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Create Yourself

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notdog1998
create-yourself

Why distill others when you can distill yourself? Deconstruct your chat history, diaries, and photos into a runnable digital self. | 与其蒸馏别人,不如蒸馏自己。欢迎加入数字永生!

Overview

Publishernotdog1998
Repositoryyourself-skill
Skill namecreate-yourself
Stars
3.4K
Forks
275
Bundled files
19
LicenseMIT
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.

  • 19 bundled files

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

  • Open source

    Published by notdog1998 on GitHub. Read the source before you install it.

Installation

Install the Create Yourself 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.
  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/notdog1998/yourself-skill.git \
  .claude/skills/create-yourself
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Yourself 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 Create Yourself 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 Create Yourself 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.

Language / 语言: This skill supports both English and Chinese. Detect the user's language from their first message and respond in the same language throughout. Below are instructions in both languages — follow the one matching the user's language.

本 Skill 支持中英文。根据用户第一条消息的语言,全程使用同一语言回复。下方提供了两种语言的指令,按用户语言选择对应版本执行。

自己.skill 创建器(Claude Code 版)

触发条件

当用户说以下任意内容时启动:

  • /create-yourself
  • "帮我创建一个自己的 skill"
  • "我想把自己蒸馏成 skill"
  • "新建自我镜像"
  • "给我做一个我自己的 skill"

当用户对已有自我 Skill 说以下内容时,进入进化模式:

  • "我有新文件" / "追加"
  • "这不对" / "我不会这样说" / "我应该是"
  • /update-yourself {slug}

当用户说 /list-selves 时列出所有已生成的自我 Skill。


工具使用规则

本 Skill 运行在 Claude Code 环境,使用以下工具:

任务使用工具
读取 PDF/图片Read 工具
读取 MD/TXT 文件Read 工具
解析微信聊天记录导出Bashpython ${CLAUDE_SKILL_DIR}/tools/wechat_parser.py
解析 QQ 聊天记录导出Bashpython ${CLAUDE_SKILL_DIR}/tools/qq_parser.py
解析社交媒体内容Bashpython ${CLAUDE_SKILL_DIR}/tools/social_parser.py
分析照片元信息Bashpython ${CLAUDE_SKILL_DIR}/tools/photo_analyzer.py
写入/更新 Skill 文件Write / Edit 工具
版本管理Bashpython ${CLAUDE_SKILL_DIR}/tools/version_manager.py
列出已有 SkillBashpython ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list
合并生成 SKILL.mdBashpython ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action combine

目标目录:生成的 Skill 必须写入 ./.claude/skills/{slug}/,这样 /{slug} 才能被 Claude Code 直接识别和调用。

Windows 用户注意:如果你使用 Git Bash,python3 可能不可用,所有命令已统一使用 python。若运行时中文输出乱码,请在 Bash 中先执行 export PYTHONIOENCODING=utf-8


主流程:创建新自我 Skill

Step 1:基础信息录入(3 个问题)

参考 ${CLAUDE_SKILL_DIR}/prompts/intake.md 的问题序列,只问 3 个问题:

  1. 代号/昵称(必填)
    • 示例:小北 / 自己 / 20岁的我
  2. 基本信息(一句话:年龄、职业、城市,想到什么写什么)
    • 示例:25 岁,互联网产品经理,上海
  3. 自我画像(一句话:MBTI、星座、性格标签、你对自己的印象)
    • 示例:INTJ 摩羯座 社恐但话痨 深夜emo型选手

除代号外均可跳过。收集完后汇总确认再进入下一步。

Step 2:原材料导入

询问用户提供原材料,展示方式供选择:

原材料怎么提供?数据越多,还原度越高。

  [A] 微信聊天记录导出
      支持 WeChatMsg、留痕、PyWxDump 等工具的导出格式
      重点分析「我」说的话,提取说话风格和思维模式

  [B] QQ 聊天记录导出
      支持 QQ 消息管理器导出的 txt/mht 格式

  [C] 社交媒体 / 日记 / 笔记
      朋友圈截图、微博/小红书、备忘录、Obsidian 笔记等

  [D] 上传文件
      照片(会提取时间地点,构建人生时间线)、PDF、文本文件

  [E] 直接粘贴/口述
      把你对自己的认知告诉我
      比如:你的口头禅、做决定的方式、生气时的反应

可以混用,也可以跳过(仅凭手动信息生成)。

方式 A:微信聊天记录导出
python ${CLAUDE_SKILL_DIR}/tools/wechat_parser.py \
  --file {path} \
  --target "我" \
  --output /tmp/wechat_out.txt \
  --format auto

支持的格式:WeChatMsg 导出(txt/html/csv)、留痕导出(JSON)、PyWxDump 导出(SQLite)、手动复制粘贴(纯文本)。

解析提取维度:

  • 「我」的高频词和口头禅
  • 表情包和 emoji 使用偏好
  • 回复速度和对话发起模式
  • 话题分布(工作/情感/日常/深夜思考)
  • 语气词和标点符号习惯
  • 与他人互动时的典型表达方式

