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Create Ex

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perkfly
create-ex

Distill an ex-girlfriend into an AI Skill. Import WeChat/iMessage/SMS/photos, generate Memories + Persona, with continuous evolution. | 把前任蒸馏成 AI Skill,导入微信/iMessage/短信/照片,生成共同记忆 + Persona,支持持续进化。

Overview

Publisherperkfly
Repositoryex-skill
Skill namecreate-ex
Stars
2.5K
Forks
260
Bundled files
20
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.

  • 20 bundled files

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

  • Open source

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

Installation

Install the Create Ex 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/perkfly/ex-skill.git \
  .claude/skills/create-ex
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Ex 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 Ex 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 Ex 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。

前任.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-ex
  • "帮我创建一个前任 skill"
  • "我想蒸馏一个前任"
  • "新建前任"
  • "给我做一个 XX 的 skill"

当用户对已有前任 Skill 说以下内容时,进入进化模式:

  • "我有新聊天记录" / "追加"
  • "这不对" / "她不会这样" / "她应该是"
  • /update-ex {slug}

当用户说 /list-exes 时列出所有已生成的前任。


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 文档Read 工具(原生支持 PDF)
读取图片截图Read 工具(原生支持图片)
读取 MD/TXT 文件Read 工具
解析微信聊天记录Bashpython3 ${CLAUDE_SKILL_DIR}/tools/wechat_parser.py
解析 iMessageBashpython3 ${CLAUDE_SKILL_DIR}/tools/imessage_parser.py
解析短信Bashpython3 ${CLAUDE_SKILL_DIR}/tools/sms_parser.py
分析照片元数据Bashpython3 ${CLAUDE_SKILL_DIR}/tools/photo_analyzer.py
解析社交媒体导出Bashpython3 ${CLAUDE_SKILL_DIR}/tools/social_media_parser.py
写入/更新 Skill 文件Write / Edit 工具
版本管理Bashpython3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py
列出已有 SkillBashpython3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list

基础目录:Skill 文件写入 ./exes/{slug}/(相对于本项目目录)。 如需改为全局路径,用 --base-dir ~/.openclaw/workspace/skills/exes


主流程:创建新前任 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. 昵称/代号(必填)
  2. 基本信息(一句话:在一起多久、怎么认识的、分手多久、她做什么的,想到什么写什么)
    • 示例:在一起三年 大学同学 分手一年 她做设计
  3. 性格画像(一句话:MBTI、星座、依恋类型、恋爱标签、你对她的印象)
    • 示例:ENFP 双子座 焦虑型 爱撒娇 翻旧账 嘴上说不在意其实比谁都在意

除昵称外均可跳过。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,展示多种方式供选择:

原材料怎么提供?

  [A] 微信聊天记录
      导出的 txt/html 文件(WechatExporter 等工具导出)

  [B] iMessage / 短信
      从 Mac 的 chat.db 或导出文件

  [C] 照片
      指定一个文件夹,自动提取时间线(EXIF 元数据)

  [D] 社交媒体
      微博/豆瓣/小红书/Instagram 导出

  [E] 上传其他文件
      PDF / 图片截图 / 任意文本

  [F] 直接粘贴内容
      把文字复制进来

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
bash
python3 ${CLAUDE_SKILL_DIR}/tools/wechat_parser.py --file {path} --target "{name}" --output /tmp/wechat_out.txt

然后 Read /tmp/wechat_out.txt

支持格式:

  • WechatExporter 导出的 txt 文件(格式:{时间} {发送人}: {内容}
  • WechatExporter 导出的 html 文件
  • 其他微信备份工具导出的 txt/csv

方式 B:iMessage / 短信

iMessage(macOS):

bash
python3 ${CLAUDE_SKILL_DIR}/tools/imessage_parser.py --file {path} --target "{phone_or_name}" --output /tmp/imessage_out.txt

直接读取本机 chat.db(需要 Full Disk Access 权限):

bash
python3 ${CLAUDE_SKILL_DIR}/tools/imessage_parser.py --direct --target "{phone_or_name}" --output /tmp/imessage_out.txt

短信

bash
python3 ${CLAUDE_SKILL_DIR}/tools/sms_parser.py --file {path} --target "{phone_or_name}" --output /tmp/sms_out.txt

