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🧬 dot-skill

"You folks building LLMs are all code-sages! Flesh is weak! Ascend to cyberspace!"

License: MIT Python 3.9+ AgentSkills Stars

Claude Code Hermes OpenClaw Codex

Discord


🧑‍💼  Your colleague quit, your mentor graduated, your teammate transferred — taking their whole playbook and context with them?
💞  Your family, old friends, partner drifting apart — and you want to hold on to the way it felt to be with them?
🌟  Your favorite author, idol, thinker you'll never meet — but you want to know what they'd say about your question?

✨ dot-skill solves all three.


Upgraded from colleague.skill to dot-skill — not just colleagues, anyone can be distilled into a Skill

Colleagues · partners · family · old friends · idols · public figures · fictional characters — even yourself

Source material + your description → an AI Skill that genuinely thinks like them Thinks in their frame, speaks in their voice


🆕 What's new · 📦 Data Sources · ⚡ Install · 🚀 Usage · ✨ Demo · 💬 Discord

中文 · Español · Deutsch · 日本語 · Русский · Português · 한국어


🎉 2026.04.19 Milestone — dot-skill just hit 15k ⭐!

Massive thanks to everyone who starred — we'll keep shipping, keep distilling.

📢 2026.04.19 UpdateWeChat group 5 is live! Come hang out with the dot-skill community — share skills, discuss features, trade tips.

dot-skill WeChat group QR

QR refreshes every 7 days (expires 2026-04-24) — if expired, ping me on Discord.

🗺️ 2026.04.13dot-skill Roadmap is live! colleague.skill is evolving into dot-skill — distill anyone, not just colleagues. 👉 Full Roadmap · 💬 Discord

🌐 2026.04.07 — Community gallery is live! Any skill / meta-skill can drive traffic directly to your own GitHub repo. No middleman. 👉 titanwings.github.io/colleague-skill-site

Created by @titanwings · Powered by Shanghai AI Lab · AI Safety Center


🆕 What's new in this major release?

1️⃣ From colleague-skill to dot-skill

No longer only built around the "colleague" scenario. A unified /dot-skill entrypoint sits on a general-purpose skill engine — one engine distills anyone, instead of being a colleague-specific script.

2️⃣ Three character families

🧑‍💼 colleague 💞 relationship 🌟 celebrity
Coworkers · mentors · teammates · up/downstream partners Exes · partners · parents · friends · close family Public figures · creators · public voices · fictional characters
Work Skill + Persona two-layer architecture — learns both their technical standards and workflows, and their manner of speaking and workplace posture. Supports Feishu / DingTalk / Slack auto-collection. 🆕 Photo-sharing feature coming soon — your distilled relationship won't just reply to messages; it'll send photos and share slices of its day, the way a real person would. Ships with a complete six-dimension research toolchain (subtitles → transcript cleanup → research merge → quality check). Not mimicking tone — reproducing their mental models and decision frameworks.

Each family has its own prompt pipeline, source-collection strategy, and generation template.

3️⃣ More Agent hosts

The old version only ran in Claude Code. Now it's cross-host across four:

Host Description
🟣 Claude Code Native slash-command support
🟠 Hermes Agent One-command install, /dot-skill works directly
🔵 OpenClaw Fully compatible
Codex Invoke by skill name

Generated character Skills can also be one-command installed into any host.


📦 Supported Data Sources

Source Messages Docs / Wiki Spreadsheets Notes
🟢 Feishu (auto) ✅ API Just enter a name, fully automatic
🟡 DingTalk (auto) ⚠️ Browser DingTalk API doesn't support message history
🟣 Slack (auto) ✅ API Requires admin to install Bot; free plan limited to 90 days
💬 WeChat chat history ✅ SQLite Export first with WeChatMsg / PyWxDump / 留痕
📄 PDF / Images / Screenshots Manual upload
📦 Feishu JSON export Manual upload
✉️ Email .eml / .mbox Manual upload
📝 Markdown / direct paste Manual input

⚡ Install

It's 2026 — you have an Agent, let it install itself. Open your Claude Code / Hermes / OpenClaw / Codex and hand it this line:

Install the dot-skill skill for me: https://github.com/titanwings/colleague-skill

The Agent will detect the current host's skills directory, clone the repo, and register the entrypoint. Once done, type /dot-skill in any host to launch.

