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.jsonstarts 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
- Installed as the Skill Seekers plugin? Nothing to do — the plugin's bundled
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 | 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_configorfetch_configif needed - Estimate scope with
estimate_pagesfor documentation sites - Scrape the source using the appropriate scraping tool
- Enhance with
enhance_skillif the user wants AI-powered improvements - Package with
package_skillfor 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 URLlist_configs— List available preset configsvalidate_config— Validate a config file
Scraping (use based on source type)
scrape_docs— Documentation sitesscrape_github— GitHub repositoriesscrape_pdf— PDF filesscrape_video— Video transcriptsscrape_codebase— Local code analysisscrape_generic— Jupyter, HTML, OpenAPI, AsciiDoc, PPTX, RSS, manpage, Confluence, Notion, chat
Post-processing
enhance_skill— AI-powered skill enhancementpackage_skill— Package for target platformupload_skill— Upload to platform APIinstall_skill— End-to-end install workflow
Advanced
detect_patterns— Design pattern detection in codeextract_test_examples— Extract usage examples from testsbuild_how_to_guides— Generate how-to guides from testssplit_config— Split large configs into focused skillsexport_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.