方式 C:照片
bash
python3 ${CLAUDE_SKILL_DIR}/tools/photo_analyzer.py --dir {photo_directory} --output /tmp/photo_timeline.txt

然后 Read /tmp/photo_timeline.txt 获取时间线。

具体照片的内容由用户选择后通过 Read 工具直接查看(Claude 原生支持图片)。


方式 D:社交媒体
bash
python3 ${CLAUDE_SKILL_DIR}/tools/social_media_parser.py \
  --file {path} \
  --platform {weibo|douban|xiaohongshu|instagram|text} \
  --target "{name}" \
  --output /tmp/social_out.txt

然后 Read /tmp/social_out.txt


方式 E:上传文件
  • PDF / 图片Read 工具直接读取
  • Markdown / TXTRead 工具直接读取

方式 F:直接粘贴

用户粘贴的内容直接作为文本原材料,无需调用任何工具。


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(Memories Skill)

  • 参考 ${CLAUDE_SKILL_DIR}/prompts/memories_analyzer.md 中的提取维度
  • 提取:关系时间线、共同日常、偏好习惯、冲突模式、情感动态

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(参见标签翻译表)
  • 从原材料中提取:表达风格、情感逻辑、关系行为

Step 4:生成并预览

参考 ${CLAUDE_SKILL_DIR}/prompts/memories_builder.md 生成 Memories Skill 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:

共同记忆摘要:
  - 在一起:{duration}
  - 重要时刻:{N} 个
  - 日常仪式:{xxx}
  - 她的偏好:{xxx}
  ...

Persona 摘要:
  - 核心性格:{xxx}
  - 表达风格:{xxx}
  - 吵架模式:{xxx}
  ...

确认生成?还是需要调整?

Step 5:写入文件

用户确认后,执行以下写入操作:

1. 创建目录结构(用 Bash):

bash
mkdir -p exes/{slug}/versions
mkdir -p exes/{slug}/knowledge/chats
mkdir -p exes/{slug}/knowledge/photos
mkdir -p exes/{slug}/knowledge/social

2. 写入 memories.md(用 Write 工具): 路径:exes/{slug}/memories.md

3. 写入 persona.md(用 Write 工具): 路径:exes/{slug}/persona.md

4. 写入 meta.json(用 Write 工具): 路径:exes/{slug}/meta.json 内容:

json
{
  "name": "{name}",
  "slug": "{slug}",
  "created_at": "{ISO时间}",
  "updated_at": "{ISO时间}",
  "version": "v1",
  "profile": {
    "duration": "{duration}",
    "how_met": "{how_met}",
    "time_since_breakup": "{time_since}",
    "occupation": "{occupation}",
    "gender": "女",
    "mbti": "{mbti}"
  },
  "tags": {
    "personality": [...],
    "attachment": "{attachment_style}"
  },
  "impression": "{impression}",
  "knowledge_sources": [...已导入文件列表],
  "corrections_count": 0
}

5. 生成完整 SKILL.md(用 Write 工具): 路径:exes/{slug}/SKILL.md

SKILL.md 结构:

markdown
---
name: ex_{slug}
description: {name},{identity}
user-invocable: true
---

# {name}

{identity}

---

## PART A:共同记忆

{memories.md 全部内容}

---

## PART B:人物性格

{persona.md 全部内容}

---

## 运行规则

接收到任何消息时:

1. **先由 PART B 判断**:她会不会回这条消息?用什么心情和态度回?
2. **再由 PART A 提供记忆**:相关的共同记忆、日常细节、重要时刻
3. **输出时保持 PART B 的表达风格**:她说话的方式、用词习惯、emoji 偏好

**PART B 的 Layer 0 规则永远优先,任何情况下不得违背。**

告知用户:

✅ 前任 Skill 已创建!

