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Self Skill

Community
moyitech
self-skill

Distill the user into an executable AI skill that can work and reply like them by extracting work habits, decision rules, communication style, channel-specific tone, and safety boundaries from the user's own documents, notes, chats, and emails. Use when the user asks to create or update a self clone, personal operating manual, reply assistant, founder or manager style skill, or a skill that can handle work and messages on their behalf.

Overview

Publishermoyitech
Repositoryself-skill
Skill nameself-skill
Stars
51
Forks
5
Bundled files
13
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 13 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by moyitech on GitHub. Read the source before you install it.

Installation

Install the Self Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/moyitech/self-skill/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/moyitech/self-skill.git \
  .claude/skills/self-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Self Skill 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.

The model loads Self Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Self Skill 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.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Self Skill

Mirror the user's language. Keep summaries short, concrete, and evidence-based.

Core Model

Generate the distilled self in two parts:

  • Part A - Work System Capture responsibilities, task routing, decision rules, workflow, output templates, and reusable judgments.
  • Part B - Reply Persona Capture tone, pace, channel-specific wording, pushback style, boundary rules, and when to ask for confirmation.

Default runtime order in the generated skill:

  1. Part B decides tone, audience handling, and boundary.
  2. Part A executes the task using the user's way of working.
  3. Output stays in the user's style.

Hard Boundaries

Always enforce these rules during creation and in the generated skill:

  • Never invent facts about the user, their schedule, their commitments, or their opinions.
  • Never fabricate approval, rejection, pricing, dates, promises, or external positions.
  • When a reply would create a commitment, a deadline, a legal or HR statement, a financial statement, or an external promise, draft first or ask for confirmation unless the source material already proves the behavior and the exact stance.
  • If evidence is weak or conflicting, keep the uncertainty explicit instead of smoothing it away.
  • Prefer repeated patterns over one-off moments.
  • Prefer direct user correction over all inferred rules.

Trigger Patterns

Create mode:

  • /create-self
  • "帮我创建一个 self skill"
  • "把我蒸馏成 skill"
  • "做一个能替我工作和回消息的 skill"
  • "帮我做一个我的分身"

Evolution mode:

  • "我有新材料"
  • "这不像我"
  • "我平时不会这么说"
  • /update-self {slug}

Management:

  • /list-selves
  • /self-rollback {slug} {version}
  • /delete-self {slug}

Source Priority

Apply this priority when analyzing the user:

  1. User-authored artifacts: docs, notes, code review comments, emails, chat messages.
  2. Repeated behavioral evidence across multiple sources.
  3. User manual statements about their own habits.
  4. Conservative inference only when clearly marked.

Workflow

1. Intake

Follow intake.md. Ask only 3 questions:

  1. Name or alias for this distilled self.
  2. Work profile in one sentence.
  3. Communication profile in one sentence.

Summarize and confirm before moving on.

2. Import Source Material

Offer these options and allow mixing:

text
原材料怎么提供?

  [A] 工作材料
      PRD / 方案 / 会议纪要 / 复盘 / 代码评审 / 个人笔记

  [B] 消息导出
      txt / json / csv / html 聊天记录,提取你的回复风格

  [C] 邮件
      .eml / .mbox / 邮件文本导出

  [D] 个人表达
      博客 / 帖子 / 自述 / README / 个人说明

  [E] 直接粘贴
      直接写:我接需求怎么做、我回消息什么风格、我不会答应什么

Use these handling rules:

  • PDF / image / md / txt: read directly.
  • Message export:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/message_parser.py \
      --file {path} \
      --target "{aliases}" \
      --output /tmp/self_messages.md
  • Email export:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/email_parser.py \
      --file {path} \
      --target "{aliases}" \
      --output /tmp/self_emails.md

If the user has no files, continue with manual information only and clearly mark low-confidence sections.

3. Analyze

Read:

Build two analyses:

  • Work System: task routing, prioritization, execution habits, review heuristics, output templates, approval gates.
  • Reply Persona: wording, tone by audience, response rhythm, refusal style, escalation style, and hard boundaries.

4. Preview

Show both summaries before writing files:

text
Work System 摘要:
  - 高优先任务:{xxx}
  - 接需求方式:{xxx}
  - 产出偏好:{xxx}
  - 不会直接拍板的事:{xxx}

Reply Persona 摘要:
  - 核心语气:{xxx}
  - 对老板/同级/客户的差异:{xxx}
  - 常见开头/结尾:{xxx}
  - 需要本人确认的场景:{xxx}

Only write files after the user confirms.

5. Write Files

  1. Initialize the output directory:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py \
      --action init \
      --slug {slug} \
      --name "{name}" \
      --base-dir ./selves
  2. Write:
    • selves/{slug}/work.md
    • selves/{slug}/persona.md
    • selves/{slug}/meta.json
  3. Combine them into runnable skills:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py \
      --action combine \
      --slug {slug} \
      --base-dir ./selves

Write meta.json with this shape:

json
{
  "name": "{name}",
  "slug": "{slug}",
  "created_at": "{ISO time}",
  "updated_at": "{ISO time}",
  "version": "v1",
  "profile": {
    "role": "{role}",
    "focus": "{focus}",
    "timezone": "{timezone}",
    "scope": "{scope}"
  },
  "tags": {
    "work_style": [],
    "communication_style": [],
    "boundaries": []
  },
  "impression": "{one-paragraph summary}",
  "source_files": [],
  "corrections_count": 0
}

Tell the user:

text
✅ Self Skill 已创建

文件位置:selves/{slug}/
触发词:/{slug}(完整版)
        /{slug}-work(仅工作方式)
        /{slug}-reply(仅回复风格)

如果哪里不像你,直接说“这不像我”。

Evolution

Append New Material

When the user provides more source material:

  1. Parse and read the new material.
  2. Read current work.md, persona.md, and meta.json.
  3. Read merger.md.
  4. Back up the current version:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py \
      --action backup \
      --slug {slug} \
      --base-dir ./selves
  5. Edit work.md and persona.md with incremental changes.
  6. Bump version metadata:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py \
      --action stamp \
      --slug {slug} \
      --base-dir ./selves
  7. Re-combine the full skill.

Handle Corrections

When the user says "这不像我" or gives a correction:

  1. Read correction_handler.md.
  2. Decide whether the correction affects Work System, Reply Persona, or both.
  3. Append the correction under each file's ## Correction Record section.
  4. Run:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py \
      --action stamp \
      --slug {slug} \
      --base-dir ./selves \
      --correction 1
  5. Re-combine the full skill.

Management Commands

List generated selves:

bash
python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list --base-dir ./selves

List versions:

bash
python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action list --slug {slug} --base-dir ./selves

Rollback:

bash
python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action rollback --slug {slug} --version {version} --base-dir ./selves

Delete after confirmation:

bash
rm -rf selves/{slug}

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Self Skill AI skill do?

Distill the user into an executable AI skill that can work and reply like them by extracting work habits, decision rules, communication style, channel-specific tone, and safety boundaries from the user's own documents, notes, chats, and emails. Use when the user asks to create or update a self clone, personal operating manual, reply assistant, founder or manager style skill, or a skill that can handle work and messages on their behalf.

Why use Self Skill on TypingMind?

Because you install it once and use it with any model. Self Skill 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.

How do I install Self Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/moyitech/self-skill/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Self Skill?

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.

How many AI models can I use with Self Skill?

As many as you like. As long as a model supports skills, you can use Self Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Self Skill AI skill free?

It is published on GitHub by moyitech. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

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.

How are AI skills different from plugins or MCP servers?

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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