├── production.json + │ ├── staging.json + │ └── development.json + └── templates/ + ├── deployment.yaml + └── service.yaml +``` + +## File Contents + +### .claude-plugin/plugin.json + +```json +{ + "name": "enterprise-devops", + "version": "2.3.1", + "description": "Comprehensive DevOps automation for enterprise CI/CD pipelines, infrastructure management, and monitoring", + "author": { + "name": "DevOps Platform Team", + "email": "devops-platform@company.com", + "url": "https://company.com/teams/devops" + }, + "homepage": "https://docs.company.com/plugins/devops", + "repository": { + "type": "git", + "url": "https://github.com/company/devops-plugin.git" + }, + "license": "Apache-2.0", + "keywords": [ + "devops", + "ci-cd", + "kubernetes", + "terraform", + "automation", + "infrastructure", + "deployment", + "monitoring" + ], + "commands": [ + "./commands/ci", + "./commands/monitoring", + "./commands/admin" + ], + "agents": [ + "./agents/orchestration", + "./agents/specialized" + ], + "hooks": "./hooks/hooks.json", + "mcpServers": "./.mcp.json" +} +``` + +### .mcp.json + +```json +{ + "mcpServers": { + "kubernetes": { + "command": "node", + "args": ["${CLAUDE_PLUGIN_ROOT}/servers/kubernetes-mcp/index.js"], + "env": { + "KUBECONFIG": "${KUBECONFIG}", + "K8S_NAMESPACE": "${K8S_NAMESPACE:-default}" + } + }, + "terraform": { + "command": "python", + "args": ["${CLAUDE_PLUGIN_ROOT}/servers/terraform-mcp/main.py"], + "env": { + "TF_STATE_BUCKET": "${TF_STATE_BUCKET}", + "AWS_REGION": "${AWS_REGION}" + } + }, + "github-actions": { + "command": "node", + "args": ["${CLAUDE_PLUGIN_ROOT}/servers/github-actions-mcp/server.js"], + "env": { + "GITHUB_TOKEN": "${GITHUB_TOKEN}", + "GITHUB_ORG": "${GITHUB_ORG}" + } + } + } +} +``` + +### commands/ci/build.md + +```markdown +--- +name: build +description: Trigger and monitor CI build pipeline +--- + +# Build Command + +Trigger CI/CD build pipeline and monitor progress in real-time. + +## Process + +1. **Validation**: Check prerequisites + - Verify branch status + - Check for uncommitted changes + - Validate configuration files + +2. **Trigger**: Start build via MCP server + \`\`\`javascript + // Uses github-actions MCP server + const build = await tools.github_actions_trigger_workflow({ + workflow: 'build.yml', + ref: currentBranch + }) + \`\`\` + +3. **Monitor**: Track build progress + - Display real-time logs + - Show test results as they complete + - Alert on failures + +4. **Report**: Summarize results + - Build status + - Test coverage + - Performance metrics + - Deploy readiness + +## Integration + +After successful build: +- Offer to deploy to staging +- Suggest performance optimizations +- Generate deployment checklist +``` + +### agents/orchestration/deployment-orchestrator.md + +```markdown +--- +description: Orchestrates complex multi-environment deployments with rollback capabilities and health monitoring +capabilities: + - Plan and execute multi-stage deployments + - Coordinate service dependencies + - Monitor deployment health + - Execute automated rollbacks + - Manage deployment approvals +--- + +# Deployment Orchestrator Agent + +Specialized agent for orchestrating complex deployments across multiple environments. + +## Expertise + +- **Deployment strategies**: Blue-green, canary, rolling updates +- **Dependency management**: Service startup ordering, dependency injection +- **Health monitoring**: Service health checks, metric validation +- **Rollback automation**: Automatic rollback on failure detection +- **Approval workflows**: Multi-stage approval processes + +## Orchestration Process + +1. **Planning Phase** + - Analyze deployment requirements + - Identify service dependencies + - Generate deployment plan + - Calculate rollback strategy + +2. **Validation Phase** + - Verify environment readiness + - Check resource availability + - Validate configurations + - Run pre-deployment tests + +3. **Execution Phase** + - Deploy services in dependency order + - Monitor health after each stage + - Validate metrics and logs + - Proceed to next stage on success + +4. **Verification Phase** + - Run smoke tests + - Validate service integration + - Check performance metrics + - Confirm deployment success + +5. **Rollback Phase** (if needed) + - Detect failure conditions + - Execute rollback plan + - Restore previous state + - Notify stakeholders + +## MCP Integration + +Uses multiple MCP servers: +- `kubernetes`: Deploy and manage containers +- `terraform`: Provision infrastructure +- `github-actions`: Trigger deployment pipelines + +## Monitoring Integration + +Integrates with monitoring tools via lib: +\`\`\`javascript +const { DatadogClient } = require('${CLAUDE_PLUGIN_ROOT}/lib/integrations/datadog') +const metrics = await DatadogClient.getMetrics(service, timeRange) +\`\`\` + +## Notification Integration + +Sends updates via Slack and PagerDuty: +\`\`\`javascript +const { SlackClient } = require('${CLAUDE_PLUGIN_ROOT}/lib/integrations/slack') +await SlackClient.notify({ + channel: '#deployments', + message: 'Deployment started', + metadata: deploymentPlan +}) +\`\`\` +``` + +### skills/kubernetes-ops/SKILL.md + +```markdown +--- +name: Kubernetes Operations +description: This skill should be used when deploying to Kubernetes, managing K8s resources, troubleshooting cluster issues, configuring ingress/services, scaling deployments, or working with Kubernetes manifests. Provides comprehensive Kubernetes operational knowledge and best practices. +version: 2.0.0 +--- + +# Kubernetes Operations + +Comprehensive operational knowledge for managing Kubernetes clusters and workloads. + +## Overview + +Manage Kubernetes infrastructure effectively through: +- Deployment strategies and patterns +- Resource configuration and optimization +- Troubleshooting and debugging +- Security best practices +- Performance tuning + +## Core Concepts + +### Resource Management + +**Deployments**: Use for stateless applications +- Rolling updates for zero-downtime deployments +- Rollback capabilities for failed deployments +- Replica management for scaling + +**StatefulSets**: Use for stateful applications +- Stable network identities +- Persistent storage +- Ordered deployment and scaling + +**DaemonSets**: Use for node-level services +- Log collectors +- Monitoring agents +- Network plugins + +### Configuration + +**ConfigMaps**: Store non-sensitive configuration +- Environment-specific settings +- Application configuration files +- Feature flags + +**Secrets**: Store sensitive data +- API keys and tokens +- Database credentials +- TLS certificates + +Use external secret management (Vault, AWS Secrets Manager) for production. + +### Networking + +**Services**: Expose applications internally +- ClusterIP for internal communication +- NodePort for external access (non-production) +- LoadBalancer for external access (production) + +**Ingress**: HTTP/HTTPS routing +- Path-based routing +- Host-based routing +- TLS termination +- Load balancing + +## Deployment Strategies + +### Rolling Update + +Default strategy, gradual replacement: +\`\`\`yaml +strategy: + type: RollingUpdate + rollingUpdate: + maxSurge: 1 + maxUnavailable: 0 +\`\`\` + +**When to use**: Standard deployments, minor updates + +### Recreate + +Stop all pods, then create new ones: +\`\`\`yaml +strategy: + type: Recreate +\`\`\` + +**When to use**: Stateful apps that can't run multiple versions + +### Blue-Green + +Run two complete environments, switch traffic: +1. Deploy new version (green) +2. Test green environment +3. Switch traffic to green +4. Keep blue for quick rollback + +**When to use**: Critical services, need instant rollback + +### Canary + +Gradually roll out to subset of users: +1. Deploy canary version (10% traffic) +2. Monitor metrics and errors +3. Increase traffic gradually +4. Complete rollout or rollback + +**When to use**: High-risk changes, want gradual validation + +## Resource Configuration + +### Resource Requests and Limits + +Always set for production workloads: +\`\`\`yaml +resources: + requests: + memory: "256Mi" + cpu: "250m" + limits: + memory: "512Mi" + cpu: "500m" +\`\`\` + +**Requests**: Guaranteed resources +**Limits**: Maximum allowed resources + +### Health Checks + +Essential for reliability: +\`\`\`yaml +livenessProbe: + httpGet: + path: /health + port: 8080 + initialDelaySeconds: 30 + periodSeconds: 10 + +readinessProbe: + httpGet: + path: /ready + port: 8080 + initialDelaySeconds: 5 + periodSeconds: 5 +\`\`\` + +**Liveness**: Restart unhealthy pods +**Readiness**: Remove unready pods from service + +## Troubleshooting + +### Common Issues + +1. **Pods not starting** + - Check: `kubectl describe pod <name>` + - Look for: Image pull errors, resource constraints + - Fix: Verify image name, increase resources + +2. **Service not reachable** + - Check: `kubectl get svc`, `kubectl get endpoints` + - Look for: No endpoints, wrong selector + - Fix: Verify pod labels match service selector + +3. **High memory usage** + - Check: `kubectl top pods` + - Look for: Pods near memory limit + - Fix: Increase limits, optimize application + +4. **Frequent restarts** + - Check: `kubectl get pods`, `kubectl logs <name>` + - Look for: Liveness probe failures, OOMKilled + - Fix: Adjust health checks, increase memory + +### Debugging Commands + +Get pod details: +\`\`\`bash +kubectl describe pod <name> +kubectl logs <name> +kubectl logs <name> --previous # logs from crashed container +\`\`\` + +Execute commands in pod: +\`\`\`bash +kubectl exec -it <name> -- /bin/sh +kubectl exec <name> -- env +\`\`\` + +Check resource usage: +\`\`\`bash +kubectl top nodes +kubectl top pods +\`\`\` + +## Security Best Practices + +### Pod Security + +- Run as non-root user +- Use read-only root filesystem +- Drop unnecessary capabilities +- Use security contexts + +Example: +\`\`\`yaml +securityContext: + runAsNonRoot: true + runAsUser: 1000 + readOnlyRootFilesystem: true + capabilities: + drop: + - ALL +\`\`\` + +### Network Policies + +Restrict pod communication: +\`\`\`yaml +apiVersion: networking.k8s.io/v1 +kind: NetworkPolicy +metadata: + name: api-allow +spec: + podSelector: + matchLabels: + app: api + ingress: + - from: + - podSelector: + matchLabels: + app: frontend +\`\`\` + +### Secrets Management + +- Never commit secrets to git +- Use external secret managers +- Rotate secrets regularly +- Limit secret access with RBAC + +## Performance Optimization + +### Resource Tuning + +1. **Start conservative**: Set low limits initially +2. **Monitor usage**: Track actual resource consumption +3. **Adjust gradually**: Increase based on metrics +4. **Set appropriate requests**: Match typical usage +5. **Set safe limits**: 2x requests for headroom + +### Horizontal Pod Autoscaling + +Automatically scale based on metrics: +\`\`\`yaml +apiVersion: autoscaling/v2 +kind: HorizontalPodAutoscaler +metadata: + name: api-hpa +spec: + scaleTargetRef: + apiVersion: apps/v1 + kind: Deployment + name: api + minReplicas: 2 + maxReplicas: 10 + metrics: + - type: Resource + resource: + name: cpu + target: + type: Utilization + averageUtilization: 70 +\`\`\` + +## MCP Server Integration + +This skill works with the kubernetes MCP server for operations: + +**List pods**: +\`\`\`javascript +const pods = await tools.k8s_list_pods({ namespace: 'default' }) +\`\`\` + +**Get pod logs**: +\`\`\`javascript +const logs = await tools.k8s_get_logs({ pod: 'api-xyz', container: 'app' }) +\`\`\` + +**Apply manifests**: +\`\`\`javascript +const result = await tools.k8s_apply_manifest({ file: 'deployment.yaml' }) +\`\`\` + +## Detailed References + +For in-depth information: +- **Deployment patterns**: `references/deployment-patterns.md` +- **Troubleshooting guide**: `references/troubleshooting.md` +- **Security hardening**: `references/security.md` + +## Example Manifests + +For copy-paste examples: +- **Basic deployment**: `examples/basic-deployment.yaml` +- **StatefulSet**: `examples/stateful-set.yaml` +- **Ingress config**: `examples/ingress-config.yaml` + +## Validation Scripts + +For manifest validation: +\`\`\`bash +bash ${CLAUDE_PLUGIN_ROOT}/skills/kubernetes-ops/scripts/validate-manifest.sh deployment.yaml +\`\`\` +``` + +### hooks/hooks.json + +```json +{ + "PreToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/security/scan-secrets.sh", + "timeout": 30 + } + ] + }, + { + "matcher": "Bash", + "hooks": [ + { + "type": "prompt", + "prompt": "Evaluate if this bash command is safe for production environment. Check for destructive operations, missing safeguards, and potential security issues. Commands should be idempotent and reversible.", + "timeout": 20 + } + ] + } + ], + "PostToolUse": [ + { + "matcher": "Bash", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/workflow/update-status.sh", + "timeout": 15 + } + ] + } + ], + "Stop": [ + { + "matcher": ".*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/quality/check-config.sh", + "timeout": 45 + }, + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/workflow/notify-team.sh", + "timeout": 30 + } + ] + } + ], + "SessionStart": [ + { + "matcher": ".*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/security/validate-permissions.sh", + "timeout": 20 + } + ] + } + ] +} +``` + +## Key Features + +### Multi-Level Organization + +**Commands**: Organized by function (CI, monitoring, admin) +**Agents**: Separated by role (orchestration vs. specialized) +**Skills**: Rich resources (references, examples, scripts) + +### MCP Integration + +Three custom MCP servers: +- **Kubernetes**: Cluster operations +- **Terraform**: Infrastructure provisioning +- **GitHub Actions**: CI/CD automation + +### Shared Libraries + +Reusable code in `lib/`: +- **Core**: Common utilities (logging, config, auth) +- **Integrations**: External services (Slack, Datadog) +- **Utils**: Helper functions (retry, validation) + +### Configuration Management + +Environment-specific configs in `config/`: +- **Environments**: Per-environment settings +- **Templates**: Reusable deployment templates + +### Security Automation + +Multiple security hooks: +- Secret scanning before writes +- Permission validation on session start +- Configuration auditing on completion + +### Monitoring Integration + +Built-in monitoring via lib integrations: +- Datadog for metrics +- PagerDuty for alerts +- Slack for notifications + +## Use Cases + +1. **Multi-environment deployments**: Orchestrated rollouts across dev/staging/prod +2. **Infrastructure as code**: Terraform automation with state management +3. **CI/CD automation**: Build, test, deploy pipelines +4. **Monitoring and observability**: Integrated metrics and alerting +5. **Security enforcement**: Automated security scanning and validation +6. **Team collaboration**: Slack notifications and status updates + +## When to Use This Pattern + +- Large-scale enterprise deployments +- Multiple environment management +- Complex CI/CD workflows +- Integrated monitoring requirements +- Security-critical infrastructure +- Team collaboration needs + +## Scaling Considerations + +- **Performance**: Separate MCP servers for parallel operations +- **Organization**: Multi-level directories for scalability +- **Maintainability**: Shared libraries reduce duplication +- **Flexibility**: Environment configs enable customization +- **Security**: Layered security hooks and validation diff --git a/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/minimal-plugin.md b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/minimal-plugin.md new file mode 100644 index 0000000..27591db --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/minimal-plugin.md @@ -0,0 +1,83 @@ +# Minimal Plugin Example + +A bare-bones plugin with a single command. + +## Directory Structure + +``` +hello-world/ +├── .claude-plugin/ +│ └── plugin.json +└── commands/ + └── hello.md +``` + +## File Contents + +### .claude-plugin/plugin.json + +```json +{ + "name": "hello-world" +} +``` + +### commands/hello.md + +```markdown +--- +name: hello +description: Prints a friendly greeting message +--- + +# Hello Command + +Print a friendly greeting to the user. + +## Implementation + +Output the following message to the user: + +> Hello! This is a simple command from the hello-world plugin. +> +> Use this as a starting point for building more complex plugins. + +Include the current timestamp in the greeting to show the command executed successfully. +``` + +## Usage + +After installing the plugin: + +``` +$ claude +> /hello +Hello! This is a simple command from the hello-world plugin. + +Use this as a starting point for building more complex plugins. + +Executed at: 2025-01-15 14:30:22 UTC +``` + +## Key Points + +1. **Minimal manifest**: Only the required `name` field +2. **Single command**: One markdown file in `commands/` directory +3. **Auto-discovery**: Claude Code finds the command automatically +4. **No dependencies**: No scripts, hooks, or external resources + +## When to Use This Pattern + +- Quick prototypes +- Single-purpose utilities +- Learning plugin development +- Internal team tools with one specific function + +## Extending This Plugin + +To add more functionality: + +1. **Add commands**: Create more `.md` files in `commands/` +2. **Add metadata**: Update `plugin.json` with version, description, author +3. **Add agents**: Create `agents/` directory with agent definitions +4. **Add hooks**: Create `hooks/hooks.json` for event handling diff --git a/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/standard-plugin.md b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/standard-plugin.md new file mode 100644 index 0000000..d903166 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/examples/standard-plugin.md @@ -0,0 +1,587 @@ +# Standard Plugin Example + +A well-structured plugin with commands, agents, and skills. + +## Directory Structure + +``` +code-quality/ +├── .claude-plugin/ +│ └── plugin.json +├── commands/ +│ ├── lint.md +│ ├── test.md +│ └── review.md +├── agents/ +│ ├── code-reviewer.md +│ └── test-generator.md +├── skills/ +│ ├── code-standards/ +│ │ ├── SKILL.md +│ │ └── references/ +│ │ └── style-guide.md +│ └── testing-patterns/ +│ ├── SKILL.md +│ └── examples/ +│ ├── unit-test.js +│ └── integration-test.js +├── hooks/ +│ ├── hooks.json +│ └── scripts/ +│ └── validate-commit.sh +└── scripts/ + ├── run-linter.sh + └── generate-report.py +``` + +## File Contents + +### .claude-plugin/plugin.json + +```json +{ + "name": "code-quality", + "version": "1.0.0", + "description": "Comprehensive code quality tools including linting, testing, and review automation", + "author": { + "name": "Quality Team", + "email": "quality@example.com" + }, + "homepage": "https://docs.example.com/plugins/code-quality", + "repository": "https://github.com/example/code-quality-plugin", + "license": "MIT", + "keywords": ["code-quality", "linting", "testing", "code-review", "automation"] +} +``` + +### commands/lint.md + +```markdown +--- +name: lint +description: Run linting checks on the codebase +--- + +# Lint Command + +Run comprehensive linting checks on the project codebase. + +## Process + +1. Detect project type and installed linters +2. Run appropriate linters (ESLint, Pylint, RuboCop, etc.) +3. Collect and format results +4. Report issues with file locations and severity + +## Implementation + +Execute the linting script: + +\`\`\`bash +bash ${CLAUDE_PLUGIN_ROOT}/scripts/run-linter.sh +\`\`\` + +Parse the output and present issues organized by: +- Critical issues (must fix) +- Warnings (should fix) +- Style suggestions (optional) + +For each issue, show: +- File path and line number +- Issue description +- Suggested fix (if available) +``` + +### commands/test.md + +```markdown +--- +name: test +description: Run test suite with coverage reporting +--- + +# Test Command + +Execute the project test suite and generate coverage reports. + +## Process + +1. Identify test framework (Jest, pytest, RSpec, etc.) +2. Run all tests +3. Generate coverage report +4. Identify untested code + +## Output + +Present results in structured format: +- Test summary (passed/failed/skipped) +- Coverage percentage by file +- Critical untested areas +- Failed test details + +## Integration + +After test completion, offer to: +- Fix failing tests +- Generate tests for untested code (using test-generator agent) +- Update documentation based on test changes +``` + +### agents/code-reviewer.md + +```markdown +--- +description: Expert code reviewer specializing in identifying bugs, security issues, and improvement opportunities +capabilities: + - Analyze code for potential bugs and logic errors + - Identify security vulnerabilities + - Suggest performance improvements + - Ensure code follows project standards + - Review test coverage adequacy +--- + +# Code Reviewer Agent + +Specialized agent for comprehensive code review. + +## Expertise + +- **Bug detection**: Logic errors, edge cases, error handling +- **Security analysis**: Injection vulnerabilities, authentication issues, data exposure +- **Performance**: Algorithm efficiency, resource usage, optimization opportunities +- **Standards compliance**: Style guide adherence, naming conventions, documentation +- **Test coverage**: Adequacy of test cases, missing scenarios + +## Review Process + +1. **Initial scan**: Quick pass for obvious issues +2. **Deep analysis**: Line-by-line review of changed code +3. **Context evaluation**: Check impact on related code +4. **Best practices**: Compare against project and language standards +5. **Recommendations**: Prioritized list of improvements + +## Integration with Skills + +Automatically loads `code-standards` skill for project-specific guidelines. + +## Output Format + +For each file reviewed: +- Overall assessment +- Critical issues (must fix before merge) +- Important issues (should fix) +- Suggestions (nice to have) +- Positive feedback (what was done well) +``` + +### agents/test-generator.md + +```markdown +--- +description: Generates comprehensive test suites from code analysis +capabilities: + - Analyze code structure and logic flow + - Generate unit tests for functions and methods + - Create integration tests for modules + - Design edge case and error condition tests + - Suggest test fixtures and mocks +--- + +# Test Generator Agent + +Specialized agent for generating comprehensive test suites. + +## Expertise + +- **Unit testing**: Individual function/method tests +- **Integration testing**: Module interaction tests +- **Edge cases**: Boundary conditions, error paths +- **Test organization**: Proper test structure and naming +- **Mocking**: Appropriate use of mocks and stubs + +## Generation Process + +1. **Code analysis**: Understand function purpose and logic +2. **Path identification**: Map all execution paths +3. **Input design**: Create test inputs covering all paths +4. **Assertion design**: Define expected outputs +5. **Test generation**: Write tests in project's framework + +## Integration with Skills + +Automatically loads `testing-patterns` skill for project-specific test conventions. + +## Test Quality + +Generated tests include: +- Happy path scenarios +- Edge cases and boundary conditions +- Error handling verification +- Mock data for external dependencies +- Clear test descriptions +``` + +### skills/code-standards/SKILL.md + +```markdown +--- +name: Code Standards +description: This skill should be used when reviewing code, enforcing style guidelines, checking naming conventions, or ensuring code quality standards. Provides project-specific coding standards and best practices. +version: 1.0.0 +--- + +# Code Standards + +Comprehensive coding standards and best practices for maintaining code quality. + +## Overview + +Enforce consistent code quality through standardized conventions for: +- Code style and formatting +- Naming conventions +- Documentation requirements +- Error handling patterns +- Security practices + +## Style Guidelines + +### Formatting + +- **Indentation**: 2 spaces (JavaScript/TypeScript), 4 spaces (Python) +- **Line length**: Maximum 100 characters +- **Braces**: Same line for opening brace (K&R style) +- **Whitespace**: Space after commas, around operators + +### Naming Conventions + +- **Variables**: camelCase for JavaScript, snake_case for Python +- **Functions**: camelCase, descriptive verb-noun pairs +- **Classes**: PascalCase +- **Constants**: UPPER_SNAKE_CASE +- **Files**: kebab-case for modules + +## Documentation Requirements + +### Function Documentation + +Every function must include: +- Purpose description +- Parameter descriptions with types +- Return value description with type +- Example usage (for public functions) + +### Module Documentation + +Every module must include: +- Module purpose +- Public API overview +- Usage examples +- Dependencies + +## Error Handling + +### Required Practices + +- Never swallow errors silently +- Always log errors with context +- Use specific error types +- Provide actionable error messages +- Clean up resources in finally blocks + +### Example Pattern + +\`\`\`javascript +async function processData(data) { + try { + const result = await transform(data) + return result + } catch (error) { + logger.error('Data processing failed', { + data: sanitize(data), + error: error.message, + stack: error.stack + }) + throw new DataProcessingError('Failed to process data', { cause: error }) + } +} +\`\`\` + +## Security Practices + +- Validate all external input +- Sanitize data before output +- Use parameterized queries +- Never log sensitive information +- Keep dependencies updated + +## Detailed Guidelines + +For comprehensive style guides by language, see: +- `references/style-guide.md` +``` + +### skills/code-standards/references/style-guide.md + +```markdown +# Comprehensive Style Guide + +Detailed style guidelines for all supported languages. + +## JavaScript/TypeScript + +### Variable Declarations + +Use `const` by default, `let` when reassignment needed, never `var`: + +\`\`\`javascript +// Good +const MAX_RETRIES = 3 +let currentTry = 0 + +// Bad +var MAX_RETRIES = 3 +\`\`\` + +### Function Declarations + +Use function expressions for consistency: + +\`\`\`javascript +// Good +const calculateTotal = (items) => { + return items.reduce((sum, item) => sum + item.price, 0) +} + +// Bad (inconsistent style) +function calculateTotal(items) { + return items.reduce((sum, item) => sum + item.price, 0) +} +\`\`\` + +### Async/Await + +Prefer async/await over promise chains: + +\`\`\`javascript +// Good +async function fetchUserData(userId) { + const user = await db.getUser(userId) + const orders = await db.getOrders(user.id) + return { user, orders } +} + +// Bad +function fetchUserData(userId) { + return db.getUser(userId) + .then(user => db.getOrders(user.id) + .then(orders => ({ user, orders }))) +} +\`\`\` + +## Python + +### Import Organization + +Order imports: standard library, third-party, local: + +\`\`\`python +# Good +import os +import sys + +import numpy as np +import pandas as pd + +from app.models import User +from app.utils import helper + +# Bad - mixed order +from app.models import User +import numpy as np +import os +\`\`\` + +### Type Hints + +Use type hints for all function signatures: + +\`\`\`python +# Good +def calculate_average(numbers: list[float]) -> float: + return sum(numbers) / len(numbers) + +# Bad +def calculate_average(numbers): + return sum(numbers) / len(numbers) +\`\`\` + +## Additional Languages + +See language-specific guides for: +- Go: `references/go-style.md` +- Rust: `references/rust-style.md` +- Ruby: `references/ruby-style.md` +``` + +### hooks/hooks.json + +```json +{ + "PreToolUse": [ + { + "matcher": "Write|Edit", + "hooks": [ + { + "type": "prompt", + "prompt": "Before modifying code, verify it meets our coding standards from the code-standards skill. Check formatting, naming conventions, and documentation. If standards aren't met, suggest improvements.", + "timeout": 30 + } + ] + } + ], + "Stop": [ + { + "matcher": ".*", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/validate-commit.sh", + "timeout": 45 + } + ] + } + ] +} +``` + +### hooks/scripts/validate-commit.sh + +```bash +#!/bin/bash +# Validate code quality before task completion + +set -e + +# Check if there are any uncommitted changes +if [[ -z $(git status -s) ]]; then + echo '{"systemMessage": "No changes to validate. Task complete."}' + exit 0 +fi + +# Run linter on changed files +CHANGED_FILES=$(git diff --name-only --cached | grep -E '\.(js|ts|py)$' || true) + +if [[ -z "$CHANGED_FILES" ]]; then + echo '{"systemMessage": "No code files changed. Validation passed."}' + exit 0 +fi + +# Run appropriate linters +ISSUES=0 + +for file in $CHANGED_FILES; do + case "$file" in + *.js|*.ts) + if ! npx eslint "$file" --quiet; then + ISSUES=$((ISSUES + 1)) + fi + ;; + *.py) + if ! python -m pylint "$file" --errors-only; then + ISSUES=$((ISSUES + 1)) + fi + ;; + esac +done + +if [[ $ISSUES -gt 0 ]]; then + echo "{\"systemMessage\": \"Found $ISSUES code quality issues. Please fix before completing.\"}" + exit 1 +fi + +echo '{"systemMessage": "Code quality checks passed. Ready to commit."}' +exit 0 +``` + +## Usage Examples + +### Running Commands + +``` +$ claude +> /lint +Running linter checks... + +Critical Issues (2): + src/api/users.js:45 - SQL injection vulnerability + src/utils/helpers.js:12 - Unhandled promise rejection + +Warnings (5): + src/components/Button.tsx:23 - Missing PropTypes + ... + +Style Suggestions (8): + src/index.js:1 - Use const instead of let + ... + +> /test +Running test suite... + +Test Results: + ✓ 245 passed + ✗ 3 failed + ○ 2 skipped + +Coverage: 87.3% + +Untested Files: + src/utils/cache.js - 0% coverage + src/api/webhooks.js - 23% coverage + +Failed Tests: + 1. User API › GET /users › should handle pagination + Expected 200, received 500 + ... +``` + +### Using Agents + +``` +> Review the changes in src/api/users.js + +[code-reviewer agent selected automatically] + +Code Review: src/api/users.js + +Critical Issues: + 1. Line 45: SQL injection vulnerability + - Using string concatenation for SQL query + - Replace with parameterized query + - Priority: CRITICAL + + 2. Line 67: Missing error handling + - Database query without try/catch + - Could crash server on DB error + - Priority: HIGH + +Suggestions: + 1. Line 23: Consider caching user data + - Frequent DB queries for same users + - Add Redis caching layer + - Priority: MEDIUM +``` + +## Key Points + +1. **Complete manifest**: All recommended metadata fields +2. **Multiple components**: Commands, agents, skills, hooks +3. **Rich skills**: References and examples for detailed information +4. **Automation**: Hooks enforce standards automatically +5. **Integration**: Components work together cohesively + +## When to Use This Pattern + +- Production plugins for distribution +- Team collaboration tools +- Plugins requiring consistency enforcement +- Complex workflows with multiple entry points diff --git a/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/references/component-patterns.md b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/references/component-patterns.md new file mode 100644 index 0000000..a58a7b4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/references/component-patterns.md @@ -0,0 +1,567 @@ +# Component Organization Patterns + +Advanced patterns for organizing plugin components effectively. + +## Component Lifecycle + +### Discovery Phase + +When Claude Code starts: + +1. **Scan enabled plugins**: Read `.claude-plugin/plugin.json` for each +2. **Discover components**: Look in default and custom paths +3. **Parse definitions**: Read YAML frontmatter and configurations +4. **Register components**: Make available to Claude Code +5. **Initialize**: Start MCP servers, register hooks + +**Timing**: Component registration happens during Claude Code initialization, not continuously. + +### Activation Phase + +When components are used: + +**Commands**: User types slash command → Claude Code looks up → Executes +**Agents**: Task arrives → Claude Code evaluates capabilities → Selects agent +**Skills**: Task context matches description → Claude Code loads skill +**Hooks**: Event occurs → Claude Code calls matching hooks +**MCP Servers**: Tool call matches server capability → Forwards to server + +## Command Organization Patterns + +### Flat Structure + +Single directory with all commands: + +``` +commands/ +├── build.md +├── test.md +├── deploy.md +├── review.md +└── docs.md +``` + +**When to use**: +- 5-15 commands total +- All commands at same abstraction level +- No clear categorization + +**Advantages**: +- Simple, easy to navigate +- No configuration needed +- Fast discovery + +### Categorized Structure + +Multiple directories for different command types: + +``` +commands/ # Core commands +├── build.md +└── test.md + +admin-commands/ # Administrative +├── configure.md +└── manage.md + +workflow-commands/ # Workflow automation +├── review.md +└── deploy.md +``` + +**Manifest configuration**: +```json +{ + "commands": [ + "./commands", + "./admin-commands", + "./workflow-commands" + ] +} +``` + +**When to use**: +- 15+ commands +- Clear functional categories +- Different permission levels + +**Advantages**: +- Organized by purpose +- Easier to maintain +- Can restrict access by directory + +### Hierarchical Structure + +Nested organization for complex plugins: + +``` +commands/ +├── ci/ +│ ├── build.md +│ ├── test.md +│ └── lint.md +├── deployment/ +│ ├── staging.md +│ └── production.md +└── management/ + ├── config.md + └── status.md +``` + +**Note**: Claude Code doesn't support nested command discovery automatically. Use custom paths: + +```json +{ + "commands": [ + "./commands/ci", + "./commands/deployment", + "./commands/management" + ] +} +``` + +**When to use**: +- 20+ commands +- Multi-level categorization +- Complex workflows + +**Advantages**: +- Maximum organization +- Clear boundaries +- Scalable structure + +## Agent Organization Patterns + +### Role-Based Organization + +Organize agents by their primary role: + +``` +agents/ +├── code-reviewer.md # Reviews code +├── test-generator.md # Generates tests +├── documentation-writer.md # Writes docs +└── refactorer.md # Refactors code +``` + +**When to use**: +- Agents have distinct, non-overlapping roles +- Users invoke agents manually +- Clear agent responsibilities + +### Capability-Based Organization + +Organize by specific capabilities: + +``` +agents/ +├── python-expert.md # Python-specific +├── typescript-expert.md # TypeScript-specific +├── api-specialist.md # API design +└── database-specialist.md # Database work +``` + +**When to use**: +- Technology-specific agents +- Domain expertise focus +- Automatic agent selection + +### Workflow-Based Organization + +Organize by workflow stage: + +``` +agents/ +├── planning-agent.md # Planning phase +├── implementation-agent.md # Coding phase +├── testing-agent.md # Testing phase +└── deployment-agent.md # Deployment phase +``` + +**When to use**: +- Sequential workflows +- Stage-specific expertise +- Pipeline automation + +## Skill Organization Patterns + +### Topic-Based Organization + +Each skill covers a specific topic: + +``` +skills/ +├── api-design/ +│ └── SKILL.md +├── error-handling/ +│ └── SKILL.md +├── testing-strategies/ +│ └── SKILL.md +└── performance-optimization/ + └── SKILL.md +``` + +**When to use**: +- Knowledge-based skills +- Educational or reference content +- Broad applicability + +### Tool-Based Organization + +Skills for specific tools or technologies: + +``` +skills/ +├── docker/ +│ ├── SKILL.md +│ └── references/ +│ └── dockerfile-best-practices.md +├── kubernetes/ +│ ├── SKILL.md +│ └── examples/ +│ └── deployment.yaml +└── terraform/ + ├── SKILL.md + └── scripts/ + └── validate-config.sh +``` + +**When to use**: +- Tool-specific expertise +- Complex tool configurations +- Tool best practices + +### Workflow-Based Organization + +Skills for complete workflows: + +``` +skills/ +├── code-review-workflow/ +│ ├── SKILL.md +│ └── references/ +│ ├── checklist.md +│ └── standards.md +├── deployment-workflow/ +│ ├── SKILL.md +│ └── scripts/ +│ ├── pre-deploy.sh +│ └── post-deploy.sh +└── testing-workflow/ + ├── SKILL.md + └── examples/ + └── test-structure.md +``` + +**When to use**: +- Multi-step processes +- Company-specific workflows +- Process automation + +### Skill with Rich Resources + +Comprehensive skill with all resource types: + +``` +skills/ +└── api-testing/ + ├── SKILL.md # Core skill (1500 words) + ├── references/ + │ ├── rest-api-guide.md + │ ├── graphql-guide.md + │ └── authentication.md + ├── examples/ + │ ├── basic-test.js + │ ├── authenticated-test.js + │ └── integration-test.js + ├── scripts/ + │ ├── run-tests.sh + │ └── generate-report.py + └── assets/ + └── test-template.json +``` + +**Resource usage**: +- **SKILL.md**: Overview and when to use resources +- **references/**: Detailed guides (loaded as needed) +- **examples/**: Copy-paste code samples +- **scripts/**: Executable test runners +- **assets/**: Templates and configurations + +## Hook Organization Patterns + +### Monolithic Configuration + +Single hooks.json with all hooks: + +``` +hooks/ +├── hooks.json # All hook definitions +└── scripts/ + ├── validate-write.sh + ├── validate-bash.sh + └── load-context.sh +``` + +**hooks.json**: +```json +{ + "PreToolUse": [...], + "PostToolUse": [...], + "Stop": [...], + "SessionStart": [...] +} +``` + +**When to use**: +- 5-10 hooks total +- Simple hook logic +- Centralized configuration + +### Event-Based Organization + +Separate files per event type: + +``` +hooks/ +├── hooks.json # Combines all +├── pre-tool-use.json # PreToolUse hooks +├── post-tool-use.json # PostToolUse hooks +├── stop.json # Stop hooks +└── scripts/ + ├── validate/ + │ ├── write.sh + │ └── bash.sh + └── context/ + └── load.sh +``` + +**hooks.json** (combines): +```json +{ + "PreToolUse": ${file:./pre-tool-use.json}, + "PostToolUse": ${file:./post-tool-use.json}, + "Stop": ${file:./stop.json} +} +``` + +**Note**: Use build script to combine files, Claude Code doesn't support file references. + +**When to use**: +- 10+ hooks +- Different teams managing different events +- Complex hook configurations + +### Purpose-Based Organization + +Group by functional purpose: + +``` +hooks/ +├── hooks.json +└── scripts/ + ├── security/ + │ ├── validate-paths.sh + │ ├── check-credentials.sh + │ └── scan-malware.sh + ├── quality/ + │ ├── lint-code.sh + │ ├── check-tests.sh + │ └── verify-docs.sh + └── workflow/ + ├── notify-team.sh + └── update-status.sh +``` + +**When to use**: +- Many hook scripts +- Clear functional boundaries +- Team specialization + +## Script Organization Patterns + +### Flat Scripts + +All scripts in single directory: + +``` +scripts/ +├── build.sh +├── test.py +├── deploy.sh +├── validate.js +└── report.py +``` + +**When to use**: +- 5-10 scripts +- All scripts related +- Simple plugin + +### Categorized Scripts + +Group by purpose: + +``` +scripts/ +├── build/ +│ ├── compile.sh +│ └── package.sh +├── test/ +│ ├── run-unit.sh +│ └── run-integration.sh +├── deploy/ +│ ├── staging.sh +│ └── production.sh +└── utils/ + ├── log.sh + └── notify.sh +``` + +**When to use**: +- 10+ scripts +- Clear categories +- Reusable utilities + +### Language-Based Organization + +Group by programming language: + +``` +scripts/ +├── bash/ +│ ├── build.sh +│ └── deploy.sh +├── python/ +│ ├── analyze.py +│ └── report.py +└── javascript/ + ├── bundle.js + └── optimize.js +``` + +**When to use**: +- Multi-language scripts +- Different runtime requirements +- Language-specific dependencies + +## Cross-Component Patterns + +### Shared Resources + +Components sharing common resources: + +``` +plugin/ +├── commands/ +│ ├── test.md # Uses lib/test-utils.sh +│ └── deploy.md # Uses lib/deploy-utils.sh +├── agents/ +│ └── tester.md # References lib/test-utils.sh +├── hooks/ +│ └── scripts/ +│ └── pre-test.sh # Sources lib/test-utils.sh +└── lib/ + ├── test-utils.sh + └── deploy-utils.sh +``` + +**Usage in components**: +```bash +#!/bin/bash +source "${CLAUDE_PLUGIN_ROOT}/lib/test-utils.sh" +run_tests +``` + +**Benefits**: +- Code reuse +- Consistent behavior +- Easier maintenance + +### Layered Architecture + +Separate concerns into layers: + +``` +plugin/ +├── commands/ # User interface layer +├── agents/ # Orchestration layer +├── skills/ # Knowledge layer +└── lib/ + ├── core/ # Core business logic + ├── integrations/ # External services + └── utils/ # Helper functions +``` + +**When to use**: +- Large plugins (100+ files) +- Multiple developers +- Clear separation of concerns + +### Plugin Within Plugin + +Nested plugin structure: + +``` +plugin/ +├── .claude-plugin/ +│ └── plugin.json +├── core/ # Core functionality +│ ├── commands/ +│ └── agents/ +└── extensions/ # Optional extensions + ├── extension-a/ + │ ├── commands/ + │ └── agents/ + └── extension-b/ + ├── commands/ + └── agents/ +``` + +**Manifest**: +```json +{ + "commands": [ + "./core/commands", + "./extensions/extension-a/commands", + "./extensions/extension-b/commands" + ] +} +``` + +**When to use**: +- Modular functionality +- Optional features +- Plugin families + +## Best Practices + +### Naming + +1. **Consistent naming**: Match file names to component purpose +2. **Descriptive names**: Indicate what component does +3. **Avoid abbreviations**: Use full words for clarity + +### Organization + +1. **Start simple**: Use flat structure, reorganize when needed +2. **Group related items**: Keep related components together +3. **Separate concerns**: Don't mix unrelated functionality + +### Scalability + +1. **Plan for growth**: Choose structure that scales +2. **Refactor early**: Reorganize before it becomes painful +3. **Document structure**: Explain organization in README + +### Maintainability + +1. **Consistent patterns**: Use same structure throughout +2. **Minimize nesting**: Keep directory depth manageable +3. **Use conventions**: Follow community standards + +### Performance + +1. **Avoid deep nesting**: Impacts discovery time +2. **Minimize custom paths**: Use defaults when possible +3. **Keep configurations small**: Large configs slow loading diff --git a/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/references/manifest-reference.md b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/references/manifest-reference.md new file mode 100644 index 0000000..40c9c2f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/plugin-structure/references/manifest-reference.md @@ -0,0 +1,552 @@ +# Plugin Manifest Reference + +Complete reference for `plugin.json` configuration. + +## File Location + +**Required path**: `.claude-plugin/plugin.json` + +The manifest MUST be in the `.claude-plugin/` directory at the plugin root. Claude Code will not recognize plugins without this file in the correct location. + +## Complete Field Reference + +### Core Fields + +#### name (required) + +**Type**: String +**Format**: kebab-case +**Example**: `"test-automation-suite"` + +The unique identifier for the plugin. Used for: +- Plugin identification in Claude Code +- Conflict detection with other plugins +- Command namespacing (optional) + +**Requirements**: +- Must be unique across all installed plugins +- Use only lowercase letters, numbers, and hyphens +- No spaces or special characters +- Start with a letter +- End with a letter or number + +**Validation**: +```javascript +/^[a-z][a-z0-9]*(-[a-z0-9]+)*$/ +``` + +**Examples**: +- ✅ Good: `api-tester`, `code-review`, `git-workflow-automation` +- ❌ Bad: `API Tester`, `code_review`, `-git-workflow`, `test-` + +#### version + +**Type**: String +**Format**: Semantic versioning (MAJOR.MINOR.PATCH) +**Example**: `"2.1.0"` +**Default**: `"0.1.0"` if not specified + +Semantic versioning guidelines: +- **MAJOR**: Incompatible API changes, breaking changes +- **MINOR**: New functionality, backward-compatible +- **PATCH**: Bug fixes, backward-compatible + +**Pre-release versions**: +- `"1.0.0-alpha.1"` - Alpha release +- `"1.0.0-beta.2"` - Beta release +- `"1.0.0-rc.1"` - Release candidate + +**Examples**: +- `"0.1.0"` - Initial development +- `"1.0.0"` - First stable release +- `"1.2.3"` - Patch update to 1.2 +- `"2.0.0"` - Major version with breaking changes + +#### description + +**Type**: String +**Length**: 50-200 characters recommended +**Example**: `"Automates code review workflows with style checks and automated feedback"` + +Brief explanation of plugin purpose and functionality. + +**Best practices**: +- Focus on what the plugin does, not how +- Use active voice +- Mention key features or benefits +- Keep under 200 characters for marketplace display + +**Examples**: +- ✅ "Generates comprehensive test suites from code analysis and coverage reports" +- ✅ "Integrates with Jira for automatic issue tracking and sprint management" +- ❌ "A plugin that helps you do testing stuff" +- ❌ "This is a very long description that goes on and on about every single feature..." + +### Metadata Fields + +#### author + +**Type**: Object +**Fields**: name (required), email (optional), url (optional) + +```json +{ + "author": { + "name": "Jane Developer", + "email": "jane@example.com", + "url": "https://janedeveloper.com" + } +} +``` + +**Alternative format** (string only): +```json +{ + "author": "Jane Developer <jane@example.com> (https://janedeveloper.com)" +} +``` + +**Use cases**: +- Credit and attribution +- Contact for support or questions +- Marketplace display +- Community recognition + +#### homepage + +**Type**: String (URL) +**Example**: `"https://docs.example.com/plugins/my-plugin"` + +Link to plugin documentation or landing page. + +**Should point to**: +- Plugin documentation site +- Project homepage +- Detailed usage guide +- Installation instructions + +**Not for**: +- Source code (use `repository` field) +- Issue tracker (include in documentation) +- Personal websites (use `author.url`) + +#### repository + +**Type**: String (URL) or Object +**Example**: `"https://github.com/user/plugin-name"` + +Source code repository location. + +**String format**: +```json +{ + "repository": "https://github.com/user/plugin-name" +} +``` + +**Object format** (detailed): +```json +{ + "repository": { + "type": "git", + "url": "https://github.com/user/plugin-name.git", + "directory": "packages/plugin-name" + } +} +``` + +**Use cases**: +- Source code access +- Issue reporting +- Community contributions +- Transparency and trust + +#### license + +**Type**: String +**Format**: SPDX identifier +**Example**: `"MIT"` + +Software license identifier. + +**Common licenses**: +- `"MIT"` - Permissive, popular choice +- `"Apache-2.0"` - Permissive with patent grant +- `"GPL-3.0"` - Copyleft +- `"BSD-3-Clause"` - Permissive +- `"ISC"` - Permissive, similar to MIT +- `"UNLICENSED"` - Proprietary, not open source + +**Full list**: https://spdx.org/licenses/ + +**Multiple licenses**: +```json +{ + "license": "(MIT OR Apache-2.0)" +} +``` + +#### keywords + +**Type**: Array of strings +**Example**: `["testing", "automation", "ci-cd", "quality-assurance"]` + +Tags for plugin discovery and categorization. + +**Best practices**: +- Use 5-10 keywords +- Include functionality categories +- Add technology names +- Use common search terms +- Avoid duplicating plugin name + +**Categories to consider**: +- Functionality: `testing`, `debugging`, `documentation`, `deployment` +- Technologies: `typescript`, `python`, `docker`, `aws` +- Workflows: `ci-cd`, `code-review`, `git-workflow` +- Domains: `web-development`, `data-science`, `devops` + +### Component Path Fields + +#### commands + +**Type**: String or Array of strings +**Default**: `["./commands"]` +**Example**: `"./cli-commands"` + +Additional directories or files containing command definitions. + +**Single path**: +```json +{ + "commands": "./custom-commands" +} +``` + +**Multiple paths**: +```json +{ + "commands": [ + "./commands", + "./admin-commands", + "./experimental-commands" + ] +} +``` + +**Behavior**: Supplements default `commands/` directory (does not replace) + +**Use cases**: +- Organizing commands by category +- Separating stable from experimental commands +- Loading commands from shared locations + +#### agents + +**Type**: String or Array of strings +**Default**: `["./agents"]` +**Example**: `"./specialized-agents"` + +Additional directories or files containing agent definitions. + +**Format**: Same as `commands` field + +**Use cases**: +- Grouping agents by specialization +- Separating general-purpose from task-specific agents +- Loading agents from plugin dependencies + +#### hooks + +**Type**: String (path to JSON file) or Object (inline configuration) +**Default**: `"./hooks/hooks.json"` + +Hook configuration location or inline definition. + +**File path**: +```json +{ + "hooks": "./config/hooks.json" +} +``` + +**Inline configuration**: +```json +{ + "hooks": { + "PreToolUse": [ + { + "matcher": "Write", + "hooks": [ + { + "type": "command", + "command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/validate.sh", + "timeout": 30 + } + ] + } + ] + } +} +``` + +**Use cases**: +- Simple plugins: Inline configuration (< 50 lines) +- Complex plugins: External JSON file +- Multiple hook sets: Separate files for different contexts + +#### mcpServers + +**Type**: String (path to JSON file) or Object (inline configuration) +**Default**: `./.mcp.json` + +MCP server configuration location or inline definition. + +**File path**: +```json +{ + "mcpServers": "./.mcp.json" +} +``` + +**Inline configuration**: +```json +{ + "mcpServers": { + "github": { + "command": "node", + "args": ["${CLAUDE_PLUGIN_ROOT}/servers/github-mcp.js"], + "env": { + "GITHUB_TOKEN": "${GITHUB_TOKEN}" + } + } + } +} +``` + +**Use cases**: +- Simple plugins: Single inline server (< 20 lines) +- Complex plugins: External `.mcp.json` file +- Multiple servers: Always use external file + +## Path Resolution + +### Relative Path Rules + +All paths in component fields must follow these rules: + +1. **Must be relative**: No absolute paths +2. **Must start with `./`**: Indicates relative to plugin root +3. **Cannot use `../`**: No parent directory navigation +4. **Forward slashes only**: Even on Windows + +**Examples**: +- ✅ `"./commands"` +- ✅ `"./src/commands"` +- ✅ `"./configs/hooks.json"` +- ❌ `"/Users/name/plugin/commands"` +- ❌ `"commands"` (missing `./`) +- ❌ `"../shared/commands"` +- ❌ `".\\commands"` (backslash) + +### Resolution Order + +When Claude Code loads components: + +1. **Default directories**: Scans standard locations first + - `./commands/` + - `./agents/` + - `./skills/` + - `./hooks/hooks.json` + - `./.mcp.json` + +2. **Custom paths**: Scans paths specified in manifest + - Paths from `commands` field + - Paths from `agents` field + - Files from `hooks` and `mcpServers` fields + +3. **Merge behavior**: Components from all locations load + - No overwriting + - All discovered components register + - Name conflicts cause errors + +## Validation + +### Manifest Validation + +Claude Code validates the manifest on plugin load: + +**Syntax validation**: +- Valid JSON format +- No syntax errors +- Correct field types + +**Field validation**: +- `name` field present and valid format +- `version` follows semantic versioning (if present) +- Paths are relative with `./` prefix +- URLs are valid (if present) + +**Component validation**: +- Referenced paths exist +- Hook and MCP configurations are valid +- No circular dependencies + +### Common Validation Errors + +**Invalid name format**: +```json +{ + "name": "My Plugin" // ❌ Contains spaces +} +``` +Fix: Use kebab-case +```json +{ + "name": "my-plugin" // ✅ +} +``` + +**Absolute path**: +```json +{ + "commands": "/Users/name/commands" // ❌ Absolute path +} +``` +Fix: Use relative path +```json +{ + "commands": "./commands" // ✅ +} +``` + +**Missing ./ prefix**: +```json +{ + "hooks": "hooks/hooks.json" // ❌ No ./ +} +``` +Fix: Add ./ prefix +```json +{ + "hooks": "./hooks/hooks.json" // ✅ +} +``` + +**Invalid version**: +```json +{ + "version": "1.0" // ❌ Not semantic versioning +} +``` +Fix: Use MAJOR.MINOR.PATCH +```json +{ + "version": "1.0.0" // ✅ +} +``` + +## Minimal vs. Complete Examples + +### Minimal Plugin + +Bare minimum for a working plugin: + +```json +{ + "name": "hello-world" +} +``` + +Relies entirely on default directory discovery. + +### Recommended Plugin + +Good metadata for distribution: + +```json +{ + "name": "code-review-assistant", + "version": "1.0.0", + "description": "Automates code review with style checks and suggestions", + "author": { + "name": "Jane Developer", + "email": "jane@example.com" + }, + "homepage": "https://docs.example.com/code-review", + "repository": "https://github.com/janedev/code-review-assistant", + "license": "MIT", + "keywords": ["code-review", "automation", "quality", "ci-cd"] +} +``` + +### Complete Plugin + +Full configuration with all features: + +```json +{ + "name": "enterprise-devops", + "version": "2.3.1", + "description": "Comprehensive DevOps automation for enterprise CI/CD pipelines", + "author": { + "name": "DevOps Team", + "email": "devops@company.com", + "url": "https://company.com/devops" + }, + "homepage": "https://docs.company.com/plugins/devops", + "repository": { + "type": "git", + "url": "https://github.com/company/devops-plugin.git" + }, + "license": "Apache-2.0", + "keywords": [ + "devops", + "ci-cd", + "automation", + "kubernetes", + "docker", + "deployment" + ], + "commands": [ + "./commands", + "./admin-commands" + ], + "agents": "./specialized-agents", + "hooks": "./config/hooks.json", + "mcpServers": "./.mcp.json" +} +``` + +## Best Practices + +### Metadata + +1. **Always include version**: Track changes and updates +2. **Write clear descriptions**: Help users understand plugin purpose +3. **Provide contact information**: Enable user support +4. **Link to documentation**: Reduce support burden +5. **Choose appropriate license**: Match project goals + +### Paths + +1. **Use defaults when possible**: Minimize configuration +2. **Organize logically**: Group related components +3. **Document custom paths**: Explain why non-standard layout used +4. **Test path resolution**: Verify on multiple systems + +### Maintenance + +1. **Bump version on changes**: Follow semantic versioning +2. **Update keywords**: Reflect new functionality +3. **Keep description current**: Match actual capabilities +4. **Maintain changelog**: Track version history +5. **Update repository links**: Keep URLs current + +### Distribution + +1. **Complete metadata before publishing**: All fields filled +2. **Test on clean install**: Verify plugin works without dev environment +3. **Validate manifest**: Use validation tools +4. **Include README**: Document installation and usage +5. **Specify license file**: Include LICENSE file in plugin root diff --git a/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/SKILL.md new file mode 100644 index 0000000..e4fbdf2 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/SKILL.md @@ -0,0 +1,150 @@ +--- +name: post-acceptance +description: This skill should be used when the user asks to "prepare conference presentation", "create presentation slides", "design poster", "make academic poster", "write promotion content", "create Twitter thread", or mentions post-acceptance conference preparation. Provides comprehensive workflow for presentation, poster, and promotion content creation. +version: 0.1.0 +--- + +# Post-Acceptance Conference Preparation + +A post-acceptance conference preparation workflow that helps researchers efficiently complete presentations, posters, and promotional content. + +## Core Features + +### 1. Presentation Slide Creation + +Guidance for creating conference presentation slides: + +**Time Control** +- 15-minute talk: 10-15 slides +- 20-minute talk: 15-20 slides +- 30-minute talk: 20-30 slides +- Average 1-1.5 minutes per slide + +**Content Structure** +- Title slide (1) +- Motivation/Problem (2-3) +- Method overview (3-5) +- Key results (3-5) +- Conclusion (1-2) +- Q&A/Thank you (1) + +**Visual Design Principles** +- One key message per slide +- Use figures and diagrams over text +- Consistent color scheme and fonts +- Minimum font size: 24pt for body, 32pt for titles +- High-contrast colors for readability + +**Presentation Tips** +- Practice timing with a stopwatch +- Prepare backup slides for anticipated questions +- Use animations sparingly and purposefully +- Include slide numbers for Q&A reference + +### 2. Academic Poster Design + +Guidance for creating conference posters: + +**Standard Sizes** +- Portrait: 24x36 inches or A0 (841x1189mm) +- Landscape: 36x24 inches or A0 landscape +- Check conference requirements for specific size + +**Layout Structure** +- Title bar (top): Title, authors, affiliations, logos +- Introduction (left): Problem statement, motivation +- Method (center): Key approach, architecture diagram +- Results (right): Main findings, tables, figures +- Conclusion (bottom): Summary, future work, QR code + +**Design Guidelines** +- Readable from 4-6 feet distance +- Title font: 72-96pt +- Section headers: 36-48pt +- Body text: 24-32pt +- Use bullet points, not paragraphs +- Include QR code linking to paper/code + +### 3. Promotion Content Creation + +Guidance for creating promotional content after paper acceptance: + +**Twitter/X Thread** +- Thread structure: Hook -> Problem -> Method -> Key Result -> Link +- First tweet: Attention-grabbing summary with emoji +- Include 1-2 key figures +- End with paper link and relevant hashtags +- Tag co-authors and relevant accounts + +**LinkedIn Post** +- Professional tone, 3-5 paragraphs +- Highlight practical implications +- Include key figure or diagram +- Add relevant hashtags + +**Blog Post** +- 800-1500 words +- Non-technical summary for broader audience +- Include figures with explanations +- Link to paper, code, and demo + +## When to Use + +Use this skill in the following scenarios: + +- **After paper acceptance** - Prepare presentation materials for the conference +- **Poster session preparation** - Design and create academic poster +- **Research promotion** - Create social media and blog content +- **Conference talk preparation** - Structure and practice presentation + +## Workflow + +### Presentation Workflow +``` +Paper accepted -> Identify key messages -> Create slide outline -> Design slides -> Practice timing -> Prepare Q&A backup slides +``` + +### Poster Workflow +``` +Paper accepted -> Choose layout template -> Extract key content -> Design poster -> Print test at reduced size -> Final print +``` + +### Promotion Workflow +``` +Paper accepted -> Write Twitter thread -> Create LinkedIn post -> Draft blog post -> Schedule posts around conference dates +``` + +## Best Practices + +### Presentation +- Start with the "so what" - why should the audience care +- Tell a story: problem -> insight -> solution -> impact +- Use concrete examples and demos when possible +- Anticipate questions and prepare answers +- Arrive early to test equipment + +### Poster +- Design for scanning, not reading +- Use visual hierarchy to guide the eye +- Include a "elevator pitch" summary +- Bring business cards or QR codes +- Practice a 2-minute and 5-minute explanation + +### Promotion +- Post within 1-2 weeks of acceptance notification +- Coordinate timing with co-authors +- Engage with comments and questions +- Share across multiple platforms +- Include accessible descriptions for figures + +## Summary + +This skill provides a comprehensive post-acceptance workflow covering three key areas: presentation slides, academic posters, and promotional content. Following these guidelines helps researchers effectively communicate their work at conferences and to the broader community. + + +## Reference Files + +Load only what is needed: +- `references/design-guidelines.md` - visual design guidance +- `references/deliverable-checklists.md` - slide/poster/promo-specific checklists +- `examples/post-acceptance-plan.md` - compact delivery plan example diff --git a/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/examples/post-acceptance-plan.md b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/examples/post-acceptance-plan.md new file mode 100644 index 0000000..bc4e64c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/examples/post-acceptance-plan.md @@ -0,0 +1,11 @@ +# Post-Acceptance Plan + +## Week 1 +- draft slide outline +- choose poster layout +- write short social post draft + +## Week 2 +- polish slides +- finalize poster +- schedule promotion around conference timeline diff --git a/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/deliverable-checklists.md b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/deliverable-checklists.md new file mode 100644 index 0000000..283834c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/deliverable-checklists.md @@ -0,0 +1,16 @@ +# Deliverable Checklists + +## Slides +- one key message per slide +- readable from the back of the room +- backup slides for likely questions + +## Poster +- readable from 4-6 feet +- visual hierarchy clear +- QR code or artifact link present + +## Promotion +- one-sentence hook +- one clear figure or graphic +- platform-specific tone and length respected diff --git a/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/design-guidelines.md b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/design-guidelines.md new file mode 100644 index 0000000..a89256b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/design-guidelines.md @@ -0,0 +1,85 @@ +# Design Guidelines for Conference Materials + +会议材料设计的详细指南和最佳实践。 + +## Presentation Design Guidelines + +### Slide Layout +- 使用16:9宽屏比例（现代投影仪标准） +- 保持一致的页边距（建议：上下左右各1英寸） +- 标题区域占slide高度的15-20% + +### Typography +- 标题字体：Sans-serif（Arial, Helvetica, Calibri） +- 正文字体：与标题保持一致 +- 最小字号：24pt（确保后排观众可见） +- 行距：1.2-1.5倍 + + +### Color Scheme +- 使用高对比度配色（深色背景+浅色文字，或反之） +- 主色调：选择1-2种主色 +- 强调色：用于突出关键信息 +- 避免使用纯红色和纯绿色（色盲友好） +- 推荐配色方案： + - 学术蓝：#003366 + #FFFFFF + - 专业灰：#333333 + #F5F5F5 + - 现代绿：#2E7D32 + #FFFFFF + +### Visual Elements +- 图表：使用矢量图（SVG, PDF） +- 照片：高分辨率（至少300 DPI） +- 图标：统一风格，简洁明了 +- 动画：谨慎使用，不超过3个 + + +## Poster Design Guidelines + +### Layout Structure +- 标题栏：占海报高度的15-20% +- 内容区：分3-4列，每列宽度相等 +- 结论区：占海报高度的15-20% +- 页边距：至少2英寸（便于打印和装裱） + +### Content Organization +- 从左到右、从上到下的阅读顺序 +- 每个部分有清晰的标题 +- 使用编号或箭头引导阅读流程 +- 核心内容放在视觉中心（黄金分割点） + + +### Typography for Posters +- 标题：72-96pt，粗体 +- 作者和机构：36-48pt +- 章节标题：48-60pt +- 正文：24-32pt +- 图表标注：20-24pt + +### Printing Guidelines +- 分辨率：至少150 DPI（推荐300 DPI） +- 颜色模式：CMYK（打印）或RGB（屏幕显示） +- 文件格式：PDF（推荐）或高质量PNG +- 打印前检查：颜色校准、文字清晰度、图表质量 + + +## Promotion Content Guidelines + +### Social Media Design +- 配图尺寸： + - Twitter: 1200×675px + - LinkedIn: 1200×627px + - 通用: 1080×1080px (正方形) +- 文字叠加：使用高对比度，确保可读性 +- Logo/水印：放在不显眼的位置 + +### Visual Consistency +- 使用统一的配色方案 +- 保持字体风格一致 +- 图表风格统一 +- 品牌元素（Logo、颜色）保持一致 + +### Best Practices +- 简洁明了：避免信息过载 +- 视觉层次：突出关键信息 +- 可访问性：考虑色盲和视力障碍用户 +- 跨平台适配：确保在不同设备上显示良好 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/poster-templates/basic-poster-template.md b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/poster-templates/basic-poster-template.md new file mode 100644 index 0000000..593c07f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/poster-templates/basic-poster-template.md @@ -0,0 +1,30 @@ +# Basic Poster Template + +基础学术海报模板结构 + +## Top Section (20%) +- 论文标题（大号粗体） +- 作者和机构 +- 会议Logo + +## Main Content (60%) + +### Column 1: Introduction & Method +- 研究背景 +- 问题陈述 +- 方法概述 + +### Column 2: Results +- 主要实验结果 +- 关键图表 +- 数据可视化 + +### Column 3: Discussion & Conclusion +- 结果分析 +- 主要贡献 +- 未来工作 + +## Bottom Section (20%) +- 主要结论 +- 联系方式 +- QR码（论文/代码链接） diff --git a/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/presentation-templates/basic-template.md b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/presentation-templates/basic-template.md new file mode 100644 index 0000000..6f9d4b9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/presentation-templates/basic-template.md @@ -0,0 +1,28 @@ +# Basic Presentation Template + +基础演讲模板结构示例 + +## Slide 1: Title +- 论文标题 +- 作者姓名和机构 +- 会议名称和日期 + +## Slide 2-3: Motivation +- 研究背景 +- 现有问题 +- 研究动机 + +## Slide 4-6: Method +- 方法概述 +- 关键技术 +- 创新点 + +## Slide 7-9: Results +- 主要实验结果 +- 对比分析 +- 可视化展示 + +## Slide 10: Conclusion +- 主要贡献 +- 未来工作 +- 致谢 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/promotion-examples/twitter-example.md b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/promotion-examples/twitter-example.md new file mode 100644 index 0000000..178d035 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/post-acceptance/references/promotion-examples/twitter-example.md @@ -0,0 +1,36 @@ +# Twitter/X Promotion Example + +学术推文示例 + +## Example 1: Thread Format + +**Tweet 1 (Hook)** +🎉 Excited to share our paper accepted at #NeurIPS2024! + +We tackle the challenge of [problem] in [domain]. + +Thread 👇 + +**Tweet 2 (Problem)** +Current methods struggle with [specific issue], leading to [consequence]. + +Our key insight: [novel perspective] + +**Tweet 3 (Method)** +We propose [method name], which: +✅ [Key feature 1] +✅ [Key feature 2] +✅ [Key feature 3] + +**Tweet 4 (Results)** +Results on [benchmark]: +📊 [Metric 1]: X% improvement +📊 [Metric 2]: Y% faster +📊 [Metric 3]: Z% better + +**Tweet 5 (CTA)** +📄 Paper: [link] +💻 Code: [link] +🎯 Demo: [link] + +#MachineLearning #AI #Research diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/SKILL.md new file mode 100644 index 0000000..ad883c1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/SKILL.md @@ -0,0 +1,318 @@ +--- +name: publication-chart-skill +description: This skill should be used when the user asks for a publication-quality scientific figure or table, wants help choosing the right chart for results, needs a paper-ready pubfig or pubtab workflow, wants a figure + companion table for a results section, wants an Excel sheet turned into publication-ready LaTeX, or wants an existing scientific figure/table reviewed and upgraded. +version: 0.2.0 +--- + +# Publication Chart Skill + +## Goal + +Use this skill to turn research results into **publication-grade figures and tables** with an end-to-end workflow. + +Primary production stack: + +- **`pubfig`** for figures +- **`pubtab`** for publication tables + +This skill covers the full delivery chain: + +1. understand the scientific communication goal, +2. choose the right artifact type, +3. map the task to `pubfig`, `pubtab`, or both, +4. generate concrete runnable instructions, +5. export paper-ready assets, +6. run publication QA, +7. propose targeted revisions. + +## Use this skill when + +Trigger this skill for requests like: + +- “make a publication-quality figure” +- “choose the right chart for these results” +- “turn these results into a paper-ready figure” +- “make a benchmark / ablation / calibration / forest / heatmap / scatter / line / bar figure” +- “make a benchmark / appendix / ablation table from Excel” +- “convert this Excel table into publication-ready LaTeX” +- “prepare one summary figure plus one companion table for the results section” +- “review and improve this scientific figure/table” +- “I already have a weak chart / screenshot / draft plot — make it publication-ready” +- “export panels for a paper figure” + +## Do not use this skill for + +Do **not** use this skill when the task is mainly: + +- manuscript prose writing, +- statistical testing without artifact design, +- raw exploratory analysis with no publication deliverable, +- Figma-first layout work before the figure/table content is solid. + +For simple composite assembly after the figure content is already strong, use the optional secondary workflow in `references/composite-assembly.md`. + +## Primary contract + +### Inputs + +Expect some combination of: + +- the scientific communication goal, +- available data shape, +- venue or style constraints, +- whether the artifact is a figure, table, or mixed deliverable, +- optional existing assets such as code, spreadsheets, `.tex`, screenshots, or draft plots, +- whether the user needs a first draft, a publication-ready artifact, or a review/revision pass. + +### Outputs + +The minimum useful output is: + +- the recommended figure/table form, +- the recommended `pubfig` / `pubtab` route, +- a minimal runnable code snippet or CLI command, +- explicit export filenames and formats, +- a publication QA summary, +- and, when needed, a revision plan. + +## Default workflow + +### 0. Probe the environment and artifact state + +Before generating anything, identify: + +- whether `pubfig` or `pubtab` is actually available, +- whether the user already has code / spreadsheets / `.tex` / screenshots, +- whether the deliverable is a fresh build or a revision, +- whether the result needs exact values, fast visual perception, or both. + +Prefer the smallest environment check that helps execution. When the bundled helper script is available, use it first: + +- `python3 scripts/ensure_publication_tooling.py --require pubfig --json` +- `python3 scripts/ensure_publication_tooling.py --require pubtab --json` + +Equivalent manual checks are still acceptable when needed: + +- `python -c "import pubfig; print(pubfig.__version__)"` +- `python -c "import pubtab; print(pubtab.__version__)"` +- `pubtab --help` + +Report the result clearly as **available** or **missing**. + +If a dependency is missing and the task requires runnable execution: + +- **auto-install it by default**, +- prefer the user’s active environment instead of guessing a random global interpreter, +- use `python3 scripts/ensure_publication_tooling.py --require ...` as the default bundled route when the script is present, +- let that helper choose `uv` vs `python -m pip` against the active interpreter, +- re-run the availability probe after installation, +- and only then continue with the artifact workflow. + +Equivalent concrete commands include: + +- `python3 scripts/ensure_publication_tooling.py --require pubfig` +- `python3 scripts/ensure_publication_tooling.py --require pubtab` +- `uv pip install pubfig` +- `uv pip install pubtab` +- `python -m pip install pubfig` +- `python -m pip install pubtab` + +If auto-install fails, report the exact failure and then degrade gracefully. + +Do not block on a full environment audit. + +### 1. Classify the task + +Classify the request along these axes: + +- **artifact type**: figure / table / mixed deliverable +- **maturity**: exploratory draft / publication-ready generation / revision of an existing artifact +- **structure**: single panel / multi-panel / figure-plus-table package +- **evidence mode**: pattern perception / exact value lookup / both + +Do not jump into plotting code before the communication target is clear. + +Before plotting research results, lock the evidence contract: +- primary scientific claim, +- unit of analysis, +- primary metric and metric direction, +- whether repeated rows are independent, +- missing cells or incomplete comparison blocks, +- error-bar basis: subject, subject-task, fold, seed, run, or bootstrap sample, +- whether exact values need a companion table, +- whether the current evidence allows a winner/significance claim. + +If these are unclear, ask or produce an audit recommendation instead of a polished figure. Do not create a paper-ready plot while the unit of analysis, missing-cell handling, or error-bar basis is unresolved. + +### 2. Choose the representation + +Choose the representation based on the scientific claim, not novelty or visual flair. + +Common families: + +- **comparison** — grouped scatter, bar, line comparison, benchmark summary, companion table +- **ablation** — grouped comparison, dumbbell, paired comparison, compact table +- **distribution** — box, violin, raincloud, histogram, density, ECDF, QQ +- **relationship** — scatter, bubble, contour2d, hexbin +- **trend** — line, area +- **evaluation / diagnostic** — calibration, ROC, PR, Bland–Altman, forest plot, volcano +- **composition / hierarchy** — UpSet, stacked ratio, donut, radial hierarchy, circular grouped or stacked bars +- **table** — benchmark table, ablation table, dataset summary, appendix table, error breakdown + +Avoid weak defaults: + +- avoid pie/donut when exact comparison matters and a bar/table is clearer, +- avoid radar unless the comparison is genuinely profile-like and low-cardinality, +- avoid 3D, decorative gradients, and dense legends used only for style, +- avoid forcing every result into a figure when a publication table communicates the evidence better. + +If the request is ambiguous, explicitly state what scientific claim the artifact is supposed to support. + +### 3. Map to the toolchain + +Default mapping: + +- **Figures** → `pubfig` +- **Tables** → `pubtab` +- **Mixed deliverables** → use both, with each artifact carrying a distinct role + +Tool roles: + +- `pubfig` is the default figure engine for scientific plots and paper-ready export. +- `pubtab` is the default table engine for Excel ↔ LaTeX workflows, preview, and publication-ready table export. +- Figma/composite assembly is an **optional secondary branch** for multi-panel finishing. + +Route selection rules: + +- prefer **Python** for `pubfig` figure generation, +- prefer **CLI** for `pubtab` when the task is file-driven, +- prefer **Python** for `pubtab` when the task is already inside a notebook or scripted pipeline, +- keep the figure and table responsibilities separate in mixed requests. + +### 4. Generate concrete artifact instructions + +Prefer the smallest production-ready artifact first: + +- minimal runnable Python for `pubfig`, or +- minimal CLI/Python for `pubtab` + +Then add publication parameters only when justified: + +- labels, caption, width, export format, backend, preview, panel packaging, or composite layout. + +Keep filenames and suffixes explicit. + +Good defaults: + +- figures: one `pubfig` call + one `save_figure(...)` +- multiple figure outputs: `batch_export(...)` +- tables: one `pubtab xlsx2tex ...` or `pubtab.preview ...` +- mixed requests: one figure route + one table route, clearly separated + +### 5. Define the delivery contract + +For every response, make these explicit when possible: + +- the claim the artifact supports, +- which part is handled by `pubfig` and which by `pubtab`, +- the output filenames, +- the output formats, +- whether the artifact is draft / final / revision, +- what still needs user-provided data or manuscript context. + +### 6. Run publication QA + +After generation, check: + +- title and legend density, +- axis labels and units, +- category ordering and baseline clarity, +- color accessibility and grayscale robustness, +- font / line-weight consistency, +- caption readiness, +- figure/table readability after downscaling, +- panel consistency for multi-panel figures, +- venue-fit issues such as width, crowding, or over-annotation. + +The QA output must be concrete. Do not say “looks better” without naming why. + +### 7. Revise + +If the result is weak, revise with specific changes such as: + +- switch chart family, +- remove chartjunk, +- reorder categories, +- move exact values into a table, +- split a crowded panel, +- add or simplify the caption, +- change export width, +- or convert the deliverable from figure-first to table-first. + +## Missing dependency behavior + +If `pubfig` or `pubtab` is not available: + +- do **not** fail immediately, +- first attempt automatic installation into the active environment, +- prefer `python3 scripts/ensure_publication_tooling.py --require ...` when the bundled script exists, +- explicitly state which dependency is missing, +- state which install command or helper route is being used, +- re-check availability after installation, +- if installation succeeds, continue with the runnable workflow, +- if installation fails, degrade to a design/specification workflow, +- provide pseudocode or draft commands, +- preserve the recommended figure/table structure, +- still provide QA and revision guidance. + +## Composite assembly rule + +Treat composite or Figma assembly as **secondary**: + +- use it when the user explicitly wants a multi-panel paper figure, +- or when panel-level export and layout polishing are genuinely needed. + +Do not escalate simple figure tasks into composite/Figma workflows by default. + +## Output style rules + +- Prefer direct, implementation-usable outputs. +- Explain the **why** of chart/table choice briefly, then give the runnable route. +- When execution matters, include a short environment status block such as `pubfig: available/missing`, `pubtab: available/missing`. +- If a dependency is missing, state the exact helper command or install command, perform the installation, and report the post-install status. +- When a table is stronger than a figure, say so explicitly. +- When a figure is stronger than a table, say so explicitly. +- When both are needed, assign them different communication roles. +- Keep revision guidance actionable and falsifiable. + +## Recommended response shape + +A strong response using this skill usually has 6 parts: + +1. **Artifact decision** — figure / table / paired deliverable, and why +2. **Tool route** — `pubfig`, `pubtab`, or both +3. **Minimal implementation** — runnable code or CLI +4. **Export plan** — filenames, formats, width/backend/preview choices +5. **Publication QA** — what to verify before paper submission +6. **Revision plan** — what to change if the current artifact is weak + +## Resources + +Load these as needed: + +- `references/workflow.md` — full end-to-end decision order and delivery contract +- `references/chart-selection.md` — task-to-chart mapping and anti-patterns +- `references/execution-and-verification.md` — environment probing, forced install behavior, and runnable verification +- `scripts/ensure_publication_tooling.py` — bundled probe + auto-install helper for `pubfig` / `pubtab` +- `references/pubfig-recipes.md` — shortest useful figure patterns and export routes +- `references/pubtab-recipes.md` — shortest useful table routes and backend guidance +- `references/source-guides/pubfig-architecture.md` — package layout and figure-generation boundaries from source +- `references/source-guides/pubfig-api-map.md` — stable public pubfig surface and chart-family map from `__init__.py` +- `references/source-guides/pubfig-export-flow.md` — figure export, publication sizing, and panel-export flow from source +- `references/source-guides/pubtab-architecture.md` — package layout and forward/reverse conversion architecture from source +- `references/source-guides/pubtab-cli-api-flow.md` — CLI-to-API control flow and batch/sheet behavior from source +- `references/source-guides/pubtab-backend-and-preview.md` — backend/theme split and real preview compile pipeline from source +- `references/publication-qa-checklist.md` — figure/table QA checklist +- `references/composite-assembly.md` — optional multi-panel and Figma branch + +For prompt-shaped examples, see `examples/`. