Distill a QQ group friend into an AI Skill. Import QQ group chat records, generate Persona, with continuous evolution. 把QQ群友蒸馏成 AI Skill,导入QQ群聊天记录,生成性格画像,支持持续进化。
先看几段任务处理样例,再决定是否下载使用。
人物蒸馏摘要
使用入口
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.
蒸馏出的核心能力
思维模型
Layer 0:核心性格(最高优先级,任何情况下不得违背)
表达风格
这个人物如何组织语言、语气和态度。
可信依据
当前版本尚未发现独立研究摘要,建议作者补充资料来源。
name: pig-skill
description: "Distill a QQ group friend into an AI Skill. Import QQ group chat records, generate Persona, with continuous evolution. | 把QQ群友蒸馏成 AI Skill,导入QQ群聊天记录,生成性格画像,支持持续进化。"
argument-hint: "[group-friend-name-or-slug]"
version: "1.0.0"
user-invocable: true
allowed-tools: Read, Write, Edit, BashLanguage / 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。
当用户说以下任意内容时启动:
/pig-skill当用户对已有群友 Skill 说以下内容时,进入进化模式:
/update-pig {slug}当用户说 /list-pigs 时列出所有已生成的群友。
本 Skill 运行在 Claude Code 环境,使用以下工具:
| 任务 | 使用工具 |
|---|---|
| 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 QQ 群聊天记录 | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/qq_chat_parser.py |
| 写入/更新 Skill 文件 | Write / Edit 工具 |
| 版本管理 | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py |
| 列出已有 Skill | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list |
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。
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)
3. 性格画像(一句话:MBTI、星座、个性标签、印象)
25岁 男 程序员 喜欢打游戏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。
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
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。
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:
${CLAUDE_SKILL_DIR}/prompts/persona_analyzer.md 中的提取维度参考 ${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?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/messages2. 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。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 ./pigs5. 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
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
/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}Activate when the user says any of the following:
/pig-skillEnter evolution mode when the user says:
/update-pig {slug}List all generated pigs when the user says /list-pigs.
This Skill runs in the Claude Code environment with the following tools:
| Task | Tool |
|---|---|
| Read image screenshots | Read tool (native image support) |
| Read MD/TXT files | Read tool |
| Parse QQ group chat records | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/qq_chat_parser.py |
| Write/update Skill files | Write / Edit tool |
| Version management | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py |
| List existing Skills | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/skill_writer.py --action list |
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.
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)
3. Personality profile (one sentence: MBTI, zodiac, traits, impressions)
25 male programmer likes gamingENFP Gemini talkative loves joking often uses emojisEverything except the alias can be skipped. Summarize and confirm before moving to the next step.
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
python3 ${CLAUDE_SKILL_DIR}/tools/qq_chat_parser.py --file {path} --target "{name}" --output /tmp/qq_out.txtThen 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.
Combine all collected materials and user-provided info, analyze the pig's personality traits:
Persona Analysis:
${CLAUDE_SKILL_DIR}/prompts/persona_analyzer.md for extraction dimensionsUse ${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?After user confirmation, execute the following:
1. Create directory structure (Bash):
mkdir -p pigs/{slug}/versions
mkdir -p pigs/{slug}/knowledge/messages2. 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 violatedInform 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.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 ./pigs5. 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
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
/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}import: github_repo https://github.com/Neko-Suwako/pig-skill
当前为只读模式,登录后可评论。
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SAFE-3
80+ 稳定 · 60+ 可用PDS-6
6/6 维已生成看这个人物是谁、身份关系是否足够清楚。
说明
看是否提炼出稳定的思维模型和判断原则。
看语气、措辞和表达节奏是否像这个人。
看事实、推断、未知与专业限制是否分清。
看关键结论能否回溯到研究摘要和资料来源。
看是否能稳定互动,而不只是静态人物介绍。
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