Skill Seekers

Install

pip install skill-seekers

This is third-party code. Review the repository files before installing.

What it does

Skill Seekers gathers knowledge from 18 source types: documentation sites, GitHub repos, local code, PDF, DOCX, EPUB, Jupyter, OpenAPI, video, Confluence, Notion and Slack or Discord exports. Output is packaged for 22 targets: skills for Claude, Gemini and OpenAI, LangChain and LlamaIndex documents, and data for Pinecone, Chroma, Qdrant and more. scan inspects a project and emits configs for detected frameworks, and install-agent places a skill into 19 coding agents. It also ships a 40-tool MCP server.

Who it is for. Developers who want to give agents knowledge of a framework or their own codebase, and teams building RAG.

Example request

Build a skill from the Django documentation and install it into Claude Code

Limitations

Requires Python 3.10+ and Git; some sources need extras such as skill-seekers[video] or skill-seekers[notion]. AI enhancement needs an agent or provider API key, and uploading to Claude needs ANTHROPIC_API_KEY. Visual video extraction needs GPU dependencies.

How to disable. Remove the MCP server entry from your client config and the installed skills from agent directories; uninstall the package with pip.

Security check

• Scrapes external sites and repositories
• Uses provider API keys for enhancement and uploads
• Writes skill files into several agents' directories

README in short

Skill Seekers presents itself as a data layer for AI systems, turning documentation and other sources into structured knowledge assets. It installs from PyPI, and the quick start is three commands: install, create and package. The README lists source types, export targets, codebase analysis with pattern detection, MCP integration and a table of agent install paths. The project reports 3,900+ tests and has docs at skillseekersweb.com. MIT licensed.

SKILL.md

---
name: skill-builder
description: Automatically detect source types and build AI skills using Skill Seekers. Use when the user wants to create skills from documentation, repos, PDFs, videos, or other knowledge sources.
---

# Skill Builder

You have access to the Skill Seekers MCP server which provides 40 tools for converting knowledge sources into AI-ready skills.

## When to Use This Skill

Use this skill when the user:
- Wants to create an AI skill from a documentation site, GitHub repo, PDF, video, or other source
- Needs to convert documentation into a format suitable for LLM consumption
- Wants to update or sync existing skills with their source documentation
- Needs to export skills to vector databases (Weaviate, Chroma, FAISS, Qdrant)
- Asks about scraping, converting, or packaging documentation for AI

## Source Type Detection

Automatically detect the source type from user input:

| Input Pattern | Source Type | Tool to Use |
|---------------|-------------|-------------|
| `https://...` (not GitHub/YouTube) | Documentation | `scrape_docs` |
| `owner/repo` or `github.com/...` | GitHub | `scrape_github` |
| `*.pdf` | PDF | `scrape_pdf` |
| YouTube/Vimeo URL or video file | Video | `scrape_video` |
| Local directory path | Codebase | `scrape_codebase` |
| `*.ipynb`, `*.html`, `*.yaml` (OpenAPI), `*.adoc`, `*.pptx`, `*.rss`, `*.1`-`.8` | Various | `scrape_generic` |
| JSON config file | Unified | Use config with `scrape_docs` |

## Recommended Workflow

1. **Detect source type** from the user's input
2. **Generate or fetch config** using `generate_config` or `fetch_config` if needed
3. **Estimate scope** with `estimate_pages` for documentation sites
4. **Scrape the source** using the appropriate scraping tool
5. **Enhance** with `enhance_skill` if the user wants AI-powered improvements
6. **Package** with `package_skill` for the target platform
7. **Export to vector DB** if requested using `export_to_*` tools

## Available MCP Tools

### Config Management
- `generate_config` — Generate a scraping config from a URL
- `list_configs` — List available preset configs
- `validate_config` — Validate a config file

### Scraping (use based on source type)
- `scrape_docs` — Documentation sites
- `scrape_github` — GitHub repositories
- `scrape_pdf` — PDF files
- `scrape_video` — Video transcripts
- `scrape_codebase` — Local code analysis
- `scrape_generic` — Jupyter, HTML, OpenAPI, AsciiDoc, PPTX, RSS, manpage, Confluence, Notion, chat

### Post-processing
- `enhance_skill` — AI-powered skill enhancement
- `package_skill` — Package for target platform

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