Skill_Seekers

Skill Seekers

English | 简体中文 | 日本語 | 한국어 | Español | Français | Deutsch | Português | Türkçe | العربية | हिन्दी | Русский

🧠 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.

💛 Sponsors

Bronze Sponsors

Sponsor — Bronze

Become a sponsor · GitHub Sponsors

🚀 Quick Start

# 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"

🛰️ AI-driven project scan

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.

All 18 source types

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.

📦 Installation

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

Video visual deps (GPU-aware): after installing skill-seekers[video-full], run skill-seekers create --setup to auto-detect your GPU and install the matching PyTorch variant + easyocr.

Prerequisites: Python 3.10+, Git. New here? → Bulletproof Quick Start 🎯

📚 Documentation

Complete documentation index: docs/README.md

🎯 What you get

Export targets (22)

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.

Why it matters

• ⚡ 99% faster — days of manual data prep → 15–45 minutes