Session Learnings

Get current date and time:

date +"%Y-%m-%d_%H%M"

# Session: YYYY-MM-DD — <Session Title>

## Summary
Brief 2-3 sentence overview of what was accomplished in this session.

## Files Changed
- `path/to/file.py` — What changed and why
- `path/to/other.ts` — What changed and why

## Decisions & Rationale
| Decision | Alternatives Considered | Why Chosen |
|----------|------------------------|------------|
| Choice made | Other options explored | Reasoning |

## Learnings
- Insight discovered during this session
- Another learning

## Subagent Analysis
| Agent | Task | Outcome | Notes |
|-------|------|---------|-------|
| agent-type | What it was asked to do | Success/Failed/Partial | Why this agent was chosen, what happened |

## Mistakes & Corrections
- **Mistake**: What went wrong
  - **Fix**: How it was corrected
  - **Prevention**: How to avoid this next time

## Unfinished Work
- [ ] Remaining TODO item
- [ ] Another item to pick up next session

## Memory Promotion Candidates
> These insights may be worth adding to MEMORY.md:
- Insight that should persist across sessions
- Pattern or convention discovered

6. Report results — print:
   • The file path that was created
   • The memory promotion candidates (so the user can decide whether to promote them)
   • If the session was trivial (no meaningful changes or learnings), say so and skip file creation

Guidelines

• Be thorough in the subagent analysis — capture WHY each agent was chosen, not just what it did
• For decisions, always include at least one alternative that was considered (even if it was briefly dismissed)
• Only include sections that have content — skip empty sections rather than writing "None"
• The summary should be useful to someone reading it weeks later with no context
• For mistakes, focus on the prevention angle — what to do differently next time
• Memory promotion candidates should be things that are broadly applicable, not session-specific details