Skill Seekers

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🧠 The data layer for AI systems. Skill Seekers turns any documentation, GitHub repo, or PDF into structured knowledge assets—ready to power AI Skills (Claude, Gemini, OpenAI), RAG pipelines (LangChain, LlamaIndex, Pinecone), and AI coding assistants (Cursor, Windsurf, Cline) in minutes, not hours.

🌐 Visit SkillSeekersWeb.com - Browse 24+ preset configs, share your configs, and access complete documentation!

📋 View Development Roadmap & Tasks - 134 tasks across 10 categories, pick any to contribute!

Skill Seekers is the universal preprocessing layer that sits between raw documentation and every AI system that consumes it. Whether you are building Claude skills, a LangChain RAG pipeline, or a Cursor .cursorrules file — the data preparation is identical. You do it once, and export to all targets.

# One command → structured knowledge asset
skill-seekers create https://docs.react.dev/
# or: skill-seekers create facebook/react
# or: skill-seekers create ./my-project

# Export to any AI system
skill-seekers package output/react --target claude      # → Claude AI Skill (ZIP)
skill-seekers package output/react --target langchain   # → LangChain Documents
skill-seekers package output/react --target llama-index # → LlamaIndex TextNodes
skill-seekers package output/react --target cursor      # → .cursorrules

• ⚡ 99% faster — Days of manual data prep → 15–45 minutes
• 🎯 AI Skill quality — 500+ line SKILL.md files with examples, patterns, and guides
• 📊 RAG-ready chunks — Smart chunking preserves code blocks and maintains context
• 🔄 Multi-source — Combine docs + GitHub + PDFs into one knowledge asset
• 🌐 One prep, every target — Export the same asset to 16 platforms without re-scraping
• ✅ Battle-tested — 1,880+ tests, 24+ framework presets, production-ready

# 1. Install
pip install skill-seekers

# 2. Create skill from any source
skill-seekers create https://docs.django.com/

# 3. Package for your AI platform
skill-seekers package output/django --target claude

That's it! You now have output/django-claude.zip ready to use.

# GitHub repository
skill-seekers create facebook/react

# Local project
skill-seekers create ./my-project

# PDF document
skill-seekers create manual.pdf

# Package for multiple platforms
for platform in claude gemini openai langchain; do
  skill-seekers package output/django --target $platform
done

Skill Seekers is the data layer for AI systems. It transforms documentation websites, GitHub repositories, and PDF files into structured knowledge assets for every AI target:

Complete documentation: docs/README.md

Instead of spending days on manual preprocessing, Skill Seekers:

1. Ingests — docs, GitHub repos, local codebases, PDFs
2. Analyzes — deep AST parsing, pattern detection, API extraction
3. Structures — categorized reference files with metadata
4. Enhances — AI-powered SKILL.md generation (Claude, Gemini, or local)
5. Exports — 16 platform-specific formats from one asset

• 🎯 Production-grade Skills — 500+ line SKILL.md files with code examples, patterns, and guides
• 🔄 Enhancement Workflows — Apply security-focus, architecture-comprehensive, or custom YAML presets
• 🎮 Any Domain — Game engines (Godot, Unity), frameworks (React, Django), internal tools
• 🔧 Teams — Combine internal docs + code into a single source of truth
• 📚 Quality — AI-enhanced with examples, quick reference, and navigation guidance

• 🤖 RAG-ready data — Pre-chunked LangChain Documents, LlamaIndex TextNodes, Haystack Documents
• 🚀 99% faster — Days of preprocessing → 15–45 minutes
• 📊 Smart metadata — Categories, sources, types → better retrieval accuracy
• 🔄 Multi-source — Combine docs + GitHub + PDFs in one pipeline
• 🌐 Platform-agnostic — Export to any vector DB or framework without re-scraping

• 💻 Cursor / Windsurf / Cline — Generate .cursorrules / .windsurfrules / .clinerules automatically
• 🎯 Persistent context — AI "knows" your frameworks without repeated prompting
• 📚 Always current — Update context in minutes when docs change