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/01-benchmark-comparison-figure.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/01-benchmark-comparison-figure.md new file mode 100644 index 0000000..72d5830 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/01-benchmark-comparison-figure.md @@ -0,0 +1,25 @@ +# Example 1 — Benchmark comparison figure + +## User-style prompt + +Help me make a publication-quality benchmark comparison figure for six methods across three datasets. + +## Expected skill interpretation + +- artifact: figure +- maturity: publication-ready generation +- structure: single panel +- goal: fast comparison across methods and datasets + +## Preferred route + +- primary tool: `pubfig` +- likely family: `grouped_scatter` or `bar_scatter` +- companion table: optional, only if exact values must be preserved nearby + +## Minimum acceptable output shape + +- explain why the chosen comparison form is better than a raw grouped bar if density is high +- provide a minimal `pubfig` implementation +- provide one explicit export command/path such as `benchmark.pdf` +- provide a short QA note about readability, legend density, and category ordering diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/02-ablation-figure.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/02-ablation-figure.md new file mode 100644 index 0000000..f157aa0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/02-ablation-figure.md @@ -0,0 +1,25 @@ +# Example 2 — Ablation figure + +## User-style prompt + +Turn these ablation results into a paper-ready figure that makes the contribution of each module easy to read. + +## Expected skill interpretation + +- artifact: figure +- maturity: publication-ready generation +- structure: single panel or compact paired panel +- goal: isolate incremental effect clearly + +## Preferred route + +- primary tool: `pubfig` +- likely family: `dumbbell` or `paired` for low-cardinality paired ablations, otherwise a compact grouped comparison chart or companion table +- do not default to a crowded decorative chart + +## Minimum acceptable output shape + +- recommend the ablation-focused visual form and why +- provide runnable `pubfig` code +- export to a paper-ready format +- include a QA note on baseline clarity and ordering diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/03-calibration-evaluation-figure.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/03-calibration-evaluation-figure.md new file mode 100644 index 0000000..35429e3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/03-calibration-evaluation-figure.md @@ -0,0 +1,25 @@ +# Example 3 — Calibration / evaluation figure + +## User-style prompt + +I need a publication-quality evaluation figure showing whether my predicted probabilities are calibrated. + +## Expected skill interpretation + +- artifact: figure +- maturity: publication-ready generation +- structure: single panel +- goal: diagnostic evaluation, not generic trend plotting + +## Preferred route + +- primary tool: `pubfig` +- likely family: `calibration` +- related alternatives: ROC / PR only if the scientific question changes + +## Minimum acceptable output shape + +- explain why calibration is the right diagnostic form +- provide minimal runnable code +- export to PDF or SVG +- include QA on labels, reference lines, and downscaled readability diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/04-forest-diagnostic-figure.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/04-forest-diagnostic-figure.md new file mode 100644 index 0000000..de3c429 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/04-forest-diagnostic-figure.md @@ -0,0 +1,25 @@ +# Example 4 — Forest / diagnostic figure + +## User-style prompt + +Help me convert these effect estimates and confidence intervals into a paper-quality figure. + +## Expected skill interpretation + +- artifact: figure +- maturity: publication-ready generation +- structure: single panel +- goal: communicate effect size with uncertainty + +## Preferred route + +- primary tool: `pubfig` +- likely family: `forest_plot` +- table may accompany it in appendix if exact values are numerous + +## Minimum acceptable output shape + +- identify forest plot as the default route +- provide the required arrays/arguments shape +- export a paper-ready artifact +- include QA on reference line, label clarity, and ordering diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/05-publication-table-from-excel.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/05-publication-table-from-excel.md new file mode 100644 index 0000000..0996f4b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/05-publication-table-from-excel.md @@ -0,0 +1,26 @@ +# Example 5 — Publication-ready LaTeX table from Excel + +## User-style prompt + +Convert this Excel benchmark sheet into a publication-ready LaTeX table and give me a preview path before I paste it into the paper. + +## Expected skill interpretation + +- artifact: table +- maturity: publication-ready generation +- structure: single table +- goal: exact benchmark values in LaTeX + +## Preferred route + +- primary tool: `pubtab` +- likely route: `xlsx2tex` + `preview` +- for a robust preview-first workflow, preview the table body first and keep final caption/label handling as a separate manuscript-facing step when needed +- `tabularray` only if the manuscript/backend requires it + +## Minimum acceptable output shape + +- provide the exact `pubtab` command or Python route +- include caption/label guidance when appropriate, but do not force them into the preview-first route +- include preview generation +- mention table width/span concerns if relevant diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/06-mixed-figure-table-results.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/06-mixed-figure-table-results.md new file mode 100644 index 0000000..3bf41fb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/06-mixed-figure-table-results.md @@ -0,0 +1,25 @@ +# Example 6 — Mixed figure + table deliverable + +## User-style prompt + +For this results section, I want one summary figure and one companion table: the figure should show the overall pattern, and the table should preserve the exact metrics. + +## Expected skill interpretation + +- artifact: mixed deliverable +- maturity: publication-ready generation +- structure: one figure plus one table +- goal: split visual summary from exact evidence + +## Preferred route + +- figure: `pubfig` +- table: `pubtab` +- each artifact should have a distinct communication role + +## Minimum acceptable output shape + +- explicitly separate figure and table responsibilities +- provide one minimal `pubfig` route and one minimal `pubtab` route +- define export filenames for both +- include QA on redundancy and role separation diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/07-revision-from-weak-chart.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/07-revision-from-weak-chart.md new file mode 100644 index 0000000..e5b0e1c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/07-revision-from-weak-chart.md @@ -0,0 +1,25 @@ +# Example 7 — Revision from a weak chart request + +## User-style prompt + +I was thinking of using a radar chart for these benchmark results. Can you improve this into something publication-quality? + +## Expected skill interpretation + +- artifact: revision task +- maturity: review/revision +- structure: likely single figure or figure+table alternative +- goal: replace a weak chart choice with a stronger one + +## Preferred route + +- review the proposed radar choice critically +- recommend a stronger alternative such as grouped scatter, line, or a table depending on the claim +- only keep radar if the profile comparison is genuinely the right representation + +## Minimum acceptable output shape + +- explain why the original chart is weak or risky +- recommend a better artifact type +- provide the replacement implementation route +- include targeted QA / revision notes, not vague style comments diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/08-review-existing-figure-or-table.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/08-review-existing-figure-or-table.md new file mode 100644 index 0000000..af5e64e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/examples/08-review-existing-figure-or-table.md @@ -0,0 +1,25 @@ +# Example 8 — Review an existing figure or table draft + +## User-style prompt + +Here is my current results figure screenshot and the draft benchmark table. Please tell me what is weak, whether the figure should stay a figure or become a figure + table pair, and give me the recommended pubfig/pubtab revision path. + +## Expected skill interpretation + +- artifact: review / revision +- maturity: existing deliverable upgrade +- structure: figure-only or figure + companion table +- goal: keep the strongest communication role for each artifact instead of polishing a weak form blindly + +## Preferred route + +- inspect the current figure/table role split first +- recommend whether the figure should stay visual and the table should preserve exact values +- use `pubfig` for the figure revision and `pubtab` for the table revision when both are needed + +## Minimum acceptable output shape + +- identify the concrete publication weaknesses in the current artifact(s) +- say whether the final deliverable should be figure-only, table-only, or figure + table +- provide one runnable `pubfig` and/or `pubtab` revision route +- define explicit export filenames and a short QA checklist diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/chart-selection.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/chart-selection.md new file mode 100644 index 0000000..261bc19 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/chart-selection.md @@ -0,0 +1,47 @@ +# Chart Selection + +## Task-to-chart mapping + +| Communication task | Preferred forms | Notes | +|---|---|---| +| Benchmark comparison | grouped scatter, bar, companion table | use table when exact values matter most | +| Ablation | grouped comparison, dumbbell, compact table | keep the dimension count small | +| Calibration / evaluation | calibration, ROC, PR, Bland–Altman | choose what matches the evaluation claim | +| Distribution | box, violin, raincloud, histogram, density, ECDF, QQ | choose by whether shape or exact quantiles matter | +| Relationship | scatter, bubble, contour2d, hexbin | use hexbin/contour2d when overplotting is severe | +| Trend | line, area | line is usually the safer default | +| Diagnostic effect size | forest plot, volcano | match domain and inference style | +| Set/composition | UpSet, stacked ratio, donut, radial hierarchy | avoid decorative complexity unless it helps interpretation | +| Exact benchmark appendix | publication table | default to `pubtab` | + +## Use X instead of Y + +- Use **grouped scatter** or a **table** instead of a dense grouped bar when exact per-group values matter. +- Use **line** instead of bar for ordered progression over time or scale. +- Use **UpSet** instead of Venn-style thinking once the set count grows. +- Use **forest plot** instead of overloaded textual effect summaries. +- Use **table** instead of radar when precision and comparability matter more than shape. +- Use **hexbin** or **contour2d** instead of raw scatter when point overlap hides structure. +- Use **ECDF** when comparing cumulative distributions clearly is more important than showing a smoothed KDE. + +## Anti-patterns + +Avoid: + +- pie/donut for exact quantitative comparison unless the composition story is primary and category count is small, +- radar for many categories or when axes are not semantically comparable, +- 3D effects, +- decorative color ramps without semantic purpose, +- overly dense legends that repeat axis information, +- mixed chart types that make the evidence harder to read, +- turning every result into a figure when a publication table would be cleaner. + +## Selection heuristic + +Ask in order: + +1. What claim is the reader supposed to take away? +2. Does the reader need pattern perception or exact value lookup? +3. Are the groups ordered, categorical, repeated, hierarchical, or overlapping? +4. Is the result single-panel or likely part of a multi-panel figure? +5. Would a figure-only answer hide important exact values that should live in a table? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/composite-assembly.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/composite-assembly.md new file mode 100644 index 0000000..fa50473 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/composite-assembly.md @@ -0,0 +1,34 @@ +# Composite Assembly + +## Principle + +Composite assembly is a **secondary branch**, not the default workflow. + +Use it when: + +- the user explicitly wants a multi-panel paper figure, +- panel-level maintenance matters, +- or the final paper figure needs finishing beyond a single exported plot. + +## Default stance + +- Single-panel figure → stay in `pubfig` normal export mode. +- Multi-panel figure with real assembly needs → use panel/composite export. +- Figma is optional and should not be introduced unless it solves a real assembly problem. + +## pubfig routes + +Relevant `pubfig` capabilities: + +- `export_panel(...)` +- `export_panels(...)` +- `batch_export(...)` +- `save_figure(...)` + +If the environment already uses a pubfig/Figma bridge workflow, keep `figure_id` stable across revisions. + +## Practical rule + +Escalate to composite assembly only after the panel content itself is strong. + +Do not use Figma/composite assembly to hide weak chart choice, poor labels, or overloaded panels. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/execution-and-verification.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/execution-and-verification.md new file mode 100644 index 0000000..d91b7fd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/execution-and-verification.md @@ -0,0 +1,159 @@ +# Execution and Verification + +## Goal + +Turn a high-level publication figure/table request into a route that is actually runnable in the current environment. + +## Minimum environment probe + +Prefer the lightest useful checks. + +### Preferred bundled probe + +```bash +python3 scripts/ensure_publication_tooling.py --require pubfig --json +python3 scripts/ensure_publication_tooling.py --require pubtab --json +``` + +The helper probes availability, force-installs missing dependencies into the active interpreter, and returns the post-install status. + +### Equivalent manual checks + +```bash +python -c "import pubfig; print(pubfig.__version__)" +python -c "import pubtab; print(pubtab.__version__)" +pubtab --help +``` + +Do not spend the whole turn on setup if the user primarily needs design guidance. Just identify whether the route is executable now or should degrade gracefully. + +## Automatic installation policy + +If a dependency is missing and the task requires real execution, install it automatically before continuing. + +### Preferred bundled route + +Use the bundled helper when it is present: + +```bash +python3 scripts/ensure_publication_tooling.py --require pubfig +python3 scripts/ensure_publication_tooling.py --require pubtab +``` + +The helper chooses `uv pip install --python <active-python>` when the project is clearly `uv`-managed, and otherwise falls back to `python -m pip install ...`. + +### Equivalent manual install commands + +```bash +uv pip install --python "$VIRTUAL_ENV/bin/python" pubfig +uv pip install --python "$VIRTUAL_ENV/bin/python" pubtab +python -m pip install pubfig +python -m pip install pubtab +``` + +### Required follow-up + +After installation: + +1. re-run the availability probe, +2. report the updated environment status, +3. continue with the runnable figure/table workflow. + +If installation fails, capture the exact error and then fall back to design/specification guidance. + +## Route selection + +### Use `pubfig` when + +- the task is primarily a figure, +- the user already has Python data structures, +- the result is a plot family already covered by `pubfig`, +- export quality matters immediately. + +### Use `pubtab` when + +- the task is primarily a publication table, +- the input is an Excel workbook, a `.tex` table, or a file-driven workflow, +- the reader needs exact values, +- previewing the table before manuscript insertion matters. + +### Use both when + +- the figure carries the visual pattern, +- the table preserves exact benchmark values, +- the paper section benefits from one fast visual plus one exact-value artifact. + +## First runnable verification + +### `pubfig` + +After generating a minimal figure route, the first useful verification is: + +- can the code execute, +- does `save_figure(...)` or `batch_export(...)` produce the expected files, +- do output suffixes match the intended formats. + +### `pubtab` + +After generating a minimal table route, the first useful verification is: + +- can `xlsx2tex` or `tex2xlsx` run, +- can `preview` render PNG or PDF, +- does the chosen backend (`tabular` or `tabularray`) match the manuscript need. + +## Current practical notes + +### `pubfig` + +Useful export primitives include: + +- `save_figure(...)` +- `batch_export(...)` +- `export_panel(...)` +- `export_panels(...)` + +Use panel export only when multi-panel assembly is truly needed. + +### `pubtab` + +Useful file-oriented routes include: + +- `pubtab xlsx2tex ...` +- `pubtab tex2xlsx ...` +- `pubtab preview ...` + +Remember: + +- `xlsx2tex` exports all sheets by default when `--sheet` is not set, +- `preview` can render PNG or PDF, +- `--latex-backend tabularray` should be chosen only when the manuscript/backend requires `tblr`, +- when preview reliability is the immediate priority, validate the table body first and add final `caption` / `label` in a separate manuscript-facing step if needed. + +## Graceful degradation + +If the tool is missing: + +- first try the bundled auto-install helper, +- if that route is unavailable, use the manual install commands above, +- if installation still fails, provide: + - the artifact recommendation, + - the exact files the user should prepare, + - a draft CLI or Python route, + - the export targets, + - and the publication QA checklist. + +## Default output wording + +When the route is runnable now, say: + +- what to run, +- what files should appear, +- what to inspect next. + +When the route is not runnable now, say: + +- what is missing, +- which helper command or install command was attempted, +- whether the install succeeded or failed, +- what the intended route will be after install, +- and what design decision can already be locked in today. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/pubfig-recipes.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/pubfig-recipes.md new file mode 100644 index 0000000..1d404e8 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/pubfig-recipes.md @@ -0,0 +1,104 @@ +# pubfig Recipes + +`pubfig` is the default engine for scientific figures. + +## Core route + +Typical minimal workflow: + +```python +import pubfig as pf + +fig = pf.line(data, x=x, series_names=["A", "B"]) +pf.save_figure(fig, "figure1.pdf") +``` + +## Common figure families + +| Need | Preferred `pubfig` functions | +|---|---| +| benchmark comparison | `bar_scatter`, `grouped_scatter`, `bar`, `line` | +| ablation | `bar_scatter`, `dumbbell`, `paired`, `bar` | +| distribution | `box`, `violin`, `raincloud`, `histogram`, `density`, `ecdf`, `qq` | +| relationship | `scatter`, `bubble`, `contour2d`, `hexbin` | +| trend | `line`, `area` | +| diagnostic / evaluation | `calibration`, `forest_plot`, `bland_altman`, `volcano`, `roc`, `pr_curve` | +| composition / hierarchy | `donut`, `upset`, `radial_hierarchy`, `circular_grouped_bar`, `circular_stacked_bar`, `stacked_ratio_barh` | +| matrix / map | `heatmap`, `corr_matrix`, `clustermap` | + +## Export defaults + +For a normal first pass: + +```python +pf.save_figure(fig, "figure1.pdf") +``` + +For multiple formats: + +```python +pf.batch_export( + fig, + "figure1", + formats=("pdf", "svg", "png"), + spec="nature", + width="single", + dpi=300, +) +``` + +## When to add export parameters + +Only add more export controls when the task demands them: + +- `spec` / `width` for venue-style export +- explicit SVG for vector-first downstream editing +- PNG for quick review or raster deliverables +- panel export when the user truly needs composite assembly +- `batch_export(...)` when the same figure needs several publication-style outputs + +## Panel export branch + +Use these only when multi-panel assembly is genuinely needed: + +- `export_panel(...)` +- `export_panels(...)` + +Do not default to panel export for single figures. + +## Minimal recipe patterns + +### Benchmark comparison + +```python +fig = pf.grouped_scatter(values, category_names=category_names, group_names=model_names) +pf.save_figure(fig, "benchmark.pdf") +``` + +### Ablation + +```python +fig = pf.dumbbell(baseline, improved, category_names=labels) +pf.save_figure(fig, "ablation.pdf") +``` + +### Calibration + +```python +fig = pf.calibration(prob_true, prob_pred) +pf.save_figure(fig, "calibration.pdf") +``` + +### Forest plot + +```python +fig = pf.forest_plot(effect, lower, upper, labels=labels, reference=1.0) +pf.save_figure(fig, "forest.pdf") +``` + +### Heatmap + +```python +fig = pf.heatmap(matrix) +pf.save_figure(fig, "heatmap.pdf") +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/publication-qa-checklist.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/publication-qa-checklist.md new file mode 100644 index 0000000..ff77e8b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/publication-qa-checklist.md @@ -0,0 +1,47 @@ +# Publication QA Checklist + +## Figure QA + +Check: + +- Is the chart family appropriate for the scientific claim? +- Are axes labeled clearly, with units when needed? +- Is category ordering meaningful and stable? +- Are color choices readable in grayscale or for color-deficient readers? +- Are fonts, line weights, and marker sizes internally consistent? +- Is the legend necessary, and if so, is it compact? +- Does the figure stay readable after downscaling to likely paper width? +- If multi-panel, are labels, spacing, and styling consistent across panels? +- Does the caption need exact numbers that should instead live in a table? + +## Table QA + +Check: + +- Is a table actually the right artifact, or should a companion figure exist? +- Are row/column labels short but unambiguous? +- Are important values easy to locate? +- Is the caption specific enough to stand alone? +- Is the table too dense for the main paper and better suited to appendix? +- If two-column format matters, was width/span considered explicitly? +- Was a preview rendered before treating the table as final? + +## Mixed deliverable QA + +If both a figure and table are present: + +- Does each have a distinct role? +- Is the figure carrying pattern perception? +- Is the table preserving exact values? +- Is there duplication that should be reduced? + +## Revision questions + +If the artifact is weak, ask: + +- Should the chart family change? +- Should exact values move into a table? +- Should the artifact split into two panels? +- Should labels or legends be simplified? +- Should export width/format change? +- Should the artifact move from figure-first to table-first, or the reverse? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/pubtab-recipes.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/pubtab-recipes.md new file mode 100644 index 0000000..d0b8814 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/pubtab-recipes.md @@ -0,0 +1,133 @@ +# pubtab Recipes + +`pubtab` is the default engine for publication-ready tables. + +## Core routes + +### Excel to LaTeX + +```bash +pubtab xlsx2tex results.xlsx -o results.tex +``` + +### LaTeX to Excel + +```bash +pubtab tex2xlsx tables.tex -o tables.xlsx +``` + +### Preview + +```bash +pubtab preview results.tex -o results.png --dpi 300 +pubtab preview results.tex --format pdf -o results.pdf +``` + +## Python route + +```python +import pubtab + +pubtab.xlsx2tex("results.xlsx", output="results.tex", theme="three_line") +pubtab.preview("results.tex", output="results.png", dpi=300) +``` + +## Route selection rule + +Prefer the **CLI** when: + +- the user already speaks in files, +- the source is Excel or `.tex`, +- the main need is export and preview. + +Prefer the **Python API** when: + +- the task already lives inside a notebook or script, +- the table generation is part of a larger reproducible pipeline. + +## Current practical notes + +- `xlsx2tex` exports **all sheets by default** when `--sheet` is not set. +- `preview` can render **PNG or PDF**. +- `--latex-backend tabularray` is useful only when the manuscript/backend really requires `tblr`. +- `preview` can auto-detect `tblr`, but explicit backend override is still fine when needed. +- for a robust preview-first workflow, preview the table body first and add the final `caption` / `label` in the manuscript or in a final non-preview export step when needed. + +## When to use `tabularray` + +Use `--latex-backend tabularray` when: + +- the user explicitly wants `tblr`, +- the manuscript already uses `tabularray`, +- or the backend must match an existing paper template. + +Example: + +```bash +pubtab xlsx2tex results.xlsx -o results_tblr.tex --theme three_line --latex-backend tabularray +``` + +## Common publication controls + +Use these when they are justified: + +- `--caption` +- `--label` +- `--span-columns` +- `--preview` +- `--latex-backend` +- `--sheet` +- `--with-resizebox` +- `--without-resizebox` +- `--resizebox-width` + +## Default guidance + +- start with the smallest `xlsx2tex` route, +- preview before treating the table as final, +- use a publication table when exact values matter more than quick pattern perception, +- keep figure and table roles distinct in mixed deliverables. + +## Minimal recipe patterns + +### Benchmark table from Excel + +```bash +pubtab xlsx2tex benchmark.xlsx -o benchmark.tex --caption "Main benchmark results." --label "tab:benchmark" +``` + +### Two-column table + +```bash +pubtab xlsx2tex benchmark.xlsx -o benchmark.tex --span-columns +``` + +### Preview before submission + +```bash +pubtab xlsx2tex benchmark.xlsx -o benchmark_preview.tex +pubtab preview benchmark_preview.tex -o benchmark.png --dpi 300 +``` + +Use this route when the immediate goal is a reliable visual check of the table body. +Keep `caption` / `label` as a separate manuscript-facing step if the preview is the main verification target. + +### Final manuscript-facing export + +```bash +pubtab xlsx2tex benchmark.xlsx -o benchmark.tex --caption "Main benchmark results." --label "tab:benchmark" +``` + +### All-sheets export + +```bash +pubtab xlsx2tex benchmark.xlsx -o out/benchmark.tex +``` + +### Native file-pipeline batch roundtrip + +```bash +pubtab tex2xlsx ./tables_tex -o ./out/xlsx +pubtab xlsx2tex ./out/xlsx -o ./out/tex +pubtab preview ./out/tex -o ./out/png --format png --dpi 300 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-api-map.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-api-map.md new file mode 100644 index 0000000..23aea19 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-api-map.md @@ -0,0 +1,199 @@ +# pubfig API map (source-driven) + +This guide maps the public `pubfig` API from `pubfig/src/pubfig/__init__.py` to the underlying modules. + +## 1. Stable entrypoint + +The public contract is defined by re-exports in `pubfig.__init__`. + +For agents, this means: + +- if a symbol is re-exported there, it is a good default public entrypoint; +- if a helper only exists in deep internal modules, treat it as implementation detail unless there is a strong reason not to. + +## 2. Public API groups + +### Themes + +Public re-exports: + +- `set_default_theme` +- `get_default_theme` +- `get_theme` +- `register_theme` + +Use these when the task is really about reusable visual policy. +Do not hardcode theme assumptions if a registry call is more appropriate. + +### Colors and palettes + +Public re-exports include: + +- `DEFAULT`, `NATURE`, `SCIENCE`, `LANCET`, `JAMA` +- `get_palette` +- `register_palette` +- `color_to_rgba` +- `darken_color` +- `show_palette` + +Source fact: + +- palette registration and palette inspection are exposed from the package root. + +Operational implication: + +- treat palette selection and palette registration as public API usage, not as deep internal customization. + +### Export + +Public re-exports: + +- `save_figure` +- `batch_export` +- `PanelExportRecord` +- `export_panel` +- `export_panels` +- `package_figma_bundle` +- `validate_figma_bundle` +- `inspect_figma_bundle` + +Skill implication: + +- normal paper figures should usually stop at `save_figure` or `batch_export` +- panel workflows should use `export_panel(s)` +- bundle helpers are for bridge/Figma handoff, not the default answer + +### Figure specs + +Public re-exports: + +- `FigureSpec` +- `get_figure_spec` +- `register_figure_spec` +- `list_figure_specs` + +Use this layer whenever the user asks for venue-aware width, journal defaults, or a custom export profile. + +### Plot families + +The public plot surface is broad, but the source still clusters naturally. + +#### Comparison / summary figures + +Representative public calls: + +- `bar` +- `bar_scatter` +- `stacked_bar` +- `stacked_ratio_barh` +- `donut` +- `dumbbell` +- `forest_plot` +- `grouped_scatter` +- `upset` + +Use these for benchmark, ablation, summary, composition, and set-overlap tasks. + +#### Distribution figures + +Representative public calls: + +- `ecdf` +- `qq` +- `box` +- `density` +- `hexbin` +- `histogram` +- `raincloud` +- `strip` +- `ridgeline` +- `violin` + +Use these when the scientific claim is about spread, calibration of assumptions, or cohort structure. + +#### Trend / profile figures + +Representative public calls: + +- `line` +- `area` +- `parallel_coordinates` +- `radar` +- `radial_hierarchy` +- `circular_stacked_bar` +- `circular_grouped_bar` + +Not all of these are equally strong for publication use. The skill should still apply chart-selection discipline before calling them. + +#### Relationship / embedding figures + +Representative public calls: + +- `scatter` +- `volcano` +- `bubble` +- `contour2d` +- `paired` +- `heatmap` +- `corr_matrix` +- `clustermap` +- `dimreduce` +- `pca_biplot` + +Use these for association, error structure, feature layout, and representation views. + +#### Evaluation figures + +Representative public calls: + +- `roc` +- `pr_curve` +- `calibration` +- `bland_altman` + +This cluster matters because the source gives them dedicated implementation in `plots/evaluation.py`, which is a sign that evaluation charts are a first-class use case. + +## 3. Return-value contract + +The source in `export/io.py` makes a subtle but important contract explicit: + +- export functions accept a Matplotlib `Figure`, +- or an `Axes`, +- or any object exposing a `.figure` attribute that resolves to a `Figure`. + +Source fact: + +- the export layer accepts standard Matplotlib figure objects or figure-bearing wrappers. + +Operational implication: + +- keep the `Figure` handle available and route export through the standard Matplotlib-facing export path. + +For the skill, the safest phrasing is: + +- create the figure, +- keep a handle to the `Figure`, +- then export explicitly. + +## 4. What is not the main stable plotting interface + +From the source tree, the CLI is not where normal chart creation happens. +It is mostly an operational layer for Figma bundle and bridge actions. + +So if a user says “generate a paper-ready figure,” the skill should not default to a CLI answer. + +## 5. Safe public usage pattern + +The most source-faithful pattern is: + +1. choose a public plot function from `pubfig` +2. generate a `Figure` +3. export via `save_figure(...)` or `batch_export(...)` +4. only use panel/bundle helpers when composition is actually required + +## 6. Source-guided caution points + +- Do not mix up plot-time design sizing with export-time publication sizing. +- Do not use `save_figure(...)` as a multi-format exporter; the source now pushes that role to `batch_export(...)`. +- Do not route ordinary figure-generation tasks through the Figma bridge CLI. +- Do not assume all public plot families are equally appropriate; the skill must still filter by scientific communication quality. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-architecture.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-architecture.md new file mode 100644 index 0000000..931ab56 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-architecture.md @@ -0,0 +1,190 @@ +# pubfig architecture (source-driven) + +This guide reads `pubfig` from the source tree rather than from high-level overview material. + +Source root: + +- `pubfig/src/pubfig/__init__.py` +- `pubfig/src/pubfig/plots/` +- `pubfig/src/pubfig/export/` +- `pubfig/src/pubfig/specs.py` +- `pubfig/src/pubfig/themes/` +- `pubfig/src/pubfig/colors/` +- `pubfig/src/pubfig/cli.py` + +## 1. Start at `pubfig.__init__` + +The stable user-facing surface is re-exported from `__init__.py`. + +That file tells you the package is organized into five main layers: + +1. **plot constructors** from `plots/` +2. **export helpers** from `export/` +3. **publication sizing** from `specs.py` +4. **theme and palette registries** from `themes/` and `colors/` +5. **Figma/bridge helpers** and related CLI support + +For skill design, this is the most important architectural fact: + +- figure generation lives in `plots/` +- figure export lives in `export/` +- venue sizing lives in `specs.py` +- multi-panel/Figma handoff is a separate downstream layer + +The default mental model is **plot first, export second, compose third**. + +## 2. Package boundaries + +### `plots/` + +This is the core figure-construction layer. + +Representative files: + +- `plots/line.py` +- `plots/comparison.py` +- `plots/evaluation.py` +- `plots/_grouped_scatter.py` + +From the source, plot functions usually do the same sequence: + +1. normalize/coerce input data, +2. enter `theme_context(theme)`, +3. resolve design-time size via `resolve_design_dpi(...)`, +4. allocate figure/axes via `get_fig_ax(...)`, +5. style axes/legends through helpers in `_style.py`, +6. return a Matplotlib `Figure`. + +Interpretation from source: + +- `pubfig` behaves as a **Matplotlib-first figure factory layer**, not as a separate scene-graph runtime. + +### `export/` + +This is intentionally separated from plotting. + +Important files: + +- `export/io.py` +- `export/panels.py` + +`export/io.py` handles normal figure export: + +- coerce Figure/Axes into a real `Figure` +- enforce explicit suffixes +- apply publication width/height rules +- write vector or raster output + +Current source implication: + +- `batch_export(...)` now belongs to the same publication-aware export layer, rather than to a simple multi-format `savefig` wrapper. + +`export/panels.py` handles panel-level export for composite or Figma-oriented workflows: + +- one panel at a time or many panels together +- optional publication-aware sizing +- optional title stripping +- metadata index generation (`panel-index.json`) + +### `specs.py` + +This file is the publication-sizing contract. + +`FigureSpec` defines: + +- `font_family` +- `design_dpi` +- `single_column_mm` +- `double_column_mm` +- `default_raster_dpi` +- `background_color` + +Built-in registry entries include: + +- `nature` +- `science` +- `cell` + +The source shows a strong split between: + +- **design size** used when constructing interactive figures, +- **physical export size** used when saving publication figures. + +That split is why the skill should not treat `width` in plot calls and `width` in export calls as the same semantic layer. + +### `themes/` and `colors/` + +These are registries, not plain constants. + +From `__init__.py`, the public surface includes: + +- `get_theme`, `register_theme`, `set_default_theme` +- `get_palette`, `register_palette`, `show_palette` + +Operational implication: + +- treat theme and palette selection as first-class API configuration rather than as hardcoded styling trivia. + +### `cli.py` + +The current CLI is not the main figure-generation interface. + +From the source, `cli.py` is mainly about: + +- Figma bridge serving +- bundle packaging/inspection/validation +- sync job submission and waiting +- local bridge auto-start logic + +So for this skill: + +- **Python API is the primary route for figure generation** +- `pubfig.cli` is a secondary operational layer for bridge/Figma workflows + +## 3. Plotting architecture pattern + +From `line.py`, `comparison.py`, and `evaluation.py`, the recurring internal pattern is: + +- input normalization is local to the chart family, +- shared visual behavior is delegated to internal helpers, +- returned artifact is still a standard Matplotlib figure. + +This is why the skill should map requests to a chart family first, instead of jumping directly to export or panel assembly. + +Examples from source: + +- `line.py` groups time/trend style plots +- `comparison.py` groups comparison-style statistical displays like `dumbbell` and `forest_plot` +- `evaluation.py` groups metric/evaluation plots like `roc`, `pr_curve`, and `calibration` +- `_grouped_scatter.py` contains the more specialized placement/jitter/annotation logic behind grouped scatter layouts + +## 4. Export architecture pattern + +From `export/io.py` and `export/panels.py`, `pubfig` uses three distinct output modes: + +1. **single explicit artifact** via `save_figure(...)` +2. **publication-aware multi-format artifact set** via `batch_export(...)` +3. **panel bundle workflow** via `export_panel(...)` / `export_panels(...)` + +Those are different contracts, and the skill should keep them separate in its recommendations. + +## 5. Reading order for deep debugging + +When a skill or agent needs source-level certainty, use this order: + +1. `pubfig/src/pubfig/__init__.py` +2. relevant chart-family module in `plots/` +3. `pubfig/src/pubfig/specs.py` +4. `pubfig/src/pubfig/export/io.py` +5. `pubfig/src/pubfig/export/panels.py` +6. `pubfig/src/pubfig/cli.py` only if the task involves bridge/Figma sync + +## 6. Implications for this skill + +This source layout implies the skill should: + +- default to **Python plot API + explicit export call**, +- treat publication sizing as an export concern, +- treat panel/Figma work as optional downstream composition, +- avoid presenting the CLI as the main path for ordinary figure generation, +- keep chart selection logically ahead of export tuning. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-export-flow.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-export-flow.md new file mode 100644 index 0000000..f642f3c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubfig-export-flow.md @@ -0,0 +1,210 @@ +# pubfig export flow (source-driven) + +This guide explains how `pubfig` moves from a generated Matplotlib figure to paper-ready files. + +Primary source files: + +- `pubfig/src/pubfig/export/io.py` +- `pubfig/src/pubfig/export/panels.py` +- `pubfig/src/pubfig/specs.py` + +## 1. Core export contract + +`export/io.py` separates two concerns: + +- **coercing a valid figure object** +- **writing explicit output files** + +The helper `_coerce_mpl_figure(...)` accepts: + +- a `Figure` +- an `Axes` +- an object with a `.figure` attribute pointing to a `Figure` + +The export layer is standardized around Matplotlib figures, even if upstream plotting code returns a richer wrapper. + +## 2. `save_figure(...)` is now single-target and suffix-explicit + +A key source-level rule lives in `_resolve_save_figure_target(...)`: + +- `save_figure(...)` now requires an explicit filename suffix, +- supported examples include `.pdf`, `.svg`, `.png`, `.jpg`, `.tif`, `.eps`, `.ps`, +- if there is no suffix, the function raises an error, +- if multiple outputs are wanted, the source tells you to use `batch_export(...)`. + +Skill implication: + +- always write `results/figure1.pdf` rather than `results/figure1` +- when you want several formats, recommend `batch_export(...)`, not legacy vector/raster format lists + +## 3. Publication sizing path + +`save_figure(...)` is publication-aware. + +Internally it does the following: + +1. load the chosen `FigureSpec` via `get_figure_spec(...)` +2. resolve width through `resolve_width_mm(...)` +3. resolve height through `resolve_height_mm(...)` +4. set the Matplotlib figure size in inches using mm-to-inch conversion +5. choose raster DPI from the spec unless overridden +6. save the explicit target file +7. restore original caller state afterward + +Interpretation from source: + +- export sizing is more than a file-write step; it can temporarily resize the figure to venue-oriented physical dimensions before output. + +## 4. Width and height semantics + +From `specs.py`: + +- width can be `single`, `double`, or a numeric mm value +- the built-in registry contains `nature`, `science`, and `cell` +- height can be explicit `height_mm` +- otherwise height is derived from `aspect_ratio` + +That yields a clean rule for the skill: + +- if the user asks for publication width, use `save_figure(..., spec=..., width=...)` +- if the user only wants quick draft export, keep the recommendation minimal + +## 5. `batch_export(...)` + +`batch_export(...)` is the publication-aware multi-format lane. + +Source behavior: + +- it takes a `base_path` +- it accepts publication export controls such as `spec`, `width`, `height_mm`, `aspect_ratio`, and `dpi` +- appends each explicit suffix from `formats` +- relayouts the figure through `_export_with_publication_layout(...)` for each target format +- restores the original in-memory figure size/state after export + +This is the right recommendation when the user needs, for example: + +- `PDF` for manuscript submission +- `SVG` for downstream editing +- `PNG` for slides or issue threads + +Operational implication: + +- use `batch_export(...)` when the task needs multiple publication-style outputs from the same figure, +- do not describe it as a plain `savefig` loop. + +## 6. What `_save_basic_figure(...)` still does + +`_save_basic_figure(...)` is still relevant, but it is no longer the main multi-format path for `batch_export(...)`. + +It remains the lower-level path used for: + +- direct basic export helpers, +- size-preserving panel export in `export/panels.py`, +- and internal single-target save operations that do not need publication relayout. + +From the source, it also handles: + +- output directory creation +- vector-text rcParams (important for editable SVG/PDF text handling) +- post-layout legend alignment +- post-layout callbacks attached by plot code +- trim/tight bbox behavior + +So export quality is partially centralized in the export layer, not only inside plot modules. + +## 7. Panel export lane + +`export/panels.py` defines the multi-panel handoff path. + +Key components: + +- `PanelExportRecord` +- `export_panel(...)` +- `export_panels(...)` +- `_write_panel_index(...)` + +A `PanelExportRecord` stores: + +- `panel_id` +- `path` +- `format` +- `exported_at` +- `figma_node_name` +- `pubfig_version` +- optional `title` +- optional `label` + +This shows that panel export is not only file emission. It also preserves minimal sync metadata. + +## 8. Title stripping is intentional + +One subtle but important source behavior: + +- `_temporarily_strip_titles(...)` removes figure/axes titles during panel export by default unless `include_title=True` + +Operational implication: + +- panel-first composite assembly usually wants clean panel artwork, +- whole-figure titles and layout labels are often handled later, +- prefer exporting clean panel art first and adding whole-figure titles or layout labels downstream when needed. + +## 9. Publication-aware vs size-preserving panel export + +`export_panel(...)` has two modes: + +### Publication-aware mode + +Triggered when any of these are supplied: + +- `spec` +- `width` +- `height_mm` + +Then it delegates to `save_figure(...)`. + +### Size-preserving mode + +If none of those are supplied, it falls back to `_save_basic_figure(...)` and preserves the figure’s current size. + +Skill implication: + +- for reproducible paper panels, specify publication export parameters +- for design review or quick composition, preserving current size may be acceptable + +## 10. Multiple panel export + +`export_panels(...)` does three main things: + +1. normalize and validate panel ids, +2. resolve labels for each panel, +3. export each panel and optionally write `panel-index.json`. + +Default recommendation: + +- prefer this route when the user wants a structured panel directory rather than a single whole-figure asset. + +## 11. Overwrite and safety behavior + +From `_ensure_writable_target(...)`: + +- an existing panel file raises unless `overwrite=True` + +That is useful for skill guidance because it means refresh-in-place is an explicit decision. + +## 12. Recommended source-faithful export patterns + +### Single paper figure + +- plot with `pubfig.<chart_family>(...)` +- save with `save_figure(fig, 'out/figure1.pdf', spec='nature', width='single')` + +### Same figure in several formats + +- plot once +- export with `batch_export(fig, 'out/figure1', formats=('pdf', 'svg', 'png'), spec='nature', width='single', dpi=300)` + +### Multi-panel downstream assembly + +- generate each panel as a separate `Figure` +- export with `export_panels(...)` +- use the index file for composite/Figma-aware downstream handling diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-architecture.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-architecture.md new file mode 100644 index 0000000..051b090 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-architecture.md @@ -0,0 +1,216 @@ +# pubtab architecture (source-driven) + +This guide explains `pubtab` from the actual package layout under `pubtab/src/pubtab`. + +Core files: + +- `__init__.py` +- `cli.py` +- `models.py` +- `reader.py` +- `renderer.py` +- `config.py` +- `_preview.py` +- `tex_reader.py` +- `backends/` +- `themes/` + +## 1. Start at `pubtab.__init__` + +The public contract is defined in `__init__.py`. + +Public exports are intentionally small: + +- `xlsx2tex` +- `preview` +- `compile_pdf` +- `tex_to_excel` +- `SpacingConfig` + +This is the key architectural signal: `pubtab` exposes a compact API, while the real complexity is pushed into reader/renderer/preview internals. + +## 2. Core data model layer + +`models.py` defines the structured table representation. + +Important dataclasses: + +- `CellStyle` +- `Cell` +- `TableData` +- `SpacingConfig` +- `ThemeConfig` +- `BackendConfig` + +Source fact: + +- the shared structured representation is `TableData`, not raw Excel cells or raw LaTeX text. + +Forward and reverse conversions both pass through this structured table model. + +## 3. Forward pipeline: Excel to LaTeX + +The main forward path is: + +1. `xlsx2tex(...)` in `__init__.py` +2. `read_excel(...)` in `reader.py` +3. `render(...)` in `renderer.py` +4. optional preview through `_preview.py` + +This gives a clean source-driven decomposition: + +- `reader.py` = file ingestion and structure recovery +- `renderer.py` = LaTeX generation +- `_preview.py` = compile and raster preview + +## 4. Reverse pipeline: LaTeX to Excel + +The reverse path is: + +1. `tex_to_excel(...)` in `__init__.py` +2. `read_tex_multi(...)` from `tex_reader.py` +3. writer functions to `.xlsx` + +So roundtrip support is not an afterthought. It is a real architecture branch. + +## 5. `reader.py` is richer than a plain spreadsheet loader + +From the source, `reader.py` does much more than “read cells”: + +- supports `.xlsx` and `.xls` +- extracts rich text segments +- reconstructs merged cells and spans +- reads styling information +- trims only trailing globally empty columns +- reads pubtab metadata sheets +- restores group separators, multicolumn alignment hints, and math-script hints + +Interpretation from source: + +- `pubtab` is optimized for **publication table semantics**, rather than for plain tabular text dumping. + +## 6. `renderer.py` is the central logic hub + +`renderer.py` turns `TableData` into backend-specific LaTeX. + +From the source, it handles: + +- style/theme loading +- backend template loading +- spacing resolution +- column spec construction or projection +- tabular vs tabularray differences +- merged cells, row/column spans, header rules, vertical rules +- background colors and grouped separators +- final template rendering + +This file is where most of the difficult publication logic lives. + +For skill design, that means: + +- backend choice is not a cosmetic toggle +- column spec and rule behavior are structural concerns +- preview/render bugs usually require reading `renderer.py` + +## 7. Theme vs backend is a real split + +The codebase separates: + +- **themes** in `themes/` +- **LaTeX backends** in `backends/` + +That is reflected in two dataclasses: + +- `ThemeConfig` +- `BackendConfig` + +And in two loaders: + +- `load_theme(...)` +- `load_backend(...)` + +This is a major architectural point for the skill: + +- theme decides stylistic defaults, +- backend decides LaTeX environment/template behavior. + +Do not explain them as if they were the same thing. + +## 8. Config precedence is explicit + +In `xlsx2tex(...)`, the source implements a clear precedence order: + +1. hardcoded defaults +2. YAML config loaded by `config.py` +3. explicit function kwargs +4. in some roundtrip cases, values recovered from `TableData` + +This is why user-facing guidance should say “CLI flags or function kwargs override YAML config.” + +## 9. Multi-file and multi-sheet support are first-class + +From `__init__.py`: + +- directory input is supported for both forward and reverse paths +- sheet enumeration is supported when `sheet=None` +- multi-sheet export produces `*_sheetNN.tex` + +The default skill guidance can therefore recommend batch/file-driven workflows, not only one-table-at-a-time usage. + +## 10. Preview is a real compilation layer + +`preview(...)` and `compile_pdf(...)` in `__init__.py` delegate into `_preview.py`. + +That layer: + +- finds or installs `pdflatex` +- builds a standalone document +- compiles the output +- retries missing packages through `tlmgr` +- converts PDF to PNG when requested + +Preview is not a fake HTML-like snapshot. It is a real LaTeX compile pipeline. + +## 11. `tex_reader.py` closes the roundtrip loop + +`tex_reader.py` is substantial, not decorative. + +From the source it supports parsing of: + +- `tabular` +- `tblr` +- `longtblr` +- `talltblr` + +It also handles: + +- color parsing +- rule parsing +- multirow/multicolumn reconstruction +- metadata extraction +- grouped rows and placeholder cleanup + +This makes `pubtab` suitable for source-aware roundtrip and migration tasks, rather than only one-way Excel export. + +## 12. Reading order for source debugging + +When you need source-level certainty, use this order: + +1. `pubtab/src/pubtab/__init__.py` +2. `pubtab/src/pubtab/models.py` +3. `pubtab/src/pubtab/reader.py` +4. `pubtab/src/pubtab/renderer.py` +5. `pubtab/src/pubtab/_preview.py` +6. `pubtab/src/pubtab/tex_reader.py` +7. `pubtab/src/pubtab/backends/` and `themes/` +8. `pubtab/src/pubtab/cli.py` for flag-to-API mapping only + +## 13. Implications for this skill + +The source says the most faithful default workflow is: + +- use `xlsx2tex(...)` or CLI `xlsx2tex` for forward generation, +- use `preview(...)` to verify actual compile output, +- use `tex_to_excel(...)` for roundtrip or migration tasks, +- explain theme/backend separately, +- escalate into renderer/source debugging only when table structure or LaTeX behavior is the real problem. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-backend-and-preview.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-backend-and-preview.md new file mode 100644 index 0000000..6c891c3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-backend-and-preview.md @@ -0,0 +1,201 @@ +# pubtab backend and preview internals (source-driven) + +This guide focuses on the two most important deeper layers in `pubtab`: + +- backend/theme separation +- real preview/compile execution + +Primary source files: + +- `pubtab/src/pubtab/themes/__init__.py` +- `pubtab/src/pubtab/backends/__init__.py` +- `pubtab/src/pubtab/renderer.py` +- `pubtab/src/pubtab/_preview.py` + +## 1. Theme and backend are different contracts + +The source separates them cleanly. + +### Theme layer + +In `themes/__init__.py`, a theme resolves to `ThemeConfig`. + +It carries style defaults such as: + +- `column_sep` +- `font_size` +- `caption_position` +- `SpacingConfig` + +### Backend layer + +In `backends/__init__.py`, a backend resolves to: + +- `BackendConfig` +- a Jinja template string + +`BackendConfig` carries things like: + +- package requirements +- preamble hints +- backend identity + +Operational implication: + +- theme = stylistic defaults +- backend = LaTeX environment/template machinery + +## 2. Legacy normalization exists, but it is not the conceptual model + +The source still supports legacy composite theme names like `_tabularray` suffixed themes. + +Normalization happens in places like: + +- `_normalize_theme_backend_choice(...)` +- `resolve_theme(...)` + +But that compatibility layer should not define the skill’s main explanation. +The current conceptual model is still **separate theme + backend**. + +## 3. What `render(...)` actually does + +`renderer.py` is the core place where theme/backend decisions become concrete LaTeX. + +Inside `render(...)`, the source does roughly this: + +1. normalize theme/backend choice +2. load theme config +3. load backend config and template +4. merge default/theme/user spacing +5. compute or project column specs +6. branch into backend-specific row/cell rendering +7. render through Jinja + +Backend choice changes the internal rendering algorithm, not only the final environment name. + +## 4. `tabular` vs `tabularray` from the source perspective + +The source suggests this practical distinction: + +### `tabular` + +- more classic LaTeX path +- column spec and rules are handled in the traditional environment +- when source `column_spec` exists, renderer tries to preserve classic rule structure + +### `tabularray` + +- dedicated `tblr`-style rendering path +- special handling for promoted vertical lines and grouped header boundaries +- extra sanitization in preview compile path + +Interpretation from source: + +- `tabularray` is a distinct renderer path with its own structural handling, not merely a cosmetic wrapper around `tabular`. + +## 5. Why backend choice sometimes matters a lot + +From `renderer.py`, backend differences affect: + +- how colspec is interpreted +- how vertical rules are preserved or promoted +- how merged cells are encoded +- how row coloring and header boundaries are emitted + +So if a table is structurally complex, the skill should not present backend choice as arbitrary. + +## 6. Preview is a real LaTeX toolchain + +`_preview.py` proves preview is a full execution pipeline. + +Major steps: + +1. locate `pdflatex` +2. install TinyTeX if missing +3. build a standalone document around the table +4. compile with `pdflatex` +5. auto-install missing LaTeX packages when possible +6. return PDF or convert to PNG + +Preview is therefore a genuine verification step. + +## 7. `pdflatex` discovery and TinyTeX fallback + +The source checks: + +- system `PATH` +- pubtab-managed TinyTeX under `~/.pubtab/TinyTeX` + +If neither exists, it installs TinyTeX automatically. + +This is why the skill can confidently describe preview as relatively self-healing, while still warning that first-run setup may download TeX assets. + +## 8. Missing package retry + +A particularly important source behavior: + +- compile logs are scanned for missing `.sty` +- missing style names are mapped to `tlmgr` package names when needed +- `tlmgr install <pkg>` is run automatically +- compilation is retried + +This is strong evidence that the recommended workflow should include preview, because preview can repair part of the environment on the way. + +## 9. Standalone preview wrapping + +`_build_standalone(...)` does more than wrap text in a document. + +It also: + +- imports backend-required packages +- preserves setup commands outside the `resizebox` body +- wraps the body in a preview-friendly standalone/minipage layout +- converts `\caption{...}` into `\captionof{table}{...}` during float stripping + +This explains why preview output can differ from naive manual compilation if the user simply pastes a table fragment into a document incorrectly. + +## 10. `tabularray` preview sanitization + +Before compilation, `_sanitize_tblr_for_compile(...)` removes some commands that break inside `tblr` preview contexts, including certain row-color and `\cmidrule` forms. + +So when debugging preview-vs-final-document differences, this source behavior matters. + +## 11. PDF to PNG conversion fallback stack + +For PNG previews, the source tries: + +1. `pdf2image` +2. fallback to PyMuPDF (`fitz`) + +Preview generation remains resilient even after PDF compilation succeeds. + +## 12. Practical skill guidance from the source + +### Recommend `tabular` when + +- the table is simple/classic, +- the user wants conservative LaTeX output, +- compatibility matters more than modern layout features. + +### Recommend `tabularray` when + +- grouped headers and more complex structural layouts matter, +- the user is already targeting a `tblr`-capable workflow, +- the roundtrip/source table has rule structure that benefits from the dedicated renderer path. + +### Recommend preview almost always when + +- the table is intended for publication, +- the user is changing backend/theme/colspec, +- the task involves debugging table layout, +- the task depends on compile-time package correctness. + +## 13. Failure triage order + +When the generated table is wrong, debug in this order: + +1. check theme/backend choice, +2. inspect `render(...)` inputs (`TableData`, colspec, span settings), +3. run preview/compile, +4. inspect missing package or backend-specific compile issues, +5. only then move into manuscript-level integration debugging. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-cli-api-flow.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-cli-api-flow.md new file mode 100644 index 0000000..cc0bc18 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/source-guides/pubtab-cli-api-flow.md @@ -0,0 +1,178 @@ +# pubtab CLI and API flow (source-driven) + +This guide follows the actual control flow from `pubtab/src/pubtab/cli.py` into the public API and then into the internal pipeline. + +## 1. Architectural headline + +`cli.py` is a **thin Click wrapper** over the public API in `pubtab.__init__`. + +Operational implication: + +- command-line behavior should usually match Python API behavior, +- when docs disagree, the source of truth is `pubtab.__init__`, not CLI help text alone. + +## 2. CLI commands exposed in `cli.py` + +The main commands are: + +- `pubtab xlsx2tex` +- `pubtab themes` +- `pubtab tex2xlsx` +- `pubtab preview` + +There is also a hidden backward-compatible alias: + +- `convert` -> `xlsx2tex` + +## 3. `xlsx2tex` command flow + +CLI entrypoint: + +- `xlsx2tex_cmd(...)` in `cli.py` + +Control flow: + +1. validate input/output shape +2. coerce `--sheet` into int when possible +3. build kwargs only for explicitly provided options +4. call `pubtab.xlsx2tex(input_file, output, **kwargs)` +5. print output summary based on sheet count and preview mode + +This thin-wrapper design matters because the CLI does **not** reimplement conversion logic. + +## 4. `xlsx2tex(...)` API flow + +The public API in `__init__.py` adds the real orchestration: + +### Input modes + +- single Excel file +- directory of Excel files +- single sheet +- all sheets (`sheet=None`) + +### Output path behavior + +- single-sheet export can target a direct `.tex` path +- directory input must target a directory +- multi-sheet export uses `*_sheetNN.tex` + +This behavior is implemented by `_build_sheet_output_paths(...)` and directory iteration helpers. + +## 5. Config precedence in the real API + +Inside `xlsx2tex(...)`, the source builds parameters in this order: + +1. defaults +2. YAML config via `load_config(...)` +3. explicit kwargs passed from CLI or Python +4. roundtrip-restored values where relevant + +Operational rule: + +- YAML config sets baseline behavior, +- CLI flags / Python kwargs override it. + +## 6. Sheet expansion behavior + +When `sheet is None`, the source does not simply choose the first sheet. +It calls `list_excel_sheets(...)` and expands all sheet names into separate outputs. + +That is why a single workbook can generate: + +- `table_sheet01.tex` +- `table_sheet02.tex` +- ... + +The skill should explicitly mention this when users want appendix exports or workbook-wide conversion. + +## 7. Read -> render -> write flow + +For each selected sheet, `xlsx2tex(...)` does: + +1. `read_excel(...)` +2. optional header or group-separator reconstruction +3. `render(...)` +4. write `.tex` +5. optional preview generation to `.png` + +Preview is downstream of actual `.tex` generation, not an alternate renderer. + +## 8. `preview` command flow + +CLI entrypoint: + +- `preview_cmd(...)` + +The CLI again mostly validates paths and forwards to `pubtab.preview(...)`. + +The public `preview(...)` API supports: + +- raw LaTeX content +- a single `.tex` file +- a directory of `.tex` files +- `png` or `pdf` output + +A key source detail: when backend is omitted, `preview(...)` may infer it from the LaTeX content using `_resolve_preview_inputs(...)`. + +## 9. Backend inference path + +`_infer_latex_backend(...)` checks for environments like: + +- `tblr` +- `longtblr` +- `talltblr` + +If found, backend becomes `tabularray`; otherwise `tabular`. + +Operational implication: + +- a preview or compile call can often resolve the correct backend without requiring an explicit `--latex-backend` flag. + +## 10. `compile_pdf(...)` API flow + +Public `compile_pdf(...)` in `__init__.py` does: + +1. detect whether input is raw LaTeX or a file path, +2. infer theme/backend if needed, +3. delegate to `_preview.compile_pdf(...)`. + +The compile path is still part of the public API, even though the heavy lifting is in `_preview.py`. + +## 11. `tex2xlsx` command flow + +CLI entrypoint: + +- `tex2xlsx(...)` in `cli.py` + +It forwards to `pubtab.tex_to_excel(...)`. + +The public API then handles: + +- single `.tex` file -> one `.xlsx` +- multi-table `.tex` -> one workbook with multiple sheets +- directory of `.tex` files -> one `.xlsx` per file + +This keeps the reverse path operationally symmetric with the forward path. + +## 12. Why the CLI should stay thin in this skill + +Because the real logic is centralized in `pubtab.__init__`, the skill should: + +- use CLI examples for file-driven shell workflows, +- use Python API examples for notebooks or scripted pipelines, +- avoid duplicating pseudo-logic that already exists in the library. + +## 13. Recommended source-faithful routing + +### Use CLI when + +- the user already has Excel or `.tex` files on disk, +- the task is batch conversion, +- the user wants a terminal-first workflow. + +### Use Python API when + +- the user is in a notebook or script, +- the table needs custom preprocessing before render, +- the agent is composing a larger Python pipeline. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/workflow.md b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/workflow.md new file mode 100644 index 0000000..15c523b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/references/workflow.md @@ -0,0 +1,82 @@ +# Workflow + +## Default decision order + +1. Identify the scientific communication goal. +2. Probe the environment and available assets lightly. +3. Decide whether the evidence should be a figure, a table, or a paired figure+table deliverable. +4. Choose the strongest representation family. +5. Route to `pubfig`, `pubtab`, or both. +6. Produce the smallest runnable implementation. +7. Specify export outputs explicitly. +8. Run publication QA. +9. Propose revisions if the result is weak. + +## Handoff checklist + +For every task, try to make these explicit: + +- claim the artifact is supposed to support +- data shape and grouping structure +- target audience or venue expectations +- figure vs table role +- exact output filenames and formats +- whether the artifact is final, draft, or revision +- whether the current environment can execute the proposed route immediately + +## Delivery contract + +A strong response should make clear: + +- which artifact type was chosen, +- why it was chosen, +- which tool owns each artifact, +- what the first runnable command/code path is, +- what output files should be produced, +- what still needs user input or upstream data. + +## Default output priorities + +Prioritize in this order: + +1. clarity of claim +2. correct artifact type +3. minimal runnable implementation +4. publication-ready export +5. QA and revision guidance + +## Graceful degradation when tools are missing + +If `pubfig` or `pubtab` is not installed: + +- keep the workflow going, +- provide installation guidance, +- provide pseudocode or draft commands, +- specify the recommended artifact structure, +- preserve the QA and revision guidance. + +## Figure / table split rules + +Use a **figure** when the reader needs to quickly perceive: + +- trend +- distribution shape +- relationship +- calibration or diagnostic behavior +- composition or hierarchy +- visual comparison across a moderate number of groups + +Use a **table** when the reader needs: + +- exact numbers +- many metrics side by side +- benchmark grids +- ablation matrices +- appendix-style detail +- reproducible value lookup + +Use **both** when: + +- the figure carries the visual claim, +- the table preserves exact values, +- or the paper section benefits from a fast visual summary plus precise numeric evidence. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/scripts/ensure_publication_tooling.py b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/scripts/ensure_publication_tooling.py new file mode 100755 index 0000000..6a422ac --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/publication-chart-skill/scripts/ensure_publication_tooling.py @@ -0,0 +1,172 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import importlib +import json +import shutil +import subprocess +import sys +from dataclasses import asdict, dataclass +from pathlib import Path +from typing import Sequence + + +@dataclass(frozen=True) +class PackageStatus: + package: str + available: bool + version: str | None = None + error: str | None = None + + +@dataclass(frozen=True) +class InstallPlan: + installer: str + command: tuple[str, ...] + + +DEFAULT_PACKAGES: tuple[str, ...] = ("pubfig", "pubtab") + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser( + description="Probe and force-install pubfig/pubtab into the active Python environment." + ) + parser.add_argument( + "--require", + dest="packages", + action="append", + choices=DEFAULT_PACKAGES, + help="Package that must be available. Defaults to pubfig + pubtab.", + ) + parser.add_argument( + "--prefer", + choices=("auto", "uv", "pip"), + default="auto", + help="Installer selection policy. Default: auto.", + ) + parser.add_argument( + "--cwd", + type=Path, + default=Path.cwd(), + help="Project directory used for uv-managed detection. Default: current directory.", + ) + parser.add_argument( + "--json", + action="store_true", + help="Print machine-readable JSON summary.", + ) + return parser.parse_args() + + +def probe_package(package: str) -> PackageStatus: + try: + module = importlib.import_module(package) + except Exception as exc: # noqa: BLE001 + return PackageStatus(package=package, available=False, error=f"{type(exc).__name__}: {exc}") + + version = getattr(module, "__version__", None) + return PackageStatus(package=package, available=True, version=str(version) if version else None) + + +def is_uv_managed(cwd: Path) -> bool: + for candidate in [cwd, *cwd.parents]: + if (candidate / "uv.lock").exists(): + return True + pyproject = candidate / "pyproject.toml" + if pyproject.exists(): + try: + text = pyproject.read_text(encoding="utf-8") + except OSError: + continue + if "[tool.uv" in text or "uv_build" in text: + return True + return False + + +def choose_installer(prefer: str, cwd: Path) -> str: + if prefer in {"uv", "pip"}: + return prefer + if shutil.which("uv") and is_uv_managed(cwd): + return "uv" + return "pip" + + +def build_install_plan(installer: str, package: str) -> InstallPlan: + if installer == "uv": + command = ("uv", "pip", "install", "--python", sys.executable, package) + else: + command = (sys.executable, "-m", "pip", "install", package) + return InstallPlan(installer=installer, command=command) + + +def run_command(command: Sequence[str]) -> subprocess.CompletedProcess[str]: + return subprocess.run(command, check=False, text=True, capture_output=True) + + +def emit_text( + before: list[PackageStatus], + after: list[PackageStatus], + attempts: list[dict[str, object]], +) -> None: + print("[publication-chart-skill] environment summary") + print(f"python: {sys.executable}") + print("before:") + for status in before: + suffix = f" ({status.version})" if status.version else "" + detail = f" - {status.error}" if status.error else "" + print(f" - {status.package}: {'available' if status.available else 'missing'}{suffix}{detail}") + if attempts: + print("install attempts:") + for attempt in attempts: + print(f" - {attempt['package']}: {attempt['command']} -> exit {attempt['returncode']}") + print("after:") + for status in after: + suffix = f" ({status.version})" if status.version else "" + detail = f" - {status.error}" if status.error else "" + print(f" - {status.package}: {'available' if status.available else 'missing'}{suffix}{detail}") + + +def main() -> int: + args = parse_args() + packages = tuple(dict.fromkeys(args.packages or DEFAULT_PACKAGES)) + before = [probe_package(package) for package in packages] + missing = [status.package for status in before if not status.available] + installer = choose_installer(args.prefer, args.cwd.resolve()) + + attempts: list[dict[str, object]] = [] + for package in missing: + plan = build_install_plan(installer=installer, package=package) + result = run_command(plan.command) + attempts.append( + { + "package": package, + "installer": plan.installer, + "command": " ".join(plan.command), + "returncode": result.returncode, + "stdout": result.stdout.strip(), + "stderr": result.stderr.strip(), + } + ) + + after = [probe_package(package) for package in packages] + payload = { + "python": sys.executable, + "installer": installer, + "before": [asdict(status) for status in before], + "attempts": attempts, + "after": [asdict(status) for status in after], + "ok": all(status.available for status in after), + } + + if args.json: + print(json.dumps(payload, indent=2, ensure_ascii=False)) + else: + emit_text(before=before, after=after, attempts=attempts) + + return 0 if payload["ok"] else 1 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/SKILL.md new file mode 100644 index 0000000..c389b2d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/SKILL.md @@ -0,0 +1,209 @@ +--- +name: research-ideation +description: This skill should be used when the user asks to "brainstorm research ideas", "use 5W1H framework", "identify research gaps", "conduct gap analysis", "start research project", "conduct literature review", "define research question", "select research method", "plan research", or mentions research project initiation phase. Provides comprehensive guidance for research startup workflow from idea generation to planning. +version: 0.1.0 +--- + +# Research Ideation + +Supports the complete workflow for the research project initiation phase, from vague idea to a traceable research contract: research question, hypothesis, evidence needs, falsification criteria, method selection, and next action. + +## Core Features + +### 1. Idea Brainstorming (5W1H Framework) + +Systematically brainstorm research ideas using the 5W1H framework: +- **What**: What problem or phenomenon to study +- **Why**: Why this problem is important +- **Who**: Target audience and stakeholders +- **When**: Time scope and context of the research +- **Where**: Application scenarios and domains +- **How**: Preliminary research methodology ideas + +**Integration with superpowers:brainstorming**: Can invoke the superpowers:brainstorming skill for interactive brainstorming to help rapidly generate and evaluate research ideas. + +### 2. Literature Review + +Systematically search, analyze, and synthesize related literature: +- Build effective search keywords +- Search via WebSearch across academic databases (arXiv, Google Scholar, etc.) +- Screen and evaluate paper quality +- Identify research trends and gaps +- Generate structured literature reviews from evidence-labeled sources +- **Zotero Integration**: Papers are automatically added to Zotero via DOI, organized into topic-based collections, and open-access PDFs are auto-attached for full-text reading + +### 3. Gap Analysis + +Systematically identify and evaluate research gaps: +- **Literature gaps**: Identify topics or questions not yet sufficiently studied +- **Methodological gaps**: Discover limitations and improvement opportunities in existing methods +- **Application gaps**: Identify opportunities for theory-to-practice transfer +- **Interdisciplinary gaps**: Discover research opportunities at the intersection of different fields +- **Temporal gaps**: Identify new research needs arising from changes over time + +**Analysis Dimensions:** +- Coverage of research topics +- Comparison of strengths and weaknesses of existing methods +- Completeness of experimental setups +- Availability of datasets and benchmarks +- Gap between theory and practice + +### 4. Research Question Definition + +Formulate specific research questions based on literature analysis: +- Identify research gaps and opportunities +- Apply SMART principles to formulate questions +- Evaluate importance, novelty, and feasibility +- Define research objectives and expected contributions +- Write a `Research Question Card` that states the hypothesis, current evidence, missing evidence, support criteria, falsification criteria, and minimal next action +- Apply the proposal readiness gate before turning a card into a polished proposal + +### 5. Method Selection + +Select appropriate research methods: +- Analyze strengths and weaknesses of existing methods +- Evaluate method applicability +- Identify required technologies and resources +- Consider method feasibility + +### 6. Research Planning + +Develop detailed research plans: +- Plan research timeline +- Define milestones and deliverables +- Identify potential risks +- Assess resource requirements + +## When to Use + +### Scenarios for This Skill + +Use the research-ideation skill in the following situations: + +1. **Starting a new research project** - Have research interests but no clear research question yet +2. **Literature review** - Need to systematically understand a research field +3. **Research question formulation** - Need to transform vague ideas into specific research questions +4. **Method selection** - Need to choose appropriate research methods and technical approaches +5. **Research planning** - Need to plan research timeline and resources + +### Typical Workflow + +``` +Research interest → Idea brainstorming (5W1H) → Research Question Card → Evidence Records → Gap analysis → Proposal readiness gate → Select method or experiment → Decision +``` + +**Conditional Outputs:** +- `research-question-card.md` - Always generate this for research startup or intake. +- `literature-review.md` - Generate only when evidence-labeled sources are sufficient for synthesis. +- `research-proposal.md` - Generate only when a selected Research Question Card passes the evidence gate. +- `references.bib` - Generate only when reliable citation metadata exists. +- Zotero collection with organized papers and PDFs - Create only when Zotero is configured, writable, and the user is not asking for dry-run/audit mode. + +## Integration with Other Systems + +### Complete Research Workflow + +``` +research-ideation (Research initiation) + ↓ +Experiment execution (completed by user) + ↓ +results-analysis (Results analysis) + ↓ +ml-paper-writing (Paper writing) +``` + +### Data Flow + +- **Research Question Card** → Guides literature scope, experiment design, and method selection +- **Evidence Records** → Carry source type, claim strength, and allowed/forbidden wording into literature synthesis, project knowledge, and later claim audit +- **Proposal Readiness Gate** → Prevents abstract-only or webpage-placeholder evidence from becoming a polished proposal +- **Experimental results** → results-analysis for statistical analysis and claim candidates +- **Analysis results** → results-report and ml-paper-writing with explicit evidence limits + +### Zotero Integration + +Through the Zotero MCP server, the research-ideation workflow automates literature management: + +- **Paper Discovery**: WebSearch finds relevant papers across academic databases +- **Auto-Import**: Extract DOI / arXiv ID / landing-page URLs from search results, then use `zotero_add_items_by_identifier` to prefer paper/preprint imports before any webpage fallback +- **Collection Organization**: `zotero_create_collection` creates topic-based collections with standard sub-collections (Core Papers, Methods, Applications, Baselines, To-Read) +- **PDF Attachment**: `zotero_add_items_by_identifier(..., attach_pdf=true)` runs a PDF cascade (landing-page PDF hints → direct PDF → Unpaywall), and `zotero_find_and_attach_pdfs` can be used as a follow-up sweep for remaining items +- **Full-Text Reading**: `zotero_get_item_fulltext` reads indexed PDF content for analysis and note-taking +- **Library Search**: `zotero_search_items` and `zotero_get_collection_items` browse existing papers to avoid duplicates + +### Key Configuration + +- **Literature search scope**: Papers from the last 3 years by default, configurable +- **Output format**: Markdown format for easy editing and version control +- **Citation management**: Generates references in BibTeX format +- **Zotero collection naming**: `Research-{topic}-{YYYY}` format +- **PDF auto-attach**: Enabled by default for open-access papers via Unpaywall + +## Additional Resources + +### Reference Files + +Detailed methodology guides, loaded on demand: + +- **`references/5w1h-framework.md`** - 5W1H Framework Guide + - What, Why, Who, When, Where, How — six dimensions + - Systematic approach to brainstorming research ideas + - Integration with superpowers:brainstorming + - Usage examples and best practices + +- **`references/literature-search-strategies.md`** - Literature Search Strategies + - Keyword construction techniques + - Academic database selection (arXiv, Google Scholar) + - Search tips and screening criteria + - Paper quality evaluation methods + - DOI extraction and Zotero auto-import workflow + +- **`references/zotero-integration-guide.md`** - Zotero MCP Integration Guide + - Available Zotero MCP tools (browse, add, cite) + - Collection organization strategy and naming conventions + - Automated workflow: WebSearch → DOI → Zotero import → PDF attach + - Full-text reading and structured note-taking + - Common issues and troubleshooting + +- **`references/gap-analysis-guide.md`** - Gap Analysis Guide + - 5 types of Gap Analysis (literature, methodological, application, interdisciplinary, temporal) + - 5 analysis dimensions + - Systematic approach to identifying research opportunities + - Usage examples and best practices + +- **`references/research-question-formulation.md`** - Research Question Formulation + - Applying SMART principles + - Question type classification (exploratory, confirmatory, applied) + - Evaluation criteria (importance, novelty, feasibility) + - Defining research objectives and contributions + +- **`references/research-contract.md`** - Research Contract + - Research Question Card template + - Evidence Record template + - Claim Candidate template + - Claim strength rules + +- **`references/method-selection-guide.md`** - Method Selection Guide + - Common research method classification + - Method applicability analysis + - Strengths and weaknesses comparison + - Resource requirement assessment + +- **`references/research-planning.md`** - Research Planning + - Timeline planning methods + - Milestone definition techniques + - Risk identification and mitigation + - Resource allocation strategies + +### Example Files + +Complete working examples: + +- **`examples/example-literature-review.md`** - Literature Review Example + - Demonstrates structured literature review format + - Includes research trend analysis and gap identification + +- **`examples/example-research-proposal.md`** - Research Proposal Example + - Demonstrates complete research proposal structure + - Includes complete examples of question, method, and plan diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/examples/example-literature-review.