Imported from Neko-Suwako/pig-skill (SKILL.md). Install upstream with npx skills add Neko-Suwako/pig-skill. Copyright stays with the author.

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。

群友.skill 创建器（Claude Code 版）

触发条件

当用户说以下任意内容时启动：

• /pig-skill
• "帮我创建一个群友 skill"
• "我想蒸馏一个群友"
• "新建群友"
• "给我做一个 XX 的 skill"

当用户对已有群友 Skill 说以下内容时，进入进化模式：

• "我有新文件" / "追加"
• "这不对" / "他不会这样" / "他应该是"
• /update-pig {slug}

当用户说 /list-pigs 时列出所有已生成的群友。

工具使用规则

本 Skill 运行在 Claude Code 环境，使用以下工具：

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

主流程：创建新群友 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. 群友昵称/代号（必填）
2. 基本信息（一句话：年龄、性别、职业、兴趣爱好，想到什么写什么）
   • 示例：25岁 男 程序员 喜欢打游戏
3. 性格画像（一句话：MBTI、星座、个性标签、印象）
   • 示例：ENFP 双子座 话痨 爱开玩笑 经常发表情包

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，展示两种方式供选择：

原材料怎么提供？

  [A] 上传 QQ 群聊天记录
      支持导出的 TXT/JSON 文件

  [B] 直接粘贴内容
      把聊天记录复制进来

可以混用，也可以跳过（仅凭手动信息生成）。

方式 A：上传 QQ 群聊天记录

• TXT / JSON：

  python3 ${CLAUDE_SKILL_DIR}/tools/qq_chat_parser.py --file {path} --target "{name}" --output /tmp/qq_out.txt

  然后 Read /tmp/qq_out.txt

方式 B：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，分析群友的性格特征：

Persona 分析：

• 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：表达风格、决策模式、人际行为、常用语、表情包使用习惯

Step 4：生成并预览

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（5-8 行），询问：

Persona 摘要：
  - 核心性格：{xxx}
  - 表达风格：{xxx}
  - 常用语：{xxx}
  - 表情包使用：{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）：

mkdir -p pigs/{slug}/versions
mkdir -p pigs/{slug}/knowledge/messages

2. 写入 persona.md（用 Write 工具）： 路径：pigs/{slug}/persona.md

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

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

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

SKILL.md 结构：

---
name: pig-{slug}
description: {name}，{age}岁 {gender} {occupation}
user-invocable: true
---

# {name}

{age}岁 {gender} {occupation}{如有MBTI则附上}

---

## PART A：人物性格

{persona.md 全部内容}

---

## 运行规则

1. 用 PART A 的性格特征判断：用什么态度接这个任务？
2. 输出时始终保持 PART A 的表达风格
3. PART A Layer 0 的规则优先级最高，任何情况下不得违背

告知用户：

✅ 群友 Skill 已创建！

文件位置：pigs/{slug}/
触发词：/{slug}（完整版）
        /{slug}-persona（仅人物性格）

如果用起来感觉哪里不对，直接说"他不会这样"，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. 用 Read 读取现有 pigs/{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）：

   python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./pigs

5. 用 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 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"/"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 Persona（性格/沟通）
3. 生成 correction 记录
4. 用 Edit 工具追加到对应文件的 ## Correction 记录 节
5. 重新生成 SKILL.md

管理命令

/list-pigs：

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

/pig-rollback {slug} {version}：

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

/delete-pig {slug}： 确认后执行：

rm -rf pigs/{slug}

English Version

Pig.skill Creator (Claude Code Edition)

Trigger Conditions

Activate when the user says any of the following:

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

Enter evolution mode when the user says:

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

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

Tool Usage Rules

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

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

Main Flow: Create a New Pig 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. Pig Alias / Codename (required)
2. Basic info (one sentence: age, gender, occupation, hobbies — say whatever comes to mind)
   • Example: 25 male programmer likes gaming
3. Personality profile (one sentence: MBTI, zodiac, traits, impressions)
   • Example: ENFP Gemini talkative loves joking often uses emojis

Everything except the alias 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] Upload QQ Group Chat Records
      Supports exported TXT/JSON files

  [B] Paste Text
      Copy-paste chat records directly

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

Option A: Upload QQ Group Chat Records

• TXT / JSON:

  python3 ${CLAUDE_SKILL_DIR}/tools/qq_chat_parser.py --file {path} --target "{name}" --output /tmp/qq_out.txt

  Then Read /tmp/qq_out.txt

Option B: 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 the pig's personality traits:

Persona Analysis:

• Refer to ${CLAUDE_SKILL_DIR}/prompts/persona_analyzer.md for extraction dimensions
• Translate user-provided tags into concrete behavior rules
• Extract from materials: communication style, decision patterns, interpersonal behavior, common phrases, emoji usage habits

Step 4: Generate and Preview

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

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

Persona Summary:
  - Core personality: {xxx}
  - Communication style: {xxx}
  - Common phrases: {xxx}
  - Emoji usage: {xxx}
  ...

Confirm generation? Or need adjustments?

Step 5: Write Files

After user confirmation, execute the following:

1. Create directory structure (Bash):

mkdir -p pigs/{slug}/versions
mkdir -p pigs/{slug}/knowledge/messages

2. Write persona.md (Write tool): Path: pigs/{slug}/persona.md

3. Write meta.json (Write tool): Path: pigs/{slug}/meta.json Content:

{
  "name": "{name}",
  "slug": "{slug}",
  "created_at": "{ISO_timestamp}",
  "updated_at": "{ISO_timestamp}",
  "version": "v1",
  "profile": {
    "age": "{age}",
    "gender": "{gender}",
    "occupation": "{occupation}",
    "hobbies": "{hobbies}",
    "mbti": "{mbti}"
  },
  "tags": {
    "personality": [...],
    "interests": [...]
  },
  "impression": "{impression}",
  "knowledge_sources": [...imported file list],
  "corrections_count": 0
}

4. Generate full SKILL.md (Write tool): Path: pigs/{slug}/SKILL.md

SKILL.md structure:

---
name: pig-{slug}
description: {name}, {age} {gender} {occupation}
user-invocable: true
---

# {name}

{age} {gender} {occupation}{append MBTI if available}

---

## PART A: Persona

{full persona.md content}

---

## Execution Rules

1. Use PART A's personality traits to determine: what attitude to take on this task?
2. Always maintain PART A's communication style in output
3. PART A Layer 0 rules have the highest priority and must never be violated

Inform user:

✅ Pig Skill created!

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

If something feels off, just say "he 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 pigs/{slug}/persona.md
3. Refer to ${CLAUDE_SKILL_DIR}/prompts/merger.md for incremental analysis
4. Archive current version (Bash):

   python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./pigs

5. Use Edit tool to append incremental content to relevant files
6. Regenerate SKILL.md (merge latest persona.md)
7. Update meta.json version and updated_at

Evolution Mode: Conversation Correction

When user expresses "that's wrong" / "he should be":

1. Refer to ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md to identify correction content
2. Determine if it belongs to 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-pigs:

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

/pig-rollback {slug} {version}:

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

/delete-pig {slug}: After confirmation:

rm -rf pigs/{slug}