handoff

Files (1)

• SKILL.md

SKILL.md (first lines)

# Handoff — Session Continuation Summary

Use this skill to generate a structured handoff summary when transitioning work to a new session.

**Policy-safe storage:** keep handoffs in `/memories/session/` during the conversation. Do not create ad-hoc `.md` files in the repository root.

---

## When to Use

- Session is ending but work is incomplete
- Computer crash or logout mid-feature
- Switching to a different machine
- User wants to start fresh but continue the same work
- Context window is getting full and a fresh session would help

---

## Handoff Format

```markdown
# Handoff: <Feature Name>

## Current Status
- Wave N completed (<description>)
- Wave N+1 pending (<description>)
- Current task: <what was being worked on>

## What Was Completed
- <file/path> — <what was implemented>
- <file/path> — <what was implemented>
- <file/path> — <what was implemented>

## Remaining Work
- <remaining task 1>
- <remaining task 2>
- <remaining task 3>

## Key Decisions
- <decision 1> (rationale)
- <decision 2> (rationale)

## Learnings (from wisdom accumulation)
- <convention 1>
- <gotcha 1>
- <failure to avoid 1>

## Relevant Files
- <path/to/file1>
- <path/to/file2>
- <path/to/file3>

## Tasks Status (if using Task System)
- T-001 [completed] <subject>
- T-002 [completed] <subject>
- T-003 [in_progress] <subject>
- T-004 [pending] <subject>

## Next Steps
1. <immediate next action>
2. <following action>
3. <eventual action>
```

---

## How to Persist Handoff (Policy-Compliant)

When user runs `/handoff`:

```
1. Mnemosyne reads current session state
2. Mnemosyne reads /memories/session/* (if relevant)
3. Mnemosyne generates handoff summary
4. Mnemosyne saves to /memories/session/handoff-<timestamp>.md
5. Mnemosyne outputs the summary in chat
6. At sprint close, promote only durable context to .pantheon/memory-bank via explicit @mnemosyne action
```

---

## How New Session Uses Handoff

When starting a new session:

```
1. User pastes handoff document (or references file path)
2. New session reads handoff
3. Agent resumes from "Next Steps"
4. Tasks continue from last known state
5. Learnings are re-injected
```

---

## Example

```markdown
# Handoff: Product Reviews

## Current Status
- Wave 2 completed (backend endpoints + frontend with mocks)
- Wave 3 pending (real API integration)
- Current task: Connecting ReviewCard to real GET /reviews API

## What Was Completed
- src/routes/reviews/post.py — POST /reviews endpoint
- src/routes/reviews/get.py — GET /reviews with pagination
- src/components/ReviewCard.tsx — ReviewCard with mocked data
- alembic/versions/xxx_reviews.py — reviews table migration

## Remaining Work
- Connect ReviewCard to real GET /reviews API
- Add ReviewForm component
- Integration tests
- Error handling for 404/500

## Key Decisions
- Use Redis for review cache (TTL 5min) — decided after Wave 2 performance testing

From ils15/pantheon-legacy, MIT.

More from ils15/pantheon-legacy