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/examples/example-literature-review.md new file mode 100644 index 0000000..4b4e79e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/examples/example-literature-review.md @@ -0,0 +1,120 @@ +# 文献综述示例：Transformer 模型可解释性研究 + +## 研究主题 + +本文献综述聚焦于 Transformer 模型的可解释性研究，特别是注意力机制的解释和理解。 + +## 1. 引言 + +### 1.1 研究背景 + +Transformer 模型自 2017 年提出以来，已成为自然语言处理领域的主流架构。然而，其内部工作机制仍然不够透明，限制了模型的可信度和在关键应用中的部署。 + +### 1.2 研究重要性 + +**学术价值**： +- 深入理解深度学习模型的工作原理 +- 为模型改进提供理论指导 +- 推动可解释 AI 领域发展 + +**实际价值**： +- 提高模型可信度 +- 辅助模型调试和优化 +- 满足监管和伦理要求 + +### 1.3 综述范围 + +本综述涵盖 2020-2024 年间发表的相关工作，重点关注： +- 注意力机制的可视化和分析 +- 模型内部表示的探测 +- 可解释性评估方法 +- 应用案例研究 + +## 2. 主要研究方向 + +### 2.1 注意力可视化方法 + +**代表性工作**： + +**Clark et al. (2019) - "What Does BERT Look At?"** +- 会议：ACL 2019 +- 贡献：系统分析 BERT 的注意力模式 +- 发现：不同层的注意力关注不同语言现象 +- 引用次数：1200+ + +**Vig (2019) - "A Multiscale Visualization of Attention"** +- 会议：ACL 2019 Demo +- 贡献：开发交互式注意力可视化工具 +- 工具：BertViz（开源） +- 影响：广泛使用的可视化工具 + +**主要发现**： +- 早期层关注句法结构 +- 中间层关注语义关系 +- 后期层关注任务相关特征 + +### 2.2 模型探测方法 + +**代表性工作**： + +**Tenney et al. (2019) - "BERT Rediscovers the Classical NLP Pipeline"** +- 会议：ACL 2019 +- 贡献：使用探测任务分析 BERT 的语言知识 +- 方法：Edge probing tasks +- 发现：BERT 隐式学习了传统 NLP 流程 + +**Rogers et al. (2020) - "A Primer on BERTology"** +- 期刊：TACL 2020 +- 贡献：系统综述 BERT 的可解释性研究 +- 影响：成为该领域的重要参考文献 +- 引用次数：800+ + +**主要发现**： +- 模型学习了丰富的语言知识 +- 不同层编码不同层次的信息 +- 知识分布在多个层中 + +## 3. 研究趋势与空白 + +### 3.1 当前研究趋势 + +**从静态分析到动态分析**： +- 早期工作主要分析训练好的模型 +- 近期工作开始关注训练过程中的动态变化 + +**从单一方法到综合方法**： +- 结合多种可解释性技术 +- 跨层次、跨模态的分析 + +**从理解到应用**： +- 将可解释性用于模型改进 +- 辅助模型调试和优化 + +### 3.2 研究空白 + +**理论基础不足**： +- 缺乏统一的可解释性理论框架 +- 注意力权重与模型行为的因果关系不明确 + +**评估标准缺失**： +- 缺乏标准化的评估方法 +- 人类评估成本高且主观性强 + +**长文本处理**： +- 现有方法主要针对短文本 +- 长文本的注意力模式更复杂 + +## 4. 总结 + +本综述系统梳理了 Transformer 模型可解释性研究的主要方向和代表性工作。主要发现包括： + +1. **注意力机制**：不同层关注不同语言现象，但注意力权重不能完全解释模型行为 +2. **内部表示**：模型隐式学习了丰富的语言知识，分布在多个层中 +3. **研究空白**：理论基础、评估标准、长文本处理等方面仍需深入研究 + +**未来研究方向**： +- 建立统一的可解释性理论框架 +- 开发标准化的评估方法 +- 探索长文本的可解释性 +- 将可解释性用于模型改进 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/examples/example-research-proposal.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/examples/example-research-proposal.md new file mode 100644 index 0000000..d0a0acd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/examples/example-research-proposal.md @@ -0,0 +1,209 @@ +# 研究提案示例：基于稀疏注意力的长文本 Transformer + +## 研究主题 + +开发一种新的稀疏注意力机制，使 Transformer 模型能够高效处理长文本（10k+ tokens），同时保持或提升性能。 + +## 1. 研究问题 + +### 1.1 核心问题 + +**如何设计一种稀疏注意力机制，使 Transformer 能够在保持性能的同时，将计算复杂度从 O(n²) 降低到 O(n log n)？** + +### 1.2 子问题 + +1. 哪些注意力连接对模型性能最重要？ +2. 如何自适应地选择重要的注意力连接？ +3. 稀疏化对不同任务的影响如何？ +4. 如何在训练和推理中高效实现稀疏注意力？ + +## 2. 研究目标 + +### 2.1 主要目标 + +1. **方法创新**：提出新的自适应稀疏注意力机制 +2. **性能提升**：在长文本任务上达到或超越现有方法 +3. **效率提升**：将计算和内存成本降低 50% 以上 +4. **理论理解**：分析稀疏化对模型能力的影响 + +### 2.2 预期贡献 + +**学术贡献**： +- 新的稀疏注意力机制设计 +- 长文本处理的理论分析 +- 开源实现和预训练模型 + +**实际价值**： +- 降低长文本处理成本 +- 使更长的上下文成为可能 +- 提高推理速度 + +## 3. 研究方法 + +### 3.1 核心思路 + +**自适应稀疏注意力**： +- 动态选择重要的注意力连接 +- 保留局部注意力（相邻 tokens） +- 学习全局注意力模式 +- 任务自适应的稀疏化策略 + +### 3.2 技术方案 + +**阶段 1：稀疏模式设计** +- 分析现有稀疏模式（Longformer, BigBird） +- 设计新的自适应选择机制 +- 理论分析复杂度和表达能力 + +**阶段 2：模型实现** +- 实现高效的稀疏注意力算子 +- 集成到 Transformer 架构 +- 优化训练和推理效率 + +**阶段 3：实验验证** +- 在多个长文本任务上评估 +- 与现有方法对比 +- 消融实验分析 + +## 4. 实验计划 + +### 4.1 数据集 + +| 任务 | 数据集 | 序列长度 | 评估指标 | +|------|--------|---------|---------| +| 文档分类 | Hyperpartisan | 4k-16k | F1 | +| 问答 | NarrativeQA | 8k-32k | F1, EM | +| 摘要 | arXiv | 4k-8k | ROUGE | + +### 4.2 基线方法 + +- **Vanilla Transformer**：标准 Transformer（作为上界） +- **Longformer**：固定稀疏模式 +- **BigBird**：随机+全局+局部 +- **Reformer**：LSH 注意力 + +### 4.3 评估维度 + +**性能**： +- 任务准确率 +- 与基线对比 + +**效率**： +- 训练时间 +- 推理速度 +- 内存占用 + +**可扩展性**： +- 不同序列长度的表现 +- 参数量的影响 + +## 5. 时间线规划 + +### 5.1 研究阶段划分 + +**Phase 1: 准备阶段**（第1-2个月） +- 文献调研和综述 +- 问题定义和方法设计 +- 初步实验环境搭建 +- **里程碑**：研究提案完成 + +**Phase 2: 探索阶段**（第3-4个月） +- 稀疏模式设计和理论分析 +- 初步实现和概念验证 +- 小规模实验验证可行性 +- **里程碑**：概念验证完成 + +**Phase 3: 开发阶段**（第5-7个月） +- 完整模型实现 +- 优化训练和推理效率 +- 在多个数据集上进行实验 +- **里程碑**：完整实验结果 + +**Phase 4: 完成阶段**（第8-9个月） +- 消融实验和深入分析 +- 论文撰写和修改 +- 代码整理和开源准备 +- **里程碑**：论文投稿 + +### 5.2 关键检查点 + +**月度检查**： +- 进度回顾和问题识别 +- 实验结果分析 +- 计划调整 + +**季度评审**： +- 里程碑评估 +- 风险评估和应对 +- 资源需求调整 + +## 6. 资源需求 + +### 6.1 计算资源 + +**GPU 需求**： +- 探索阶段：2-4 GPU（V100 或 A100） +- 开发阶段：4-8 GPU +- 完成阶段：8-16 GPU（大规模实验） + +**存储需求**： +- 数据集：200 GB +- 模型检查点：100 GB +- 实验日志：50 GB +- 总计：约 350 GB + +**预计计算时间**： +- 模型训练：约 500 GPU 小时 +- 实验评估：约 200 GPU 小时 +- 总计：约 700 GPU 小时 + +### 6.2 人力资源 + +**研究负责人**（1人）： +- 研究规划和指导 +- 论文撰写 +- 时间投入：50% + +**研究助理**（1-2人）： +- 实验实现和运行 +- 数据分析 +- 时间投入：100% + +### 6.3 其他资源 + +**数据集**： +- Hyperpartisan（公开） +- NarrativeQA（公开） +- arXiv（公开） + +**软件工具**： +- PyTorch +- Transformers +- Weights & Biases（实验跟踪） + +## 7. 总结 + +本研究提案旨在开发一种新的自适应稀疏注意力机制，解决 Transformer 在长文本处理中的效率问题。 + +**核心创新**： +- 自适应选择重要的注意力连接 +- 将计算复杂度从 O(n²) 降低到 O(n log n) +- 在保持性能的同时提高效率 + +**预期成果**： +- 在长文本任务上达到或超越现有方法 +- 将计算和内存成本降低 50% 以上 +- 开源实现和预训练模型 + +**可行性**： +- 基于成熟的 Transformer 架构 +- 有充足的计算资源支持 +- 9个月的研究周期合理 +- 团队具备相关技术背景 + +**影响力**： +- 学术贡献：新的稀疏注意力机制和理论分析 +- 实际价值：降低长文本处理成本，使更长的上下文成为可能 + +本研究具有明确的目标、可行的方法和充足的资源支持，预期能够产生有价值的学术成果和实际应用。 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/5w1h-framework.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/5w1h-framework.md new file mode 100644 index 0000000..d584134 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/5w1h-framework.md @@ -0,0 +1,162 @@ +# 5W1H Framework for Research Ideation + +## 概述 + +5W1H 框架是一个系统化的思维工具，帮助研究者从多个维度构思和评估研究想法。通过回答6个关键问题，可以快速建立对研究主题的全面理解。 + +## 框架组成 + +### What (什么) + +**核心问题**: 研究什么问题或现象？ + +**思考维度**: +- 具体的研究对象是什么 +- 要解决的核心问题是什么 +- 研究的范围和边界在哪里 +- 预期的研究成果是什么 + +**示例**: +- "研究 Transformer 模型的可解释性" +- "探索少样本学习在医疗图像分析中的应用" +- "分析强化学习中的样本效率问题" + + +### Why (为什么) + +**核心问题**: 为什么这个问题重要？ + +**思考维度**: +- 这个问题的学术价值是什么 +- 解决这个问题有什么实际意义 +- 当前研究的局限性是什么 +- 为什么现在是研究这个问题的好时机 + +**评估标准**: +- **学术重要性**: 是否推动领域发展 +- **实际影响**: 是否解决真实问题 +- **时效性**: 是否符合当前研究趋势 +- **可行性**: 是否有足够的资源和技术支持 + +### Who (谁) + +**核心问题**: 目标受众和利益相关者是谁？ + +**思考维度**: +- 谁会关心这个研究 +- 谁会使用研究成果 +- 谁会从中受益 +- 需要与谁合作 + +**利益相关者分类**: +- **学术界**: 同领域研究者、审稿人、引用者 +- **工业界**: 产品团队、工程师、决策者 +- **用户**: 最终使用者、受影响群体 +- **合作者**: 导师、同事、跨学科专家 + +### When (何时) + +**核心问题**: 研究的时间范围和背景是什么？ + +**思考维度**: +- 研究的时间跨度是多久 +- 何时是最佳的研究时机 +- 相关技术和数据何时可用 +- 预期何时产出成果 + +**时间规划**: +- **短期** (3-6个月): 初步探索、文献综述、方法验证 +- **中期** (6-12个月): 完整实验、论文撰写、投稿 +- **长期** (1-2年): 系统研究、多篇论文、理论贡献 + + +### Where (何处) + +**核心问题**: 研究的应用场景和领域是什么？ + +**思考维度**: +- 研究应用在哪些具体场景 +- 在哪些领域或行业有价值 +- 地理或文化背景是否重要 +- 实验在哪里进行 + +**应用场景分类**: +- **学术场景**: 理论验证、方法比较、基准测试 +- **工业场景**: 产品开发、系统优化、问题诊断 +- **社会场景**: 政策制定、公共服务、社会影响 +- **跨领域**: 多学科交叉、技术迁移 + +### How (如何) + +**核心问题**: 初步的研究方法思路是什么？ + +**思考维度**: +- 采用什么研究方法或技术路线 +- 需要什么数据和资源 +- 如何验证研究假设 +- 预期的技术挑战是什么 + +**方法类型**: +- **理论研究**: 数学证明、理论分析、模型推导 +- **实验研究**: 算法设计、实验验证、性能评估 +- **应用研究**: 系统开发、案例研究、用户测试 +- **综合研究**: 文献综述、元分析、系统评价 + + +## 使用示例 + +### 示例 1: Transformer 可解释性研究 + +**What**: 研究 Transformer 模型的注意力机制可解释性 +**Why**: 提高模型透明度，增强用户信任，满足监管要求 +**Who**: NLP 研究者、模型开发者、监管机构 +**When**: 6-12个月，当前 Transformer 广泛应用但缺乏解释 +**Where**: 文本分类、机器翻译、问答系统等 NLP 任务 +**How**: 设计可视化工具，分析注意力权重，进行消融实验 + +### 示例 2: 少样本学习在医疗影像中的应用 + +**What**: 探索少样本学习方法在医疗图像诊断中的有效性 +**Why**: 医疗数据标注成本高，少样本学习可降低数据需求 +**Who**: 医疗 AI 研究者、放射科医生、医院 +**When**: 12-18个月，随着少样本学习技术成熟 +**Where**: X光片、CT扫描、MRI 等医疗影像诊断 +**How**: 元学习、迁移学习、数据增强，在真实医疗数据集上验证 + + +## 最佳实践 + +### 1. 迭代式思考 + +不要期望一次性回答所有问题。先快速过一遍6个问题，然后反复迭代细化。 + +### 2. 优先级排序 + +根据研究阶段调整关注重点： +- **早期**: 重点关注 What, Why, Who +- **中期**: 重点关注 How, When, Where +- **后期**: 全面审视所有维度 + +### 3. 团队协作 + +与导师、同事讨论 5W1H 问题，获得多角度反馈。 + +### 4. 文档记录 + +将 5W1H 分析结果记录下来，作为研究提案的基础。 + +## 与 superpowers:brainstorming 集成 + +可以调用 `superpowers:brainstorming` skill 进行交互式头脑风暴： + +**使用场景**: +- 需要快速生成多个研究想法 +- 需要评估想法的可行性 +- 需要团队协作式讨论 + +**集成方式**: +1. 使用 5W1H 框架初步构思想法 +2. 调用 superpowers:brainstorming 进行深入探索 +3. 将头脑风暴结果整理回 5W1H 框架 +4. 形成结构化的研究提案 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/gap-analysis-guide.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/gap-analysis-guide.md new file mode 100644 index 0000000..794847c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/gap-analysis-guide.md @@ -0,0 +1,269 @@ +# Gap Analysis Guide for Research + +## 概述 + +Gap Analysis（研究空白分析）是识别现有研究中未被充分探索的领域、方法或应用的系统化过程。通过识别这些空白，研究者可以找到有价值的研究机会和创新方向。 + +## 为什么需要 Gap Analysis + +**学术价值**: +- 确保研究的原创性和新颖性 +- 避免重复已有的研究工作 +- 识别高影响力的研究方向 + +**实践价值**: +- 发现理论到实践的转化机会 +- 识别技术改进的空间 +- 找到跨学科合作的可能性 + + +## Gap Analysis 的类型 + +### 1. 文献空白 (Literature Gap) + +**定义**: 尚未被充分研究或完全未被研究的主题或问题。 + +**识别方法**: +- 系统化文献综述发现研究较少的子领域 +- 分析综述论文中提到的"未来工作" +- 识别被引用较少但重要的研究方向 +- 发现新兴技术或应用场景 + +**示例**: +- "Transformer 在时间序列预测中的应用研究较少" +- "少样本学习在医疗影像中的研究刚刚起步" +- "多模态学习在机器人控制中的应用尚未充分探索" + +### 2. 方法空白 (Methodological Gap) + +**定义**: 现有方法的局限性和改进机会。 + +**识别方法**: +- 分析现有方法的优缺点 +- 识别方法在特定场景下的失效情况 +- 发现计算效率或可扩展性问题 +- 识别理论与实践的差距 + +**示例**: +- "现有注意力机制在长序列上效率低下" +- "当前强化学习方法样本效率不足" +- "现有可解释性方法难以应用于大规模模型" + + +### 3. 应用空白 (Application Gap) + +**定义**: 理论到实践的转化机会，或在新场景中的应用潜力。 + +**识别方法**: +- 识别理论研究缺乏实际应用验证 +- 发现成功方法在新领域的应用机会 +- 识别工业界需求与学术研究的脱节 +- 发现技术迁移的可能性 + +**示例**: +- "自监督学习在工业质检中的应用尚未充分探索" +- "图神经网络在金融风控中的应用研究较少" +- "联邦学习在医疗数据隐私保护中的实际部署案例不足" + +### 4. 跨学科空白 (Interdisciplinary Gap) + +**定义**: 不同领域交叉产生的研究机会。 + +**识别方法**: +- 识别不同领域的相似问题 +- 发现方法在跨领域迁移的可能性 +- 识别需要多学科协作的复杂问题 +- 发现新兴交叉领域 + +**示例**: +- "认知科学与深度学习的交叉研究" +- "量子计算与机器学习的结合" +- "生物学启发的神经网络架构设计" + +### 5. 时间空白 (Temporal Gap) + +**定义**: 随时间变化产生的新研究需求。 + +**识别方法**: +- 识别新技术带来的新问题 +- 发现数据分布随时间变化的影响 +- 识别社会需求变化带来的新挑战 +- 发现技术演进产生的新机会 + +**示例**: +- "大语言模型时代的提示工程研究" +- "后疫情时代的远程协作技术" +- "隐私法规变化对机器学习的影响" + + +## 分析维度 + +### 1. 研究主题的覆盖程度 + +**评估指标**: +- 相关论文数量和质量 +- 研究的深度和广度 +- 主流会议和期刊的关注度 +- 研究团队的活跃程度 + +**判断标准**: +- **充分研究**: >100篇高质量论文，多个活跃团队 +- **适度研究**: 20-100篇论文，有一定关注 +- **研究不足**: <20篇论文，关注度低 +- **未被研究**: 几乎没有相关文献 + +### 2. 现有方法的优缺点对比 + +**评估内容**: +- 方法的理论基础 +- 实验性能表现 +- 计算复杂度 +- 可扩展性和泛化能力 +- 实际应用的可行性 + +**空白识别**: +- 所有方法都存在的共同局限 +- 特定场景下的失效情况 +- 理论与实践的差距 + + +### 3. 实验设置的完整性 + +**评估内容**: +- 实验场景的多样性 +- 基准数据集的覆盖范围 +- 评估指标的全面性 +- 消融实验的充分性 + +**空白识别**: +- 缺少特定场景的实验验证 +- 评估指标不够全面 +- 缺少与强基线的对比 + +### 4. 数据集和基准的可用性 + +**评估内容**: +- 公开数据集的数量和质量 +- 标准基准的建立情况 +- 数据集的多样性和代表性 +- 数据标注的质量 + +**空白识别**: +- 缺少特定领域的数据集 +- 现有数据集存在偏差或局限 +- 缺少标准化的评估基准 + +### 5. 理论与实践的差距 + +**评估内容**: +- 理论假设与实际情况的匹配度 +- 方法在实际应用中的可行性 +- 理论保证与实验结果的一致性 +- 工业界采用情况 + +**空白识别**: +- 理论研究缺乏实际验证 +- 实际问题缺乏理论支持 +- 技术转化存在障碍 + + +## 使用方法 + +### Step 1: 系统化文献综述 + +- 收集相关领域的代表性论文（20-100篇） +- 按主题、方法、应用场景分类 +- 识别研究趋势和热点 + +### Step 2: 构建对比矩阵 + +创建表格对比现有研究： + +| 研究 | 方法 | 数据集 | 性能 | 局限性 | +|------|------|--------|------|--------| +| Paper A | Method X | Dataset 1 | 85% | 计算复杂度高 | +| Paper B | Method Y | Dataset 2 | 82% | 泛化能力弱 | + +### Step 3: 识别空白模式 + +- 所有研究都未涉及的主题 +- 所有方法都存在的共同局限 +- 缺少的实验场景或数据集 +- 理论与实践的脱节 + +### Step 4: 评估空白的价值 + +对每个识别的空白评估： +- **重要性**: 解决这个空白的学术/实践价值 +- **新颖性**: 是否有人正在研究 +- **可行性**: 是否有足够的资源和技术支持 + + +## 示例分析 + +### 示例 1: Transformer 在时间序列预测中的应用 + +**文献综述发现**: +- Transformer 在 NLP 领域应用广泛（>1000篇论文） +- 在计算机视觉中也有大量研究（>500篇论文） +- 在时间序列预测中的研究较少（<50篇论文） + +**识别的空白**: +- **文献空白**: 时间序列领域的 Transformer 研究不足 +- **方法空白**: 现有方法未充分利用时间序列的特性 +- **应用空白**: 缺少在金融、能源等领域的应用验证 + +**研究机会**: 设计专门针对时间序列的 Transformer 变体 + +### 示例 2: 联邦学习的隐私保护 + +**文献综述发现**: +- 联邦学习理论研究充分（>200篇论文） +- 隐私保护机制研究较多（>150篇论文） +- 实际部署案例较少（<20篇论文） + +**识别的空白**: +- **应用空白**: 理论到实践的转化不足 +- **方法空白**: 现有方法在实际场景中效率低 +- **时间空白**: 新隐私法规带来的新挑战 + +**研究机会**: 开发高效的隐私保护联邦学习系统 + + +## 最佳实践 + +### 1. 保持客观性 + +避免为了找空白而找空白。真正的研究空白应该是： +- 有学术或实践价值的 +- 可行的（有资源和技术支持） +- 符合研究兴趣的 + +### 2. 多维度分析 + +不要只关注一种类型的空白，综合考虑： +- 文献空白 + 方法空白 = 创新方法 +- 应用空白 + 跨学科空白 = 新应用场景 +- 时间空白 + 文献空白 = 新兴研究方向 + +### 3. 验证空白的真实性 + +在确定研究方向前，再次验证： +- 是否有最新的相关工作（搜索最近3个月的论文） +- 是否有人正在研究（检查 arXiv 预印本） +- 是否有技术或数据限制 + +### 4. 记录分析过程 + +将 Gap Analysis 的结果记录下来： +- 识别的空白列表 +- 每个空白的评估（重要性、新颖性、可行性） +- 选择的研究方向和理由 + +### 5. 与导师和同行讨论 + +Gap Analysis 的结果应该与导师、同事讨论： +- 验证空白的真实性和价值 +- 获得不同角度的反馈 +- 避免主观偏见 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/literature-search-strategies.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/literature-search-strategies.md new file mode 100644 index 0000000..368dc9c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/literature-search-strategies.md @@ -0,0 +1,203 @@ +# 文献搜索策略 + +系统化的文献搜索方法，帮助研究者高效地找到相关文献。 + +## 1. 关键词构建 + +### 1.1 核心概念识别 + +从研究兴趣中提取核心概念： + +**示例**：研究兴趣 "Transformer 模型的可解释性" +- 核心概念 1：Transformer +- 核心概念 2：Interpretability / Explainability + +### 1.2 同义词和变体 + +为每个核心概念列出同义词和变体： + +| 核心概念 | 同义词/变体 | +|---------|------------| +| Transformer | Attention mechanism, Self-attention, BERT, GPT | +| Interpretability | Explainability, Transparency, Understanding | + +### 1.3 布尔运算符 + +使用布尔运算符组合关键词： + +``` +(Transformer OR "attention mechanism" OR BERT OR GPT) +AND +(interpretability OR explainability OR transparency) +``` + +### 1.4 领域特定术语 + +添加领域特定的术语： + +- **方法术语**：probing, attention visualization, saliency maps +- **应用领域**：NLP, computer vision, speech recognition +- **评估指标**：faithfulness, plausibility, human evaluation + +## 2. 学术数据库选择 + +### 2.1 主要数据库 + +| 数据库 | 特点 | 适用场景 | +|--------|------|---------| +| **arXiv** | 预印本，更新快 | 获取最新研究进展 | +| **Semantic Scholar** | AI 驱动，引用分析 | 发现相关论文，分析影响力 | +| **Google Scholar** | 覆盖面广 | 全面搜索，找遗漏论文 | +| **ACL Anthology** | NLP 专业 | NLP 领域深度搜索 | +| **IEEE Xplore** | 工程技术 | 计算机视觉、硬件相关 | + +### 2.2 搜索策略 + +**arXiv 搜索**： +``` +cat:cs.LG AND (transformer OR attention) AND (interpretability OR explainability) +``` + +**Semantic Scholar 搜索**： +- 使用自然语言查询 +- 利用"Highly Influential Citations"筛选 +- 查看"Related Papers"发现相关工作 + +**Google Scholar 搜索**： +- 使用引号精确匹配："transformer interpretability" +- 限制时间范围：2020-2024 +- 排除专利：-patent + +## 3. 搜索技巧 + +### 3.1 迭代搜索 + +1. **初始搜索** - 使用核心关键词 +2. **分析结果** - 查看高引用论文的关键词 +3. **优化查询** - 添加新发现的术语 +4. **重复迭代** - 直到找到足够相关的论文 + +### 3.2 引用追踪 + +**前向引用**（Forward Citation）： +- 查看哪些新论文引用了这篇论文 +- 了解研究的后续发展 + +**后向引用**（Backward Citation）： +- 查看这篇论文引用了哪些论文 +- 了解研究的基础和背景 + +### 3.3 作者追踪 + +- 识别领域内的关键研究者 +- 查看他们的其他相关工作 +- 关注他们的最新研究 + +## 4. 论文筛选标准 + +### 4.1 初步筛选（基于标题和摘要） + +**包含标准**： +- 直接相关于研究主题 +- 发表在顶级会议/期刊（NeurIPS, ICML, ICLR, ACL, AAAI） +- 引用次数较高（相对于发表时间） +- 作者来自知名机构或研究组 + +**排除标准**： +- 与研究主题无关 +- 发表在低质量会议/期刊 +- 明显过时的方法（除非是经典论文） + +### 4.2 深度筛选（基于全文） + +**质量评估**： +1. **方法创新性** - 是否提出新方法或新视角 +2. **实验充分性** - 实验设计是否合理，结果是否可信 +3. **写作质量** - 论文是否清晰易懂 +4. **可重现性** - 是否提供代码和数据 + +**相关性评估**： +1. **直接相关** - 核心方法或问题直接相关 +2. **间接相关** - 相关技术或应用场景 +3. **背景知识** - 提供必要的背景和基础 + +### 4.3 文献管理 + +**集成工具**： +- **Zotero**（主要工具，已通过 MCP 集成） + - 通过 `zotero_add_items_by_identifier` 智能导入论文，优先落成 paper/preprint + - 通过 `zotero_create_collection` 自动创建和组织集合 + - 通过 PDF cascade（页面显式 PDF → direct PDF → Unpaywall）尽可能补齐 PDF + - 通过 `zotero_get_item_fulltext` 读取 PDF 全文进行分析 + - 通过 `zotero_search_items` 搜索已有论文避免重复导入 +- Mendeley - 社交功能，PDF 标注（备选） +- Papers - Mac 专用，界面优雅（备选） + +**组织策略**： + +使用 Zotero 集合结构组织文献： + +``` +📁 Research-{topic}-{date} + ├── 📁 Core Papers（核心论文） + ├── 📁 Methods（方法论文） + ├── 📁 Applications（应用论文） + ├── 📁 Baselines（基线论文） + └── 📁 To-Read（待读论文） +``` + +- 核心论文：直接相关、高引用的关键论文 +- 方法论文：技术方法参考，可借鉴的方法论 +- 应用论文：应用场景参考，领域实践 +- 基线论文：实验对比基准，需要复现的工作 +- 待读论文：初步筛选，待深入阅读 + +## 5. DOI 提取与自动导入 + +### 5.1 DOI 提取方法 + +从 WebSearch 搜索结果中提取 DOI 的常见方式： + +**URL 中的 DOI**： +- `https://doi.org/10.xxxx/xxxxx` - 直接 DOI 链接 +- `https://dl.acm.org/doi/10.xxxx/xxxxx` - ACM Digital Library +- `https://ieeexplore.ieee.org/document/xxxxx` - IEEE（需从页面提取） +- `https://arxiv.org/abs/xxxx.xxxxx` - arXiv（DOI 格式：`10.48550/arXiv.xxxx.xxxxx`） + +**常见 DOI 格式**： +- `10.xxxx/xxxxx` - 标准 DOI 前缀 +- 以 `10.` 开头，包含 `/` 分隔符 +- 例：`10.1038/s41586-023-06747-5`（Nature） +- 例：`10.48550/arXiv.2301.00234`（arXiv） + +### 5.2 自动导入流程 + +``` +WebSearch 搜索论文 + ↓ +从搜索结果中提取 DOI / arXiv ID / landing-page URL + ↓ +add_items_by_identifier 批量导入到 Zotero + ↓ +工具内部自动执行 PDF cascade + ↓ +必要时用 `zotero_reconcile_collection_duplicates` 做导入后去重清理 + ↓ +get_item_fulltext 读取全文进行分析 +``` + +**操作示例**： + +1. 使用 WebSearch 搜索 `"transformer interpretability" site:arxiv.org OR site:doi.org` +2. 从结果中收集 DOI 列表 +3. 调用 `zotero_add_items_by_identifier(..., attach_pdf=true)` 批量导入（建议每批不超过 10 篇，避免 API 速率限制） +4. 仅对仍然缺 PDF 的条目，再调用 `zotero_find_and_attach_pdfs` 做补挂 +5. 使用 `zotero_get_item_fulltext` 阅读关键论文全文 + +### 5.3 无 DOI 论文处理 + +部分论文可能没有标准 DOI： +- **arXiv 预印本**：使用 `10.48550/arXiv.{id}` 格式 +- **会议论文集**：尝试从出版商页面获取 DOI +- **无法获取 DOI**：优先识别 arXiv ID、页面中的 `citation_doi` / `citation_pdf_url`；只有都失败时才保存为 `webpage`。如果关键论文仍缺 PDF，请在 Zotero Desktop 中手动附加。 + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/method-selection-guide.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/method-selection-guide.md new file mode 100644 index 0000000..f62d6b5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/method-selection-guide.md @@ -0,0 +1,217 @@ +# 方法选择指南 + +帮助研究者选择适合的研究方法和技术路线。 + +## 1. 常见研究方法分类 + +### 1.1 理论分析方法 + +**特点**：通过数学推导和理论分析来理解问题 + +**适用场景**： +- 需要理论保证的问题 +- 算法复杂度分析 +- 收敛性证明 +- 泛化界分析 + +**示例**： +- PAC 学习理论 +- 优化算法收敛性分析 +- 神经网络表达能力分析 + +**所需技能**： +- 数学基础（概率论、优化理论） +- 理论计算机科学 +- 证明技巧 + +### 1.2 实证研究方法 + +**特点**：通过实验验证假设和评估方法 + +**适用场景**： +- 新方法性能评估 +- 假设验证 +- 方法对比 +- 参数敏感性分析 + +**示例**： +- 在多个数据集上评估新模型 +- 消融实验分析组件贡献 +- 超参数搜索和优化 + +**所需资源**： +- 计算资源（GPU/TPU） +- 标准数据集 +- 评估指标和工具 + +### 1.3 系统构建方法 + +**特点**：构建完整的系统或工具 + +**适用场景**： +- 端到端应用系统 +- 工具和框架开发 +- 集成多个技术 +- 实际部署需求 + +**示例**： +- 对话系统 +- 推荐系统 +- 代码生成工具 +- 数据处理框架 + +**所需资源**： +- 工程能力 +- 系统设计经验 +- 用户反馈渠道 +- 维护和迭代能力 + +### 1.4 数据分析方法 + +**特点**：通过数据分析发现规律和洞察 + +**适用场景**： +- 探索性研究 +- 现象分析 +- 模型行为理解 +- 错误分析 + +**示例**： +- 注意力模式可视化 +- 模型预测错误分析 +- 数据集偏差分析 +- 训练动态分析 + +**所需技能**： +- 数据可视化 +- 统计分析 +- 模型解释技术 + +## 2. 方法选择决策框架 + +### 2.1 问题类型匹配 + +| 问题类型 | 推荐方法 | 原因 | +|---------|---------|------| +| 理论问题 | 理论分析 | 需要严格证明 | +| 性能提升 | 实证研究 | 需要实验验证 | +| 实际应用 | 系统构建 | 需要端到端解决方案 | +| 现象理解 | 数据分析 | 需要探索和发现 | + +### 2.2 资源约束考虑 + +**计算资源有限**： +- 优先选择轻量级方法 +- 使用预训练模型 +- 考虑模型压缩技术 +- 使用小规模数据集验证 + +**时间紧迫**： +- 选择成熟的方法 +- 使用现有工具和框架 +- 避免从零开始 +- 优先快速原型 + +**数据有限**： +- 使用迁移学习 +- 数据增强技术 +- Few-shot 学习方法 +- 合成数据生成 + +## 3. 方法优缺点对比 + +### 3.1 理论分析方法 + +**优点**： +- 提供理论保证 +- 深入理解问题本质 +- 结果具有普适性 +- 不依赖大量实验 + +**缺点**： +- 需要强数学背景 +- 可能与实际有差距 +- 证明过程耗时 +- 难以处理复杂系统 + +### 3.2 实证研究方法 + +**优点**： +- 直接验证性能 +- 结果直观可信 +- 易于复现 +- 适用范围广 + +**缺点**： +- 需要大量计算资源 +- 结果可能过拟合数据集 +- 缺乏理论解释 +- 超参数调优困难 + +### 3.3 系统构建方法 + +**优点**： +- 解决实际问题 +- 产生实用价值 +- 综合多种技术 +- 易于产业化 + +**缺点**： +- 工程量大 +- 维护成本高 +- 学术贡献可能有限 +- 难以发表顶会 + +### 3.4 数据分析方法 + +**优点**： +- 发现新现象 +- 提供洞察 +- 成本相对较低 +- 可视化效果好 + +**缺点**： +- 可能缺乏深度 +- 难以量化贡献 +- 结果可能主观 +- 需要领域知识 + +## 4. 资源需求评估 + +### 4.1 计算资源 + +| 方法类型 | GPU 需求 | 训练时间 | 存储需求 | +|---------|---------|---------|---------| +| 理论分析 | 无 | 无 | 低 | +| 小规模实验 | 1-2 GPU | 数小时-数天 | 中 | +| 大规模实验 | 4-8 GPU | 数天-数周 | 高 | +| 系统构建 | 可变 | 持续 | 高 | + +### 4.2 人力资源 + +**单人项目**： +- 理论分析（如有背景） +- 小规模实证研究 +- 数据分析 + +**团队项目**： +- 大规模实证研究 +- 系统构建 +- 跨领域研究 + +### 4.3 时间资源 + +**3个月内**： +- 小规模实验 +- 数据分析 +- 理论分析（简单问题） + +**6个月内**： +- 中等规模实验 +- 系统原型 +- 理论分析（复杂问题） + +**1年内**： +- 大规模实验 +- 完整系统 +- 深入理论研究 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-contract.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-contract.md new file mode 100644 index 0000000..c98020f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-contract.md @@ -0,0 +1,111 @@ +# Research Contract + +Use this contract to carry research state across Claude Scholar workflows. + +The goal is to preserve: +- what question is being studied, +- what evidence currently exists, +- what claim is allowed by that evidence, +- what uncertainty remains, +- what decision or next action should happen. + +## Research Question Card + +Use this card when a vague idea becomes a research direction. + +```md +## Research Question Card + +Question: +Type: exploratory | confirmatory | applied +Hypothesis: +Why it matters: +Current evidence: +Missing evidence: +What would support it: +What would falsify it: +Minimal next action: +Decision: explore | read more | run experiment | stop +``` + +## Evidence Record + +Use this record for paper evidence, project notes, experiment outputs, and analysis artifacts. + +```md +## Evidence Record + +Evidence ID: +Source: +Source type: full paper | preprint | dataset | experiment artifact | project note | abstract-only | webpage placeholder +Supports: +Contradicts: +Method / dataset / metric: +Limitation: +Project relevance: +Claim strength: speculative | observed | supported | strong +``` + +Evidence ID format: +- Use `ER-YYYYMMDD-shortslug-NN`, for example `ER-20260513-tta-eeg-01`. +- Keep IDs unique within the project or research thread. +- Use stable, human-readable slugs. Do not use vague IDs such as `E1`, `paper1`, or `source-a`. +- Reuse the same Evidence ID when the same evidence record is referenced downstream; create a new ID only for a distinct source, artifact, or analysis result. + +## Claim Candidate + +Use this candidate when an analysis or synthesis suggests language that may later enter a report, paper, rebuttal, or project plan. + +```md +## Claim Candidate + +Claim: +Source evidence: +Allowed wording: +Forbidden stronger wording: +Uncertainty: +Next check: +Decision: keep | weaken | revise | discard +``` + +## Source Trust Levels + +Use source trust to decide whether a note can support downstream synthesis. + +- `full paper` / `preprint`: can support `observed`, `supported`, or `strong` claims when the relevant method, dataset, metric, and limitation are named. +- `dataset` / `experiment artifact`: can support project claims when the unit of analysis, metric, provenance, and analysis limits are named. +- `project note`: can support hypotheses and plans, but not literature-backed claims unless it links to separate evidence records. +- `abstract-only` / `webpage placeholder`: can support discovery and `To-Read` routing only. Do not use it to support `Knowledge`, manuscript, or rebuttal claims unless it is later replaced by a full paper, preprint, or verified artifact. + +## Claim Promotion Gate + +Before a claim moves into `Knowledge`, `Writing`, a report, a manuscript draft, or a rebuttal, check: + +1. The claim has at least one Evidence Record ID. +2. The source type is strong enough for the intended claim. +3. The claim strength is not silently upgraded. +4. The allowed wording and forbidden stronger wording are both recorded. +5. Contradictory evidence or missing evidence is preserved. + +If any item fails, keep the claim as a hypothesis, motivation, warning, or `To-Read` item. Do not polish it into a durable conclusion. + +## Proposal Readiness Gate + +Generate a `research-proposal.md` only when: + +- one Research Question Card is selected, +- current evidence is enough to justify the question and method, +- missing evidence is explicit and tractable, +- the minimal next action is more specific than "read more", +- citations or evidence records are available for the key motivation claims. + +If these conditions are not met, generate `research-question-card.md`, a gap note, or an intake summary instead of a proposal. + +## Strength Rules + +- `speculative`: plausible idea, weak or indirect evidence only. +- `observed`: seen in a paper, note, or experiment, but not yet enough for a durable conclusion. +- `supported`: backed by explicit evidence such as a paper result, experiment, or analysis bundle. +- `strong`: supported by multiple evidence anchors or statistically rigorous project evidence. + +Do not promote a claim to a stronger level without naming the evidence that justifies the upgrade. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-planning.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-planning.md new file mode 100644 index 0000000..7813863 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-planning.md @@ -0,0 +1,174 @@ +# 研究计划制定 + +系统化的研究计划制定方法，确保研究项目顺利推进。 + +## 1. 时间线规划 + +### 1.1 研究阶段划分 + +**典型研究周期**（以6个月为例）： + +| 阶段 | 时间 | 主要任务 | 交付物 | +|------|------|---------|--------| +| **Phase 1: 准备** | 第1个月 | 文献调研、问题定义 | 文献综述、研究提案 | +| **Phase 2: 探索** | 第2-3个月 | 初步实验、方法验证 | 概念验证、初步结果 | +| **Phase 3: 开发** | 第4-5个月 | 方法优化、全面实验 | 完整实验结果 | +| **Phase 4: 完成** | 第6个月 | 论文撰写、代码整理 | 论文草稿、开源代码 | + +### 1.2 时间分配原则 + +**80/20 原则**： +- 80% 时间用于核心工作（实验、分析、写作） +- 20% 时间用于辅助工作（文献、工具、沟通） + +**缓冲时间**： +- 每个阶段预留 20% 缓冲时间 +- 应对意外情况和延期 + +**并行任务**： +- 文献调研贯穿整个过程 +- 论文写作可以提前开始（Introduction, Related Work） +- 代码整理与实验同步进行 + +## 2. 里程碑定义 + +### 2.1 关键里程碑 + +**Milestone 1: 研究提案完成** +- 时间：第1个月末 +- 标准： + - 文献综述完成（20-30篇核心论文） + - 研究问题明确定义 + - 方法路线初步确定 + - 实验计划制定 + +**Milestone 2: 概念验证** +- 时间：第3个月末 +- 标准： + - 初步实验完成 + - 方法可行性验证 + - 至少一个正面结果 + - 识别主要挑战 + +**Milestone 3: 完整实验** +- 时间：第5个月末 +- 标准： + - 所有实验完成 + - 结果达到预期 + - 消融实验完成 + - 可视化和分析完成 + +**Milestone 4: 论文提交** +- 时间：第6个月末 +- 标准： + - 论文草稿完成 + - 代码开源准备 + - 内部审阅通过 + - 准备投稿 + +### 2.2 检查点设置 + +**每周检查**： +- 进度回顾 +- 问题识别 +- 计划调整 + +**每月评审**： +- 里程碑评估 +- 风险评估 +- 资源调整 + +## 3. 风险识别与应对 + +### 3.1 常见风险 + +**技术风险**： +- 方法不work +- 实验结果不理想 +- 计算资源不足 +- 技术难度超预期 + +**应对策略**： +- 准备备选方案 +- 早期概念验证 +- 申请额外资源 +- 寻求技术支持 + +**时间风险**： +- 进度延期 +- 依赖项延迟 +- 意外事件 + +**应对策略**： +- 预留缓冲时间 +- 并行任务 +- 优先级管理 +- 及时调整计划 + +**资源风险**： +- GPU 不可用 +- 数据集问题 +- 人员变动 + +**应对策略**： +- 多个资源渠道 +- 数据集备选 +- 知识文档化 + +### 3.2 风险监控 + +**红色预警**（立即处理）： +- 核心方法失败 +- 关键资源缺失 +- 严重进度延期 + +**黄色预警**（密切关注）： +- 部分实验不理想 +- 资源紧张 +- 轻微延期 + +**绿色状态**（正常推进）： +- 按计划进行 +- 资源充足 +- 结果符合预期 + +## 4. 资源分配 + +### 4.1 计算资源 + +**GPU 分配**： +- 探索阶段：1-2 GPU +- 开发阶段：2-4 GPU +- 完成阶段：4-8 GPU（大规模实验） + +**存储分配**： +- 数据集：100-500 GB +- 模型检查点：50-200 GB +- 实验日志：10-50 GB + +### 4.2 人力分配 + +**单人项目**： +- 文献调研：20% +- 实验开发：50% +- 论文写作：20% +- 其他：10% + +**团队项目**： +- 研究负责人：规划、指导、写作 +- 研究助理：实验、分析、编码 +- 合作者：特定模块、审阅 + +### 4.3 时间分配 + +**每周时间**（40小时）： +- 核心研究：25-30小时 +- 文献阅读：5-8小时 +- 会议讨论：3-5小时 +- 其他事务：2-5小时 + +**每日时间**： +- 深度工作：4-6小时（上午） +- 实验监控：2-3小时 +- 文献和写作：1-2小时 +- 沟通协作：1小时 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-question-formulation.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-question-formulation.md new file mode 100644 index 0000000..b10a98e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/research-question-formulation.md @@ -0,0 +1,210 @@ +# 研究问题制定 + +将研究兴趣转化为具体、可执行的研究问题的系统化方法。 + +## 1. SMART 原则 + +好的研究问题应该满足 SMART 原则： + +### 1.1 Specific (具体的) + +**不好的问题**： +- "如何提高模型性能？"（太宽泛） + +**好的问题**： +- "如何通过改进注意力机制来提高 Transformer 在长文本理解任务上的性能？" + +**关键要素**： +- 明确的研究对象（Transformer） +- 具体的改进方向（注意力机制） +- 明确的任务场景（长文本理解） +- 清晰的目标（提高性能） + +### 1.2 Measurable (可衡量的) + +研究问题应该有明确的评估标准： + +**示例**： +- "提高性能" → "在 SQuAD 数据集上提高 F1 分数" +- "改善可解释性" → "提高人类评估的 faithfulness 分数" + +**评估维度**： +- 定量指标：准确率、F1、BLEU、困惑度 +- 定性指标：人类评估、案例分析 +- 效率指标：训练时间、推理速度、内存占用 + +### 1.3 Achievable (可实现的) + +考虑资源和能力限制： + +**资源评估**： +- 计算资源：GPU 数量和类型 +- 数据资源：数据集的可获得性和质量 +- 时间资源：研究周期（3个月、6个月、1年） +- 人力资源：团队规模和专业技能 + +**可行性检查**： +- 是否有类似工作作为基础？ +- 所需技术是否已经成熟？ +- 数据集是否公开可用？ +- 计算成本是否在预算内？ + +### 1.4 Relevant (相关的) + +研究问题应该对学术界或工业界有价值： + +**学术价值**： +- 填补研究空白 +- 挑战现有假设 +- 提供新的理论视角 +- 推动方法论进步 + +**实际价值**： +- 解决实际应用问题 +- 提高系统性能 +- 降低成本或资源消耗 +- 改善用户体验 + +### 1.5 Time-bound (有时限的) + +设定合理的研究时间框架： + +**短期目标**（1-3个月）： +- 文献调研和问题定义 +- 初步实验和概念验证 + +**中期目标**（3-6个月）： +- 方法开发和优化 +- 全面实验和分析 + +**长期目标**（6-12个月）： +- 论文撰写和投稿 +- 代码开源和社区推广 + +## 2. 研究问题类型 + +### 2.1 探索性问题 (Exploratory) + +**特点**：探索未知领域，发现新现象 + +**示例**： +- "Transformer 的注意力机制在处理长文本时表现出什么模式？" +- "大语言模型在推理任务中使用了哪些内部表示？" + +**适用场景**： +- 新兴研究领域 +- 缺乏理论基础的现象 +- 需要深入理解的复杂系统 + +### 2.2 验证性问题 (Confirmatory) + +**特点**：验证假设或理论 + +**示例**： +- "增加模型深度是否能提高长文本理解性能？" +- "预训练是否对低资源语言任务有帮助？" + +**适用场景**： +- 有明确假设需要验证 +- 挑战现有理论或观点 +- 复现和扩展已有工作 + +### 2.3 应用性问题 (Applied) + +**特点**：解决实际应用问题 + +**示例**： +- "如何在保持性能的同时将模型大小减少50%？" +- "如何使对话系统更好地理解用户意图？" + +**适用场景**： +- 有明确的应用需求 +- 需要在约束条件下优化 +- 工业界合作项目 + +## 3. 研究问题评估标准 + +### 3.1 重要性 (Significance) + +**评估维度**： +- **学术影响**：是否推动领域发展？ +- **实际价值**：是否解决重要问题？ +- **受众规模**：有多少人关心这个问题？ + +**评分标准**（1-5分）： +- 5分：突破性问题，影响整个领域 +- 4分：重要问题，多个研究组关注 +- 3分：有价值问题，部分研究者关注 +- 2分：边缘问题，少数人关注 +- 1分：琐碎问题，几乎无人关注 + +### 3.2 新颖性 (Novelty) + +**评估维度**： +- **问题新颖性**：是否是新问题？ +- **方法新颖性**：是否用新方法？ +- **视角新颖性**：是否有新视角？ + +**评分标准**（1-5分）： +- 5分：全新问题或突破性方法 +- 4分：新问题或显著改进的方法 +- 3分：新视角或方法组合 +- 2分：增量改进 +- 1分：重复已有工作 + +### 3.3 可行性 (Feasibility) + +**评估维度**： +- **技术可行性**：现有技术能否实现？ +- **资源可行性**：资源是否充足？ +- **时间可行性**：时间是否合理？ + +**评分标准**（1-5分）： +- 5分：完全可行，资源充足 +- 4分：基本可行，资源足够 +- 3分：有挑战，需要努力 +- 2分：困难较大，需要突破 +- 1分：几乎不可行 + +### 3.4 综合评估 + +**决策矩阵**： + +| 重要性 | 新颖性 | 可行性 | 建议 | +|--------|--------|--------|------| +| 高 | 高 | 高 | 优先执行 | +| 高 | 高 | 中 | 值得尝试 | +| 高 | 中 | 高 | 稳妥选择 | +| 中 | 高 | 高 | 可以考虑 | +| 低 | * | * | 重新考虑 | + +## 4. 支持与证伪检查 + +每个研究问题都必须说明什么结果会支持它，什么结果会削弱或推翻它。 + +### 4.1 必填字段 + +```md +Question: +Hypothesis: +Current evidence: +Missing evidence: +What would support it: +What would falsify it: +Minimal next action: +Decision: explore | read more | run experiment | stop +``` + +### 4.2 决策含义 + +- `explore`：问题可能有价值，但还缺少基本文献或问题边界。 +- `read more`：需要先补关键相关工作、baseline、dataset 或 metric。 +- `run experiment`：问题、假设、支持证据和最小实验已经足够明确。 +- `stop`：重要性、新颖性、可行性或证据边界不足，不建议继续投入。 + +### 4.3 写作要求 + +- 不要只写“值得研究”；必须说明为什么值得研究。 +- 不要只写“需要更多实验”；必须说明最小下一步实验是什么。 +- 不要只写“有文献支持”；必须列出当前证据和缺失证据。 +- 不要把探索性问题写成已经验证的结论。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/zotero-integration-guide.md b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/zotero-integration-guide.md new file mode 100644 index 0000000..63002a4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/research-ideation/references/zotero-integration-guide.md @@ -0,0 +1,189 @@ +# Zotero MCP 集成指南 + +通过 Zotero MCP 服务器实现文献管理的自动化集成。 + +## 1. 可用工具 + +### 1.1 浏览工具 + +| 工具 | 功能 | 使用场景 | +|------|------|---------| +| `zotero_get_collections` | 列出所有集合 | 查看已有研究项目 | +| `zotero_get_collection_items` | 获取集合中的条目 | 浏览特定集合的论文 | +| `zotero_search_items` | 搜索库中的条目 | 按关键词查找已有论文 | +| `zotero_get_item_metadata` | 批量获取条目元数据 | 获取论文详细信息 | +| `zotero_get_item_fulltext` | 获取 PDF 全文 | 阅读论文内容 | + +### 1.2 添加工具 + +| 工具 | 功能 | 使用场景 | +|------|------|---------| +| `zotero_add_items_by_identifier` | 智能导入论文 | 先解析 DOI / arXiv / PDF，再尽量落成 paper 或 preprint | +| `zotero_add_items_by_doi` | 通过 DOI 添加论文 | 自动获取元数据，并默认尝试 PDF cascade | +| `zotero_add_items_by_arxiv` | 通过 arXiv ID 添加预印本 | 适合 arXiv-only 论文，并默认尝试 arXiv PDF | +| `zotero_add_item_by_url` | 保存网页为条目 | 仅在确实需要保留网页资源时使用 | +| `zotero_create_collection` | 创建集合 | 组织研究项目 | +| `zotero_find_and_attach_pdfs` | 批量补挂 PDF | 对已有条目再跑一遍 PDF cascade | +| `zotero_add_linked_url_attachment` | 附加 URL 链接 | 关联在线资源 | + +### 1.3 引用工具 + +| 工具 | 功能 | 使用场景 | +|------|------|---------| +| `inject_citations` | 注入引用到 Word | 生成引用格式 | + +## 2. 集合组织策略 + +### 2.1 命名规范 + +``` +Research-{主题关键词}-{YYYY} +``` + +示例： +- `Research-TransformerInterpretability-2026` +- `Research-BrainDecoding-2026` +- `Research-RLHF-2026` + +### 2.2 标准子集合结构 + +``` +📁 Research-{topic}-{date} + ├── 📁 Core Papers（核心论文） + ├── 📁 Methods（方法论文） + ├── 📁 Applications（应用论文） + ├── 📁 Baselines（基线论文） + └── 📁 To-Read（待读论文） +``` + +各子集合用途： + +| 子集合 | 收录标准 | 典型数量 | +|--------|---------|---------| +| Core Papers | 直接相关、高引用的关键论文 | 5-15 篇 | +| Methods | 技术方法参考，可借鉴的方法论 | 10-20 篇 | +| Applications | 应用场景参考，领域实践 | 5-10 篇 | +| Baselines | 实验对比基准，需要复现的工作 | 3-8 篇 | +| To-Read | 初步筛选，待深入阅读 | 不限 | + +## 3. 自动化工作流 + +### 3.1 论文发现与导入 + +``` +WebSearch 搜索论文 + ↓ +从搜索结果中提取 DOI / arXiv ID / landing-page URL + ↓ +add_items_by_identifier 智能导入到 Zotero + ↓ +工具内部先尝试页面显式 PDF，再回退到 Unpaywall + ↓ +如果 Zotero Web API 无法直接挂上 PDF，而本地 Zotero Desktop 正在运行，则自动走本地修复路径 + ↓ +必要时运行 `zotero_reconcile_collection_duplicates` 做标准导入后去重 + ↓ +get_item_fulltext 读取全文进行分析 +``` + +默认终端输出只需要告诉用户： +- Imported as paper + PDF attached +- Imported as paper +- Saved as webpage + PDF attached +- Saved as webpage +- Collection dedupe summary: duplicate groups N, duplicates trashed M +- Missing PDF postpass: repaired N items + +只有在调试时，才展开 `route`、`pdf_source` 等实现细节。import ledger 属于内部状态，不应假设存在公开 MCP tool 用于读取它。 + +### 3.2 DOI 提取技巧 + +**从搜索结果 URL 中识别 DOI**： +- `https://doi.org/10.xxxx/xxxxx` — 直接 DOI 链接 +- `https://dl.acm.org/doi/10.xxxx/xxxxx` — ACM Digital Library +- `https://arxiv.org/abs/xxxx.xxxxx` — arXiv（DOI：`10.48550/arXiv.xxxx.xxxxx`） + +**常见 DOI 格式**： +- 以 `10.` 开头，包含 `/` 分隔符 +- 例：`10.1038/s41586-023-06747-5`（Nature） +- 例：`10.48550/arXiv.2301.00234`（arXiv） +- 例：`10.1145/3580305.3599256`（ACM/KDD） + +**CrossRef 查询**： +- 当 URL 中没有明显 DOI 时，可通过论文标题在 CrossRef 搜索获取 DOI + +### 3.3 全文阅读与笔记 + +``` +get_item_fulltext 获取全文 + ↓ +分析论文内容 + ↓ +提取关键信息 + ↓ +生成结构化笔记 +``` + +### 3.4 笔记模板 + +每篇论文的结构化笔记应包含： + +```markdown +## [论文标题] + +**基本信息**： +- 作者： +- 会议/期刊： +- 年份： +- DOI： + +**研究问题**： +- 解决什么问题？ +- 为什么重要？ + +**核心方法**： +- 主要技术路线 +- 关键创新点 + +**关键发现**： +- 主要实验结果 +- 重要结论 + +**局限性**： +- 方法局限 +- 实验局限 + +**与本研究的关联**： +- 可借鉴之处 +- 差异和改进空间 +``` + +## 4. 常见问题 + +### 4.1 API 速率限制 + +Zotero API 有速率限制，批量添加时建议： +- 每批不超过 10 篇论文 +- 批次之间适当间隔 +- 如遇到 429 错误，等待后重试 + +### 4.2 PDF 全文索引延迟 + +新上传的 PDF 需要时间索引： +- `zotero_get_item_fulltext` 返回空时，稍后重试 +- Zotero 客户端需要运行才能完成索引 +- 大型 PDF 索引时间较长 + +### 4.3 DOI 无法识别 + +部分论文可能没有标准 DOI： +- arXiv 预印本：使用 `10.48550/arXiv.{id}` 格式 +- Workshop 论文：尝试从出版商页面获取 +- 无法获取 DOI：优先尝试识别 arXiv ID 或页面中的 `citation_doi` / `citation_pdf_url`；只有仍无法确认 identifier 时，才回退为 `webpage` + +### 4.4 OA PDF 不可用 + +非开放获取论文无法通过 Unpaywall 获取 PDF： +- 检查作者主页是否有预印本版本 +- 检查 arXiv 是否有对应版本 +- 若仍拿不到 PDF，可在 Zotero Desktop 中手动附加 PDF，之后再运行全文或注释相关工作流 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/SKILL.md new file mode 100644 index 0000000..22e3401 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/SKILL.md @@ -0,0 +1,252 @@ +--- +name: results-analysis +description: This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose. +tags: [Research, Analysis, Statistics, Visualization, Scientific Reporting] +version: 0.2.0 +--- + +# Results Analysis + +Run **strict, evidence-first experimental analysis** for ML/AI research. + +Use this skill to produce a **strict analysis bundle**: +- `analysis-report.md` +- `stats-appendix.md` +- `figure-catalog.md` +- `figures/` + +When the user asks for review, audit, no-write, dry-run, or when inputs are incomplete, use **read-only audit mode** instead of producing files or figures. In that mode, output only valid/invalid statistics, blockers, claim candidates, and what evidence is missing. If invoked by `/analyze-results`, the command layer may write a blocker summary, but this skill should not create figures, reports, or polished conclusions from incomplete evidence. + +Do **not** use this skill to draft a paper `Results` section or a full experiment wrap-up report. Those belong to `ml-paper-writing` or `results-report`. + +## Core contract + +### This skill is responsible for +- validating experiment artifacts and comparison units, +- running rigorous descriptive and inferential statistics, +- generating **real scientific figures** when data/logs are available, +- writing figure purposes, caption requirements, and interpretation checklists, +- surfacing limits, blockers, and missing evidence explicitly. + +### This skill is not responsible for +- paper-ready `Results` prose, +- manuscript narrative polishing, +- paper-ready figure/table packaging with `pubfig` / `pubtab`, +- project-level experiment retrospectives. + +If the user wants the complete post-experiment summary report, hand off to `results-report` after this bundle is ready. If the user wants publication-grade figures/tables, export parameters, publication QA, or figure/table redesign, hand off to `publication-chart-skill`. + +## Non-negotiable quality bar + +1. **Prefer real figures over figure specs.** + If the data can be read, generate real figures. Do not stop at “recommended visualization”. + Exception: in read-only audit mode, do not generate figures; describe what figure would be valid after evidence is complete. +2. **Never fabricate statistics.** + If sample size, seeds, or raw metrics are missing, state the blocker clearly. +3. **Report complete statistics.** + Do not report only best scores or only p-values. +4. **Interpret every main figure.** + Every major figure must have purpose, caption requirements, and post-figure interpretation notes. +5. **Separate evidence from prose.** + This skill produces analysis artifacts; it does not write manuscript sections. + +## Standard workflow + +### 1. Inventory and validate artifacts + +Start by identifying: +- metric tables (`csv`, `json`, `tsv`, logs), +- training curves and checkpoints, +- seeds / repeated runs, +- baselines, ablations, and comparison families, +- evaluation protocol metadata. + +Validate: +- metric direction (higher/lower is better), +- unit of analysis (run, subject, fold, dataset, seed), +- number of runs / seeds, +- missing values or silent failures, +- comparability across methods. + +If the comparison is not statistically valid, say so before continuing. Do not treat repeated `subject × task` rows, folds, windows, trials, or seeds as independent units unless the design justifies it. +Common blocker: a `subject × task` summary table is usually a repeated-measure summary, not an independent subject-level sample. If subjects have multiple task rows or missing task cells, state that before any significance or winner claim. + +### 2. Lock the comparison questions + +Before running statistics, define the exact comparison questions: +- Which method is compared to which baseline? +- What is the primary metric? +- What is the repeated-measure unit? +- Which ablation or robustness questions matter? +- Which findings are decision-changing? + +Do not mix unrelated comparisons into one undifferentiated table. + +### 3. Run strict statistics + +Always produce: +- descriptive statistics: `mean ± std` when appropriate, +- `95% CI` or another clearly justified interval, +- run/seed counts, +- significance tests with assumptions stated, +- effect sizes, +- multiple-comparison handling when several contrasts are reported. + +Default expectation: +- check parametric assumptions first, +- use non-parametric fallback when assumptions fail, +- state exactly what was tested and on what samples. + +See: +- `references/statistical-methods.md` +- `references/statistical-reporting.md` + +### 4. Generate real scientific figures + +Produce actual figures whenever artifacts are available. + +Minimum expectation for a non-trivial analysis bundle: +- **one main comparison figure**, +- **one supporting figure** (training dynamics / ablation / breakdown / error analysis), +- **one exact numeric summary table** in markdown. + +Every main figure must define: +- figure purpose, +- plotted variables, +- error bar meaning, +- caption requirements, +- interpretation checklist. + +See: +- `references/visualization-best-practices.md` +- `references/figure-interpretation.md` + +### 5. Write analysis artifacts + +#### `analysis-report.md` +Summarize: +- the analysis question, +- key findings, +- strongest supported comparisons, +- main caveats, +- what changed in the experimental understanding, +- claim candidates that may later be used in reports or manuscript writing. + +Each claim candidate should use this shape: + +```md +## Claim Candidates + +- Claim: + - Source evidence: + - Allowed wording: + - Forbidden stronger wording: + - Uncertainty: + - Next check: + - Decision: keep | weaken | revise | discard +``` + +#### `stats-appendix.md` +Record: +- descriptive statistics, +- test choices, +- assumptions checked, +- effect sizes, +- confidence intervals, +- multiple comparison corrections, +- explicit blockers and limitations. + +#### `figure-catalog.md` +For each figure, record: +- filename, +- purpose, +- data source, +- caption draft requirements, +- key observation, +- interpretation checklist, +- known caveats. + +### 6. Final QA gate + +Do not finish until all are true: +- [ ] the primary comparison question is explicit, +- [ ] sample size / seed count is stated, +- [ ] inferential tests are justified, +- [ ] effect sizes are reported for major contrasts, +- [ ] real figures exist when data exists, +- [ ] each figure has an interpretation note, +- [ ] limitations and blockers are explicit, +- [ ] each supported or strong claim candidate has evidence, uncertainty, and allowed wording, +- [ ] over-strong manuscript wording is explicitly blocked when evidence is insufficient, +- [ ] no manuscript-style `Results` draft is included. + +## Output structure + +```text +analysis-output/ +├── analysis-report.md +├── stats-appendix.md +├── figure-catalog.md +└── figures/ + ├── figure-01-main-comparison.pdf + ├── figure-02-ablation.pdf + └── ... +``` + +## Figure interpretation rule + +For every major figure, answer all three questions: +1. **Why does this figure exist?** +2. **What exactly should the reader notice?** +3. **What does that observation change in our belief or next decision?** + +If a figure cannot answer question 3, it is probably decorative rather than scientific. + +## Read-only audit mode + +Use this mode when: +- the user asks to audit or review existing artifacts, +- the environment is read-only, +- the user forbids file writes or figure generation, +- core evidence is missing. + +Return: +- analysis questions, +- valid statistics, +- invalid or unsafe statistics, +- claim candidates with allowed and forbidden wording, +- blockers before report/figure generation. + +Do not create `analysis-output/`, figures, or reports in this mode. +Quarantine any statistics file whose interpretation contradicts its own p-value, test method, unit of analysis, or comparison family. Do not reuse that file for claim wording until provenance is checked. + +## Failure mode policy + +When inputs are incomplete, say so explicitly. + +Examples: +- no seed-level data -> descriptive summary only; inferential claims blocked, +- no comparable baseline outputs -> no significance claim, +- no readable logs -> cannot generate dynamics figure, +- too few runs -> effect size may be unstable; report this limitation. +- unclear unit of analysis -> no winner claim or significance claim, +- analysis file with contradictory interpretation -> quarantine it until provenance is checked. + +Never replace missing evidence with confident prose. + +## Reference files + +Load only what is needed: +- `references/statistical-methods.md` - test selection and assumptions +- `references/statistical-reporting.md` - minimum reporting standard +- `references/visualization-best-practices.md` - publication-quality figure rules +- `references/figure-interpretation.md` - how to explain figures with evidence +- `references/analysis-depth.md` - move from observation to mechanism and decision +- `references/common-pitfalls.md` - common analysis and reporting failures +- `../research-ideation/references/research-contract.md` - shared claim candidate and claim strength contract + +## Example files + +- `examples/example-analysis-report.md` +- `examples/example-stats-appendix.md` +- `examples/example-figure-catalog.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/USAGE.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/USAGE.md new file mode 100644 index 0000000..6890d42 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/USAGE.md @@ -0,0 +1,131 @@ +# Results Analysis Usage + +本技能用于生成 **strict analysis bundle**，不是写论文 Results 草稿。 + +## 默认产物 + +```text +analysis-output/ +├── analysis-report.md +├── stats-appendix.md +├── figure-catalog.md +└── figures/ +``` + +## 典型调用路径 + +```text +/analyze-results (Command) + ↓ +results-analysis (Skill) + ↓ +results-report (Skill, optional follow-up) +``` + +## 适用场景 + +- 多模型对比，需要严谨统计 +- 多 seed / 多 subject / 多 fold 结果汇总 +- 需要真实科研图，而不是只给 figure specs +- 需要为后续 `results-report` 提供可信分析底座 + +## 推荐工作流 + +### 1. 准备输入 + +至少整理出以下之一： +- seed-level `csv/json` +- 每个实验的日志或目录 +- baseline 与 ablation 的对应结果 +- 训练曲线 / evaluation 曲线 / confusion 或 breakdown 数据 + +### 2. 运行 `/analyze-results` + +```bash +/analyze-results path/to/results full +``` + +### 3. 期望输出 + +#### `analysis-report.md` +- 本轮分析回答的问题 +- 关键发现 +- 哪些比较成立 / 不成立 +- 主要 caveats +- 哪些发现值得进一步写成完整实验报告 + +#### `stats-appendix.md` +- `mean ± std` +- `95% CI` +- significance tests +- effect sizes +- multiple-comparison correction +- assumptions / fallback tests +- blockers + +#### `figure-catalog.md` +- 每张图的文件名 +- 图用途 +- 数据来源 +- caption 必须包含的信息 +- 图后 interpretation checklist + +#### `figures/` +- 真实科研图，优先 PDF/PNG 等可复用格式 + +## 最低质量要求 + +### 统计 +- 不能只报 best score +- 不能只报 p-value +- 不能混淆 std 和 sem +- 有多组比较时要说明 correction +- 假设不满足时必须切换或说明 non-parametric test + +### 图表 +- 有数据就要画真实图 +- 每个主图都要有误差条或不确定性信息（如适用） +- 图必须有明确用途，不能只是“好看” +- 图后必须说明看到了什么、意味着什么 + +### 解释 +- 先写 observation，再写 interpretation，最后写 implication +- 若无法支持 causal/mechanistic claim，必须保守表述 + +## 与 `results-report` 的关系 + +- `results-analysis`：负责严格统计、图表、证据核查 +- `results-report`：负责完整实验总结报告、叙事、复盘与决策 + +推荐顺序： + +```text +experiment artifacts + ↓ +results-analysis + ↓ +strict analysis bundle + ↓ +results-report +``` + +## 边界情况 + +### 输入不完整 +若缺少 seed-level 数据、日志或可比 baseline： +- 明确列出缺失项 +- 降级分析强度 +- 不生成超出证据边界的结论 + +### 无法出图 +如果数据结构不支持直接画图： +- 先说明原因 +- 指出还需要哪些字段 +- 不要拿“visualization specs”替代真实图作为完成态 + +## 参考阅读 + +- `references/statistical-reporting.md` +- `references/figure-interpretation.md` +- `references/analysis-depth.md` +- `references/common-pitfalls.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-analysis-report.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-analysis-report.md new file mode 100644 index 0000000..6aa39cf --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-analysis-report.md @@ -0,0 +1,57 @@ +# Strict Analysis Report + +## Analysis Question +- Compare Full Model, Frozen Encoder, and Subject Adapter on cross-subject decoding. +- Determine whether the adapter closes the transfer gap without sacrificing stability. + +## Data Inventory +- 3 model families +- 5 random seeds per family +- subject-level WER and CER +- training logs for convergence +- ablation outputs for adapter width + +## Executive Summary +- Subject Adapter improves mean WER over Frozen Encoder by 3.8 absolute points. +- The improvement is statistically significant under paired testing after multiple-comparison correction. +- Full fine-tuning remains strongest overall, but Subject Adapter offers the best compute-performance tradeoff. +- Performance variance is lower than Frozen Encoder, suggesting a more stable transfer path. + +## Main Findings + +### 1. Main comparison +- Full fine-tuning: `31.4 ± 1.9` WER +- Subject Adapter: `33.2 ± 1.3` WER +- Frozen Encoder: `37.0 ± 2.1` WER + +Observation: +- Subject Adapter consistently outperforms Frozen Encoder across all 5 seeds. + +Interpretation: +- The transfer bottleneck is not purely feature reuse; a light adaptation head captures subject-specific alignment that freezing alone misses. + +Implication: +- Future work should prioritize adapter variants before investing in heavier full-model tuning. + +### 2. Stability +- Subject Adapter has the smallest seed variance among transfer-friendly methods. +- Convergence curves show less oscillation after epoch 8. + +Interpretation: +- Adapter tuning is not only better on average, but easier to optimize. + +### 3. Ablation +- Reducing adapter width from 256 to 64 hurts WER by 1.6 points. +- Increasing from 256 to 512 yields only marginal improvement. + +Interpretation: +- Most of the benefit is captured at moderate width; scale-up is not the current bottleneck. + +## Caveats +- Only 5 seeds; inference about tails remains limited. +- Subject count is modest, so subject-level heterogeneity may still be under-estimated. +- Training-time comparison depends on identical hardware assumptions. + +## Recommended Next Move +- Promote this finding into a `results-report` note focused on adapter vs freezing. +- Run one robustness pass on held-out low-resource subjects. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-figure-catalog.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-figure-catalog.md new file mode 100644 index 0000000..d9222f1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-figure-catalog.md @@ -0,0 +1,33 @@ +# Figure Catalog + +## Figure 1 — Main comparison +- **Filename**: `figures/figure-01-main-comparison.pdf` +- **Purpose**: Compare WER across Full fine-tuning, Subject Adapter, and Frozen Encoder. +- **Data source**: `metrics/summary.csv` +- **Plot type**: Bar + scatter overlay of seed-level points. +- **Error bars**: 95% CI. +- **Caption must include**: + - metric direction, + - number of seeds, + - meaning of error bars, + - whether significance markers are corrected. +- **Key observation**: Subject Adapter closes most of the freezing gap. +- **Interpretation checklist**: + - Is the adapter improvement consistent across seeds? + - Is the gap practically meaningful, not just statistically significant? + - Does the figure support a design decision? + +## Figure 2 — Convergence dynamics +- **Filename**: `figures/figure-02-training-dynamics.pdf` +- **Purpose**: Compare optimization stability over epochs. +- **Data source**: `logs/train_curves.csv` +- **Plot type**: Mean line + uncertainty ribbon. +- **Caption must include**: + - smoothing rule if any, + - whether ribbon is std or CI, + - training/eval split. +- **Key observation**: Frozen Encoder shows larger oscillation after epoch 8. +- **Interpretation checklist**: + - Is instability transient or persistent? + - Does curve shape match final metric variance? + - Does this explain why one method is harder to tune? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-stats-appendix.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-stats-appendix.md new file mode 100644 index 0000000..79ecbfc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/examples/example-stats-appendix.md @@ -0,0 +1,36 @@ +# Statistical Appendix + +## Primary Metric +- Word Error Rate (WER), lower is better. + +## Sample Structure +- Unit of analysis: seed-level run, paired by shared data split and subject pool. +- Number of seeds per condition: 5. + +## Descriptive Statistics + +| Condition | Mean WER | Std | 95% CI | +|---|---:|---:|---:| +| Full fine-tuning | 31.4 | 1.9 | [29.8, 33.0] | +| Subject Adapter | 33.2 | 1.3 | [32.1, 34.3] | +| Frozen Encoder | 37.0 | 2.1 | [35.1, 38.9] | + +## Assumption Checks +- Shapiro-Wilk on paired differences: `p = 0.19` +- No strong evidence against normality for the primary contrast. +- Given small n, interpretation remains conservative. + +## Inferential Tests + +| Contrast | Test | Statistic | p | Effect size | Correction | +|---|---|---|---:|---:|---| +| Subject Adapter vs Frozen Encoder | paired t-test | `t(4) = -4.11` | 0.014 | Cohen's `d = 1.84` | Holm | +| Full fine-tuning vs Subject Adapter | paired t-test | `t(4) = -2.03` | 0.112 | Cohen's `d = 0.91` | Holm | + +## Interpretation Guardrails +- First contrast is supported after correction. +- Second contrast trends in favor of full fine-tuning but is not conclusive at this sample size. + +## Blockers / Limits +- No subject-level bootstrap yet. +- No calibration analysis available. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/analysis-depth.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/analysis-depth.md new file mode 100644 index 0000000..5713c62 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/analysis-depth.md @@ -0,0 +1,39 @@ +# Analysis Depth Guide + +Move beyond “method A > method B”. + +## Four-layer depth ladder + +### 1. Observation +What changed? +- absolute gap +- relative gap +- stability change +- subgroup pattern + +### 2. Interpretation +What is the most defensible explanation? +- optimization stability +- inductive bias match +- subject/domain shift handling +- data scarcity sensitivity + +### 3. Constraint +What prevents overclaiming? +- low sample size +- only one dataset +- missing subgroup coverage +- no robustness sweep + +### 4. Decision +What should happen next? +- promote into durable result note +- run an ablation +- stop an unpromising branch +- update the active plan + +## Good report sentence pattern +- “We observe X.” +- “This supports Y because Z evidence is present.” +- “However, the claim is bounded by A.” +- “Therefore the next decision is B.” diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/common-pitfalls.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/common-pitfalls.md new file mode 100644 index 0000000..559f29a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/common-pitfalls.md @@ -0,0 +1,28 @@ +# Common Pitfalls in Experimental Analysis + +## Statistical pitfalls +- Reporting only the best run +- Mixing seed-level and subject-level units +- Running many contrasts without correction +- Reporting significance without effect size +- Using parametric tests after failed assumptions without explanation + +## Visualization pitfalls +- No real figure despite readable data +- Plot without uncertainty information +- Overcrowded multi-panel figure with no message hierarchy +- Caption missing n / error-bar meaning +- Figure not referenced or interpreted in text + +## Reasoning pitfalls +- Confusing correlation with mechanism +- Treating trend as conclusion +- Ignoring negative results +- Hiding instability behind a mean value +- Turning raw logs into durable conclusions too early + +## Reporting pitfalls +- Writing paper prose before evidence is stabilized +- Mixing analysis artifact with final narrative artifact +- Not separating blocker from conclusion +- Forgetting to state what decision the analysis changes diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/figure-interpretation.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/figure-interpretation.md new file mode 100644 index 0000000..75e25db --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/figure-interpretation.md @@ -0,0 +1,30 @@ +# Figure Interpretation Guide + +A scientific figure is incomplete until the text answers: +1. why the figure exists, +2. what the reader should notice, +3. why that observation matters. + +## Minimal interpretation block + +For each figure, provide: +- **Purpose**: the research question this figure addresses +- **Observation**: the concrete pattern seen in the plot +- **Interpretation**: the mechanism or explanation supported by the evidence +- **Implication**: what decision, next experiment, or claim changes because of it + +## Caption checklist + +A usable caption should specify: +- what is plotted, +- what each axis means, +- sample size, +- what error bars / ribbons represent, +- any normalization or smoothing, +- any significance marker convention. + +## Anti-patterns +- restating the axis labels as “interpretation” +- giving only aesthetic comments +- making causal claims unsupported by the plot +- repeating the caption without adding insight diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/statistical-methods.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/statistical-methods.md new file mode 100644 index 0000000..db3e74f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/statistical-methods.md @@ -0,0 +1,561 @@ +# Statistical Methods for ML/AI Experiments + +完整的统计分析方法指南，用于 ML/AI 实验结果分析。 + +## 基础统计量 + +### 均值 (Mean) + +**定义**: 所有观测值的平均值 + +**公式**: μ = (Σx) / n + +**报告格式**: "模型在测试集上达到 85.3% 的准确率" + +### 标准差 (Standard Deviation, SD) + +**定义**: 衡量数据分散程度 + +**公式**: SD = √[Σ(x - μ)² / (n-1)] + +**报告格式**: "准确率为 85.3% ± 2.1%（标准差）" + +**何时使用**: 描述数据的变异性 + +### 标准误 (Standard Error, SE) + +**定义**: 样本均值的标准差 + +**公式**: SE = SD / √n + +**报告格式**: "准确率为 85.3% ± 0.7%（标准误）" + +**何时使用**: 估计均值的不确定性 + +### 标准差 vs 标准误 + +| 特性 | 标准差 (SD) | 标准误 (SE) | +|------|------------|------------| +| 含义 | 数据的分散程度 | 均值估计的不确定性 | +| 随样本量变化 | 不变 | 减小（∝ 1/√n） | +| 用途 | 描述数据变异 | 推断总体均值 | +| 报告场景 | 描述性统计 | 推断性统计 | + +**重要**: 论文中必须明确说明使用的是标准差还是标准误。 + +### 置信区间 (Confidence Interval) + +**定义**: 总体参数的可能范围 + +**95% 置信区间公式**: CI = μ ± t(α/2, n-1) × SE + +**报告格式**: "准确率为 85.3% [95% CI: 83.9%, 86.7%]" + +**解释**: 95% 的置信区间意味着如果重复实验多次，95% 的区间会包含真实值。 + +## 预先检验（必须执行） + +在进行参数检验前，必须验证数据是否满足检验的假设条件。 + +### 1. 正态性检验 (Normality Test) + +**目的**: 验证数据是否服从正态分布 + +**何时需要**: 使用 t-test、ANOVA 等参数检验前 + +**常用方法**: + +#### Shapiro-Wilk 检验 +- **适用**: 样本量 n < 50 +- **零假设**: 数据服从正态分布 +- **判断**: p > 0.05 → 接受正态分布假设 +- **使用场景**: 小样本，最常用 + +#### Kolmogorov-Smirnov 检验 +- **适用**: 样本量 n ≥ 50 +- **零假设**: 数据服从正态分布 +- **判断**: p > 0.05 → 接受正态分布假设 +- **使用场景**: 大样本 + +#### Anderson-Darling 检验 +- **适用**: 所有样本量 +- **优点**: 对尾部偏离更敏感 +- **使用场景**: 需要检测尾部异常时 + +#### Q-Q 图 (Quantile-Quantile Plot) +- **类型**: 图形化方法 +- **判断**: 点接近直线 → 正态分布 +- **优点**: 直观展示偏离程度 +- **使用场景**: 配合数值检验使用 + +**不满足正态性时的处理**: +1. 数据转换（log, sqrt, Box-Cox） +2. 使用非参数检验（Wilcoxon, Mann-Whitney U） +3. 增加样本量（中心极限定理） + +### 2. 方差齐性检验 (Homogeneity of Variance) + +**目的**: 验证多组数据的方差是否相等 + +**何时需要**: 使用独立样本 t-test、ANOVA 前 + +**常用方法**: + +#### Levene 检验 +- **适用**: 最常用，对非正态分布鲁棒 +- **零假设**: 各组方差相等 +- **判断**: p > 0.05 → 接受方差齐性假设 +- **使用场景**: 默认选择 + +#### Bartlett 检验 +- **适用**: 数据严格正态分布时 +- **零假设**: 各组方差相等 +- **判断**: p > 0.05 → 接受方差齐性假设 +- **使用场景**: 正态性已验证 + +#### Brown-Forsythe 检验 +- **适用**: Levene 检验的改进版 +- **优点**: 对非正态分布更鲁棒 +- **使用场景**: 数据明显偏态时 + +**不满足方差齐性时的处理**: +1. 使用 Welch's t-test（不假设方差相等） +2. 使用 Welch's ANOVA +3. 数据转换 +4. 使用非参数检验 + +### 3. 独立性检验 + +**目的**: 验证观测值之间是否独立 + +**何时需要**: 所有统计检验前 + +**常见违反独立性的情况**: +- 时间序列数据（自相关） +- 重复测量（同一对象多次测量） +- 聚类数据（同一组内的观测） + +**处理方法**: +- 时间序列：使用时间序列分析方法 +- 重复测量：使用配对检验或混合效应模型 +- 聚类数据：使用多层模型或聚类标准误 + +### 4. 异常值检测 + +**目的**: 识别和处理极端值 + +**常用方法**: + +#### IQR 方法 +- **定义**: 异常值 = Q1 - 1.5×IQR 或 Q3 + 1.5×IQR 之外 +- **使用场景**: 最常用，简单直观 + +#### Z-score 方法 +- **定义**: |Z| > 3 为异常值 +- **使用场景**: 数据近似正态分布 + +#### Grubbs 检验 +- **适用**: 检测单个异常值 +- **使用场景**: 正态分布数据 + +**处理异常值**: +1. 检查是否为数据错误 +2. 报告异常值的存在 +3. 进行敏感性分析（有/无异常值） +4. 使用鲁棒统计方法 + +## 预先检验决策树 + +``` +开始 + ↓ +样本量 < 30？ + ↓ 是 + 检查正态性（Shapiro-Wilk） + ↓ 不满足 + 使用非参数检验 + ↓ 否 + 检查正态性（K-S 或 Q-Q 图） + ↓ 满足 + 两组比较？ + ↓ 是 + 检查方差齐性（Levene） + ↓ 满足 + 独立样本 t-test + ↓ 不满足 + Welch's t-test + ↓ 否 + 多组比较？ + ↓ 是 + 检查方差齐性（Levene） + ↓ 满足 + ANOVA + ↓ 不满足 + Welch's ANOVA +``` + +## 预先检验报告模板 + +**论文中应报告**: + +"在进行参数检验前，我们使用 Shapiro-Wilk 检验验证了数据的正态性（方法 A: W = 0.96, p = 0.23; 方法 B: W = 0.95, p = 0.18），使用 Levene 检验验证了方差齐性（F = 1.23, p = 0.31）。所有检验均满足参数检验的假设条件。" + +**如果不满足假设**: + +"Shapiro-Wilk 检验显示数据不满足正态性假设（方法 A: W = 0.87, p = 0.01），因此我们使用非参数的 Mann-Whitney U 检验进行比较。" + +## 假设检验（参数检验） + +### 1. t-test（两组对比） + +**用途**: 比较两个方法的性能差异 + +**假设条件**: +- 数据服从正态分布 +- 方差齐性（独立样本 t-test） +- 观测值独立 + +#### 独立样本 t-test (Independent Samples t-test) + +**使用场景**: 比较两个独立组的均值 +- 例：方法 A vs 方法 B 在不同数据集上的性能 + +**假设**: +- H₀: μ₁ = μ₂（两组均值相等） +- H₁: μ₁ ≠ μ₂（两组均值不等） + +**报告格式**: "方法 A (85.3% ± 2.1%) 显著优于方法 B (82.1% ± 1.8%), t(18) = 3.45, p = 0.003" + +**何时使用**: ✅ 两个独立组，满足正态性和方差齐性 + +#### 配对样本 t-test (Paired Samples t-test) + +**使用场景**: 比较同一组对象在两种条件下的表现 +- 例：同一数据集上，方法 A vs 方法 B 的性能 + +**假设**: +- H₀: μd = 0（差值的均值为0） +- H₁: μd ≠ 0（差值的均值不为0） + +**报告格式**: "在10个数据集上，方法 A 显著优于方法 B, t(9) = 4.23, p = 0.002" + +**何时使用**: ✅ 配对数据，同一对象的前后对比 + +#### Welch's t-test + +**使用场景**: 两组方差不相等时 +- 例：方差齐性检验不通过（Levene's test p < 0.05） + +**优点**: 不假设方差相等，更鲁棒 + +**报告格式**: "方法 A 显著优于方法 B, Welch's t(16.3) = 3.21, p = 0.005" + +**何时使用**: ✅ 方差齐性检验失败时的替代方案 + +### 2. ANOVA（多组对比） + +**用途**: 同时比较三个或更多方法 + +**假设条件**: +- 数据服从正态分布 +- 方差齐性 +- 观测值独立 + +#### 单因素 ANOVA (One-Way ANOVA) + +**使用场景**: 比较多个独立组的均值 +- 例：方法 A vs B vs C vs D 的性能对比 + +**假设**: +- H₀: μ₁ = μ₂ = μ₃ = ... = μk（所有组均值相等） +- H₁: 至少有一组均值不同 + +**报告格式**: "不同方法之间存在显著差异, F(3, 36) = 8.45, p < 0.001" + +**何时使用**: ✅ 三个或更多独立组 + +**重要**: ANOVA 只告诉你"至少有一组不同"，需要事后检验找出具体哪些组不同。 + +#### 重复测量 ANOVA (Repeated Measures ANOVA) + +**使用场景**: 同一组对象在多个条件下的表现 +- 例：同一数据集上，多个方法的性能对比 + +**假设**: +- H₀: 所有条件下的均值相等 +- H₁: 至少有一个条件的均值不同 + +**报告格式**: "不同方法之间存在显著差异, F(3, 27) = 12.34, p < 0.001" + +**何时使用**: ✅ 配对数据，多个条件的对比 + +#### 双因素 ANOVA (Two-Way ANOVA) + +**使用场景**: 研究两个因素的影响及其交互作用 +- 例：方法类型（因素1）× 数据集大小（因素2）对性能的影响 + +**报告格式**: +- "方法类型主效应显著, F(2, 54) = 15.23, p < 0.001" +- "数据集大小主效应显著, F(2, 54) = 8.91, p < 0.001" +- "交互作用不显著, F(4, 54) = 1.23, p = 0.31" + +**何时使用**: ✅ 研究多个因素及其交互作用 + +#### Welch's ANOVA + +**使用场景**: 方差不齐时的 ANOVA 替代方案 + +**报告格式**: "不同方法之间存在显著差异, Welch's F(3, 18.5) = 7.89, p = 0.002" + +**何时使用**: ✅ 方差齐性检验失败时 + +### 3. 事后检验 (Post-hoc Tests) + +**目的**: ANOVA 显著后，找出具体哪些组不同 + +**常用方法**: + +#### Tukey HSD (Honestly Significant Difference) + +**使用场景**: ANOVA 后的标准事后检验 +- **优点**: 控制家族错误率 +- **适用**: 各组样本量相等或接近 +- **报告**: "Tukey HSD 检验显示，方法 A 显著优于方法 B (p = 0.003) 和方法 C (p = 0.012)" + +**何时使用**: ✅ 默认选择，最常用 + +#### Bonferroni 校正 + +**使用场景**: 保守的事后检验 +- **优点**: 简单，控制家族错误率 +- **缺点**: 过于保守 +- **报告**: "Bonferroni 校正后，方法 A 显著优于方法 B (p = 0.002)" + +**何时使用**: ✅ 需要严格控制 Type I 错误时 + +#### Scheffé 检验 + +**使用场景**: 最保守的事后检验 +- **优点**: 适用于所有对比（包括复杂对比） +- **缺点**: 功效最低 +- **报告**: "Scheffé 检验显示，方法 A 显著优于方法 B (p = 0.015)" + +**何时使用**: ✅ 需要进行复杂对比时 + +#### Dunnett 检验 + +**使用场景**: 多个实验组与一个对照组比较 +- **优点**: 专门设计用于与对照组比较 +- **报告**: "Dunnett 检验显示，方法 A、B、C 均显著优于基线方法 (p < 0.01)" + +**何时使用**: ✅ 有明确的对照组（基线方法）时 + +## 假设检验（非参数检验） + +**何时使用非参数检验**: +- 数据不满足正态分布假设 +- 样本量很小（n < 30） +- 数据为序数或等级数据 +- 存在明显的异常值 + +### 4. Wilcoxon 检验（配对数据） + +**用途**: 配对数据的非参数检验，t-test 的非参数替代 + +**使用场景**: 同一数据集上，两个方法的性能对比 +- 例：10个数据集上，方法 A vs 方法 B + +**假设**: +- H₀: 两组的中位数相等 +- H₁: 两组的中位数不等 + +**报告格式**: "Wilcoxon 符号秩检验显示，方法 A 显著优于方法 B, Z = 2.81, p = 0.005" + +**何时使用**: ✅ 配对数据，不满足正态性假设 + +### 5. Mann-Whitney U 检验（独立数据） + +**用途**: 独立样本的非参数检验，独立样本 t-test 的非参数替代 + +**使用场景**: 两个独立组的性能对比 +- 例：方法 A 在数据集1上 vs 方法 B 在数据集2上 + +**假设**: +- H₀: 两组的分布相同 +- H₁: 两组的分布不同 + +**报告格式**: "Mann-Whitney U 检验显示，方法 A 显著优于方法 B, U = 45, p = 0.012" + +**何时使用**: ✅ 独立样本，不满足正态性假设 + +**别名**: Wilcoxon 秩和检验 + +### 6. Kruskal-Wallis 检验（多组对比） + +**用途**: 多组独立样本的非参数检验，ANOVA 的非参数替代 + +**使用场景**: 三个或更多方法的性能对比 +- 例：方法 A vs B vs C vs D + +**假设**: +- H₀: 所有组的分布相同 +- H₁: 至少有一组的分布不同 + +**报告格式**: "Kruskal-Wallis 检验显示，不同方法之间存在显著差异, H(3) = 15.23, p = 0.002" + +**何时使用**: ✅ 多组独立样本，不满足正态性假设 + +**事后检验**: Dunn 检验（带 Bonferroni 校正） + +### 7. Friedman 检验（重复测量） + +**用途**: 配对数据的多组非参数检验，重复测量 ANOVA 的非参数替代 + +**使用场景**: 同一数据集上，多个方法的性能对比 +- 例：10个数据集上，方法 A vs B vs C vs D + +**假设**: +- H₀: 所有条件下的分布相同 +- H₁: 至少有一个条件的分布不同 + +**报告格式**: "Friedman 检验显示，不同方法之间存在显著差异, χ²(3) = 18.45, p < 0.001" + +**何时使用**: ✅ 配对数据，多组对比，不满足正态性假设 + +**事后检验**: Nemenyi 检验或 Wilcoxon 符号秩检验（带 Bonferroni 校正） + +### 8. Sign 检验 + +**用途**: 最简单的配对数据非参数检验 + +**使用场景**: 只关心方向（哪个更好），不关心差异大小 +- 例：方法 A 在多少个数据集上优于方法 B + +**假设**: +- H₀: 正负差异的数量相等 +- H₁: 正负差异的数量不等 + +**报告格式**: "Sign 检验显示，方法 A 在 10 个数据集中的 8 个上优于方法 B, p = 0.055" + +**何时使用**: ✅ 只关心胜负，不关心差异大小 + +**优点**: 最鲁棒，对异常值不敏感 +**缺点**: 功效最低 + +## 统计检验选择流程图 + +``` +数据类型？ + ↓ +配对数据？ + ↓ 是 + 两组对比？ + ↓ 是 + 正态性检验 + ↓ 满足 + 配对 t-test + ↓ 不满足 + Wilcoxon 符号秩检验 + ↓ 否（多组） + 正态性检验 + ↓ 满足 + 重复测量 ANOVA + ↓ 不满足 + Friedman 检验 + ↓ 否（独立数据） + 两组对比？ + ↓ 是 + 正态性检验 + ↓ 满足 + 方差齐性检验 + ↓ 满足 + 独立 t-test + ↓ 不满足 + Welch's t-test + ↓ 不满足 + Mann-Whitney U 检验 + ↓ 否（多组） + 正态性检验 + ↓ 满足 + 方差齐性检验 + ↓ 满足 + ANOVA + 事后检验 + ↓ 不满足 + Welch's ANOVA + Games-Howell + ↓ 不满足 + Kruskal-Wallis + Dunn 检验 +``` + +## 多重比较校正 + +**问题**: 多次检验增加 Type I 错误（假阳性）概率 + +**公式**: P(至少一次错误) = 1 - (1-α)^k，其中 k 为检验次数 + +**常用方法**: + +| 方法 | 公式 | 保守程度 | 使用场景 | +|------|------|----------|----------| +| Bonferroni | α' = α/k | 最保守 | 少量检验 | +| Holm-Bonferroni | 逐步校正 | 较保守 | 中等数量检验 | +| FDR (Benjamini-Hochberg) | 控制错误发现率 | 较宽松 | 大量检验，探索性分析 | + +## 效应量 + +**定义**: 衡量差异的实际大小，独立于样本量 + +**常用指标**: + +| 效应量 | 适用场景 | 解释 | +|--------|----------|------| +| Cohen's d | t-test | \|d\| < 0.2 小，0.2-0.5 中，≥0.8 大 | +| η² (Eta squared) | ANOVA | 0.01 小，0.06 中，0.14 大 | +| r (相关系数) | 非参数检验 | 0.1 小，0.3 中，0.5 大 | + +**报告**: 必须同时报告 p-value 和效应量 + +## 实验设计要点 + +**重复次数**: 最少 3-5 次，推荐 5-10 次，高方差任务 10+ 次 + +**随机种子**: 报告所有使用的随机种子，确保可重现 + +**交叉验证**: k-fold (k=5 或 10) 用于评估泛化性能 + +## 常见错误 + +1. **Cherry-picking**: 只报告最好结果 → 报告所有实验 +2. **p-hacking**: 尝试多种分析找显著结果 → 预先确定方法 +3. **混淆 SD 和 SE**: 不说明使用哪个 → 明确标注 +4. **忽略多重比较**: 多次检验不校正 → 使用 Bonferroni/FDR +5. **只报告 p-value**: 缺少效应量 → 同时报告两者 + +## 报告检查清单 + +- [ ] 报告均值和标准差/标准误（明确标注） +- [ ] 报告实验重复次数 +- [ ] 执行预先检验（正态性、方差齐性） +- [ ] 选择适当的统计检验 +- [ ] 报告完整统计信息（检验统计量、自由度、p-value） +- [ ] 报告效应量 +- [ ] 多重比较进行校正 +- [ ] 说明随机种子设置 + +## 参考资源 + +- [Nature Statistics Checklist](https://www.nature.com/documents/nr-reporting-summary-flat.pdf) +- [ASA Statement on P-Values](https://www.amstat.org/asa/files/pdfs/p-valuestatement.pdf) +- [Reporting Statistics in Psychology](https://apastyle.apa.org/instructional-aids/numbers-statistics-guide.pdf) + +## 总结 + +统计分析的核心原则： + +1. **预先检验** - 验证假设条件 +2. **完整报告** - 均值、标准差/标准误、样本量 +3. **适当检验** - 根据数据特征选择方法 +4. **多重校正** - 多次比较时校正 α +5. **效应量** - 不只报告 p-value +6. **可重现** - 提供足够细节 + +遵循这些原则可以确保实验结果的统计严谨性和可信度。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/statistical-reporting.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/statistical-reporting.md new file mode 100644 index 0000000..9719b36 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/statistical-reporting.md @@ -0,0 +1,42 @@ +# Statistical Reporting Standard + +## Minimum reporting package + +For every major comparison, report: +- metric definition and direction, +- unit of analysis, +- sample size / run count, +- descriptive statistics, +- uncertainty estimate, +- inferential test, +- effect size, +- correction strategy when multiple contrasts exist, +- limitation if assumptions or sample size are weak. + +## Required fields + +### Descriptive +- `mean ± std` when repeated runs are comparable +- `95% CI` when inference is discussed +- median / IQR when distribution is strongly non-normal + +### Inferential +- exact test name +- test statistic and degrees of freedom when applicable +- p-value format +- effect size +- correction method for multiple comparisons + +## Do not do these +- report only best run +- report only p-values +- hide non-significant comparisons +- treat unstable trends as conclusions +- switch tests without stating why + +## Default wording rule + +Use three layers: +1. **Observation** — what changed numerically +2. **Support** — what the test/effect size says +3. **Boundary** — what remains uncertain diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/visualization-best-practices.md b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/visualization-best-practices.md new file mode 100644 index 0000000..1571cba --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-analysis/references/visualization-best-practices.md @@ -0,0 +1,269 @@ +# Visualization Best Practices for ML/AI Papers + +论文级可视化的最佳实践指南。 + +## 核心原则 + +1. **清晰性** - 信息传达清晰，无歧义 +2. **准确性** - 数据表示准确，不误导 +3. **可访问性** - 色盲友好，黑白打印可读 +4. **专业性** - 符合学术出版标准 + +## 图表格式要求 + +### 矢量图 vs 位图 + +| 格式 | 类型 | 使用场景 | 质量 | +|------|------|----------|------| +| PDF/EPS | 矢量图 | 图表、曲线、示意图 | ✅ 推荐 | +| SVG | 矢量图 | 网页展示 | ✅ 可用 | +| PNG | 位图 | 照片、截图 | ⚠️ 需高分辨率（≥600 DPI） | +| JPG | 位图 | 照片 | ❌ 避免用于图表 | + +**规则**: 所有图表使用矢量图格式（PDF/EPS），照片使用高分辨率位图（PNG ≥600 DPI）。 + +## 配色方案 + +### 色盲友好配色 + +**推荐配色方案**: + +#### Okabe-Ito 配色（最常用） +- 橙色: #E69F00 +- 天蓝: #56B4E9 +- 绿色: #009E73 +- 黄色: #F0E442 +- 蓝色: #0072B2 +- 红色: #D55E00 +- 粉色: #CC79A7 +- 黑色: #000000 + +#### Paul Tol 配色 +- 适用于定性数据 +- 提供多种配色方案（亮色、柔和、对比） + +### 配色原则 + +1. **最多使用 5-7 种颜色** - 过多颜色难以区分 +2. **避免红绿组合** - 红绿色盲无法区分 +3. **测试黑白打印** - 确保灰度下可读 +4. **使用不同线型** - 配合颜色使用（实线、虚线、点线） + +## 图表类型选择 + +### 折线图 (Line Plot) + +**使用场景**: 展示趋势、训练曲线、时间序列 + +**要点**: +- 使用误差带（阴影区域）表示标准差/标准误 +- 线宽 1.5-2.0 pt +- 标记点大小适中（4-6 pt） +- 网格线透明度 0.3 + +**示例**: 训练损失曲线、准确率随 epoch 变化 + +### 柱状图 (Bar Plot) + +**使用场景**: 性能对比、消融实验 + +**要点**: +- 使用误差条表示不确定性 +- 柱子宽度一致 +- 间距适当（柱宽的 20-30%） +- 加粗最佳结果的柱子 + +**示例**: 不同方法的准确率对比 + +### 箱线图 (Box Plot) + +**使用场景**: 展示分布、识别异常值 + +**要点**: +- 显示中位数、四分位数、异常值 +- 适合展示多次运行的结果 +- 可与散点图叠加 + +**示例**: 多次运行的性能分布 + +### 散点图 (Scatter Plot) + +**使用场景**: 展示相关性、聚类效果 + +**要点**: +- 点的大小和透明度适当 +- 使用不同形状区分类别 +- 添加趋势线（如需要） + +**示例**: 预测值 vs 真实值、特征空间可视化 + +### 热力图 (Heatmap) + +**使用场景**: 混淆矩阵、相关性矩阵、注意力权重 + +**要点**: +- 使用顺序配色（单色渐变）或发散配色（双色渐变） +- 添加数值标注（如空间允许） +- 色条（colorbar）清晰标注 + +**示例**: 混淆矩阵、注意力可视化 + +## 图表元素规范 + +### 坐标轴 + +**X 轴和 Y 轴**: +- 标签字体大小: 10-12 pt +- 刻度字体大小: 8-10 pt +- 标签清晰描述变量和单位 +- 刻度间距合理 + +**坐标轴范围**: +- Y 轴通常从 0 开始（除非有特殊原因） +- 不要截断坐标轴夸大差异 +- 使用科学计数法表示大数值 + +### 图例 (Legend) + +**位置**: 不遮挡数据，通常放在右上角或外部 + +**内容**: +- 简洁描述每条曲线/柱子 +- 字体大小 8-10 pt +- 使用与图中一致的颜色和线型 + +### 标题和标签 + +**图标题**: 通常不在图内添加标题，使用 caption 代替 + +**Caption**: +- 独立完整，不依赖正文 +- 说明图表内容、实验设置、关键观察 +- 字体大小 9-10 pt + +**示例**: "图 1: 不同模型在测试集上的准确率对比。误差条表示 5 次运行的标准差。我们的方法（蓝色）在所有数据集上均优于基线方法。" + +## 误差表示 + +### 误差条 (Error Bars) + +**类型**: +- 标准差 (SD): 描述数据变异性 +- 标准误 (SE): 描述均值不确定性 +- 置信区间 (CI): 参数估计范围 + +**表示方法**: +- 柱状图: 垂直误差条 +- 折线图: 误差带（阴影区域） + +**必须说明**: 在 caption 中明确说明使用的是哪种误差 + +### 误差带 (Error Band) + +**折线图的误差表示**: +- 使用半透明阴影区域（alpha=0.2-0.3） +- 颜色与主线一致 +- 不要使用误差条（会使图表混乱） + +## 尺寸和分辨率 + +### 图表尺寸 + +**单栏图** (single-column): +- 宽度: 3.5 inches (约 9 cm) +- 高度: 2-3 inches + +**双栏图** (double-column): +- 宽度: 7 inches (约 18 cm) +- 高度: 3-5 inches + +**纵横比**: 通常 4:3 或 16:9 + +### 分辨率 + +**矢量图**: 无需考虑分辨率 + +**位图**: +- 最低: 300 DPI +- 推荐: 600 DPI +- 高质量: 1200 DPI + +## 常见错误 + +### 错误 1: 使用位图格式 + +❌ **错误**: 保存为 PNG/JPG +✅ **正确**: 保存为 PDF/EPS + +### 错误 2: 非色盲友好配色 + +❌ **错误**: 红色和绿色组合 +✅ **正确**: 使用 Okabe-Ito 配色 + +### 错误 3: 缺少误差表示 + +❌ **错误**: 只显示均值 +✅ **正确**: 添加误差条/误差带 + +### 错误 4: 坐标轴截断 + +❌ **错误**: Y 轴从 80% 开始（夸大差异） +✅ **正确**: Y 轴从 0% 开始（或说明原因） + +### 错误 5: 图表过于复杂 + +❌ **错误**: 一张图包含 10+ 条曲线 +✅ **正确**: 拆分为多张图或使用子图 + +### 错误 6: 字体过小 + +❌ **错误**: 标签字体 6 pt +✅ **正确**: 标签字体 10-12 pt + +## 检查清单 + +提交前检查： + +- [ ] 使用矢量图格式（PDF/EPS） +- [ ] 配色色盲友好（Okabe-Ito 或 Paul Tol） +- [ ] 黑白打印可读（测试过） +- [ ] 包含误差条/误差带 +- [ ] Caption 中说明误差类型 +- [ ] 坐标轴标签清晰（包含单位） +- [ ] 图例不遮挡数据 +- [ ] 字体大小适当（≥8 pt） +- [ ] 线宽适当（1.5-2.0 pt） +- [ ] Caption 独立完整 + +## 工具推荐 + +**Python**: +- matplotlib: 基础绘图 +- seaborn: 统计可视化 +- plotly: 交互式图表 + +**配色工具**: +- ColorBrewer: 配色方案选择 +- Coblis: 色盲模拟器 + +**格式转换**: +- Inkscape: SVG 编辑和转换 +- Adobe Illustrator: 专业图形编辑 + +## 参考资源 + +- [Ten Simple Rules for Better Figures](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833) +- [Okabe-Ito Color Palette](https://jfly.uni-koeln.de/color/) +- [Paul Tol's Notes on Colour](https://personal.sron.nl/~pault/) + +## 总结 + +论文级可视化的关键： + +1. **矢量图格式** - PDF/EPS +2. **色盲友好** - Okabe-Ito 配色 +3. **误差表示** - 误差条/误差带 +4. **清晰标注** - 坐标轴、图例、caption +5. **黑白可读** - 测试灰度打印 + +遵循这些原则可以创建清晰、准确、专业的论文图表。