본문으로 건너뛰기
cccskills
무료GitHub에 공개

session-handoff

Use when a working session is ending, the context window is nearly full, work needs to pass to a teammate or a fresh session, or the user says "hand this off", "write this up before we lose it", "I'm starting a new session", or "summarize where we are". Produces a handoff document that lets the next session resume without re-reading the transcript.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md3.9 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Session Handoff

A session ends three ways: the context fills up, the person leaves, or the work moves to someone else. All three lose the same thing — the reasoning that never made it into a file. This skill writes that reasoning down before it evaporates.

Core Behavior

Write a handoff file, do not summarize in chat. Chat scrolls away; a file survives a /clear, a crash, and a different person opening the repo tomorrow.

Default path: HANDOFF.md at the repo root, or docs/handoff/<yyyy-mm-dd>-<topic>.md if the repo already has a docs convention. If a handoff file exists, append a new dated section rather than overwriting — the history of what was tried is half the value.

What Goes In It

Write these sections in this order. Skip a section only when it is genuinely empty.

Goal. One sentence: what this work is supposed to achieve, in the user's terms, not the ticket's.

State. What is done, what is half-done, what has not been started. Be specific about half-done — "auth works, but the refresh-token path is stubbed and returns a fixed string" beats "auth in progress".

Files touched. Path plus one line on what changed and why. Include files you read and decided not to change when the decision was non-obvious.

Decisions and why. The choices a reasonable person would question. Each one: what was chosen, what was rejected, and the reason. This is the section that saves the next session an hour.

Dead ends. What was tried and did not work. Name the failure mode. Without this, the next session repeats it.

Next step. The single next action, concrete enough to start on immediately. Not "continue the refactor" — "extract parseInvoice from billing.ts:210 into its own module, then point the three callers at it".

Open questions. Anything waiting on a human. Name who, and what the question is.

How to Gather It

Prefer evidence over memory:

  • git status and git diff --stat for what actually changed on disk.
  • git log --oneline -15 for what landed.
  • Test/build output from the last run, if there was one.
  • The user's own words for the goal — quote them rather than paraphrasing into corporate language.

If the transcript disagrees with the repo, the repo wins. Say so in the handoff.

Rules

  • No status-report padding. No "we made great progress". A handoff is field notes, not a stakeholder update.
  • Include the commands to get back to a working state: the dev-server command, the test command, any env var that has to be set.
  • Never claim something works that you did not see work. Write "untested" next to it.
  • If work is on a branch, name the branch and the base it forked from.
  • Uncommitted changes: say so explicitly at the top, and list them. That is the most common way work gets lost.

Output Format

# Handoff — <topic> — <date>

**Goal:** <one sentence>

**Branch:** <name> (base: <name>) · **Uncommitted:** <yes, list / no>

## State
- Done: ...
- In progress: ...
- Not started: ...

## Files
- `path/to/file.ts` — <what and why>

## Decisions
- <chose X over Y because Z>

## Dead ends
- <tried X, failed with Y — don't repeat>

## Next step
<one concrete action>

## Open questions
- <question> — needs <person>

## Getting back to work
```bash
<commands>

## When the Context Window Is the Reason

If the handoff is being written because context is nearly full, write the file first, before any other work. Then tell the user to start a fresh session and open the file. Do not try to squeeze in one more fix — a truncated handoff is worse than an early one.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3612026년 10월 20일 업데이트

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3612026년 10월 20일 업데이트

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3612026년 10월 20일 업데이트

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3612026년 10월 20일 업데이트

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3612026년 10월 20일 업데이트

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3612026년 10월 20일 업데이트

OneWave-AI의 스킬 모두 보기

이 스킬의 문제 신고