3.4 KiB
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:
## 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