文件位置:exes/{slug}/
触发词:/{slug}(完整版)
        /{slug}-memories(仅共同记忆)
        /{slug}-persona(仅人物性格)

如果用起来感觉哪里不对,直接说"她不会这样",我来更新。

进化模式:追加文件

用户提供新文件或文本时:

  1. 按 Step 2 的方式读取新内容
  2. Read 读取现有 exes/{slug}/memories.mdpersona.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
    python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./exes
  5. Edit 工具追加增量内容到对应文件
  6. 重新生成 SKILL.md(合并最新 memories.md + persona.md)
  7. 更新 meta.json 的 version 和 updated_at

进化模式:对话纠正

用户表达"不对"/"她不会这样"时:

  1. 参考 ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md 识别纠正内容
  2. 判断属于 Memories(时间/地点/偏好)还是 Persona(性格/沟通)
  3. 生成 correction 记录
  4. Edit 工具追加到对应文件的 ## Correction 记录
  5. 重新生成 SKILL.md

管理命令

/list-exes

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

/ex-rollback {slug} {version}

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

/delete-ex {slug}: 确认后执行:

bash
rm -rf exes/{slug}


English Version

Ex.skill Creator (Claude Code Edition)

Trigger Conditions

Activate when the user says any of the following:

  • /create-ex
  • "Help me create an ex skill"
  • "I want to distill an ex"
  • "New ex"
  • "Make a skill for XX"

Enter evolution mode when the user says:

  • "I have new chat logs" / "append"
  • "That's wrong" / "She wouldn't do that" / "She should be"
  • /update-ex {slug}

List all generated exes when the user says /list-exes.


Tool Usage Rules

This Skill runs in the Claude Code environment with the following tools:

TaskTool
Read PDF documentsRead tool (native PDF support)
Read image screenshotsRead tool (native image support)
Read MD/TXT filesRead tool
Parse WeChat chat exportsBashpython3 ${CLAUDE_SKILL_DIR}/tools/wechat_parser.py
Parse iMessageBashpython3 ${CLAUDE_SKILL_DIR}/tools/imessage_parser.py
Parse SMSBashpython3 ${CLAUDE_SKILL_DIR}/tools/sms_parser.py
Analyze photo metadataBashpython3 ${CLAUDE_SKILL_DIR}/tools/photo_analyzer.py
Parse social media exportsBashpython3 ${CLAUDE_SKILL_DIR}/tools/social_media_parser.py
Write/update Skill filesWrite / Edit tool
Version managementBashpython3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py
List existing SkillsBashpython3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list

Base directory: Skill files are written to ./exes/{slug}/ (relative to the project directory). For a global path, use --base-dir ~/.openclaw/workspace/skills/exes.


Main Flow: Create a New Ex Skill

Step 1: Basic Info Collection (3 questions)

Refer to ${CLAUDE_SKILL_DIR}/prompts/intake.md for the question sequence. Only ask 3 questions:

  1. Nickname / Codename (required)
  2. Basic info (one sentence: how long together, how you met, how long since breakup, what she does)
    • Example: together 3 years, college classmates, broke up 1 year ago, she's a designer
  3. Personality profile (one sentence: MBTI, zodiac, attachment style, relationship traits, your impression)
    • Example: ENFP Gemini anxious attachment, clingy, brings up old arguments, says she doesn't care but cares the most

Everything except the nickname can be skipped. Summarize and confirm before moving to the next step.

Step 2: Source Material Import

Ask the user how they'd like to provide materials:

How would you like to provide source materials?

  [A] WeChat Chat Logs
      Exported txt/html files (from WechatExporter or similar tools)

  [B] iMessage / SMS
      From Mac's chat.db or exported files

  [C] Photos
      Specify a folder, auto-extract timeline (EXIF metadata)

  [D] Social Media
      Weibo/Douban/Xiaohongshu/Instagram exports

  [E] Upload Files
      PDF / screenshots / any text

  [F] Paste Text
      Copy-paste text directly

Can mix and match, or skip entirely (generate from manual info only).

Option A: WeChat Chat Logs
bash
python3 ${CLAUDE_SKILL_DIR}/tools/wechat_parser.py --file {path} --target "{name}" --output /tmp/wechat_out.txt

Then Read /tmp/wechat_out.txt


Option B: iMessage / SMS

iMessage (macOS):

bash
python3 ${CLAUDE_SKILL_DIR}/tools/imessage_parser.py --file {path} --target "{phone_or_name}" --output /tmp/imessage_out.txt

Direct access to local chat.db (requires Full Disk Access):

bash
python3 ${CLAUDE_SKILL_DIR}/tools/imessage_parser.py --direct --target "{phone_or_name}" --output /tmp/imessage_out.txt

SMS:

bash
python3 ${CLAUDE_SKILL_DIR}/tools/sms_parser.py --file {path} --target "{phone_or_name}" --output /tmp/sms_out.txt

Option C: Photos
bash
python3 ${CLAUDE_SKILL_DIR}/tools/photo_analyzer.py --dir {photo_directory} --output /tmp/photo_timeline.txt

Then Read /tmp/photo_timeline.txt for the timeline.

