三点摘要
将任意输入文本精炼为恰好三个要点,每个要点一句话。
工作流程
- 通读全文,识别核心论点与关键信息
- 按重要性排序,提取最关键的三个独立观点
- 每个要点压缩为一句简洁、完整、可独立理解的陈述
输出格式
- [要点一] - [要点二] - [要点三]
规则
- 恰好三条,不多不少
- 每条一句话,不超过 30 字
- 保留原文核心含义,不添加推测
- 去除冗余修饰,只留干货
- 如原文信息不足三点,从不同角度拆分主论点
三点摘要:将输入文本提炼为三个要点。适用于:用户提供一段文字并要求总结、提炼要点、 生成摘要,或明确要求"三个要点""三点总结""bullet points"等场景。
| Publisher | laborany |
| Repository | laborany |
| Skill name | three-bullet-summary |
| Stars | 84 |
| Forks | 10 |
| 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 laborany on GitHub. Read the source before you install it.
Install the Three Bullet Summary 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.
Any 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/laborany/laborany.git /tmp/laborany
mkdir -p .claude/skills
cp -r /tmp/laborany/skills/three-bullet-summary .claude/skills/three-bullet-summaryEnable Three Bullet Summary 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 Three Bullet Summary 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.
将任意输入文本精炼为恰好三个要点,每个要点一句话。
- [要点一] - [要点二] - [要点三]
三点摘要:将输入文本提炼为三个要点。适用于:用户提供一段文字并要求总结、提炼要点、 生成摘要,或明确要求"三个要点""三点总结""bullet points"等场景。
Because you install it once and use it with any model. Three Bullet Summary 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/laborany/laborany/tree/main/skills/three-bullet-summary. 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 Three Bullet Summary 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 laborany 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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