行動清單核對
- 先確認使用者指定的輸入檔案與輸出檔案;未指定時先詢問,不自行猜測。
- 只讀取指定輸入,不修改原檔案。
- 每個行動項必須包含:事項、負責人、截止日期、限制或驗收條件。
- 原文沒有的資訊寫“原文未說明”,不補寫人名或日期。
- 寫入後重新讀取輸入與輸出,逐項核對遺漏、重複和臆測。
- 最後報告讀取路徑、寫入路徑、行動項數量和仍不確定的內容。
把會議記錄整理為可核對的行動清單;當任務要求提取負責人、截止日期、交付物和限制時使用。
| Publisher | xiaomoBoy |
| Repository | pi-bluebook |
| Skill name | action-list-review |
| Stars | 325 |
| Forks | 20 |
| 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 xiaomoBoy on GitHub. Read the source before you install it.
Install the Action List Review 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/xiaomoBoy/pi-bluebook/tree/main/docs/public/examples-tw/skill/action-list-reviewAny 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/xiaomoBoy/pi-bluebook.git /tmp/pi-bluebook
mkdir -p .claude/skills
cp -r /tmp/pi-bluebook/docs/public/examples-tw/skill/action-list-review .claude/skills/action-list-reviewEnable Action List Review 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 Action List Review 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.
把會議記錄整理為可核對的行動清單;當任務要求提取負責人、截止日期、交付物和限制時使用。
Because you install it once and use it with any model. Action List Review 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/xiaomoBoy/pi-bluebook/tree/main/docs/public/examples-tw/skill/action-list-review. 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 Action List Review 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 xiaomoBoy 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.
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