# 🧬 dot-skill(同事.skill)
### *"You folks building LLMs are all code-sages! Flesh is weak! Ascend to cyberspace!"*
[](LICENSE)
[](https://python.org)
[](https://agentskills.io)
[](https://github.com/titanwings/colleague-skill/stargazers)
[](https://claude.ai/code)
[](https://github.com/titanwings/colleague-skill)
[](https://github.com/titanwings/colleague-skill)
[](https://github.com/titanwings/colleague-skill)
[](https://discord.gg/NVX66RxWZv)
🧑💼 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](#-whats-new-in-this-major-release) · [📦 Data Sources](#-supported-data-sources) · [⚡ Install](#-install) · [🚀 Usage](#-usage) · [✨ Demo](#-demo) · [📝 Citation](#-citation) · [💬 Discord](https://discord.gg/NVX66RxWZv)
[**中文**](docs/lang/README_ZH.md) · [**Español**](docs/lang/README_ES.md) · [**Deutsch**](docs/lang/README_DE.md) · [**日本語**](docs/lang/README_JA.md) · [**Русский**](docs/lang/README_RU.md) · [**Português**](docs/lang/README_PT.md) · [**한국어**](docs/lang/README_KO.md)
---
### 🎉 2026.04.19 Milestone — **dot-skill just hit 15k ⭐!**
Massive thanks to everyone who starred — we'll keep shipping, keep distilling.
> 📝 **2026.06.01 Update** — **[COLLEAGUE.SKILL 技术报告](colleague_skill.pdf) 已上线**;这次最开心的不只是发了篇 paper,而是社区一起把 gallery 推到 215 个 skills、165 位贡献者和 100k+ skill-card 累计 stars,论文 Acknowledgements 也专门收录并感谢了所有社区贡献者。
> 📢 **2026.05.11 Update** — **WeChat group 12 is live!** Come hang out with the dot-skill community — share skills, discuss features, trade tips.
>
>
>
> QR refreshes every 7 days (expires 2026-05-18) — if expired, ping me on Discord.
> 🗺️ **2026.04.13** — **dot-skill Roadmap is live!** colleague.skill is evolving into **dot-skill** — distill anyone, not just colleagues. 👉 **[Full Roadmap](ROADMAP.md)** · **[💬 Discord](https://discord.gg/NVX66RxWZv)**
> 🌐 **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](https://titanwings.github.io/colleague-skill-site/)**
Created by [@titanwings](https://github.com/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
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:
Compatible hosts:
| 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
```bash
git clone https://github.com/titanwings/colleague-skill
```
| Host | `` 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` |
Generated character Skills can be published with `tools/install_claude_generated_skill.py`,
`tools/install_openclaw_generated_skill.py`, and `tools/install_codex_generated_skill.py`.
> For Feishu/DingTalk auto-collection credentials, publishing a generated character Skill to any host, Windows-specific handling, etc., see **[Detailed Install Guide (INSTALL.md)](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:
```bash
# Download video subtitles
bash tools/research/download_subtitles.sh "" "./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/"
# Quality check
python3 tools/research/quality_check.py "./skills/celebrity//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](https://github.com/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](https://titanwings.github.io/colleague-skill-site/)** — 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](https://agentskills.io) open standard. The entire repo is a skill directory.
Generated colleague skills live under `./skills/colleague`:
```
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](colleague_skill.pdf)** ([arXiv](https://arxiv.org/abs/2605.31264) · [arXiv PDF](https://arxiv.org/pdf/2605.31264))
>
> 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.
---
## 📝 Citation
If you use **dot-skill** or **colleague.skill** in your research or applications, please cite the technical report:
```bibtex
@misc{zhou2026colleagueskill,
title = {COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation},
author = {Tianyi Zhou and Dongrui Liu and Leitao Yuan and Jing Shao and Xia Hu},
year = {2026},
eprint = {2605.31264},
archivePrefix = {arXiv},
primaryClass = {cs.AI},
url = {https://arxiv.org/abs/2605.31264}
}
```
You can also use the machine-readable citation metadata in [CITATION.cff](CITATION.cff).
---
## ⭐ Star History
---