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Prompts Knowledge Source to AI Skill Builder

agent tool_use skill risk: low

Knowledge Source to AI Skill Builder

The prompt instructs the model to detect source types from user input and use Skill Seekers MCP server tools to convert documentation sites, GitHub repos, PDFs, videos, codebases,…

  • External action: medium

SKILL 1 file

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 35 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

REQUIRED CONTEXT

  • user request describing a knowledge source

TOOLS REQUIRED

  • generate_config
  • list_configs
  • validate_config
  • scrape_docs
  • scrape_github
  • scrape_pdf
  • scrape_video
  • scrape_codebase
  • scrape_generic
  • enhance_skill
  • package_skill
  • upload_skill
  • install_skill
  • detect_patterns
  • extract_test_examples
  • build_how_to_guides
  • split_config
  • export_to_weaviate
  • export_to_chroma
  • export_to_faiss
  • export_to_qdrant

EXPECTED OUTPUT

Format
chat_message
Constraints
  • follow recommended workflow steps
  • use appropriate MCP tool based on detected source type

QUALITY

OVERALL
0.82
CLARITY
0.90
SPECIFICITY
0.85
REUSABILITY
0.80
COMPLETENESS
0.80

IMPROVEMENT SUGGESTIONS

  • Add 2-3 example user inputs with expected first actions to demonstrate detection and workflow.

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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