By name: capture-learning description: Capture significant learnings from the current work session. Structures insights for future sessions and updates agent memory. argument-hint: [optional topic or context] user-invocable: true
Reflect on the current session and capture learnings. Context: $ARGUMENTS
Process
1. Reflect
- What was the main problem being solved?
- What non-obvious insights emerged?
- What patterns are reusable in future work?
- What failed and why?
2. Structure the Learning
Format each learning as:
### [Date]: [Title]
- **Issue**: [The problem encountered]
- **Solution**: [What worked]
- **Pattern**: [The reusable principle extracted]
- **Files**: [Key file references, if applicable]
- **Freshness**: HOT (actively relevant) | WARM (occasionally relevant) | COLD (reference only)
3. Store
Write the learning to the appropriate location:
- Agent-specific patterns: Update the relevant agent's project memory
- Project-wide rules: Add to
.claude/rules/as a new file or append to an existing one - Debugging insights: Add to auto-memory
MEMORY.md
4. Calibrate
Check existing learnings for staleness:
- Are any HOT items now WARM or COLD?
- Are any previous learnings contradicted by what we learned today?
- Remove or update anything that's no longer accurate.