Skill Seekers 是一个把多种知识来源转成结构化 AI 数据的工具。它支持文档站、GitHub 仓库、PDF、视频、Notebook、Wiki 等 18 种来源,抓取后自动分类、分块,并能用多种大模型增强内容,同时检测多源信息之间的冲突。产出可导出为 Claude、Gemini、OpenAI 等平台可用的技能文件,也能生成适配 LangChain、LlamaIndex 及各类向量数据库的 RAG 数据,或供 Cursor、Windsurf 等编码助手读取的上下文文件。项目用 Python 编写,支持 API 和本地代理两种增强模式,提供大量预设工作流,适合需要为 AI 系统批量准备知识资产的人。
pip install skill-seekers[all]🧠 The data layer for AI systems. Skill Seekers turns documentation sites, GitHub repos, PDFs, videos, notebooks, wikis, and more — 18 source types — into structured knowledge assets, ready to power AI Skills (Claude, Gemini, OpenAI), RAG pipelines (LangChain, LlamaIndex, Pinecone), and AI coding assistants (Cursor, Windsurf, Cline). Prepare once, export to 22 targets.
Sponsor — Bronze
# 1. Install
pip install skill-seekers
# 2. Create a skill from any source
skill-seekers create https://docs.djangoproject.com/
# Optional: preview how a source will be detected without creating anything
skill-seekers detect https://docs.djangoproject.com/ --json
# 3. Package it for your AI platform
skill-seekers package output/django --target claude
You now have output/django-claude.zip, ready to use.
# Pick a different AI agent for enhancement (default: claude)
skill-seekers create https://docs.djangoproject.com/ --agent kimi
skill-seekers create https://docs.djangoproject.com/ --agent-cmd "my-custom-agent run"
Point scan at a project and an AI agent reads its manifests, README, Dockerfile/CI and sampled source imports — then emits one config per detected framework, plus a -codebase.json for your own code:
skill-seekers scan ./my-react-app --out ./configs/scanned/
# → react.json, vite.json, tailwind.json, jest.json, my-react-app-codebase.json
skill-seekers create ./configs/scanned/react.json
If a detection has no existing preset, the AI generates a fresh config; on exit you can optionally publish it back to the community registry.
skill-seekers create facebook/react # GitHub repository
skill-seekers create ./my-project # Local codebase
skill-seekers create manual.pdf # PDF
skill-seekers create report.docx # Word
skill-seekers create book.epub # EPUB
skill-seekers create notebook.ipynb # Jupyter
skill-seekers create openapi.yaml # OpenAPI/Swagger
skill-seekers create presentation.pptx # PowerPoint
skill-seekers create guide.adoc # AsciiDoc
skill-seekers create page.html # Local HTML (or a whole dir)
skill-seekers create feed.rss # RSS/Atom
skill-seekers create curl.1 # Man page
# Video (YouTube, Vimeo, or local — needs skill-seekers[video])
skill-seekers create --video-url https://www.youtube.com/watch?v=... --name mytutorial
skill-seekers create --setup # auto-install GPU-aware visual deps
skill-seekers create --space-key TEAM --name wiki # Confluence
skill-seekers create --database-id ... --name docs # Notion
skill-seekers create --chat-export-path ./slack-export --name team-chat # Slack/Discord
See the Scraping Guide for every source type and its options.
pip install skill-seekers # Core: scraping, GitHub, PDF, packaging
pip install skill-seekers[all-llms] # + every LLM platform
pip install skill-seekers[mcp] # + MCP server
pip install skill-seekers[all] # Everything
Not sure what you need? Run the wizard: skill-seekers-setup
All installation extras
| Install | Adds |
|---|---|
skill-seekers[gemini] | Google Gemini support |
skill-seekers[openai] | OpenAI ChatGPT support |
skill-seekers[all-llms] | All LLM platforms |
skill-seekers[mcp] | MCP server for Claude Code, Cursor, etc. |
skill-seekers[video] | YouTube/Vimeo transcript & metadata extraction |
skill-seekers[video-full] | + Whisper transcription & visual frame extraction |
skill-seekers[jupyter] | Jupyter Notebook support |
skill-seekers[pptx] | PowerPoint support |
skill-seekers[confluence] | Confluence wiki support |
skill-seekers[notion] | Notion pages support |
skill-seekers[rss] | RSS/Atom feed support |
skill-seekers[chat] | Slack/Discord chat export support |
skill-seekers[asciidoc] | AsciiDoc support |
skill-seekers[all] | Everything |
Video visual deps (GPU-aware): after installing
skill-seekers[video-full], runskill-seekers create --setupto auto-detect your GPU and install the matching PyTorch variant + easyocr.
