| name | self-improving |
| description | Capture learnings, errors, and corrections from conversations for continuous self-improvement. Use when: completing a complex task, encountering an error and fixing it, learning a user preference, or discovering a better approach. |
| metadata | {"rooster":{"emoji":"🧠","category":"meta","kits":["System"],"platform":["any"],"requires":{"python_packages":[],"bins":[],"env_vars":[]}}} |
Self-Improving Agent
Automatically capture insights from task execution to improve future performance.
When to Record Learnings
Record a learning when:
- Error → Fix pattern: You encountered an error and found a working solution
- User correction: The user corrected your approach or output
- Preference discovery: You learned the user prefers a specific style, format, or tool
- Optimization found: You discovered a faster or better way to accomplish something
- Tool discovery: You found a tool combination that works well for a specific domain
How to Record
Use the memory_add_fact tool to store learnings as structured facts:
Type: learning
Content: "When doing X, prefer Y because Z"
Confidence: high|medium|low
Categories
- tool-pattern: Effective tool combinations or sequences
- error-recipe: Common errors and their fixes
- user-preference: User-specific preferences (style, format, language)
- performance: Faster approaches or shortcuts discovered
- domain-knowledge: Facts learned about the user's project/domain
Anti-Patterns (Do NOT Record)
- Obvious or trivial facts
- Temporary state (file paths, current date)
- Speculative guesses without evidence
- Duplicate or contradictory existing learnings