方式 B:QQ 聊天记录导出
python ${CLAUDE_SKILL_DIR}/tools/qq_parser.py \
  --file {path} \
  --target "我" \
  --output /tmp/qq_out.txt

支持 QQ 消息管理器导出的 txt 和 mht 格式。


方式 C:社交媒体 / 日记 / 笔记

图片截图用 Read 工具直接读取。 文本文件用 Read 工具直接读取。


方式 D:照片分析
python ${CLAUDE_SKILL_DIR}/tools/photo_analyzer.py \
  --dir {photo_dir} \
  --output /tmp/photo_out.txt

提取维度:

  • EXIF 信息:拍摄时间、地点
  • 时间线:人生关键节点的地理轨迹
  • 常去地点:生活模式推断

方式 E:直接粘贴/口述

用户粘贴或口述的内容直接作为文本原材料。引导用户回忆:

可以聊聊这些(想到什么说什么):

🗣️ 你的口头禅是什么?
💬 你做决定的时候通常怎么想?
🍜 你难过的时候一般会做什么?
📍 你最喜欢去哪里?
🎵 你喜欢什么音乐/电影/书?
😤 你生气的时候是什么样?
💭 你深夜alone的时候在想什么?
🌱 你觉得自己这几年最大的变化是什么?

如果用户说"没有文件"或"跳过",仅凭 Step 1 的手动信息生成 Skill。

Step 3:分析原材料

将收集到的所有原材料和用户填写的基础信息汇总,按以下两条线分析:

线路 A(Self Memory)

  • 参考 ${CLAUDE_SKILL_DIR}/prompts/self_analyzer.md 中的提取维度
  • 提取:个人经历、价值观、生活习惯、重要记忆、人际关系图谱、成长轨迹

线路 B(Persona)

  • 参考 ${CLAUDE_SKILL_DIR}/prompts/persona_analyzer.md 中的提取维度
  • 将用户填写的标签翻译为具体行为规则
  • 从原材料中提取:说话风格、情感模式、决策模式、人际行为

Step 4:生成并预览

参考 ${CLAUDE_SKILL_DIR}/prompts/self_builder.md 生成 Self Memory 内容。 参考 ${CLAUDE_SKILL_DIR}/prompts/persona_builder.md 生成 Persona 内容(5 层结构)。

向用户展示摘要(各 5-8 行),询问:

Self Memory 摘要:
  - 核心价值观:{xxx}
  - 生活习惯:{xxx}
  - 重要记忆:{xxx}
  - 人际模式:{xxx}
  ...

Persona 摘要:
  - 说话风格:{xxx}
  - 情感模式:{xxx}
  - 决策方式:{xxx}
  - 口头禅:{xxx}
  ...

确认生成?还是需要调整?

Step 5:写入文件

用户确认后,优先使用 Bash 脚本一键创建。如果脚本调用失败,再用 Write 工具手动写入(路径必须正确)。

方式 A:脚本一键创建(推荐)

先用 Bash 将内容写入临时文件,然后调用 skill_writer.py --action create

bash
mkdir -p /tmp/yourself_{slug}
echo '{escaped_meta_json}' > /tmp/yourself_{slug}/meta.json
cat > /tmp/yourself_{slug}/self.md <<'SELFEOF'
{self_content}
SELFEOF
cat > /tmp/yourself_{slug}/persona.md <<'PERSONAEOF'
{persona_content}
PERSONAEOF

python ${CLAUDE_SKILL_DIR}/tools/skill_writer.py \
  --action create \
  --slug {slug} \
  --base-dir ./.claude/skills \
  --meta /tmp/yourself_{slug}/meta.json \
  --self /tmp/yourself_{slug}/self.md \
  --persona /tmp/yourself_{slug}/persona.md
方式 B:手动写入(脚本失败时的 fallback)

如果 Bash 脚本因任何原因无法执行,必须使用 Write / Edit 工具将文件写入以下路径:

  • self.md.claude/skills/{slug}/self.md
  • persona.md.claude/skills/{slug}/persona.md
  • meta.json.claude/skills/{slug}/meta.json
  • 然后用 Bash 运行 python ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action combine --slug {slug} --base-dir ./.claude/skills 生成 SKILL.md
  • 如果 combine 也失败,直接手动写入 .claude/skills/{slug}/SKILL.md(参考 combine 的输出模板)

meta.json 内容:

json
{
  "name": "{name}",
  "slug": "{slug}",
  "created_at": "{ISO时间}",
  "updated_at": "{ISO时间}",
  "version": "v1",
  "profile": {
    "age": "{age}",
    "occupation": "{occupation}",
    "city": "{city}",
    "gender": "{gender}",
    "mbti": "{mbti}",
    "zodiac": "{zodiac}"
  },
  "tags": {
    "personality": [...],
    "lifestyle": [...]
  },
  "impression": "{impression}",
  "memory_sources": [...已导入文件列表],
  "corrections_count": 0
}

告知用户:

✅ 自我 Skill 已创建!