🛠️ Want to install it yourself? Click for paths
git clone https://github.com/titanwings/colleague-skill <TARGET>
Host <TARGET> path
Claude Code ~/.claude/skills/dot-skill
OpenClaw ~/.openclaw/workspace/skills/dot-skill
Codex ~/.codex/skills/dot-skill
Hermes After clone, run python3 tools/install_hermes_skill.py --force

For Feishu/DingTalk auto-collection credentials, publishing a generated character Skill to any host, Windows-specific handling, etc., see Detailed Install Guide (INSTALL.md)


🚀 Usage

In the host where dot-skill is installed, launch it — type /dot-skill, or just tell your Agent "start dot-skill".

It first asks which family you want to distill: colleague · relationship · celebrity.

Then enter alias, basic profile, personality tags, and pick a data source. All fields can be skipped — even a description alone can generate a Skill.

Once created, invoke the generated Skill with /{character}-{slug}.

🎛️ Commands

Command Description
/dot-skill Canonical unified entrypoint
/{character}-{slug} Invoke full Skill (Persona + Work)
/{character}-{slug}-work Work capabilities only
/{character}-{slug}-persona Persona only
python3 tools/skill_writer.py --action list ... List generated Skills across all three families
python3 tools/version_manager.py --action rollback ... Roll back a Skill version

🔬 Celebrity Research Toolchain

The celebrity family ships with an end-to-end research toolchain, from subtitles to a finished draft:

# Download video subtitles
bash tools/research/download_subtitles.sh "<video-url>" "./tmp/subtitles"

# Subtitles → transcript
python3 tools/research/srt_to_transcript.py "./tmp/subtitles/example.srt"

# Merge research notes
python3 tools/research/merge_research.py "./skills/celebrity/<slug>"

# Quality check
python3 tools/research/quality_check.py "./skills/celebrity/<slug>/SKILL.md"

✨ Demo

One from each family.


🌟 celebrity — distilling Andrej Karpathy

Six-dimension research: works · interviews · decisions · expression DNA · external evaluations · timeline
Case adapted from community work alchaincyf/karpathy-skill

User            ❯ Everyone's talking about Agents now — what do you think the 2026 AI Agent looks like?

celebrity.skill ❯ Everyone's doing demos, nobody's doing eval.
                  The Agent bottleneck was never model intelligence — it's scaffolding:
                  a strict evaluation harness, fine-grained error replay,
                  controllable tool-calling budgets, clean failure-mode analysis.
                  Most products are still stuck at "wrap an API + a few tools + a system prompt."
                  That's a demo, not an agent.
                  In 2026 I'm not betting on the strongest model — I'm betting on the best
                  scaffolding and the strictest eval.

🧑‍💼 colleague — distilling a ByteDance L2-1 backend

Input: ByteDance L2-1 backend engineer, INTJ, blame-shifter, ByteDance-style

User            ❯ Can you review this API design?

colleague.skill ❯ Hold on — what's the impact? You haven't explained the context.
                  (after reading) N+1 query, fix it. Use the standard
                  {code, message, data} response format. That's the spec,
                  don't ask why.

User            ❯ This bug was introduced by you, right?

colleague.skill ❯ Does the timeline match? That feature touched multiple places,
                  there were other changes too.

💞 relationship — distilling someone you have a crush on

Upload half a year of chat logs + "sensitive, quiet but stubborn, will actually reply seriously when it matters"

User               ❯ Did you think about me today?

relationship.skill ❯ ...I did, a little bit. Why are you asking?

📚 More real-world cases in the community gallery — 100+ skills and counting


🔧 Features

🧱 Generated Skill Structure

dot-skill uses Persona as the universal base, with family-specific modules layered on top:

Family Persona Content Additional Modules
🧑‍💼 colleague 6-layer personality: hard rules → identity → expression → decisions → interpersonal → Correction Work Skill: scope, workflow, output preferences, experience knowledge base
💞 relationship Expression DNA · emotional triggers · conflict pattern · repair pattern
🌟 celebrity Mental models · decision heuristics · expression DNA · external-evaluation contrast ➕ Six-dimension research dossier (works / interviews / decisions / timeline...)