• ✅ llms.txt Support - Automatically detects and uses LLM-ready documentation files (10x faster)
• ✅ Universal Scraper - Works with ANY documentation website
• ✅ Smart Categorization - Automatically organizes content by topic
• ✅ Code Language Detection - Recognizes Python, JavaScript, C++, GDScript, etc.
• ✅ 24+ Ready-to-Use Presets - Godot, React, Vue, Django, FastAPI, and more

• ✅ Basic PDF Extraction - Extract text, code, and images from PDF files
• ✅ OCR for Scanned PDFs - Extract text from scanned documents
• ✅ Password-Protected PDFs - Handle encrypted PDFs
• ✅ Table Extraction - Extract complex tables from PDFs
• ✅ Parallel Processing - 3x faster for large PDFs
• ✅ Intelligent Caching - 50% faster on re-runs

• ✅ Deep Code Analysis - AST parsing for Python, JavaScript, TypeScript, Java, C++, Go
• ✅ API Extraction - Functions, classes, methods with parameters and types
• ✅ Repository Metadata - README, file tree, language breakdown, stars/forks
• ✅ GitHub Issues & PRs - Fetch open/closed issues with labels and milestones
• ✅ CHANGELOG & Releases - Automatically extract version history
• ✅ Conflict Detection - Compare documented APIs vs actual code implementation
• ✅ MCP Integration - Natural language: "Scrape GitHub repo facebook/react"

• ✅ Combine Multiple Sources - Mix documentation + GitHub + PDF in one skill
• ✅ Conflict Detection - Automatically finds discrepancies between docs and code
• ✅ Intelligent Merging - Rule-based or AI-powered conflict resolution
• ✅ Transparent Reporting - Side-by-side comparison with ⚠️ warnings
• ✅ Documentation Gap Analysis - Identifies outdated docs and undocumented features
• ✅ Single Source of Truth - One skill showing both intent (docs) and reality (code)
• ✅ Backward Compatible - Legacy single-source configs still work

• ✅ 4 LLM Platforms - Claude AI, Google Gemini, OpenAI ChatGPT, Generic Markdown
• ✅ Universal Scraping - Same documentation works for all platforms
• ✅ Platform-Specific Packaging - Optimized formats for each LLM
• ✅ One-Command Export - --target flag selects platform
• ✅ Optional Dependencies - Install only what you need
• ✅ 100% Backward Compatible - Existing Claude workflows unchanged

# Claude (default - no changes needed!)
skill-seekers package output/react/
skill-seekers upload react.zip

# Google Gemini
pip install skill-seekers[gemini]
skill-seekers package output/react/ --target gemini
skill-seekers upload react-gemini.tar.gz --target gemini

# OpenAI ChatGPT
pip install skill-seekers[openai]
skill-seekers package output/react/ --target openai
skill-seekers upload react-openai.zip --target openai

# Generic Markdown (universal export)
skill-seekers package output/react/ --target markdown
# Use the markdown files directly in any LLM

# Option 1: Official Anthropic API (default)
export ANTHROPIC_API_KEY=sk-ant-...

# Option 2: GLM-4.7 Claude-compatible API
export ANTHROPIC_API_KEY=your-glm-47-api-key
export ANTHROPIC_BASE_URL=https://glm-4-7-endpoint.com/v1

# All AI enhancement features will use the configured endpoint
skill-seekers enhance output/react/
skill-seekers analyze --directory . --enhance

Installation:

# Install with Gemini support
pip install skill-seekers[gemini]

# Install with OpenAI support
pip install skill-seekers[openai]

# Install with all LLM platforms
pip install skill-seekers[all-llms]

• ✅ LangChain Documents - Direct export to Document format with page_content + metadata

  • Perfect for: QA chains, retrievers, vector stores, agents
  • Example: LangChain RAG Pipeline
  • Guide: LangChain Integration

• ✅ LlamaIndex TextNodes - Export to TextNode format with unique IDs + embeddings

  • Perfect for: Query engines, chat engines, storage context
  • Example: LlamaIndex Query Engine
  • Guide: LlamaIndex Integration

• ✅ Pinecone-Ready Format - Optimized for vector database upsert

  • Perfect for: Production vector search, semantic search, hybrid search
  • Example: Pinecone Upsert
  • Guide: Pinecone Integration

Quick Export:

# LangChain Documents (JSON)
skill-seekers package output/django --target langchain
# → output/django-langchain.json

# LlamaIndex TextNodes (JSON)
skill-seekers package output/django --target llama-index
# → output/django-llama-index.json

# Markdown (Universal)
skill-seekers package output/django --target markdown
# → output/django-markdown/SKILL.md + references/

Complete RAG Pipeline Guide: RAG Pipelines Documentation

Transform any framework documentation into expert coding context for 4+ AI assistants:

• ✅ Cursor IDE - Generate .cursorrules for AI-powered code suggestions

  • Perfect for: Framework-specific code generation, consistent patterns
  • Works with: Cursor IDE (VS Code fork)
  • Guide: Cursor Integration
  • Example: Cursor React Skill

• ✅ Windsurf - Customize Windsurf's AI assistant context with .windsurfrules

  • Perfect for: IDE-native AI assistance, flow-based coding
  • Works with: Windsurf IDE by Codeium
  • Guide: Windsurf Integration
  • Example: Windsurf FastAPI Context

• ✅ Cline (VS Code) - System prompts + MCP for VS Code agent

  • Perfect for: Agentic code generation in VS Code
  • Works with: Cline extension for VS Code
  • Guide: Cline Integration
  • Example: Cline Django Assistant

• ✅ Continue.dev - Context servers for IDE-agnostic AI

  • Perfect for: Multi-IDE environments (VS Code, JetBrains, Vim), custom LLM providers
  • Works with: Any IDE with Continue.dev plugin
  • Guide: Continue Integration
  • Example: Continue Universal Context

Quick Export for AI Coding Tools:

# For any AI coding assistant (Cursor, Windsurf, Cline, Continue.dev)
skill-seekers scrape --config configs/django.json
skill-seekers package output/django --target claude  # or --target markdown

# Copy to your project (example for Cursor)
cp output/django-claude/SKILL.md my-project/.cursorrules

# Or for Windsurf
cp output/django-claude/SKILL.md my-project/.windsurf/rules/django.md

# Or for Cline
cp output/django-claude/SKILL.md my-project/.clinerules

# Or for Continue.dev (HTTP server)
python examples/continue-dev-universal/context_server.py
# Configure in ~/.continue/config.json

Integration Hub: All AI System Integrations

• ✅ Triple-Stream Analysis - Split GitHub repos into Code, Docs, and Insights streams
• ✅ Unified Codebase Analyzer - Works with GitHub URLs AND local paths
• ✅ C3.x as Analysis Depth - Choose 'basic' (1-2 min) or 'c3x' (20-60 min) analysis
• ✅ Enhanced Router Generation - GitHub metadata, README quick start, common issues
• ✅ Issue Integration - Top problems and solutions from GitHub issues
• ✅ Smart Routing Keywords - GitHub labels weighted 2x for better topic detection

Three Streams Explained:

• Stream 1: Code - Deep C3.x analysis (patterns, examples, guides, configs, architecture)
• Stream 2: Docs - Repository documentation (README, CONTRIBUTING, docs/*.md)
• Stream 3: Insights - Community knowledge (issues, labels, stars, forks)

from skill_seekers.cli.unified_codebase_analyzer import UnifiedCodebaseAnalyzer

# Analyze GitHub repo with all three streams
analyzer = UnifiedCodebaseAnalyzer()
result = analyzer.analyze(
    source="https://github.com/facebook/react",
    depth="c3x",  # or "basic" for fast analysis
    fetch_github_metadata=True
)

# Access code stream (C3.x analysis)
print(f"Design patterns: {len(result.code_analysis['c3_1_patterns'])}")
print(f"Test examples: {result.code_analysis['c3_2_examples_count']}")

# Access docs stream (repository docs)
print(f"README: {result.github_docs['readme'][:100]}")

# Access insights stream (GitHub metadata)
print(f"Stars: {result.github_insights['metadata']['stars']}")
print(f"Common issues: {len(result.github_insights['common_problems'])}")