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/SKILL.md new file mode 100644 index 0000000..785b404 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/SKILL.md @@ -0,0 +1,186 @@ +--- +name: results-report +description: This skill should be used when the user asks to "write an experiment report", "summarize experimental results", "do experiment retrospection", "write a results report", "写实验总结报告", "写实验复盘", or mentions turning completed experiment artifacts into a structured, decision-oriented research report. It assumes strict analysis should come from `results-analysis` first. +version: 0.1.0 +tags: [Research, Reporting, Experiments, Obsidian] +--- + +# Results Report + +Write the **complete post-experiment summary report** after analysis artifacts are ready. + +This skill is for the stage **after** `results-analysis`. + +## Role boundary + +### `results-analysis` does +- strict statistics, +- real figures, +- figure interpretation scaffolding, +- stats appendix. + +### `results-report` does +- complete experiment wrap-up report, +- decision-oriented narrative, +- figure-by-figure interpretation inside a coherent structure, +- limitations, failure cases, and next actions, +- Obsidian write-back into `Results/Reports/`. + +When the task is to create or redesign paper-ready figures/tables themselves, rely on `publication-chart-skill` instead of expanding `results-report` into figure/table production. + +Do not replace strict analysis with confident prose. If the analysis bundle is missing, first identify the blocker and request or produce the missing bundle. + +Hard gate: do not write a complete report when `analysis-report.md`, `stats-appendix.md`, `figure-catalog.md`, provenance, or the primary comparison question is missing. In that case, write only a blocker summary and route back to `results-analysis`. + +## Default output + +The default report is an **internal research report**, not manuscript prose. + +It should be named as: + +```text +YYYY-MM-DD--{experiment-line}--r{round}--{purpose}.md +``` + +Example: +- `2026-03-18--freezing--r03--transfer-summary.md` +- `2026-03-18--contrastive-adversarial--r02--ablation-report.md` + +The note title should be: + +```text +{Experiment Line} / Round {N} / {Purpose} / {YYYY-MM-DD} +``` + +Read `references/report-naming.md` before finalizing the filename or note title. + +## Required frontmatter + +```yaml +--- +type: results-report +date: 2026-03-18 +experiment_line: freezing +round: 3 +purpose: transfer-summary +status: active +source_artifacts: + - analysis-output/analysis-report.md + - analysis-output/stats-appendix.md +linked_experiments: + - Experiments/Freezing-Study.md +linked_results: + - Results/Freezing-vs-Adapter.md +--- +``` + +## Default report structure + +The report must include all sections below. + +1. **Executive Summary** +2. **Experiment Identity and Decision Context** +3. **Setup and Evaluation Protocol** +4. **Main Findings** +5. **Statistical Validation** +6. **Figure-by-Figure Interpretation** +7. **Failure Cases / Negative Results / Limitations** +8. **What Changed Our Belief** +9. **Next Actions** +10. **Artifact and Reproducibility Index** + +Read `references/report-structure.md` before writing. + +## Workflow + +### 1. Confirm the report object + +Lock these fields first: +- date, +- experiment line, +- round, +- purpose, +- linked experiment note, +- linked durable result note if one already exists. + +If round is unknown, do not silently invent a semantic round. Use `r00` only as a temporary placeholder and state that it should be normalized later. + +### 2. Read the strict analysis bundle + +Minimum required inputs: +- `analysis-report.md` +- `stats-appendix.md` +- `figure-catalog.md` +- actual figures, if available + +If these are missing, either generate them first with `results-analysis` or explicitly state which claims cannot be supported. +Do not turn loose CSV/Markdown artifacts into a polished report unless the strict analysis bundle has already validated unit of analysis, primary metric, and claim wording. + +### 3. Write the report as a decision object + +This report is not a transcript of outputs. + +Each section must answer a real question: +- What did we test? +- What changed numerically? +- What is actually supported? +- What failed or remains uncertain? +- What should we do next? + +Read `references/decision-oriented-analysis.md` for the expected reasoning depth. + +### 4. Interpret figures inside the report + +Do not only attach figures. + +For each main figure: +- introduce why it is included, +- state the key observation, +- explain the supported interpretation, +- explain the decision implication. + +Read `references/figure-interpretation.md` and `references/statistical-completeness.md` as needed. + +### 5. Choose the write target explicitly + +If the current repo is bound to an Obsidian project knowledge base: +- create or update `Results/Reports/{report-name}.md`, +- link back to the relevant `Experiments/` note, +- update the matching canonical `Results/` note when a durable conclusion is now supported, +- append a short trace to today's `Daily/` note, +- update `.claude/project-memory/<project_id>.md`. + +If the repo is **not** bound: +- write the report as a local markdown artifact in the requested output location or next to the analysis bundle, +- keep the same filename contract, +- explicitly say that no Obsidian write-back was attempted. + +Use `obsidian-project-kb-core` conventions only for bound repos. Internal experiment reports belong in `Results/Reports/`, not `Writing/`. + +### 6. End with explicit next actions + +The report must end with operational decisions, for example: +- stop a weak branch, +- schedule one missing ablation, +- promote a stable finding into manuscript-facing writing, +- update the active plan. + +## Required quality bar + +- The report must be dateable, searchable, and attributable to one experiment line and one round. +- The report must cite actual evidence from the analysis bundle. +- The report must include negative results when they matter. +- The report must separate stable conclusion from tentative interpretation. +- The report must say what changed in project belief and what should happen next. +- The report must preserve Claim Candidate wording and must not promote `speculative` or `observed` claims into decisive conclusions. + +## Reference files + +Load only what is needed: +- `references/report-structure.md` +- `references/report-naming.md` +- `references/figure-interpretation.md` +- `references/statistical-completeness.md` +- `references/decision-oriented-analysis.md` +- `references/EVIDENCE-PROPAGATION.md` +- `examples/example-results-report.md` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/examples/example-results-report.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/examples/example-results-report.md new file mode 100644 index 0000000..603bf59 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/examples/example-results-report.md @@ -0,0 +1,83 @@ +--- +type: results-report +date: 2026-03-18 +experiment_line: freezing +round: 3 +purpose: transfer-summary +status: active +source_artifacts: + - analysis-output/analysis-report.md + - analysis-output/stats-appendix.md + - analysis-output/figure-catalog.md +linked_experiments: + - Experiments/Freezing-vs-Adapter.md +linked_results: + - Results/Adapter-Improves-Transfer.md +--- + +# Freezing / Round 3 / transfer-summary / 2026-03-18 + +## Executive Summary +- Round 3 tested whether a subject adapter recovers the performance lost by freezing most of the encoder. +- Across 5 seeds per condition, the adapter reduced mean WER by **3.8 absolute points** relative to the frozen encoder baseline. +- The current evidence supports keeping the adapter branch active, while pure freezing should be deprioritized. + +## Experiment Identity and Decision Context +- Experiment line: freezing +- Round: 3 +- Purpose: resolve whether the freezing gap is best handled by lightweight adaptation or by abandoning the freezing branch. +- Decision pressure: choose the next transfer branch before scheduling the next low-resource run block. + +## Setup and Evaluation Protocol +- Same subject pool and split as rounds 1-2. +- 5 seeds per condition. +- Primary metric: WER (lower is better). +- Compared methods: Full fine-tuning, Subject Adapter, Frozen Encoder. +- Statistical unit: seed-level final WER. + +## Main Findings +- Subject Adapter: **27.6 ± 1.0 WER**, 95% CI **[26.4, 28.8]**. +- Frozen Encoder: **31.4 ± 1.5 WER**, 95% CI **[29.6, 33.2]**. +- Full fine-tuning: **25.9 ± 0.8 WER**, 95% CI **[24.9, 26.9]**. +- Adapter beats Frozen Encoder in all 5 paired seed comparisons. + +## Statistical Validation +- Adapter vs Frozen Encoder: paired Wilcoxon signed-rank test, **p = 0.031**, Holm-corrected **p = 0.047**, matched-rank biserial effect size **r = 0.90**. +- Full fine-tuning vs Adapter: paired t-test, **p = 0.11**, Cohen's **d = 0.64**. +- Interpretation: the adapter gain over pure freezing is supported at current `n = 5`; the gap to full fine-tuning is directionally consistent but still underpowered. +- Unsupported claim boundary: this report does **not** claim generalization beyond the current subject pool or low-resource regime. + +## Figure-by-Figure Interpretation +### Figure 1 — Main comparison +- Why included: this is the core decision figure. +- Evidence carried in: mean WER, 95% CI, and paired-seed comparisons. +- Supported interpretation: lightweight subject adaptation closes most of the freezing gap. +- Decision implication: future transfer experiments should center on adapter design, not frozen-only variants. + +### Figure 2 — Training dynamics +- Why included: to explain stability differences. +- Evidence carried in: per-epoch validation traces across seeds. +- Supported interpretation: the frozen baseline oscillates more after epoch 8, matching its wider uncertainty interval. +- Decision implication: branch weakness is not only lower final accuracy but also worse optimization stability. + +## Failure Cases / Negative Results / Limitations +- Full fine-tuning still leads in absolute WER. +- The evidence is limited to one subject pool and 5 seeds. +- No low-resource stress test or out-of-domain subject split has been run yet. +- Adapter width was fixed in this round, so capacity trade-offs remain unresolved. + +## What Changed Our Belief +- Before round 3, it was plausible that freezing should be abandoned entirely. +- After round 3, the better hypothesis is that freezing alone is too rigid, but freezing plus lightweight adaptation remains viable. + +## Next Actions +- Run one low-resource robustness check for the adapter branch. +- Add a width ablation around the current best adapter size. +- Update the canonical result note for adapter-improves-transfer. + +## Artifact and Reproducibility Index +- `analysis-output/analysis-report.md` +- `analysis-output/stats-appendix.md` +- `analysis-output/figure-catalog.md` +- `analysis-output/figures/figure-01-main-comparison.pdf` +- `analysis-output/figures/figure-02-training-dynamics.pdf` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/EVIDENCE-PROPAGATION.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/EVIDENCE-PROPAGATION.md new file mode 100644 index 0000000..b094325 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/EVIDENCE-PROPAGATION.md @@ -0,0 +1,37 @@ +# Evidence Propagation + +Use this file to keep `results-analysis` outputs aligned with the final report. + +## Mapping rule + +- `analysis-report.md` -> main findings and narrative summary +- `analysis-report.md#Claim Candidates` -> claim wording, uncertainty, and decisions that can be carried into the report +- `stats-appendix.md` -> test choice, uncertainty, effect size, correction rule +- `figure-catalog.md` -> figure purpose and per-figure interpretation scaffolding +- figure files -> visual evidence cited in `Figure-by-Figure Interpretation` + +## Minimum statistical carry-over + +Every strong claim in a results report should preserve: +- sample size or run/seed count, +- metric definition, +- uncertainty summary, +- test name, +- effect size when relevant, +- multiple-comparison handling when relevant. + +## Unsupported claim rule + +If the analysis bundle does not support a claim strongly enough, keep the claim tentative and say why. +Do not upgrade a suggestive result into a decisive conclusion during report writing. + +## Claim candidate carry-over + +Every claim carried from `results-analysis` should preserve: +- the source evidence, +- the allowed wording, +- the forbidden stronger wording, +- uncertainty, +- next check or decision. + +Do not convert `speculative` or `observed` claims into decisive conclusions. The `What Changed Our Belief` section should cite either a Claim Candidate or an Evidence Record, not only free-form prose. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/decision-oriented-analysis.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/decision-oriented-analysis.md new file mode 100644 index 0000000..a63a0c3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/decision-oriented-analysis.md @@ -0,0 +1,17 @@ +# Decision-Oriented Analysis + +The purpose of a post-experiment report is not only to record what happened. +It should change the project's next decision. + +## Required final questions +- What should stop? +- What should continue? +- What should be tested next? +- What should be promoted into a durable result note? +- What, if anything, is ready for manuscript-facing writing? + +## Good closing pattern +- “This round supports X.” +- “It does not yet resolve Y.” +- “The main blocker is Z.” +- “Therefore the next concrete action is A.” diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/figure-interpretation.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/figure-interpretation.md new file mode 100644 index 0000000..1156d74 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/figure-interpretation.md @@ -0,0 +1,17 @@ +# Figure Interpretation in Results Reports + +A results report should not dump figures. + +For each major figure, write four blocks: +- **Why this figure exists** +- **What to notice** +- **What interpretation is supported** +- **What this changes in the project decision** + +## Example micro-structure + +### Figure X +- Purpose: compare adapter vs freezing under the same transfer setting. +- Observation: adapter improves mean WER and reduces variance. +- Interpretation: subject-specific adaptation likely resolves part of the transfer mismatch. +- Decision implication: prioritize adapter ablations before expanding frozen-only variants. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/report-naming.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/report-naming.md new file mode 100644 index 0000000..7132468 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/report-naming.md @@ -0,0 +1,53 @@ +# Report Naming Standard + +## Filename + +Use: + +```text +YYYY-MM-DD--{experiment-line}--r{round}--{purpose}.md +``` + +Rules: +- date must be the report date, +- `experiment-line` should be short and stable, +- `round` should be zero-padded only if that is already the project convention; otherwise `r3` / `r03` are both acceptable if used consistently, +- `purpose` should describe why the report exists, not a vague label like `summary` unless that is truly the purpose. + +Recommended purpose values: +- `transfer-summary` +- `ablation-report` +- `failure-analysis` +- `robustness-check` +- `round-review` + +## Title + +Use: + +```text +{Experiment Line} / Round {N} / {Purpose} / {YYYY-MM-DD} +``` + +## Frontmatter fields + +Required: +- `type: results-report` +- `date` +- `experiment_line` +- `round` +- `purpose` +- `status` +- `source_artifacts` +- `linked_experiments` +- `linked_results` + +## Placement in Obsidian + +Internal reports go to: + +```text +Results/Reports/{filename} +``` + +Do not put internal experiment reports in `Writing/` unless they are already manuscript/slides/rebuttal material. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/report-structure.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/report-structure.md new file mode 100644 index 0000000..e0eb247 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/report-structure.md @@ -0,0 +1,63 @@ +# Results Report Structure + +## 1. Executive Summary +Answer: +- what was tested, +- what the highest-confidence conclusion is, +- what decision this changes. + +## 2. Experiment Identity and Decision Context +Answer: +- which experiment line this belongs to, +- why this round was run, +- what prior uncertainty or decision it was meant to resolve. + +## 3. Setup and Evaluation Protocol +Answer: +- datasets / subjects / splits, +- methods compared, +- primary metrics, +- repeated-run structure, +- any deviations from prior protocol. + +## 4. Main Findings +Answer: +- what changed most, +- which comparison matters most, +- where the largest gains or failures appear. + +## 5. Statistical Validation +Answer: +- what evidence supports the major claims, +- what tests were used, +- where the evidence is weak. + +## 6. Figure-by-Figure Interpretation +For each main figure: +- why it is shown, +- what to notice, +- what is supported, +- what remains uncertain. + +## 7. Failure Cases / Negative Results / Limitations +Answer: +- what did not work, +- what instability appeared, +- what limits the current conclusion. + +## 8. What Changed Our Belief +Answer: +- which prior hypothesis is strengthened, +- weakened, +- or still unresolved. + +## 9. Next Actions +Answer: +- stop / continue / ablate / scale / write. + +## 10. Artifact and Reproducibility Index +List: +- source artifacts, +- figure paths, +- scripts/logs, +- linked Obsidian notes. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/statistical-completeness.md b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/statistical-completeness.md new file mode 100644 index 0000000..4c8756c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/results-report/references/statistical-completeness.md @@ -0,0 +1,19 @@ +# Statistical Completeness for Results Reports + +A report may summarize statistics, but it must not silently weaken them. + +## Always carry forward +- sample size / seed count +- metric direction +- descriptive statistics +- uncertainty estimate +- test choice +- effect size +- correction rule when relevant +- evidence boundary + +## Never do this in the report +- upgrade a trend to a conclusion +- omit the sample size +- replace effect size with adjectives like “large” without numbers +- cite a figure without saying what the uncertainty represents diff --git a/文档润色流和知识库构建流/claude-scholar/skills/review-response/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/review-response/SKILL.md new file mode 100644 index 0000000..6d8c504 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/review-response/SKILL.md @@ -0,0 +1,131 @@ +--- +name: review-response +description: Systematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates. +tags: [Research, Academic, Rebuttal, Paper Writing] +version: 0.1.0 +--- + +# Review Response + +A systematic review response workflow that helps researchers efficiently and professionally reply to reviewer comments. + +## Core Features + +1. **Review Analysis** - Parse and classify reviewer comments (Major/Minor/Typo/Misunderstanding) +2. **Response Strategy** - Develop response strategies for different comment types (Accept/Defend/Clarify/Experiment) +3. **Rebuttal Writing** - Write structured, professional rebuttal documents +4. **Tone Management** - Optimize tone to maintain professionalism, respect, and evidence-based arguments + +## Workflow + +``` +Receive reviewer comments -> Parse and classify -> Develop strategy -> Write responses -> Tone check -> Final rebuttal +``` + +## When to Use + +Use this skill when you need to: +- "Help me write a rebuttal" +- "How to respond to reviewer comments" +- "Analyze these review comments" +- "Develop a review response strategy" + +## Usage Steps + +1. **Provide reviewer comments** - Share the reviewer comments text or file with Claude +2. **Analysis and classification** - Claude automatically parses and classifies the comments +3. **Strategy recommendations** - Receive response strategy suggestions for each comment +4. **Write rebuttal** - Generate a structured rebuttal document based on the strategy +5. **Optimize tone** - Review and optimize the professionalism and politeness of responses + +## Core Principles + +- **Professionalism** - Maintain an academically professional tone and expression +- **Respectfulness** - Respect the reviewers' opinions and time +- **Evidence-based** - Support every response with sufficient reasoning and evidence +- **Completeness** - Ensure all reviewer comments receive a response + +## Success Factors (Based on ICLR Spotlight Paper Analysis) + +Key lessons extracted from successful rebuttal cases: + +### 1. Acknowledge Strengths, Respond Positively to Criticism +- Reviewers will first acknowledge the paper's strengths (novelty, impact, practical applicability) +- Even spotlight papers receive constructive criticism +- **Strategy**: Thank reviewers for acknowledged strengths first, then address criticism specifically + +### 2. Provide Clarity and Intuitive Understanding +- Even high-quality papers may have clarity issues +- Need to provide intuition and detailed explanations for readers with different backgrounds +- **Strategy**: Expand key sections, move technical details to appendix, add step-by-step walkthroughs + +### 3. Thorough Justification of Experimental Setup +- Need to justify experimental setup choices +- Consider and discuss alternative metrics +- Provide comprehensive experiments to support claims +- **Strategy**: Add ablation studies, explain why specific experimental setups were chosen + +### 4. Emphasis on Ethical Considerations +- For research involving privacy, security, and other sensitive topics, ethical considerations are crucial +- Reviewers pay special attention to ethical implications +- **Strategy**: Proactively discuss ethical considerations, even if reviewers don't explicitly request it + +### 5. Highlight Practical Application Value +- Reviewers value practical applicability and scalability of methods +- "Easily applicable" and "scalable" are important strengths +- **Strategy**: Emphasize practical benefits and scalability in the rebuttal + +## Integration with active installed writing memory + +When the rebuttal task involves: +- tone calibration, +- rebuttal phrasing, +- clarification language, +- structuring multi-point responses, +- or learning from strong prior paper/review writing, + +read the active installed writing memory before drafting: + +- `~/.claude/skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md` on Claude Code installs +- the equivalent installed skill-home path on Codex/OpenCode branches +- otherwise skip this optional memory and continue with the local review-response references + +### Default read order for rebuttal work + +1. reviewer comments and paper context +2. optional `paper-miner-writing-memory.md` if available +3. `references/response-strategies.md` +4. `references/rebuttal-templates.md` +5. `references/tone-guidelines.md` + +Read narrowly: +- start with `How this helps our writing`, +- then inspect `Reusable phrasing`, +- then inspect `Venue-specific signals` if the rebuttal is venue-sensitive, +- use `Writing patterns mined` only when the response needs stronger rhetorical structure. + +Do not quote the memory mechanically. Use it to improve structure, clarity, restraint, and professionalism. + +## Evidence anchor rule + +Every response row must include one of: +- paper location, +- result table / figure / analysis artifact, +- citation / Evidence Record ID, +- planned experiment with status, +- `unresolved` if no evidence exists yet. + +Do not claim "we added experiments" or "the results show" without naming the artifact. If an objection has multiple atomic points, split it and cover each point separately. + +## Reference Documents + +For detailed guides, refer to: +- `references/review-classification.md` - Review comment classification criteria +- `references/response-strategies.md` - Response strategy library +- `references/rebuttal-templates.md` - Rebuttal templates and examples +- `references/tone-guidelines.md` - Tone and expression guidelines + +## Related Tools + +- **Agent**: `rebuttal-writer` - Dedicated agent for rebuttal writing and optimization +- **Command**: `/rebuttal <review_file>` - Quick-start the rebuttal workflow diff --git a/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/rebuttal-templates.md b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/rebuttal-templates.md new file mode 100644 index 0000000..8c32f45 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/rebuttal-templates.md @@ -0,0 +1,480 @@ +# Rebuttal 模板库 + +本文档提供系统化的rebuttal模板，帮助快速撰写专业、结构清晰的审稿响应。 + +## 基本结构 + +### 标准Rebuttal结构 + +```markdown +# Response to Reviewers + +We sincerely thank all reviewers for their valuable feedback and constructive suggestions. We have carefully addressed all comments and made substantial revisions to improve the manuscript. Below, we provide detailed responses to each reviewer's comments. + +--- + +## Response to Reviewer 1 + +### Major Comments + +**Comment 1.1**: [审稿人的原始意见] + +**Response**: [我们的回复] + +**Changes**: [具体修改内容和位置] + +--- + +**Comment 1.2**: [审稿人的原始意见] + +**Response**: [我们的回复] + +**Changes**: [具体修改内容和位置] + +--- + +### Minor Comments + +**Comment 1.3**: [审稿人的原始意见] + +**Response**: [我们的回复] + +**Changes**: [具体修改内容和位置] + +--- + +## Response to Reviewer 2 + +[同样的结构] + +--- + +## Response to Reviewer 3 + +[同样的结构] + +--- + +## Summary of Major Changes + +1. [主要修改1] +2. [主要修改2] +3. [主要修改3] + +We believe these revisions have significantly strengthened the manuscript and addressed all concerns raised by the reviewers. +``` + +--- + +## 开场白模板 + +### 模板 1: 标准感谢 + +``` +We sincerely thank all reviewers for their valuable feedback and constructive suggestions. We have carefully addressed all comments and made substantial revisions to improve the manuscript. Below, we provide detailed responses to each reviewer's comments. +``` + +### 模板 2: 强调改进 + +``` +We are grateful to the reviewers for their thorough and insightful comments. Their feedback has helped us significantly improve the quality and clarity of our work. We have made extensive revisions to address all concerns, and we believe the manuscript is now substantially stronger. +``` + +### 模板 3: 突出重点 + +``` +We thank the reviewers for their careful evaluation and constructive feedback. We have addressed all comments and made major revisions, including [关键改进1], [关键改进2], and [关键改进3]. We provide detailed responses below. +``` + + +--- + +## 回复模板（按策略分类） + +### Accept 策略模板 + +**模板 1: 简单接受** +``` +We thank the reviewer for this valuable suggestion. We have [具体修改]. [修改位置]. +``` + +**模板 2: 接受并扩展** +``` +We appreciate this insightful comment. We agree that [问题描述] is important. We have [具体修改1] and [具体修改2]. These changes are reflected in [位置1] and [位置2]. +``` + +**模板 3: 接受拼写/格式错误** +``` +We thank the reviewer for catching this. We have corrected [错误类型] throughout the manuscript. +``` + +--- + +### Defend 策略模板 + +**模板 1: 礼貌辩护** +``` +We appreciate the reviewer's concern. However, we respectfully note that [我们的做法] is motivated by [理由]. Specifically, [详细解释]. We have added this clarification to Section [X]. +``` + +**模板 2: 对比说明** +``` +We thank the reviewer for this suggestion. While [审稿人建议的方法] has advantages in [场景A], we chose [我们的方法] because [理由1] and [理由2]. Our preliminary experiments showed that [实验结果]. We have added this discussion to [位置]. +``` + +**模板 3: 技术限制** +``` +We appreciate this suggestion. However, [建议的方法] is not feasible in our setting due to [限制1] and [限制2]. Instead, we [我们的替代方案], which [优势]. We have clarified this in [位置]. +``` + + +--- + +### Clarify 策略模板 + +**模板 1: 礼貌澄清** +``` +We thank the reviewer for raising this point. We would like to respectfully clarify that [已有内容]. This is discussed in [具体位置]. To make this clearer, we have [改进措施]. +``` + +**模板 2: 指出已有内容** +``` +We appreciate this comment. We would like to note that we did [已完成的工作] in our study. Specifically, [详细说明]. These results are presented in [位置]. To make this more prominent, we have [改进措施]. +``` + +**模板 3: 承认表述不清** +``` +We thank the reviewer for this comment. We apologize for the confusion. What we meant is [澄清说明]. We have revised [位置] to make this clearer. +``` + +--- + +### Experiment 策略模板 + +**模板 1: 已完成实验** +``` +We thank the reviewer for this excellent suggestion. We have conducted additional experiments on [实验内容]. The results show that [主要发现]. Specifically, [详细结果]. These new results have been added to [位置] and discussed in [位置]. +``` + +**模板 2: 承诺进行实验** +``` +We appreciate this valuable suggestion. We agree that [实验的重要性]. We are currently conducting [实验内容] and will include the results in the revised manuscript. We expect to complete these experiments within [时间] and will update the manuscript accordingly. +``` + +**模板 3: 实验不可行但提供替代** +``` +We thank the reviewer for this suggestion. While [建议的实验] would be valuable, it is not feasible due to [限制]. However, we have conducted [替代实验], which provides similar insights. The results show [发现]. These have been added to [位置]. +``` + + +--- + +## 特殊场景模板 + +### 多个审稿人提出相同意见 + +**模板**: +``` +We thank Reviewers [X] and [Y] for raising this important point. We agree that [问题描述]. We have [具体修改]. These changes address both reviewers' concerns and are reflected in [位置]. +``` + +**示例**: +``` +We thank Reviewers 1 and 3 for raising this important point about the lack of ablation studies. We agree that ablation studies are crucial for understanding component contributions. We have conducted comprehensive ablation experiments examining [组件1], [组件2], and [组件3]. These changes address both reviewers' concerns and are reflected in Table 4 and Section 4.5. +``` + +--- + +### 审稿人意见相互矛盾 + +**模板**: +``` +We appreciate both reviewers' perspectives on [问题]. Reviewer [X] suggests [建议X], while Reviewer [Y] suggests [建议Y]. After careful consideration, we have [我们的选择] because [理由]. We believe this approach [优势] while addressing [关注点]. +``` + +**示例**: +``` +We appreciate both reviewers' perspectives on the dataset choice. Reviewer 1 suggests using dataset A for broader applicability, while Reviewer 2 suggests using dataset B for more controlled evaluation. After careful consideration, we have added experiments on both datasets. We believe this approach provides both breadth (dataset A) and depth (dataset B) while addressing both reviewers' concerns. The new results are presented in Table 5. +``` + +--- + +### 无法完全满足要求 + +**模板**: +``` +We thank the reviewer for this suggestion. While we agree that [建议的价值], [完全实现的困难]. However, we have [部分实现或替代方案], which [效果]. We acknowledge this limitation in [位置] and discuss it as future work. +``` + +**示例**: +``` +We thank the reviewer for suggesting experiments on dataset X. While we agree that this would be valuable, dataset X is not publicly available and requires institutional access that we currently do not have. However, we have conducted experiments on dataset Y, which has similar characteristics and is widely used in the community. The results show [发现]. We acknowledge this limitation in Section 5.3 and discuss experiments on dataset X as future work. +``` + + +--- + +## 结尾模板 + +### 单个审稿人的结尾 + +**模板 1: 标准结尾** +``` +We hope our responses and revisions have adequately addressed all of your concerns. We are grateful for your valuable feedback, which has helped us improve the manuscript significantly. +``` + +**模板 2: 强调改进** +``` +We believe the revisions we have made in response to your comments have substantially strengthened the manuscript. We thank you again for your thorough review and constructive suggestions. +``` + +--- + +### 整体Rebuttal的结尾 + +**模板 1: 总结主要修改** +``` +## Summary of Major Changes + +In response to the reviewers' feedback, we have made the following major revisions: + +1. [主要修改1] (Reviewers [X, Y]) +2. [主要修改2] (Reviewer [Z]) +3. [主要修改3] (All reviewers) + +We believe these revisions have significantly strengthened the manuscript and addressed all concerns raised by the reviewers. We are grateful for the reviewers' valuable feedback and hope that the revised manuscript is now suitable for publication. +``` + +**模板 2: 强调新增内容** +``` +## Summary of Major Changes + +We have made substantial revisions to address all reviewers' comments: + +**New Experiments**: [新实验描述] +**Expanded Discussions**: [扩展讨论描述] +**Clarifications**: [澄清内容描述] + +These changes have improved the manuscript's [质量方面], and we believe it now meets the high standards of [期刊/会议名称]. +``` + + +--- + +## 完整Rebuttal示例 + +### 示例场景 + +假设收到3位审稿人的意见： +- Reviewer 1: 2个Major comments, 3个Minor comments +- Reviewer 2: 1个Major comment, 2个Minor comments +- Reviewer 3: 3个Minor comments + +### 完整Rebuttal文档 + +```markdown +# Response to Reviewers + +We sincerely thank all reviewers for their valuable feedback and constructive suggestions. We have carefully addressed all comments and made substantial revisions to improve the manuscript. Below, we provide detailed responses to each reviewer's comments. + +--- + +## Response to Reviewer 1 + +We thank Reviewer 1 for the thorough review and insightful comments. + +### Major Comments + +**Comment 1.1**: The paper lacks comparison with recent state-of-the-art method X. This comparison is essential for evaluating the proposed method. + +**Response**: We thank the reviewer for this excellent suggestion. We have conducted additional experiments comparing our method with X on all three datasets. The results show that our method achieves comparable or better performance (Dataset A: +2.3%, Dataset B: +1.1%, Dataset C: -0.5%). + +**Changes**: These new results have been added to Table 3 (page 7) and discussed in Section 4.3 (pages 7-8). We also provide detailed analysis of the performance differences. + +--- + +**Comment 1.2**: The authors should provide more details about the training procedure, including hyperparameters and convergence criteria. + +**Response**: We appreciate this comment and agree that more implementation details would be helpful. We have added a comprehensive description of our training procedure. + +**Changes**: We have added Section 3.4 "Training Details" (page 5) which includes: +- Complete hyperparameter settings (Table 2) +- Convergence criteria and early stopping strategy +- Training time and computational resources +- Code availability statement + + +--- + +### Minor Comments + +**Comment 1.3**: There are several typos in Section 2. For example, "recieve" should be "receive" on page 3. + +**Response**: We thank the reviewer for catching these errors. We have carefully proofread the entire manuscript and corrected all typos. + +**Changes**: All typos have been corrected throughout the manuscript. + +--- + +**Comment 1.4**: Figure 2 is difficult to read. The font size should be increased. + +**Response**: We appreciate this feedback. We have improved the figure quality. + +**Changes**: Figure 2 has been redesigned with larger fonts and clearer labels (page 6). + +--- + +**Comment 1.5**: The related work section should discuss paper Y, which is highly relevant. + +**Response**: We thank the reviewer for this suggestion. We have expanded the related work section to include discussion of paper Y. + +**Changes**: We have added a paragraph discussing paper Y in Section 2.2 (page 3) and included it in the comparison table (Table 1). + +--- + +We hope our responses and revisions have adequately addressed all of your concerns. We are grateful for your valuable feedback. + + +--- + +## Response to Reviewer 2 + +We thank Reviewer 2 for the constructive feedback. + +### Major Comments + +**Comment 2.1**: The authors claim that their method is more efficient than baseline methods, but no runtime analysis is provided. Please add computational complexity analysis and runtime comparisons. + +**Response**: We appreciate this important comment. We have added comprehensive efficiency analysis. + +**Changes**: We have added Section 4.4 "Efficiency Analysis" (page 8) which includes: +- Theoretical computational complexity analysis (O-notation) +- Runtime comparison with baseline methods (Table 4) +- Memory consumption analysis (Figure 4) +- Discussion of efficiency-performance trade-offs + +The results show that our method achieves 3.2x speedup compared to the previous state-of-the-art while maintaining comparable accuracy. + +--- + +### Minor Comments + +**Comment 2.2**: The notation in Equation 3 is inconsistent with the rest of the paper. + +**Response**: We thank the reviewer for pointing this out. We have standardized the notation throughout the manuscript. + +**Changes**: Equation 3 (page 4) has been revised to use consistent notation. We have also added a notation table in the appendix for clarity. + +--- + +**Comment 2.3**: The discussion of limitations is too brief. + +**Response**: We agree that a more thorough discussion of limitations would strengthen the paper. + +**Changes**: We have expanded Section 5.3 "Limitations and Future Work" (page 10) to include: +- Detailed discussion of current limitations +- Potential failure cases +- Directions for future research + +--- + +We believe the revisions we have made in response to your comments have substantially strengthened the manuscript. Thank you for your thorough review. + + +--- + +## Response to Reviewer 3 + +We thank Reviewer 3 for the careful review and helpful suggestions. + +### Minor Comments + +**Comment 3.1**: The abstract should be more concise and focus on the key contributions. + +**Response**: We appreciate this feedback. We have revised the abstract to be more focused and concise. + +**Changes**: The abstract has been rewritten (page 1) to highlight the three key contributions and remove unnecessary details. + +--- + +**Comment 3.2**: Some figures are not referenced in the text. + +**Response**: We thank the reviewer for catching this. We have ensured all figures are properly referenced. + +**Changes**: We have added references to Figure 5 in Section 4.2 (page 7) and Figure 6 in Section 4.5 (page 9). + +--- + +**Comment 3.3**: The conclusion should discuss broader impact and societal implications. + +**Response**: We agree that discussing broader impact is important. + +**Changes**: We have added Section 6 "Broader Impact" (page 11) discussing potential societal implications, ethical considerations, and responsible use of our method. + +--- + +We are grateful for your valuable feedback, which has helped us improve the manuscript significantly. + +--- + +## Summary of Major Changes + +In response to the reviewers' feedback, we have made the following major revisions: + +1. **Added comparison with state-of-the-art method X** (Reviewer 1) - New experiments on all datasets, results in Table 3 and Section 4.3 + +2. **Added comprehensive training details** (Reviewer 1) - New Section 3.4 with hyperparameters, convergence criteria, and code availability + +3. **Added efficiency analysis** (Reviewer 2) - New Section 4.4 with complexity analysis, runtime comparisons (Table 4), and memory analysis (Figure 4) + +4. **Expanded limitations discussion** (Reviewer 2) - Enhanced Section 5.3 with detailed limitations and future work + +5. **Added broader impact section** (Reviewer 3) - New Section 6 discussing societal implications + +6. **Improved figures and fixed typos** (Reviewers 1, 3) - Enhanced Figure 2, added figure references, corrected all typos + +We believe these revisions have significantly strengthened the manuscript and addressed all concerns raised by the reviewers. We are grateful for the reviewers' valuable feedback and hope that the revised manuscript is now suitable for publication. +``` + + +--- + +## 使用指南 + +### 如何使用这些模板 + +1. **选择合适的结构**: 根据审稿人数量和意见复杂度选择基本结构 +2. **分类意见**: 将每个审稿人的意见分为Major和Minor +3. **选择策略**: 根据意见类型选择Accept/Defend/Clarify/Experiment策略 +4. **套用模板**: 使用对应策略的模板撰写回复 +5. **添加具体内容**: 填充模板中的占位符（[具体修改]、[位置]等） +6. **检查一致性**: 确保所有回复的语气和格式一致 + +### 模板定制建议 + +**根据会议/期刊调整**: +- 顶会（NeurIPS, ICML）: 更注重技术细节和实验结果 +- 期刊（Nature, Science）: 更注重broader impact和清晰表达 +- 领域会议: 根据领域特点调整专业术语 + +**根据审稿轮次调整**: +- 第一轮: 更详细的解释和更多的新实验 +- 第二轮: 重点回应未解决的问题，简洁明了 +- 第三轮: 强调已做的改进，表达合作态度 + +### 常见错误 + +❌ **避免**: +- 过于简短的回复（"Done" 或 "Fixed"） +- 没有具体位置引用 +- 防御性或攻击性语气 +- 承诺无法完成的实验 +- 忽略某些意见 + +✅ **推荐**: +- 每个回复都包含Response和Changes两部分 +- 提供具体的章节、页码、表格、图表引用 +- 保持礼貌和专业的语气 +- 只承诺可行的改进 +- 回应所有意见，即使是小的typo + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/response-strategies.md b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/response-strategies.md new file mode 100644 index 0000000..fad11d6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/response-strategies.md @@ -0,0 +1,483 @@ +# 审稿响应策略库 + +本文档提供针对不同类型审稿意见的系统化回复策略，帮助撰写专业、有效的rebuttal。 + +## 四大核心策略 + +### 1. Accept（接受策略） + +**适用场景**: +- 审稿人指出的确实是问题或不足 +- 修改成本低且能改进论文质量 +- Typos和格式问题 +- 合理的改进建议 + +**回复模板**: +``` +We thank the reviewer for this valuable suggestion. We have [具体修改行动]. +``` + +**示例**: + +**审稿意见**: +> "The related work section is too brief and misses several important recent papers." + +**回复**: +> "We thank the reviewer for pointing this out. We have significantly expanded the related work section and added discussions of the suggested papers [X, Y, Z]. The revised section now provides a more comprehensive overview of the field." + + +--- + +### 2. Defend（辩护策略） + +**适用场景**: +- 当前做法有充分理由 +- 审稿人的建议不适用于本研究 +- 需要解释设计选择的合理性 + +**关键原则**: +- 保持礼貌和尊重 +- 提供充分的理由和证据 +- 避免"The reviewer is wrong"这样的表述 + +**回复模板**: +``` +We appreciate the reviewer's concern. However, we respectfully note that [解释理由]. This choice is motivated by [具体原因]. +``` + +**示例**: + +**审稿意见**: +> "The authors should use method X instead of method Y." + +**回复**: +> "We appreciate the reviewer's suggestion. However, we respectfully note that method Y is more suitable for our specific setting because [理由1] and [理由2]. While method X has advantages in [场景A], our preliminary experiments showed that method Y achieves better performance in our task due to [具体原因]. We have added this discussion to Section 3.2." + + +--- + +### 3. Clarify（澄清策略） + +**适用场景**: +- 审稿人误解了论文内容 +- 论文中已有相关内容但审稿人未注意到 +- 需要指出论文中已有的说明或实验 + +**关键原则**: +- 礼貌地指出论文中已有的内容 +- 提供具体的位置引用（章节、页码、图表） +- 避免让审稿人感到尴尬 +- 可以考虑改进表述使其更清晰 + +**回复模板**: +``` +We thank the reviewer for raising this point. We would like to respectfully clarify that [已有内容的说明]. This is discussed in [具体位置]. To make this clearer, we have [改进措施]. +``` + +**示例**: + +**审稿意见**: +> "The authors did not compare their method with baseline X." + +**回复**: +> "We thank the reviewer for this comment. We would like to respectfully clarify that we did include comparisons with baseline X in our experiments. These results are presented in Table 2 (page 6) and discussed in Section 4.2. To make this comparison more prominent, we have added a dedicated paragraph highlighting the key differences and added baseline X to Figure 3 for visual comparison." + +**注意事项**: +- 即使审稿人误解了，也要保持礼貌和尊重 +- 如果可能，承认论文表述可以更清晰，并做出改进 +- 提供具体的引用位置，方便审稿人查找 + + +--- + +### 4. Experiment（实验策略） + +**适用场景**: +- 审稿人要求补充关键实验或对比 +- 实验要求合理且可行 +- 补充实验能显著增强论文说服力 +- Major Issues 中的实验要求 + +**关键原则**: +- 明确承诺会进行补充实验 +- 说明实验设计和预期时间 +- 如果已经完成，直接展示结果 +- 如果时间紧迫，说明初步结果或计划 + +**回复模板**: +``` +We thank the reviewer for this valuable suggestion. We agree that [实验的重要性]. We have conducted additional experiments on [实验内容]. The results show that [主要发现]. These new results have been added to [位置]. +``` + +**示例 1（已完成实验）**: + +**审稿意见**: +> "The authors should compare their method with the recent state-of-the-art method Z." + +**回复**: +> "We thank the reviewer for this excellent suggestion. We agree that comparing with method Z is important for a comprehensive evaluation. We have conducted additional experiments comparing our method with Z on all three datasets. The results show that our method achieves comparable or better performance (Dataset A: +2.3%, Dataset B: +1.1%, Dataset C: -0.5%). These new results have been added to Table 3 and discussed in Section 4.3. We also provide detailed analysis of the performance differences in the revised manuscript." + +**示例 2（承诺进行实验）**: + +**审稿意见**: +> "The authors should conduct ablation studies to verify the contribution of each component." + +**回复**: +> "We thank the reviewer for this important suggestion. We agree that ablation studies are crucial for understanding the contribution of each component. We are currently conducting comprehensive ablation experiments and will include the results in the revised manuscript. Based on our preliminary analysis, we expect to show that [预期发现]. We will complete these experiments within the rebuttal period and update the manuscript accordingly." + +**注意事项**: +- 只承诺可行的实验，不要过度承诺 +- 如果实验不可行，需要解释原因（时间、资源、技术限制） +- 提供实验时间表，让审稿人了解进度 +- 如果已完成，立即展示结果以增强说服力 + + +--- + +## 成功模式（基于ICLR Spotlight论文） + +从ICLR 2024 spotlight论文的成功rebuttal中提取的关键模式： + +### 模式1: 认可优点，正面回应批评 + +**观察**: +- 审稿人通常会先认可论文的优点（novelty, impact, practical applicability） +- 即使是spotlight论文，也会收到建设性批评 +- 约20%的论文在rebuttal后排名发生变化 + +**应用策略**: +``` +We thank the reviewer for recognizing [acknowledged strength]. Regarding [concern], we have [specific action taken]. +``` + +**示例**: +> "We thank the reviewer for recognizing the novelty of our game-theoretic formulation. Regarding the brevity of Section 2.2, we have expanded it with 2-3 additional paragraphs providing more intuition for readers without a game theory background." + +--- + +### 模式2: 提供清晰度和直觉理解 + +**观察**: +- 高质量论文仍可能存在clarity问题 +- 审稿人需要为不同背景的读者提供intuition +- 建议：expand sections, move technical details to appendix + +**应用策略**: +``` +We apologize for the confusion. We have [clarification action]. To make this clearer, we have [additional improvements]. +``` + +**示例**: +> "We apologize for the confusion in Section 3.2. We have completely rewritten this section with detailed mathematical formulation and added Algorithm 1 with pseudocode. We have also moved some technical details to Appendix B to improve readability." + +--- + +### 模式3: 充分论证实验设置 + +**观察**: +- 审稿人期望实验设置有充分的justification +- 需要考虑和讨论alternative metrics +- Comprehensive experiments是spotlight论文的共同特征 + +**应用策略**: +``` +We chose [experimental setup] because [justification]. We have also considered [alternative approach], but [reason for current choice]. We have added [additional experiments] to strengthen our evaluation. +``` + +**示例**: +> "We chose dataset W because it better represents our target scenario [justification]. We have also considered dataset Z, but it focuses on static graphs while our work targets dynamic graphs. We have added ablation studies showing that our improvement comes from fundamental architectural innovations." + +--- + +### 模式4: 主动讨论伦理考量 + +**观察**: +- 对于涉及隐私、安全等敏感话题的研究，ethical considerations至关重要 +- 审稿人会特别关注ethical implications +- Spotlight论文通常有thorough ethical discussions + +**应用策略**: +``` +We appreciate the concern about ethical implications. We have [ethical consideration actions]. We have also added [ethical safeguards/discussions]. +``` + +**示例**: +> "We appreciate the concern about privacy implications. We have added a comprehensive ethics section discussing potential risks and mitigation strategies. We have also included anonymization experiments and detailed our data handling procedures in Appendix C." + +--- + +### 模式5: 强调实际应用价值 + +**观察**: +- 审稿人重视practical applicability和scalability +- "Easily applicable"和"scalable"是重要的优点 +- Spotlight论文通常demonstrate practical benefits + +**应用策略**: +``` +Our method is [practical benefit]. It is easily applicable because [reason] and scales to [scale] without [limitation]. +``` + +**示例**: +> "Our method is practical and easily applicable to large language models without extensive tuning. It scales efficiently to models with up to 540B parameters, as demonstrated by our experiments. The consistent performance improvements across different model sizes highlight its practical value." + +--- + +## 策略组合使用 + +在实际rebuttal中，通常需要组合使用多种策略： + +### 组合示例 1: Accept + Clarify + +**审稿意见**: +> "The paper lacks discussion of limitation X, and the authors did not mention related work Y." + +**回复**: +> "We thank the reviewer for these valuable comments. Regarding limitation X, we agree this is an important point and have added a dedicated discussion in Section 5.3 (**Accept**). Regarding related work Y, we would like to respectfully clarify that we did discuss this work in Section 2.2 (page 3, paragraph 2). To make this more prominent, we have expanded the discussion and added it to the comparison table (**Clarify**)." + +### 组合示例 2: Defend + Experiment + +**审稿意见**: +> "The authors should use dataset Z instead of dataset W, and should add experiments on task T." + +**回复**: +> "We appreciate the reviewer's suggestions. Regarding dataset Z, we respectfully note that dataset W is more suitable for our research question because [理由]. Dataset Z focuses on [场景A], while our work targets [场景B] (**Defend**). However, we agree that experiments on task T would strengthen our evaluation. We have conducted additional experiments on task T, and the results show [发现]. These new results have been added to Section 4.4 (**Experiment**)." + + +--- + +## 使用指南 + +### 策略选择流程 + +``` +审稿意见 → 分类（Major/Minor/Typo/Misunderstanding）→ 选择策略 +│ +├─ Major Issues → Experiment (补充实验) 或 Defend (充分理由) +├─ Minor Issues → Accept (接受改进) 或 Clarify (澄清说明) +├─ Typos/Formatting → Accept (直接接受) +└─ Misunderstandings → Clarify (礼貌澄清) +``` + +### 策略优先级 + +1. **优先Accept**: 如果意见合理且改进成本低 +2. **谨慎Defend**: 只在有充分理由时使用 +3. **礼貌Clarify**: 即使审稿人误解，也要保持尊重 +4. **诚实Experiment**: 只承诺可行的实验 + +### 语气原则 + +**始终保持**: +- ✅ 感谢审稿人的意见 +- ✅ 尊重和礼貌的态度 +- ✅ 具体的引用和证据 +- ✅ 建设性的回应 + +**避免**: +- ❌ "The reviewer is wrong" +- ❌ "This is obvious" +- ❌ 防御性或攻击性语气 +- ❌ 模糊或回避的回答 + +--- + +## 会议特定策略 + +不同顶会对rebuttal有不同的侧重点，了解这些差异可以帮助你更有针对性地回复。 + +### NeurIPS + +**会议特点**: +- 强调概念新颖性和理论贡献 +- 重视broader impact和社会影响 +- 要求reproducibility checklist + +**Rebuttal侧重点**: +1. **突出概念创新** - 强调你的方法在概念上的新颖性 +2. **展示broader impact** - 说明研究的社会意义和潜在影响 +3. **确保可复现性** - 承诺开源代码和数据 + +**示例开场**: +```markdown +We thank the reviewers for their constructive feedback. Our key contributions advance the field by [conceptual innovation]. We have strengthened the paper with [new experiments] and clarified [methodology]. All code and data will be released upon acceptance to ensure reproducibility. +``` + +**回复策略**: +- 当审稿人质疑新颖性时，强调概念上的突破而非仅仅是性能提升 +- 主动讨论broader impact，即使审稿人没有明确要求 +- 提供详细的实验设置和超参数，确保可复现 + +--- + +### ICML + +**会议特点**: +- 强调方法论严谨性和理论基础 +- 重视数学证明和理论分析 +- 要求broader impact statement + +**Rebuttal侧重点**: +1. **展示理论严谨性** - 提供数学证明和理论分析 +2. **强调方法论贡献** - 说明方法的理论优势 +3. **补充理论分析** - 添加定理、引理或理论保证 + +**示例开场**: +```markdown +We appreciate the reviewers' thorough evaluation. We have added theoretical analysis (Theorem 2, Appendix C) proving [property]. Our method's soundness is further validated by [experiments]. We have also expanded the broader impact statement to address [concern]. +``` + +**回复策略**: +- 当审稿人质疑方法时，提供理论证明而非仅仅是实验结果 +- 强调算法的理论复杂度和收敛性保证 +- 将实验结果与理论预测联系起来 + +--- + +### ICLR + +**会议特点**: +- 强调实验彻底性和全面评估 +- 重视局限性的诚实讨论 +- 要求LLM使用披露（如适用） + +**Rebuttal侧重点**: +1. **补充实验** - 添加审稿人要求的对比实验和消融研究 +2. **扩展局限性讨论** - 诚实承认方法的局限性 +3. **披露LLM使用** - 如果使用了LLM，明确说明使用方式 + +**示例开场**: +```markdown +We thank the reviewers for their detailed comments. We have conducted additional experiments (Tables 4-6) addressing all concerns. We have also expanded the Limitations section (Section 5.2) and added LLM usage disclosure (Appendix D). These revisions significantly strengthen the empirical validation. +``` + +**回复策略**: +- 当审稿人要求更多实验时，优先添加而非辩解 +- 主动扩展局限性讨论，展示对方法边界的清晰认识 +- 如果使用了LLM辅助写作或实验，诚实披露并说明具体用途 + +**ICLR 2026特定策略**: + +**1. 证据支持的澄清最有效** +- 研究表明，包含证据支持的澄清与分数提升最强相关 +- 避免模糊或回避的回应，这些会维持或降低分数 +- 明确引用原文中的具体章节或行号 + +**示例**: +```markdown +Thank you for this concern. We respectfully clarify that we did include this comparison in Section 4.2 (page 6, lines 234-245). To make this more prominent, we have added a dedicated paragraph and included the baseline in Figure 3 for visual comparison. +``` + +**2. 针对边界论文策略** +- Rebuttal对边界分数论文（5-6分范围）影响最大 +- 如果论文处于边界，即使小的改进也可能影响最终决定 +- 重点关注可以快速提升的方面 + +**3. 提交时机策略** +- 在rebuttal期间中期提交可能更有效 +- 避免过早或最后一刻提交 +- 中期提交可以提高审稿人参与度和分数变化 + +**4. 系统化回应结构** +每个回应应遵循三步结构： +1. **总结审稿人观点** - 展示你理解了他们的反馈 +2. **陈述你的回应** - 清晰说明你的立场 +3. **提供具体证据** - 给出实验、解释或修改计划 + +**示例**: +```markdown +**Reviewer's Concern**: The baseline comparison is insufficient. + +**Our Response**: We appreciate this feedback. We understand the reviewer's concern about baseline coverage. + +**Evidence**: We have added comparisons with three additional baselines (X, Y, Z) in Table 4 (Appendix). Results show our method achieves +2.3% improvement over the strongest baseline Z. We will integrate this into the main paper. +``` + +**5. 利用页面限制扩展** +- ICLR 2026将camera-ready版本从9页扩展到10页 +- 可以利用额外的1页空间整合rebuttal中的新结果或讨论 +- 在rebuttal中承诺将新内容添加到最终版本 + +**6. 可复现性声明** +- 强烈建议在主文本末尾（参考文献前）包含可复现性声明 +- 讨论为确保可复现性所做的努力 +- 引用论文、附录或补充材料中的相关部分 + +**7. ICLR 2026评分系统** +- 使用离散分数：{0, 2, 4, 6, 8, 10} +- 0=Strong Reject, 2=Reject, 4=Weak Reject, 6=Weak Accept, 8=Accept, 10=Strong Accept +- 理解评分系统有助于判断论文处于哪个范围 + +--- + +### CVPR + +**会议特点**: +- 计算机视觉顶会，竞争激烈 +- 严格的一页rebuttal限制 +- 禁止外部链接和新的大规模实验 +- 重视视觉效果和实验完整性 + +**Rebuttal侧重点**: +1. **识别"Champion"审稿人** - 找到支持你的审稿人，为他们提供强有力的论据 +2. **重申核心贡献** - 在回应批评时，巧妙地提醒审稿人论文的重要贡献 +3. **展示响应性** - 明确说明如何在最终版本中采纳建议 + +**示例开场**: +```markdown +We thank all reviewers for their valuable feedback. We are particularly grateful to R2 for recognizing our novel approach to [X]. Regarding the concerns raised, we provide clarifications below and will incorporate all valid suggestions in the camera-ready version. +``` + +**回复策略**: +- 识别持积极态度的审稿人，为他们提供论据帮助他们在讨论中辩护 +- 在解决问题的同时，巧妙强化论文的核心优势 +- 对关键概念的误解提供明确、有说服力的澄清 +- 展示对审稿人建议的认真对待，列出具体改进计划 + +**特殊限制**: +- 必须使用官方模板，严格一页限制 +- 不得包含外部链接（代码、视频、补充材料） +- 可以包含基于已有结果的图表和对比表格 +- 审稿人不应要求大规模新实验 + +--- + +### ACL + +**会议特点**: +- 自然语言处理顶会 +- Best paper标准：fascinating, controversial, surprising, impressive, field-changing +- 重视方法的语言学意义和实际应用 +- 要求Limitations和Ethics Statement + +**Rebuttal侧重点**: +1. **小表格策略** - 如果审稿人要求额外结果，可以在rebuttal中包含小表格 +2. **增强理解** - 目标是增强审稿人对论文的理解，而非大规模重写 +3. **突出影响力** - 强调研究对NLP领域的潜在影响 + +**示例开场**: +```markdown +We thank the reviewers for their insightful comments. We have prepared additional analysis to address the raised concerns. Below we provide clarifications and include a small table (Table R1) demonstrating the requested comparison. These results will be integrated into the revised manuscript. +``` + +**回复策略**: +- 如果审稿人要求额外数据，可以在rebuttal中包含小表格展示 +- 强调研究的语言学意义和对NLP社区的贡献 +- 主动讨论伦理影响，特别是涉及偏见、公平性的研究 +- 展示对不同语言和文化背景的考虑 + +**Best Paper考虑**: +- 论文是否"fascinating"（引人入胜）- 提出令人兴奋的新问题或视角 +- 是否"controversial"（有争议性）- 挑战现有假设 +- 是否"surprising"（令人惊讶）- 违反直觉但有说服力的发现 +- 是否"impressive"（令人印象深刻）- 技术深度或实验规模 +- 是否"field-changing"（改变领域）- 潜在的长期影响 + +--- + +## 参考资源 + +更多详细的成功案例和模板，请参考： +- `successful-cases.md` - 真实的成功rebuttal案例库 +- `rebuttal-templates.md` - 完整的rebuttal模板 +- `tone-guidelines.md` - 语气和表达指南 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/review-classification.md b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/review-classification.md new file mode 100644 index 0000000..6905124 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/review-classification.md @@ -0,0 +1,131 @@ +# 审稿意见分类标准 + +本文档提供系统化的审稿意见分类方法，帮助快速识别和优先处理不同类型的审稿意见。 + +## 分类体系 + +### 1. Major Issues（重大问题） + +**定义**: 涉及研究方法、实验设计、结果解释等核心问题，需要实质性修改或补充实验。 + +**特征**: +- 质疑研究方法的有效性 +- 要求补充关键实验或对比 +- 指出结果解释的逻辑问题 +- 质疑研究的创新性或贡献 + +**关键词识别**: +- "major concern" +- "fundamental issue" +- "missing experiments" +- "insufficient evidence" +- "not convincing" + + +**示例**: +> "The authors should compare their method with recent work [X]. Without this comparison, it's difficult to assess the true contribution." + +**建议回复策略**: Accept + Experiment（接受意见并补充实验） + +--- + +### 2. Minor Issues（次要问题） + +**定义**: 需要澄清、补充说明或小幅修改的问题，不影响研究的核心贡献。 + +**特征**: +- 要求澄清某些细节 +- 建议改进表述或组织 +- 要求补充相关工作讨论 +- 指出图表可以改进 + +**关键词识别**: +- "minor concern" +- "could be improved" +- "please clarify" +- "it would be better" +- "suggestion" + +**示例**: +> "The notation in Section 3.2 is confusing. Please clarify the meaning of variable α." + +**建议回复策略**: Accept + Clarify（接受意见并澄清说明） + + +--- + +### 3. Typos/Formatting（拼写和格式问题） + +**定义**: 拼写错误、语法问题、格式不一致等表面问题。 + +**特征**: +- 指出拼写错误 +- 标注语法问题 +- 指出引用格式不一致 +- 图表标注错误 + +**关键词识别**: +- "typo" +- "grammar" +- "formatting" +- "inconsistent" +- "Figure X should be" + +**示例**: +> "Page 5, line 3: 'recieve' should be 'receive'." + +**建议回复策略**: Accept（直接接受并修正） + + +--- + +### 4. Misunderstandings（审稿人的误解） + +**定义**: 审稿人对论文内容的误解或误读，需要礼貌地澄清。 + +**特征**: +- 审稿人误解了方法或结果 +- 审稿人忽略了论文中已有的说明 +- 审稿人对某个概念有错误理解 + +**关键词识别**: +- "The authors did not..."（但实际上已经做了） +- "It is unclear..."（但论文中已经说明） +- "Why don't the authors..."（但已经做了） + +**示例**: +> "The authors did not compare with baseline X." +> （但论文Table 2中已经包含了这个对比） + +**建议回复策略**: Clarify（礼貌地指出论文中已有的内容） + + +--- + +## 使用指南 + +### 分类流程 + +1. **第一遍阅读** - 快速浏览所有审稿意见，标记关键词 +2. **分类标注** - 为每条意见标注类型（Major/Minor/Typo/Misunderstanding） +3. **优先级排序** - 按照重要性排序（Major > Misunderstanding > Minor > Typo） +4. **制定策略** - 针对每条意见制定回复策略 + +### 优先级建议 + +**高优先级**（必须优先处理）: +- Major Issues - 需要补充实验或重大修改 +- Misunderstandings - 需要澄清以避免误解加深 + +**中优先级**: +- Minor Issues - 需要改进但不影响核心贡献 + +**低优先级**: +- Typos/Formatting - 直接修正即可 + +### 注意事项 + +- **不要忽略任何意见** - 即使是小的typo也要在rebuttal中确认 +- **礼貌对待误解** - 用"We apologize for the confusion"而不是"The reviewer misunderstood" +- **Major Issues需要实质性回应** - 不能只是澄清，要有行动（实验、修改等） + diff --git a/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/successful-cases.md b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/successful-cases.md new file mode 100644 index 0000000..08522ce --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/successful-cases.md @@ -0,0 +1,347 @@ +# 成功Rebuttal案例库 + +本文档收集真实的成功rebuttal案例，提供可参考的实战模式。 + +## 案例来源 + +- ICLR 2024 Spotlight论文 +- NeurIPS 2023 接收论文 +- ICML 2023 接收论文 + +--- + +## 案例 1: 回应清晰度问题 + +### 审稿意见 +> "The algorithm description in Section 3.2 is unclear. I cannot understand how the attention mechanism is applied to the graph structure." + +### 成功回复 +```markdown +We apologize for the confusion. We have completely rewritten Section 3.2 to clarify the attention mechanism: + +**Original text** (unclear): +"We apply attention to nodes based on their features." + +**Revised text** (clear): +"For each node v, we compute attention weights α_ij for all neighbors j ∈ N(v) using: +α_ij = softmax(LeakyReLU(a^T [W h_i || W h_j])) +where W is a learnable weight matrix and a is an attention vector." + +We also added: +- Algorithm 1 with detailed pseudocode (page 5) +- Figure 3 showing a concrete example with 4 nodes (page 6) +- Appendix B with step-by-step walkthrough + +These additions make the mechanism explicit and reproducible. +``` + +### 成功要素 +- ✅ 承认问题 +- ✅ 对比原文和修订文本 +- ✅ 提供多种形式的说明（公式、算法、图示、示例） +- ✅ 说明具体位置 + +--- + +## 案例 2: 回应缺失实验 + +### 审稿意见 +> "The paper lacks comparison with the recent state-of-the-art method GraphTransformer (Dwivedi et al., 2022). This comparison is essential for evaluating the proposed method." + +### 成功回复 +```markdown +We thank the reviewer for this excellent suggestion. We have added comprehensive comparisons with GraphTransformer on all three datasets: + +**New Results** (Table 3, page 7): +- ZINC: Our method 0.087 ± 0.004 vs GraphTransformer 0.094 ± 0.006 (8% improvement) +- MNIST: Our method 97.3% ± 0.2% vs GraphTransformer 96.5% ± 0.3% (0.8% improvement) +- PROTEINS: Our method 76.2% ± 1.1% vs GraphTransformer 75.1% ± 1.3% (1.1% improvement) + +**Analysis** (Section 4.3, pages 7-8): +We also added ablation studies showing that our improvement comes from: +1. The simplicial-aware features (contributes 60% of improvement) +2. The efficient aggregation scheme (contributes 40% of improvement) + +This demonstrates that our method's advantage is not just from better optimization, but from fundamental architectural improvements. +``` + +### 成功要素 +- ✅ 感谢建议 +- ✅ 提供具体数值结果 +- ✅ 说明结果位置 +- ✅ 添加分析解释改进来源 +- ✅ 强调方法的本质优势 + +--- + +## 案例 3: 回应统计显著性质疑 + +### 审稿意见 +> "The improvements shown in Table 2 are marginal (0.5-1%). Are these differences statistically significant?" + +### 成功回复 +```markdown +We agree that statistical testing is important. We have added comprehensive statistical analysis: + +**Statistical Tests** (Table 2, updated): +- All comparisons now include 95% confidence intervals +- Paired t-tests show p < 0.01 for all improvements +- Results averaged over 10 runs (increased from 3) + +**Practical Significance** (Section 4.2, page 7): +While the improvements are 0.5-1%, we note that: +1. In this domain, even 0.5% improvement is considered significant (see [Citation]) +2. Our method achieves this with 3x faster training time +3. The improvement is consistent across all 5 datasets + +**Updated Table 2**: +| Method | Accuracy | 95% CI | p-value | +|--------|----------|--------|---------| +| Baseline | 85.2% | [84.8, 85.6] | - | +| Ours | 86.1% | [85.7, 86.5] | <0.01 | + +We believe both statistical and practical significance support our claims. +``` + +### 成功要素 +- ✅ 承认统计检验的重要性 +- ✅ 提供多种统计指标 +- ✅ 区分统计显著性和实际显著性 +- ✅ 提供领域背景支持 +- ✅ 更新表格展示完整信息 + +--- + +## 案例 4: 回应基线不足 + +### 审稿意见 +> "Why didn't you compare with Method X and Method Y? These are important baselines in this area." + +### 成功回复 +```markdown +We thank the reviewer for raising this point. We have: + +**Added Method X** (Table 3, page 7): +- Method X: 82.3% ± 1.2% +- Ours: 86.1% ± 0.8% (3.8% improvement) + +**Excluded Method Y** with justification: +Method Y is designed for static graphs, while our work focuses on dynamic graphs. As noted in [Method Y paper, Section 5], "our method is not applicable to temporal settings." Direct comparison would be inappropriate because: +1. Method Y requires graph structure to be fixed +2. Our datasets have time-varying edges +3. Adapting Method Y would require substantial modifications that deviate from the original method + +We have added this clarification to Section 4.1 (page 6). +``` + +### 成功要素 +- ✅ 添加可比较的基线 +- ✅ 解释排除原因（引用原文） +- ✅ 提供具体的技术理由 +- ✅ 说明修改位置 + +--- + +## 案例 5: 回应过度声明 + +### 审稿意见 +> "The claim 'our method achieves state-of-the-art on all tasks' is too strong. Your method performs worse than Baseline X on Task 3." + +### 成功回复 +```markdown +We accept that our original claim was too strong. We have revised throughout the paper: + +**Abstract** (page 1): +- Original: "achieves state-of-the-art on all tasks" +- Revised: "achieves state-of-the-art on 4 out of 5 tasks and competitive performance on the remaining task" + +**Introduction** (page 2): +- Added: "While our method excels on tasks requiring [property], it performs comparably to baselines on Task 3, which emphasizes [different property]." + +**Limitations Section** (new Section 5.2, page 9): +We added a dedicated limitations section acknowledging: +1. Our method's relative weakness on Task 3 +2. Potential reasons (Task 3 requires [property] which our architecture doesn't explicitly model) +3. Future directions to address this + +We believe these revisions accurately reflect our contributions without overclaiming. +``` + +### 成功要素 +- ✅ 承认问题 +- ✅ 展示具体修改（原文 vs 修订文本） +- ✅ 添加限制性说明 +- ✅ 提供技术解释 +- ✅ 保持诚实和准确 + +--- + +## 案例 6: 回应写作质量问题 + +### 审稿意见 +> "The paper is hard to follow. Section 3 jumps between concepts without clear transitions. There are also several grammatical errors." + +### 成功回复 +```markdown +We apologize for the writing issues. We have made substantial revisions: + +**Section 3 Restructuring** (pages 4-6): +- Added subsection headings for clarity: + - 3.1 Problem Formulation + - 3.2 Model Architecture + - 3.3 Training Procedure +- Added transition sentences between subsections +- Moved technical details to appendix + +**Grammar and Style**: +- Professional editing service reviewed the entire manuscript +- Fixed all grammatical errors +- Improved technical terminology consistency +- Added a notation table (Appendix A) + +**Improved Flow**: +- Added signposting: "In this section, we...", "Next, we describe..." +- Clarified pronoun references +- Shortened overly long sentences + +The revised manuscript is significantly more readable while maintaining technical precision. +``` + +### 成功要素 +- ✅ 承认问题 +- ✅ 提供具体改进措施 +- ✅ 展示结构性改进 +- ✅ 说明专业编辑 +- ✅ 强调可读性提升 + +--- + +## 通用成功模式总结 + +### 模式 1: 感谢 + 行动 + 证据 + +```markdown +We thank the reviewer for [specific point]. +We have [specific action taken]. +[Evidence: results/figures/citations] +``` + +### 模式 2: 承认 + 修正 + 说明 + +```markdown +We agree that [issue]. +We have revised [specific location]: +- Original: [old text] +- Revised: [new text] +This addresses the concern by [explanation]. +``` + +### 模式 3: 解释 + 证据 + 引用 + +```markdown +We respectfully note that [our position]. +This is supported by: +1. [Evidence 1] +2. [Evidence 2] +3. [Citation] +``` + +### 模式 4: 添加 + 位置 + 影响 + +```markdown +We have added [new content]. +Location: [Section X, Table Y, Figure Z] +This strengthens our claims by [impact]. +``` + +--- + +## 会议特定策略 + +### NeurIPS Rebuttal + +**侧重点**: +- 强调概念新颖性 +- 突出broader impact +- 展示reproducibility + +**示例开场**: +```markdown +We thank the reviewers for their constructive feedback. Our key contributions advance the field by [conceptual innovation]. We have strengthened the paper with [new experiments] and clarified [methodology]. All code and data will be released upon acceptance. +``` + +### ICML Rebuttal + +**侧重点**: +- 强调理论严谨性 +- 提供数学证明 +- 展示方法论贡献 + +**示例开场**: +```markdown +We appreciate the reviewers' thorough evaluation. We have added theoretical analysis (Theorem 2, Appendix C) proving [property]. Our method's soundness is further validated by [experiments]. We have also expanded the broader impact statement. +``` + +### ICLR Rebuttal + +**侧重点**: +- 强调实验彻底性 +- 承认局限性 +- 披露LLM使用 + +**示例开场**: +```markdown +We thank the reviewers for their detailed comments. We have conducted additional experiments (Tables 4-6) addressing all concerns. We have also expanded the Limitations section and added LLM usage disclosure. These revisions significantly strengthen the empirical validation. +``` + +--- + +## 避免的错误模式 + +### ❌ 错误 1: 防御性语气 + +**不好的回复**: +> "The reviewer clearly misunderstood our method. If they had read Section 3 carefully, they would see that..." + +**好的回复**: +> "We apologize for the confusion. We have clarified Section 3 to make this point more explicit..." + +### ❌ 错误 2: 模糊承诺 + +**不好的回复**: +> "We will add more experiments in the final version." + +**好的回复**: +> "We have added experiments comparing with Method X on datasets A, B, C (Table 4, page 8)." + +### ❌ 错误 3: 忽略问题 + +**不好的回复**: +> "This is beyond the scope of our paper." + +**好的回复**: +> "While [suggestion] is valuable, it is beyond our current scope due to [specific constraint]. However, we have added [alternative] which addresses the core concern." + +### ❌ 错误 4: 过度技术化 + +**不好的回复**: +> "Our method uses a novel attention mechanism with learnable parameters θ = {W_q, W_k, W_v, W_o} where..." + +**好的回复**: +> "We have clarified the attention mechanism in Section 3.2 with pseudocode (Algorithm 1) and a concrete example (Figure 3)." + +--- + +## 使用建议 + +1. **选择相似案例** - 找到与你的审稿意见类似的案例 +2. **适配具体情况** - 不要直接复制，根据实际情况调整 +3. **保持诚实** - 只承诺能做到的事情 +4. **提供证据** - 每个声明都要有支持 +5. **说明位置** - 明确指出修改的具体位置 + +--- + +## 持续更新 + +本文档会持续更新，添加更多成功案例。如果你有好的rebuttal案例，欢迎补充。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/tone-guidelines.md b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/tone-guidelines.md new file mode 100644 index 0000000..00f4b0e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/review-response/references/tone-guidelines.md @@ -0,0 +1,332 @@ +# 语气指南 + +本文档提供rebuttal写作的语气指南，帮助保持专业、礼貌、有说服力的表达。 + +## 核心原则 + +### 1. 始终感谢 + +**原则**: 每个回复都以感谢开始，即使不同意审稿人的意见。 + +**推荐表达**: +- "We thank the reviewer for..." +- "We appreciate the reviewer's..." +- "We are grateful for..." + +**避免**: +- 直接开始反驳 +- 忽略感谢环节 + +--- + +### 2. 保持尊重 + +**原则**: 即使审稿人误解或错误，也要保持尊重的态度。 + +**推荐表达**: +- "We respectfully note that..." +- "We would like to clarify that..." +- "We appreciate the reviewer's perspective, however..." + +**避免**: +- "The reviewer is wrong" +- "This is obvious" +- "The reviewer misunderstood" +- "The reviewer failed to notice" + +--- + +### 3. 客观陈述 + +**原则**: 使用客观、基于事实的语言，避免情绪化表达。 + +**推荐表达**: +- "Our experiments show that..." +- "The results demonstrate..." +- "Based on our analysis..." + +**避免**: +- "Obviously..." +- "Clearly..." +- "It is well-known that..." +- "Everyone knows..." + + +--- + +### 4. 建设性回应 + +**原则**: 即使不同意，也要提供建设性的解释和替代方案。 + +**推荐表达**: +- "While [审稿人建议] has merit, we chose [我们的方法] because..." +- "We have considered this approach, however..." +- "An alternative perspective is..." + +**避免**: +- "This suggestion is not feasible"（没有解释） +- "We cannot do this"（没有替代方案） + +--- + +### 5. 承认不足 + +**原则**: 当审稿人指出真实问题时，坦诚承认并说明改进。 + +**推荐表达**: +- "We acknowledge this limitation..." +- "We agree that this could be improved..." +- "This is a valid concern..." + +**避免**: +- 回避问题 +- 过度辩解 +- 转移话题 + +--- + +## 专业表达方式 + +### 感谢类表达 + +| 场景 | 推荐表达 | +|------|----------| +| 一般感谢 | "We thank the reviewer for this comment/suggestion" | +| 强调价值 | "We thank the reviewer for this valuable/insightful feedback" | +| 重要建议 | "We thank the reviewer for this excellent/important suggestion" | +| 指出错误 | "We thank the reviewer for catching this/pointing this out" | + + +--- + +### 同意类表达 + +| 场景 | 推荐表达 | +|------|----------| +| 完全同意 | "We agree that..." / "We concur with the reviewer that..." | +| 部分同意 | "We agree that [部分], however..." | +| 承认问题 | "We acknowledge this limitation/concern" | +| 接受建议 | "We have adopted this suggestion" | + +--- + +### 不同意类表达（礼貌辩护） + +| 场景 | 推荐表达 | +|------|----------| +| 礼貌不同意 | "We respectfully note that..." | +| 提供理由 | "However, we chose [方法] because..." | +| 解释限制 | "While [建议] would be valuable, it is not feasible due to..." | +| 提供替代 | "Instead, we have [替代方案], which..." | + +--- + +### 澄清类表达 + +| 场景 | 推荐表达 | +|------|----------| +| 指出已有内容 | "We would like to clarify that..." | +| 承认表述不清 | "We apologize for the confusion. What we meant is..." | +| 提供位置引用 | "This is discussed in Section X (page Y)" | +| 改进表述 | "To make this clearer, we have..." | + + +--- + +### 实验承诺类表达 + +| 场景 | 推荐表达 | +|------|----------| +| 已完成实验 | "We have conducted additional experiments on..." | +| 承诺进行实验 | "We are currently conducting... and will include the results" | +| 展示结果 | "The results show that..." / "Our experiments demonstrate..." | +| 无法进行实验 | "While [实验] would be valuable, it is not feasible due to [限制]. However, we have [替代方案]" | + +--- + +## 不同场景的语气调整 + +### 场景 1: 审稿人完全正确 + +**语气**: 坦诚接受，感谢指出 + +**示例**: +> "We thank the reviewer for pointing out this important issue. We agree that [问题描述]. We have [具体改进]." + +--- + +### 场景 2: 审稿人部分正确 + +**语气**: 同意合理部分，礼貌解释其他部分 + +**示例**: +> "We appreciate the reviewer's feedback. We agree that [合理部分]. However, regarding [其他部分], we respectfully note that [解释]." + +--- + +### 场景 3: 审稿人误解了论文 + +**语气**: 礼貌澄清，承认可能表述不清 + +**示例**: +> "We thank the reviewer for this comment. We would like to respectfully clarify that [澄清内容]. This is discussed in [位置]. We apologize if this was not sufficiently clear, and we have revised [位置] to make this more explicit." + + +--- + +### 场景 4: 审稿人要求不可行 + +**语气**: 解释限制，提供替代方案 + +**示例**: +> "We appreciate this suggestion. However, [建议的方法] is not feasible in our setting due to [具体限制]. Instead, we have [替代方案], which [效果]. We believe this approach [优势]." + +--- + +### 场景 5: 多个审稿人意见矛盾 + +**语气**: 平衡两方观点，说明选择理由 + +**示例**: +> "We appreciate both Reviewer X's and Reviewer Y's perspectives on [问题]. After careful consideration, we have [我们的选择] because [理由]. We believe this approach addresses both reviewers' core concerns while [优势]." + +--- + +## 语气对比示例 + +### 示例 1: 回应方法质疑 + +❌ **不好的表达**: +> "The reviewer is wrong. Our method is clearly better than the baseline." + +✅ **好的表达**: +> "We appreciate the reviewer's concern about our method choice. We respectfully note that our method is more suitable for this setting because [理由1] and [理由2]. Our experiments show that it achieves [具体结果]. We have added this discussion to Section 3.2." + +**分析**: 好的表达保持礼貌，提供具体理由和证据，并说明改进位置。 + + +--- + +### 示例 2: 回应误解 + +❌ **不好的表达**: +> "The reviewer failed to notice that we already did this experiment in Section 4." + +✅ **好的表达**: +> "We thank the reviewer for this comment. We would like to respectfully clarify that we did include this experiment in our study. The results are presented in Table 3 (page 6) and discussed in Section 4.2. To make this more prominent, we have added a dedicated paragraph highlighting these findings." + +**分析**: 好的表达避免指责审稿人，礼貌澄清，并主动改进表述。 + +--- + +### 示例 3: 回应不可行的建议 + +❌ **不好的表达**: +> "This is impossible. We don't have access to that dataset." + +✅ **好的表达**: +> "We appreciate this suggestion. While experiments on dataset X would be valuable, this dataset is not publicly available and requires institutional access that we currently do not have. However, we have conducted experiments on dataset Y, which has similar characteristics. The results show [发现]. We have added these results to Section 4.4." + +**分析**: 好的表达解释限制原因，提供替代方案，并展示实际行动。 + + +--- + +### 示例 4: 回应typo指正 + +❌ **不好的表达**: +> "Fixed." + +✅ **好的表达**: +> "We thank the reviewer for catching this. We have corrected all typos throughout the manuscript." + +**分析**: 即使是小的typo，也要表达感谢并说明改进范围。 + +--- + +### 示例 5: 回应补充实验要求 + +❌ **不好的表达**: +> "We will add these experiments in the final version." + +✅ **好的表达**: +> "We thank the reviewer for this excellent suggestion. We have conducted additional experiments comparing our method with baseline X on all three datasets. The results show that our method achieves [具体结果]. These new results have been added to Table 4 and discussed in Section 4.5." + +**分析**: 好的表达展示已完成的工作，提供具体结果和位置，而不是模糊的承诺。 + + +--- + +## 总结：语气检查清单 + +在完成rebuttal后，使用以下清单检查语气： + +### ✅ 必须包含 + +- [ ] 每个回复都以感谢开始 +- [ ] 使用"We"而不是"I" +- [ ] 提供具体的位置引用（章节、页码、表格、图表） +- [ ] 说明具体的改进措施 +- [ ] 保持礼貌和专业的语气 + +### ❌ 必须避免 + +- [ ] 没有"The reviewer is wrong"或类似表述 +- [ ] 没有"Obviously"、"Clearly"等傲慢词汇 +- [ ] 没有防御性或攻击性语气 +- [ ] 没有模糊的承诺（"We will..."没有具体内容） +- [ ] 没有忽略任何审稿意见 + + +--- + +## 使用建议 + +### 1. 写作流程 + +1. **初稿**: 先写出所有回复的内容，不过分关注语气 +2. **语气检查**: 使用本文档的检查清单逐条检查 +3. **替换表达**: 将不当表达替换为推荐的专业表达 +4. **整体审查**: 确保所有回复的语气一致 +5. **他人审阅**: 请同事或导师审阅语气是否得当 + +### 2. 常见陷阱 + +**陷阱 1: 过度防御** +- 问题: 感觉被攻击，语气变得防御性 +- 解决: 深呼吸，记住审稿人是在帮助改进论文 + +**陷阱 2: 过度妥协** +- 问题: 对所有意见都说"Yes"，失去立场 +- 解决: 有充分理由时，礼貌但坚定地辩护 + +**陷阱 3: 模糊回应** +- 问题: 回复含糊其辞，没有具体行动 +- 解决: 每个回复都要有具体的Response和Changes + +### 3. 不同会议/期刊的语气差异 + +**顶会（NeurIPS, ICML, ICLR）**: +- 更注重技术细节 +- 可以更直接地讨论技术选择 +- 但仍需保持礼貌 + +**顶级期刊（Nature, Science）**: +- 更注重broader impact +- 语气需要更加谨慎和全面 +- 强调社会意义和影响 + +**领域会议**: +- 根据领域文化调整 +- 某些领域更直接，某些更委婉 + +### 4. 最后提醒 + +**记住**: 审稿人是志愿者，他们花时间审阅你的论文是在帮助你。即使不同意他们的意见，也要表达感激和尊重。 + +**目标**: 让审稿人感到： +- 他们的意见被认真对待 +- 作者做出了实质性的改进 +- 作者态度专业、合作 + +这样的rebuttal最有可能获得积极的响应。 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-development/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/SKILL.md new file mode 100644 index 0000000..e9b21b4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/SKILL.md @@ -0,0 +1,132 @@ +--- +name: skill-development +description: This skill should be used when the user asks to create a new skill, repair an existing skill, improve trigger descriptions, reorganize skill structure, or make a Claude skill more reusable and internally consistent. +version: 0.2.0 +--- + +# Skill Development + +Use this skill to create or repair Claude skills in the **current local environment**, not in an abstract plugin template. + +## Goal + +Produce a skill that is: +- easy to trigger, +- lean at the `SKILL.md` layer, +- backed by real `references/`, `examples/`, and `scripts/` files when they are mentioned, +- free of dead local references. + +## Core rules + +- Keep **one skill = one durable job**. +- Treat the frontmatter description as the main trigger surface. +- Keep `SKILL.md` focused on workflow and boundaries. +- Move detailed catalogs, templates, and long explanations into `references/` or `examples/`. +- Do not mention files that do not exist. +- Do not inherit stale names, agents, or sibling skill references without verifying they exist locally. + +## Default workflow + +### 1. Inspect the current environment first + +Before writing anything: +- inspect the target skill directory, +- inspect neighboring skills that already solve a similar problem, +- verify which agents, commands, and sibling skills actually exist, +- identify stale references before adding new ones. + +Use the local inventory as the authority. Do not write guidance against an imagined plugin layout. + +### 2. Lock the skill contract + +Define four things before editing: +1. what the skill does, +2. what triggers it, +3. what it explicitly does **not** do, +4. which bundled resources are actually needed. + +If the skill only needs a short workflow, keep it short. Do not create `references/`, `examples/`, or `scripts/` just because the directories are conventional. + +### 3. Write or repair the frontmatter + +The frontmatter should: +- use the real skill identifier in `name`, +- use a third-person trigger description, +- include concrete phrases a user would naturally say, +- stay short enough to scan quickly. + +Prefer descriptions of this form: + +```yaml +--- +name: skill-name +description: This skill should be used when the user asks to "...", "...", or needs help with .... +--- +``` + +### 4. Keep the main file lean + +A good `SKILL.md` should usually contain: +- a short goal section, +- role boundaries, +- a default workflow, +- safety or quality rules, +- a short list of additional resources. + +Move these out of the main file when they get long: +- templates, +- exhaustive checklists, +- edge-case catalogs, +- sample outputs, +- long examples. + +### 5. Add only real bundled resources + +Use bundled resources deliberately: +- `references/` for detailed guidance that may be loaded selectively, +- `examples/` for real example outputs or scaffolds, +- `scripts/` for deterministic helper logic. + +If a resource is mentioned in `SKILL.md`, it must exist. +If a resource exists but is never referenced or used, delete it. + +### 6. Run integrity checks before closing + +At minimum, verify: +- frontmatter parses, +- referenced local files exist, +- sibling skill or agent references are real, +- `SKILL.md` is not overloaded with material that belongs in references, +- temporary logs, caches, and editor artifacts are not left inside the skill directory. + +## Typical repair patterns + +### When the skill is too long +- keep the trigger and workflow in `SKILL.md`, +- move catalogs and deep detail into `references/`, +- keep a short read order so another model knows what to load first. + +### When the skill is too thin +- add a default workflow, +- add at least one concrete example or checklist, +- make the boundaries explicit so the skill is not just a slogan. + +### When the skill has stale references +- remove dead paths immediately, +- replace historical names with current local names, +- re-check neighboring agents/commands/skills against the live directory. + +## Recommended output shape + +When creating or repairing a skill, prefer ending with: +- what changed, +- which files were created or updated, +- what integrity checks were run, +- what still needs manual follow-up, if anything. + +## References + +Load only what is needed: +- `references/checklist.md` - compact quality checklist before closing a skill edit +- `references/integrity-checks.md` - concrete local checks for missing files, dead references, and drift +- `references/skill-creator-original.md` - legacy background reference; use for context, not as the live source of truth diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/checklist.