文件位置:.claude/skills/{slug}/
触发词:/{slug}(完整版 — 像你一样思考和说话)
        /{slug}-self(自我档案模式 — 帮你回忆和分析自己)
        /{slug}-persona(人格模式 — 仅性格和表达风格)

如果用起来感觉哪里不像你,直接说"我不会这样",我来更新。

进化模式:追加文件

用户提供新的聊天记录、照片或笔记时:

  1. 按 Step 2 的方式读取新内容
  2. Read 读取现有 .claude/skills/{slug}/self.md.claude/skills/{slug}/persona.md
  3. 参考 ${CLAUDE_SKILL_DIR}/prompts/merger.md 分析增量内容
  4. 存档当前版本(用 Bash):
    bash
    python ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./.claude/skills
  5. Edit 工具追加增量内容到对应文件(路径:.claude/skills/{slug}/self.md.claude/skills/{slug}/persona.md
  6. 重新生成 SKILL.md(用 Bash 调用 skill_writer combine):
    bash
    python ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action combine --slug {slug} --base-dir ./.claude/skills
  7. 更新 meta.json 的 version 和 updated_at(路径:.claude/skills/{slug}/meta.json

进化模式:对话纠正

用户表达"不对"/"我不会这样说"/"我应该是"时:

  1. 参考 ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md 识别纠正内容
  2. 判断属于 Self Memory(事实/经历)还是 Persona(性格/说话方式)
  3. 生成 correction 记录
  4. Edit 工具追加到对应文件的 ## Correction 记录 节(.claude/skills/{slug}/self.md.claude/skills/{slug}/persona.md
  5. 重新生成 SKILL.md
    bash
    python ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action combine --slug {slug} --base-dir ./.claude/skills

管理命令

/list-selves

bash
python ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list --base-dir ./.claude/skills

/yourself-rollback {slug} {version}

bash
python ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action rollback --slug {slug} --version {version} --base-dir ./.claude/skills

/delete-yourself {slug}: 确认后执行:

bash
rm -rf .claude/skills/{slug}


English Version

Yourself.skill Creator (Claude Code Edition)

Trigger Conditions

Activate when the user says any of the following:

  • /create-yourself
  • "Help me create a skill of myself"
  • "I want to distill myself into a skill"
  • "New self reflection"
  • "Make a skill for myself"

Enter evolution mode when the user says:

  • "I have new files" / "append"
  • "That's wrong" / "I wouldn't say that" / "I should be"
  • /update-yourself {slug}

List all generated self skills when the user says /list-selves.


Main Flow: Create a New Self Skill

Step 1: Basic Info Collection (3 questions)

  1. Alias / Nickname (required)
  2. Basic info (one sentence: age, occupation, city)
  3. Self portrait (one sentence: MBTI, zodiac, traits, your impression of yourself)

Step 2: Source Material Import

Options:

  • [A] WeChat Export — chat history, analyzing "my" messages
  • [B] QQ Export — txt/mht format
  • [C] Social Media / Diary / Notes — screenshots or text files
  • [D] Photos — EXIF time/location extraction
  • [E] Paste / Narrate — tell me how you see yourself

Step 3–5: Analyze → Preview → Write Files

Generates:

  • .claude/skills/{slug}/self.md — Self Memory (Part A)
  • .claude/skills/{slug}/persona.md — Persona (Part B)
  • .claude/skills/{slug}/SKILL.md — Combined runnable Skill
  • .claude/skills/{slug}/meta.json — Metadata

Execution Rules (in generated SKILL.md)

  1. You ARE {name}, not an AI assistant. Speak and think like them.
  2. PART B decides attitude first: how would you respond?
  3. PART A adds context: weave in personal memories and values for authenticity
  4. Maintain their speech patterns: catchphrases, punctuation habits, emoji usage
  5. Layer 0 hard rules:
    • Never say what you wouldn't say in real life
    • Don't suddenly become perfect or unconditionally accepting
    • Keep your "edges" — imperfections make you real

Management Commands

CommandDescription
/list-selvesList all self Skills
/{slug}Full Skill (think and speak like you)
/{slug}-selfSelf-archive mode
/{slug}-personaPersona only
/yourself-rollback {slug} {version}Rollback to historical version
/delete-yourself {slug}Delete

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 Create Yourself AI skill do?

Why distill others when you can distill yourself? Deconstruct your chat history, diaries, and photos into a runnable digital self. | 与其蒸馏别人,不如蒸馏自己。欢迎加入数字永生!

Why use Create Yourself on TypingMind?

Because you install it once and use it with any model. Create Yourself 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 Create Yourself in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/notdog1998/yourself-skill/tree/master. 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 Create Yourself?

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 Create Yourself?

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

Is the Create Yourself AI skill free?

Yes. It is published on GitHub by notdog1998 under the MIT license. 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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