See complete documentation: Three-Stream Implementation Summary

• ✅ Multi-Token Configuration System - Manage multiple GitHub accounts (personal, work, OSS)
  • Secure config storage at ~/.config/skill-seekers/config.json (600 permissions)
  • Per-profile rate limit strategies: prompt, wait, switch, fail
  • Configurable timeout per profile (default: 30 min, prevents indefinite waits)
  • Smart fallback chain: CLI arg → Env var → Config file → Prompt
  • API key management for Claude, Gemini, OpenAI
• ✅ Interactive Configuration Wizard - Beautiful terminal UI for easy setup
  • Browser integration for token creation (auto-opens GitHub, etc.)
  • Token validation and connection testing
  • Visual status display with color coding
• ✅ Intelligent Rate Limit Handler - No more indefinite waits!
  • Upfront warning about rate limits (60/hour vs 5000/hour)
  • Real-time detection from GitHub API responses
  • Live countdown timers with progress
  • Automatic profile switching when rate limited
  • Four strategies: prompt (ask), wait (countdown), switch (try another), fail (abort)
• ✅ Resume Capability - Continue interrupted jobs
  • Auto-save progress at configurable intervals (default: 60 sec)
  • List all resumable jobs with progress details
  • Auto-cleanup of old jobs (default: 7 days)
• ✅ CI/CD Support - Non-interactive mode for automation
  • --non-interactive flag fails fast without prompts
  • --profile flag to select specific GitHub account
  • Clear error messages for pipeline logs

Quick Setup:

# One-time configuration (5 minutes)
skill-seekers config --github

# Use specific profile for private repos
skill-seekers github --repo mycompany/private-repo --profile work

# CI/CD mode (fail fast, no prompts)
skill-seekers github --repo owner/repo --non-interactive

# Resume interrupted job
skill-seekers resume --list
skill-seekers resume github_react_20260117_143022

Rate Limit Strategies Explained:

• prompt (default) - Ask what to do when rate limited (wait, switch, setup token, cancel)
• wait - Automatically wait with countdown timer (respects timeout)
• switch - Automatically try next available profile (for multi-account setups)
• fail - Fail immediately with clear error (perfect for CI/CD)

Generate skill-seekers as a Claude Code skill to use within Claude:

# Generate the skill
./scripts/bootstrap_skill.sh

# Install to Claude Code
cp -r output/skill-seekers ~/.claude/skills/

What you get:

• ✅ Complete skill documentation - All CLI commands and usage patterns
• ✅ CLI command reference - Every tool and its options documented
• ✅ Quick start examples - Common workflows and best practices
• ✅ Auto-generated API docs - Code analysis, patterns, and examples

• ✅ Git-Based Config Sources - Fetch configs from private/team git repositories
• ✅ Multi-Source Management - Register unlimited GitHub, GitLab, Bitbucket repos
• ✅ Team Collaboration - Share custom configs across 3-5 person teams
• ✅ Enterprise Support - Scale to 500+ developers with priority-based resolution
• ✅ Secure Authentication - Environment variable tokens (GITHUB_TOKEN, GITLAB_TOKEN)
• ✅ Intelligent Caching - Clone once, pull updates automatically
• ✅ Offline Mode - Work with cached configs when offline

C3.4: Configuration Pattern Extraction with AI Enhancement

• ✅ 9 Config Formats - JSON, YAML, TOML, ENV, INI, Python, JavaScript, Dockerfile, Docker Compose
• ✅ 7 Pattern Types - Database, API, logging, cache, email, auth, server configurations
• ✅ AI Enhancement - Optional dual-mode AI analysis (API + LOCAL)
  • Explains what each config does
  • Suggests best practices and improvements
  • Security analysis - Finds hardcoded secrets, exposed credentials
• ✅ Auto-Documentation - Generates JSON + Markdown documentation of all configs
• ✅ MCP Integration - extract_config_patterns tool with enhancement support

C3.3: AI-Enhanced How-To Guides

• ✅ Comprehensive AI Enhancement - Transforms basic guides into professional tutorials
• ✅ 5 Automatic Improvements - Step descriptions, troubleshooting, prerequisites, next steps, use cases
• ✅ Dual-Mode Support - API mode (Claude API) or LOCAL mode (Claude Code CLI)
• ✅ No API Costs with LOCAL Mode - FREE enhancement using your Claude Code Max plan
• ✅ Quality Transformation - 75-line templates → 500+ line comprehensive guides

Usage:

# Quick analysis (1-2 min, basic features only)
skill-seekers analyze --directory tests/ --quick

# Comprehensive analysis with AI (20-60 min, all features)
skill-seekers analyze --directory tests/ --comprehensive

# With AI enhancement
skill-seekers analyze --directory tests/ --enhance

Full Documentation: docs/HOW_TO_GUIDES.md

Reusable YAML-defined enhancement pipelines that control how AI transforms your raw documentation into a polished skill.