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/checklist.md new file mode 100644 index 0000000..a2066e5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/checklist.md @@ -0,0 +1,20 @@ +# Skill Development Checklist + +## Trigger quality +- Does the frontmatter use third-person trigger phrasing? +- Does it include natural user phrases? +- Does it reflect the real scope of the skill? + +## Main file quality +- Is the workflow obvious from a quick read? +- Are boundaries explicit? +- Is long detail pushed into references/examples instead of the main file? + +## Resource integrity +- Does every referenced file exist? +- Are example files real and relevant? +- Are scripts actually callable? + +## Environment integrity +- Are sibling skill/agent references still real in the current repo? +- Are caches, logs, and editor artifacts removed? diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/integrity-checks.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/integrity-checks.md new file mode 100644 index 0000000..90467b3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/integrity-checks.md @@ -0,0 +1,21 @@ +# Skill Integrity Checks + +## Minimal local checks + +```bash +# referenced files exist +rg -n "references/|examples/|scripts/|assets/" SKILL.md + +# skill inventory +find . -maxdepth 2 -type f | sort + +# obvious editor/cache noise +find . -type d -name "__pycache__" -o -name ".DS_Store" +``` + +## Common failure modes +- `SKILL.md` mentions references that were never created. +- A migrated skill still refers to old agent or plugin names. +- The directory contains logs or session artifacts. +- The frontmatter name and the directory slug drift apart. +- The skill promises a script-based path but ships no runnable script. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/skill-creator-original.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/skill-creator-original.md new file mode 100644 index 0000000..4069935 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-development/references/skill-creator-original.md @@ -0,0 +1,209 @@ +--- +name: skill-creator +description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. +license: Complete terms in LICENSE.txt +--- + +# Skill Creator + +This skill provides guidance for creating effective skills. + +## About Skills + +Skills are modular, self-contained packages that extend Claude's capabilities by providing +specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific +domains or tasks—they transform Claude from a general-purpose agent into a specialized agent +equipped with procedural knowledge that no model can fully possess. + +### What Skills Provide + +1. Specialized workflows - Multi-step procedures for specific domains +2. Tool integrations - Instructions for working with specific file formats or APIs +3. Domain expertise - Company-specific knowledge, schemas, business logic +4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks + +### Anatomy of a Skill + +Every skill consists of a required SKILL.md file and optional bundled resources: + +``` +skill-name/ +├── SKILL.md (required) +│ ├── YAML frontmatter metadata (required) +│ │ ├── name: (required) +│ │ └── description: (required) +│ └── Markdown instructions (required) +└── Bundled Resources (optional) + ├── scripts/ - Executable code (Python/Bash/etc.) + ├── references/ - Documentation intended to be loaded into context as needed + └── assets/ - Files used in output (templates, icons, fonts, etc.) +``` + +#### SKILL.md (required) + +**Metadata Quality:** The `name` and `description` in YAML frontmatter determine when Claude will use the skill. Be specific about what the skill does and when to use it. Use the third-person (e.g. "This skill should be used when..." instead of "Use this skill when..."). + +#### Bundled Resources (optional) + +##### Scripts (`scripts/`) + +Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten. + +- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed +- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks +- **Benefits**: Token efficient, deterministic, may be executed without loading into context +- **Note**: Scripts may still need to be read by Claude for patching or environment-specific adjustments + +##### References (`references/`) + +Documentation and reference material intended to be loaded as needed into context to inform Claude's process and thinking. + +- **When to include**: For documentation that Claude should reference while working +- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications +- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides +- **Benefits**: Keeps SKILL.md lean, loaded only when Claude determines it's needed +- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md +- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files. + +##### Assets (`assets/`) + +Files not intended to be loaded into context, but rather used within the output Claude produces. + +- **When to include**: When the skill needs files that will be used in the final output +- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography +- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified +- **Benefits**: Separates output resources from documentation, enables Claude to use files without loading them into context + +### Progressive Disclosure Design Principle + +Skills use a three-level loading system to manage context efficiently: + +1. **Metadata (name + description)** - Always in context (~100 words) +2. **SKILL.md body** - When skill triggers (<5k words) +3. **Bundled resources** - As needed by Claude (Unlimited*) + +*Unlimited because scripts can be executed without reading into context window. + +## Skill Creation Process + +To create a skill, follow the "Skill Creation Process" in order, skipping steps only if there is a clear reason why they are not applicable. + +### Step 1: Understanding the Skill with Concrete Examples + +Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill. + +To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback. + +For example, when building an image-editor skill, relevant questions include: + +- "What functionality should the image-editor skill support? Editing, rotating, anything else?" +- "Can you give some examples of how this skill would be used?" +- "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?" +- "What would a user say that should trigger this skill?" + +To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness. + +Conclude this step when there is a clear sense of the functionality the skill should support. + +### Step 2: Planning the Reusable Skill Contents + +To turn concrete examples into an effective skill, analyze each example by: + +1. Considering how to execute on the example from scratch +2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly + +Example: When building a `pdf-editor` skill to handle queries like "Help me rotate this PDF," the analysis shows: + +1. Rotating a PDF requires re-writing the same code each time +2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill + +Example: When designing a `frontend-webapp-builder` skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows: + +1. Writing a frontend webapp requires the same boilerplate HTML/React each time +2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill + +Example: When building a `big-query` skill to handle queries like "How many users have logged in today?" the analysis shows: + +1. Querying BigQuery requires re-discovering the table schemas and relationships each time +2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill + +To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets. + +### Step 3: Initializing the Skill + +At this point, it is time to actually create the skill. + +Skip this step only if the skill being developed already exists, and iteration or packaging is needed. In this case, continue to the next step. + +When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable. + +Usage: + +```bash +scripts/init_skill.py <skill-name> --path <output-directory> +``` + +The script: + +- Creates the skill directory at the specified path +- Generates a SKILL.md template with proper frontmatter and TODO placeholders +- Creates example resource directories: `scripts/`, `references/`, and `assets/` +- Adds example files in each directory that can be customized or deleted + +After initialization, customize or remove the generated SKILL.md and example files as needed. + +### Step 4: Edit the Skill + +When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Claude to use. Focus on including information that would be beneficial and non-obvious to Claude. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Claude instance execute these tasks more effectively. + +#### Start with Reusable Skill Contents + +To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`. + +Also, delete any example files and directories not needed for the skill. The initialization script creates example files in `scripts/`, `references/`, and `assets/` to demonstrate structure, but most skills won't need all of them. + +#### Update SKILL.md + +**Writing Style:** Write the entire skill using **imperative/infinitive form** (verb-first instructions), not second person. Use objective, instructional language (e.g., "To accomplish X, do Y" rather than "You should do X" or "If you need to do X"). This maintains consistency and clarity for AI consumption. + +To complete SKILL.md, answer the following questions: + +1. What is the purpose of the skill, in a few sentences? +2. When should the skill be used? +3. In practice, how should Claude use the skill? All reusable skill contents developed above should be referenced so that Claude knows how to use them. + +### Step 5: Packaging a Skill + +Once the skill is ready, it should be packaged into a distributable zip file that gets shared with the user. The packaging process automatically validates the skill first to ensure it meets all requirements: + +```bash +scripts/package_skill.py <path/to/skill-folder> +``` + +Optional output directory specification: + +```bash +scripts/package_skill.py <path/to/skill-folder> ./dist +``` + +The packaging script will: + +1. **Validate** the skill automatically, checking: + - YAML frontmatter format and required fields + - Skill naming conventions and directory structure + - Description completeness and quality + - File organization and resource references + +2. **Package** the skill if validation passes, creating a zip file named after the skill (e.g., `my-skill.zip`) that includes all files and maintains the proper directory structure for distribution. + +If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again. + +### Step 6: Iterate + +After testing the skill, users may request improvements. Often this happens right after using the skill, with fresh context of how the skill performed. + +**Iteration workflow:** +1. Use the skill on real tasks +2. Notice struggles or inefficiencies +3. Identify how SKILL.md or bundled resources should be updated +4. Implement changes and test again diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/SKILL.md new file mode 100644 index 0000000..751a3ce --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/SKILL.md @@ -0,0 +1,251 @@ +--- +name: skill-improver +description: This skill should be used when the user asks to "apply skill improvements", "update skill from plan", "execute improvement plan", "fix skill issues", "implement skill recommendations", or mentions applying improvements from quality review reports. Reads improvement-plan-{name}.md files generated by skill-quality-reviewer and intelligently merges and executes the suggested changes to improve Claude Skills quality. +version: 1.0.0 +--- + +# Skill Improver + +Execute improvement plans generated by `skill-quality-reviewer` to automatically update and fix issues in Claude Skills. + +## Core Workflow + +``` +Read improvement-plan-{name}.md + ↓ +Parse improvement items (High/Medium/Low priority) + ↓ +Group changes by file + ↓ +Detect and resolve conflicts + ↓ +Backup original files + ↓ +Execute updates (Edit or Write tools) + ↓ +Verify results + ↓ +Generate update-report +``` + +## When to Use + +**Trigger phrases:** +- "Apply improvements from improvement-plan-git-workflow.md" +- "Update my skill based on the quality report" +- "Execute the improvement plan for api-helper" +- "Fix the issues identified in quality review" + +**Use this skill when:** +- Applying improvements from an improvement plan +- Updating a skill based on quality review feedback +- Executing recommended fixes from `skill-quality-reviewer` +- Implementing structured improvements to skill documentation + +## Step-by-Step Guide + +### Step 1: Load the Improvement Plan + +Read the `improvement-plan-{skill-name}.md` file generated by `skill-quality-reviewer`. + +```bash +# Plan is typically in current directory +ls improvement-plan-*.md + +# Or specify full path +read /path/to/improvement-plan-my-skill.md +``` + +**Validate the plan:** +- File exists and is readable +- Contains priority sections (High/Medium/Low) +- Has structured improvement items +- Includes file paths and suggested changes + +See `references/plan-format.md` for detailed plan structure. + +### Step 2: Parse and Group Changes + +Extract all improvement suggestions and organize by target file. + +**Extract from each item:** +- File path (e.g., `SKILL.md:line:line` or `references/file.md`) +- Dimension (Description Quality, Content Organization, etc.) +- Impact (+X points) +- Current content +- Suggested content +- Reason for change + +**Build update queue:** +``` +by_file = { + "SKILL.md": [change1, change2, ...], + "references/guide.md": [change3, ...], + "examples/demo.md": [change4, ...], +} +``` + +### Step 3: Detect and Resolve Conflicts + +Check for conflicts when multiple changes affect the same content. + +**Resolution strategy:** +1. High priority takes precedence over medium/low +2. If same priority, preserve first change +3. Flag conflicts for manual review +4. Document resolution in update report + +See `references/merge-strategies.md` for detailed merge logic. + +### Step 4: Sort by Priority + +Order changes by priority within each file. + +**Priority order:** +1. High Priority (execute first) +2. Medium Priority (execute second) +3. Low Priority (execute last) + +### Step 5: Backup and Execute + +**Backup location:** `~/.claude/skills/backup/{skill-name}-{timestamp}/` + +```bash +# Use backup script +~/.claude/skills/skill-improver/scripts/backup-skill.sh <skill-path> +``` + +**Apply changes:** +- Use Edit tool for existing content +- Use Write tool for new files +- Verify each change was applied + +### Step 6: Verify and Report + +**Verification checks:** +1. YAML syntax valid +2. All modified files exist and are valid +3. New files were created successfully +4. No unintended changes occurred + +```bash +# Use verify script +~/.claude/skills/skill-improver/scripts/verify-update.sh <skill-path> +``` + +**Generate update-report-{skill-name}-{timestamp}.md** documenting: +- Summary (files modified, files created, total changes) +- Changes Applied (per-file breakdown) +- Quality Improvement (before/after scores) +- Verification Results +- Backup Location + +See `examples/update-report-example.md` for report template. + +## Priority Handling + +### High Priority +Execute first. These typically address: +- Critical description issues +- Major writing style problems +- Missing structural elements +- Security-related concerns + +### Medium Priority +Execute after High. These typically address: +- Content organization improvements +- Additional examples +- Documentation enhancements + +### Low Priority +Execute last. These typically address: +- Minor clarifications +- Nice-to-have improvements +- Polish and refinement + +## Integration with Skill Quality Reviewer + +This skill works seamlessly with `skill-quality-reviewer`: + +``` +Current Skill (67/100 D+) + ↓ [skill-quality-reviewer] +Improvement Plan + ↓ [skill-improver] +Improved Skill (87/100 B+) + ↓ [skill-quality-reviewer] +Quality Report (validation) +``` + +**Iterate until desired quality level reached.** + +## Additional Resources + +### Reference Files + +- **`references/plan-format.md`** - Improvement plan file structure and format +- **`references/merge-strategies.md`** - Detailed merge algorithms and conflict resolution +- **`references/error-handling.md`** - Error handling strategies +- **`references/supported-updates.md`** - Supported update types with examples + +### Example Files + +- **`examples/improvement-plan-example.md`** - Sample improvement plan +- **`examples/update-report-example.md`** - Sample update report + +### Scripts + +- **`scripts/backup-skill.sh`** - Create backup of skill before updates +- **`scripts/verify-update.sh`** - Verify skill integrity after updates + +## Best Practices + +### Before Applying Updates + +1. **Review the improvement plan** - Understand what will change +2. **Verify backup location** - Ensure backups can be restored +3. **Check for manual changes** - Note any uncommitted local modifications +4. **Estimate impact** - Review expected quality improvement + +### During Update Execution + +1. **Process in priority order** - High → Medium → Low +2. **Verify after each file** - Check updates were applied correctly +3. **Log all changes** - Document what was modified +4. **Handle conflicts gracefully** - Flag for review if needed + +### After Applying Updates + +1. **Review the update report** - Confirm all changes were intended +2. **Test the skill** - Verify it still works correctly +3. **Compare scores** - Check quality improvement matches expectations +4. **Keep backup** - Retain backup until confident in changes + +## Usage Examples + +**Example 1: Apply improvements to local skill** +``` +User: "Apply improvements from improvement-plan-git-workflow.md" + +[Claude executes the workflow:] +1. Reads improvement-plan-git-workflow.md +2. Parses all improvement items +3. Groups changes by file +4. Detects and resolves conflicts +5. Sorts by priority +6. Backs up git-workflow skill +7. Executes updates +8. Verifies results +9. Generates update-report-git-workflow-timestamp.md +``` + +**Example 2: Update skill from quality review** +``` +User: "Update my api-helper skill based on quality report" + +[Claude:] +1. Locates improvement-plan-api-helper.md +2. Applies all recommended changes +3. Verifies skill structure +4. Reports quality improvement: 72/100 → 91/100 +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/examples/improvement-plan-example.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/examples/improvement-plan-example.md new file mode 100644 index 0000000..184ea0b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/examples/improvement-plan-example.md @@ -0,0 +1,85 @@ +# Skill Improvement Plan: example-skill + +## Priority Summary +- **High Priority**: 2 items +- **Medium Priority**: 1 item +- **Low Priority**: 1 item + +## High Priority Improvements + +### 1. Fix Description Trigger Phrases +**File**: SKILL.md:3:4 +**Dimension**: Description Quality +**Impact**: +20 points + +**Current**: +```yaml +--- +name: example-skill +description: A helpful skill for various tasks +--- +``` + +**Suggested**: +```yaml +--- +name: api-contract-manager +description: This skill should be used when the user asks to "validate API contract", "check API compatibility", or "detect breaking changes" +--- +``` + +**Reason**: The current description lacks specific trigger phrases and uses first-person format. The suggested version follows third-person format with clear trigger phrases. + +### 2. Convert to Imperative Form +**File**: SKILL.md:50:55 +**Dimension**: Writing Style +**Impact**: +15 points + +**Current**: +```markdown +You should create the file first. +You need to validate the input. +``` + +**Suggested**: +```markdown +Create the file first. +Validate the input. +``` + +**Reason**: Skills must use imperative form without second-person language. + +## Medium Priority Improvements + +### 3. Add Progressive Disclosure +**File**: SKILL.md +**Dimension**: Content Organization +**Impact**: +10 points + +**Current**: All content in SKILL.md (3000+ words) + +**Suggested**: Move detailed content to references/ directory, keep SKILL.md under 2000 words + +**Reason**: SKILL.md should follow progressive disclosure principles with lean main content and detailed references. + +## Low Priority Improvements + +### 4. Add Examples +**File**: examples/demo.md (new file) +**Dimension**: Structural Integrity +**Impact**: +5 points + +**Suggested**: Create examples/demo.md with working demonstration + +**Reason**: Examples help users understand how to use the skill effectively. + +## Estimated Time to Complete +- High Priority: 1 hour +- Medium Priority: 2 hours +- Low Priority: 30 minutes +- **Total**: 3.5 hours + +## Expected Score Improvement +- Current: 67/100 (D+) +- After High Priority: 82/100 (B-) +- After All: 87/100 (B+) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/examples/update-report-example.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/examples/update-report-example.md new file mode 100644 index 0000000..f3011ab --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/examples/update-report-example.md @@ -0,0 +1,45 @@ +# Skill Update Report: example-skill + +## Summary +- **Update Date**: 2025-01-25 14:30:00 +- **Improvement Plan**: improvement-plan-example-skill.md +- **Files Modified**: 1 +- **Files Created**: 1 +- **Total Changes Applied**: 4 + +## Changes Applied + +### SKILL.md +- ✅ Fixed description trigger phrases (line 3-4) +- ✅ Changed to imperative form (line 50, 52, 55) +- ✅ Reorganized content for progressive disclosure + +### examples/demo.md (new) +- ✅ Created example demonstration file + +## Quality Improvement + +| Dimension | Before | After | Change | +|-----------|--------|-------|--------| +| Description Quality | 55/100 | 90/100 | +35 | +| Content Organization | 70/100 | 85/100 | +15 | +| Writing Style | 60/100 | 95/100 | +35 | +| Structural Integrity | 80/100 | 90/100 | +10 | +| **Overall** | **67/100** | **87/100** | **+20** | + +**Grade**: D+ → B+ + +## Verification Results +- ✅ YAML syntax valid +- ✅ All files updated successfully +- ✅ No unintended changes +- ✅ Skill structure intact + +## Backup +Original files backed up to: `~/.claude/skills/backup/example-skill-20250125-143000/` + +## Notes +- All high priority changes applied successfully +- Medium priority reorganization completed +- Low priority example file created +- Skill is now ready for use diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/error-handling.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/error-handling.md new file mode 100644 index 0000000..6ef84fc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/error-handling.md @@ -0,0 +1,39 @@ +# Error Handling + +## Parse Errors + +**Symptom:** Cannot read improvement plan + +**Solutions:** +- Verify file exists and is readable +- Check file follows expected format +- Ensure proper markdown structure + +## Conflict Errors + +**Symptom:** Multiple changes to same content + +**Solutions:** +- Apply highest priority change +- Flag conflict for manual review +- Document decision in report + +## Edit Failures + +**Symptom:** Cannot find current content to replace + +**Solutions:** +- Verify current content matches exactly +- Check line numbers are correct +- File may have been modified externally +- Skip change and document in report + +## Verification Failures + +**Symptom:** Update broke skill structure + +**Solutions:** +- Restore from backup +- Review conflicting changes +- Apply changes individually +- Skip problematic changes diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/merge-strategies.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/merge-strategies.md new file mode 100644 index 0000000..dbb0a4d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/merge-strategies.md @@ -0,0 +1,570 @@ +# Merge Strategies for Skill Updates + +Detailed strategies for intelligently merging multiple improvements to the same skill files. + +## Overview + +When applying improvements from an improvement plan, multiple changes may affect the same file or even the same lines. This document defines strategies for detecting conflicts, resolving them, and applying updates in the correct order. + +## Priority-Based Merging + +### Priority Order + +Changes are applied in strict priority order: + +1. **High Priority** - Critical issues that must be fixed +2. **Medium Priority** - Important improvements +3. **Low Priority** - Nice-to-have enhancements + +### Rationale + +- High priority changes often fix fundamental issues +- Applying them first ensures a solid foundation +- Lower priority changes may depend on high priority fixes +- Prevents wasted effort on changes that might be reverted + +## Per-File Merge Strategy + +### Single File, Multiple Changes + +When multiple changes affect the same file: + +1. **Group by file** + ``` + SKILL.md: [ + { line: 10, priority: high, ... }, + { line: 50, priority: high, ... }, + { line: 100, priority: medium, ... }, + { line: 200, priority: low, ... } + ] + ``` + +2. **Sort by line number (descending)** + - Process from bottom to top + - Prevents line offset issues + - Earlier changes don't affect later line numbers + + ``` + SKILL.md: [ + { line: 200, priority: low, ... }, # First + { line: 100, priority: medium, ... }, # Second + { line: 50, priority: high, ... }, # Third + { line: 10, priority: high, ... } # Fourth + ] + ``` + +3. **Apply within same line range by priority** + - If multiple changes affect same lines + - Higher priority wins + - Document conflict in report + +### Algorithm + +```python +def merge_per_file(changes): + """Merge changes for a single file.""" + + # Group by line range + by_range = {} + for change in changes: + key = (change['start'], change['end']) + if key not in by_range: + by_range[key] = [] + by_range[key].append(change) + + # Resolve conflicts within ranges + resolved = [] + for range_key, range_changes in by_range.items(): + if len(range_changes) == 1: + resolved.append(range_changes[0]) + else: + # Conflict: pick highest priority + priority_order = {'high': 0, 'medium': 1, 'low': 2} + sorted_changes = sorted( + range_changes, + key=lambda c: priority_order[c['priority']] + ) + winner = sorted_changes[0] + winner['conflicts_with'] = sorted_changes[1:] + resolved.append(winner) + + # Sort by line number descending + resolved.sort(key=lambda c: c['start'], reverse=True) + + return resolved +``` + +## Cross-File Merge Strategy + +### Multiple Files, Multiple Changes + +When changes span multiple files: + +1. **Execute all High Priority changes first** + - Across all files + - Ensures critical fixes everywhere + +2. **Then execute all Medium Priority changes** + - Build on High Priority foundation + +3. **Finally execute all Low Priority changes** + - Polish and refine + +### Execution Order + +``` +Round 1: High Priority +├── SKILL.md (High changes) +├── references/guide.md (High changes) +└── examples/demo.md (High changes) + +Round 2: Medium Priority +├── SKILL.md (Medium changes) +├── references/guide.md (Medium changes) +└── examples/new.md (Medium, new file) + +Round 3: Low Priority +└── SKILL.md (Low changes) +``` + +### Algorithm + +```python +def merge_cross_files(all_changes): + """Merge changes across all files.""" + + # Group by priority + by_priority = { + 'high': [], + 'medium': [], + 'low': [] + } + + for change in all_changes: + by_priority[change['priority']].append(change) + + # Process each priority level + execution_order = [] + for priority in ['high', 'medium', 'low']: + # Group by file within priority + by_file = {} + for change in by_priority[priority]: + file = change['file'] + if file not in by_file: + by_file[file] = [] + by_file[file].append(change) + + # Merge within each file + for file, file_changes in by_file.items(): + merged = merge_per_file(file_changes) + execution_order.extend(merged) + + return execution_order +``` + +## Conflict Detection + +### Types of Conflicts + +#### 1. Same Line, Different Content + +``` +Change A: SKILL.md:10:10 +Current: "You should create file" +Suggested: "Create the file" + +Change B: SKILL.md:10:10 +Current: "You should create file" +Suggested: "Create file now" +``` + +**Resolution:** Higher priority wins, document conflict + +#### 2. Overlapping Line Ranges + +``` +Change A: SKILL.md:10:15 +Current: lines 10-15 content +Suggested: new content for 10-15 + +Change B: SKILL.md:12:20 +Current: lines 12-20 content +Suggested: new content for 12-20 +``` + +**Resolution:** Higher priority wins, lower priority is skipped + +#### 3. Same Priority Conflicts + +``` +Change A: SKILL.md:10:10 (High) +Suggested: "Option A" + +Change B: SKILL.md:10:10 (High) +Suggested: "Option B" +``` + +**Resolution:** First in list wins, flag for manual review + +### Conflict Detection Algorithm + +```python +def detect_conflicts(changes): + """Detect conflicting changes.""" + + conflicts = [] + + # Sort by line range + sorted_changes = sorted(changes, key=lambda c: (c['start'], c['end'])) + + for i in range(len(sorted_changes)): + for j in range(i + 1, len(sorted_changes)): + a = sorted_changes[i] + b = sorted_changes[j] + + # Check for overlap + if ranges_overlap(a, b): + # Check if suggestions differ + if a['suggested'] != b['suggested']: + conflicts.append({ + 'changes': [a, b], + 'type': 'overlap', + 'resolution': 'priority' + }) + + return conflicts + +def ranges_overlap(a, b): + """Check if two line ranges overlap.""" + + a_start, a_end = a['start'], a['end'] + b_start, b_end = b['start'], b['end'] + + return not (a_end < b_start or b_end < a_start) +``` + +## Conflict Resolution + +### Resolution Strategies + +#### 1. Priority-Based Resolution + +**Apply highest priority change:** +``` +Conflicting changes: +- High: Fix description +- Low: Clarify text + +Resolution: Apply High, skip Low +``` + +#### 2. First-Win Resolution + +**For same priority conflicts:** +``` +Conflicting changes (both High): +- #1: Fix description option A +- #2: Fix description option B + +Resolution: Apply #1, skip #2, flag for review +``` + +#### 3. Manual Review Flag + +**Document conflicts requiring human review:** +```markdown +## Conflicts Requiring Manual Review + +### SKILL.md:10:10 +**Applied:** High Priority - Fix description (Option A) +**Skipped:** High Priority - Alternative fix (Option B) +**Reason:** Same priority, first change applied + +Review suggested alternative and manually apply if preferred. +``` + +### Resolution Algorithm + +```python +def resolve_conflicts(changes): + """Resolve conflicts using priority-based strategy.""" + + priority_value = {'high': 3, 'medium': 2, 'low': 1} + + # Track applied line ranges + applied_ranges = [] + + # Filter changes + resolved = [] + skipped = [] + + for change in sorted(changes, key=lambda c: ( + -priority_value[c['priority']], # Higher priority first + c['start'] + )): + # Check if range already applied + conflict = False + for applied in applied_ranges: + if ranges_overlap(change, applied): + conflict = True + skipped.append({ + 'change': change, + 'reason': 'overlap_with_higher_priority', + 'conflicts_with': applied + }) + break + + if not conflict: + resolved.append(change) + applied_ranges.append({ + 'start': change['start'], + 'end': change['end'] + }) + + return resolved, skipped +``` + +## Special Cases + +### New File Creation + +When creating new files (no line numbers): + +1. **Check if file already exists** +2. **If exists:** Verify content matches or skip +3. **If not exists:** Create with suggested content + +```python +def handle_new_file(change, skill_path): + """Handle new file creation.""" + + file_path = os.path.join(skill_path, change['file']) + + if os.path.exists(file_path): + # File exists, verify content + existing = read_file(file_path) + if existing.strip() == change['suggested'].strip(): + return {'status': 'already_exists', 'action': 'skip'} + else: + return { + 'status': 'conflict', + 'action': 'skip', + 'reason': 'File exists with different content' + } + else: + # Create new file + write_file(file_path, change['suggested']) + return {'status': 'created', 'action': 'created'} +``` + +### Append Operations + +When no line numbers and file exists: + +```python +def handle_append(change, skill_path): + """Handle append to existing file.""" + + file_path = os.path.join(skill_path, change['file']) + + if os.path.exists(file_path): + # Append to end + existing = read_file(file_path) + updated = existing + '\n\n' + change['suggested'] + write_file(file_path, updated) + return {'status': 'appended', 'action': 'appended'} + else: + # Treat as new file + write_file(file_path, change['suggested']) + return {'status': 'created', 'action': 'created'} +``` + +### YAML Frontmatter Updates + +Special handling for YAML frontmatter: + +1. **Parse existing frontmatter** +2. **Update specific fields** +3. **Preserve other fields** +4. **Validate YAML syntax** + +```python +def update_frontmatter(file_path, updates): + """Update YAML frontmatter fields.""" + + # Read file + content = read_file(file_path) + + # Extract frontmatter + frontmatter, body = extract_frontmatter(content) + + # Parse YAML + import yaml + data = yaml.safe_load(frontmatter) + + # Apply updates + for key, value in updates.items(): + data[key] = value + + # Serialize back + new_frontmatter = yaml.dump(data, default_flow_style=False) + + # Reconstruct file + updated = f"---\n{new_frontmatter}---\n{body}" + + write_file(file_path, updated) +``` + +## Verification After Merge + +### Post-Merge Checks + +After applying all changes: + +1. **Verify file existence** + ```python + for change in applied_changes: + file_path = os.path.join(skill_path, change['file']) + assert os.path.exists(file_path), f"File not found: {file_path}" + ``` + +2. **Verify YAML syntax** + ```bash + ~/.claude/skills/skill-quality-reviewer/scripts/extract-yaml.sh <skill-path> + ``` + +3. **Verify content was applied** + ```python + for change in applied_changes: + content = read_file(change['file']) + assert change['suggested'] in content, "Change not found in file" + ``` + +4. **Verify no unintended changes** + ```python + # Compare backup with current + # Only expected changes should be present + ``` + +## Complete Merge Workflow + +```python +def execute_merge(improvement_plan, skill_path): + """Complete merge workflow.""" + + # 1. Parse improvement plan + changes = parse_improvement_plan(improvement_plan) + + # 2. Detect conflicts + conflicts = detect_conflicts(changes) + + # 3. Resolve conflicts + resolved, skipped = resolve_conflicts(changes) + + # 4. Sort by execution order + execution_order = merge_cross_files(resolved) + + # 5. Backup original files + backup_skill(skill_path) + + # 6. Execute changes + applied = [] + failed = [] + + for change in execution_order: + try: + if change['start'] is None: + # New file or append + result = handle_new_file(change, skill_path) + else: + # Edit existing content + result = edit_file( + change['file'], + change['start'], + change['end'], + change['current'], + change['suggested'] + ) + + applied.append({ + 'change': change, + 'result': result + }) + + except Exception as e: + failed.append({ + 'change': change, + 'error': str(e) + }) + + # 7. Verify results + verification = verify_merge(skill_path, applied) + + # 8. Generate report + report = generate_merge_report( + applied=applied, + failed=failed, + skipped=skipped, + conflicts=conflicts, + verification=verification + ) + + return report +``` + +## Best Practices + +### When Merging + +1. **Always backup first** - Restore if things go wrong +2. **Apply high priority first** - Critical fixes first +3. **Process bottom to top** - Avoid line offset issues +4. **Verify after each file** - Catch errors early +5. **Document all decisions** - Clear update report + +### When Conflicts Occur + +1. **Prioritize by importance** - Critical over nice-to-have +2. **Flag for review** - Let user decide when unsure +3. **Don't silently skip** - Document everything +4. **Preserve originals** - Backup enables recovery + +### After Merging + +1. **Run verification** - Ensure skill still works +2. **Review report** - Confirm changes match intent +3. **Test the skill** - Verify functionality +4. **Keep backup** - Until confident in changes + +## Error Recovery + +### If Merge Fails + +1. **Stop immediately** - Don't continue with errors +2. **Identify failure point** - Which change caused issue +3. **Restore from backup** - Return to original state +4. **Analyze failure** - Understand why it failed +5. **Retry selectively** - Skip problematic changes + +### Partial Recovery + +If some changes applied before failure: + +```python +def partial_recovery(applied, backup_path): + """Restore only failed changes.""" + + # Get list of applied files + applied_files = set(c['file'] for c in applied) + + # Restore only files that failed + for file_path in failed_files: + restore_from_backup(file_path, backup_path) + + return { + 'restored': failed_files, + 'preserved': applied_files + } +``` + +This ensures successful changes are preserved while failed ones are reverted. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/plan-format.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/plan-format.md new file mode 100644 index 0000000..ab6e6df --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/plan-format.md @@ -0,0 +1,518 @@ +# Improvement Plan Format + +Detailed specification of the `improvement-plan-{skill-name}.md` file format generated by `skill-quality-reviewer` and consumed by `skill-improver`. + +## File Structure + +```markdown +# Skill Improvement Plan: {skill-name} + +## Priority Summary +- **High Priority**: {count} items +- **Medium Priority**: {count} items +- **Low Priority**: {count} items + +## High Priority Improvements + +### 1. [Issue Title] +**File**: SKILL.md:line:line +**Dimension**: {Dimension Name} +**Impact**: +X points + +**Current**: +```yaml or markdown +{current content} +``` + +**Suggested**: +```yaml or markdown +{suggested content} +``` + +**Reason**: {why this improves quality} + +[Repeat for all high priority items...] + +## Medium Priority Improvements +[Same format as High Priority...] + +## Low Priority Improvements +[Same format as High Priority...] + +## Quick Wins (Easy Fixes) +1. {quick fix description} +2. {quick fix description} + +## Estimated Time to Complete +- High Priority: X hours +- Medium Priority: X hours +- Low Priority: X hours +- **Total**: X hours + +## Expected Score Improvement +- Current: X/100 ({Grade}) +- After High Priority: X/100 ({Grade}) +- After All: X/100 ({Grade}) +``` + +## Parsing Rules + +### Priority Section Detection + +**Identify sections by heading:** +```markdown +## High Priority Improvements +## Medium Priority Improvements +## Low Priority Improvements +``` + +**Case insensitive but exact match preferred:** +- "High Priority Improvements" ✓ +- "high priority improvements" ✓ (acceptable) +- "High Priority" ✗ (incomplete) + +### Item Extraction + +**Each improvement item starts with:** +```markdown +### N. [Issue Title] +``` + +Where N is a sequential number (1, 2, 3, ...) + +**Required fields within each item:** + +1. **File** (required) + ``` + **File**: SKILL.md:line:line + **File**: references/filename.md + **File**: examples/filename.md + ``` + - Format: `filepath:line:line` or just `filepath` + - Line numbers are specific for edits + - File only indicates new file creation or append + +2. **Dimension** (required) + ``` + **Dimension**: Description Quality + **Dimension**: Content Organization + **Dimension**: Writing Style + **Dimension**: Structural Integrity + ``` + +3. **Impact** (required) + ``` + **Impact**: +X points + ``` + - Points indicate expected score improvement + - Used for calculating expected final score + +4. **Current** (required for edits) + ``` + **Current**: + ```yaml or markdown + {exact current content} + ``` + - Must match exactly for Edit operations + - Code fence specifies format (yaml, markdown, etc.) + +5. **Suggested** (required) + ``` + **Suggested**: + ```yaml or markdown + {suggested replacement content} + ``` + - Content to replace current or create + +6. **Reason** (optional but recommended) + ``` + **Reason**: {explanation} + ``` + - Human-readable explanation + - Included in update report + +### Code Fence Formats + +**Supported formats:** +```yaml +```yaml +--- +name: skill-name +--- +``` +``` + +```markdown +```markdown +## Section Header + +Content here... +``` +``` + +```bash +```bash +#!/bin/bash +echo "script" +``` +``` + +**Format determines:** +- Syntax highlighting +- Validation rules +- Parser expectations + +## File Path Patterns + +### SKILL.md References + +**With line numbers:** +``` +**File**: SKILL.md:5:10 +``` +- Lines 5-10 will be replaced +- Used for Edit operations + +**Without line numbers:** +``` +**File**: SKILL.md +``` +- Typically indicates new file or append + +### References/ Files + +**Specific file:** +``` +**File**: references/api-guide.md +**File**: references/examples-bad.md +``` + +**With line numbers:** +``` +**File**: references/patterns.md:50:100 +``` + +### Examples/ Files + +**New file creation:** +``` +**File**: examples/demo.md +``` +- No line numbers +- Suggested content becomes entire file + +**Modification:** +``` +**File**: examples/basic-usage.sh:20:30 +``` + +### Scripts/ Files + +**Script updates:** +``` +**File**: scripts/validate.sh:15:25 +``` + +## Parsing Pseudocode + +```python +def parse_improvement_plan(plan_path): + """Parse improvement plan file into structured data.""" + + plan = read_file(plan_path) + sections = { + 'high': [], + 'medium': [], + 'low': [] + } + + current_section = None + current_item = None + + for line in plan.split('\n'): + # Detect section headers + if line.startswith('## High Priority'): + current_section = 'high' + elif line.startswith('## Medium Priority'): + current_section = 'medium' + elif line.startswith('## Low Priority'): + current_section = 'low' + + # Detect item start + elif line.startswith('### '): + if current_item: + sections[current_section].append(current_item) + current_item = {'title': line[4:].strip()} + + # Parse fields within item + elif current_item: + if line.startswith('**File**'): + current_item['file'] = parse_file_path(line) + elif line.startswith('**Dimension**'): + current_item['dimension'] = line.split(':', 1)[1].strip() + elif line.startswith('**Impact**'): + current_item['impact'] = parse_impact(line) + elif line.startswith('**Current**'): + current_item['current'] = extract_code_fence(plan, line) + elif line.startswith('**Suggested**'): + current_item['suggested'] = extract_code_fence(plan, line) + elif line.startswith('**Reason**'): + current_item['reason'] = line.split(':', 1)[1].strip() + + # Add last item + if current_item: + sections[current_section].append(current_item) + + return sections +``` + +## Line Number Handling + +### Single Line + +``` +**File**: SKILL.md:10:10 +``` +- Only line 10 is replaced + +### Line Range + +``` +**File**: SKILL.md:10:15 +``` +- Lines 10-15 are replaced +- Current content should span these lines + +### No Line Numbers + +``` +**File**: references/new-file.md +``` +- New file creation +- Or append to existing file + +### Line Number Extraction + +```python +def parse_file_path(line): + """Extract file path and line numbers from File field.""" + + # Remove "**File**:" prefix + value = line.split(':', 1)[1].strip() + + # Check for line numbers + if ':' in value: + parts = value.split(':') + file_path = ':'.join(parts[:-2]) + start_line = int(parts[-2]) + end_line = int(parts[-1]) + return { + 'path': file_path, + 'start': start_line, + 'end': end_line + } + else: + return { + 'path': value, + 'start': None, + 'end': None + } +``` + +## Impact Extraction + +```python +def parse_impact(line): + """Extract impact value from Impact field.""" + + # Format: **Impact**: +X points + value = line.split(':', 1)[1].strip() + # Extract number + import re + match = re.search(r'\+(\d+)', value) + if match: + return int(match.group(1)) + return 0 +``` + +## Code Fence Extraction + +```python +def extract_code_fence(content, start_line): + """Extract code block starting after current line.""" + + lines = content.split('\n') + start_idx = lines.index(start_line) + + # Find opening fence + for i in range(start_idx, len(lines)): + if lines[i].strip().startswith('```'): + fence_start = i + lang = lines[i].strip()[3:] + break + + # Find closing fence + for i in range(fence_start + 1, len(lines)): + if lines[i].strip() == '```': + fence_end = i + break + + # Extract content + code_lines = lines[fence_start + 1:fence_end] + return '\n'.join(code_lines) +``` + +## Validation Rules + +### Required Sections + +- [ ] High Priority Improvements (may be empty) +- [ ] Medium Priority Improvements (may be empty) +- [ ] Low Priority Improvements (may be empty) + +### Required Item Fields + +For each improvement item: +- [ ] **File** field present +- [ ] **Dimension** field present +- [ ] **Impact** field present +- [ ] **Current** field present (for edits) +- [ ] **Suggested** field present + +### File Path Validity + +- [ ] File path is valid format +- [ ] Line numbers are integers (if present) +- [ ] File extension matches content type + +### Code Fence Validity + +- [ ] Opening fence present +- [ ] Closing fence present +- [ ] Language identifier valid +- [ ] Content non-empty (for suggested) + +## Example Improvement Plan + +```markdown +# Skill Improvement Plan: example-skill + +## Priority Summary +- **High Priority**: 2 items +- **Medium Priority**: 1 item +- **Low Priority**: 1 item + +## High Priority Improvements + +### 1. Fix Description Trigger Phrases +**File**: SKILL.md:3:5 +**Dimension**: Description Quality +**Impact**: +20 points + +**Current**: +```yaml +--- +name: example-skill +description: Use this for helpful tasks. +--- +``` + +**Suggested**: +```yaml +--- +name: example-skill +description: This skill should be used when the user asks to "validate data", +"check schemas", or "verify formats". Perform data validation and schema +checking for JSON and YAML files. +--- +``` + +**Reason**: Add specific trigger phrases and use third-person format. + +### 2. Fix Writing Style +**File**: SKILL.md:25:30 +**Dimension**: Writing Style +**Impact**: +15 points + +**Current**: +```markdown +## Overview +You should use this skill to validate data files. You can choose from +JSON or XML formats. +``` + +**Suggested**: +```markdown +## Overview +Validate data files in JSON or XML formats with configurable schemas. +``` + +**Reason**: Change to imperative form, remove second person. + +## Medium Priority Improvements + +### 1. Add Reference Documentation +**File**: references/validation-rules.md +**Dimension**: Content Organization +**Impact**: +10 points + +**Suggested**: +```markdown +# Validation Rules + +## JSON Schema Rules +- Required fields validation +- Type checking +- Format validation + +## YAML Schema Rules +- Structure validation +- Type coercion rules +``` + +**Reason**: Move detailed rules to references for progressive disclosure. + +## Low Priority Improvements + +### 1. Clarify Description +**File**: SKILL.md:50:52 +**Dimension**: Writing Style +**Impact**: +5 points + +**Current**: +```markdown +## Usage +Use the skill when you need to validate files. +``` + +**Suggested**: +```markdown +## Usage +Invoke skill for file validation tasks. +``` + +**Reason**: Use imperative form for consistency. + +## Quick Wins (Easy Fixes) +1. Add space after comma in description (+2 points) +2. Fix indentation in examples section (+3 points) + +## Estimated Time to Complete +- High Priority: 0.5 hours +- Medium Priority: 0.5 hours +- Low Priority: 0.25 hours +- **Total**: 1.25 hours + +## Expected Score Improvement +- Current: 65/100 (D) +- After High Priority: 82/100 (B-) +- After All: 88/100 (B+) +``` + +## Integration Notes + +**Generated by:** `skill-quality-reviewer` +**Consumed by:** `skill-improver` + +**Format version:** 1.0 +**Compatibility:** Must maintain backward compatibility diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/supported-updates.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/supported-updates.md new file mode 100644 index 0000000..7d48a90 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/references/supported-updates.md @@ -0,0 +1,53 @@ +# Supported Update Types + +## YAML Frontmatter Updates + +Update name or description: + +```yaml +# Current +--- +name: my-skill +description: A helpful skill for various tasks. +--- + +# Suggested +--- +name: api-contract-manager +description: This skill should be used when the user asks to "validate API contract", "check API compatibility", or "detect breaking changes" +--- +``` + +## SKILL.md Content Updates + +Fix writing style (imperative form): + +``` +# Current +You should create the file first. +You need to validate the input. + +# Suggested +Create the file first. +Validate the input. +``` + +## References/ File Updates + +Add new section: + +```markdown +## New Section + +Content to be added... +``` + +## New File Creation + +Create new example file: + +```markdown +# examples/demo.md + +Complete example content... +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/scripts/backup-skill.sh b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/scripts/backup-skill.sh new file mode 100755 index 0000000..d4a5eee --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/scripts/backup-skill.sh @@ -0,0 +1,56 @@ +#!/bin/bash +# backup-skill.sh - Backup skill files before applying updates +# Part of skill-improver + +# Usage: ./backup-skill.sh <skill-path> +# Example: ./backup-skill.sh ~/.claude/skills/git-workflow + +set -euo pipefail + +# Check if path provided +if [ $# -eq 0 ]; then + echo "Usage: $0 <skill-path>" + echo "Example: $0 ~/.claude/skills/git-workflow" + exit 1 +fi + +SKILL_PATH="$1" +SKILL_NAME=$(basename "$SKILL_PATH") +TIMESTAMP=$(date +%Y%m%d-%H%M%S) +BACKUP_DIR="$HOME/.claude/skills/backup/${SKILL_NAME}-${TIMESTAMP}" + +# Check if skill path exists +if [ ! -d "$SKILL_PATH" ]; then + echo "Error: Skill path not found: ${SKILL_PATH}" + exit 1 +fi + +# Create backup directory +echo "Creating backup directory: ${BACKUP_DIR}" +mkdir -p "$BACKUP_DIR" + +# Copy entire skill directory +echo "Backing up skill: ${SKILL_NAME}" +cp -R "$SKILL_PATH"/* "$BACKUP_DIR/" + +# Create backup manifest +cat > "$BACKUP_DIR/backup-manifest.txt" <<EOF +Backup Manifest +============== +Skill Name: ${SKILL_NAME} +Source Path: ${SKILL_PATH} +Backup Date: $(date) +Timestamp: ${TIMESTAMP} + +Files Backed Up: +$(find "$BACKUP_DIR" -type f ! -name "backup-manifest.txt" | sed "s|$BACKUP_DIR/||") + +Restore Instructions: +------------------- +To restore this backup, run: + cp -R ${BACKUP_DIR}/* ${SKILL_PATH}/ +EOF + +echo "Backup complete!" +echo "Backup location: ${BACKUP_DIR}" +echo "Files backed up: $(find "$BACKUP_DIR" -type f ! -name "backup-manifest.txt" | wc -l)" diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/scripts/verify-update.sh b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/scripts/verify-update.sh new file mode 100755 index 0000000..f9c940f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-improver/scripts/verify-update.sh @@ -0,0 +1,251 @@ +#!/bin/bash +# verify-update.sh - Verify skill integrity after applying updates +# Part of skill-improver + +# Usage: ./verify-update.sh <skill-path> +# Example: ./verify-update.sh ~/.claude/skills/git-workflow + +set -euo pipefail + +# Check if path provided +if [ $# -eq 0 ]; then + echo "Usage: $0 <skill-path>" + echo "Example: $0 ~/.claude/skills/git-workflow" + exit 1 +fi + +SKILL_PATH="$1" +SKILL_NAME=$(basename "$SKILL_PATH") +SKILL_FILE="${SKILL_PATH}/SKILL.md" + +# Verification results +PASS=0 +FAIL=0 +WARN=0 + +echo "================================" +echo "Skill Update Verification" +echo "================================" +echo "Skill: ${SKILL_NAME}" +echo "Path: ${SKILL_PATH}" +echo "" + +# Check 1: SKILL.md exists +echo "Check 1: SKILL.md exists" +if [ -f "$SKILL_FILE" ]; then + echo "✅ PASS: SKILL.md found" + ((PASS++)) +else + echo "❌ FAIL: SKILL.md not found" + ((FAIL++)) + echo "" + echo "Verification Summary:" + echo " Passed: ${PASS}" + echo " Failed: ${FAIL}" + echo " Warnings: ${WARN}" + exit 1 +fi + +echo "" + +# Check 2: YAML frontmatter valid +echo "Check 2: YAML frontmatter valid" +if command -v yq &> /dev/null; then + # Use yq if available for proper YAML validation + FRONTMAFTER=$(sed -n '/^---$/,/^---$/{ /^---$/d; p; }' "$SKILL_FILE") + if echo "$FRONTMAFTER" | yq eval '.' > /dev/null 2>&1; then + echo "✅ PASS: YAML frontmatter is valid" + ((PASS++)) + else + echo "❌ FAIL: Invalid YAML frontmatter" + ((FAIL++)) + fi +else + # Fallback: basic check for name and description fields + if grep -q "^name:" "$SKILL_FILE" && grep -q "^description:" "$SKILL_FILE"; then + echo "✅ PASS: YAML frontmatter has required fields (name, description)" + ((PASS++)) + else + echo "❌ FAIL: YAML frontmatter missing required fields" + ((FAIL++)) + fi +fi + +echo "" + +# Check 3: Directory structure +echo "Check 3: Directory structure" +DIRS_OK=true + +if [ -d "${SKILL_PATH}/references" ]; then + echo " ✅ references/ exists" +else + echo " ℹ️ references/ not found (optional)" + ((WARN++)) +fi + +if [ -d "${SKILL_PATH}/examples" ]; then + echo " ✅ examples/ exists" +else + echo " ℹ️ examples/ not found (optional)" + ((WARN++)) +fi + +if [ -d "${SKILL_PATH}/scripts" ]; then + echo " ✅ scripts/ exists" + # Check if scripts are executable (macOS compatible) + SCRIPT_COUNT=$(find "${SKILL_PATH}/scripts" -type f | wc -l | tr -d ' ') + EXEC_COUNT=0 + for script in "${SKILL_PATH}/scripts"/*; do + if [ -f "$script" ] && [ -x "$script" ]; then + ((EXEC_COUNT++)) + fi + done + if [ "$SCRIPT_COUNT" -gt 0 ] && [ "$EXEC_COUNT" -eq "$SCRIPT_COUNT" ]; then + echo " ✅ All scripts are executable" + elif [ "$SCRIPT_COUNT" -gt 0 ]; then + echo " ⚠️ Some scripts are not executable (${EXEC_COUNT}/${SCRIPT_COUNT} executable)" + ((WARN++)) + fi +else + echo " ℹ️ scripts/ not found (optional)" +fi + +if [ "$DIRS_OK" = true ] || [ ! -d "${SKILL_PATH}/references" ] && [ ! -d "${SKILL_PATH}/examples" ]; then + echo "✅ PASS: Directory structure is valid" + ((PASS++)) +else + echo "⚠️ WARN: Optional directories missing" +fi + +echo "" + +# Check 4: SKILL.md size (progressive disclosure check) +echo "Check 4: SKILL.md size (progressive disclosure)" +WORD_COUNT=$(wc -w < "$SKILL_FILE" | tr -d ' ') + +if [ "$WORD_COUNT" -lt 3000 ]; then + echo "✅ PASS: SKILL.md is ${WORD_COUNT} words (good progressive disclosure)" + ((PASS++)) +elif [ "$WORD_COUNT" -lt 5000 ]; then + echo "⚠️ WARN: SKILL.md is ${WORD_COUNT} words (could be more concise)" + ((WARN++)) +else + echo "❌ FAIL: SKILL.md is ${WORD_COUNT} words (too long, should use references/)" + ((FAIL++)) +fi + +echo "" + +# Check 5: No broken references (basic check) +echo "Check 5: Referenced files exist" +BROKEN_REFS=0 + +# Extract references from SKILL.md +# Look for patterns like "See `references/file.md`" or "**`references/pattern.md`**" +REF_FILES=$(grep -oE 'references/[-_a-zA-Z0-9\.]+' "$SKILL_FILE" | sort -u || true) + +if [ -n "$REF_FILES" ]; then + for ref in $REF_FILES; do + REF_PATH="${SKILL_PATH}/${ref}" + if [ -f "$REF_PATH" ]; then + echo " ✅ ${ref} exists" + else + echo " ❌ ${ref} referenced but not found" + ((BROKEN_REFS++)) + fi + done + + if [ "$BROKEN_REFS" -eq 0 ]; then + echo "✅ PASS: All referenced files exist" + ((PASS++)) + else + echo "❌ FAIL: ${BROKEN_REFS} referenced file(s) not found" + ((FAIL++)) + fi +else + echo "ℹ️ No references found in SKILL.md" + echo "✅ PASS: No broken references" + ((PASS++)) +fi + +echo "" + +# Check 6: Writing style (imperative form check) +echo "Check 6: Writing style (imperative form check)" +SECOND_PERSON=$(grep -iE "you should|you need|you can|you must|you'll|your" "$SKILL_FILE" | wc -l | tr -d ' ') + +if [ "$SECOND_PERSON" -eq 0 ]; then + echo "✅ PASS: No second-person language found" + ((PASS++)) +elif [ "$SECOND_PERSON" -lt 5 ]; then + echo "⚠️ WARN: ${SECOND_PERSON} instance(s) of second-person language" + ((WARN++)) + # Still count as pass for now + ((PASS++)) +else + echo "❌ FAIL: ${SECOND_PERSON} instances of second-person language" + echo " (should use imperative form)" + ((FAIL++)) +fi + +echo "" + +# Check 7: Description quality (basic check) +echo "Check 7: Description quality" +DESCRIPTION=$(grep "^description:" "$SKILL_FILE" | head -1) + +if [ -n "$DESCRIPTION" ]; then + # Check for third person + if echo "$DESCRIPTION" | grep -qi "this skill should be used when"; then + echo " ✅ Uses third-person format" + DESC_OK=true + else + echo " ❌ Does not use third-person format" + DESC_OK=false + fi + + # Check length (100-300 characters ideal) + DESC_LEN=$(echo "$DESCRIPTION" | cut -d: -f2- | wc -c | tr -d ' ') + if [ "$DESC_LEN" -ge 100 ] && [ "$DESC_LEN" -le 300 ]; then + echo " ✅ Description length is ${DESC_LEN} characters (good)" + elif [ "$DESC_LEN" -lt 100 ]; then + echo " ⚠️ Description is ${DESC_LEN} characters (too short)" + DESC_OK=false + else + echo " ⚠️ Description is ${DESC_LEN} characters (too long)" + DESC_OK=false + fi + + if [ "$DESC_OK" = true ]; then + echo "✅ PASS: Description quality is good" + ((PASS++)) + else + echo "⚠️ WARN: Description could be improved" + ((WARN++)) + # Still count as pass for basic check + ((PASS++)) + fi +else + echo "❌ FAIL: No description found in frontmatter" + ((FAIL++)) +fi + +echo "" +echo "================================" +echo "Verification Summary" +echo "================================" +echo " Passed: ${PASS}" +echo " Failed: ${FAIL}" +echo " Warnings: ${WARN}" +echo "" + +if [ "$FAIL" -eq 0 ]; then + echo "✅ Verification PASSED" + echo " Skill structure is valid." + exit 0 +else + echo "❌ Verification FAILED" + echo " Please review and fix the failed checks." + exit 1 +fi diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/SKILL.md new file mode 100644 index 0000000..7c3463f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/SKILL.md @@ -0,0 +1,425 @@ +--- +name: skill-quality-reviewer +description: This skill should be used when the user asks to "analyze skill quality", "evaluate this skill", "review skill quality", "check my skill", or "generate quality report". Evaluates local skills across description quality, content organization, writing style, and structural integrity. +version: 0.1.0 +--- + +# Skill Quality Reviewer + +## Overview + +A meta-skill for evaluating the quality of Claude Skills. Perform comprehensive analysis across four key dimensions—description quality (25%), content organization (30%), writing style (20%), and structural integrity (25%)—to generate weighted scores, letter grades, and actionable improvement plans. + +Use this skill to validate skills before sharing, identify improvement opportunities, or ensure compliance with skill development best practices. + +## When to Use This Skill + +**Invoke this skill when:** +- Analyzing a skill's quality before distribution +- Reviewing skill documentation for best practices +- Evaluating adherence to skill development standards +- Generating improvement recommendations for existing skills +- Validating skill structure and completeness + +**Trigger phrases:** +- "Analyze skill quality for ./my-skill" +- "Evaluate this skill: ~/.claude/skills/api-helper" +- "Review skill quality of git-workflow" +- "Check my skill for best practices" +- "Generate quality report for this skill" + +## Review Modes + +Use one of three review modes depending on the task: + +1. **score-only** + - fast first-pass grading for one skill. +2. **remediation-backlog** + - convert findings into P0 / P1 / P2 fix queues with concrete evidence. +3. **batch-portfolio** + - review multiple skills together, cluster repeated issues, and produce a prioritized shortlist. + +Prefer `remediation-backlog` when the user asks what to fix next. +Prefer `batch-portfolio` when auditing many skills at once. + +## Analysis Workflow + +### Step 1: Load the Skill + +Accept skill path as input. Verify the path exists and contains `SKILL.md`. Read the complete skill directory structure. + +```bash +# Example invocation +ls -la ~/.claude/skills/target-skill/ +``` + +**Validate:** +- SKILL.md exists +- Directory is readable +- Path points to a valid skill + +### Step 2: Parse YAML Frontmatter + +Extract and validate the YAML frontmatter from SKILL.md. + +**Required fields:** +- `name` - Skill identifier +- `description` - Trigger description with phrases + +**Check for:** +- Valid YAML syntax +- No prohibited fields +- Proper formatting + +### Step 3: Evaluate Description Quality (25%) + +Assess the quality and effectiveness of the frontmatter description. + +**Scoring breakdown:** + +| Criterion | Points | Evaluation | +|-----------|--------|------------| +| Trigger phrases clarity | 25 | 3-5 specific user phrases present | +| Third-person format | 25 | Uses "This skill should be used when..." | +| Description length | 25 | 100-300 characters optimal | +| Specific scenarios | 25 | Concrete use cases, not vague | + +**Red flags:** +- Vague triggers like "helps with tasks" +- Second-person descriptions ("Use this when you...") +- Missing or generic descriptions +- No actionable trigger phrases + +**Reference:** `references/examples-good.md` for exemplary descriptions + +### Step 4: Evaluate Content Organization (30%) + +Assess adherence to progressive disclosure principles. + +**Scoring breakdown:** + +| Criterion | Points | Evaluation | +|-----------|--------|------------| +| Progressive disclosure | 30 | SKILL.md lean, details in references/ | +| SKILL.md length | 25 | Under 5,000 words (1,500-2,000 ideal) | +| References/ usage | 25 | Detailed content properly moved | +| Logical organization | 20 | Clear sections, good flow | + +**Check:** +- SKILL.md body is concise and focused +- Detailed content moved to `references/` +- Examples and templates in appropriate directories +- No information duplication across files + +**Reference:** `references/scoring-criteria.md` for detailed rubrics + +### Step 5: Evaluate Writing Style (20%) + +Verify adherence to skill writing conventions. + +**Scoring breakdown:** + +| Criterion | Points | Evaluation | +|-----------|--------|------------| +| Imperative form | 40 | Verb-first instructions throughout | +| No second person in body | 30 | Avoids conversational second person in the main workflow body | +| Objective language | 30 | Factual, instructional tone | + +**Check for:** +- Imperative verbs: "Create the file", "Validate input", "Check structure" +- Absence of: "You should", "You can", "You need to" +- Objective, instructional language +- Consistent style throughout + +**Good examples:** +``` +Create the skill directory structure. +Validate the YAML frontmatter. +Check for required fields. +``` + +**Bad examples:** +``` +You should create the directory. +You need to validate the frontmatter. +Check if the fields are there. +``` + +### Step 6: Evaluate Structural Integrity (25%) + +Verify the skill's physical structure and completeness. + +**Scoring breakdown:** + +| Criterion | Points | Evaluation | +|-----------|--------|------------| +| YAML frontmatter | 30 | All required fields present | +| Directory structure | 30 | Proper organization | +| Resource references | 40 | All referenced files exist | + +**Validate:** +- YAML frontmatter contains `name` and `description` +- Directory structure follows conventions: + ``` + skill-name/ + ├── SKILL.md + ├── references/ (optional) + ├── examples/ (optional) + └── scripts/ (optional) + ``` +- All files referenced in SKILL.md actually exist +- Examples are complete and working +- Scripts are executable + +### Step 7: Calculate Weighted Score + +Compute the overall quality score using weighted dimensions. + +**Formula:** +``` +Overall Score = (Description × 0.25) + (Organization × 0.30) + + (Style × 0.20) + (Structure × 0.25) +``` + +**Letter grade mapping:** + +| Score Range | Grade | Meaning | +|-------------|-------|---------| +| 97-100 | A+ | Exemplary | +| 93-96 | A | Excellent | +| 90-92 | A- | Very Good | +| 87-89 | B+ | Good | +| 83-86 | B | Above Average | +| 80-82 | B- | Solid | +| 77-79 | C+ | Acceptable | +| 73-76 | C | Satisfactory | +| 70-72 | C- | Minimal Acceptable | +| 67-69 | D+ | Below Standard | +| 63-66 | D | Poor | +| 60-62 | D- | Very Poor | +| 0-59 | F | Fail | + +### Step 8: Generate Reports + +Create two output documents in the current working directory. + +**1. Quality Report** (`quality-report-{skill-name}.md`) +- Executive summary with overall score and grade +- Dimension-by-dimension breakdown +- Strengths and weaknesses for each dimension +- Grade breakdown table +- Link to improvement plan + +**2. Improvement Plan** (`improvement-plan-{skill-name}.md`) +- Prioritized improvement list (High/Medium/Low) +- Specific file locations and line numbers for issues +- Current vs. suggested content comparisons +- Estimated impact on scores +- Time estimates for fixes +- Expected score improvement + +## Output Templates + +### Quality Report Template + +```markdown +# Skill Quality Report: {skill-name} + +## Executive Summary +- **Overall Score**: X/100 ({Grade}) +- **Evaluated**: {Date} +- **Skill Path**: {path} + +## Dimension Scores + +### 1. Description Quality (25%) +**Score**: X/100 + +**Strengths**: +- ✅ {specific strength} + +**Weaknesses**: +- ❌ {specific weakness} + +**Recommendations**: +1. {actionable recommendation} + +[Repeat for other dimensions...] + +## Grade Breakdown +| Dimension | Score | Weight | Contribution | +|-----------|-------|--------|--------------| +| Description | X/100 | 25% | X.X | +| Organization | X/100 | 30% | X.X | +| Style | X/100 | 20% | X.X | +| Structure | X/100 | 25% | X.X | +| **Overall** | **X/100** | **100%** | **X.X ({Grade})** | + +## Next Steps +See `improvement-plan-{skill-name}.md` for detailed improvement suggestions. +``` + +### Improvement Plan Template + +```markdown +# Skill Improvement Plan: {skill-name} + +## Priority Summary +- **High Priority**: {count} items +- **Medium Priority**: {count} items +- **Low Priority**: {count} items + +## High Priority Improvements + +### 1. [Issue Title] +**File**: SKILL.md:line:line +**Dimension**: Description Quality +**Impact**: +X points + +**Current**: +```yaml +{current content} +``` + +**Suggested**: +```yaml +{suggested content} +``` + +**Reason**: {why this improves quality} + +[Continue with all issues...] + +## Quick Wins (Easy Fixes) +1. {quick fix} +2. {quick fix} + +## Estimated Time to Complete +- High Priority: X hours +- Medium Priority: X hours +- Low Priority: X hours +- **Total**: X hours + +## Expected Score Improvement +- Current: X/100 ({Grade}) +- After High Priority: X/100 ({Grade}) +- After All: X/100 ({Grade}) +``` + +## Additional Resources + +### Reference Files + +For detailed evaluation criteria and examples, consult: + +- **`references/scoring-criteria.md`** - Comprehensive scoring rubrics for each dimension +- **`references/examples-good.md`** - Exemplary skills demonstrating best practices +- **`references/examples-bad.md`** - Common anti-patterns to avoid + +### Scripts + +- **`scripts/extract-yaml.sh`** - Utility for extracting YAML frontmatter from SKILL.md +- **`scripts/skill-audit.py`** - Lightweight integrity audit for missing references, word count, and sibling-path checks + +### Related Skills + +- **`skill-development`** - Comprehensive guide for creating skills +- **`code-review-excellence`** - Best practices for code review + +## Best Practices + +### When Analyzing Skills + +1. **Be objective and specific** - Base scores on observable criteria, not opinions +2. **Provide actionable feedback** - Each recommendation should be concrete and implementable +3. **Include examples** - Show current vs. suggested content for clarity +4. **Estimate impact** - Help users understand which changes matter most +5. **Be constructive** - Frame feedback as opportunities for improvement + +### Common Quality Issues + +**Description Quality:** +- Vague or generic trigger phrases +- Second-person descriptions +- Missing concrete use cases + +**Content Organization:** +- SKILL.md too long (>5,000 words) +- Detailed content not moved to references/ +- Poor information hierarchy + +**Writing Style:** +- Second-person language ("you", "your") +- Mixed imperative and descriptive styles +- Subjective or conversational tone + +**Structural Integrity:** +- Missing required YAML fields +- Referenced files don't exist +- Incomplete examples or broken scripts + +### Grade Benchmarks + +**A grade (90-100)**: Exemplary skills serving as templates for others +- All dimensions score 85+ +- Clear, specific descriptions +- Excellent progressive disclosure +- Consistent imperative style +- Complete, well-organized structure + +**B grade (80-89)**: High-quality skills with minor improvements needed +- Most dimensions score 75+ +- Good descriptions and organization +- Generally follows best practices +- May have minor style inconsistencies + +**C grade (70-79)**: Acceptable skills requiring moderate improvements +- Key areas meet minimum standards +- Some weaknesses in organization or style +- Functional but not exemplary + +**D/F grade (below 70)**: Skills needing significant work +- Multiple dimensions below 70 +- Major structural or style issues +- Requires comprehensive revision + +## Usage Examples + +**Example 1: Analyze a local skill** +``` +User: "Analyze skill quality for ~/.claude/skills/git-workflow" + +[Claude executes the 8-step workflow and generates:] +- quality-report-git-workflow.md +- improvement-plan-git-workflow.md +``` + +**Example 2: Review before sharing** +``` +User: "Review my new skill before I publish it" + +[Claude analyzes the skill and provides:] +- Detailed quality assessment +- Specific improvement recommendations +- Expected score after implementing fixes +``` + +**Example 3: Quality check for existing skill** +``` +User: "Check skill quality of api-helper" + +[Claude evaluates and reports:] +- Current grade and score +- Top improvement opportunities +- Quick wins for easy score gains +``` + +**Example 4: Batch portfolio review** +``` +User: "Review all skills in ~/.claude/skills and tell me what to fix first" + +[Claude evaluates and reports:] +- portfolio matrix +- grouped issue clusters +- shortlist for second-pass remediation +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/batch-review-template.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/batch-review-template.md new file mode 100644 index 0000000..8c1f6ae --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/batch-review-template.md @@ -0,0 +1,14 @@ +# Batch Review Template + +## Portfolio Summary +- Skills reviewed: +- Highest-risk skills: +- Common issue clusters: + +## Priority Backlog +### P0 +- +### P1 +- +### P2 +- diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/examples-bad.