Skill Builder

Skill Builder

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

Overview

Build new agent skills with proper structure, triggers, and verification.

When NOT to Use

• You need to edit an existing skill (use the skill's own editing workflow)
• The source is a conversational transcript with no clear structure (use manual writing)
• You're looking for pre-built skills (use skill_view or search the 1ai-skills library)

Anti-Rationalization Table

When to Use

Trigger phrases:

• "skill builder"
• "Wants to create an AI skill from a documentation site, GitHub repo, PDF, video,"
• "Needs to convert documentation into a format suitable for LLM consumption"
• "Wants to update or sync existing skills with their source documentation"

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:

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

Commands

# Detect source type from input
#   URL → scrape_docs
#   owner/repo → scrape_github
#   file.pdf → scrape_pdf
#   video URL → scrape_video

# Basic workflow pipeline
python3 -c "
from skill_seekers import scrape_docs, enhance_skill, package_skill
# Step 1: Scrape
config = scrape_docs('https://example.com/docs', output_dir='./scraped')
# Step 2: Enhance
enhanced = enhance_skill(config, target_platform='hermes')
# Step 3: Package
package_skill(enhanced, format='SKILL.md', output='./output/')
"

Dependencies

• Python 3.10+
• skill-seekers package (tools for scraping and packaging)
• Internet access for documentation scraping
• API keys for vector DB exports (optional)

Process

1. Design — Define interface, identify patterns, plan implementation
2. Implement — Write code following existing conventions, add tests
3. Verify — Run tests, check integration, validate behavior

Verification

• Skill has SKILL.md with frontmatter
• Has ## When to Use with triggers
• Has ## Process section
• Has ## Verification checklist
• Lint passes with 0 errors