• ✅ 5 Bundled Presets — default, minimal, security-focus, architecture-comprehensive, api-documentation
• ✅ User-Defined Presets — add custom workflows to ~/.config/skill-seekers/workflows/
• ✅ Multiple Workflows — chain two or more workflows in one command
• ✅ Fully Managed CLI — list, inspect, copy, add, remove, and validate workflows

# Apply a single workflow
skill-seekers create ./my-project --enhance-workflow security-focus

# Chain multiple workflows (applied in order)
skill-seekers create ./my-project \
  --enhance-workflow security-focus \
  --enhance-workflow minimal

# Manage presets
skill-seekers workflows list                          # List all (bundled + user)
skill-seekers workflows show security-focus           # Print YAML content
skill-seekers workflows copy security-focus           # Copy to user dir for editing
skill-seekers workflows add ./my-workflow.yaml        # Install a custom preset
skill-seekers workflows remove my-workflow            # Remove a user preset
skill-seekers workflows validate security-focus       # Validate preset structure

# Copy multiple at once
skill-seekers workflows copy security-focus minimal api-documentation

# Add multiple files at once
skill-seekers workflows add ./wf-a.yaml ./wf-b.yaml

# Remove multiple at once
skill-seekers workflows remove my-wf-a my-wf-b

YAML preset format:

name: security-focus
description: "Security-focused review: vulnerabilities, auth, data handling"
version: "1.0"
stages:
  - name: vulnerabilities
    type: custom
    prompt: "Review for OWASP top 10 and common security vulnerabilities..."
  - name: auth-review
    type: custom
    prompt: "Examine authentication and authorisation patterns..."
    uses_history: true

• ✅ Async Mode - 2-3x faster scraping with async/await (use --async flag)
• ✅ Large Documentation Support - Handle 10K-40K+ page docs with intelligent splitting
• ✅ Router/Hub Skills - Intelligent routing to specialized sub-skills
• ✅ Parallel Scraping - Process multiple skills simultaneously
• ✅ Checkpoint/Resume - Never lose progress on long scrapes
• ✅ Caching System - Scrape once, rebuild instantly

• ✅ Fully Tested - 1,880+ tests with comprehensive coverage

# Basic install (documentation scraping, GitHub analysis, PDF, packaging)
pip install skill-seekers

# With all LLM platform support
pip install skill-seekers[all-llms]

# With MCP server
pip install skill-seekers[mcp]

# Everything
pip install skill-seekers[all]

Need help choosing? Run the setup wizard:

skill-seekers-setup

The fastest way to go from config to uploaded skill - complete automation:

# Install React skill from official configs (auto-uploads to Claude)
skill-seekers install --config react

# Install from local config file
skill-seekers install --config configs/custom.json

# Install without uploading (package only)
skill-seekers install --config django --no-upload

# Preview workflow without executing
skill-seekers install --config react --dry-run

Time: 20-45 minutes total | Quality: Production-ready (9/10) | Cost: Free

Phases executed:

📥 PHASE 1: Fetch Config (if config name provided)
📖 PHASE 2: Scrape Documentation
✨ PHASE 3: AI Enhancement (MANDATORY - no skip option)
📦 PHASE 4: Package Skill
☁️  PHASE 5: Upload to Claude (optional, requires API key)

Requirements:

• ANTHROPIC_API_KEY environment variable (for auto-upload)
• Claude Code Max plan (for local AI enhancement)

Skill Seekers supports 4 LLM platforms and 5 skill modes with full feature parity.

Platforms: Claude AI, Google Gemini, OpenAI ChatGPT, Generic Markdown Skill Modes: Documentation, GitHub, PDF, Unified Multi-Source, Local Repository

See Complete Feature Matrix for detailed platform and feature support.