Prerequisites: Python 3.10+, Git. New here? → Bulletproof Quick Start 🎯
| I want to... | Read this |
|---|---|
| Get started quickly | Quick Start — 3 commands to your first skill |
| Understand the concepts | Core Concepts |
| Scrape sources | Scraping Guide — all 18 source types |
| Enhance skills with AI | Enhancement Guide · Enhancement Modes |
| Export skills | Packaging Guide |
| Build workflows | Workflows |
| Look up a command | CLI Reference — all 19 commands |
| Configure | Config Format · Environment Variables |
| Set up MCP | MCP Setup · MCP Reference |
| Integrate with RAG / IDEs | LangChain · RAG Pipelines · Cursor · Windsurf · Cline |
| Handle huge doc sets | Large Documentation — 10K–40K+ pages |
| Understand the architecture | UML Architecture — 14 diagrams |
| Fix a problem | Troubleshooting |
Complete documentation index: docs/README.md
| Use case | Output | Powers |
|---|---|---|
| AI Skills | Comprehensive SKILL.md + reference files | Claude Code, Gemini, GPT |
| RAG pipelines | Chunked documents with rich metadata | LangChain, LlamaIndex, Haystack |
| Vector databases | Pre-formatted data ready for upsert | Pinecone, Chroma, Weaviate, FAISS, Qdrant |
| AI coding assistants | Context files your IDE AI reads automatically | Cursor, Windsurf, Cline, Continue.dev |
skill-seekers package output/react --target claude # → Claude Skill (ZIP + YAML)
skill-seekers package output/react --target langchain # → LangChain Documents
skill-seekers package output/react --target llama-index # → LlamaIndex TextNodes
skill-seekers package output/react --target ibm-bob # → IBM Bob skill directory
LLM platforms (12): claude · gemini · openai · minimax · opencode · kimi · deepseek · qwen · openrouter · together · fireworks · markdown
RAG & vector (8): langchain · llama-index · haystack · chroma · faiss · weaviate · qdrant · pinecone
Other (2): atlas · ibm-bob
See the Feature Matrix for per-platform support details.
SKILL.md files with examples, patterns, and guidesDocumentation scraping — SPA discovery, llms.txt, smart categorization
Three-layer discovery for JavaScript SPA sites (sitemap.xml → llms.txt → headless browser rendering), automatic llms.txt detection (10× faster when present), smart topic categorization, and a lenient HTML parser fallback so broken markup still scrapes.
GitHub & codebase analysis (C3.x) — AST parsing, pattern detection, how-to guides
Three-stream architecture: code analysis (AST, design patterns, tests), documentation (README, docs/, wiki), and community (issues, PRs, metadata). The C3.x pipeline adds 10 GoF pattern detectors across 9 languages, usage examples extracted from tests, AI-written how-to guides, config extraction, and architecture overviews.
skill-seekers create ./my-project --preset quick # 1–2 min, surface level
skill-seekers create ./my-project --preset standard # balanced (default)
skill-seekers create ./my-project --preset comprehensive # deep, exhaustive
AI enhancement — API or local agents, 68 workflow presets
Every AI call runs through one transport, in API mode (Anthropic, Google Gemini, OpenAI, Moonshot/Kimi, MiniMax) or LOCAL mode (Claude Code, Kimi Code, Codex, Copilot, OpenCode, custom agents — no API costs). Control depth with --enhance-level 0-3 and pick an agent with --agent.
Unified multi-source scraping — combine many sources into one skill
One config can pull documentation, GitHub, PDFs, videos, and more into a single knowledge asset, with conflict detection and pairwise synthesis across sources.
Search index inside the skill — query before you read (opt-in)
skill-seekers create --index adds a stdlib-only scripts/search.py and a SQLite FTS5 index over the generated references, so an agent can find the right file#anchor before reading a large Markdown file wholesale. Off by default; the Markdown is untouched.
Video extraction — transcripts, frames, on-screen code
YouTube, Vimeo, and local files. Three-tier transcript fallback (subtitles → YouTube transcript API → local Whisper), plus optional visual extraction that OCRs on-screen code from sampled frames.
Quality, sync & scale
Quality scoring with a gate (skill-seekers quality output/react/ --threshold 7) or JSON stdout (skill-seekers quality output/react/ --json), provisional English readability metrics (informational — they never affect the score), doc-change detection with scheduled re-scrapes and notifications, streaming ingestion for very large doc sets, and incremental updates.
