Skill Builder

This skill uses the Skill Seekers MCP server, which provides 40 tools for converting knowledge sources into AI-ready skills. If the MCP tools are not available, use the CLI fallback at the bottom of this file instead — do not stop.

Prerequisites

The MCP tools below only work when the Skill Seekers MCP server is connected:

Install the package: pip install "skill-seekers[mcp]"
Connect the server:
- Installed as the Skill Seekers plugin? Nothing to do — the plugin's bundled .mcp.json starts the server automatically (it still needs step 1).
- Installed standalone (e.g. copied into ~/.claude/skills/)? Register the server once: claude mcp add skill-seekers -- python -m skill_seekers.mcp.server_fastmcp

If tools like scrape_docs or package_skill are not in your tool list, the server is not connected. Tell the user about the two steps above, and use the CLI fallback in the meantime.

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

Detect source type from the user's input
Generate or fetch config using generate_config or fetch_config if needed
Estimate scope with estimate_pages for documentation sites
Scrape the source using the appropriate scraping tool
Enhance with enhance_skill if the user wants AI-powered improvements
Package with package_skill for the target platform
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
upload_skill — Upload to platform API
install_skill — End-to-end install workflow

Advanced

detect_patterns — Design pattern detection in code
extract_test_examples — Extract usage examples from tests
build_how_to_guides — Generate how-to guides from tests
split_config — Split large configs into focused skills
export_to_weaviate, export_to_chroma, export_to_faiss, export_to_qdrant — Vector DB export

CLI Fallback (MCP server not connected)

The same pipeline is available from the command line (requires pip install skill-seekers). Run it with the Bash tool:

skill-seekers create <source>                      # auto-detects: URL, owner/repo, ./path, file.pdf, video URL, ...
skill-seekers package <skill_dir> --target claude  # or gemini/openai/langchain/chroma/...

create covers detection, scraping, and building in one step; add --enhance-level 0 to skip AI enhancement. After it finishes, read the generated SKILL.md and summarize what was created.

Skill_Seekers