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yaofeino1/tech-distiller

把公司技术文档蒸馏成按职位方向过滤的结构化技术报告 | Inspired by colleague-skill & ex-skill

History

Review weekly changes to SKILL.md before updating. Dates mark the weeks in which we observed each version; checks apply to the recorded commits.

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SKILL.md

Week of Oct 26, 2026 · Line counts unavailable

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Verified commit 035fe2cbf8f8ab6ad1bf19719dbaadd60b607b20

144GitHub stars
0stars in 7 days
1skill in this repository
0commits in 30 days

Heat

0.4
  • Star growth, last 7 daysNot available
  • Star growth, last 24 hoursNot available
  • Rank movement, last 7 daysNot available
  • Commits, last 30 daysNot available
  • Accounts asking about it through MCP, last 7 daysNot available
  • Hot votes this weekNot available

Heat never changes the order by stars, and sponsorship never touches it. How heat works

Stars over time

Oct 25, 2026Oct 25, 2026144

30-day change not yet available: not enough history.

Individual skills in this repository

How it works

tech-distiller

When your agent uses it

Distill company/team technical knowledge from internal or external documents into a structured report, filtered by technical direction/role. Use when the user wants to: (1) collect and summarize technical docs from any source (URL, file, wiki, API, knowledge base), (2) filter content by role or direction (e.g., 搜索, 推荐, 后端, 基础架构, 数据平台, ML, 客户端, 前端), (3) generate a polished technical summary report capturing architecture, algorithms, interfaces, and design decisions, (4) evolve or refine an existing report with new documents. Triggers on phrases like "蒸馏技术文档", "生成技术报告", "distill tech docs", "tech knowledge report", "技术总结", "按职位方向生成报告", "公司技术蒸馏", "知识沉淀".

What it loads into context

Frontmatter

187 tokens

Always available to the agent

SKILL.md

1,336 tokens

When the skill is activated

Reference documents

3,310 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

  1. Workflow
  2. Evolution — 报告进化机制
  3. Notes

Scripts executed separately

  • scripts/render_report.py

Files

  • .gitignoreasset46 bytes
  • README.mddoc9,249 bytes
  • SKILL.mdcore5,346 bytes
  • SKILL.mdcore5,346 bytes
  • SKILL.mdcore5,346 bytes
  • SKILL.mdcore5,346 bytes
  • references/filtering-guide.mddoc3,113 bytes
  • requirements.txtdoc276 bytes
  • scripts/render_report.pyruns3,089 bytes

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

Skills included

  • tech-distiller

Repository facts

License
No license detected
Created
Apr 6, 2026
Last pushed
Apr 6, 2026
Forks
17
Open issues
1
Project activity
Slowing

Before you install

Local scripts

Automated signals, not a guarantee

Checked Nov 5, 2026

Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.

Show 3 notes
  • SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
  • SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
  • SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
Show all 15 signals by file

README.md

  • Network accessline 8
    [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](./LICENSE)
  • Network accessline 9
    [![Python 3.9+](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://python.org/)
  • Network accessline 10
    [![Claude Code](https://img.shields.io/badge/Claude%20Code-Skill-blueviolet)](https://claude.ai/code)
  • Network accessline 11
    [![AgentSkills](https://img.shields.io/badge/AgentSkills-Standard-green)](https://agentskills.io/)
  • Network accessline 195
    本项目遵循 [AgentSkills](https://agentskills.io/) 开放标准,整个 repo 即一个 skill 目录:
  • Network accessline 238
    - **[同事.skill](https://github.com/titanwings/colleague-skill)**(by [@titanwings](https://github.com/titanwings))— 首创"把人蒸馏成 AI Skill"的双层架构与进化机制
  • Network accessline 239
    - **[前任.skill](https://github.com/therealXiaomanChu/ex-skill)**(by [@therealXiaomanChu](https://github.com/therealXiaomanChu))— 验证了蒸馏模式在职场之外的普适性
  • Network accessline 245
    本项目遵循 [AgentSkills](https://agentskills.io/) 开放标准,兼容 Claude Code 和 OpenClaw。

SKILL.md

  • Network accessline 16
    | Input | Description | Example | |---|---|---| | **文档来源** | URLs, file paths, API endpoints, wiki spaces, knowledge base IDs | `https://wiki.company.com`, local `.md` files, Feishu docs |
  • Network accessline 17
    |---|---|---| | **文档来源** | URLs, file paths, API endpoints, wiki spaces, knowledge base IDs | `https://wiki.company.com`, local `.md` files, Feishu docs | | **技术方向** | Role / domain to focus on | `搜索算法`, `推荐系统`, `后端服务`, `数据平台`, `基础架构`, `ML/
  • Network accessline 18
    | **文档来源** | URLs, file paths, API endpoints, wiki spaces, knowledge base IDs | `https://wiki.company.com`, local `.md` files, Feishu docs |

scripts/render_report.py

  • Executable scriptline 1
    #!/usr/bin/env python3
  • Network accessline 10
    "direction": "搜索算法",   "audience": "新员工",   "sources": ["https://...", "wiki://..."],
  • Network accessline 11
    "audience": "新员工",   "sources": ["https://...", "wiki://..."],   "generated_at": "2026-04-06",
  • Network accessline 12
    "sources": ["https://...", "wiki://..."],

How the signals fit together

Facts from a static read of the files at the pinned commit. They describe what the code does, not why.

Signal confidence: 15 facts

Works with

Agent compatibility, from the files in this repository
AgentStatusEvidenceInstall to
Claude CodeCompatibleStandard SKILL.md SKILL.md.claude/skills/<skill-name>/
CodexCompatibleStandard SKILL.md SKILL.md.agents/skills/<skill-name>/
CursorCompatibleStandard SKILL.md SKILL.md.cursor/skills/<skill-name>/
Gemini CLICompatibleStandard SKILL.md SKILL.md.gemini/skills/<skill-name>/
GitHub CopilotCompatibleStandard SKILL.md SKILL.md.github/skills/<skill-name>/
OpenCodeCompatibleStandard SKILL.md SKILL.md.opencode/skills/<skill-name>/
  • Native The repository ships a manifest, folder or frontmatter field for this agent.
  • Compatible A standard SKILL.md that this agent can read.
  • Unknown No evidence either way.

Derived automatically from paths, manifests and frontmatter. Not tested on each agent.