Skill Seekers ships an MCP server for Claude Code, Cursor, Windsurf, VS Code + Cline, and IntelliJ IDEA.
# stdio mode (Claude Code, VS Code + Cline)
python -m skill_seekers.mcp.server_fastmcp
# HTTP mode (Cursor, Windsurf, IntelliJ)
python -m skill_seekers.mcp.server_fastmcp --transport http --port 8765
Then just ask your assistant: "Package and upload the React skill."
Skills install automatically into 19 AI coding agents:
skill-seekers install-agent output/react/ --agent cursor
skill-seekers install-agent output/react/ --agent all # every detected agent
skill-seekers install-agent output/react/ --agent cursor --dry-run
| Agent | Path | Scope |
|---|---|---|
| Claude Code | ~/.claude/skills/ | Global |
| Cursor | .cursor/skills/ | Project |
| VS Code / Copilot | .github/skills/ | Project |
| Amp | ~/.amp/skills/ | Global |
| Goose | ~/.config/goose/skills/ | Global |
| OpenCode | ~/.opencode/skills/ | Global |
| Letta | ~/.letta/skills/ | Global |
| Aide | ~/.aide/skills/ | Global |
| Windsurf | ~/.windsurf/skills/ | Global |
| Neovate | ~/.neovate/skills/ | Global |
| Roo Code | .roo/skills/ | Project |
| Cline | .cline/skills/ | Project |
| Aider | ~/.aider/skills/ | Global |
| Bolt | .bolt/skills/ | Project |
| Kilo Code | .kilo/skills/ | Project |
| Continue | ~/.continue/skills/ | Global |
| Kimi Code | ~/.kimi/skills/ | Global |
| IBM Bob | .bob/skills/ | Project |
export ANTHROPIC_API_KEY=sk-ant-...
skill-seekers package output/react/ --upload # package + upload
skill-seekers upload output/react.zip # upload an existing zip
No API key? Package it and upload output/react.zip manually at claude.ai/skills.
graph LR
A[Documentation Website] --> B[Skill Seekers]
B --> C[Scraper]
B --> D[AI Enhancement]
B --> E[Packager]
C --> F[Organized References]
D --> F
F --> E
E --> G[AI Skill .zip]
G --> H[Upload to AI Platform]
llms.txt first)SKILL.md with examples8 core modules + 5 utility modules (~200 classes):
| Module | Purpose |
|---|---|
| CLICore | Git-style command dispatcher, source auto-detection |
| Scrapers | 18 source-type extractors on a shared build layer |
| Adaptors | 22 output platform formats behind one SkillAdaptor ABC |
| Analysis | C3.x codebase pipeline, 10 GoF pattern detectors |
| Enhancement | AI improvement via a single AgentClient transport |
| Packaging | Package, upload, and install skills |
| MCP | FastMCP server (40 tools, 10 tool modules) |
| Sync | Doc change detection and notification |
fetch_config (#92) now retry connection blips and 5xx with backoff; 4xx still fails fast.Full history: CHANGELOG.md
| Documentation size | Time | Output |
|---|---|---|
| Small (< 100 pages) | 5–10 min | ~2 MB |
| Medium (100–500 pages) | 15–30 min | ~10 MB |
| Large (500–2,000 pages) | 30–60 min | ~40 MB |
| Huge (10K–40K+ pages) | Use stream | See Large Documentation |
skill-seekers doctor # diagnose installation & environment
skill-seekers doctor --json # machine-readable diagnostics for CI and agents
skill-seekers sync-config # detect config drift
Common issues and fixes: Troubleshooting Guide · TROUBLESHOOTING.md
Contributions are welcome — see CONTRIBUTING.md.
MIT — see LICENSE.
Skill Seekers is a multi-repo project:
| Repository | Description | Links |
|---|---|---|
| Skill_Seekers | Core CLI & MCP server (this repo) | PyPI |
| skillseekersweb | Website & documentation | Live |
| skill-seekers-configs | Community config repository | |
| skill-seekers-action | GitHub Action for CI/CD | |
| skill-seekers-plugin | Claude Code plugin | |
| homebrew-skill-seekers | Homebrew tap for macOS |
Want to contribute? The website and configs repos are great starting points for new contributors!
内容由编辑整理,部分信息来自 GitHub 与项目官网,版权归原作者所有。发现错误?报告问题