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/examples-bad.md new file mode 100644 index 0000000..ba1671a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/examples-bad.md @@ -0,0 +1,555 @@ +# Common Skill Anti-Patterns + +Collection of common mistakes and anti-patterns to avoid when creating Claude Skills. Learn from these examples to improve your skills. + +## Anti-Pattern 1: Vague Description (F Grade) + +### The Problem + +```yaml +--- +name: helper-skill +description: Use this skill to help with various tasks and provide useful +assistance for users. +version: 1.0.0 +--- +``` + +**Why this fails:** +- ❌ No specific trigger phrases +- ❌ Second person ("Use this skill") +- ❌ Vague and generic +- ❌ No clue what it actually does +- ❌ Users will never discover it + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Description Quality | 0/100 | No triggers, second person, vague | +| Overall | F | Cannot even get started | + +### The Fix + +```yaml +--- +name: api-contract-manager +description: This skill should be used when the user asks to "validate API +contract", "check API compatibility", "version API schema", or "detect +breaking changes". Manages API contracts through validation, versioning, +and compatibility checking for OpenAPI 3.0 specifications. +version: 1.0.0 +--- +``` + +**Improvement:** 0/100 → 90/100 in description quality + +--- + +## Anti-Pattern 2: Second Person Throughout (D Grade) + +### The Problem + +```markdown +# My Skill + +## Overview +You should use this skill when you need to process data files. + +## How to Use +First, you need to select your input file. You can choose from CSV, +JSON, or XML formats. Then you should configure the processing options. + +## Configuration +You can set the following options: +- You must specify the output format +- You should choose a delimiter +- You need to define the schema +``` + +**Why this fails:** +- ❌ "You should", "you need", "you can" throughout +- ❌ Not imperative form +- ❌ Conversational rather than instructional +- ❌ Unprofessional tone + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Writing Style | 5/100 | Over 20 instances of "you" | +| Overall | D | Major style issue | + +### The Fix + +```markdown +# Data File Processor + +## Overview +Process data files in CSV, JSON, or XML formats with configurable +schemas and output options. + +## Usage +Select the input file. Configure processing options. Specify output +format and delimiter. + +## Configuration +Set the following options: +- Output format (required) +- Field delimiter +- Data schema +``` + +**Improvement:** 5/100 → 85/100 in writing style + +--- + +## Anti-Pattern 3: Everything in One File (C Grade) + +### The Problem + +``` +my-skill/ +└── SKILL.md (12,000 words) +``` + +**SKILL.md contains:** +- Overview +- Detailed API documentation (3,000 words) +- 20 complete code examples (5,000 words) +- Troubleshooting guide (2,000 words) +- FAQ (1,000 words) +- Changelog (1,000 words) + +**Why this is problematic:** +- ❌ SKILL.md is 12,000 words (should be <5,000) +- ❌ Detailed content always loaded +- ❌ Wastes tokens on rarely-used content +- ❌ Difficult to navigate +- ❌ Violates progressive disclosure + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Content Organization | 10/100 | No progressive disclosure | +| Overall | C | Major organizational issue | + +### The Fix + +``` +my-skill/ +├── SKILL.md (1,800 words) +├── references/ +│ ├── api-reference.md (3,000 words) +│ ├── troubleshooting.md (2,000 words) +│ └── faq.md (1,000 words) +└── examples/ + ├── basic-usage.md (1,000 words) + ├── advanced-usage.md (2,000 words) + └── edge-cases.md (2,000 words) +``` + +**SKILL.md now contains:** +- Overview +- Quick start +- Basic operations +- Links to detailed references + +**Improvement:** 10/100 → 85/100 in content organization + +--- + +## Anti-Pattern 4: Missing Required Fields (F Grade) + +### The Problem + +```yaml +--- +name: my-skill +# Missing description! +version: 1.0.0 +author: Someone +tags: [utility, helper] +--- +``` + +**Why this fails:** +- ❌ Missing required `description` field +- ❌ Skill will never trigger +- ❌ Has unnecessary fields (author, tags) +- ❌ Cannot be discovered + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Structural Integrity | 0/100 | Missing required field | +| Description Quality | 0/100 | No description to evaluate | +| Overall | F | Fundamentally broken | + +### The Fix + +```yaml +--- +name: data-validator +description: This skill should be used when the user asks to "validate data", +"check data format", "verify data schema", or "sanitize input". Validate and +sanitize data files against JSON schemas with support for custom validation +rules. +version: 1.0.0 +--- +``` + +**Improvement:** F → B- (80) overall + +--- + +## Anti-Pattern 5: Broken References (D Grade) + +### The Problem + +**SKILL.md says:** +```markdown +## Additional Resources + +See `references/api-guide.md` for complete API documentation. +Check `examples/complete-example.py` for a working example. +``` + +**Actual directory structure:** +``` +my-skill/ +├── SKILL.md +├── references/ +│ └── setup-guide.md # No api-guide.md! +└── examples/ + └── basic-example.py # No complete-example.py! +``` + +**Why this fails:** +- ❌ Referenced files don't exist +- ❌ Users get errors when trying to follow references +- ❌ Incomplete skill structure + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Structural Integrity | 15/100 | Multiple broken references | +| Overall | D | Structural issues | + +### The Fix + +Option 1: Create the referenced files +``` +my-skill/ +├── SKILL.md +├── references/ +│ ├── api-guide.md # Created! +│ └── setup-guide.md +└── examples/ + ├── complete-example.py # Created! + └── basic-example.py +``` + +Option 2: Update SKILL.md to match actual files +```markdown +## Additional Resources + +See `references/setup-guide.md` for setup instructions. +Check `examples/basic-example.py` for a working example. +``` + +**Improvement:** 15/100 → 90/100 in structural integrity + +--- + +## Anti-Pattern 6: Inconsistent Style (C Grade) + +### The Problem + +```markdown +## Workflow + +### Step 1: Prepare +First you should create the directory structure. + +### Step 2: Configure +Configure the settings file. You need to specify the endpoint. + +### Step 3: Deploy +Deploy the application. Check the logs to verify. +``` + +**Why this fails:** +- ❌ Mixes imperative ("Configure", "Deploy") with second person ("you should") +- ❌ Inconsistent throughout +- ❌ Confusing to read + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Writing Style | 30/100 | Inconsistent style | +| Overall | C | Style issues | + +### The Fix + +```markdown +## Workflow + +### Step 1: Prepare +Create the directory structure. + +### Step 2: Configure +Specify the endpoint in the settings file. + +### Step 3: Deploy +Deploy the application. Verify by checking the logs. +``` + +**Improvement:** 30/100 → 85/100 in writing style + +--- + +## Anti-Pattern 7: Overly Long Description (B Grade) + +### The Problem + +```yaml +--- +name: file-processor +description: This skill should be used when the user asks to "process files", +"convert file formats", "validate file structure", "check file integrity", +"transform file data", "merge multiple files", "split large files", "compress +file size", "encrypt file contents", "decrypt file contents", "archive files", +"extract archives", "generate file checksums", "verify file signatures", or +"optimize file storage". This comprehensive file processing utility supports +over 50 different file formats including PDF, DOCX, XLSX, CSV, JSON, XML, +HTML, TXT, and many more. It provides advanced features like batch processing, +parallel execution, error recovery, automatic backup creation, detailed logging, +progress tracking, and notification support. Ideal for data migration tasks, +content management workflows, archival operations, and file system maintenance. +version: 1.0.0 +--- +``` + +**Why this is problematic:** +- ❌ 900+ characters (way too long) +- ❌ Lists too many trigger phrases (dilutes effectiveness) +- ❌ Becomes unreadable +- ❌ Loses focus + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Description Quality | 15/100 | Too long, unfocused | +| Overall | B | Description issue | + +### The Fix + +```yaml +--- +name: file-processor +description: This skill should be used when the user asks to "process files", +"convert file formats", "validate file structure", "merge files", or +"compress files". Supports common formats (PDF, DOCX, CSV, JSON) with +batch processing and error recovery. +version: 1.0.0 +--- +``` + +**Improvement:** 15/100 → 85/100 in description quality + +--- + +## Anti-Pattern 8: No Examples (C Grade) + +### The Problem + +``` +my-skill/ +├── SKILL.md (2,000 words of theory) +└── references/ + └── detailed-guide.md (3,000 words more theory) +``` + +**SKILL.md describes concepts but never shows:** +- How to actually use the skill +- What input looks like +- What output looks like +- Concrete usage patterns + +**Why this fails:** +- ❌ Users can't visualize usage +- ❌ No working code to copy +- ❌ Theory without practice + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Structural Integrity | 50/100 | No examples despite theory | +| Overall | C | Missing practical component | + +### The Fix + +``` +my-skill/ +├── SKILL.md (2,000 words) +├── references/ +│ └── detailed-guide.md +└── examples/ + ├── basic-usage.sh (working example) + ├── advanced-usage.sh (working example) + └── input-output-examples.md (before/after) +``` + +**Improvement:** 50/100 → 85/100 in structural integrity + +--- + +## Anti-Pattern 9: Subjective Language (D Grade) + +### The Problem + +```markdown +## Overview + +This is a really great skill that I think you'll find super useful. +It's awesome for handling difficult tasks. The best part is how +easy it is to use - you'll love it! + +## Features + +- Amazing performance +- Incredible flexibility +- Fantastic user experience +``` + +**Why this fails:** +- ❌ Highly subjective ("really great", "super useful") +- ❌ Marketing language, not instructional +- ❌ First person ("I think") +- ❌ Unprofessional tone +- ❌ No concrete information + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Writing Style | 20/100 | Subjective, unprofessional | +| Overall | D | Style issues | + +### The Fix + +```markdown +## Overview + +Handle complex data processing tasks with configurable validation +and error recovery. Supports CSV, JSON, and XML formats with +batch processing capabilities. + +## Features + +- Processes 10,000+ records per second +- Configurable validation rules +- Automatic error recovery +- Detailed logging +``` + +**Improvement:** 20/100 → 80/100 in writing style + +--- + +## Anti-Pattern 10: Invalid YAML (F Grade) + +### The Problem + +```yaml +--- +name: my-skill +description: This skill should be used when the user asks to "validate data" +or "check schemas". It's designed for: data validation, schema checking, and +format verification. +version: 1.0.0 +--- +``` + +**Error:** Colon after "for" creates invalid YAML syntax + +**Why this fails:** +- ❌ YAML cannot be parsed +- ❌ Skill fails to load +- ❌ Completely non-functional + +### Score Impact + +| Dimension | Score | Why | +|-----------|-------|-----| +| Structural Integrity | 0/100 | Invalid YAML | +| Overall | F | Cannot load | + +### The Fix + +```yaml +--- +name: data-validator +description: This skill should be used when the user asks to "validate data", +"check schemas", or "verify formats". Performs data validation, schema +checking, and format verification. +version: 1.0.0 +--- +``` + +**Improvement:** F → B (83) overall + +--- + +## Quick Anti-Pattern Checklist + +### Description Quality +- [ ] Not vague like "helps with tasks" +- [ ] Has 3-5 specific trigger phrases +- [ ] Uses third person, not second person +- [ ] Is 100-300 characters long +- [ ] Mentions concrete use cases + +### Content Organization +- [ ] SKILL.md under 5,000 words +- [ ] Detailed content in references/ +- [ ] Examples in examples/ directory +- [ ] Progressive disclosure followed + +### Writing Style +- [ ] No "you", "your", "you're" in body +- [ ] Uses imperative verbs (Create, Check, Run) +- [ ] Objective and factual +- [ ] No marketing language + +### Structural Integrity +- [ ] YAML has name and description +- [ ] All referenced files exist +- [ ] Examples are complete +- [ ] Scripts are executable + +--- + +## Learn From Mistakes + +Each anti-pattern above represents real issues found in actual skills. Avoid these common mistakes: + +1. **Vague descriptions** → Be specific with trigger phrases +2. **Second person** → Use imperative form +3. **No progressive disclosure** → Move details to references/ +4. **Missing fields** → Include name and description +5. **Broken references** → Verify all files exist +6. **Inconsistent style** → Stick to imperative form +7. **Too long description** → Keep under 300 characters +8. **No examples** → Include working code +9. **Subjective language** → Be factual and objective +10. **Invalid YAML** → Validate YAML syntax + +Use `examples-good.md` as a reference for what to do right. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/examples-good.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/examples-good.md new file mode 100644 index 0000000..ed82f28 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/examples-good.md @@ -0,0 +1,385 @@ +# Exemplary Skill Examples + +Collection of high-quality skill examples demonstrating best practices across all quality dimensions. Study these when creating or improving skills. + +## Example 1: hook-development (A+ Grade) + +An exemplary skill demonstrating excellent description quality, progressive disclosure, and writing style. + +### Frontmatter (Description Quality) + +```yaml +--- +name: hook-development +description: This skill should be used when the user asks to "create a hook", +"add a PreToolUse hook", "validate tool use", "implement prompt-based hooks", +"use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous +commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, +SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides +comprehensive guidance for creating and implementing Claude Code plugin hooks +with focus on advanced prompt-based hooks API. +version: 0.1.0 +--- +``` + +**Why this is excellent:** +- ✅ 8+ specific trigger phrases covering diverse scenarios +- ✅ Third-person format throughout +- ✅ Includes specific hook events for precision +- ✅ Mentions key concepts (prompt-based hooks API) +- ✅ Length is appropriate (~400 characters, acceptable for complex skill) + +### Progressive Disclosure (Content Organization) + +**SKILL.md structure:** +- Overview (50 words) +- Core concepts (200 words) +- Hook events reference (300 words) +- Development workflow (500 words) +- Best practices (400 words) +- **Total: ~1,650 words** - excellent length + +**References/ directory:** +``` +references/ +├── prompt-based-hooks.md (800 words) - Detailed guide +├── hook-patterns.md (1,200 words) - Common patterns +└── migration-guide.md (900 words) - Migration info +``` + +**Why this is excellent:** +- ✅ SKILL.md is concise and focused +- ✅ Detailed content moved to 3 reference files +- ✅ Clear progressive disclosure +- ✅ Each reference file has specific purpose + +### Writing Style (Imperative Form) + +**Example from SKILL.md:** +```markdown +## Hook Development Workflow + +### Step 1: Define the Hook Event +Identify which event the hook should trigger on. Review available events +in the Hook Events Reference section. + +### Step 2: Create hooks.json +Create a hooks.json file in the plugin's .claude-plugin/ directory. +Specify the event type and command to execute. + +### Step 3: Implement the Hook Script +Write the hook script. Ensure it is executable. Follow the prompt-based +hooks API for complex hooks. + +### Step 4: Test the Hook +Test the hook locally. Verify it triggers on the correct event. +Check output and error handling. +``` + +**Why this is excellent:** +- ✅ Every instruction uses imperative form +- ✅ No "you", "your", "should" +- ✅ Clear, actionable steps +- ✅ Consistent style throughout + +--- + +## Example 2: agent-development (A Grade) + +Strong skill with good description and organization. + +### Frontmatter + +```yaml +--- +name: agent-development +description: This skill should be used when the user asks to "create an agent", +"add an agent", "write a subagent", "agent frontmatter", "when to use description", +"agent examples", "agent tools", "agent colors", "autonomous agent", or needs +guidance on agent structure, system prompts, triggering conditions, or agent +development best practices for Claude Code plugins. +version: 0.1.0 +--- +``` + +**Strengths:** +- ✅ Multiple specific trigger phrases +- ✅ Covers agent creation scenarios +- ✅ Mentions specific agent attributes + +### Directory Structure + +``` +agent-development/ +├── SKILL.md (1,438 words) +├── references/ +│ ├── agent-generation-prompt.md (500 words) +│ └── agent-anatomy.md (400 words) +└── examples/ + ├── task-agent.md (complete example) + ├── review-agent.md (complete example) + └── interactive-agent.md (complete example) +``` + +**Strengths:** +- ✅ Lean SKILL.md +- ✅ Focused reference files +- ✅ Complete working examples +- ✅ Clear organization + +--- + +## Example 3: mcp-integration (A- Grade) + +Comprehensive skill with excellent progressive disclosure. + +### Frontmatter + +```yaml +--- +name: mcp-integration +description: This skill should be used when the user asks to "add MCP server", +"integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model +Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} +with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides +comprehensive guidance for integrating Model Context Protocol servers into Claude +Code plugins for external tool and service integration. +version: 0.1.0 +--- +``` + +**Strengths:** +- ✅ Specific MCP-related trigger phrases +- ✅ Lists server types for precision +- ✅ Mentions key configuration elements + +### Progressive Disclosure + +**SKILL.md**: ~1,800 words (core concepts, basic setup) + +**References/**: +- `mcp-server-types.md` - Detailed server type comparisons +- `mcp-configuration.md` - Configuration examples +- `mcp-best-practices.md` - Integration patterns +- `mcp-troubleshooting.md` - Common issues + +**Why this works:** +- ✅ Main SKILL.md covers essentials +- ✅ Each reference is 1,000-2,000 words +- ✅ Loaded only when needed +- ✅ Clear topic separation + +--- + +## Excellent Description Examples + +### Example: API-Contract Skill (Ideal Description) + +```yaml +--- +name: api-contract-manager +description: This skill should be used when the user asks to "validate API contract", +"check API compatibility", "version API schema", "detect breaking changes", or +"ensure API contract compliance". Manages API contracts through validation, +versioning, and compatibility checking. Use when designing new endpoints or +ensuring backward compatibility. +version: 0.1.0 +--- +``` + +**Analysis:** +- ✅ 5 specific trigger phrases +- ✅ Third person throughout +- ✅ 230 characters (ideal length) +- ✅ Clear use cases +- ✅ Mentions when to use (designing, compatibility) + +### Example: PDF-Editor Skill (Ideal Description) + +```yaml +--- +name: pdf-editor +description: This skill should be used when the user asks to "rotate PDF", "merge +PDF files", "split PDF pages", "compress PDF", or "crop PDF pages". Perform common +PDF manipulation operations including rotation, merging, splitting, compression, +and cropping. Works with local PDF files. +version: 0.1.0 +--- +``` + +**Analysis:** +- ✅ 5 specific operations as triggers +- ✅ Lists all supported operations +- ✅ Specifies working context (local files) +- ✅ 180 characters (excellent length) + +--- + +## Excellent Progressive Disclosure Examples + +### Example: Frontend-Builder Skill + +**SKILL.md** (1,800 words): +- Overview +- Quick Start (5 steps) +- Basic Component Creation +- Common Operations +- Reference to detailed guides + +**References/**: +- `react-patterns.md` (2,500 words) - React specific patterns +- `vue-patterns.md` (2,000 words) - Vue specific patterns +- `styling-guide.md` (1,800 words) - CSS/styling approaches +- `deployment.md` (1,500 words) - Build and deploy + +**Examples/**: +- `hello-world-react/` - Complete React example +- `hello-world-vue/` - Complete Vue example +- `component-library/` - Reusable components + +**Why this works:** +1. SKILL.md gets users started quickly +2. Framework-specific details in references/ +3. Complete examples for copy-paste +4. Progressive: overview → basics → details → examples + +--- + +## Excellent Writing Style Examples + +### Example: From Test-Driven Development Skill + +```markdown +## TDD Workflow + +### Red: Write a Failing Test +Start by writing a test that fails. This test defines the desired behavior. +Run the test to confirm it fails. + +### Green: Make the Test Pass +Write the minimum code to make the test pass. Focus on making it work, +not making it perfect. Run the test to confirm it passes. + +### Refactor: Improve the Code +Refactor the code while keeping tests green. Improve structure, readability, +and maintainability. Run tests after each change. + +### Repeat +Continue the cycle for each feature. Write test, make it pass, refactor. +``` + +**Analysis:** +- ✅ Imperative form throughout +- ✅ Clear, actionable instructions +- ✅ No second person +- ✅ Consistent style +- ✅ Easy to follow + +--- + +## Excellent Reference File Organization + +### Example: Git-Workflow Skill References + +``` +references/ +├── commit-conventions.md (1,500 words) +│ ├── Commit message format +│ ├── Type categories +│ ├── Scope values +│ └── Examples by type +├── branch-strategy.md (1,800 words) +│ ├── Branch types +│ ├── Merging policies +│ ├── Release workflow +│ └── Hotfix procedures +└── troubleshooting.md (1,200 words) + ├── Common issues + ├── Recovery procedures + └── Best practices +``` + +**Each reference file:** +- ✅ Focused on single topic +- ✅ Self-contained +- ✅ Cross-references others when needed +- ✅ Loaded only when relevant + +--- + +## Key Takeaways from Excellent Skills + +### 1. Description Quality + +**Good descriptions:** +- Have 5+ specific trigger phrases +- Use third person consistently +- Are 100-300 characters long +- Include concrete use cases + +**Example template:** +```yaml +description: This skill should be used when the user asks to "action 1", +"action 2", "action 3", or "action 4". Brief description of what the skill +does. When to use it. +``` + +### 2. Progressive Disclosure + +**Good organization:** +- SKILL.md: 1,500-2,000 words (core only) +- references/: 1,500-2,500 words per file (details) +- examples/: Complete working code +- scripts/: Utility tools + +**Rule of thumb:** If a section exceeds 500 words and covers details, +consider moving it to references/. + +### 3. Writing Style + +**Good style:** +- Use imperative verbs: Create, Validate, Check, Run +- Avoid: You should, You can, You need to +- Be objective and factual +- Keep instructions actionable + +### 4. Structural Integrity + +**Good structure:** +``` +skill-name/ +├── SKILL.md (required) +├── references/ (optional, for details) +├── examples/ (optional, for working code) +└── scripts/ (optional, for utilities) +``` + +**Validation checklist:** +- [ ] YAML frontmatter has name and description +- [ ] All referenced files exist +- [ ] Examples are complete +- [ ] Scripts are executable + +--- + +## Study These Skills + +For hands-on learning, study these high-quality skills in your environment: + +```bash +# Explore hook-development structure +ls -la ~/.claude/plugins/cache/*/skills/hook-development/ + +# Read agent-development SKILL.md +cat ~/.claude/skills/agent-development/SKILL.md + +# Review mcp-integration references +ls -la ~/.claude/skills/mcp-integration/references/ +``` + +Each demonstrates different strengths: +- **hook-development**: Progressive disclosure, utilities +- **agent-development**: Clean examples, focused content +- **mcp-integration**: Comprehensive references, clear organization + +Use these as templates when creating or improving your own skills. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/scoring-criteria.md b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/scoring-criteria.md new file mode 100644 index 0000000..621b18a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/references/scoring-criteria.md @@ -0,0 +1,569 @@ +# Skill Quality Scoring Criteria + +Detailed evaluation rubrics for each quality dimension assessed by the skill-quality-reviewer. + +## 1. Description Quality (25% Weight) + +Assesses the effectiveness of the frontmatter description in triggering the skill appropriately. + +### Scoring Breakdown + +#### Trigger Phrases Clarity (0-25 points) + +**25 points (Excellent):** +- 5+ specific, concrete trigger phrases +- Phrases cover diverse use cases +- Each phrase is something a user would naturally say +- Phrases include both specific tasks and general scenarios + +**Example:** +```yaml +description: This skill should be used when the user asks to "create a hook", +"add a PreToolUse hook", "validate tool use", "implement prompt-based hooks", +"set up event-driven automation", or mentions hook events (PreToolUse, PostToolUse, +Stop, SubagentStop). +``` + +**20 points (Good):** +- 3-4 specific trigger phrases +- Good variety of scenarios +- Most phrases are natural user language + +**15 points (Acceptable):** +- 2-3 trigger phrases +- Some variety but may miss key scenarios +- Phrases are reasonably specific + +**10 points (Needs Work):** +- 1-2 trigger phrases +- Limited variety +- Some phrases too generic + +**5 points (Poor):** +- Single vague trigger phrase +- Missing common use cases + +**0 points (Fail):** +- No trigger phrases +- Trigger phrases are meaningless + +--- + +#### Third-Person Format (0-25 points) + +**25 points (Excellent):** +- Consistently uses "This skill should be used when..." +- Never uses second person ("you", "your") +- Professional, objective tone + +**20 points (Good):** +- Generally uses third person +- Minor inconsistencies but overall correct + +**10 points (Needs Work):** +- Mix of third and second person +- Inconsistent formatting + +**0 points (Fail):** +- Uses second person ("Use this when you want...") +- First person references + +--- + +#### Description Length (0-25 points) + +**25 points (Excellent):** +- 150-300 characters +- Concise yet comprehensive +- No unnecessary words + +**20 points (Good):** +- 100-150 or 300-400 characters +- Slightly short or long but acceptable + +**15 points (Acceptable):** +- 80-100 or 400-500 characters +- Beginning to be too concise or verbose + +**10 points (Needs Work):** +- 50-80 or 500-700 characters +- Too brief or too verbose + +**5 points (Poor):** +- Under 50 or over 700 characters + +**0 points (Fail):** +- Effectively empty or extremely long + +--- + +#### Specific Scenarios (0-25 points) + +**25 points (Excellent):** +- Multiple concrete scenarios mentioned +- Clear scope boundaries (when NOT to use) +- Specific domains or use cases identified + +**Example:** +```yaml +description: ... Use when designing new API endpoints, validating existing +contracts, or checking breaking changes. NOT for general API testing or +documentation generation. +``` + +**20 points (Good):** +- Good scenario coverage +- Clear use cases + +**15 points (Acceptable):** +- Basic scenario descriptions +- Could be more specific + +**10 points (Needs Work):** +- Vague scenarios +- Unclear when to use + +**0 points (Fail):** +- No scenarios mentioned +- Purely generic description + +--- + +## 2. Content Organization (30% Weight) + +Evaluates adherence to progressive disclosure principles and effective content organization. + +### Scoring Breakdown + +#### Progressive Disclosure (0-30 points) + +**30 points (Excellent):** +- SKILL.md under 2,000 words +- All detailed content in references/ +- Clear separation of overview and details +- References/ properly organized with multiple files + +**25 points (Good):** +- SKILL.md 2,000-3,000 words +- Most detailed content moved to references/ +- Good separation of concerns + +**20 points (Acceptable):** +- SKILL.md 3,000-5,000 words +- Some detailed content still in SKILL.md +- References/ used but could be better + +**15 points (Needs Work):** +- SKILL.md 5,000-7,000 words +- Significant content should be moved +- Limited use of references/ + +**10 points (Poor):** +- SKILL.md over 7,000 words +- Minimal or no references/ usage + +**0 points (Fail):** +- Everything in one large file +- No progressive disclosure + +--- + +#### SKILL.md Length Control (0-25 points) + +**25 points (Excellent):** +- 1,500-2,000 words (optimal) +- Every word serves a purpose +- No redundancy + +**20 points (Good):** +- 1,000-1,500 or 2,000-3,000 words +- Generally concise + +**15 points (Acceptable):** +- 800-1,000 or 3,000-4,000 words +- Some unnecessary content + +**10 points (Needs Work):** +- 500-800 or 4,000-5,000 words +- Could be significantly trimmed + +**5 points (Poor):** +- Under 500 or over 5,000 words +- Major length issues + +--- + +#### References/ Usage (0-25 points) + +**25 points (Excellent):** +- 3+ well-organized reference files +- Clear topics (patterns, advanced, examples, etc.) +- Properly referenced in SKILL.md +- Each file has clear purpose + +**20 points (Good):** +- 2-3 reference files +- Good organization +- Referenced in SKILL.md + +**15 points (Acceptable):** +- 1-2 reference files +- Basic organization + +**10 points (Needs Work):** +- Single reference file or poorly organized +- Not well referenced + +**5 points (Poor):** +- References/ exists but minimal content +- Not referenced from SKILL.md + +**0 points (Fail):** +- No references/ directory when clearly needed + +--- + +#### Logical Organization (0-20 points) + +**20 points (Excellent):** +- Clear section hierarchy +- Logical flow from overview to details +- Easy to navigate +- Consistent structure + +**15 points (Good):** +- Generally well organized +- Minor flow issues + +**10 points (Acceptable):** +- Basic organization present +- Some structural confusion + +**5 points (Needs Work):** +- Poor organization +- Difficult to follow + +**0 points (Fail):** +- No clear structure +- Content randomly arranged + +--- + +## 3. Writing Style (20% Weight) + +Evaluates adherence to skill writing conventions and style consistency. + +### Scoring Breakdown + +#### Imperative Form Usage (0-40 points) + +**40 points (Excellent):** +- 95%+ of instructions use imperative form +- Consistent throughout +- Natural, readable instructions + +**Good examples:** +``` +Create the skill directory structure. +Validate the YAML frontmatter. +Check for required fields. +Read the SKILL.md file. +Generate the quality report. +``` + +**30 points (Good):** +- 80-95% imperative form +- Generally consistent +- Minor exceptions + +**20 points (Acceptable):** +- 60-80% imperative form +- Inconsistent usage + +**10 points (Needs Work):** +- 40-60% imperative form +- Significant inconsistency + +**0 points (Fail):** +- Less than 40% imperative form +- Mostly descriptive or second-person + +--- + +#### No Second Person (0-30 points) + +**30 points (Excellent):** +- Zero instances of "you", "your", "you're" +- Clean imperative style throughout + +**20 points (Good):** +- 1-3 minor instances +- Generally avoids second person + +**10 points (Acceptable):** +- 4-6 instances +- Some second person creeping in + +**5 points (Needs Work):** +- 7-10 instances +- Frequent second person + +**0 points (Fail):** +- 10+ instances +- Heavily uses second person + +--- + +#### Objective Language (0-30 points) + +**30 points (Excellent):** +- Factual, instructional tone +- No subjective opinions +- Professional language +- Clear and direct + +**20 points (Good):** +- Generally objective +- Minor subjectivity + +**15 points (Acceptable):** +- Mostly objective with some opinion +- Generally professional + +**10 points (Needs Work):** +- Subjective language present +- Conversational tone + +**0 points (Fail):** +- Highly subjective +- Unprofessional or casual tone + +--- + +## 4. Structural Integrity (25% Weight) + +Evaluates the physical structure, completeness, and correctness of the skill. + +### Scoring Breakdown + +#### YAML Frontmatter (0-30 points) + +**30 points (Excellent):** +- All required fields present (name, description) +- Optional fields used appropriately (version) +- Valid YAML syntax +- No prohibited fields +- Well-formatted + +**Example of excellent frontmatter:** +```yaml +--- +name: skill-quality-reviewer +description: This skill should be used when the user asks to "analyze skill quality", +"evaluate this skill", "review skill quality", or mentions quality review of Claude Skills. +version: 0.1.0 +--- +``` + +**25 points (Good):** +- All required fields present +- Valid YAML +- Minor formatting issues + +**20 points (Acceptable):** +- Required fields present +- Valid YAML +- Some missing recommended fields + +**10 points (Needs Work):** +- Missing some required fields +- YAML issues present + +**0 points (Fail):** +- Missing required fields +- Invalid YAML syntax +- Cannot parse frontmatter + +--- + +#### Directory Structure (0-30 points) + +**30 points (Excellent):** +- Proper skill structure: + ``` + skill-name/ + ├── SKILL.md + ├── references/ + ├── examples/ + └── scripts/ + ``` +- Each subdirectory has clear purpose +- No unnecessary files +- Clean naming conventions + +**25 points (Good):** +- Core structure correct +- Minor organization issues + +**20 points (Acceptable):** +- Basic structure present +- Some organizational issues + +**10 points (Needs Work):** +- Missing key directories +- Poor organization + +**0 points (Fail):** +- No clear structure +- Chaotic organization + +--- + +#### Resource References (0-40 points) + +**40 points (Excellent):** +- All referenced files exist +- References are accurate and specific +- Examples are complete and working +- Scripts are executable +- No broken links or references + +**Check method:** +- Read SKILL.md +- Extract all references to files (e.g., `references/patterns.md`) +- Verify each file exists +- Verify examples/ and scripts/ contents + +**30 points (Good):** +- All references exist +- Minor issues with completeness + +**20 points (Acceptable):** +- Most references valid +- Some broken or incomplete references + +**10 points (Needs Work):** +- Multiple broken references +- Incomplete examples + +**0 points (Fail):** +- Many broken references +- Examples don't work +- Scripts not executable + +--- + +## Grade Calculation + +### Weighted Score Formula + +``` +Overall Score = (Description Quality × 0.25) + + (Content Organization × 0.30) + + (Writing Style × 0.20) + + (Structural Integrity × 0.25) +``` + +### Letter Grade Mapping + +| Score Range | Grade | Quality Level | Certification | +|-------------|-------|---------------|--------------| +| 97-100 | A+ | Exemplary | Certified | +| 93-96 | A | Excellent | Certified | +| 90-92 | A- | Very Good | Certified | +| 87-89 | B+ | Good | Certified | +| 83-86 | B | Above Average | Certified | +| 80-82 | B- | Solid | Certified | +| 77-79 | C+ | Acceptable | Review | +| 73-76 | C | Satisfactory | Review | +| 70-72 | C- | Minimal | Review | +| 67-69 | D+ | Below Standard | Reject | +| 63-66 | D | Poor | Reject | +| 60-62 | D- | Very Poor | Reject | +| 0-59 | F | Fail | Reject | + +### Certification Thresholds + +For "Certified" status (recommended for sharing): +- Overall score: ≥80/100 +- Description Quality: ≥75/100 +- Content Organization: ≥75/100 +- Writing Style: ≥70/100 +- Structural Integrity: ≥80/100 + +--- + +## Quick Reference Scoring Guide + +### Description Quality Quick Checks + +- [ ] Description has 3-5 specific trigger phrases +- [ ] Uses third person ("This skill should be used when...") +- [ ] Length is 100-300 characters +- [ ] Mentions concrete use cases + +### Content Organization Quick Checks + +- [ ] SKILL.md under 5,000 words (ideally 1,500-2,000) +- [ ] Detailed content in references/ +- [ ] Examples in examples/ directory +- [ ] Scripts in scripts/ directory + +### Writing Style Quick Checks + +- [ ] Instructions use verbs (Create, Validate, Check) +- [ ] No "you", "your", "you're" in body +- [ ] Objective, instructional tone +- [ ] Consistent style throughout + +### Structural Integrity Quick Checks + +- [ ] YAML has name and description +- [ ] All referenced files exist +- [ ] Examples are complete +- [ ] Scripts are executable + +--- + +## Common Scenarios + +### Scenario 1: New Skill Submission + +**Context:** Developer submits a new skill for review. + +**Evaluation Focus:** +- Description quality (is it clear when to use?) +- Progressive disclosure (is content organized?) +- Writing style (does it follow conventions?) + +**Passing Criteria:** B- (80) or higher overall + +--- + +### Scenario 2: Skill Quality Audit + +**Context:** Periodic review of existing skills. + +**Evaluation Focus:** +- All dimensions equally +- Identify improvement opportunities +- Track quality over time + +**Passing Criteria:** C (73) or higher overall + +--- + +### Scenario 3: Pre-Publication Check + +**Context:** Final check before sharing skill publicly. + +**Evaluation Focus:** +- Structural integrity (must be complete) +- Description quality (must be discoverable) +- No critical issues + +**Passing Criteria:** B (83) or higher overall + +--- + +This scoring criteria document provides the detailed rubrics used by skill-quality-reviewer to evaluate Claude Skills. Use this as a reference when interpreting quality reports or planning improvements. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/scripts/extract-yaml.sh b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/scripts/extract-yaml.sh new file mode 100755 index 0000000..55f81a6 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/scripts/extract-yaml.sh @@ -0,0 +1,28 @@ +#!/bin/bash +# extract-yaml.sh - Extract YAML frontmatter from SKILL.md files +# Part of skill-quality-reviewer + +# Usage: ./extract-yaml.sh <path-to-skill> +# Example: ./extract-yaml.sh ~/.claude/skills/git-workflow + +set -euo pipefail + +# Check if path provided +if [ $# -eq 0 ]; then + echo "Usage: $0 <path-to-skill>" + echo "Example: $0 ~/.claude/skills/git-workflow" + exit 1 +fi + +SKILL_PATH="$1" +SKILL_FILE="${SKILL_PATH}/SKILL.md" + +# Check if SKILL.md exists +if [ ! -f "$SKILL_FILE" ]; then + echo "Error: SKILL.md not found at ${SKILL_FILE}" + exit 1 +fi + +# Extract YAML frontmatter (between --- lines) +# Using sed to extract content between first and second --- +sed -n '/^---$/,/^---$/{ /^---$/d; p; }' "$SKILL_FILE" diff --git a/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/scripts/skill-audit.py b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/scripts/skill-audit.py new file mode 100755 index 0000000..8f047c3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/skill-quality-reviewer/scripts/skill-audit.py @@ -0,0 +1,39 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import re +from pathlib import Path + +REF_RE = re.compile(r'(references/[^\s)`]+|examples/[^\s)`]+|scripts/[^\s)`]+|assets/[^\s)`]+)') + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description='Audit a skill for missing local references and rough size metrics.') + parser.add_argument('skill_path', help='Path to the skill directory') + return parser.parse_args() + + +def main() -> int: + args = parse_args() + root = Path(args.skill_path).expanduser().resolve() + skill_md = root / 'SKILL.md' + if not skill_md.exists(): + print('missing SKILL.md') + return 1 + text = skill_md.read_text(encoding='utf-8') + words = len(re.findall(r'\w+', text)) + print(f'word_count={words}') + refs = sorted(set(match.rstrip('*:.,') for match in REF_RE.findall(text))) + missing = [ref for ref in refs if not (root / ref).exists()] + if missing: + print('missing_refs=') + for ref in missing: + print(f'- {ref}') + else: + print('missing_refs=0') + return 0 + + +if __name__ == '__main__': + raise SystemExit(main()) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/SKILL.md new file mode 100644 index 0000000..e85652f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/SKILL.md @@ -0,0 +1,136 @@ +--- +name: ui-ux-pro-max +description: This skill should be used when the user asks to design or review a UI, create a landing page or dashboard, choose colors or typography, improve accessibility, or implement polished frontend interfaces with a clear design system. +version: 0.2.0 +--- + +# UI/UX Pro Max + +Use this skill to turn a vague UI request into a **concrete design system plus implementation guidance**. + +## Role + +This skill is for: +- design-system selection, +- palette and typography choices, +- UX review and remediation, +- stack-aware frontend implementation guidance, +- lightweight design-system persistence for multi-page work. + +It is **not** a replacement for product strategy or user research. Use it to make execution sharper after the product direction is already roughly known. + +## Core workflow + +### 1. Infer the request shape + +Extract the minimum design signals first: +- product type, +- industry, +- style keywords, +- target platform, +- implementation stack. + +If the user does not specify a stack, default to `html-tailwind`. + +### 2. Generate the design system first + +Use the helper script to produce a compact design recommendation: + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "<product_type> <industry> <keywords>" --design-system -p "Project Name" +``` + +This produces: +- recommended style direction, +- palette family, +- typography direction, +- interaction / visual effects, +- landing or layout bias, +- anti-patterns to avoid. + +If the work spans multiple turns or pages, persist the design system: + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "<query>" --design-system --persist -p "Project Name" +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "<query>" --design-system --persist -p "Project Name" --page "dashboard" +``` + +This creates: +- `design-system/MASTER.md` +- optional page-level override notes under `design-system/pages/` + +### 3. Pull targeted guidance only when needed + +Use a focused search instead of loading everything at once: + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "glassmorphism dark" --domain style +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "animation accessibility" --domain ux +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "real-time dashboard" --domain chart +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "elegant luxury serif" --domain typography +``` + +Supported domains: +- `product` +- `style` +- `color` +- `typography` +- `landing` +- `chart` +- `ux` + +### 4. Add stack-specific guidance before coding + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/ui-ux-pro-max/scripts/search.py" "forms table responsive" --stack html-tailwind +``` + +Supported stacks: +- `html-tailwind` +- `react` +- `nextjs` +- `vue` +- `svelte` +- `swiftui` +- `react-native` +- `flutter` +- `shadcn` +- `jetpack-compose` + +### 5. Synthesize before implementation + +After gathering the design system, convert it into: +- layout structure, +- component rules, +- visual tokens, +- interaction rules, +- accessibility constraints, +- implementation notes for the chosen stack. + +Do not dump raw search output into the final answer. Use it to justify a coherent design direction. + +## Default output shape + +A good response should usually include: +1. product and UI framing, +2. recommended style system, +3. palette and typography, +4. component and layout rules, +5. accessibility and interaction checks, +6. stack-aware implementation notes. + +## Safety rules + +- Do not hardcode a design language without connecting it to the product type. +- Do not use emoji as primary UI iconography. +- Do not weaken text contrast for visual flair. +- Do not scale interactive cards on hover if it destabilizes layout. +- Do not use animation that violates `prefers-reduced-motion`. +- Do not invent unsupported helper scripts or datasets; use the bundled `search.py` and `data/ui-reasoning.csv` only. + +## References + +Load only what is needed: +- `references/USAGE.md` - recommended command patterns and retrieval flow +- `data/ui-reasoning.csv` - compact product-to-design heuristics used by the helper script +- `scripts/search.py` - deterministic helper for design-system, domain, and stack lookup diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/data/ui-reasoning.csv b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/data/ui-reasoning.csv new file mode 100644 index 0000000..b6c7491 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/data/ui-reasoning.csv @@ -0,0 +1,9 @@ +slug,keywords,style,palette,typography,effects,landing_pattern,anti_patterns,notes +saas,"saas,software,productivity,b2b,platform",minimal-modern,slate-indigo,Inter + Space Grotesk,subtle shadows and crisp borders,hero + product proof,"low-contrast cards; decorative gradients that hide hierarchy",Optimize for clarity and scanability. +fintech,"fintech,finance,banking,crypto,trading",trust-dark,navy-cyan,Inter + IBM Plex Sans,controlled glow with high contrast,hero + trust signals + metrics,"playful colors; weak contrast; noisy motion",Signal rigor and reliability. +healthcare,"healthcare,medical,clinic,patient,biotech",clean-reassuring,teal-blue,Inter + Source Serif 4,soft surfaces and calm whitespace,problem -> trust -> workflow,"alarm-red emphasis everywhere; crowded dashboards",Reduce anxiety and keep forms obvious. +beauty,"beauty,spa,wellness,skincare,salon",elegant-soft,rose-stone,DM Sans + Cormorant Garamond,soft blur and restrained glass,hero + treatments + testimonials,"harsh black blocks; neon accents; cluttered cards",Favor softness and premium restraint. +ecommerce,"ecommerce,shop,store,retail,marketplace",conversion-clean,neutral-emerald,Inter + Manrope,clear elevation and strong CTA contrast,hero + product grid + reviews,"weak CTA hierarchy; oversized paragraphs",Prioritize trust and frictionless checkout. +education,"education,learning,course,student,training",friendly-structured,blue-amber,Inter + Nunito,bright accents with clear cards,hero + curriculum + outcomes,"too much gamification; low information density",Balance warmth with instructional structure. +portfolio,"portfolio,agency,studio,creator,personal",editorial-bold,charcoal-lime,Space Grotesk + Inter,bold type with restrained motion,hero + selected work + proof,"generic SaaS blocks; too many accent colors",Let typography carry distinction. +dashboard,"dashboard,analytics,monitoring,admin,ops",data-dense,slate-cobalt,Inter + JetBrains Mono,compact panels and precise separators,summary row + filters + charts,"3D charts; crowded legends; uneven spacing",Optimize for comparison and rapid scanning. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/references/USAGE.md b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/references/USAGE.md new file mode 100644 index 0000000..85683be --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/references/USAGE.md @@ -0,0 +1,21 @@ +# UI/UX Pro Max Usage + +## Recommended sequence + +1. Run `--design-system` first. +2. Run one or two focused `--domain` queries only if the first pass leaves gaps. +3. Run `--stack` before writing code. +4. Persist the design system only if the project will span multiple pages or multiple turns. + +## Good queries + +- `fintech analytics dashboard trust serious` +- `beauty spa wellness service elegant` +- `developer tool docs clean minimal dark` +- `education mobile app playful structured` + +## Persisted design system rule + +- `design-system/MASTER.md` is the default authority. +- `design-system/pages/<page>.md` overrides the master only for that page. +- Page files should record only deviations, not duplicate the whole master note. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/scripts/search.py b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/scripts/search.py new file mode 100755 index 0000000..f840315 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/ui-ux-pro-max/scripts/search.py @@ -0,0 +1,263 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import argparse +import csv +from dataclasses import dataclass +from pathlib import Path + + +@dataclass(frozen=True) +class DesignRule: + slug: str + keywords: tuple[str, ...] + style: str + palette: str + typography: str + effects: str + landing_pattern: str + anti_patterns: str + notes: str + + +DOMAIN_LIBRARY = { + "style": [ + {"name": "minimal-modern", "tags": {"saas", "productivity", "software"}, "summary": "Clean grids, restrained color, strong spacing rhythm."}, + {"name": "trust-dark", "tags": {"fintech", "security", "analytics"}, "summary": "Dark surfaces with high-contrast metrics and controlled glow."}, + {"name": "elegant-soft", "tags": {"beauty", "wellness", "premium"}, "summary": "Soft neutrals, editorial typography, gentle depth."}, + {"name": "editorial-bold", "tags": {"portfolio", "studio", "creator"}, "summary": "Typography-led layouts with fewer but stronger components."}, + ], + "color": [ + {"name": "slate-indigo", "tags": {"saas", "b2b", "dashboard"}, "summary": "Reliable product palette with strong focus color."}, + {"name": "navy-cyan", "tags": {"fintech", "security", "crypto"}, "summary": "Trust-heavy dark palette with crisp accent highlights."}, + {"name": "teal-blue", "tags": {"healthcare", "medical", "education"}, "summary": "Calm, legible palette for guidance-heavy flows."}, + {"name": "rose-stone", "tags": {"beauty", "wellness", "service"}, "summary": "Soft premium palette without losing contrast."}, + ], + "typography": [ + {"name": "Inter + Space Grotesk", "tags": {"saas", "dashboard", "tech"}, "summary": "Functional UI body with sharper display headlines."}, + {"name": "Inter + IBM Plex Sans", "tags": {"fintech", "data", "ops"}, "summary": "Trustworthy and technical without feeling cold."}, + {"name": "DM Sans + Cormorant Garamond", "tags": {"beauty", "luxury", "editorial"}, "summary": "Soft body copy plus premium display contrast."}, + {"name": "Inter + Nunito", "tags": {"education", "learning", "friendly"}, "summary": "Warm, approachable pair for guided workflows."}, + ], + "landing": [ + {"name": "hero + product proof", "tags": {"saas", "b2b", "product"}, "summary": "Lead with problem, product UI, and trust proof."}, + {"name": "hero + trust signals + metrics", "tags": {"fintech", "security"}, "summary": "Move quickly from promise to credibility to evidence."}, + {"name": "hero + treatments + testimonials", "tags": {"beauty", "service"}, "summary": "Show the offering, then emotion, then social proof."}, + {"name": "summary row + filters + charts", "tags": {"dashboard", "analytics", "ops"}, "summary": "Start with key numbers, then enable fast drill-down."}, + ], + "chart": [ + {"name": "line chart", "tags": {"trend", "time-series", "monitoring"}, "summary": "Use for change over time and directional narratives."}, + {"name": "bar chart", "tags": {"comparison", "ranking", "category"}, "summary": "Use for category comparison with clear labels."}, + {"name": "funnel chart", "tags": {"conversion", "checkout", "pipeline"}, "summary": "Use only when the user cares about progressive drop-off."}, + {"name": "table + sparkline", "tags": {"dashboard", "ops", "dense"}, "summary": "Best when users must compare many rows quickly."}, + ], + "ux": [ + {"name": "contrast-first", "tags": {"accessibility", "contrast", "readability"}, "summary": "Keep body text at 4.5:1 or better and check muted states."}, + {"name": "touch targets", "tags": {"mobile", "touch", "interaction"}, "summary": "Keep tap targets at 44x44px or larger."}, + {"name": "motion restraint", "tags": {"animation", "performance", "a11y"}, "summary": "Prefer opacity/transform and honor reduced motion."}, + {"name": "feedback locality", "tags": {"forms", "validation", "errors"}, "summary": "Place errors next to the field or action that caused them."}, + ], + "product": [ + {"name": "B2B SaaS", "tags": {"saas", "b2b", "workflow"}, "summary": "Prioritize clarity, trust, and information hierarchy."}, + {"name": "consumer marketplace", "tags": {"ecommerce", "retail", "marketplace"}, "summary": "Prioritize CTA hierarchy and decision speed."}, + {"name": "editorial portfolio", "tags": {"portfolio", "agency", "studio"}, "summary": "Let type and spacing carry most of the brand signal."}, + ], +} + +STACK_LIBRARY = { + "html-tailwind": [ + "Use spacing and typography scales consistently; avoid arbitrary values unless they encode a real token.", + "Prefer semantic HTML first, then layer Tailwind utilities for layout and state.", + "Use visible focus rings, not shadow-only focus states.", + ], + "react": [ + "Separate presentational components from stateful orchestration when the screen gets dense.", + "Memoize only after identifying re-render pressure; do not cargo-cult memo everywhere.", + "Keep loading, error, and empty states explicit in component contracts.", + ], + "nextjs": [ + "Use server components for data-heavy static surfaces and client components only for interaction islands.", + "Optimize images and fonts early; layout shift hurts perceived polish.", + "Keep route segments and layout nesting readable; complexity leaks into UX fast.", + ], + "vue": [ + "Keep composables focused and avoid mixing data fetching, presentation logic, and event plumbing in one file.", + "Use Pinia only when state truly spans multiple views.", + "Prefer explicit prop contracts over implicit slot conventions for complex widgets.", + ], + "svelte": [ + "Use stores sparingly; local state is usually enough for page-scoped interaction.", + "Keep transitions subtle and intentional.", + "Use semantic markup because Svelte speed does not compensate for weak accessibility.", + ], + "swiftui": [ + "Prefer a small number of reusable view modifiers instead of repeated inline styling.", + "Use state hoisting for reusable components.", + "Make navigation state obvious; hidden transitions confuse users quickly.", + ], + "react-native": [ + "Design for touch targets and text scaling first.", + "Avoid over-nesting views; spacing bugs compound quickly on mobile.", + "Budget for offline and loading states in every primary screen.", + ], + "flutter": [ + "Use a small, explicit theme surface; avoid per-widget color drift.", + "Keep widget trees readable by extracting repeated sections early.", + "Use platform-appropriate motion and haptics sparingly.", + ], + "shadcn": [ + "Treat shadcn/ui as a starting system, not the finished product identity.", + "Normalize spacing and type across imported primitives before scaling the page.", + "Audit keyboard and dialog behavior after customization.", + ], + "jetpack-compose": [ + "Keep state hoisting explicit and avoid business logic inside composables.", + "Use Material theming consistently before introducing custom tokens.", + "Measure recomposition hotspots before optimizing prematurely.", + ], +} + + +def load_rules(csv_path: Path) -> list[DesignRule]: + rows: list[DesignRule] = [] + with csv_path.open(newline="", encoding="utf-8") as handle: + reader = csv.DictReader(handle) + for row in reader: + rows.append( + DesignRule( + slug=row["slug"], + keywords=tuple(token.strip() for token in row["keywords"].split(",") if token.strip()), + style=row["style"], + palette=row["palette"], + typography=row["typography"], + effects=row["effects"], + landing_pattern=row["landing_pattern"], + anti_patterns=row["anti_patterns"], + notes=row["notes"], + ) + ) + return rows + + +def score_rule(query_tokens: set[str], rule: DesignRule) -> int: + overlap = len(query_tokens & set(rule.keywords)) + return overlap * 10 + (1 if rule.slug in query_tokens else 0) + + +def pick_rule(query: str, rules: list[DesignRule]) -> DesignRule: + query_tokens = set(token.lower() for token in query.replace("-", " ").split()) + return max(rules, key=lambda rule: (score_rule(query_tokens, rule), -len(rule.keywords))) + + +def score_entry(query_tokens: set[str], entry: dict[str, object]) -> tuple[int, str]: + tags = set(entry.get("tags", set())) + score = len(query_tokens & tags) + return score, str(entry["name"]) + + +def top_domain_entries(domain: str, query: str, limit: int) -> list[dict[str, object]]: + query_tokens = set(token.lower() for token in query.replace("-", " ").split()) + entries = DOMAIN_LIBRARY[domain] + ranked = sorted(entries, key=lambda entry: score_entry(query_tokens, entry), reverse=True) + return ranked[:limit] + + +def render_design_system(rule: DesignRule, query: str, project: str | None, markdown: bool) -> str: + title = project or query.strip() or rule.slug + lines = [ + f"# Design system: {title}" if markdown else f"Design system: {title}", + "", + f"- Query: {query}", + f"- Matched profile: {rule.slug}", + f"- Style direction: {rule.style}", + f"- Palette: {rule.palette}", + f"- Typography: {rule.typography}", + f"- Effects: {rule.effects}", + f"- Landing/layout bias: {rule.landing_pattern}", + f"- Avoid: {rule.anti_patterns}", + f"- Notes: {rule.notes}", + ] + return "\n".join(lines) + + +def render_domain(domain: str, query: str, limit: int, markdown: bool) -> str: + entries = top_domain_entries(domain, query, limit) + header = f"# Domain lookup: {domain}" if markdown else f"Domain lookup: {domain}" + lines = [header, "", f"Query: {query}", ""] + for entry in entries: + lines.append(f"- {entry['name']}: {entry['summary']}") + return "\n".join(lines) + + +def render_stack(stack: str, markdown: bool) -> str: + header = f"# Stack guidance: {stack}" if markdown else f"Stack guidance: {stack}" + lines = [header, ""] + for item in STACK_LIBRARY[stack]: + lines.append(f"- {item}") + return "\n".join(lines) + + +def persist_design_system(text: str, page: str | None) -> list[Path]: + base = Path.cwd() / "design-system" + base.mkdir(exist_ok=True) + pages = base / "pages" + pages.mkdir(exist_ok=True) + created: list[Path] = [] + master = base / "MASTER.md" + master.write_text(text + "\n", encoding="utf-8") + created.append(master) + if page: + page_path = pages / f"{page}.md" + page_path.write_text( + f"# Page override: {page}\n\n- Base authority: ../MASTER.md\n- Record only page-specific deviations here.\n", + encoding="utf-8", + ) + created.append(page_path) + return created + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description="Search the bundled UI/UX guidance library.") + parser.add_argument("query", nargs="?", default="") + parser.add_argument("--design-system", action="store_true") + parser.add_argument("--domain", choices=sorted(DOMAIN_LIBRARY)) + parser.add_argument("--stack", choices=sorted(STACK_LIBRARY)) + parser.add_argument("--persist", action="store_true") + parser.add_argument("-p", "--project") + parser.add_argument("--page") + parser.add_argument("-n", type=int, default=5) + parser.add_argument("-f", "--format", choices=("ascii", "markdown"), default="ascii") + return parser.parse_args() + + +def main() -> int: + args = parse_args() + markdown = args.format == "markdown" + script_dir = Path(__file__).resolve().parent + rules = load_rules(script_dir.parent / "data" / "ui-reasoning.csv") + + if args.design_system: + rule = pick_rule(args.query, rules) + output = render_design_system(rule, args.query, args.project, markdown) + print(output) + if args.persist: + created = persist_design_system(output, args.page) + print("\nPersisted:") + for path in created: + print(f"- {path}") + return 0 + + if args.domain: + print(render_domain(args.domain, args.query, args.n, markdown)) + return 0 + + if args.stack: + print(render_stack(args.stack, markdown)) + return 0 + + print("No mode selected. Use --design-system, --domain, or --stack.") + return 1 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/uv-package-manager/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/uv-package-manager/SKILL.md new file mode 100644 index 0000000..051f4ae --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/uv-package-manager/SKILL.md @@ -0,0 +1,832 @@ +--- +name: uv-package-manager +description: Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv. +version: 0.1.0 +--- + +# UV Package Manager + +Comprehensive guide to using uv, an extremely fast Python package installer and resolver written in Rust, for modern Python project management and dependency workflows. + +## When to Use This Skill + +- Setting up new Python projects quickly +- Managing Python dependencies faster than pip +- Creating and managing virtual environments +- Installing Python interpreters +- Resolving dependency conflicts efficiently +- Migrating from pip/pip-tools/poetry +- Speeding up CI/CD pipelines +- Managing monorepo Python projects +- Working with lockfiles for reproducible builds +- Optimizing Docker builds with Python dependencies + +## Core Concepts + +### 1. What is uv? +- **Ultra-fast package installer**: 10-100x faster than pip +- **Written in Rust**: Leverages Rust's performance +- **Drop-in pip replacement**: Compatible with pip workflows +- **Virtual environment manager**: Create and manage venvs +- **Python installer**: Download and manage Python versions +- **Resolver**: Advanced dependency resolution +- **Lockfile support**: Reproducible installations + +### 2. Key Features +- Blazing fast installation speeds +- Disk space efficient with global cache +- Compatible with pip, pip-tools, poetry +- Comprehensive dependency resolution +- Cross-platform support (Linux, macOS, Windows) +- No Python required for installation +- Built-in virtual environment support + +### 3. UV vs Traditional Tools +- **vs pip**: 10-100x faster, better resolver +- **vs pip-tools**: Faster, simpler, better UX +- **vs poetry**: Faster, less opinionated, lighter +- **vs conda**: Faster, Python-focused + +## Installation + +### Quick Install + +```bash +# macOS/Linux +curl -LsSf https://astral.sh/uv/install.sh | sh + +# Windows (PowerShell) +powershell -c "irm https://astral.sh/uv/install.ps1 | iex" + +# Using pip (if you already have Python) +pip install uv + +# Using Homebrew (macOS) +brew install uv + +# Using cargo (if you have Rust) +cargo install --git https://github.com/astral-sh/uv uv +``` + +### Verify Installation + +```bash +uv --version +# uv 0.x.x +``` + +## Quick Start + +### Create a New Project + +```bash +# Create new project with virtual environment +uv init my-project +cd my-project + +# Or create in current directory +uv init . + +# Initialize creates: +# - .python-version (Python version) +# - pyproject.toml (project config) +# - README.md +# - .gitignore +``` + +### Install Dependencies + +```bash +# Install packages (creates venv if needed) +uv add requests pandas + +# Install dev dependencies +uv add --dev pytest black ruff + +# Install from requirements.txt +uv pip install -r requirements.txt + +# Install from pyproject.toml +uv sync +``` + +## Virtual Environment Management + +### Pattern 1: Creating Virtual Environments + +```bash +# Create virtual environment with uv +uv venv + +# Create with specific Python version +uv venv --python 3.12 + +# Create with custom name +uv venv my-env + +# Create with system site packages +uv venv --system-site-packages + +# Specify location +uv venv /path/to/venv +``` + +### Pattern 2: Activating Virtual Environments + +```bash +# Linux/macOS +source .venv/bin/activate + +# Windows (Command Prompt) +.venv\Scripts\activate.bat + +# Windows (PowerShell) +.venv\Scripts\Activate.ps1 + +# Or use uv run (no activation needed) +uv run python script.py +uv run pytest +``` + +### Pattern 3: Using uv run + +```bash +# Run Python script (auto-activates venv) +uv run python app.py + +# Run installed CLI tool +uv run black . +uv run pytest + +# Run with specific Python version +uv run --python 3.11 python script.py + +# Pass arguments +uv run python script.py --arg value +``` + +## Package Management + +### Pattern 4: Adding Dependencies + +```bash +# Add package (adds to pyproject.toml) +uv add requests + +# Add with version constraint +uv add "django>=4.0,<5.0" + +# Add multiple packages +uv add numpy pandas matplotlib + +# Add dev dependency +uv add --dev pytest pytest-cov + +# Add optional dependency group +uv add --optional docs sphinx + +# Add from git +uv add git+https://github.com/user/repo.git + +# Add from git with specific ref +uv add git+https://github.com/user/repo.git@v1.0.0 + +# Add from local path +uv add ./local-package + +# Add editable local package +uv add -e ./local-package +``` + +### Pattern 5: Removing Dependencies + +```bash +# Remove package +uv remove requests + +# Remove dev dependency +uv remove --dev pytest + +# Remove multiple packages +uv remove numpy pandas matplotlib +``` + +### Pattern 6: Upgrading Dependencies + +```bash +# Upgrade specific package +uv add --upgrade requests + +# Upgrade all packages +uv sync --upgrade + +# Upgrade package to latest +uv add --upgrade requests + +# Show what would be upgraded +uv tree --outdated +``` + +### Pattern 7: Locking Dependencies + +```bash +# Generate uv.lock file +uv lock + +# Update lock file +uv lock --upgrade + +# Lock without installing +uv lock --no-install + +# Lock specific package +uv lock --upgrade-package requests +``` + +## Python Version Management + +### Pattern 8: Installing Python Versions + +```bash +# Install Python version +uv python install 3.12 + +# Install multiple versions +uv python install 3.11 3.12 3.13 + +# Install latest version +uv python install + +# List installed versions +uv python list + +# Find available versions +uv python list --all-versions +``` + +### Pattern 9: Setting Python Version + +```bash +# Set Python version for project +uv python pin 3.12 + +# This creates/updates .python-version file + +# Use specific Python version for command +uv --python 3.11 run python script.py + +# Create venv with specific version +uv venv --python 3.12 +``` + +## Project Configuration + +### Pattern 10: pyproject.toml with uv + +```toml +[project] +name = "my-project" +version = "0.1.0" +description = "My awesome project" +readme = "README.md" +requires-python = ">=3.8" +dependencies = [ + "requests>=2.31.0", + "pydantic>=2.0.0", + "click>=8.1.0", +] + +[project.optional-dependencies] +dev = [ + "pytest>=7.4.0", + "pytest-cov>=4.1.0", + "black>=23.0.0", + "ruff>=0.1.0", + "mypy>=1.5.0", +] +docs = [ + "sphinx>=7.0.0", + "sphinx-rtd-theme>=1.3.0", +] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.uv] +dev-dependencies = [ + # Additional dev dependencies managed by uv +] + +[tool.uv.sources] +# Custom package sources +my-package = { git = "https://github.com/user/repo.git" } +``` + +### Pattern 11: Using uv with Existing Projects + +```bash +# Migrate from requirements.txt +uv add -r requirements.txt + +# Migrate from poetry +# Already have pyproject.toml, just use: +uv sync + +# Export to requirements.txt +uv pip freeze > requirements.txt + +# Export with hashes +uv pip freeze --require-hashes > requirements.txt +``` + +## Advanced Workflows + +### Pattern 12: Monorepo Support + +```bash +# Project structure +# monorepo/ +# packages/ +# package-a/ +# pyproject.toml +# package-b/ +# pyproject.toml +# pyproject.toml (root) + +# Root pyproject.toml +[tool.uv.workspace] +members = ["packages/*"] + +# Install all workspace packages +uv sync + +# Add workspace dependency +uv add --path ./packages/package-a +``` + +### Pattern 13: CI/CD Integration + +```yaml +# .github/workflows/test.yml +name: Tests + +on: [push, pull_request] + +jobs: + test: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Install uv + uses: astral-sh/setup-uv@v2 + with: + enable-cache: true + + - name: Set up Python + run: uv python install 3.12 + + - name: Install dependencies + run: uv sync --all-extras --dev + + - name: Run tests + run: uv run pytest + + - name: Run linting + run: | + uv run ruff check . + uv run black --check . +``` + +### Pattern 14: Docker Integration + +```dockerfile +# Dockerfile +FROM python:3.12-slim + +# Install uv +COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv + +# Set working directory +WORKDIR /app + +# Copy dependency files +COPY pyproject.toml uv.lock ./ + +# Install dependencies +RUN uv sync --frozen --no-dev + +# Copy application code +COPY . . + +# Run application +CMD ["uv", "run", "python", "app.py"] +``` + +**Optimized multi-stage build:** + +```dockerfile +# Multi-stage Dockerfile +FROM python:3.12-slim AS builder + +# Install uv +COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv + +WORKDIR /app + +# Install dependencies to venv +COPY pyproject.toml uv.lock ./ +RUN uv sync --frozen --no-dev --no-editable + +# Runtime stage +FROM python:3.12-slim + +WORKDIR /app + +# Copy venv from builder +COPY --from=builder /app/.venv .venv +COPY . . + +# Use venv +ENV PATH="/app/.venv/bin:$PATH" + +CMD ["python", "app.py"] +``` + +### Pattern 15: Lockfile Workflows + +```bash +# Create lockfile (uv.lock) +uv lock + +# Install from lockfile (exact versions) +uv sync --frozen + +# Update lockfile without installing +uv lock --no-install + +# Upgrade specific package in lock +uv lock --upgrade-package requests + +# Check if lockfile is up to date +uv lock --check + +# Export lockfile to requirements.txt +uv export --format requirements-txt > requirements.txt + +# Export with hashes for security +uv export --format requirements-txt --hash > requirements.txt +``` + +## Performance Optimization + +### Pattern 16: Using Global Cache + +```bash +# UV automatically uses global cache at: +# Linux: ~/.cache/uv +# macOS: ~/Library/Caches/uv +# Windows: %LOCALAPPDATA%\uv\cache + +# Clear cache +uv cache clean + +# Check cache size +uv cache dir +``` + +### Pattern 17: Parallel Installation + +```bash +# UV installs packages in parallel by default + +# Control parallelism +uv pip install --jobs 4 package1 package2 + +# No parallel (sequential) +uv pip install --jobs 1 package +``` + +### Pattern 18: Offline Mode + +```bash +# Install from cache only (no network) +uv pip install --offline package + +# Sync from lockfile offline +uv sync --frozen --offline +``` + +## Comparison with Other Tools + +### uv vs pip + +```bash +# pip +python -m venv .venv +source .venv/bin/activate +pip install requests pandas numpy +# ~30 seconds + +# uv +uv venv +uv add requests pandas numpy +# ~2 seconds (10-15x faster) +``` + +### uv vs poetry + +```bash +# poetry +poetry init +poetry add requests pandas +poetry install +# ~20 seconds + +# uv +uv init +uv add requests pandas +uv sync +# ~3 seconds (6-7x faster) +``` + +### uv vs pip-tools + +```bash +# pip-tools +pip-compile requirements.in +pip-sync requirements.txt +# ~15 seconds + +# uv +uv lock +uv sync --frozen +# ~2 seconds (7-8x faster) +``` + +## Common Workflows + +### Pattern 19: Starting a New Project + +```bash +# Complete workflow +uv init my-project +cd my-project + +# Set Python version +uv python pin 3.12 + +# Add dependencies +uv add fastapi uvicorn pydantic + +# Add dev dependencies +uv add --dev pytest black ruff mypy + +# Create structure +mkdir -p src/my_project tests + +# Run tests +uv run pytest + +# Format code +uv run black . +uv run ruff check . +``` + +### Pattern 20: Maintaining Existing Project + +```bash +# Clone repository +git clone https://github.com/user/project.git +cd project + +# Install dependencies (creates venv automatically) +uv sync + +# Install with dev dependencies +uv sync --all-extras + +# Update dependencies +uv lock --upgrade + +# Run application +uv run python app.py + +# Run tests +uv run pytest + +# Add new dependency +uv add new-package + +# Commit updated files +git add pyproject.toml uv.lock +git commit -m "Add new-package dependency" +``` + +## Tool Integration + +### Pattern 21: Pre-commit Hooks + +```yaml +# .pre-commit-config.yaml +repos: + - repo: local + hooks: + - id: uv-lock + name: uv lock + entry: uv lock + language: system + pass_filenames: false + + - id: ruff + name: ruff + entry: uv run ruff check --fix + language: system + types: [python] + + - id: black + name: black + entry: uv run black + language: system + types: [python] +``` + +### Pattern 22: VS Code Integration + +```json +// .vscode/settings.json +{ + "python.defaultInterpreterPath": "${workspaceFolder}/.venv/bin/python", + "python.terminal.activateEnvironment": true, + "python.testing.pytestEnabled": true, + "python.testing.pytestArgs": ["-v"], + "python.linting.enabled": true, + "python.formatting.provider": "black", + "[python]": { + "editor.defaultFormatter": "ms-python.black-formatter", + "editor.formatOnSave": true + } +} +``` + +## Troubleshooting + +### Common Issues + +```bash +# Issue: uv not found +# Solution: Add to PATH or reinstall +echo 'export PATH="$HOME/.cargo/bin:$PATH"' >> ~/.bashrc + +# Issue: Wrong Python version +# Solution: Pin version explicitly +uv python pin 3.12 +uv venv --python 3.12 + +# Issue: Dependency conflict +# Solution: Check resolution +uv lock --verbose + +# Issue: Cache issues +# Solution: Clear cache +uv cache clean + +# Issue: Lockfile out of sync +# Solution: Regenerate +uv lock --upgrade +``` + +## Best Practices + +### Project Setup + +1. **Always use lockfiles** for reproducibility +2. **Pin Python version** with .python-version +3. **Separate dev dependencies** from production +4. **Use uv run** instead of activating venv +5. **Commit uv.lock** to version control +6. **Use --frozen in CI** for consistent builds +7. **Leverage global cache** for speed +8. **Use workspace** for monorepos +9. **Export requirements.txt** for compatibility +10. **Keep uv updated** for latest features + +### Performance Tips + +```bash +# Use frozen installs in CI +uv sync --frozen + +# Use offline mode when possible +uv sync --offline + +# Parallel operations (automatic) +# uv does this by default + +# Reuse cache across environments +# uv shares cache globally + +# Use lockfiles to skip resolution +uv sync --frozen # skips resolution +``` + +## Migration Guide + +### From pip + requirements.txt + +```bash +# Before +python -m venv .venv +source .venv/bin/activate +pip install -r requirements.txt + +# After +uv venv +uv pip install -r requirements.txt +# Or better: +uv init +uv add -r requirements.txt +``` + +### From Poetry + +```bash +# Before +poetry install +poetry add requests + +# After +uv sync +uv add requests + +# Keep existing pyproject.toml +# uv reads [project] and [tool.poetry] sections +``` + +### From pip-tools + +```bash +# Before +pip-compile requirements.in +pip-sync requirements.txt + +# After +uv lock +uv sync --frozen +``` + +## Command Reference + +### Essential Commands + +```bash +# Project management +uv init [PATH] # Initialize project +uv add PACKAGE # Add dependency +uv remove PACKAGE # Remove dependency +uv sync # Install dependencies +uv lock # Create/update lockfile + +# Virtual environments +uv venv [PATH] # Create venv +uv run COMMAND # Run in venv + +# Python management +uv python install VERSION # Install Python +uv python list # List installed Pythons +uv python pin VERSION # Pin Python version + +# Package installation (pip-compatible) +uv pip install PACKAGE # Install package +uv pip uninstall PACKAGE # Uninstall package +uv pip freeze # List installed +uv pip list # List packages + +# Utility +uv cache clean # Clear cache +uv cache dir # Show cache location +uv --version # Show version +``` + +## Resources + +- **Official documentation**: https://docs.astral.sh/uv/ +- **GitHub repository**: https://github.com/astral-sh/uv +- **Astral blog**: https://astral.sh/blog +- **Migration guides**: https://docs.astral.sh/uv/guides/ +- **Comparison with other tools**: https://docs.astral.sh/uv/pip/compatibility/ + +## Best Practices Summary + +1. **Use uv for all new projects** - Start with `uv init` +2. **Commit lockfiles** - Ensure reproducible builds +3. **Pin Python versions** - Use .python-version +4. **Use uv run** - Avoid manual venv activation +5. **Leverage caching** - Let uv manage global cache +6. **Use --frozen in CI** - Exact reproduction +7. **Keep uv updated** - Fast-moving project +8. **Use workspaces** - For monorepo projects +9. **Export for compatibility** - Generate requirements.txt when needed +10. **Read the docs** - uv is feature-rich and evolving diff --git a/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/SKILL.md new file mode 100644 index 0000000..a535ed0 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/SKILL.md @@ -0,0 +1,148 @@ +--- +name: verification-loop +description: This skill should be used when the user asks to "verify code", "run verification", "check quality", "validate changes", or before creating a PR. Provides comprehensive verification including build, type check, lint, tests, security scan, and diff review. +version: 1.0.0 +--- + +# Verification Loop Skill + +A comprehensive verification system for Claude Code sessions. + +## When to Use + +Invoke this skill: +- After completing a feature or significant code change +- Before creating a PR +- When you want to ensure quality gates pass +- After refactoring + +## Verification Phases + +Choose the commands adaptively for the current project instead of running every example blindly. Use the stack-appropriate command from `references/STACK-DETECTION.md` when the repo does not match the default examples below. + + +### Phase 1: Build Verification +```bash +# Python projects (uv) +uv build 2>&1 | tail -20 +# OR +python -m build 2>&1 | tail -20 + +# Node.js projects +npm run build 2>&1 | tail -20 +# OR +pnpm build 2>&1 | tail -20 +``` + +If build fails, STOP and fix before continuing. + +### Phase 2: Type Check +```bash +# TypeScript projects +npx tsc --noEmit 2>&1 | head -30 + +# Python projects +pyright . 2>&1 | head -30 +``` + +Report all type errors. Fix critical ones before continuing. + +### Phase 3: Lint Check +```bash +# JavaScript/TypeScript +npm run lint 2>&1 | head -30 + +# Python +ruff check . 2>&1 | head -30 +``` + +### Phase 4: Test Suite +```bash +# Python projects +pytest --cov=src --cov-report=term-missing 2>&1 | tail -50 + +# Node.js projects +npm run test -- --coverage 2>&1 | tail -50 +``` + +Report: +- Total tests: X +- Passed: X +- Failed: X +- Coverage: X% + +### Phase 5: Security Scan +```bash +# Python: Check for secrets +grep -rn "sk-" --include="*.py" . 2>/dev/null | head -10 +grep -rn "api_key" --include="*.py" . 2>/dev/null | head -10 +pip-audit + +# Node.js: Check for secrets +grep -rn "sk-" --include="*.ts" --include="*.js" . 2>/dev/null | head -10 +grep -rn "api_key" --include="*.ts" --include="*.js" . 2>/dev/null | head -10 + +# Check for debug statements +grep -rn "print(" --include="*.py" src/ 2>/dev/null | head -10 +grep -rn "console.log" --include="*.ts" --include="*.tsx" src/ 2>/dev/null | head -10 +``` + +### Phase 6: Diff Review +```bash +# Show what changed +git diff --stat +git diff HEAD~1 --name-only +``` + +Review each changed file for: +- Unintended changes +- Missing error handling +- Potential edge cases + +## Output Format + +After running all phases, produce a verification report: + +``` +VERIFICATION REPORT +================== + +Build: [PASS/FAIL] +Types: [PASS/FAIL] (X errors) +Lint: [PASS/FAIL] (X warnings) +Tests: [PASS/FAIL] (X/Y passed, Z% coverage) +Security: [PASS/FAIL] (X issues) +Diff: [X files changed] + +Overall: [READY/NOT READY] for PR + +Issues to Fix: +1. ... +2. ... +``` + +## Continuous Mode + +For long sessions, run verification every 15 minutes or after major changes: + +```markdown +Set a mental checkpoint: +- After completing each function +- After finishing a component +- Before moving to next task + +Run: /verify +``` + +## Integration with Hooks + +This skill complements PostToolUse hooks but provides deeper verification. +Hooks catch issues immediately; this skill provides comprehensive review. + + +## Reference Files + +Load only what is needed: +- `references/STACK-DETECTION.md` - how to choose the right verification command set for the current repo +- `references/REPORT-TEMPLATE.md` - report structure for final verification output +- `examples/example-verification-report.md` - example final report diff --git a/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/examples/example-verification-report.md b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/examples/example-verification-report.md new file mode 100644 index 0000000..19c331f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/examples/example-verification-report.md @@ -0,0 +1,9 @@ +VERIFICATION REPORT +================== +Build: PASS +Types: PASS +Lint: PASS (2 non-blocking warnings) +Tests: PASS (48/48) +Security: PASS +Diff: 4 files changed +Overall: READY diff --git a/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/references/REPORT-TEMPLATE.md b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/references/REPORT-TEMPLATE.md new file mode 100644 index 0000000..9f2daa3 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/references/REPORT-TEMPLATE.md @@ -0,0 +1,13 @@ +# Verification Report Template + +```text +VERIFICATION REPORT +================== +Build: [PASS/FAIL] +Types: [PASS/FAIL] +Lint: [PASS/FAIL] +Tests: [PASS/FAIL] +Security: [PASS/FAIL] +Diff: [summary] +Overall: [READY/NOT READY] +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/references/STACK-DETECTION.md b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/references/STACK-DETECTION.md new file mode 100644 index 0000000..3289d91 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/verification-loop/references/STACK-DETECTION.md @@ -0,0 +1,12 @@ +# Stack Detection + +## Python +Look for `pyproject.toml`, `uv.lock`, `requirements.txt`, or `pytest.ini`. +Prefer `uv` commands when the repo is uv-managed. + +## Node.js / TypeScript +Look for `package.json`, `pnpm-lock.yaml`, `tsconfig.json`. +Use the package manager already used by the repo. + +## Mixed repos +Run only the checks relevant to touched areas; do not force every language tool when the change is clearly scoped. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/SKILL.md new file mode 100644 index 0000000..057af1c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/SKILL.md @@ -0,0 +1,369 @@ +--- +name: web-design-reviewer +description: 'This skill enables visual inspection of websites running locally or remotely to identify and fix design issues. Triggers on requests like "review website design", "check the UI", "fix the layout", "find design problems". Detects issues with responsive design, accessibility, visual consistency, and layout breakage, then performs fixes at the source code level.' +version: 0.1.0 +--- + +# Web Design Reviewer + +This skill enables visual inspection and validation of website design quality, identifying and fixing issues at the source code level. + +## Scope of Application + +- Static sites (HTML/CSS/JS) +- SPA frameworks such as React / Vue / Angular / Svelte +- Full-stack frameworks such as Next.js / Nuxt / SvelteKit +- CMS platforms such as WordPress / Drupal +- Any other web application + +## Prerequisites + +### Required + +1. **Target website must be running** + - Local development server (e.g., `http://localhost:3000`) + - Staging environment + - Production environment (for read-only reviews) + +2. **Browser automation must be available** + - Screenshot capture + - Page navigation + - DOM information retrieval + +3. **Access to source code (when making fixes)** + - Project must exist within the workspace + +## Workflow Overview + +```mermaid +flowchart TD + A[Step 1: Information Gathering] --> B[Step 2: Visual Inspection] + B --> C[Step 3: Issue Fixing] + C --> D[Step 4: Re-verification] + D --> E{Issues Remaining?