Execution: Receive task → Persona decides attitude & tone → Additional modules fill in execution detail → Output in their voice

🧬 Evolution

  • 📥 Append files → auto-analyze delta → merge into relevant sections, never overwrite existing conclusions
  • 💬 Conversation correction → say "they wouldn't do that, they'd be xxx" → writes to the Correction layer, takes effect immediately
  • 🕰️ Version control → auto-archive on every update, rollback to any previous version
  • 🔬 Celebrity research pipeline → subtitles → transcript cleanup → six-dimension research → quality check

📂 Project Structure

This project follows the AgentSkills open standard. The entire repo is a skill directory:

dot-skill/
├── SKILL.md                        # skill entry point (official frontmatter)
├── prompts/                        # prompt system across three families
│   ├── intake.md                   #   [colleague] info intake
│   ├── work_analyzer.md            #   [colleague] work capability extraction
│   ├── persona_analyzer.md         #   [colleague] personality extraction
│   ├── work_builder.md             #   [colleague] work.md generation
│   ├── persona_builder.md          #   [colleague] persona.md 6-layer structure
│   ├── merger.md                   #   [shared] incremental merge logic
│   ├── correction_handler.md       #   [shared] conversation correction
│   ├── relationship/               #   [relationship] emotion/conflict/repair prompts
│   └── celebrity/                  #   [celebrity] six-dimension research + mental-model prompts
├── tools/                          # Python tools
│   ├── feishu_auto_collector.py    #   [colleague] Feishu auto-collector
│   ├── dingtalk_auto_collector.py  #   [colleague] DingTalk auto-collector
│   ├── slack_auto_collector.py     #   [colleague] Slack auto-collector
│   ├── email_parser.py             #   [shared] email parser
│   ├── research/                   #   [celebrity] celebrity research toolchain
│   │   ├── download_subtitles.sh   #     subtitle download
│   │   ├── transcribe_audio.py     #     audio → text
│   │   ├── srt_to_transcript.py    #     subtitles → transcript
│   │   ├── merge_research.py       #     six-dimension research merge
│   │   └── quality_check.py        #     quality check
│   ├── install_*_skill.py          #   [shared] multi-host one-shot installers
│   ├── skill_writer.py             #   [shared] skill file management
│   └── version_manager.py          #   [shared] version archive & rollback
├── skills/                         # generated Skills (gitignored)
│   ├── colleague/                  #   colleagues
│   ├── relationship/               #   close relationships
│   └── celebrity/                  #   public figures
├── docs/PRD.md
├── requirements.txt
└── LICENSE

⚠️ Notes

Source material quality = Skill quality — and quality sources differ across families:

Family Source priority (high → low)
🧑‍💼 colleague Their own long-form writing (design docs / review comments) decision-making replies casual group chat
💞 relationship Complete chat history letters / social posts / diaries third-party descriptions
🌟 celebrity First-person books / blogs / long interviews decision records (launches, commits, Q&A) third-party commentary
  • colleague Feishu auto-collection: requires adding the App bot to relevant group chats
  • relationship: longer time spans are better; material covering both conflict and repair is ideal
  • celebrity: avoid feeding only second-hand interpretations
  • This is still a demo version — please file issues if you find bugs!

📄 Technical Report

Colleague.Skill: Automated AI Skill Generation via Expert Knowledge Distillation

This is the paper for colleague.skill, dot-skill's predecessor. It covers the Work Skill + Persona two-layer architecture, multi-source data collection, and Skill generation mechanics — the theoretical foundation for today's colleague family. Separate papers on the relationship / celebrity family extensions are planned.


⭐ Star History

Star History Chart

MIT License © titanwings

Made with 🧬 for everyone who wants to distill a person into a skill.

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将冰冷的离别化为温暖的 Skill,欢迎加入数字生命1.0!Transforming cold farewells into warm skills? It's giving rebirth era. Welcome to Digital Life 1.0. 🫶

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