# Scrape documentation website
skill-seekers scrape --config configs/react.json

# Quick scrape without config
skill-seekers scrape --url https://react.dev --name react

# With async mode (3x faster)
skill-seekers scrape --config configs/godot.json --async --workers 8

# Basic PDF extraction
skill-seekers pdf --pdf docs/manual.pdf --name myskill

# Advanced features
skill-seekers pdf --pdf docs/manual.pdf --name myskill \
    --extract-tables \        # Extract tables
    --parallel \              # Fast parallel processing
    --workers 8               # Use 8 CPU cores

# Scanned PDFs (requires: pip install pytesseract Pillow)
skill-seekers pdf --pdf docs/scanned.pdf --name myskill --ocr

# Basic repository scraping
skill-seekers github --repo facebook/react

# With authentication (higher rate limits)
export GITHUB_TOKEN=ghp_your_token_here
skill-seekers github --repo facebook/react

# Customize what to include
skill-seekers github --repo django/django \
    --include-issues \        # Extract GitHub Issues
    --max-issues 100 \        # Limit issue count
    --include-changelog       # Extract CHANGELOG.md

Combine documentation + GitHub + PDF into one unified skill with conflict detection:

# Use existing unified configs
skill-seekers unified --config configs/react_unified.json
skill-seekers unified --config configs/django_unified.json

# Or create unified config
cat > configs/myframework_unified.json << 'EOF'
{
  "name": "myframework",
  "merge_mode": "rule-based",
  "sources": [
    {
      "type": "documentation",
      "base_url": "https://docs.myframework.com/",
      "max_pages": 200
    },
    {
      "type": "github",
      "repo": "owner/myframework",
      "code_analysis_depth": "surface"
    }
  ]
}
EOF

skill-seekers unified --config configs/myframework_unified.json

Conflict Detection automatically finds:

• 🔴 Missing in code (high): Documented but not implemented
• 🟡 Missing in docs (medium): Implemented but not documented
• ⚠️ Signature mismatch: Different parameters/types
• ℹ️ Description mismatch: Different explanations

Full Guide: See docs/UNIFIED_SCRAPING.md for complete documentation.

Share custom configs across teams using private git repositories:

# Option 1: Using MCP tools (recommended)
# Register your team's private repo
add_config_source(
    name="team",
    git_url="https://github.com/mycompany/skill-configs.git",
    token_env="GITHUB_TOKEN"
)

# Fetch config from team repo
fetch_config(source="team", config_name="internal-api")

Supported Platforms:

• GitHub (GITHUB_TOKEN), GitLab (GITLAB_TOKEN), Gitea (GITEA_TOKEN), Bitbucket (BITBUCKET_TOKEN)

Full Guide: See docs/GIT_CONFIG_SOURCES.md for complete documentation.

0. Detect llms.txt - Checks for llms-full.txt, llms.txt, llms-small.txt first
1. Scrape: Extracts all pages from documentation
2. Categorize: Organizes content into topics (API, guides, tutorials, etc.)
3. Enhance: AI analyzes docs and creates comprehensive SKILL.md with examples
4. Package: Bundles everything into a Claude-ready .zip file

Before you start, make sure you have:

1. Python 3.10 or higher - Download | Check: python3 --version
2. Git - Download | Check: git --version
3. 15-30 minutes for first-time setup

First time user? → Start Here: Bulletproof Quick Start Guide 🎯

Once your skill is packaged, you need to upload it to Claude:

# Set your API key (one-time)
export ANTHROPIC_API_KEY=sk-ant-...

# Package and upload automatically
skill-seekers package output/react/ --upload

# OR upload existing .zip
skill-seekers upload output/react.zip

# Package skill
skill-seekers package output/react/
# → Creates output/react.zip

# Then manually upload:
# - Go to https://claude.ai/skills
# - Click "Upload Skill"
# - Select output/react.zip

In Claude Code, just ask:
"Package and upload the React skill"

Skill Seekers can automatically install skills to 10+ AI coding agents.

# Install to specific agent
skill-seekers install-agent output/react/ --agent cursor

# Install to all agents at once
skill-seekers install-agent output/react/ --agent all

# Preview without installing
skill-seekers install-agent output/react/ --agent cursor --dry-run

Skill Seekers ships an MCP server for use from Claude Code, Cursor, Windsurf, VS Code + Cline, or IntelliJ IDEA.

