写一份交接文档,总结当前这次对话,好让一个全新的代理能接着干活。保存到用户操作系统的临时目录——不是当前工作区。
文档里要有一节「建议调用的技能」,写明下一个代理应当为哪些技能调用 Skill 工具。
不要重复其他产物(规格说明、计划、ADR、议题、提交、差异)里已经记下的内容,改用路径或 URL 引用它们。
任何敏感信息都要脱敏,例如 API 密钥、密码或可识别个人身份的信息。
如果用户传了参数,就把它们当作对下一次会话关注点的描述,并据此调整文档。
把当前这次对话压缩成一份交接文档,供另一个代理接手。
| Publisher | FeatherHunter |
| Repository | dsh-mattpocock-skills-deck |
| Skill name | handoff |
| Stars | 263 |
| Forks | 22 |
| Bundled files | Instructions only |
| License | MIT |
| Links |
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Everything the model needs lives in the instructions — no extra files to sync.
Published by FeatherHunter on GitHub. Read the source before you install it.
Install the Handoff AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.
TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.
https://github.com/FeatherHunter/dsh-mattpocock-skills-deck/tree/main/package/bundled-skills-zh/handoffAny agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.
git clone --depth 1 https://github.com/FeatherHunter/dsh-mattpocock-skills-deck.git /tmp/dsh-mattpocock-skills-deck
mkdir -p .claude/skills
cp -r /tmp/dsh-mattpocock-skills-deck/package/bundled-skills-zh/handoff .claude/skills/handoffEnable Handoff in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.
AI skills are plain Markdown instructions rather than provider-specific code, so Handoff is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.
This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.
写一份交接文档,总结当前这次对话,好让一个全新的代理能接着干活。保存到用户操作系统的临时目录——不是当前工作区。
文档里要有一节「建议调用的技能」,写明下一个代理应当为哪些技能调用 Skill 工具。
不要重复其他产物(规格说明、计划、ADR、议题、提交、差异)里已经记下的内容,改用路径或 URL 引用它们。
任何敏感信息都要脱敏,例如 API 密钥、密码或可识别个人身份的信息。
如果用户传了参数,就把它们当作对下一次会话关注点的描述,并据此调整文档。
把当前这次对话压缩成一份交接文档,供另一个代理接手。
Because you install it once and use it with any model. Handoff is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/FeatherHunter/dsh-mattpocock-skills-deck/tree/main/package/bundled-skills-zh/handoff. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.
Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.
As many as you like. As long as a model supports skills, you can use Handoff with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
Yes. It is published on GitHub by FeatherHunter under the MIT license. You only pay your own AI provider for the tokens you use.
An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.
A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.
Openclaw Pr Maintainer
Review, triage, repair, or land OpenClaw issues and pull requests with current-source evidence and the native maintainer workflow.
Solid
Write, port, review, or test Solid 2 UI in OpenClaw (Control UI, plugin views, Canvas hosts), including state ownership, Lit interop during the migration, native overlays, testing, performance, and…
Agent Transcript
Requested GitHub PR/issue agent transcripts: redact, trim, preview, and insert safely.
Auto Qa
Run OpenClaw-wide autonomous QA and live/stress campaigns across independent subsystem lanes, with verified fixes and a resumable evidence report.
Get notified about new features and future giveaways by subscribing to our newsletter 👇