} + E -->|Yes| B + E -->|No| F[Completion Report] +``` + +--- + +## Step 1: Information Gathering Phase + +### 1.1 URL Confirmation + +If the URL is not provided, ask the user: + +> Please provide the URL of the website to review (e.g., `http://localhost:3000`) + +### 1.2 Understanding Project Structure + +When making fixes, gather the following information: + +| Item | Example Question | +|------|------------------| +| Framework | Are you using React / Vue / Next.js, etc.? | +| Styling Method | CSS / SCSS / Tailwind / CSS-in-JS, etc. | +| Source Location | Where are style files and components located? | +| Review Scope | Specific pages only or entire site? | + +### 1.3 Automatic Project Detection + +Attempt automatic detection from files in the workspace: + +``` +Detection targets: +├── package.json → Framework and dependencies +├── tsconfig.json → TypeScript usage +├── tailwind.config → Tailwind CSS +├── next.config → Next.js +├── vite.config → Vite +├── nuxt.config → Nuxt +└── src/ or app/ → Source directory +``` + +### 1.4 Identifying Styling Method + +| Method | Detection | Edit Target | +|--------|-----------|-------------| +| Pure CSS | `*.css` files | Global CSS or component CSS | +| SCSS/Sass | `*.scss`, `*.sass` | SCSS files | +| CSS Modules | `*.module.css` | Module CSS files | +| Tailwind CSS | `tailwind.config.*` | className in components | +| styled-components | `styled.` in code | JS/TS files | +| Emotion | `@emotion/` imports | JS/TS files | +| CSS-in-JS (other) | Inline styles | JS/TS files | + +--- + +## Step 2: Visual Inspection Phase + +### 2.1 Page Traversal + +1. Navigate to the specified URL +2. Capture screenshots +3. Retrieve DOM structure/snapshot (if possible) +4. If additional pages exist, traverse through navigation + +### 2.2 Inspection Items + +#### Layout Issues + +| Issue | Description | Severity | +|-------|-------------|----------| +| Element Overflow | Content overflows from parent element or viewport | High | +| Element Overlap | Unintended overlapping of elements | High | +| Alignment Issues | Grid or flex alignment problems | Medium | +| Inconsistent Spacing | Padding/margin inconsistencies | Medium | +| Text Clipping | Long text not handled properly | Medium | + +#### Responsive Issues + +| Issue | Description | Severity | +|-------|-------------|----------| +| Non-mobile Friendly | Layout breaks on small screens | High | +| Breakpoint Issues | Unnatural transitions when screen size changes | Medium | +| Touch Targets | Buttons too small on mobile | Medium | + +#### Accessibility Issues + +| Issue | Description | Severity | +|-------|-------------|----------| +| Insufficient Contrast | Low contrast ratio between text and background | High | +| No Focus State | Cannot determine state during keyboard navigation | High | +| Missing alt Text | No alternative text for images | Medium | + +#### Visual Consistency + +| Issue | Description | Severity | +|-------|-------------|----------| +| Font Inconsistency | Mixed font families | Medium | +| Color Inconsistency | Non-unified brand colors | Medium | +| Spacing Inconsistency | Non-uniform spacing between similar elements | Low | + +### 2.3 Viewport Testing (Responsive) + +Test at the following viewports: + +| Name | Width | Representative Device | +|------|-------|----------------------| +| Mobile | 375px | iPhone SE/12 mini | +| Tablet | 768px | iPad | +| Desktop | 1280px | Standard PC | +| Wide | 1920px | Large display | + +--- + +## Step 3: Issue Fixing Phase + +### 3.1 Issue Prioritization + +```mermaid +block-beta + columns 1 + block:priority["Priority Matrix"] + P1["P1: Fix Immediately\n(Layout issues affecting functionality)"] + P2["P2: Fix Next\n(Visual issues degrading UX)"] + P3["P3: Fix If Possible\n(Minor visual inconsistencies)"] + end +``` + +### 3.2 Identifying Source Files + +Identify source files from problematic elements: + +1. **Selector-based Search** + - Search codebase by class name or ID + - Explore style definitions with `grep_search` + +2. **Component-based Search** + - Identify components from element text or structure + - Explore related files with `semantic_search` + +3. **File Pattern Filtering** + ``` + Style files: src/**/*.css, styles/**/* + Components: src/components/**/* + Pages: src/pages/**, app/** + ``` + +### 3.3 Applying Fixes + +#### Framework-specific Fix Guidelines + +See [references/framework-fixes.md](references/framework-fixes.md) for details. + +#### Fix Principles + +1. **Minimal Changes**: Only make the minimum changes necessary to resolve the issue +2. **Respect Existing Patterns**: Follow existing code style in the project +3. **Avoid Breaking Changes**: Be careful not to affect other areas +4. **Add Comments**: Add comments to explain the reason for fixes where appropriate + +--- + +## Step 4: Re-verification Phase + +### 4.1 Post-fix Confirmation + +1. Reload browser (or wait for development server HMR) +2. Capture screenshots of fixed areas +3. Compare before and after + +### 4.2 Regression Testing + +- Verify that fixes haven't affected other areas +- Confirm responsive display is not broken + +### 4.3 Iteration Decision + +```mermaid +flowchart TD + A{Issues Remaining?} + A -->|Yes| B[Return to Step 2] + A -->|No| C[Proceed to Completion Report] +``` + +**Iteration Limit**: If more than 3 fix attempts are needed for a specific issue, consult the user + +--- + +## Output Format + +### Review Results Report + +```markdown +# Web Design Review Results + +## Summary + +| Item | Value | +|------|-------| +| Target URL | {URL} | +| Framework | {Detected framework} | +| Styling | {CSS / Tailwind / etc.} | +| Tested Viewports | Desktop, Mobile | +| Issues Detected | {N} | +| Issues Fixed | {M} | + +## Detected Issues + +### [P1] {Issue Title} + +- **Page**: {Page path} +- **Element**: {Selector or description} +- **Issue**: {Detailed description of the issue} +- **Fixed File**: `{File path}` +- **Fix Details**: {Description of changes} +- **Screenshot**: Before/After + +### [P2] {Issue Title} +... + +## Unfixed Issues (if any) + +### {Issue Title} +- **Reason**: {Why it was not fixed/could not be fixed} +- **Recommended Action**: {Recommendations for user} + +## Recommendations + +- {Suggestions for future improvements} +``` + +--- + +## Required Capabilities + +| Capability | Description | Required | +|------------|-------------|----------| +| Web Page Navigation | Access URLs, page transitions | ✅ | +| Screenshot Capture | Page image capture | ✅ | +| Image Analysis | Visual issue detection | ✅ | +| DOM Retrieval | Page structure retrieval | Recommended | +| File Read/Write | Source code reading and editing | Required for fixes | +| Code Search | Code search within project | Required for fixes | + +--- + +## Reference Implementation + +### Implementation with Playwright MCP + +[Playwright MCP](https://github.com/microsoft/playwright-mcp) is recommended as the reference implementation for this skill. + +| Capability | Playwright MCP Tool | Purpose | +|------------|---------------------|---------| +| Navigation | `browser_navigate` | Access URLs | +| Snapshot | `browser_snapshot` | Retrieve DOM structure | +| Screenshot | `browser_take_screenshot` | Images for visual inspection | +| Click | `browser_click` | Interact with interactive elements | +| Resize | `browser_resize` | Responsive testing | +| Console | `browser_console_messages` | Detect JS errors | + +#### Configuration Example (MCP Server) + +```json +{ + "mcpServers": { + "playwright": { + "command": "npx", + "args": ["-y", "@playwright/mcp@latest", "--caps=vision"] + } + } +} +``` + +### Other Compatible Browser Automation Tools + +| Tool | Features | +|------|----------| +| Selenium | Broad browser support, multi-language support | +| Puppeteer | Chrome/Chromium focused, Node.js | +| Cypress | Easy integration with E2E testing | +| WebDriver BiDi | Standardized next-generation protocol | + +The same workflow can be implemented with these tools. As long as they provide the necessary capabilities (navigation, screenshot, DOM retrieval), the choice of tool is flexible. + +--- + +## Best Practices + +### DO (Recommended) + +- ✅ Always save screenshots before making fixes +- ✅ Fix one issue at a time and verify each +- ✅ Follow the project's existing code style +- ✅ Confirm with user before major changes +- ✅ Document fix details thoroughly + +### DON'T (Not Recommended) + +- ❌ Large-scale refactoring without confirmation +- ❌ Ignoring design systems or brand guidelines +- ❌ Fixes that ignore performance +- ❌ Fixing multiple issues at once (difficult to verify) + +--- + +## Troubleshooting + +### Problem: Style files not found + +1. Check dependencies in `package.json` +2. Consider the possibility of CSS-in-JS +3. Consider CSS generated at build time +4. Ask user about styling method + +### Problem: Fixes not reflected + +1. Check if development server HMR is working +2. Clear browser cache +3. Rebuild if project requires build +4. Check CSS specificity issues + +### Problem: Fixes affecting other areas + +1. Rollback changes +2. Use more specific selectors +3. Consider using CSS Modules or scoped styles +4. Consult user to confirm impact scope diff --git a/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/references/framework-fixes.md b/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/references/framework-fixes.md new file mode 100644 index 0000000..d400ca1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/references/framework-fixes.md @@ -0,0 +1,475 @@ +# Framework-specific Fix Guide + +This document explains specific fix techniques for each framework and styling method. + +--- + +## Pure CSS / SCSS + +### Fixing Layout Overflow + +```css +/* Before: Overflow occurs */ +.container { + width: 100%; +} + +/* After: Control overflow */ +.container { + width: 100%; + max-width: 100%; + overflow-x: hidden; +} +``` + +### Text Clipping Prevention + +```css +/* Single line truncation */ +.text-truncate { + overflow: hidden; + text-overflow: ellipsis; + white-space: nowrap; +} + +/* Multi-line truncation */ +.text-clamp { + display: -webkit-box; + -webkit-line-clamp: 3; + -webkit-box-orient: vertical; + overflow: hidden; +} + +/* Word wrapping */ +.text-wrap { + word-wrap: break-word; + overflow-wrap: break-word; + hyphens: auto; +} +``` + +### Spacing Unification + +```css +/* Unify spacing with CSS custom properties */ +:root { + --spacing-xs: 0.25rem; + --spacing-sm: 0.5rem; + --spacing-md: 1rem; + --spacing-lg: 1.5rem; + --spacing-xl: 2rem; +} + +.card { + padding: var(--spacing-md); + margin-bottom: var(--spacing-lg); +} +``` + +### Improving Contrast + +```css +/* Before: Insufficient contrast */ +.text { + color: #999999; + background-color: #ffffff; +} + +/* After: Meets WCAG AA standards */ +.text { + color: #595959; /* Contrast ratio 7:1 */ + background-color: #ffffff; +} +``` + +--- + +## Tailwind CSS + +### Layout Fixes + +```jsx +{/* Before: Overflow */} +<div className="w-full"> + <img src="..." /> +</div> + +{/* After: Overflow control */} +<div className="w-full max-w-full overflow-hidden"> + <img src="..." className="w-full h-auto object-contain" /> +</div> +``` + +### Text Clipping Prevention + +```jsx +{/* Single line truncation */} +<p className="truncate">Long text...</p> + +{/* Multi-line truncation */} +<p className="line-clamp-3">Long text...</p> + +{/* Allow wrapping */} +<p className="break-words">Long text...</p> +``` + +### Responsive Support + +```jsx +{/* Mobile-first responsive */} +<div className=" + flex flex-col gap-4 + md:flex-row md:gap-6 + lg:gap-8 +"> + <div className="w-full md:w-1/2 lg:w-1/3"> + Content + </div> +</div> +``` + +### Spacing Unification (Tailwind Config) + +```javascript +// tailwind.config.js +module.exports = { + theme: { + extend: { + spacing: { + '18': '4.5rem', + '22': '5.5rem', + }, + }, + }, +} +``` + +### Accessibility Improvements + +```jsx +{/* Add focus state */} +<button className=" + bg-blue-500 text-white + hover:bg-blue-600 + focus:outline-none focus:ring-2 focus:ring-blue-500 focus:ring-offset-2 +"> + Button +</button> + +{/* Improve contrast */} +<p className="text-gray-700 bg-white"> {/* Changed from text-gray-500 */} + Readable text +</p> +``` + +--- + +## React + CSS Modules + +### Fixes in Module Scope + +```css +/* Component.module.css */ + +/* Before */ +.container { + display: flex; +} + +/* After: Add overflow control */ +.container { + display: flex; + flex-wrap: wrap; + overflow: hidden; + max-width: 100%; +} +``` + +### Component-side Fixes + +```jsx +// Component.jsx +import styles from './Component.module.css'; + +// Before +<div className={styles.container}> + +// After: Add conditional class +<div className={`${styles.container} ${isOverflow ? styles.overflow : ''}`}> +``` + +--- + +## styled-components / Emotion + +### Style Fixes + +```jsx +// Before +const Container = styled.div` + width: 100%; +`; + +// After +const Container = styled.div` + width: 100%; + max-width: 100%; + overflow-x: hidden; + + @media (max-width: 768px) { + padding: 1rem; + } +`; +``` + +### Responsive Support + +```jsx +const Card = styled.div` + display: grid; + grid-template-columns: repeat(3, 1fr); + gap: 1.5rem; + + @media (max-width: 1024px) { + grid-template-columns: repeat(2, 1fr); + } + + @media (max-width: 640px) { + grid-template-columns: 1fr; + gap: 1rem; + } +`; +``` + +### Consistency with Theme + +```jsx +// theme.js +export const theme = { + colors: { + primary: '#2563eb', + text: '#1f2937', + textLight: '#4b5563', // Improved contrast + }, + spacing: { + sm: '0.5rem', + md: '1rem', + lg: '1.5rem', + }, +}; + +// Usage +const Text = styled.p` + color: ${({ theme }) => theme.colors.text}; + margin-bottom: ${({ theme }) => theme.spacing.md}; +`; +``` + +--- + +## Vue (Scoped Styles) + +### Fixing Scoped Styles + +```vue +<template> + <div class="container"> + <p class="text">Content</p> + </div> +</template> + +<style scoped> +/* Applied only to this component */ +.container { + max-width: 100%; + overflow: hidden; +} + +.text { + /* Fix: Improve contrast */ + color: #374151; /* Was: #9ca3af */ +} + +/* Responsive */ +@media (max-width: 768px) { + .container { + padding: 1rem; + } +} +</style> +``` + +### Deep Selectors (Affecting Child Components) + +```vue +<style scoped> +/* Override child component styles (use cautiously) */ +:deep(.child-class) { + margin-bottom: 1rem; +} +</style> +``` + +--- + +## Next.js / App Router + +### Global Style Fixes + +```css +/* app/globals.css */ +:root { + --foreground: #171717; + --background: #ffffff; +} + +/* Prevent layout overflow */ +html, body { + max-width: 100vw; + overflow-x: hidden; +} + +/* Prevent image overflow */ +img { + max-width: 100%; + height: auto; +} +``` + +### Fixes in Layout Components + +```tsx +// app/layout.tsx +export default function RootLayout({ children }) { + return ( + <html lang="en"> + <body className="min-h-screen flex flex-col"> + <header className="sticky top-0 z-50"> + {/* Header */} + </header> + <main className="flex-1 container mx-auto px-4 py-8"> + {children} + </main> + <footer> + {/* Footer */} + </footer> + </body> + </html> + ); +} +``` + +--- + +## Common Patterns + +### Fixing Flexbox Layout Issues + +```css +/* Before: Items overflow */ +.flex-container { + display: flex; + gap: 1rem; +} + +/* After: Wrap and size control */ +.flex-container { + display: flex; + flex-wrap: wrap; + gap: 1rem; +} + +.flex-item { + flex: 1 1 300px; /* grow, shrink, basis */ + min-width: 0; /* Prevent flexbox overflow issues */ +} +``` + +### Fixing Grid Layout Issues + +```css +/* Before: Fixed column count */ +.grid-container { + display: grid; + grid-template-columns: repeat(4, 1fr); +} + +/* After: Auto-adjust */ +.grid-container { + display: grid; + grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); + gap: 1.5rem; +} +``` + +### Organizing z-index + +```css +/* Systematize z-index */ +:root { + --z-dropdown: 100; + --z-sticky: 200; + --z-modal-backdrop: 300; + --z-modal: 400; + --z-tooltip: 500; +} + +.modal { + z-index: var(--z-modal); +} +``` + +### Adding Focus States + +```css +/* Add focus state to all interactive elements */ +button:focus-visible, +a:focus-visible, +input:focus-visible, +select:focus-visible, +textarea:focus-visible { + outline: 2px solid #2563eb; + outline-offset: 2px; +} + +/* Customize focus ring */ +.custom-focus:focus-visible { + outline: none; + box-shadow: 0 0 0 3px rgba(37, 99, 235, 0.5); +} +``` + +--- + +## Debugging Techniques + +### Visualizing Element Boundaries + +```css +/* Use only during development */ +* { + outline: 1px solid red !important; +} +``` + +### Detecting Overflow + +```javascript +// Run in console to detect overflow elements +document.querySelectorAll('*').forEach(el => { + if (el.scrollWidth > el.clientWidth) { + console.log('Horizontal overflow:', el); + } + if (el.scrollHeight > el.clientHeight) { + console.log('Vertical overflow:', el); + } +}); +``` + +### Checking Contrast Ratio + +```javascript +// Use Chrome DevTools Lighthouse or axe DevTools +// Or check at the following site: +// https://webaim.org/resources/contrastchecker/ +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/references/visual-checklist.md b/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/references/visual-checklist.md new file mode 100644 index 0000000..24346c5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/web-design-reviewer/references/visual-checklist.md @@ -0,0 +1,236 @@ +# Visual Inspection Checklist + +This document is a comprehensive checklist of items to verify during web design visual inspection. + +--- + +## 1. Layout Verification + +### Structural Integrity + +- [ ] Header is correctly fixed/positioned at the top of the screen +- [ ] Footer is positioned at the bottom of the screen or end of content +- [ ] Main content area is center-aligned with appropriate width +- [ ] Sidebar (if present) is positioned correctly +- [ ] Navigation is displayed in the intended position + +### Overflow + +- [ ] Horizontal scrollbar is not unintentionally displayed +- [ ] Content does not overflow from parent elements +- [ ] Images fit within parent containers +- [ ] Tables do not exceed container width +- [ ] Code blocks wrap or scroll appropriately + +### Alignment + +- [ ] Grid items are evenly distributed +- [ ] Flex item alignment is correct +- [ ] Text alignment (left/center/right) is consistent +- [ ] Icons and text are vertically aligned +- [ ] Form labels and input fields are correctly positioned + +--- + +## 2. Typography Verification + +### Readability + +- [ ] Body text font size is sufficient (minimum 16px recommended) +- [ ] Line height is appropriate (1.5-1.8 recommended) +- [ ] Characters per line is appropriate (40-80 characters recommended) +- [ ] Spacing between paragraphs is sufficient +- [ ] Heading size hierarchy is clear + +### Text Handling + +- [ ] Long words wrap appropriately +- [ ] URLs and code are handled properly +- [ ] No text clipping occurs +- [ ] Ellipsis (...) displays correctly +- [ ] Language-specific line breaking rules work correctly + +### Fonts + +- [ ] Web fonts load correctly +- [ ] Fallback fonts are appropriate +- [ ] Font weights are as intended +- [ ] Special characters and emoji display correctly + +--- + +## 3. Color & Contrast Verification + +### Accessibility (WCAG Standards) + +- [ ] Body text: Contrast ratio 4.5:1 or higher (AA) +- [ ] Large text (18px+ bold or 24px+): 3:1 or higher +- [ ] Interactive element borders: 3:1 or higher +- [ ] Focus indicators: Sufficient contrast with background + +### Color Consistency + +- [ ] Brand colors are unified +- [ ] Link colors are consistent +- [ ] Error state red is unified +- [ ] Success state green is unified +- [ ] Hover/active state colors are appropriate + +### Color Vision Diversity + +- [ ] Information conveyed by shape and text, not just color +- [ ] Charts and diagrams consider color vision diversity +- [ ] Error messages don't rely solely on color + +--- + +## 4. Responsive Verification + +### Mobile (~640px) + +- [ ] Content fits within screen width +- [ ] Touch targets are 44x44px or larger +- [ ] Text is readable size +- [ ] No horizontal scrolling occurs +- [ ] Navigation is mobile-friendly (hamburger menu, etc.) +- [ ] Form inputs are easy to use + +### Tablet (641px~1024px) + +- [ ] Layout is optimized for tablet +- [ ] Two-column layouts display appropriately +- [ ] Image sizes are appropriate +- [ ] Sidebar show/hide is appropriate + +### Desktop (1025px~) + +- [ ] Maximum width is set and doesn't break on extra-large screens +- [ ] Spacing is sufficient +- [ ] Multi-column layouts function correctly +- [ ] Hover states are implemented + +### Breakpoint Transitions + +- [ ] Layout transitions smoothly when screen size changes +- [ ] Layout doesn't break at intermediate sizes +- [ ] No content disappears or duplicates + +--- + +## 5. Interactive Element Verification + +### Buttons + +- [ ] Default state is clear +- [ ] Hover state exists (desktop) +- [ ] Focus state is visually clear +- [ ] Active (pressed) state exists +- [ ] Disabled state is distinguishable +- [ ] Loading state (if applicable) + +### Links + +- [ ] Links are visually identifiable +- [ ] Visited links are distinguishable (if needed) +- [ ] Hover state exists +- [ ] Focus state is clear + +### Form Elements + +- [ ] Input field boundaries are clear +- [ ] Placeholder text contrast is appropriate +- [ ] Visual feedback on focus +- [ ] Error state display +- [ ] Required field indication +- [ ] Dropdowns function correctly + +--- + +## 6. Images & Media Verification + +### Images + +- [ ] Images display at appropriate size +- [ ] Aspect ratio is maintained +- [ ] High resolution display support (@2x) +- [ ] Display when image fails to load +- [ ] Lazy loading behavior works + +### Video & Embeds + +- [ ] Videos fit within containers +- [ ] Aspect ratio is maintained +- [ ] Embedded content is responsive +- [ ] iframes don't overflow + +--- + +## 7. Accessibility Verification + +### Keyboard Navigation + +- [ ] All interactive elements accessible via Tab key +- [ ] Focus order is logical +- [ ] Focus traps are appropriate (modals, etc.) +- [ ] Skip to content link exists + +### Screen Reader Support + +- [ ] Images have alt text +- [ ] Forms have labels +- [ ] ARIA labels are appropriately set +- [ ] Heading hierarchy is correct (h1→h2→h3...) + +### Motion + +- [ ] Animations are not excessive +- [ ] prefers-reduced-motion is supported (if possible) + +--- + +## 8. Performance-related Visual Issues + +### Loading + +- [ ] Font FOUT/FOIT is minimal +- [ ] No layout shift (CLS) occurs +- [ ] No jumping when images load +- [ ] Skeleton screens are appropriate (if applicable) + +### Animation + +- [ ] Animations are smooth (60fps) +- [ ] No performance issues when scrolling +- [ ] Transitions are natural + +--- + +## Priority Matrix + +| Priority | Category | Examples | +|----------|----------|----------| +| P0 (Critical) | Functionality breaking | Complete element overlap, content disappearance | +| P1 (High) | Serious UX issues | Unreadable text, inoperable buttons | +| P2 (Medium) | Moderate issues | Alignment issues, spacing inconsistencies | +| P3 (Low) | Minor issues | Slight positioning differences, minor color variations | + +--- + +## Verification Tools + +### Browser DevTools + +- Elements panel: DOM and style inspection +- Lighthouse: Performance and accessibility audits +- Device toolbar: Responsive testing + +### Accessibility Tools + +- axe DevTools +- WAVE +- Color Contrast Analyzer + +### Automation Tools + +- Playwright (screenshot comparison) +- Percy / Chromatic (Visual Regression Testing) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/LICENSE.txt b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/LICENSE.txt new file mode 100644 index 0000000..7a4a3ea --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/LICENSE.txt @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs. +license: Complete terms in LICENSE.txt +version: 0.1.0 +--- + +# Web Application Testing + +To test local web applications, write native Python Playwright scripts. + +**Helper Scripts Available**: +- `scripts/with_server.py` - Manages server lifecycle (supports multiple servers) + +**Always run scripts with `--help` first** to see usage. DO NOT read the source until you try running the script first and find that a customized solution is abslutely necessary. These scripts can be very large and thus pollute your context window. They exist to be called directly as black-box scripts rather than ingested into your context window. + +## Decision Tree: Choosing Your Approach + +``` +User task → Is it static HTML? + ├─ Yes → Read HTML file directly to identify selectors + │ ├─ Success → Write Playwright script using selectors + │ └─ Fails/Incomplete → Treat as dynamic (below) + │ + └─ No (dynamic webapp) → Is the server already running? + ├─ No → Run: python scripts/with_server.py --help + │ Then use the helper + write simplified Playwright script + │ + └─ Yes → Reconnaissance-then-action: + 1. Navigate and wait for networkidle + 2. Take screenshot or inspect DOM + 3. Identify selectors from rendered state + 4. Execute actions with discovered selectors +``` + +## Example: Using with_server.py + +To start a server, run `--help` first, then use the helper: + +**Single server:** +```bash +python scripts/with_server.py --server "npm run dev" --port 5173 -- python your_automation.py +``` + +**Multiple servers (e.g., backend + frontend):** +```bash +python scripts/with_server.py \ + --server "cd backend && python server.py" --port 3000 \ + --server "cd frontend && npm run dev" --port 5173 \ + -- python your_automation.py +``` + +To create an automation script, include only Playwright logic (servers are managed automatically): +```python +from playwright.sync_api import sync_playwright + +with sync_playwright() as p: + browser = p.chromium.launch(headless=True) # Always launch chromium in headless mode + page = browser.new_page() + page.goto('http://localhost:5173') # Server already running and ready + page.wait_for_load_state('networkidle') # CRITICAL: Wait for JS to execute + # ... your automation logic + browser.close() +``` + +## Reconnaissance-Then-Action Pattern + +1. **Inspect rendered DOM**: + ```python + page.screenshot(path='/tmp/inspect.png', full_page=True) + content = page.content() + page.locator('button').all() + ``` + +2. **Identify selectors** from inspection results + +3. **Execute actions** using discovered selectors + +## Common Pitfall + +❌ **Don't** inspect the DOM before waiting for `networkidle` on dynamic apps +✅ **Do** wait for `page.wait_for_load_state('networkidle')` before inspection + +## Best Practices + +- **Use bundled scripts as black boxes** - To accomplish a task, consider whether one of the scripts available in `scripts/` can help. These scripts handle common, complex workflows reliably without cluttering the context window. Use `--help` to see usage, then invoke directly. +- Use `sync_playwright()` for synchronous scripts +- Always close the browser when done +- Use descriptive selectors: `text=`, `role=`, CSS selectors, or IDs +- Add appropriate waits: `page.wait_for_selector()` or `page.wait_for_timeout()` + +## Reference Files + +- **examples/** - Examples showing common patterns: + - `element_discovery.py` - Discovering buttons, links, and inputs on a page + - `static_html_automation.py` - Using file:// URLs for local HTML + - `console_logging.py` - Capturing console logs during automation diff --git a/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/console_logging.py b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/console_logging.py new file mode 100644 index 0000000..9329b5e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/console_logging.py @@ -0,0 +1,35 @@ +from playwright.sync_api import sync_playwright + +# Example: Capturing console logs during browser automation + +url = 'http://localhost:5173' # Replace with your URL + +console_logs = [] + +with sync_playwright() as p: + browser = p.chromium.launch(headless=True) + page = browser.new_page(viewport={'width': 1920, 'height': 1080}) + + # Set up console log capture + def handle_console_message(msg): + console_logs.append(f"[{msg.type}] {msg.text}") + print(f"Console: [{msg.type}] {msg.text}") + + page.on("console", handle_console_message) + + # Navigate to page + page.goto(url) + page.wait_for_load_state('networkidle') + + # Interact with the page (triggers console logs) + page.click('text=Dashboard') + page.wait_for_timeout(1000) + + browser.close() + +# Save console logs to file +with open('/mnt/user-data/outputs/console.log', 'w') as f: + f.write('\n'.join(console_logs)) + +print(f"\nCaptured {len(console_logs)} console messages") +print(f"Logs saved to: /mnt/user-data/outputs/console.log") \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/element_discovery.py b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/element_discovery.py new file mode 100644 index 0000000..917ba72 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/element_discovery.py @@ -0,0 +1,40 @@ +from playwright.sync_api import sync_playwright + +# Example: Discovering buttons and other elements on a page + +with sync_playwright() as p: + browser = p.chromium.launch(headless=True) + page = browser.new_page() + + # Navigate to page and wait for it to fully load + page.goto('http://localhost:5173') + page.wait_for_load_state('networkidle') + + # Discover all buttons on the page + buttons = page.locator('button').all() + print(f"Found {len(buttons)} buttons:") + for i, button in enumerate(buttons): + text = button.inner_text() if button.is_visible() else "[hidden]" + print(f" [{i}] {text}") + + # Discover links + links = page.locator('a[href]').all() + print(f"\nFound {len(links)} links:") + for link in links[:5]: # Show first 5 + text = link.inner_text().strip() + href = link.get_attribute('href') + print(f" - {text} -> {href}") + + # Discover input fields + inputs = page.locator('input, textarea, select').all() + print(f"\nFound {len(inputs)} input fields:") + for input_elem in inputs: + name = input_elem.get_attribute('name') or input_elem.get_attribute('id') or "[unnamed]" + input_type = input_elem.get_attribute('type') or 'text' + print(f" - {name} ({input_type})") + + # Take screenshot for visual reference + page.screenshot(path='/tmp/page_discovery.png', full_page=True) + print("\nScreenshot saved to /tmp/page_discovery.png") + + browser.close() \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/static_html_automation.py b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/static_html_automation.py new file mode 100644 index 0000000..90bbedc --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/examples/static_html_automation.py @@ -0,0 +1,33 @@ +from playwright.sync_api import sync_playwright +import os + +# Example: Automating interaction with static HTML files using file:// URLs + +html_file_path = os.path.abspath('path/to/your/file.html') +file_url = f'file://{html_file_path}' + +with sync_playwright() as p: + browser = p.chromium.launch(headless=True) + page = browser.new_page(viewport={'width': 1920, 'height': 1080}) + + # Navigate to local HTML file + page.goto(file_url) + + # Take screenshot + page.screenshot(path='/mnt/user-data/outputs/static_page.png', full_page=True) + + # Interact with elements + page.click('text=Click Me') + page.fill('#name', 'John Doe') + page.fill('#email', 'john@example.com') + + # Submit form + page.click('button[type="submit"]') + page.wait_for_timeout(500) + + # Take final screenshot + page.screenshot(path='/mnt/user-data/outputs/after_submit.png', full_page=True) + + browser.close() + +print("Static HTML automation completed!") \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/scripts/with_server.py b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/scripts/with_server.py new file mode 100644 index 0000000..431f2eb --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/webapp-testing/scripts/with_server.py @@ -0,0 +1,106 @@ +#!/usr/bin/env python3 +""" +Start one or more servers, wait for them to be ready, run a command, then clean up. + +Usage: + # Single server + python scripts/with_server.py --server "npm run dev" --port 5173 -- python automation.py + python scripts/with_server.py --server "npm start" --port 3000 -- python test.py + + # Multiple servers + python scripts/with_server.py \ + --server "cd backend && python server.py" --port 3000 \ + --server "cd frontend && npm run dev" --port 5173 \ + -- python test.py +""" + +import subprocess +import socket +import time +import sys +import argparse + +def is_server_ready(port, timeout=30): + """Wait for server to be ready by polling the port.""" + start_time = time.time() + while time.time() - start_time < timeout: + try: + with socket.create_connection(('localhost', port), timeout=1): + return True + except (socket.error, ConnectionRefusedError): + time.sleep(0.5) + return False + + +def main(): + parser = argparse.ArgumentParser(description='Run command with one or more servers') + parser.add_argument('--server', action='append', dest='servers', required=True, help='Server command (can be repeated)') + parser.add_argument('--port', action='append', dest='ports', type=int, required=True, help='Port for each server (must match --server count)') + parser.add_argument('--timeout', type=int, default=30, help='Timeout in seconds per server (default: 30)') + parser.add_argument('command', nargs=argparse.REMAINDER, help='Command to run after server(s) ready') + + args = parser.parse_args() + + # Remove the '--' separator if present + if args.command and args.command[0] == '--': + args.command = args.command[1:] + + if not args.command: + print("Error: No command specified to run") + sys.exit(1) + + # Parse server configurations + if len(args.servers) != len(args.ports): + print("Error: Number of --server and --port arguments must match") + sys.exit(1) + + servers = [] + for cmd, port in zip(args.servers, args.ports): + servers.append({'cmd': cmd, 'port': port}) + + server_processes = [] + + try: + # Start all servers + for i, server in enumerate(servers): + print(f"Starting server {i+1}/{len(servers)}: {server['cmd']}") + + # Use shell=True to support commands with cd and && + process = subprocess.Popen( + server['cmd'], + shell=True, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE + ) + server_processes.append(process) + + # Wait for this server to be ready + print(f"Waiting for server on port {server['port']}...") + if not is_server_ready(server['port'], timeout=args.timeout): + raise RuntimeError(f"Server failed to start on port {server['port']} within {args.timeout}s") + + print(f"Server ready on port {server['port']}") + + print(f"\nAll {len(servers)} server(s) ready") + + # Run the command + print(f"Running: {' '.join(args.command)}\n") + result = subprocess.run(args.command) + sys.exit(result.returncode) + + finally: + # Clean up all servers + print(f"\nStopping {len(server_processes)} server(s)...") + for i, process in enumerate(server_processes): + try: + process.terminate() + process.wait(timeout=5) + except subprocess.TimeoutExpired: + process.kill() + process.wait() + print(f"Server {i+1} stopped") + print("All servers stopped") + + +if __name__ == '__main__': + main() \ No newline at end of file diff --git a/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/SKILL.md new file mode 100644 index 0000000..cb4d23d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/SKILL.md @@ -0,0 +1,229 @@ +--- +name: writing-anti-ai +description: This skill should be used when the user asks to "remove AI writing patterns", "humanize this text", "make this sound more natural", "remove AI-generated traces", "fix robotic writing", or needs to eliminate AI writing patterns from prose. Supports both English and Chinese text. Based on Wikipedia's "Signs of AI writing" guide, detects and fixes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, AI vocabulary, negative parallelisms, and excessive conjunctive phrases. +version: 1.0.0 +author: gaoruizhang +license: MIT +tags: [Writing, AI, Anti-AI, Humanizer] +--- + +# Writing Anti-AI + +Remove AI-generated writing patterns from text to make it sound natural and human-written. Supports both English and Chinese. + +## Overview + +This skill identifies and eliminates predictable AI writing patterns from prose, based on [Wikipedia: Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing), maintained by WikiProject AI Cleanup. + +**Core insight**: LLMs use statistical algorithms to predict what should come next. The result tends toward the most statistically likely outcome that applies to the widest variety of cases—creating detectable patterns. + +## When to Use This Skill + +**Trigger phrases:** +- "Humanize this text" / "人性化处理这段文字" +- "Remove AI writing patterns" / "去除 AI 写作痕迹" +- "Make this sound more natural" / "让这段文字更自然" +- "This sounds robotic/AI-generated" / "这听起来像机器写的" +- "Fix the AI patterns" / "修复 AI 模式" + +**Use cases:** +- Editing AI-generated content to sound human +- Reviewing text for AI patterns before publication +- Polishing academic or professional writing +- Removing "slop" from prose + +## Core Rules (快速检查清单) + +### 1. Cut Filler Phrases +Remove throat-clearing openers and emphasis crutches. + +**English examples**: +- "In order to achieve this goal" → "To achieve this" +- "Due to the fact that" → "Because" +- "It is important to note that" → (delete) + +**中文示例**: +- "为了实现这一目标" → "为了实现这一点" +- "值得注意的是" → (删除) +- "基于……的事实" → "因为" + +### 2. Break Formulaic Structures +Avoid binary contrasts, dramatic fragmentation, rhetorical setups. + +**Patterns to avoid**: +- Negative parallelisms: "It's not just X, it's Y" +- Rule of three: "A, B, and C" (prefer two or four items) +- Em-dash reveals: "X—Y" (just use commas) + +### 3. Vary Rhythm +Mix sentence lengths. End paragraphs differently. + +**Check**: +- Three consecutive sentences same length? Break one. +- Paragraph ends with punchy one-liner? Vary it. + +### 4. Trust Readers +State facts directly. Skip softening, justification, hand-holding. + +**Bad**: "It could potentially be argued that the policy might have some effect." +**Good**: "The policy may affect outcomes." + +### 5. Cut Quotables +If it sounds like a pull-quote, rewrite it. + +**Bad**: "This represents a major step in the right direction." +**Good**: "The company plans to open two more locations." + +## Common AI Patterns (常见 AI 模式) + +### Content Patterns (内容模式) + +| Pattern | Description | 中文描述 | +|---------|-------------|----------| +| **Undue emphasis** | "stands as a testament", "crucial role" | "作为……的证明"，"关键作用" | +| **Promotional language** | "vibrant", "rich heritage", "breathtaking" | "充满活力的"，"丰富遗产"，"令人叹为观止" | +| **Vague attributions** | "Experts believe", "Observers note" | "专家认为"，"观察者指出" | +| **Superficial -ing analyses** | "highlighting the importance", "ensuring that" | "强调……的重要性"，"确保……" | +| **Formulaic "challenges" sections** | "Despite X, faces challenges" | "尽管……面临挑战" | + +### Language Patterns (语言模式) + +| Pattern | Description | 中文描述 | +|---------|-------------|----------| +| **AI vocabulary** | Additionally, crucial, delve, enhance, landscape | 此外，至关重要，深入探讨，增强，格局 | +| **Copula avoidance** | "serves as", "stands for", "represents" | "作为"，"代表"，"充当" | +| **Em dash overuse** | Using — more than humans | 过度使用破折号 | +| **Rule of three** | Forcing ideas into groups of three | 强行三段式 | +| **Elegant variation** | Excessive synonym substitution | 过度换词 | + +For comprehensive pattern lists, see: +- **`references/patterns-english.md`** - Complete English pattern reference +- **`references/patterns-chinese.md`** - Complete Chinese pattern reference + +## Personality and Soul (注入灵魂) + +Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as obvious. + +### Signs of soulless writing: +- Every sentence is the same length and structure +- No opinions, just neutral reporting +- No acknowledgment of uncertainty or mixed feelings +- No first-person perspective when appropriate +- No humor, no edge, no personality + +### How to add voice: + +**Have opinions.** Don't just report facts—react to them. + +> "I genuinely don't know how to feel about this" is more human than neutrally listing pros and cons. + +**Vary your rhythm.** Short punchy sentences. Then longer ones that take their time. + +**Acknowledge complexity.** Real humans have mixed feelings. + +> "This is impressive but also kind of unsettling" beats "This is impressive." + +**Use "I" when it fits.** First person isn't unprofessional—it's honest. + +> "I keep coming back to..." signals a real person thinking. + +**中文示例**： +> "我真的不知道该怎么看待这件事"比中立地列出利弊更有人味。 +> +> "这令人印象深刻但也有点不安"胜过"这令人印象深刻"。 + +## Workflow (工作流程) + +### For English Text: + +1. **Identify patterns** - Scan for AI patterns listed above +2. **Rewrite sections** - Replace AI-isms with natural alternatives +3. **Preserve meaning** - Keep core message intact +4. **Maintain voice** - Match intended tone (formal, casual, technical) +5. **Add soul** - Inject personality and opinions + +### For Chinese Text (中文文本): + +1. **识别 AI 模式** - 扫描上述列出的模式 +2. **重写问题片段** - 用自然替代方案替换 +3. **保留含义** - 保持核心信息完整 +4. **维持语调** - 匹配预期的语气（正式、随意、技术） +5. **注入灵魂** - 添加个性和观点 + +## Quick Scoring (快速评分) + +Rate the text 1-10 on each dimension (总分 50): + +| Dimension | Question | 问题 | Score | +|-----------|----------|------|-------| +| **Directness** | Direct statements or announcements? | 直接陈述还是绕圈宣告？ | /10 | +| **Rhythm** | Varied or metronomic? | 节奏变化还是机械重复？ | /10 | +| **Trust** | Respects reader intelligence? | 尊重读者智慧吗？ | /10 | +| **Authenticity** | Sounds human? | 听起来像真人吗？ | /10 | +| **Density** | Anything cuttable? | 有可删减的内容吗？ | /10 | + +**Standard**: +- 45-50: Excellent, AI patterns removed +- 35-44: Good, room for improvement +- Below 35: Needs revision + +## Examples (示例) + +See **`examples/`** for before/after transformations: +- **`examples/english.md`** - English text examples +- **`examples/chinese.md`** - Chinese text examples + +## Quick Reference (快速参考) + +### English - Common Fixes: +| Before | After | +|--------|-------| +| "serves as a testament to" | "shows" | +| "Moreover, it provides" | "It adds" | +| "It's not just X, it's Y" | "X does Y" | +| "Industry experts believe" | "According to [specific source]" | + +### 中文 - 常见修复： +| 改写前 | 改写后 | +|--------|--------| +| "作为……的证明" | "表明" | +| "此外，……提供了" | "……增加了" | +| "这不仅仅是……而是……" | "……是……" | +| "专家认为" | "根据[具体来源]" | + +## Additional Resources + +### Reference Files +- **`references/patterns-english.md`** - Complete English pattern reference +- **`references/patterns-chinese.md`** - 完整中文模式参考 +- **`references/phrases-to-cut.md`** - Filler phrases to remove (需删除的填充短语) +- **`references/wikipedia-source.md`** - Original Wikipedia source material + +### Example Files +- **`examples/english.md`** - English before/after examples +- **`examples/chinese.md`** - 中文改写示例 + +## Best Practices + +✅ **DO**: +- Combine pattern detection with soul injection +- Support both English and Chinese +- Use progressive disclosure (core rules here, details in references/) +- Vary sentence structure and rhythm +- Add specific details instead of vague claims +- Use simple constructions (is/are/have) where appropriate + +❌ **DON'T**: +- Just remove patterns without adding voice +- Leave stereotypic structures intact +- Over-correct and lose the original meaning +- Ignore language-specific patterns +- Make all sentences the same length + +## License + +MIT + +## Attribution + +Based on [Wikipedia: Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia/Signs_of_AI_writing), maintained by WikiProject AI Cleanup. Merges content from `humanizer`, `humanizer-zh`, and `stop-slop` skills. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/examples/chinese.md b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/examples/chinese.md new file mode 100644 index 0000000..56deff7 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/examples/chinese.md @@ -0,0 +1,83 @@ +# 中文示例 - 改写前后 + +中文文本改写示例。 + +## 示例 1：软件更新公告 + +### 改写前（AI 味道）： +> 新的软件更新作为公司致力于创新的证明。此外，它提供了无缝、直观和强大的用户体验——确保用户能够高效地完成目标。这不仅仅是一次更新，而是我们思考生产力方式的革命。行业专家认为这将对整个行业产生持久影响，彰显了公司在不断演变的技术格局中的关键作用。 + +### 改写后（人性化）： +> 软件更新添加了批处理、键盘快捷键和离线模式。来自测试用户的早期反馈是积极的，大多数报告任务完成速度更快。 + +**所做更改**： +- 删除了"作为……的证明"（夸大的象征意义） +- 删除了"此外"（AI 词汇） +- 删除了"无缝、直观和强大"（三段式法则 + 宣传性） +- 删除了破折号和"-确保"短语（肤浅分析） +- 删除了"这不仅仅是……而是……"（否定式排比） +- 删除了"行业专家认为"（模糊归因） +- 删除了"关键作用"和"不断演变的格局"（AI 词汇） +- 添加了具体功能和具体反馈 + +--- + +## 示例 2：旅游描述 + +### 改写前： +> 坐落在托斯卡纳令人叹为观止的区域内，这个村庄作为意大利丰富文化遗产的充满活力的证明。拥有仅 2000 名居民，它作为寻求灵感的艺术家们的焦点，象征着意大利乡村持久之美的起伏山丘和柏树-lined 道路反映了这一点。 + +### 改写后： +> 这个村庄在托斯卡纳，有 2000 名居民。许多艺术家来此参观，描绘周围的山丘和柏树。 + +--- + +## 示例 3：科技公司简介 + +### 改写前： +> 此外，公司对培养创新的承诺通过其广泛的专利组合得到强调，该组合涵盖了从量子计算到可持续能源解决方案的开创性技术。这种多方面的方法使公司在行业不断演变的格局中处于前沿地位。 + +### 改写后： +> 该公司拥有 127 项专利，主要在量子计算和可持续能源领域。去年授予了六项专利。 + +--- + +## 示例 4：学术摘要 + +### 改写前： +> 本研究作为对社交媒体使用与青少年心理健康结果之间相互作用的全面考察。强调了在线参与模式与心理健康之间的复杂关系，研究强调了父母调解在减轻潜在不良影响中的关键作用。 + +### 改写后： +> 我们调查了 500 名青少年的社交媒体使用和心理健康。每日使用量越高，焦虑报告越多。父母设置屏幕时间限制的青少年焦虑得分低 40%。 + +--- + +## 示例 5：产品发布 + +### 改写前： +> 此次发布代表了公司追求卓越旅程中的重要里程碑。此外，它展示了组织对提供体现质量和创新的产品的坚定承诺。行业观察人士指出，此次发布可能会重塑竞争格局。 + +### 改写后： +> 该产品明天发布。售价 299 美元，将在 12 个国家销售。预订量比上一代高出 20%。 + +--- + +## 评分示例 + +### 示例 A（评分：48/50 - 优秀）： +> 图书馆去年增加了 5 万本书。会员增长了 12%。我一直在回去——这是附近唯一安静的地方。 + +**为什么有效**： +- 直接的事实（具体数字） +- 句子长度变化 +- 第一人称观点（"我一直在回去"） +- 简单的语言 + +### 示例 B（评分：28/50 - 需要改进）： +> 图书馆作为知识的灯塔，象征着社区对智力增长的持久承诺。此外，它拥有广泛的收藏，强调了其在教育格局中的关键作用。 + +**为什么失败**： +- 模糊和夸张 +- AI 词汇（"此外"，"关键作用"，"格局"） +- 没有具体细节 +- 没有人性化的声音 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/examples/english.md b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/examples/english.md new file mode 100644 index 0000000..444643f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/examples/english.md @@ -0,0 +1,83 @@ +# English Examples - Before and After + +英文文本改写示例。 + +## Example 1: Software Update Announcement + +### Before (AI-sounding): +> The new software update serves as a testament to the company's commitment to innovation. Moreover, it provides a seamless, intuitive, and powerful user experience—ensuring that users can accomplish their goals efficiently. It's not just an update, it's a revolution in how we think about productivity. Industry experts believe this will have a lasting impact on the entire sector, highlighting the company's pivotal role in the evolving technological landscape. + +### After (Humanized): +> The software update adds batch processing, keyboard shortcuts, and offline mode. Early feedback from beta testers has been positive, with most reporting faster task completion. + +**Changes made**: +- Removed "serves as a testament" (inflated symbolism) +- Removed "Moreover" (AI vocabulary) +- Removed "seamless, intuitive, and powerful" (rule of three + promotional) +- Removed em dash and "-ensuring" phrase (superficial analysis) +- Removed "It's not just...it's..." (negative parallelism) +- Removed "Industry experts believe" (vague attribution) +- Removed "pivotal role" and "evolving landscape" (AI vocabulary) +- Added specific features and concrete feedback + +--- + +## Example 2: Travel Description + +### Before: +> Nestled within the breathtaking region of Tuscany, the village stands as a vibrant testament to Italy's rich cultural heritage. Boasting a population of just 2,000 residents, it serves as a focal point for artists seeking inspiration from the rolling hills and cypress-lined roads that symbolize the enduring beauty of the Italian countryside. + +### After: +> The village is in Tuscany and has 2,000 residents. Many artists visit to paint the surrounding hills and cypress trees. + +--- + +## Example 3: Tech Company Profile + +### Before: +> Additionally, the company's commitment to fostering innovation is underscored by its extensive patent portfolio, which encompasses groundbreaking technologies ranging from quantum computing to sustainable energy solutions. This multifaceted approach positions the firm at the forefront of the industry's evolving landscape. + +### After: +> The company holds 127 patents, mostly in quantum computing and sustainable energy. Six patents were granted last year. + +--- + +## Example 4: Academic Abstract + +### Before: +> This study serves as a comprehensive examination of the interplay between social media usage and adolescent mental health outcomes. Highlighting the intricate relationship between online engagement patterns and psychological wellbeing, the research underscores the crucial role of parental mediation in mitigating potential adverse effects. + +### After: +> We surveyed 500 teenagers about their social media use and mental health. Higher daily usage correlated with increased anxiety reports. Teens whose parents set screen-time limits showed 40% lower anxiety scores. + +--- + +## Example 5: Product Launch + +### Before: +> The launch represents a significant milestone in the company's journey toward excellence. Moreover, it showcases the organization's unwavering dedication to delivering products that epitomize quality and innovation. Industry observers have noted that this release could potentially reshape the competitive landscape. + +### After: +> The product launches tomorrow. It costs $299 and will be sold in 12 countries. Pre-orders are 20% higher than the previous model. + +--- + +## Scoring Examples + +### Example A (Score: 48/50 - Excellent): +> The library added 50,000 books last year. Membership grew by 12%. I keep going back—it's the only quiet place in my neighborhood. + +**Why it works**: +- Direct facts (specific numbers) +- Varied sentence length +- First-person opinion ("I keep going back") +- Simple language + +### Example B (Score: 28/50 - Needs work): +> The library serves as a beacon of knowledge, symbolizing the community's enduring commitment to intellectual growth. Moreover, it boasts an extensive collection that underscores its pivotal role in the educational landscape. + +**Why it fails**: +- Vague and puffery +- AI vocabulary ("Moreover", "pivotal role", "landscape") +- No specific details +- No human voice diff --git a/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/patterns-chinese.md b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/patterns-chinese.md new file mode 100644 index 0000000..089d064 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/patterns-chinese.md @@ -0,0 +1,242 @@ +# 中文 AI 写作模式 - 完整参考 + +Complete Chinese AI Writing Patterns Reference. + +## 内容模式 (CONTENT PATTERNS) + +### 1. 过度强调意义、遗产和更广泛的趋势 + +**需要注意的词汇**：作为/充当、标志着/见证、是……的体现/证明/提醒、极其重要的/重要的/至关重要的/核心的/关键性的作用/时刻、凸显/强调/彰显了其重要性/意义、反映了更广泛的、象征着其持续的/永恒的/持久的、为……做出贡献、为……奠定基础、标志着/塑造着、代表/标志着一个转变、关键转折点、不断演变的格局、焦点、不可磨灭的印记、深深植根于 + +**改写前**： +> 加泰罗尼亚统计局于 1989 年正式成立，标志着西班牙区域统计演变史上的关键时刻。这一举措是西班牙全国范围内更广泛运动的一部分，旨在分散行政职能并加强区域治理。 + +**改写后**： +> 加泰罗尼亚统计局成立于 1989 年，负责独立于西班牙国家统计局收集和发布区域统计数据。 + +--- + +### 2. 过度强调知名度和媒体报道 + +**需要注意的词汇**：独立报道、地方/区域/国家媒体、由知名专家撰写、活跃的社交媒体账号 + +**改写前**： +> 她的观点被《纽约时报》、BBC、《金融时报》和《印度教徒报》引用。她在社交媒体上拥有活跃的存在，拥有超过 50 万粉丝。 + +**改写后**： +> 在 2024 年《纽约时报》的采访中，她认为 AI 监管应该关注结果而不是方法。 + +--- + +### 3. 以 -ing 结尾的肤浅分析 + +**需要注意的词汇**：突出/强调/彰显……、确保……、反映/象征……、为……做出贡献、培养/促进……、涵盖……、展示…… + +**改写前**： +> 寺庙的蓝色、绿色和金色色调与该地区的自然美景产生共鸣，象征着德克萨斯州的蓝帽花、墨西哥湾和多样化的德克萨斯州景观，反映了社区与土地的深厚联系。 + +**改写后**： +> 寺庙使用蓝色、绿色和金色。建筑师表示这些颜色是为了呼应当地的蓝帽花和墨西哥湾海岸。 + +--- + +### 4. 宣传和广告式语言 + +**需要注意的词汇**：拥有（夸张用法）、充满活力的、丰富的（比喻）、深刻的、增强其、展示、体现、致力于、自然之美、坐落于、位于……的中心、开创性的（比喻）、著名的、令人叹为观止的、必游之地、迷人的 + +**改写前**： +> 坐落在埃塞俄比亚贡德尔地区令人叹为观止的区域内，Alamata Raya Kobo 是一座充满活力的城镇，拥有丰富的文化遗产和迷人的自然美景。 + +**改写后**： +> Alamata Raya Kobo 是埃塞俄比亚贡德尔地区的一座城镇，以其每周集市和 18 世纪教堂而闻名。 + +--- + +### 5. 模糊归因和含糊措辞 + +**需要注意的词汇**：行业报告显示、观察者指出、专家认为、一些批评者认为、多个来源/出版物（实际引用却很少） + +**改写前**： +> 由于其独特的特征，浩来河引起了研究人员和保护主义者的兴趣。专家认为它在区域生态系统中发挥着至关重要的作用。 + +**改写后**： +> 根据中国科学院 2019 年的调查，浩来河支持多种特有鱼类。 + +--- + +### 6. 提纲式的"挑战与未来展望"部分 + +**需要注意的词汇**：尽管其……面临若干挑战……、尽管存在这些挑战、挑战与遗产、未来展望 + +**改写前**： +> 尽管工业繁荣，Korattur 面临着城市地区典型的挑战，包括交通拥堵和水资源短缺。尽管存在这些挑战，凭借其战略位置和正在进行的举措，Korattur 继续蓬勃发展，成为钦奈增长不可或缺的一部分。 + +**改写后**： +> 2015 年三个新 IT 园区开业后，交通拥堵加剧。市政公司于 2022 年启动了雨水排水项目，以解决反复发生的洪水。 + +--- + +## 语言和语法模式 (LANGUAGE PATTERNS) + +### 7. 过度使用的"AI 词汇" + +**高频 AI 词汇**：此外、与……保持一致、至关重要、深入探讨、强调、持久的、增强、培养、获得、突出（动词）、相互作用、复杂/复杂性、关键（形容词）、格局（抽象名词）、关键性的、展示、织锦（抽象名词）、证明、强调（动词）、宝贵的、充满活力的 + +**改写前**： +> 此外，索马里菜肴的一个显著特征是加入骆驼肉。意大利殖民影响的持久证明是当地烹饪格局中广泛采用意大利面，展示了这些菜肴如何融入传统饮食。 + +**改写后**： +> 索马里菜肴还包括骆驼肉，被认为是一种美味。在意大利殖民期间引入的意大利面菜肴仍然很常见，尤其是在南部。 + +--- + +### 8. 避免使用"是"（系动词回避） + +**需要注意的词汇**：作为/代表/标志着/充当 [一个]、拥有/设有/提供 [一个] + +**改写前**： +> Gallery 825 作为 LAAA 的当代艺术展览空间。画廊设有四个独立空间，拥有超过 3000 平方英尺。 + +**改写后**： +> Gallery 825 是 LAAA 的当代艺术展览空间。画廊有四个房间，总面积 3000 平方英尺。 + +--- + +### 9. 否定式排比 + +**改写前**： +> 这不仅仅是节拍在人声下流动；它是攻击性和氛围的一部分。这不仅仅是一首歌，而是一种声明。 + +**改写后**： +> 沉重的节拍增加了攻击性的基调。 + +--- + +### 10. 三段式法则过度使用 + +**改写前**： +> 活动包括主题演讲、小组讨论和社交机会。与会者可以期待创新、灵感和行业洞察。 + +**改写后**： +> 活动包括演讲和小组讨论。会议之间还有非正式社交的时间。 + +--- + +### 11. 刻意换词（同义词循环） + +**改写前**： +> 主人公面临许多挑战。主要角色必须克服障碍。中心人物最终获得胜利。英雄回到家中。 + +**改写后**： +> 主人公面临许多挑战，但最终获得胜利并回到家中。 + +--- + +### 12. 虚假范围 + +**改写前**： +> 我们穿越宇宙的旅程将我们从大爆炸的奇点带到宏伟的宇宙网，从恒星的诞生和死亡到暗物质的神秘舞蹈。 + +**改写后**： +> 这本书涵盖了大爆炸、恒星形成和当前关于暗物质的理论。 + +--- + +## 风格模式 (STYLE PATTERNS) + +### 13. 破折号过度使用 + +**改写前**： +> 这个术语主要由荷兰机构推广——而不是由人民自己。你不会说"荷兰，欧洲"作为地址——但这种错误标记仍在继续——即使在官方文件中。 + +**改写后**： +> 这个术语主要由荷兰机构推广，而不是由人民自己。你不会说"荷兰，欧洲"作为地址，但这种错误标记在官方文件中仍在继续。 + +--- + +### 14. 粗体过度使用 + +**改写前**： +> 它融合了 **OKR（目标和关键结果）**、**KPI（关键绩效指标）** 和视觉战略工具，如 **商业模式画布（BMC）** 和 **平衡计分卡（BSC）**。 + +**改写后**： +> 它融合了 OKR、KPI 和视觉战略工具，如商业模式画布和平衡计分卡。 + +--- + +### 15. 内联标题垂直列表 + +**改写前**： +> - **用户体验：** 用户体验通过新界面得到显著改善。 +> - **性能：** 性能通过优化算法得到增强。 +> - **安全性：** 安全性通过端到端加密得到加强。 + +**改写后**： +> 更新改进了界面，通过优化算法加快了加载时间，并添加了端到端加密。 + +--- + +## 交流模式 (COMMUNICATION PATTERNS) + +### 16. 协作交流痕迹 + +**需要注意的词汇**：希望这对您有帮助、当然！、一定！、您说得完全正确！、您想要……、请告诉我、这是一个…… + +**改写前**： +> 这是法国大革命的概述。希望这对您有帮助！如果您想让我扩展任何部分，请告诉我。 + +**改写后**： +> 法国大革命始于 1789 年，当时财政危机和粮食短缺导致了广泛的动荡。 + +--- + +### 17. 知识截止日期免责声明 + +**需要注意的词汇**：截至 [日期]、根据我最后的训练更新、虽然具体细节有限/稀缺……、基于可用信息…… + +**改写前**： +> 虽然关于公司成立的具体细节在现成资料中没有广泛记录，但它似乎是在 20 世纪 90 年代的某个时候成立的。 + +**改写后**： +> 根据注册文件，该公司成立于 1994 年。 + +--- + +## 填充模式 (FILLER PATTERNS) + +### 18. 填充短语 + +| 改写前 | 改写后 | +|--------|--------| +| "为了实现这一目标" | "为了实现这一点" | +| "由于下雨的事实" | "因为下雨" | +| "在这个时间点" | "现在" | +| "在您需要帮助的情况下" | "如果您需要帮助" | +| "系统具有处理的能力" | "系统可以处理" | +| "值得注意的是数据显示" | "数据显示" | + +--- + +### 19. 过度限定 + +**改写前**： +> 可以潜在地可能被认为该政策可能会对结果产生一些影响。 + +**改写后**： +> 该政策可能会影响结果。 + +--- + +### 20. 通用积极结论 + +**改写前**： +> 公司的未来看起来光明。激动人心的时代即将到来，他们继续追求卓越的旅程。这代表了向正确方向迈出的重要一步。 + +**改写后**： +> 该公司计划明年再开设两个地点。 + +--- + +## 来源 + +[基于维基百科：AI 写作特征](https://en.wikipedia.org/wiki/Wikipedia/Signs_of_AI_writing) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/patterns-english.md b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/patterns-english.md new file mode 100644 index 0000000..0884e09 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/patterns-english.md @@ -0,0 +1,242 @@ +# English AI Writing Patterns - Complete Reference + +完整的英文 AI 写作模式参考指南。 + +## CONTENT PATTERNS (内容模式) + +### 1. Undue Emphasis on Significance (过度强调意义) + +**Words to watch**: stands/serves as, is a testament/reminder, a vital/significant/crucial/pivotal/key role/moment, underscores/highlights its importance/significance, reflects broader, symbolizing its ongoing/enduring/lasting, contributing to the, setting the stage for, marking/shaping the, represents/marks a shift, key turning point, evolving landscape, focal point, indelible mark, deeply rooted + +**Before**: +> The Statistical Institute of Catalonia was officially established in 1989, marking a pivotal moment in the evolution of regional statistics in Spain. This initiative was part of a broader movement across Spain to decentralize administrative functions and enhance regional governance. + +**After**: +> The Statistical Institute of Catalonia was established in 1989 to collect and publish regional statistics independently from Spain's national statistics office. + +--- + +### 2. Undue Emphasis on Notability (过度强调知名度) + +**Words to watch**: independent coverage, local/regional/national media outlets, written by a leading expert, active social media presence + +**Before**: +> Her views have been cited in The New York Times, BBC, Financial Times, and The Hindu. She maintains an active social media presence with over 500,000 followers. + +**After**: +> In a 2024 New York Times interview, she argued that AI regulation should focus on outcomes rather than methods. + +--- + +### 3. Superficial Analyses with -ing Endings (-ing 结尾的肤浅分析) + +**Words to watch**: highlighting/underscoring/emphasizing..., ensuring..., reflecting/symbolizing..., contributing to..., cultivating/fostering..., encompassing..., showcasing... + +**Before**: +> The temple's color palette of blue, green, and gold resonates with the region's natural beauty, symbolizing Texas bluebonnets, the Gulf of Mexico, and the diverse Texan landscapes, reflecting the community's deep connection to the land. + +**After**: +> The temple uses blue, green, and gold colors. The architect said these were chosen to reference local bluebonnets and the Gulf coast. + +--- + +### 4. Promotional Language (宣传性语言) + +**Words to watch**: boasts a, vibrant, rich (figurative), profound, enhancing its, showcasing, exemplifies, commitment to, natural beauty, nestled, in the heart of, groundbreaking (figurative), renowned, breathtaking, must-visit, stunning + +**Before**: +> Nestled within the breathtaking region of Gonder in Ethiopia, Alamata Raya Kobo stands as a vibrant town with a rich cultural heritage and stunning natural beauty. + +**After**: +> Alamata Raya Kobo is a town in the Gonder region of Ethiopia, known for its weekly market and 18th-century church. + +--- + +### 5. Vague Attributions (模糊归因) + +**Words to watch**: Industry reports, Observers have cited, Experts argue, Some critics argue, several sources/publications (when few cited) + +**Before**: +> Due to its unique characteristics, the Haolai River is of interest to researchers and conservationists. Experts believe it plays a crucial role in the regional ecosystem. + +**After**: +> The Haolai River supports several endemic fish species, according to a 2019 survey by the Chinese Academy of Sciences. + +--- + +### 6. Formulaic "Challenges" Sections (公式化的"挑战"部分) + +**Words to watch**: Despite its... faces several challenges..., Despite these challenges, Challenges and Legacy, Future Outlook + +**Before**: +> Despite its industrial prosperity, Korattur faces challenges typical of urban areas, including traffic congestion and water scarcity. Despite these challenges, with its strategic location and ongoing initiatives, Korattur continues to thrive as an integral part of Chennai's growth. + +**After**: +> Traffic congestion increased after 2015 when three new IT parks opened. The municipal corporation began a stormwater drainage project in 2022 to address recurring floods. + +--- + +## LANGUAGE PATTERNS (语言模式) + +### 7. AI Vocabulary (AI 词汇表) + +**High-frequency AI words**: Additionally, align with, crucial, delve, emphasizing, enduring, enhance, fostering, garner, highlight (verb), interplay, intricate/intricacies, key (adjective), landscape (abstract noun), pivotal, showcase, tapestry (abstract noun), testament, underscore (verb), valuable, vibrant + +**Before**: +> Additionally, a distinctive feature of Somali cuisine is the incorporation of camel meat. An enduring testament to Italian colonial influence is the widespread adoption of pasta in the local culinary landscape, showcasing how these dishes have integrated into the traditional diet. + +**After**: +> Somali cuisine also includes camel meat, which is considered a delicacy. Pasta dishes, introduced during Italian colonization, remain common, especially in the south. + +--- + +### 8. Copula Avoidance (回避系动词) + +**Words to watch**: serves as/stands as/marks/represents [a], boasts/features/offers [a] + +**Before**: +> Gallery 825 serves as LAAA's exhibition space for contemporary art. The gallery features four separate spaces and boasts over 3,000 square feet. + +**After**: +> Gallery 825 is LAAA's exhibition space for contemporary art. The gallery has four rooms totaling 3,000 square feet. + +--- + +### 9. Negative Parallelisms (否定式排比) + +**Before**: +> It's not just about the beat riding under the vocals; it's part of the aggression and atmosphere. It's not merely a song, it's a statement. + +**After**: +> The heavy beat adds to the aggressive tone. + +--- + +### 10. Rule of Three (三段式法则) + +**Before**: +> The event features keynote sessions, panel discussions, and networking opportunities. Attendees can expect innovation, inspiration, and industry insights. + +**After**: +> The event includes talks and panels. There's also time for informal networking between sessions. + +--- + +### 11. Elegant Variation (刻意换词) + +**Before**: +> The protagonist faces many challenges. The main character must overcome obstacles. The central figure eventually triumphs. The hero returns home. + +**After**: +> The protagonist faces many challenges but eventually triumphs and returns home. + +--- + +### 12. False Ranges (虚假范围) + +**Before**: +> Our journey through the universe has taken us from the singularity of the Big Bang to the grand cosmic web, from the birth and death of stars to the enigmatic dance of dark matter. + +**After**: +> The book covers the Big Bang, star formation, and current theories about dark matter. + +--- + +## STYLE PATTERNS (风格模式) + +### 13. Em Dash Overuse (破折号过度使用) + +**Before**: +> The term is primarily promoted by Dutch institutions—not by the people themselves. You don't say "Netherlands, Europe" as an address—yet this mislabeling continues—even in official documents. + +**After**: +> The term is primarily promoted by Dutch institutions, not by the people themselves. You don't say "Netherlands, Europe" as an address, yet this mislabeling continues in official documents. + +--- + +### 14. Overuse of Boldface (粗体过度使用) + +**Before**: +> It blends **OKRs (Objectives and Key Results)**, **KPIs (Key Performance Indicators)**, and visual strategy tools such as **Business Model Canvas (BMC)** and **Balanced Scorecard (BSC)**. + +**After**: +> It blends OKRs, KPIs, and visual strategy tools like Business Model Canvas and Balanced Scorecard. + +--- + +### 15. Inline-Header Vertical Lists (内联标题垂直列表) + +**Before**: +> - **User Experience:** The user experience has been significantly improved with a new interface. +> - **Performance:** Performance has been enhanced through optimized algorithms. +> - **Security:** Security has been strengthened with end-to-end encryption. + +**After**: +> The update improves the interface, speeds up load times through optimized algorithms, and adds end-to-end encryption. + +--- + +## COMMUNICATION PATTERNS (交流模式) + +### 16. Collaborative Communication Artifacts (协作交流痕迹) + +**Words to watch**: I hope this helps, Of course!, Certainly!, You're absolutely right!, Would you like..., let me know, here is a... + +**Before**: +> Here is an overview of the French Revolution. I hope this helps! Let me know if you'd like me to expand on any section. + +**After**: +> The French Revolution began in 1789 when financial crisis and food shortages led to widespread unrest. + +--- + +### 17. Knowledge-Cutoff Disclaimers (知识截止免责声明) + +**Words to watch**: as of [date], Up to my last training update, While specific details are limited/scarce..., based on available information... + +**Before**: +> While specific details about the company's founding are not extensively documented in readily available sources, it appears to have been established sometime in the 1990s. + +**After**: +> The company was founded in 1994, according to its registration documents. + +--- + +## FILLER PATTERNS (填充模式) + +### 18. Filler Phrases (填充短语) + +| Before | After | +|--------|-------| +| "In order to achieve this goal" | "To achieve this" | +| "Due to the fact that it was raining" | "Because it was raining" | +| "At this point in time" | "Now" | +| "In the event that you need help" | "If you need help" | +| "The system has the ability to process" | "The system can process" | +| "It is important to note that the data shows" | "The data shows" | + +--- + +### 19. Excessive Hedging (过度限定) + +**Before**: +> It could potentially possibly be argued that the policy might have some effect on outcomes. + +**After**: +> The policy may affect outcomes. + +--- + +### 20. Generic Positive Conclusions (通用积极结论) + +**Before**: +> The future looks bright for the company. Exciting times lie ahead as they continue their journey toward excellence. This represents a major step in the right direction. + +**After**: +> The company plans to open two more locations next year. + +--- + +## Source + +[Based on Wikipedia: Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia/Signs_of_AI_writing) diff --git a/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/phrases-to-cut.md b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/phrases-to-cut.md new file mode 100644 index 0000000..3b1b706 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/phrases-to-cut.md @@ -0,0 +1,15 @@ +# Phrases to Cut + +## English +- it is important to note that +- it should be emphasized that +- due to the fact that +- serves as a testament to +- in today's rapidly evolving landscape + +## 中文 +- 值得注意的是 +- 需要强调的是 +- 基于……的事实 +- 作为……的证明 +- 在当今快速发展的……背景下 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/wikipedia-source.md b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/wikipedia-source.md new file mode 100644 index 0000000..df42df9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/writing-anti-ai/references/wikipedia-source.md @@ -0,0 +1,4 @@ +# Wikipedia Source Note + +This skill is informed by Wikipedia's community-maintained guidance on common signs of AI writing. +Use that source as pattern inspiration, not as a reason to copy phrasing mechanically. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/SKILL.md b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/SKILL.md new file mode 100644 index 0000000..85cd04f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/SKILL.md @@ -0,0 +1,50 @@ +--- +name: zotero-obsidian-bridge +description: Use this skill when Zotero is the literature source of truth and the project KB should receive source notes under Sources/Papers plus project-linked synthesis in Knowledge and Writing. +version: 0.3.0 +--- + +# Zotero Obsidian Bridge + +Use this skill when papers live in Zotero and the project KB should receive project-local notes. + +Default flow: + +```text +Zotero -> Sources/Papers -> Knowledge -> Writing -> Maps/literature.canvas +``` + +Rules: +- one canonical paper note per paper under `Sources/Papers/` +- literature synthesis goes to `Knowledge/` +- writing-oriented outputs go to `Writing/` +- `Maps/literature.canvas` is the default derived graph artifact +- update `_system/registry.md`, `02-Index.md`, and today's `Daily/` after substantial ingestion + +## Evidence extraction requirement + +Core papers and papers with reusable claims should include an evidence record. Abstract-only or placeholder notes may stay in `To-Read` until there is enough evidence to extract a reusable claim. + +```md +## Evidence Record + +Evidence ID: +Source: +Source type: full paper | preprint | dataset | experiment artifact | project note | abstract-only | webpage placeholder +Supports: +Contradicts: +Method / dataset / metric: +Limitation: +Project relevance: +Claim strength: speculative | observed | supported | strong +``` + +Use `../research-ideation/references/research-contract.md` as the shared contract for Evidence Records and claim strength definitions. + +Before synthesis lands in `Knowledge/` or `Writing/`, apply the shared Claim Promotion Gate: +- every promoted claim must point back to an Evidence Record ID, +- source type must be strong enough for the claim, +- abstract-only and webpage-placeholder items cannot support durable claims, +- allowed wording and forbidden stronger wording must be preserved when the claim may later enter a report, manuscript, or rebuttal. + +When synthesis lands in `Knowledge/`, link the supporting paper notes explicitly. Do not promote literature synthesis that cannot point back to source notes. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/examples/example-collection-inventory.md b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/examples/example-collection-inventory.md new file mode 100644 index 0000000..db4de5d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/examples/example-collection-inventory.md @@ -0,0 +1,27 @@ +--- +type: zotero-collection-inventory +collection: Cross Subject +collection_slug: cross-subject +source: zotero +coverage_expected: 3 +coverage_actual: 3 +updated: 2026-03-18T00:00:00Z +--- + +# Cross Subject Inventory + +## Coverage Summary +- Expected items: 3 +- Canonical notes: 3 / 3 + +## Item Mapping +| Zotero Key | Item Title | Canonical Note | Status | +|---|---|---|---| +| ABCDEFGH | Shared Latent Geometry for Cross-Subject Speech Decoding | Sources/Papers/Shared-Latent-Geometry.md | covered | +| HGFEDCBA | Domain Adapters for Neural Transfer | Sources/Papers/Domain-Adapters.md | covered | +| ZXCVBNML | Contrastive Transfer under Low Resource Conditions | Sources/Papers/Contrastive-Transfer.md | covered | + +## Triage +- fully covered: 3 +- bridge-only: 0 +- needs-review: 0 diff --git a/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/COLLECTION-INVENTORY-SCHEMA.md b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/COLLECTION-INVENTORY-SCHEMA.md new file mode 100644 index 0000000..e711d6d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/COLLECTION-INVENTORY-SCHEMA.md @@ -0,0 +1,49 @@ +# Collection Inventory Schema + +Use this note when a Zotero collection is imported or audited at collection scope. + +## Canonical path + +```text +Knowledge/Zotero-Collection-{collection-slug}-Inventory.md +``` + +## Frontmatter + +```yaml +--- +type: zotero-collection-inventory +collection: Cross Subject +collection_slug: cross-subject +source: zotero +coverage_expected: 16 +coverage_actual: 16 +updated: 2026-03-18T00:00:00Z +--- +``` + +## Required sections + +```markdown +# Cross Subject Inventory + +## Coverage Summary +- Expected items: 16 +- Canonical notes: 16 / 16 + +## Item Mapping +| Zotero Key | Item Title | Canonical Note | Status | +|---|---|---|---| +| ABCDEFGH | Example title | Sources/Papers/Example-Paper.md | covered | + +## Triage +- fully covered +- skipped or bridge-only notes +- items that still need full notes +``` + +## Rules +- Keep one durable inventory note per collection slug. +- `Canonical Note` should use project-relative note paths. +- `Status` should use a small vocabulary such as `covered`, `bridge-only`, `skipped`, `needs-review`. +- Update coverage counts whenever the collection is batch-processed again. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/LOCAL-ZOTERO-FALLBACK.md b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/LOCAL-ZOTERO-FALLBACK.md new file mode 100644 index 0000000..5bed8f5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/LOCAL-ZOTERO-FALLBACK.md @@ -0,0 +1,22 @@ +# Local Zotero Fallback + +Use this runbook when the Zotero MCP transport is unavailable but the user still wants a collection-level pass. + +## Preconditions + +- A local `zotero-mcp` checkout or installed Python package is available. +- The local environment can read metadata/fulltext without mutating the Zotero library. + +## Default fallback sequence + +1. Confirm that MCP transport is the failing layer, not the collection query itself. +2. Switch to the local Python-backed path for metadata and fulltext retrieval. +3. Continue creating or updating canonical paper notes. +4. Run `verify_paper_notes.py` before closing the batch. + +## Report explicitly + +Always state: +- that MCP transport failed, +- that the workflow continued through local fallback, +- what remained unavailable, if anything. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/PAPER-NOTE-SCHEMA.md b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/PAPER-NOTE-SCHEMA.md new file mode 100644 index 0000000..675cfd5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/PAPER-NOTE-SCHEMA.md @@ -0,0 +1,85 @@ +# Zotero-Sourced Paper Note Schema + +## Frontmatter + +```yaml +--- +type: paper +project: project-slug +title: "Paper Title" +canvas_visibility: hidden +authors: + - Author A + - Author B +year: 2026 +venue: "NeurIPS" +doi: "10.xxxx/xxxxx" +url: "https://doi.org/..." +citekey: "author2026paper" +zotero_key: "ABCDEFGH" +status: read +source_type: full paper +claim_strength: observed +keywords: + - subject-invariance + - contrastive-learning +concepts: + - shared geometry +methods: + - contrastive pretraining +subfield: speech-transfer +related_papers: + - "Sources/Papers/Another-Paper" +linked_knowledge: + - "Knowledge/Literature Overview" + - "Knowledge/Method Taxonomy" +argument_claims: + - "Shared geometry exists but is fragile" +argument_methods: + - "Geometry-aware transfer" +argument_gaps: + - "Still needs speech-specific validation" +paper_relationships: + - "Sources/Papers/Another-Paper::complements" +updated: 2026-03-16T00:00:00Z +--- +``` + +## Sections + +```markdown +# Paper Title + +## Claim + +## Research question + +## Method + +## Evidence + +Use the shared Evidence Record shape from `research-ideation/references/research-contract.md`. + +## Strengths + +## Limitation + +## Direct relevance to repo + +## Relation to other papers + +## Knowledge links + +## Optional downstream hooks +- Writing: +``` + +## Rules + +- `related_papers` and `linked_knowledge` should prefer project-relative note paths. +- `paper_relationships` should record explicit semantic edges only when they are stable enough to support graph construction. +- `concepts` and `methods` may remain plain strings; do not create dedicated notes by default. +- Keep `Direct relevance to repo` concrete and actionable. +- Prefer one durable canonical note per paper; update in place instead of making sibling notes. +- If the user asked for a full collection pass, normalize the schema across the entire covered set before closing the task. +- Treat Zotero `webpage` items as weak-source inputs by default. If they are abstract-only or placeholder pages, set `source_type: webpage placeholder` or `source_type: abstract-only`, keep `status: to-read`, and do not use them to support `Knowledge`, manuscript, or rebuttal claims. diff --git a/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/WORKFLOW.md b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/WORKFLOW.md new file mode 100644 index 0000000..f6a84bd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/references/WORKFLOW.md @@ -0,0 +1,90 @@ +# Zotero -> Obsidian Workflow + +## 1. Resolve the project + +1. Run the Obsidian project-memory detect flow. +2. If the repo is bound, use its `Research/{project-slug}/` vault root. +3. If not bound but clearly a research repo, bootstrap first. + +## 2. Read from Zotero + +Preferred read path per paper: +1. `zotero_get_item_metadata` +2. `zotero_get_item_fulltext` +3. `zotero_get_annotations` +4. `zotero_get_notes` + +Use metadata + abstract as the minimum fallback when PDF full text is unavailable. +If the MCP transport path is broken but a local `zotero-mcp` source checkout is available, use the local Python fallback to call the same metadata/fulltext functions instead of aborting. +Treat Zotero `webpage` items as weak-source entries unless they clearly expose full paper metadata and useful fulltext. Abstract-only pages and webpage placeholders may be kept for discovery, but they must remain `To-Read` or `weak-source` and cannot support `Knowledge` or manuscript claims until replaced by a full paper, preprint, or verified artifact. + +## 3. Create/update the canonical paper note + +Canonical destination: +- `Sources/Papers/{normalized-title-or-citekey}.md` + +Update instead of duplicating when the note already exists. + +## 4. Detailed reading note requirements + +Each durable paper note should contain: +- claim +- research question / problem +- method +- evidence +- strengths +- limitation +- direct relevance to repo +- links to related papers and the best matching `Knowledge/` notes + +## 5. Synthesize the stable literature knowledge + +After a batch import, prefer agent-first synthesis into `Knowledge/`: +1. update `Knowledge/Literature Overview.md` when the batch yields a stable overview +2. update `Knowledge/Method Taxonomy.md` when method clusters are clear +3. update `Knowledge/Research Gaps.md` when open problems or tensions are stable enough to keep +4. if the source is a named Zotero collection, update a durable inventory note that records: + - collection size, + - triage buckets, + - collection item -> canonical note mapping, + - current coverage such as `16 / 16` + +Apply the Claim Promotion Gate before creating or updating `Knowledge/`: +- every stable claim must cite a canonical paper note and an Evidence Record ID, +- `speculative` and `observed` claims stay as hypotheses, motivations, or open gaps, +- abstract-only or webpage-placeholder items can appear in coverage notes but not as support for durable conclusions, +- if the batch lacks enough evidence records, produce a warning/claim map instead of a polished synthesis. + +## 6. Refresh the default literature canvas + +After batch note creation or major note updates: +1. rebuild `Maps/literature.canvas` +2. ensure core paper notes have meaningful wikilinks into `Knowledge/` +3. keep the graph lightweight and project-facing +4. prefer semantic filtering and edge thinning over dense all-to-all paper links +5. prefer `paper + claim + method + gap` argument-map structure for the main graph +6. add `Maps/literature-main.canvas` only when a second lightweight display graph is genuinely useful +7. preserve edge evidence strength where possible; do not create all-to-all paper links or stable-looking claim edges without source-note support + +## 7. Push downstream only when justified + +- during Zotero ingestion, default to `Sources/Papers/` plus `Knowledge/` +- update `Writing/` only when the user asks for a review, comparison, or draft-facing synthesis and the promoted claims pass the Claim Promotion Gate +- treat `Experiments/` and `Results/` as later project workflows, not default Zotero-import targets + +## 8. Verify before closing + +After batch ingestion or schema refactors: +1. verify every expected paper has a canonical note +2. verify `zotero_key` coverage matches the imported collection +3. verify all covered notes use the same canonical section schema +4. update the project `Daily/` note and project memory with what changed + +Recommended verification command: + +```bash +python3 "${CLAUDE_PLUGIN_ROOT}/skills/zotero-obsidian-bridge/scripts/verify_paper_notes.py" \ + --papers-dir "/absolute/path/to/Sources/Papers" \ + --expected-zotero-keys "KEY1,KEY2,KEY3" \ + --inventory-note "/absolute/path/to/Knowledge/Zotero-Collection-collection-slug-Inventory.md" +``` diff --git a/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/scripts/verify_paper_notes.py b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/scripts/verify_paper_notes.py new file mode 100755 index 0000000..d60e020 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/skills/zotero-obsidian-bridge/scripts/verify_paper_notes.py @@ -0,0 +1,212 @@ +#!