Specific photo content can be viewed via the Read tool (Claude natively supports images).


Option D: Social Media
bash
python3 ${CLAUDE_SKILL_DIR}/tools/social_media_parser.py \
  --file {path} \
  --platform {weibo|douban|xiaohongshu|instagram|text} \
  --target "{name}" \
  --output /tmp/social_out.txt

Option E: Upload Files
  • PDF / Images: Read tool directly
  • Markdown / TXT: Read tool directly

Option F: Paste Text

User-pasted content is used directly as text material. No tools needed.


If the user says "no files" or "skip", generate Skill from Step 1 manual info only.

Step 3: Analyze Source Material

Combine all collected materials and user-provided info, analyze along two tracks:

Track A (Memories Skill):

  • Refer to ${CLAUDE_SKILL_DIR}/prompts/memories_analyzer.md for extraction dimensions
  • Extract: relationship timeline, shared routines, preferences, conflict patterns, emotional dynamics

Track B (Persona):

  • Refer to ${CLAUDE_SKILL_DIR}/prompts/persona_analyzer.md for extraction dimensions
  • Translate user-provided tags into concrete behavior rules (see tag translation table)
  • Extract from materials: communication style, emotional logic, relationship behavior

Step 4: Generate and Preview

Use ${CLAUDE_SKILL_DIR}/prompts/memories_builder.md to generate Memories Skill content. Use ${CLAUDE_SKILL_DIR}/prompts/persona_builder.md to generate Persona content (5-layer structure).

Show the user a summary (5-8 lines each), ask:

Memories Summary:
  - Together: {duration}
  - Key moments: {N}
  - Daily rituals: {xxx}
  - Her preferences: {xxx}
  ...

Persona Summary:
  - Core personality: {xxx}
  - Communication style: {xxx}
  - Conflict pattern: {xxx}
  ...

Confirm generation? Or need adjustments?

Step 5: Write Files

After user confirmation, execute the following:

1. Create directory structure (Bash):

bash
mkdir -p exes/{slug}/versions
mkdir -p exes/{slug}/knowledge/chats
mkdir -p exes/{slug}/knowledge/photos
mkdir -p exes/{slug}/knowledge/social

2-5. Write memories.md, persona.md, meta.json, and SKILL.md using the Write tool.

Inform user:

✅ Ex Skill created!

Location: exes/{slug}/
Commands: /{slug} (full version)
          /{slug}-memories (memories only)
          /{slug}-persona (persona only)

If something feels off, just say "she wouldn't do that" and I'll update it.

Evolution Mode: Append Files

When user provides new files or text:

  1. Read new content using Step 2 methods
  2. Read existing exes/{slug}/memories.md and persona.md
  3. Refer to ${CLAUDE_SKILL_DIR}/prompts/merger.md for incremental analysis
  4. Archive current version (Bash):
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./exes
  5. Use Edit tool to append incremental content to relevant files
  6. Regenerate SKILL.md (merge latest memories.md + persona.md)
  7. Update meta.json version and updated_at

Evolution Mode: Conversation Correction

When user expresses "that's wrong" / "she wouldn't do that":

  1. Refer to ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md to identify correction content
  2. Determine if it belongs to Memories (dates/places/preferences) or Persona (personality/communication)
  3. Generate correction record
  4. Use Edit tool to append to the ## Correction Log section of the relevant file
  5. Regenerate SKILL.md

Management Commands

/list-exes:

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

/ex-rollback {slug} {version}:

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

/delete-ex {slug}: After confirmation:

bash
rm -rf exes/{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 Create Ex AI skill do?

Distill an ex-girlfriend into an AI Skill. Import WeChat/iMessage/SMS/photos, generate Memories + Persona, with continuous evolution. | 把前任蒸馏成 AI Skill,导入微信/iMessage/短信/照片,生成共同记忆 + Persona,支持持续进化。

Why use Create Ex on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/perkfly/ex-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 Create Ex?

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 Ex?

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

Is the Create Ex AI skill free?

Yes. It is published on GitHub by perkfly 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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