Claude Handoff — AI skill for Claude Code
Summarize & export a Claude Code session into one clean handoff.md for Gemini, GPT, or another Claude.
How to install Claude Handoff
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open Vasilispapg/claude-handoff and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Claude Handoff does
Summarize & export a Claude Code session into one clean handoff.md for Gemini, GPT, or another Claude. Zero deps, single file, post-hoc.
Alternatives in AI
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- Fusion Plan — OMC interview (interactive) → 3-round Opus 4.8 + GPT-5.5 fusion deepening → concise .omc/plans/ output → revie 468 ★
README
claude-handoff

[](https://pypi.org/project/claude-handoff/) [](https://pypi.org/project/claude-handoff/) [](https://github.com/Vasilispapg/claude-handoff/actions/workflows/ci.yml) [](https://pypi.org/project/claude-handoff/) [](LICENSE)
**Turn any Claude Code session — even a crashed one — into a clean `handoff.md` another AI can continue from. And give Claude Code permanent project memory, distilled from your own history.**
chf
That's it. Your latest session becomes `handoff.md`: the conversation without the noise, the files that changed, the commands that ran — opening with instructions to the receiving assistant, so you can paste it straight into Gemini, GPT, claude.ai, or a fresh Claude Code session with zero extra prompting.

Claude Code stores every session locally as JSONL (`~/.claude/projects/…/*.jsonl`), full of tool calls, tool results, thinking blocks and system reminders. Existing exporters dump all of that into markdown. `claude-handoff` instead produces a **handoff document** — and, since it can read your *entire* history, a **project memory brief** too.
- Zero dependencies. Stdlib only, Python 3.9+. A nine-module package —
also shipped as a generated single-file script you can
curland audit. - Deterministic by default. No API call, no cost, works offline.
--llmwhen you want a real summary. Claude, OpenAI or Gemini via your own API key — or `--llm
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