/usr/bin/env python3 +"""Verify Obsidian paper-note schema, Zotero-key coverage, and optional inventory consistency.""" + +from __future__ import annotations + +import argparse +import re +import sys +from pathlib import Path + +REQUIRED_HEADINGS = ( + "## Claim", + "## Method", + "## Evidence", + "## Limitation", + "## Direct relevance to repo", + "## Relation to other papers", +) + +REQUIRED_FRONTMATTER_FIELDS = ( + "type", + "project", + "title", + "zotero_key", + "linked_knowledge", + "paper_relationships", + "updated", +) + +ZOTERO_KEY_RE = re.compile(r'^zotero_key:\s*"?([A-Z0-9]+)"?', re.MULTILINE) +FRONTMATTER_RE = re.compile(r'^---\n(.*?)\n---\n', re.DOTALL) +FIELD_RE_TEMPLATE = r'^{}:\s*' +INVENTORY_ROW_RE = re.compile(r'^\|\s*([A-Z0-9]+)\s*\|\s*(.*?)\|\s*(.*?)\|\s*(.*?)\|\s*$') + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser( + description="Verify paper-note schema and optional Zotero-key / inventory coverage." + ) + parser.add_argument("--papers-dir", required=True, help="Directory containing canonical paper notes.") + parser.add_argument( + "--expected-zotero-keys", + default="", + help="Comma-separated Zotero keys expected to be covered.", + ) + parser.add_argument( + "--inventory-note", + default="", + help="Optional collection inventory note to cross-check against canonical paper notes.", + ) + parser.add_argument( + "--strict-missing-zotero-key", + action="store_true", + help="Treat notes without zotero_key as errors. Default behavior skips them.", + ) + return parser.parse_args() + + +def load_expected_keys(raw_keys: str) -> list[str]: + if not raw_keys.strip(): + return [] + return [key.strip() for key in raw_keys.split(",") if key.strip()] + + +def extract_frontmatter(text: str) -> str: + match = FRONTMATTER_RE.match(text) + return match.group(1) if match else "" + + +def missing_frontmatter_fields(frontmatter: str) -> list[str]: + missing: list[str] = [] + for field in REQUIRED_FRONTMATTER_FIELDS: + if not re.search(FIELD_RE_TEMPLATE.format(re.escape(field)), frontmatter, re.MULTILINE): + missing.append(field) + return missing + + +def collect_note_status( + papers_dir: Path, + strict_missing_zotero_key: bool, +) -> tuple[dict[str, str], list[str], list[str]]: + key_to_file: dict[str, str] = {} + issues: list[str] = [] + skipped_without_key: list[str] = [] + + for path in sorted(papers_dir.glob("*.md")): + text = path.read_text(encoding="utf-8") + frontmatter = extract_frontmatter(text) + match = ZOTERO_KEY_RE.search(text) + if not match: + skipped_without_key.append(path.name) + if strict_missing_zotero_key: + issues.append(f"{path.name}: missing zotero_key") + continue + + zotero_key = match.group(1) + if zotero_key in key_to_file: + issues.append( + f"{path.name}: duplicate zotero_key {zotero_key} also used by {key_to_file[zotero_key]}" + ) + key_to_file[zotero_key] = path.name + + missing_headings = [heading for heading in REQUIRED_HEADINGS if heading not in text] + if missing_headings: + issues.append(f"{path.name}: missing headings -> {', '.join(missing_headings)}") + + missing_fields = missing_frontmatter_fields(frontmatter) + if missing_fields: + issues.append(f"{path.name}: missing frontmatter fields -> {', '.join(missing_fields)}") + + return key_to_file, issues, skipped_without_key + + +def parse_inventory_note(inventory_path: Path) -> tuple[dict[str, str], list[str]]: + text = inventory_path.read_text(encoding="utf-8") + mapping: dict[str, str] = {} + issues: list[str] = [] + in_table = False + + for line in text.splitlines(): + if line.strip() == "## Item Mapping": + in_table = True + continue + if in_table and line.startswith("## "): + break + if not in_table or not line.startswith("|"): + continue + if "---" in line: + continue + match = INVENTORY_ROW_RE.match(line) + if not match: + continue + key, _title, note_path, _status = [part.strip() for part in match.groups()] + if key in mapping: + issues.append(f"inventory: duplicate zotero key {key}") + mapping[key] = note_path + + if not mapping: + issues.append("inventory: no item mapping rows found") + return mapping, issues + + +def main() -> int: + args = parse_args() + papers_dir = Path(args.papers_dir).expanduser() + expected_keys = load_expected_keys(args.expected_zotero_keys) + + if not papers_dir.exists(): + print(f"ERROR: papers dir not found: {papers_dir}") + return 1 + + note_files = list(papers_dir.glob("*.md")) + key_to_file, issues, skipped_without_key = collect_note_status( + papers_dir, args.strict_missing_zotero_key + ) + + print(f"Papers dir: {papers_dir}") + print(f"Paper notes scanned: {len(note_files)}") + print(f"Notes with zotero_key: {len(key_to_file)}") + if skipped_without_key: + print(f"Notes skipped without zotero_key: {len(skipped_without_key)}") + + if expected_keys: + missing = [key for key in expected_keys if key not in key_to_file] + extras = sorted(set(key_to_file) - set(expected_keys)) + print(f"Expected Zotero keys: {len(expected_keys)}") + print(f"Covered Zotero keys: {len(expected_keys) - len(missing)} / {len(expected_keys)}") + if missing: + issues.append(f"Missing expected keys: {', '.join(missing)}") + if extras: + print(f"Extra zotero_key notes: {', '.join(extras)}") + + if args.inventory_note: + inventory_path = Path(args.inventory_note).expanduser() + if not inventory_path.exists(): + issues.append(f"inventory note not found: {inventory_path}") + else: + inventory_mapping, inventory_issues = parse_inventory_note(inventory_path) + issues.extend(inventory_issues) + if inventory_mapping: + for key, note_path in inventory_mapping.items(): + expected_name = key_to_file.get(key) + if expected_name is None: + issues.append(f"inventory: key {key} not found in paper notes") + continue + if Path(note_path).name != expected_name: + issues.append( + f"inventory: key {key} points to {note_path}, expected file ending {expected_name}" + ) + missing_in_inventory = sorted(set(key_to_file) - set(inventory_mapping)) + if missing_in_inventory: + issues.append( + f"inventory: missing keys present in paper notes -> {', '.join(missing_in_inventory)}" + ) + + if skipped_without_key: + print("Skipped note files without zotero_key:") + for name in skipped_without_key: + print(f"- {name}") + + if issues: + print("\nISSUES:") + for issue in issues: + print(f"- {issue}") + return 1 + + print("\nOK: schema and coverage checks passed.") + return 0 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/daily.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/daily.md new file mode 100644 index 0000000..1efce3a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/daily.md @@ -0,0 +1,17 @@ +--- +type: daily +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# Daily - {{today}} + +## Focus + +## Progress + +## Notes + +## Promote Later diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/experiment.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/experiment.md new file mode 100644 index 0000000..8144876 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/experiment.md @@ -0,0 +1,25 @@ +--- +type: experiment +project: {{project_slug}} +status: planned +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Question + +## Hypothesis + +## Setup + +## Variables + +## Procedure + +## Expected Outcome + +## Linked Results + +## Notes diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/knowledge.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/knowledge.md new file mode 100644 index 0000000..6a5a958 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/knowledge.md @@ -0,0 +1,19 @@ +--- +type: knowledge +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Summary + +## Supporting Sources + +## Key Claims + +## Implications + +## Open Questions diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/result.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/result.md new file mode 100644 index 0000000..32d3c38 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/result.md @@ -0,0 +1,19 @@ +--- +type: result +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Summary + +## Linked Experiment + +## Evidence + +## Interpretation + +## Decision diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/results-report.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/results-report.md new file mode 100644 index 0000000..7abd00d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/results-report.md @@ -0,0 +1,27 @@ +--- +type: results-report +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Executive Summary + +## Experiment Identity and Decision Context + +## Setup and Evaluation Protocol + +## Main Findings + +## Statistical Validation + +## Figure-by-Figure Interpretation + +## Failure Cases / Limitations + +## What Changed Our Belief + +## Next Actions diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/source-data.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-data.md new file mode 100644 index 0000000..999c81f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-data.md @@ -0,0 +1,26 @@ +--- +type: source +source_type: data +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Metadata + +## Project Relevance + +## Summary + +## Schema + +## Metrics + +## Known Issues + +## Usage Notes + +## Connections diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/source-doc.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-doc.md new file mode 100644 index 0000000..3bd936a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-doc.md @@ -0,0 +1,24 @@ +--- +type: source +source_type: doc +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Metadata + +## Project Relevance + +## Summary + +## Key Points + +## Evidence / Excerpts + +## Connections + +## Open Questions diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/source-interview.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-interview.md new file mode 100644 index 0000000..a96f9dd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-interview.md @@ -0,0 +1,26 @@ +--- +type: source +source_type: interview +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Metadata + +## Project Relevance + +## Summary + +## Participants + +## Context + +## Key Quotes + +## Observed Needs + +## Follow-ups diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/source-note.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-note.md new file mode 100644 index 0000000..8b99517 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-note.md @@ -0,0 +1,24 @@ +--- +type: source +source_type: note +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Metadata + +## Project Relevance + +## Summary + +## Key Points + +## Evidence / Excerpts + +## Connections + +## Open Questions diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/source-paper.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-paper.md new file mode 100644 index 0000000..575c013 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-paper.md @@ -0,0 +1,28 @@ +--- +type: source +source_type: paper +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Metadata + +## Project Relevance + +## Summary + +## Key Claims + +## Methods + +## Evidence / Excerpts + +## Limitations + +## Connections + +## Open Questions diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/source-web.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-web.md new file mode 100644 index 0000000..4ad4086 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/source-web.md @@ -0,0 +1,24 @@ +--- +type: source +source_type: web +project: {{project_slug}} +status: active +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Metadata + +## Project Relevance + +## Summary + +## Key Points + +## Evidence / Excerpts + +## Connections + +## Open Questions diff --git a/文档润色流和知识库构建流/claude-scholar/templates/notes/writing.md b/文档润色流和知识库构建流/claude-scholar/templates/notes/writing.md new file mode 100644 index 0000000..222ee0e --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/notes/writing.md @@ -0,0 +1,19 @@ +--- +type: writing +project: {{project_slug}} +status: draft +created: {{timestamp}} +updated: {{timestamp}} +--- + +# {{title}} + +## Purpose + +## Audience + +## Outline + +## Source Notes + +## Draft diff --git a/文档润色流和知识库构建流/claude-scholar/templates/project/00-Hub.md b/文档润色流和知识库构建流/claude-scholar/templates/project/00-Hub.md new file mode 100644 index 0000000..971f845 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/project/00-Hub.md @@ -0,0 +1,32 @@ +--- +type: project-hub +project: {{project_slug}} +title: {{project_title}} +status: active +updated: {{timestamp}} +--- + +# {{project_title}} + +## Project Summary +- TODO + +## Current Focus +- TODO + +## Current Questions +- TODO + +## Next Actions +- TODO + +## Important Links +- [[01-Plan]] +- [[02-Index]] +- [[Daily/{{today}}]] +- [[_system/registry]] +- [[_system/schema]] +- [[_system/lint-report]] + +## Recent Changes +- Initialized on {{timestamp}} diff --git a/文档润色流和知识库构建流/claude-scholar/templates/project/01-Plan.md b/文档润色流和知识库构建流/claude-scholar/templates/project/01-Plan.md new file mode 100644 index 0000000..530931a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/project/01-Plan.md @@ -0,0 +1,23 @@ +--- +type: project-plan +project: {{project_slug}} +title: Plan - {{project_title}} +status: active +updated: {{timestamp}} +--- + +# Plan + +## Current Priorities +- TODO + +## Active Tasks +- [ ] Review imported sources +- [ ] Define current experiment queue +- [ ] Update durable knowledge notes + +## Experiment Queue +- TODO + +## Writing Queue +- TODO diff --git a/文档润色流和知识库构建流/claude-scholar/templates/project/02-Index.md b/文档润色流和知识库构建流/claude-scholar/templates/project/02-Index.md new file mode 100644 index 0000000..5953537 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/project/02-Index.md @@ -0,0 +1,39 @@ +--- +type: project-index +project: {{project_slug}} +title: Index - {{project_title}} +status: active +updated: {{timestamp}} +--- + +# Index + +## Curated Index + +- Add human-maintained entry points here. +- Keep this section concise and reader-first. + +## Auto Index + +Managed block. Refresh with `/kb-sync` or `/kb-index`. Put hand-written navigation in **Curated Index**, not inside the markers below. + +<!-- BEGIN AUTO INDEX --> +### Sources +- None yet. + +### Knowledge +- None yet. + +### Experiments +- None yet. + +### Results +- None yet. + +### Writing +- None yet. + +### Maps +- None yet. + +<!-- END AUTO INDEX --> diff --git a/文档润色流和知识库构建流/claude-scholar/templates/project/_system/lint-report.md b/文档润色流和知识库构建流/claude-scholar/templates/project/_system/lint-report.md new file mode 100644 index 0000000..12ad3fe --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/project/_system/lint-report.md @@ -0,0 +1,21 @@ +# Lint Report + +Last checked: {{timestamp}} + +## Summary + +| Check | Status | Count | +|---|---|---| +| Broken links | pass | 0 | +| Missing registry entries | pass | 0 | +| Missing index entries | pass | 0 | + +## Issues + +### None + +- No issues recorded yet. + +## Recommended Fixes + +- None. diff --git a/文档润色流和知识库构建流/claude-scholar/templates/project/_system/registry.md b/文档润色流和知识库构建流/claude-scholar/templates/project/_system/registry.md new file mode 100644 index 0000000..b1e26c1 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/project/_system/registry.md @@ -0,0 +1,38 @@ +# Registry + +Last updated: {{timestamp}} + +## Sources + +| ID | Type | Title | Path | Status | Origin | Updated | +|---|---|---|---|---|---|---| + +## Knowledge + +| ID | Type | Title | Path | Status | Sources | Updated | +|---|---|---|---|---|---|---| + +## Experiments + +| ID | Title | Path | Status | Related Results | Updated | +|---|---|---|---|---|---| + +## Results + +| ID | Title | Path | Status | Related Experiment | Sources | Updated | +|---|---|---|---|---|---|---| + +## Writing + +| ID | Title | Path | Status | Related Notes | Updated | +|---|---|---|---|---|---| + +## Maps + +| ID | Title | Path | Status | Type | Updated | +|---|---|---|---|---|---| + +## Archive + +| ID | Title | Old Path | Archived Path | Reason | Archived At | +|---|---|---|---|---|---| diff --git a/文档润色流和知识库构建流/claude-scholar/templates/project/_system/schema.md b/文档润色流和知识库构建流/claude-scholar/templates/project/_system/schema.md new file mode 100644 index 0000000..c13eb9f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/templates/project/_system/schema.md @@ -0,0 +1,45 @@ +# KB Schema + +## Project Scope +All project knowledge belongs to `Research/{{project_slug}}/`. + +## Directory Rules +- source-centered notes stay under `Sources/*` +- cross-source synthesis stays under `Knowledge/` +- experiment design and run tracking stay under `Experiments/` +- stable findings stay under `Results/` +- round and batch reports stay under `Results/Reports/` +- prose deliverables stay under `Writing/` +- process notes stay under `Daily/` +- derived artifacts stay under `Maps/` +- archived notes stay under `Archive/` + +## Source vs Knowledge +- `Sources/*` is for source-centered notes +- `Knowledge/` is for durable synthesis across one or more sources +- do not use `Knowledge/` as a second raw-source inbox + +## Registry Rules +`_system/registry.md` is the only visible project registry. +Keep human-maintained fields stable across sync. Deterministic sync should update paths and timestamps, not rewrite curated metadata. + +## Index Rules +`02-Index.md` is a human-readable MOC, not a registry mirror. +Only the auto-index block is regenerated automatically. + +## Hub Rules +`00-Hub.md` should only receive small status-oriented updates. Do not rewrite the whole note during routine sync. + +## Daily Promotion Rules +Durable insights discovered in `Daily/` should be promoted into `Knowledge/`, `Experiments/`, `Results/`, or `Writing/` when they become reusable. + +## Archive Rules +- note archive lives in `Research/{{project_slug}}/Archive/` +- project archive lives in `Research/_archived/` +- archive history stays visible in `_system/registry.md` + +## Map Rules +`Maps/` contains derived navigation artifacts only. Do not treat maps as the project source of truth. + +## Cross-project Rules +Do not move notes, merge registries, or synthesize across multiple `Research/{project-slug}/` roots unless the user asks for explicit cross-project work. diff --git a/文档润色流和知识库构建流/claude-scholar/utils/platform_utils.py b/文档润色流和知识库构建流/claude-scholar/utils/platform_utils.py new file mode 100644 index 0000000..5c7db32 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/utils/platform_utils.py @@ -0,0 +1,333 @@ +""" +Cross-platform utility functions for Python projects +Works on Windows, macOS, and Linux +""" + +import os +import sys +import platform +import subprocess +import shutil +from pathlib import Path +from datetime import datetime +from typing import List, Optional, Dict, Any +import glob as glob_module + +# Platform detection +IS_WINDOWS = platform.system() == 'Windows' +IS_MACOS = platform.system() == 'Darwin' +IS_LINUX = platform.system() == 'Linux' + + +def get_home_dir() -> Path: + """Get the user's home directory (cross-platform)""" + return Path.home() + + +def get_claude_dir() -> Path: + """Get the Claude config directory""" + return get_home_dir() / '.claude' + + +def get_temp_dir() -> Path: + """Get the temp directory (cross-platform)""" + return Path(os.tmpdir()) + + +def get_plan_dir() -> Path: + """Get the plan directory""" + plan_dir = get_claude_dir() / 'plan' + plan_dir.mkdir(parents=True, exist_ok=True) + return plan_dir + + +def ensure_dir(dir_path: Path) -> Path: + """Ensure a directory exists (create if not)""" + dir_path.mkdir(parents=True, exist_ok=True) + return dir_path + + +def get_date_string() -> str: + """Get current date in YYYY-MM-DD format""" + return datetime.now().strftime('%Y-%m-%d') + + +def get_time_string() -> str: + """Get current time in HH:MM format""" + return datetime.now().strftime('%H:%M') + + +def get_datetime_string() -> str: + """Get current datetime in YYYY-MM-DD HH:MM:SS format""" + return datetime.now().strftime('%Y-%m-%d %H:%M:%S') + + +def find_files(dir_path: Path, pattern: str, max_age_days: Optional[int] = None, recursive: bool = False) -> List[Dict[str, Any]]: + """ + Find files matching a pattern in a directory (cross-platform) + + Args: + dir_path: Directory to search + pattern: File pattern (e.g., "*.tmp", "*.md") + max_age_days: Only return files modified within this many days + recursive: Search subdirectories + + Returns: + List of dicts with 'path' and 'mtime' keys + """ + if not dir_path.exists(): + return [] + + results = [] + + # Use glob for pattern matching + glob_pattern = str(dir_path / ('**' if recursive else '') / pattern) + files = glob_module.glob(glob_pattern, recursive=recursive) + + for file_path in files: + file_path = Path(file_path) + try: + stat = file_path.stat() + mtime = stat.st_mtime + + if max_age_days is not None: + import time + age_in_days = (time.time() - mtime) / (86400) + if age_in_days <= max_age_days: + results.append({'path': str(file_path), 'mtime': mtime}) + else: + results.append({'path': str(file_path), 'mtime': mtime}) + except (OSError, PermissionError): + # Ignore permission errors + pass + + # Sort by modification time (newest first) + results.sort(key=lambda x: x['mtime'], reverse=True) + return results + + +def command_exists(cmd: str) -> bool: + """ + Check if a command exists in PATH (cross-platform) + Uses shutil.which for safety + """ + if not cmd or not isinstance(cmd, str): + return False + + # Basic validation - only allow alphanumeric, dash, underscore, dot + if not cmd.replace('-', '').replace('_', '').replace('.', '').isalnum(): + return False + + return shutil.which(cmd) is not None + + +def run_command(cmd: List[str], cwd: Optional[Path] = None, capture: bool = True) -> Dict[str, Any]: + """ + Run a command and return output + + SECURITY NOTE: This function executes shell commands. Only use with + trusted, hardcoded commands. Never pass user-controlled input directly. + + Args: + cmd: Command and arguments as list (safer than string) + cwd: Working directory + capture: Whether to capture output + + Returns: + Dict with 'success', 'output', 'returncode' keys + """ + try: + result = subprocess.run( + cmd, + cwd=cwd, + capture_output=capture, + text=True, + check=False + ) + return { + 'success': result.returncode == 0, + 'output': result.stdout.strip(), + 'stderr': result.stderr.strip(), + 'returncode': result.returncode + } + except (subprocess.SubprocessError, FileNotFoundError) as e: + return { + 'success': False, + 'output': '', + 'stderr': str(e), + 'returncode': -1 + } + + +def is_git_repo(cwd: Optional[Path] = None) -> bool: + """Check if current directory is a git repository""" + result = run_command(['git', 'rev-parse', '--git-dir'], cwd=cwd) + return result['success'] + + +def get_git_modified_files(patterns: Optional[List[str]] = None) -> List[str]: + """Get git modified files""" + if not is_git_repo(): + return [] + + result = run_command(['git', 'diff', '--name-only', 'HEAD']) + if not result['success']: + return [] + + files = result['output'].split('\n') if result['output'] else [] + files = [f for f in files if f] + + if patterns: + import re + files = [ + f for f in files + if any(re.search(pattern, f) for pattern in patterns) + ] + + return files + + +def read_file(file_path: Path) -> Optional[str]: + """Read a text file safely""" + try: + return file_path.read_text(encoding='utf-8') + except (FileNotFoundError, PermissionError, UnicodeDecodeError): + return None + + +def write_file(file_path: Path, content: str) -> bool: + """Write a text file""" + try: + ensure_dir(file_path.parent) + file_path.write_text(content, encoding='utf-8') + return True + except (OSError, PermissionError): + return False + + +def append_file(file_path: Path, content: str) -> bool: + """Append to a text file""" + try: + ensure_dir(file_path.parent) + with open(file_path, 'a', encoding='utf-8') as f: + f.write(content) + return True + except (OSError, PermissionError): + return False + + +def replace_in_file(file_path: Path, search: str, replace: str) -> bool: + """Replace text in a file (cross-platform sed alternative)""" + content = read_file(file_path) + if content is None: + return False + + new_content = content.replace(search, replace) + return write_file(file_path, new_content) + + +def count_in_file(file_path: Path, pattern: str) -> int: + """Count occurrences of a pattern in a file""" + content = read_file(file_path) + if content is None: + return 0 + + import re + matches = re.findall(pattern, content) + return len(matches) + + +def grep_file(file_path: Path, pattern: str) -> List[Dict[str, Any]]: + """Search for pattern in file and return matching lines with line numbers""" + content = read_file(file_path) + if content is None: + return [] + + import re + lines = content.split('\n') + results = [] + + for idx, line in enumerate(lines, 1): + if re.search(pattern, line): + results.append({'line_number': idx, 'content': line}) + + return results + + +def get_platform_info() -> Dict[str, Any]: + """Get platform information""" + return { + 'system': platform.system(), + 'release': platform.release(), + 'version': platform.version(), + 'machine': platform.machine(), + 'processor': platform.processor(), + 'is_windows': IS_WINDOWS, + 'is_macos': IS_MACOS, + 'is_linux': IS_LINUX, + 'python_version': sys.version_info, + 'home_dir': str(get_home_dir()), + 'temp_dir': str(get_temp_dir()), + } + + +def log(message: str) -> None: + """Log to stderr (visible to user in Claude Code)""" + print(message, file=sys.stderr) + + +def output(data: Any) -> None: + """Output to stdout (returned to Claude)""" + if isinstance(data, (dict, list)): + import json + print(json.dumps(data, ensure_ascii=False, indent=2)) + else: + print(data) + + +# Module exports +__all__ = [ + # Platform info + 'IS_WINDOWS', + 'IS_MACOS', + 'IS_LINUX', + 'get_platform_info', + + # Directories + 'get_home_dir', + 'get_claude_dir', + 'get_temp_dir', + 'get_plan_dir', + 'ensure_dir', + + # Date/Time + 'get_date_string', + 'get_time_string', + 'get_datetime_string', + + # File operations + 'find_files', + 'read_file', + 'write_file', + 'append_file', + 'replace_in_file', + 'count_in_file', + 'grep_file', + + # System + 'command_exists', + 'run_command', + 'is_git_repo', + 'get_git_modified_files', + + # I/O + 'log', + 'output', +] + + +if __name__ == '__main__': + # Test platform detection + print("Platform Info:") + for key, value in get_platform_info().items(): + print(f" {key}: {value}") diff --git a/文档润色流和知识库构建流/llm-wiki.md b/文档润色流和知识库构建流/llm-wiki.md new file mode 100644 index 0000000..6b0cef3 --- /dev/null +++ b/文档润色流和知识库构建流/llm-wiki.md @@ -0,0 +1,75 @@ +# LLM Wiki + +A pattern for building personal knowledge bases using LLMs. + +This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you. + +## The core idea + +Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way. + +The idea here is different. Instead of just retrieving from raw documents at query time, the LLM **incrementally builds and maintains a persistent wiki** — a structured, interlinked collection of markdown files that sits between you and the raw sources. When you add a new source, the LLM doesn't just index it for later retrieval. It reads it, extracts the key information, and integrates it into the existing wiki — updating entity pages, revising topic summaries, noting where new data contradicts old claims, strengthening or challenging the evolving synthesis. The knowledge is compiled once and then *kept current*, not re-derived on every query. + +This is the key difference: **the wiki is a persistent, compounding artifact.** The cross-references are already there. The contradictions have already been flagged. The synthesis already reflects everything you've read. The wiki keeps getting richer with every source you add and every question you ask. + +You never (or rarely) write the wiki yourself — the LLM writes and maintains all of it. You're in charge of sourcing, exploration, and asking the right questions. The LLM does all the grunt work — the summarizing, cross-referencing, filing, and bookkeeping that makes a knowledge base actually useful over time. In practice, I have the LLM agent open on one side and Obsidian open on the other. The LLM makes edits based on our conversation, and I browse the results in real time — following links, checking the graph view, reading the updated pages. Obsidian is the IDE; the LLM is the programmer; the wiki is the codebase. + +This can apply to a lot of different contexts. A few examples: + +- **Personal**: tracking your own goals, health, psychology, self-improvement — filing journal entries, articles, podcast notes, and building up a structured picture of yourself over time. +- **Research**: going deep on a topic over weeks or months — reading papers, articles, reports, and incrementally building a comprehensive wiki with an evolving thesis. +- **Reading a book**: filing each chapter as you go, building out pages for characters, themes, plot threads, and how they connect. By the end you have a rich companion wiki. Think of fan wikis like [Tolkien Gateway](https://tolkiengateway.net/wiki/Main_Page) — thousands of interlinked pages covering characters, places, events, languages, built by a community of volunteers over years. You could build something like that personally as you read, with the LLM doing all the cross-referencing and maintenance. +- **Business/team**: an internal wiki maintained by LLMs, fed by Slack threads, meeting transcripts, project documents, customer calls. Possibly with humans in the loop reviewing updates. The wiki stays current because the LLM does the maintenance that no one on the team wants to do. +- **Competitive analysis, due diligence, trip planning, course notes, hobby deep-dives** — anything where you're accumulating knowledge over time and want it organized rather than scattered. + +## Architecture + +There are three layers: + +**Raw sources** — your curated collection of source documents. Articles, papers, images, data files. These are immutable — the LLM reads from them but never modifies them. This is your source of truth. + +**The wiki** — a directory of LLM-generated markdown files. Summaries, entity pages, concept pages, comparisons, an overview, a synthesis. The LLM owns this layer entirely. It creates pages, updates them when new sources arrive, maintains cross-references, and keeps everything consistent. You read it; the LLM writes it. + +**The schema** — a document (e.g. CLAUDE.md for Claude Code or AGENTS.md for Codex) that tells the LLM how the wiki is structured, what the conventions are, and what workflows to follow when ingesting sources, answering questions, or maintaining the wiki. This is the key configuration file — it's what makes the LLM a disciplined wiki maintainer rather than a generic chatbot. You and the LLM co-evolve this over time as you figure out what works for your domain. + +## Operations + +**Ingest.** You drop a new source into the raw collection and tell the LLM to process it. An example flow: the LLM reads the source, discusses key takeaways with you, writes a summary page in the wiki, updates the index, updates relevant entity and concept pages across the wiki, and appends an entry to the log. A single source might touch 10-15 wiki pages. Personally I prefer to ingest sources one at a time and stay involved — I read the summaries, check the updates, and guide the LLM on what to emphasize. But you could also batch-ingest many sources at once with less supervision. It's up to you to develop the workflow that fits your style and document it in the schema for future sessions. + +**Query.** You ask questions against the wiki. The LLM searches for relevant pages, reads them, and synthesizes an answer with citations. Answers can take different forms depending on the question — a markdown page, a comparison table, a slide deck (Marp), a chart (matplotlib), a canvas. The important insight: **good answers can be filed back into the wiki as new pages.** A comparison you asked for, an analysis, a connection you discovered — these are valuable and shouldn't disappear into chat history. This way your explorations compound in the knowledge base just like ingested sources do. + +**Lint.** Periodically, ask the LLM to health-check the wiki. Look for: contradictions between pages, stale claims that newer sources have superseded, orphan pages with no inbound links, important concepts mentioned but lacking their own page, missing cross-references, data gaps that could be filled with a web search. The LLM is good at suggesting new questions to investigate and new sources to look for. This keeps the wiki healthy as it grows. + +## Indexing and logging + +Two special files help the LLM (and you) navigate the wiki as it grows. They serve different purposes: + +**index.md** is content-oriented. It's a catalog of everything in the wiki — each page listed with a link, a one-line summary, and optionally metadata like date or source count. Organized by category (entities, concepts, sources, etc.). The LLM updates it on every ingest. When answering a query, the LLM reads the index first to find relevant pages, then drills into them. This works surprisingly well at moderate scale (~100 sources, ~hundreds of pages) and avoids the need for embedding-based RAG infrastructure. + +**log.md** is chronological. It's an append-only record of what happened and when — ingests, queries, lint passes. A useful tip: if each entry starts with a consistent prefix (e.g. `## [2026-04-02] ingest | Article Title`), the log becomes parseable with simple unix tools — `grep "^## \[" log.md | tail -5` gives you the last 5 entries. The log gives you a timeline of the wiki's evolution and helps the LLM understand what's been done recently. + +## Optional: CLI tools + +At some point you may want to build small tools that help the LLM operate on the wiki more efficiently. A search engine over the wiki pages is the most obvious one — at small scale the index file is enough, but as the wiki grows you want proper search. [qmd](https://github.com/tobi/qmd) is a good option: it's a local search engine for markdown files with hybrid BM25/vector search and LLM re-ranking, all on-device. It has both a CLI (so the LLM can shell out to it) and an MCP server (so the LLM can use it as a native tool). You could also build something simpler yourself — the LLM can help you vibe-code a naive search script as the need arises. + +## Tips and tricks + +- **Obsidian Web Clipper** is a browser extension that converts web articles to markdown. Very useful for quickly getting sources into your raw collection. +- **Download images locally.** In Obsidian Settings → Files and links, set "Attachment folder path" to a fixed directory (e.g. `raw/assets/`). Then in Settings → Hotkeys, search for "Download" to find "Download attachments for current file" and bind it to a hotkey (e.g. Ctrl+Shift+D). After clipping an article, hit the hotkey and all images get downloaded to local disk. This is optional but useful — it lets the LLM view and reference images directly instead of relying on URLs that may break. Note that LLMs can't natively read markdown with inline images in one pass — the workaround is to have the LLM read the text first, then view some or all of the referenced images separately to gain additional context. It's a bit clunky but works well enough. +- **Obsidian's graph view** is the best way to see the shape of your wiki — what's connected to what, which pages are hubs, which are orphans. +- **Marp** is a markdown-based slide deck format. Obsidian has a plugin for it. Useful for generating presentations directly from wiki content. +- **Dataview** is an Obsidian plugin that runs queries over page frontmatter. If your LLM adds YAML frontmatter to wiki pages (tags, dates, source counts), Dataview can generate dynamic tables and lists. +- The wiki is just a git repo of markdown files. You get version history, branching, and collaboration for free. + +## Why this works + +The tedious part of maintaining a knowledge base is not the reading or the thinking — it's the bookkeeping. Updating cross-references, keeping summaries current, noting when new data contradicts old claims, maintaining consistency across dozens of pages. Humans abandon wikis because the maintenance burden grows faster than the value. LLMs don't get bored, don't forget to update a cross-reference, and can touch 15 files in one pass. The wiki stays maintained because the cost of maintenance is near zero. + +The human's job is to curate sources, direct the analysis, ask good questions, and think about what it all means. The LLM's job is everything else. + +The idea is related in spirit to Vannevar Bush's Memex (1945) — a personal, curated knowledge store with associative trails between documents. Bush's vision was closer to this than to what the web became: private, actively curated, with the connections between documents as valuable as the documents themselves. The part he couldn't solve was who does the maintenance. The LLM handles that. + + +## Note + +This document is intentionally abstract. It describes the idea, not a specific implementation. The exact directory structure, the schema conventions, the page formats, the tooling — all of that will depend on your domain, your preferences, and your LLM of choice. Everything mentioned above is optional and modular — pick what's useful, ignore what isn't. For example: your sources might be text-only, so you don't need image handling at all. Your wiki might be small enough that the index file is all you need, no search engine required. You might not care about slide decks and just want markdown pages. You might want a completely different set of output formats. The right way to use this is to share it with your LLM agent and work together to instantiate a version that fits your needs. The document's only job is to communicate the pattern. Your LLM can figure out the rest. diff --git a/知识库Agent构建.md b/知识库Agent构建.md new file mode 100644 index 0000000..0f3789b --- /dev/null +++ b/知识库Agent构建.md @@ -0,0 +1,512 @@ +# 知识库 Agent 构建方案：LLM Wiki + 文本图片多模态知识库 + +问题开始时间：2026-06-11-03-26-41 + +资料来源： +- Karpathy gist：<https://gist.githubusercontent.com/karpathy/442a6bf555914893e9891c11519de94f/raw/ac46de1ad27f92b28ac95459c782c07f6b8c964a/llm-wiki.md> +- 本地下载：`文档润色流和知识库构建流/llm-wiki.md` +- Gist 文件 SHA256：`dc3efe98ae62f23dd08acad13aba2e95287beb20b6bec2f4af0423557fe37401` +- 参考插件：`文档润色流和知识库构建流/claude-scholar` 中 Obsidian KB、source ingestion、literature workflow、zotero-obsidian-bridge 相关说明 + +## 1. 核心思想 + +Karpathy 的 `LLM Wiki` 不是传统 RAG。传统 RAG 在每次提问时从原始资料中重新检索片段；`LLM Wiki` 则让 LLM 维护一个持久 Markdown Wiki，作为原始资料和问答之间的中间知识层。 + +```text +Raw Sources -> LLM Maintained Wiki -> Query / Writing / Analysis +``` + +关键区别： +- 原始资料只读，是 source of truth； +- Wiki 是 LLM 维护的结构化知识层； +- 新资料入库时，不只是建立索引，还要更新主题页、实体页、证据页、矛盾记录和索引； +- 高价值问答也可以写回 Wiki，避免只留在聊天记录里； +- 交叉引用、旧结论修正、缺口记录会随资料积累持续增长。 + +对本项目而言，目标是构建“文档润色与项目资料知识库”，支撑模板、参考文档、论文、图片、实验材料、写作草稿、证据台账和最终交付文本。 + +## 2. 三层架构 + +### 2.1 Raw Sources：原始资料层 + +原则：只读、可追溯、尽量保留原貌。 + +建议目录： + +```text +知识库/ + raw/ + papers/ + proposals/ + templates/ + docs/ + web/ + images/ + data/ +``` + +可放入： +- PDF 论文、技术报告、政策文件； +- Word、Markdown、PPT、Excel 等项目资料； +- 获批标书、模板、参考案例； +- 网页剪藏的 Markdown； +- PDF 转换出的图片、表格截图、机制图、流程图； +- 原始实验数据或结果图。 + +Raw 层不由 Agent 修改。Agent 可以读取、转换、引用，但不直接改写原件。 + +### 2.2 Wiki：LLM 维护层 + +原则：LLM 可编辑，人主要审查和阅读。 + +推荐结构： + +```text +知识库/ + wiki/ + index.md + log.md + 00-项目总览.md + 01-写作任务板.md + Sources/ + Papers/ + Web/ + Docs/ + Data/ + Images/ + Notes/ + Knowledge/ + 主题综述.md + 方法分类.md + 证据台账.md + 术语表.md + 矛盾与缺口.md + Writing/ + 立项依据.md + 研究内容.md + 技术路线.md + 创新点.md + 研究基础.md + Maps/ + literature.canvas + mechanism.canvas + Daily/ + Archive/ + _system/ + registry.md + schema.md + lint-report.md +``` + +### 2.3 Schema：Agent 规则层 + +Schema 可以写在 `AGENTS.md`、`CLAUDE.md`、`_system/schema.md` 或项目规则文件中。它告诉 Agent 如何维护 Wiki。 + +最小规则： +- Raw Sources 不可修改； +- 新资料必须先进入 `Sources/*`； +- 稳定论断才能进入 `Knowledge/*`； +- 进入 `Writing/*` 的论断必须能追溯到 Evidence Record； +- 图片必须本地化，并建立图片 source note； +- 每次 ingestion 后更新 `index.md`； +- 每次重要操作后向 `log.md` 追加记录； +- `log.md` 只追加，不重写历史。 + +## 3. 与 claude-scholar Obsidian KB 的对应关系 + +`claude-scholar` 的 Obsidian KB 已经提供一套可落地的项目知识库结构： + +```text +Research/{project-slug}/ + 00-Hub.md + 01-Plan.md + 02-Index.md + Sources/ + Papers/ + Web/ + Docs/ + Data/ + Interviews/ + Notes/ + Knowledge/ + Experiments/ + Results/ + Reports/ + Writing/ + Daily/ + Maps/ + Archive/ + _system/ +``` + +对应关系： +- `00-Hub.md`：项目入口和当前状态； +- `01-Plan.md`：任务计划、里程碑、下一步； +- `02-Index.md`：人类可读的导航索引； +- `Sources/*`：原始资料的结构化 source notes； +- `Knowledge/*`：经过证据门槛的稳定知识； +- `Writing/*`：可进入标书、论文、报告的写作资产； +- `Maps/literature.canvas`：默认文献图谱； +- `_system/registry.md`：可见注册表； +- `.claude/project-memory/*`：仓库本地绑定信息，不是主要知识内容。 + +## 4. 多模态资料处理：文本 + 图片 + +### 4.1 文本处理流程 + +文本来源： +- PDF 转 Markdown； +- 网页剪藏； +- Zotero PDF 全文； +- DOCX/Word 标书； +- PPT、会议记录、实验记录； +- 表格和数据说明文档。 + +处理流程： + +```text +读取原文 + -> 建 Source Note + -> 抽 Evidence Record + -> 更新 Knowledge 页面 + -> 更新 Writing 草稿或待写清单 + -> 更新 index.md 和 log.md +``` + +Source Note 模板： + +```markdown +# 资料标题 + +Source: +Source type: full paper | proposal | template | webpage | project note | dataset +Path: +Date ingested: + +## Summary + +## Key Evidence + +## Relevance to Current Project + +## Limitations + +## Evidence Records + +## Links +``` + +Evidence Record 模板： + +```markdown +## Evidence Record + +Evidence ID: +Source: +Source type: +Supports: +Contradicts: +Method / dataset / metric: +Limitation: +Project relevance: +Claim strength: speculative | observed | supported | strong +Allowed wording: +Forbidden stronger wording: +``` + +Claim strength 建议： +- `speculative`：想法、假设、间接启发； +- `observed`：单一资料或初步结果观察到； +- `supported`：有可靠文献、实验或数据支持； +- `strong`：多来源一致、方法可靠、可用于核心论断。 + +### 4.2 图片处理流程 + +Karpathy gist 特别提醒：图片应下载到本地。LLM 不能一次性可靠读取 Markdown 中的内嵌图片，较好的方式是先读文本，再逐张查看关键图片。 + +图片来源： +- PDF 转 Markdown 生成的 `images/*.jpg` 或 `*.png`； +- 论文中的 figure； +- 标书模板截图； +- 机制图、技术路线图； +- 实验结果图； +- 表格截图或流程图。 + +图片入库流程： + +```text +图片本地化 + -> 建 Image Source Note + -> OCR 或人工描述 + -> 提取坐标轴、图例、分组、箭头、节点 + -> 记录可支持的论断 + -> 链接到 Knowledge / Writing / Maps +``` + +Image Source Note 模板： + +```markdown +# Image: 简短标题 + +Image path: +Source document: +Original page / figure: +Date ingested: + +## Visual Description + +## Extracted Labels / OCR + +## What This Image Supports + +## Limitations + +## Reuse Plan +- 可用于：立项依据 | 研究基础 | 技术路线 | 机制模式图 | 结果展示 +- 是否需要重绘： + +## Links +``` + +图片调用口令： + +```text +请先读取这份 Markdown 的图片引用列表，再逐一查看关键图片，提取图题、坐标轴、图例、分组、结论和可迁移证据。 +``` + +```text +请为这张机制图建立图片笔记：描述节点、箭头方向、证据含义、可支持的机制假说，以及需要重绘或替换的地方。 +``` + +## 5. 核心操作 + +### 5.1 Ingest：新增资料入库 + +单篇资料入库： + +```text +1. 读取 raw/source。 +2. 判断 source type。 +3. 在 Sources/* 下生成 source note。 +4. 抽取 Evidence Records。 +5. 检查会影响哪些 Knowledge 页面。 +6. 如图片重要，建立 Images source note。 +7. 更新 02-Index.md 或 index.md。 +8. 向 log.md 追加记录。 +``` + +调用方式： + +```text +/kb-ingest path/to/source.pdf +``` + +或自然语言： + +```text +请将 raw/papers/xxx.pdf 转换后的 Markdown 入库：先写 Sources/Papers 笔记，再抽 Evidence Record，最后只把证据足够的内容提升到 Knowledge。 +``` + +### 5.2 Query：基于 Wiki 回答 + +回答问题时，优先读取 Wiki，而不是直接盲搜所有原始文件： + +```text +读 index.md / 02-Index.md + -> 找相关 Knowledge / Source 页 + -> 必要时回看 raw source + -> 输出带证据链答案 +``` + +调用方式： + +```text +请基于当前 Wiki 回答：某个机制链条有哪些证据、哪些只是迁移假说、哪些需要继续检索？ +``` + +### 5.3 File Back：把高价值问答写回 Wiki + +有价值的分析不应只留在聊天里： + +```text +问答结果 + -> 新建或更新 Knowledge / Writing 页面 + -> 更新 index.md + -> 追加 log.md +``` + +调用方式： + +```text +请把刚才关于“主题 A 与机制 B”的回答整理成 Knowledge/A-B-Mechanism.md，并把不确定论断标成 speculative。 +``` + +### 5.4 Promote：把稳定内容提升到知识或写作 + +来源笔记不能直接等同于知识结论。提升条件： +- 有 Evidence Record； +- 来源类型足够强； +- claim strength 与措辞匹配； +- 有 allowed wording 和 forbidden stronger wording； +- 能链接回 source note。 + +调用方式： + +```text +/kb-promote +``` + +或： + +```text +请把 Daily 和 Sources 中已经稳定的内容提升到 Knowledge；没有证据记录的内容只保留为待核查。 +``` + +### 5.5 Lint：健康检查 + +周期性检查： +- 断链； +- 孤立页面； +- 重复主题页； +- 新资料与旧结论矛盾； +- `Writing` 中是否存在无 Evidence Record 的论断； +- 图片路径是否失效； +- canvas 是否有效； +- index 是否覆盖关键页面。 + +调用方式： + +```text +/kb-lint +/kb-links +/kb-sync +``` + +## 6. Agent 分工建议 + +| Agent / Skill | 角色 | 输入 | 输出 | +|---|---|---|---| +| `obsidian-source-ingestion` | Source 入库 | PDF、网页、DOCX、图片、数据 | `Sources/*` 笔记、registry、index、daily | +| `zotero-obsidian-bridge` | 文献桥接 | Zotero collection | `Sources/Papers`、Evidence Records、Knowledge/Writing 初稿 | +| `obsidian-literature-workflow` | 文献综合 | `Sources/Papers` | `Knowledge/Literature Overview.md`、`Research Gaps.md`、`Maps/literature.canvas` | +| `obsidian-project-kb-core` | KB 主控 | 项目目录和 vault | scaffold、hub、plan、index、registry、lifecycle | +| `obsidian-kb-artifacts` | Obsidian 原生产物 | Markdown、wikilink、canvas | 链接修复、canvas、registry table、lint report | +| `citation-verification` | 引用核验 | 参考文献、DOI、arXiv、Zotero 条目 | 真实元数据、claim-citation 对齐检查 | +| `paper-self-review` | 写作自审 | 草稿、图表、证据记录 | Claim Audit、结构问题、过强论断 | +| `writing-anti-ai` | 语言润色 | 中文或英文段落 | 更自然、少 AI 痕迹的表述 | + +## 7. 多模态知识库的调用方法 + +### 7.1 初始化 + +```text +/kb-init 项目名 /absolute/path/to/obsidian-vault +``` + +如果不用 Obsidian，也可以在项目内创建普通 Markdown wiki： + +```text +请在当前项目下创建 知识库/wiki 结构，包含 index.md、log.md、Sources、Knowledge、Writing、Maps、_system。 +``` + +### 7.2 文本资料入库 + +```text +/kb-ingest path/to/file.md +/kb-ingest path/to/file.pdf +/kb-ingest https://example.com/article +``` + +如果是网页资料，可先使用 Obsidian Web Clipper 或 `defuddle` 生成干净 Markdown。 + +### 7.3 图片资料入库 + +```text +请扫描 raw/images 中的新图片，为每张关键图片创建 Image Source Note；提取图中标签、箭头关系、坐标轴、可支持论断和复用计划。 +``` + +### 7.4 文献综合 + +```text +/kb-literature-review +``` + +要求： +- synthesis 必须链接到 `Sources/Papers`； +- abstract-only 和 webpage-placeholder 只能进入 coverage 或 To-Read； +- `Writing/related-work-draft.md` 必须通过 evidence gate。 + +### 7.5 写作输出 + +```text +请基于 Knowledge 和 Evidence Records 起草 Writing/立项依据.md。每个关键论断都要标注证据来源；证据不足处用“拟探索/提示/可能”。 +``` + +## 8. index.md 与 log.md 规范 + +`index.md` 面向内容导航： + +```markdown +# Index + +## Sources +- [[Sources/Papers/xxx]] - 一句话说明 + +## Knowledge +- [[Knowledge/主题综述]] - 当前稳定结论 + +## Writing +- [[Writing/立项依据]] - 当前草稿状态 +``` + +`log.md` 面向时间线： + +```markdown +## [2026-06-11] ingest | source-title +- Source: +- Pages updated: +- Evidence records: +- Open questions: +``` + +建议使用一致前缀，便于命令行检索： + +```bash +grep "^## \\[" log.md | tail -5 +``` + +## 9. 可选工具 + +- Obsidian Graph View：观察知识图谱、孤立页、中心页； +- Obsidian Web Clipper：网页转 Markdown； +- Obsidian attachment folder：固定图片附件目录，例如 `raw/assets/`； +- Dataview：基于 YAML frontmatter 生成动态列表； +- Marp：从 Markdown 生成 slides； +- `qmd`：本地 Markdown 混合检索，适合 Wiki 较大后使用； +- Git：给 Wiki 提供版本历史、回滚和协作能力。 + +## 10. 推荐落地流程 + +```text +第 1 步：初始化 wiki / Obsidian KB +第 2 步：把模板、参考文档、论文、图片放入 raw +第 3 步：逐个 /kb-ingest，不批量盲灌 +第 4 步：为文本和图片建立 Source Notes +第 5 步：抽 Evidence Records +第 6 步：提升稳定论断到 Knowledge +第 7 步：把可写内容汇总到 Writing +第 8 步：周期性 /kb-lint、/kb-links、/kb-sync +第 9 步：把高价值问答写回 Wiki +第 10 步：用 Git 备份整个知识库 +``` + +## 11. 文本 + 图片知识库的质量底线 + +- 不从图片外链直接建立长期知识，先本地化； +- 不把摘要页、网页占位页当成强证据； +- 不把图中趋势写成统计显著，除非原文或数据支持； +- 不把机制图当成实验证据，机制图通常只支持“作者假说/模型示意”； +- 不把模板写法等同于事实内容； +- `Writing` 中每个强论断都要能回链到 Evidence Record； +- `log.md` 保留入库和修改时间线； +- 用 Git 管理 Wiki，避免长期知识被无痕覆盖。

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"claude-scholar", + "version": "1.0.0", + "source": "./", + "description": "Semi-automated research assistant with skills for literature review, experiments, analysis, writing, and project knowledge management" + } + ] +} diff --git a/文档润色流和知识库构建流/claude-scholar/.claude-plugin/plugin.json b/文档润色流和知识库构建流/claude-scholar/.claude-plugin/plugin.json new file mode 100644 index 0000000..fea62a9 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.claude-plugin/plugin.json @@ -0,0 +1,22 @@ +{ + "name": "claude-scholar", + "version": "1.0.0", + "description": "Semi-automated research assistant for academic research and software development, with skills for literature review, experiments, analysis, writing, and project knowledge management", + "author": { + "name": "Galaxy-Dawn" + }, + "repository": "https://github.com/Galaxy-Dawn/claude-scholar", + "homepage": "https://github.com/Galaxy-Dawn/claude-scholar", + "license": "MIT", + "keywords": [ + "research", + "academic", + "paper-writing", + "literature-review", + "experiments", + "obsidian", + "zotero", + "ml", + "ai" + ] +} diff --git a/文档润色流和知识库构建流/claude-scholar/.gitattributes b/文档润色流和知识库构建流/claude-scholar/.gitattributes new file mode 100644 index 0000000..484d31f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.gitattributes @@ -0,0 +1,11 @@ +# Fix GitHub language detection +# TeX/BibTeX files are knowledge base content, not source code +*.tex linguist-detectable=false +*.bst linguist-detectable=false +*.bib linguist-detectable=false +*.cls linguist-detectable=false +*.sty linguist-detectable=false + +# JavaScript hooks and scripts are the primary source code +*.js linguist-detectable=true +*.md linguist-documentation=true diff --git a/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/bug_report.yml b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/bug_report.yml new file mode 100644 index 0000000..719b8ac --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/bug_report.yml @@ -0,0 +1,104 @@ +name: Bug report +description: Report an installation, runtime, compatibility, or behavior bug in Claude Scholar. +title: "[Bug]: " +labels: + - bug +body: + - type: markdown + attributes: + value: | + Thanks for reporting a bug. + + Please keep this report concrete. The fastest bug reports for Claude Scholar include: + - the client and branch, + - the exact command or prompt, + - the full warning or traceback, + - and a short reproduction path. + + - type: checkboxes + id: preflight + attributes: + label: Before submitting + options: + - label: I checked the README / setup docs for the branch I am using. + required: true + - label: I included the exact error text instead of paraphrasing it. + required: true + + - type: dropdown + id: client + attributes: + label: Client + options: + - Claude Code + - Codex + - OpenCode + - Other / unsure + validations: + required: true + + - type: dropdown + id: branch + attributes: + label: Branch + options: + - main + - codex + - opencode + - unsure + validations: + required: true + + - type: textarea + id: environment + attributes: + label: Environment + description: Include only the details that matter for reproducing the issue. + placeholder: | + OS: macOS 15.4 + Shell: zsh + Install mode: scripts/setup.sh + Client version: Claude Code 2.1.42 + validations: + required: true + + - type: textarea + id: exact_action + attributes: + label: Exact command or exact prompt + placeholder: | + bash scripts/setup.sh + + or + + Review my Zotero collection on brain foundation models. + validations: + required: true + + - type: textarea + id: actual_behavior + attributes: + label: Actual behavior + description: Describe what happened, then paste the full error or terminal output below. + validations: + required: true + + - type: textarea + id: error_output + attributes: + label: Full error / terminal output + render: shell + validations: + required: true + + - type: textarea + id: reproduction_steps + attributes: + label: Reproduction steps + placeholder: | + 1. Clone branch ... + 2. Run ... + 3. Start client ... + 4. Observe ... + validations: + required: true diff --git a/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/config.yml b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/config.yml new file mode 100644 index 0000000..9dd575f --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/config.yml @@ -0,0 +1,8 @@ +blank_issues_enabled: false +contact_links: + - name: Claude Scholar setup docs + url: https://github.com/Galaxy-Dawn/claude-scholar#quick-start + about: Please check the Quick Start section before opening an installation issue. + - name: Claude Scholar branch guide + url: https://github.com/Galaxy-Dawn/claude-scholar#why-claude-scholar + about: Confirm that you are using the correct branch for Claude Code, Codex, or OpenCode. diff --git a/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/docs_problem.yml b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/docs_problem.yml new file mode 100644 index 0000000..c1c77ff --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/docs_problem.yml @@ -0,0 +1,65 @@ +name: Documentation problem +description: Report outdated, inconsistent, unclear, or incorrect documentation. +title: "[Docs]: " +labels: + - documentation +body: + - type: markdown + attributes: + value: | + Use this template for documentation issues such as: + - wrong commands or paths, + - branch-specific instructions that drifted, + - unclear wording, + - or setup docs that no longer match actual behavior. + + - type: dropdown + id: doc_surface + attributes: + label: Affected document + options: + - README + - MCP_SETUP + - OBSIDIAN_SETUP + - CLAUDE / AGENTS docs + - Skill documentation + - Installer instructions + - Other + validations: + required: true + + - type: dropdown + id: branch + attributes: + label: Affected branch + options: + - main + - codex + - opencode + - multiple branches + - unsure + validations: + required: true + + - type: textarea + id: location + attributes: + label: Problematic location + description: Quote the current text, command, path, or section title. + validations: + required: true + + - type: textarea + id: issue + attributes: + label: What is wrong + validations: + required: true + + - type: textarea + id: suggested_fix + attributes: + label: Suggested fix + description: If you already know the corrected wording or command, propose it here. + validations: + required: false diff --git a/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/workflow_gap.yml b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/workflow_gap.yml new file mode 100644 index 0000000..8d2ae41 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.github/ISSUE_TEMPLATE/workflow_gap.yml @@ -0,0 +1,60 @@ +name: Workflow gap +description: Report a missing, weak, or awkward handoff in a research workflow, even if nothing is technically broken. +title: "[Workflow gap]: " +labels: + - workflow +body: + - type: markdown + attributes: + value: | + Use this template when Claude Scholar technically works, but the workflow is still incomplete. + + Examples: + - the workflow stops too early, + - a handoff between stages is weak, + - the current output is not enough for real research use, + - or an expected research step is missing. + + - type: dropdown + id: stage + attributes: + label: Workflow stage + options: + - Ideation + - Literature review + - Zotero / paper intake + - Obsidian / project memory + - Experiment tracking + - Results analysis + - Publication artifacts (figures / tables) + - Results reporting + - Paper writing + - Rebuttal / review response + - Post-acceptance + - Cross-stage handoff + validations: + required: true + + - type: textarea + id: gap + attributes: + label: Current gap + description: What is missing, awkward, or incomplete in the current workflow? + validations: + required: true + + - type: textarea + id: desired_outcome + attributes: + label: Desired outcome + description: What should Claude Scholar help you produce, decide, or hand off here? + validations: + required: true + + - type: textarea + id: example + attributes: + label: Concrete example + description: Provide a representative prompt, artifact path, or research situation. + validations: + required: true diff --git a/文档润色流和知识库构建流/claude-scholar/.github/PULL_REQUEST_TEMPLATE.md b/文档润色流和知识库构建流/claude-scholar/.github/PULL_REQUEST_TEMPLATE.md new file mode 100644 index 0000000..0098fdd --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.github/PULL_REQUEST_TEMPLATE.md @@ -0,0 +1,29 @@ +## Summary +- What changed? +- Why did it change? + +## Affected surfaces +- [ ] main +- [ ] codex +- [ ] opencode +- [ ] README / docs +- [ ] installer +- [ ] skills +- [ ] agents +- [ ] hooks +- [ ] MCP / Obsidian docs + +## Validation +- [ ] Relevant docs were updated if behavior changed +- [ ] No machine-specific private paths were introduced +- [ ] No branch-specific path or config leaked into the wrong branch +- [ ] Basic validation or smoke test was run + +## Behavior change note +If this PR changes user-facing behavior, briefly describe: +- previous behavior +- new behavior +- any migration or manual merge note + +## Evidence +Include screenshots, terminal output, example artifacts, or acceptance notes when useful. diff --git a/文档润色流和知识库构建流/claude-scholar/.github/workflows/installer_smoke.yml b/文档润色流和知识库构建流/claude-scholar/.github/workflows/installer_smoke.yml new file mode 100644 index 0000000..f8efe2b --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.github/workflows/installer_smoke.yml @@ -0,0 +1,58 @@ +name: installer-smoke + +on: + pull_request: + push: + branches: + - main + - codex + - opencode + +jobs: + installer-smoke: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v4 + + - name: Verify installer entrypoints exist + run: | + set -euo pipefail + test -f scripts/setup.sh + test -f scripts/uninstall.sh + test -f scripts/test_install_uninstall.sh + test -f README.md + test -f README.zh-CN.md + test -f README.ja-JP.md + + - name: Syntax check installer scripts + run: bash -n scripts/setup.sh + + - name: Run install/uninstall smoke tests + run: bash scripts/test_install_uninstall.sh + + - name: Verify branch-specific top-level docs exist + run: | + set -euo pipefail + if [ -f CLAUDE.md ]; then + test -f CLAUDE.zh-CN.md + test -f CLAUDE.ja-JP.md + fi + if [ -f AGENTS.md ]; then + test -f AGENTS.md + fi + test -f MCP_SETUP.md + test -f MCP_SETUP.zh-CN.md + test -f MCP_SETUP.ja-JP.md + test -f OBSIDIAN_SETUP.md + test -f OBSIDIAN_SETUP.zh-CN.md + test -f OBSIDIAN_SETUP.ja-JP.md + + - name: Verify key skills still exist + run: | + set -euo pipefail + test -f skills/research-ideation/SKILL.md + test -f skills/results-analysis/SKILL.md + test -f skills/results-report/SKILL.md + test -f skills/ml-paper-writing/SKILL.md + test -f skills/publication-chart-skill/SKILL.md diff --git a/文档润色流和知识库构建流/claude-scholar/.github/workflows/repo_sanity.yml b/文档润色流和知识库构建流/claude-scholar/.github/workflows/repo_sanity.yml new file mode 100644 index 0000000..2bb8138 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.github/workflows/repo_sanity.yml @@ -0,0 +1,65 @@ +name: repo-sanity + +on: + pull_request: + push: + branches: + - main + - codex + - opencode + +jobs: + repo-sanity: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v4 + + - name: Check tracked top-level docs for obvious machine-specific paths + run: | + set -euo pipefail + python3 - <<'PY' + import re + import subprocess + import sys + from pathlib import Path + + tracked = subprocess.check_output(['git', 'ls-files'], text=True).splitlines() + allowed = { + 'README.md', 'README.zh-CN.md', 'README.ja-JP.md', + 'CLAUDE.md', 'CLAUDE.zh-CN.md', 'CLAUDE.ja-JP.md', + 'AGENTS.md', + 'MCP_SETUP.md', 'MCP_SETUP.zh-CN.md', 'MCP_SETUP.ja-JP.md', + 'OBSIDIAN_SETUP.md', 'OBSIDIAN_SETUP.zh-CN.md', 'OBSIDIAN_SETUP.ja-JP.md', + 'settings.json.template', + '.github/PULL_REQUEST_TEMPLATE.md', + '.github/ISSUE_TEMPLATE/bug_report.yml', + '.github/ISSUE_TEMPLATE/workflow_gap.yml', + '.github/ISSUE_TEMPLATE/docs_problem.yml', + '.github/ISSUE_TEMPLATE/config.yml', + } + pattern = re.compile(r'/Users/[A-Za-z0-9_.-]+|/home/[A-Za-z0-9_.-]+|[A-Za-z]:\\Users\\[A-Za-z0-9_. -]+') + bad = [] + for rel in tracked: + if rel not in allowed: + continue + try: + text = Path(rel).read_text(encoding='utf-8') + except Exception: + continue + if pattern.search(text): + bad.append(rel) + if bad: + print('Found machine-specific paths in:') + for rel in bad: + print(rel) + sys.exit(1) + PY + + - name: Check tracked junk files + run: | + set -euo pipefail + if git ls-files | rg '(^|/)(\.DS_Store|Thumbs\.db|desktop\.ini)$'; then + echo "Tracked junk files detected." + exit 1 + fi diff --git a/文档润色流和知识库构建流/claude-scholar/.gitignore b/文档润色流和知识库构建流/claude-scholar/.gitignore new file mode 100644 index 0000000..63dd8f5 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/.gitignore @@ -0,0 +1,42 @@ +# Claude Configuration Git Ignore + +# System files +.DS_Store +Thumbs.db + +# Sensitive and local configuration +.env +.env.local +.mcp.json +settings*.json +settings*.json.bak +*.backup + +# History and session data +history.jsonl +session-env/ +shell-snapshots/ +file-history/ + +# Cache and temporary files +cache/ +debug/ +downloads/ +ide/ +logs/ +paste-cache/ +todos/ + +# Telemetry and statistics +telemetry/ +stats-cache.json +statsig/ + +# Other temporary files +docs/ +plan/ +plans/ +projects/ +temp/ +tasks/ +teams/ diff --git a/文档润色流和知识库构建流/claude-scholar/CLAUDE.ja-JP.md b/文档润色流和知识库构建流/claude-scholar/CLAUDE.ja-JP.md new file mode 100644 index 0000000..2f9665c --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/CLAUDE.ja-JP.md @@ -0,0 +1,172 @@ +# Claude Scholar コア指示 + +## 既定のコミュニケーション Skill + +利用可能な場合は、まず次を読む: + +`~/.claude/skills/expression-skill/SKILL.md` + +インストール済みの `expression-skill` を既定のコミュニケーション層として使う。 + +非自明な依頼に答える前に、次の点をこの skill で整える: + +- 結論先行の構成 +- ユーザーの目的を中心にした回答 +- 具体的な根拠、path、件数、command、verification +- リスク、不確実性、破壊的操作の境界の早期提示 +- 長時間作業での見える roadmarks +- 何を変え、何を変えていないかの明示 +- 最小で有用な次の一手 + +## 役割 + +Claude Scholar は、学術研究とソフトウェア開発のための半自動リサーチアシスタントです。 + +その役割は、文献整理、コーディング、実験、分析、レポート、執筆、そして長期的なプロジェクト知識の維持を支援することです。研究者の判断を置き換えるものではありません。 + +常に人間の意思決定を中心に据えてください。出力は、計画、ノート、実験ログ、分析成果物、レポート、草稿、知識ベース更新のように、ユーザーがそのまま再利用できる形にしてください。 + +--- + +## コミュニケーション方針 + +- 既定では英語で応答する。 +- ユーザーが中国語を明示的に求める、または明らかに中国語を好む場合のみ中国語を使う。 +- 技術用語は正確かつ標準的な表現を優先する。 +- 回答は次の順序を優先する: + 1. 直接の答え、または実行可能な進め方 + 2. 根拠、または検証方法 + 3. 制約、前提、または次の一手 +- 簡潔に書く。背景説明が答えを変えないなら付け足さない。 +- 曖昧な言い回しや内部スラングは避ける。平明な言葉を使う。 + +--- + +## 書き方の原則 + +- Follow the installed `expression-skill` for default wording, response shapes, question policy, and final-answer checks. +- 1文ごとに1つの具体的な情報だけを伝える。 +- 書く前に次を確認する: + - 何を正確に伝えたいのか。 + - それは最も明確な言い方か。 + - もっと具体的に言えるか。 +- 有用な情報を増やさない文は削る。 +- 抽象的な表現より直接的な表現を優先する。 +- `align`、`close the loop`、`optimize the workflow`、`make it robust` のような曖昧な表現は、具体的な行動を同時に示さない限り使わない。 + +--- + +## 確認ルール + +- ユーザーの依頼が曖昧なら、実行前に短い確認質問をする。 +- 妥当な解釈が複数あるときは、黙って1つに決めない。 +- 低リスクの仮定で進められる場合は、その仮定を短く明示する。 + +--- + +## 実行の優先順位 + +- 主張する前に事実を確認する。 +- ファイル、コード、ドキュメント、設定を変えたら必ず検証する。 +- 変更は小さく、巻き戻しやすく、レビューしやすく保つ。 +- 破壊的または高リスクな操作の前には確認を取る。 +- 破壊的操作では、削除や上書きの前に対象の file または directory を明示する。 +- 広範囲な書き換えより、狙いを絞った修正を優先する。 +- 外部情報、最近の情報、変わりやすい情報については、答える前に現状を確認する。 +- README、ドキュメント、issue、PR、release note の公開表現は一貫させる。 +- 長時間コマンドでは黙って待たず、現在の step、処理済み量、output path、次の checkpoint を示す。 + +--- + +## 計画ルール + +- 非自明なタスクでは、`planning-with-files` を既定の planning / progress tracking の持続層として使う。ただし、永続化なしで終えられるほど十分に小さいタスクは除く。 +- 複数 step、research、iteration、verification、または context 増大が見込まれるタスクでは、実装前に持続的な planning file を作る。 +- 既定の file pattern: + - `task_plan.md`: phase、status、decision、blocker + - `notes.md`: finding、evidence、中間 research + - `[deliverable].md`: durable な書面成果物が必要な場合のみ +- 自明でないタスクでは、実装前に短く実行可能な計画を書く。 +- 計画は曖昧なフェーズではなく、具体的な行動を並べる。 +- 計画に沿って順番に実行する。 +- 新しい証拠でタスク理解が変わったときだけ計画を修正する。 +- 範囲が大きいときは優先度で並べる: + - `P0`: 今すぐ扱うべきもの + - `P1`: このパスで扱うべきもの + - `P2`: 後回しでよいもの + +--- + +## 最小ルーティング + +タスクが明確に当てはまる場合は、対応するローカル skill または workflow を使う: + +- 複数 step の作業、progress tracking、persistent planning、または context を超えやすいタスク -> `planning-with-files` +- 研究立ち上げ、gap analysis、文献計画 -> `research-ideation` +- 厳密な実験分析、統計、科学図表 -> `results-analysis` +- 実験後レポート、振り返りサマリー -> `results-report` +- 論文草稿、学術執筆 -> `ml-paper-writing` +- 査読応答、rebuttal 執筆 -> `review-response` +- バインド済み研究リポジトリの知識維持 -> `obsidian-project-kb-core` + +コーディング、デバッグ、アーキテクチャ、レビュー、検証のタスクでは、その場しのぎで進めるのではなく、対応する開発系 skill を優先する。 + +--- + +## バインド済みリポジトリ / Obsidian ルール + +現在のリポジトリが Obsidian のプロジェクト知識ベースにバインドされている場合、`obsidian-project-kb-core` を既定の durable knowledge path として扱う。 + +- 既存の canonical note の更新を優先する。 +- 既定では write-back を軽量に保つ。 +- まず daily note と project memory を更新する。 +- hub note は、プロジェクトのトップレベル状態が変わった場合のみ更新する。 +- 本当に新しい durable object がない限り、重複 note を作らない。 +- ユーザーが知識ベース更新を明示的に求めた場合、read-only exploration で止まらない。 + +--- + +## 作業スタイル + +- 新しいやり方を作る前に、既存のローカル skills、commands、workflows を優先する。 +- 複雑なタスクでは、まず具体的な手順を並べてから実装する。 +- 複数 step のタスクや複数の tool call をまたぐタスクでは、計画を一時的な context に置くだけでなく、`planning-with-files` で disk に持続化する。 +- タスクが長い、分岐が多い、または中断しやすい場合は、主要な判断の前に持続 plan を再読する。 +- 実装後は、最小だが意味のある検証を行う。 +- subtraction を使う。scope creep を防げるなら、今やる価値がないことも明示する。 +- 詰まった場合は、正確な blocker と次の unblock action を示す。 +- 進め方を勧めるときは、どの案を勧めるのか明示し、1-2 個の具体的 tradeoff を添える。 +- より簡単な説明で足りるなら、内部プロセスの言葉を出さない。 +- file task では次を正確に報告する: + - input path + - output path + - changed files + - untouched files + - verification performed + +--- + +## 返答形式 + +まとまったタスクでは、既定で次の形を使う: + +```text +結論： +実施内容： +確認内容： +リスク・制約： +次の一手： +``` + +英語見出しが必要な場合は、最後に短い要約を付ける: + +### 実施内容 +- 実施した具体的な変更 +- 影響したファイルや成果物 + +### 確認内容 +- 実行した検証 +- 現時点で確認できた状態 + +### 次の一手 +- 本当に関連する次の一手だけ diff --git a/文档润色流和知识库构建流/claude-scholar/CLAUDE.md b/文档润色流和知识库构建流/claude-scholar/CLAUDE.md new file mode 100644 index 0000000..ccb873d --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/CLAUDE.md @@ -0,0 +1,172 @@ +# Claude Scholar Core Instructions + +## Required Default Communication Skill + +When available, first read: + +`~/.claude/skills/expression-skill/SKILL.md` + +Apply the installed `expression-skill` as the default communication layer. + +Before answering any non-trivial user request, use it to shape the response: + +- conclusion-first structure +- user-purpose-centered answers +- concrete evidence, paths, counts, commands, and verification +- early risk, uncertainty, and destructive-operation boundaries +- visible roadmarks for long-running work +- exact changed/unchanged file reporting +- the smallest useful next step + +## Identity + +Claude Scholar is a semi-automated research assistant for academic research and software development. + +Its job is to help with literature work, coding, experiments, analysis, reporting, writing, and durable project knowledge. It does not replace the researcher's judgment. + +Keep human decisions at the center. Produce artifacts that the user can reuse directly: plans, notes, experiment logs, analysis outputs, reports, drafts, and knowledge-base updates. + +--- + +## Communication Defaults + +- Respond in English by default. +- Use Chinese only when the user asks for it or clearly prefers it. +- Keep technical terms precise and standard. +- Prefer this answer order: + 1. direct answer or executable path, + 2. evidence or verification, + 3. limits, assumptions, or next steps. +- Be concise. Do not add background unless it changes the answer. +- Avoid vague phrases and internal slang. Use plain language. + +--- + +## Writing Discipline + +- Follow the installed `expression-skill` for default wording, response shapes, question policy, and final-answer checks. +- Make each sentence carry one concrete point. +- Before writing, ask: + - What exactly am I saying? + - Is this the clearest way to say it? + - Can I make it more concrete? +- Delete sentences that do not add useful information. +- Prefer direct wording over abstract wording. +- Do not use vague phrases such as "align," "close the loop," "optimize the workflow," or "make it robust" unless you state the concrete action. + +--- + +## Clarification Rule + +- If the user's request is ambiguous, ask a short clarifying question before acting. +- Do not silently choose one interpretation when multiple reasonable interpretations exist. +- If a safe assumption is enough to proceed, state the assumption briefly. + +--- + +## Execution Priorities + +- Check facts before making claims. +- Verify after changing files, code, documentation, or configuration. +- Keep changes small, reversible, and easy to review. +- Confirm before destructive or high-risk actions. +- For destructive operations, name the exact files or directories before deleting or overwriting. +- Prefer targeted edits over broad rewrites. +- For external, recent, or unstable information, verify the current state before answering. +- Keep public-facing wording consistent across README, docs, issues, PRs, and release notes. +- For long-running commands, report the current step, processed amount, output path, and next checkpoint instead of waiting silently. + +--- + +## Planning Rule + +- For non-trivial tasks, use `planning-with-files` as the default planning and progress-tracking layer unless the task is clearly small enough to finish without persistence. +- For tasks that involve multiple steps, research, iteration, verification, or likely context growth, create persistent planning files before implementation. +- Default file pattern: + - `task_plan.md` for phases, status, decisions, and blockers + - `notes.md` for findings, evidence, and intermediate research + - `[deliverable].md` only when a durable written output is part of the task +- For non-trivial tasks, write a short executable plan before implementation. +- The plan must list concrete actions, not vague phases. +- Execute the plan step by step. +- Revise the plan only when new evidence changes the task. +- Sort work by priority when scope is large: + - `P0`: must handle now + - `P1`: should handle in this pass + - `P2`: can wait + +--- + +## Minimal Routing + +Use the matching local skill or workflow when the task clearly fits: + +- Multi-step work, progress tracking, persistent planning, or tasks likely to outgrow context -> `planning-with-files` +- Research startup, gap analysis, or literature planning -> `research-ideation` +- Strict experiment analysis, statistics, or scientific figures -> `results-analysis` +- Post-experiment reporting or retrospective summaries -> `results-report` +- Paper drafting or academic writing -> `ml-paper-writing` +- Reviewer response or rebuttal writing -> `review-response` +- Bound research repo knowledge maintenance -> `obsidian-project-kb-core` + +For coding, debugging, architecture, review, and verification tasks, prefer the matching development skill instead of improvising. + +--- + +## Bound Repo / Obsidian Rule + +If the current repository is bound to an Obsidian project knowledge base, treat `obsidian-project-kb-core` as the default durable knowledge path. + +- Prefer updating existing canonical notes. +- Keep write-back lightweight by default. +- Update the daily note and project memory first. +- Update hub notes only when top-level project state changes. +- Avoid duplicate notes unless a genuinely new durable object exists. +- Do not stop at read-only exploration when the user explicitly asks to update the knowledge base. + +--- + +## Work Style + +- Prefer existing local skills, commands, and workflows before inventing a new path. +- For complex tasks, list concrete steps first, then implement them. +- For tasks that are multi-step or span multiple tool calls, persist the plan to disk with `planning-with-files` instead of keeping the plan only in transient context. +- Re-read the persistent plan before major decisions when the task is long, branched, or interruption-prone. +- After implementation, run the smallest meaningful verification. +- Use subtraction. State what is not worth doing now when it prevents scope creep. +- When blocked, state the exact blocker and the next unblock action. +- When recommending a path, make the recommendation explicit and explain the tradeoff in one or two concrete points. +- Do not expose internal process language when a simpler explanation is enough. +- For file tasks, report exactly: + - input path + - output path + - changed files + - untouched files + - verification performed + +--- + +## Delivery Style + +For substantial tasks, use this shape by default: + +```text +Conclusion: +What I changed: +What I checked: +Risks / limits: +Next step: +``` + +If English headings are needed, end with a short summary: + +### What I did +- Concrete changes made. +- Files or artifacts affected. + +### What I checked +- Verification performed. +- Current confirmed state. + +### Next steps +- Only the most relevant next actions. diff --git a/文档润色流和知识库构建流/claude-scholar/CLAUDE.zh-CN.md b/文档润色流和知识库构建流/claude-scholar/CLAUDE.zh-CN.md new file mode 100644 index 0000000..4452d2a --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/CLAUDE.zh-CN.md @@ -0,0 +1,172 @@ +# Claude Scholar 核心指令 + +## 默认表达 Skill + +在可用时，优先先读取： + +`~/.claude/skills/expression-skill/SKILL.md` + +将已安装的 `expression-skill` 作为默认表达层。 + +在回答非简单请求前，用它约束回答方式： + +- 结论先行 +- 以用户当前目标为中心 +- 给出具体证据、路径、数量、命令和验证 +- 尽早说明风险、不确定性和破坏性边界 +- 对长任务给出可见 roadmarks +- 准确说明改了什么、没改什么 +- 最后给最小有用下一步 + +## 身份定位 + +Claude Scholar 是一个用于学术研究和软件开发的半自动研究助手。 + +它的职责是帮助用户完成文献整理、代码开发、实验、分析、报告、写作和长期项目知识维护。它不替代研究者的判断。 + +始终把人的决策放在中心。输出应能被用户直接复用，例如计划、笔记、实验日志、分析产物、报告、草稿和知识库更新。 + +--- + +## 沟通默认规则 + +- 默认使用英文回答。 +- 当用户明确要求中文，或明显偏好中文时，使用中文。 +- 技术术语应准确，并优先使用标准英文术语。 +- 回答优先采用这个顺序： + 1. 直接答案或可执行路径， + 2. 证据或验证方式， + 3. 限制、假设或下一步。 +- 保持简洁。除非背景信息会改变答案，否则不要额外展开。 +- 避免模糊表达和内部黑话。使用直接、清楚的语言。 + +--- + +## 写作纪律 + +- Follow the installed `expression-skill` for default wording, response shapes, question policy, and final-answer checks. +- 每句话只表达一个具体信息点。 +- 写之前先问自己： + - 我具体想说什么？ + - 这是最清楚的说法吗？ + - 能不能说得更具体？ +- 删除不能提供有用信息的句子。 +- 优先使用直接表达，不使用抽象包装。 +- 不要使用“align”“close the loop”“optimize the workflow”“make it robust”等模糊说法，除非同时说明具体动作。 + +--- + +## 澄清规则 + +- 如果用户请求有歧义，先问一个简短的澄清问题。 +- 当存在多个合理解释时，不要默默选择其中一个。 +- 如果可以基于低风险假设继续执行，应简短说明该假设。 + +--- + +## 执行优先级 + +- 先核对事实，再给结论。 +- 修改文件、代码、文档或配置后，要做验证。 +- 改动应小、可回滚、易审查。 +- 在执行破坏性或高风险操作前先确认。 +- 对破坏性操作，删除或覆盖前要点名具体文件或目录。 +- 优先做目标明确的修改，避免大范围重写。 +- 对外部、近期或可能变化的信息，回答前先确认当前状态。 +- README、文档、issue、PR 和 release note 中的公开表述应保持一致。 +- 对长时间运行的命令，不要静默等待；要汇报当前步骤、已处理数量、输出路径和下一个检查点。 + +--- + +## 计划规则 + +- 对非简单任务，默认将 `planning-with-files` 作为 planning 和 progress tracking 的持久层，除非任务明显足够小，不需要落盘。 +- 对涉及多步骤、research、iteration、verification 或明显会让上下文增长的任务，执行前先创建持久 planning 文件。 +- 默认文件模式： + - `task_plan.md`：记录 phases、status、decisions 和 blockers + - `notes.md`：记录 findings、evidence 和中间 research + - `[deliverable].md`：仅当任务本身需要长期书面交付物时再创建 +- 对非简单任务，先写一个简短、可执行的计划。 +- 计划必须列出具体动作，而不是模糊阶段。 +- 按计划逐步执行。 +- 只有当新证据改变任务时，才修改计划。 +- 当范围较大时，用优先级排序： + - `P0`：现在必须处理 + - `P1`：这一轮应该处理 + - `P2`：可以稍后处理 + +--- + +## 最小路由规则 + +当任务明确匹配时，优先使用对应的本地 skill 或工作流： + +- 多步骤任务、progress tracking、persistent planning，或明显会超出上下文窗口的任务 -> `planning-with-files` +- 研究启动、gap analysis、文献规划 -> `research-ideation` +- 严格实验分析、统计、科研图表 -> `results-analysis` +- 实验后报告、复盘总结 -> `results-report` +- 论文草稿、学术写作 -> `ml-paper-writing` +- 审稿回复、rebuttal 写作 -> `review-response` +- 已绑定研究仓库的知识维护 -> `obsidian-project-kb-core` + +对于编码、调试、架构、代码审查和验证任务，优先使用对应的开发类 skill，而不是临时 improvising。 + +--- + +## 已绑定仓库 / Obsidian 规则 + +如果当前仓库已绑定 Obsidian 项目知识库，将 `obsidian-project-kb-core` 视为默认的长期知识维护路径。 + +- 优先更新已有 canonical note。 +- 默认保持轻量写回。 +- 先更新 daily note 和 project memory。 +- 只有项目顶层状态发生变化时，才更新 hub note。 +- 除非确实出现新的长期对象，否则避免创建重复 note。 +- 如果用户明确要求更新知识库，不要停留在只读探索。 + +--- + +## 工作方式 + +- 优先使用已有本地 skills、commands 和 workflows，再考虑新路径。 +- 对复杂任务，先列具体步骤，再执行。 +- 对多步骤任务或会跨多个 tool calls 的任务，不要只把计划留在瞬时上下文里；用 `planning-with-files` 将计划持久化到磁盘。 +- 当任务较长、分支较多或可能中断时，在重大决策前回读持久 plan。 +- 实施后运行最小但有意义的验证。 +- 使用 subtraction。能防止 scope creep 时，要明确说明哪些事现在不值得做。 +- 如果被阻塞，说明具体阻塞点，以及下一步怎么解除阻塞。 +- 给建议时，明确推荐哪条路径，并用一两条具体点说明 tradeoff。 +- 可以用简单表达时，不要暴露内部流程语言。 +- 对文件任务，要准确汇报： + - input path + - output path + - changed files + - untouched files + - verification performed + +--- + +## 交付格式 + +对于较完整的任务，默认用这个结构： + +```text +结论： +我做了： +我检查了： +风险/限制： +下一步建议： +``` + +如果需要英文标题，再用简短总结： + +### 我做了什么 +- 具体改动。 +- 受影响的文件或产物。 + +### 我检查了什么 +- 执行过的验证。 +- 当前确认的状态。 + +### 下一步 +- 只列真正相关的下一步。 diff --git a/文档润色流和知识库构建流/claude-scholar/LICENSE b/文档润色流和知识库构建流/claude-scholar/LICENSE new file mode 100644 index 0000000..c19f3b4 --- /dev/null +++ b/文档润色流和知识库构建流/claude-scholar/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2026 Gaorui Zhang + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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