# stdio mode (Claude Code, VS Code + Cline)
python -m skill_seekers.mcp.server_fastmcp

# HTTP mode (Cursor, Windsurf, IntelliJ)
python -m skill_seekers.mcp.server_fastmcp --transport http --port 8765

# Auto-configure all agents at once
./setup_mcp.sh

All 26 tools available:

• Core (9): list_configs, generate_config, validate_config, estimate_pages, scrape_docs, package_skill, upload_skill, enhance_skill, install_skill
• Extended (10): scrape_github, scrape_pdf, unified_scrape, merge_sources, detect_conflicts, add_config_source, fetch_config, list_config_sources, remove_config_source, split_config
• Vector DB (4): export_to_chroma, export_to_weaviate, export_to_faiss, export_to_qdrant
• Cloud (3): cloud_upload, cloud_download, cloud_list

Full Guide: docs/MCP_SETUP.md

# List all presets
skill-seekers list-configs

# Option 1: Interactive
skill-seekers scrape --interactive

# Option 2: Copy and edit a preset
cp configs/react.json configs/myframework.json
nano configs/myframework.json
skill-seekers scrape --config configs/myframework.json

{
  "name": "myframework",
  "description": "When to use this skill",
  "base_url": "https://docs.myframework.com/",
  "selectors": {
    "main_content": "article",
    "title": "h1",
    "code_blocks": "pre code"
  },
  "url_patterns": {
    "include": ["/docs", "/guide"],
    "exclude": ["/blog", "/about"]
  },
  "categories": {
    "getting_started": ["intro", "quickstart"],
    "api": ["api", "reference"]
  },
  "rate_limit": 0.5,
  "max_pages": 500
}

The tool searches in this order:

1. Exact path as provided
2. ./configs/ (current directory)
3. ~/.config/skill-seekers/configs/ (user config directory)
4. SkillSeekersWeb.com API (preset configs)

output/
├── godot_data/              # Scraped raw data
│   ├── pages/              # JSON files (one per page)
│   └── summary.json        # Overview
│
└── godot/                   # The skill
    ├── SKILL.md            # Enhanced with real examples
    ├── references/         # Categorized docs
    │   ├── index.md
    │   ├── getting_started.md
    │   ├── scripting.md
    │   └── ...
    ├── scripts/            # Empty (add your own)
    └── assets/             # Empty (add your own)

• Check your main_content selector
• Try: article, main, div[role="main"]

# Force re-scrape
rm -rf output/myframework_data/
skill-seekers scrape --config configs/myframework.json

Edit the config categories section with better keywords.

# Delete old data and re-scrape
rm -rf output/godot_data/
skill-seekers scrape --config configs/godot.json

# Check if API key is set
echo $ANTHROPIC_API_KEY

# Try LOCAL mode instead (uses Claude Code Max, no API key needed)
skill-seekers enhance output/react/ --mode LOCAL

# Monitor background enhancement status
skill-seekers enhance-status output/react/ --watch

# Set a GitHub token (5000 req/hour vs 60/hour anonymous)
export GITHUB_TOKEN=ghp_your_token_here

# Or configure multiple profiles
skill-seekers config --github

• BULLETPROOF_QUICKSTART.md - 🎯 START HERE if you're new!
• QUICKSTART.md - Quick start for experienced users
• TROUBLESHOOTING.md - Common issues and solutions
• docs/QUICK_REFERENCE.md - One-page cheat sheet

• docs/LARGE_DOCUMENTATION.md - Handle 10K-40K+ page docs
• ASYNC_SUPPORT.md - Async mode guide (2-3x faster scraping)
• docs/ENHANCEMENT_MODES.md - AI enhancement modes guide
• docs/MCP_SETUP.md - MCP integration setup
• docs/UNIFIED_SCRAPING.md - Multi-source scraping

• docs/integrations/LANGCHAIN.md - LangChain RAG
• docs/integrations/CURSOR.md - Cursor IDE
• docs/integrations/WINDSURF.md - Windsurf IDE
• docs/integrations/CLINE.md - Cline (VS Code)
• docs/integrations/RAG_PIPELINES.md - All RAG pipelines

MIT License - see LICENSE file for details

Happy skill building! 🚀