skill-builder
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.
Works with
--- 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. license: MIT --- # 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 - `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
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Rigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.
repo-intake-and-plan
lllllllama/rigorpilot-skills
Rigor Intake helper for README-first deep learning repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.
minimal-run-and-audit
lllllllama/rigorpilot-skills
Rigor Run skill for README-first deep learning repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, hidden scientific-meaning changes, or end-to-end orchestration by itself.
