Automatically convert documentation websites, GitHub repositories, and PDFs into Claude AI skills in minutes.

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

Skill Seeker is an automated tool that transforms documentation websites, GitHub repositories, and PDF files into production-ready Claude AI skills. Instead of manually reading and summarizing documentation, Skill Seeker:

1. Scrapes multiple sources (docs, GitHub repos, PDFs) automatically
2. Analyzes code repositories with deep AST parsing
3. Detects conflicts between documentation and code implementation
4. Organizes content into categorized reference files
5. Enhances with AI to extract best examples and key concepts
6. Packages everything into an uploadable .zip file for Claude

Result: Get comprehensive Claude skills for any framework, API, or tool in 20-40 minutes instead of hours of manual work.

• 🎯 For Developers: Create skills from documentation + GitHub repos with conflict detection
• 🎮 For Game Devs: Generate skills for game engines (Godot docs + GitHub, Unity, etc.)
• 🔧 For Teams: Combine internal docs + code repositories into single source of truth
• 📚 For Learners: Build comprehensive skills from docs, code examples, and PDFs
• 🔍 For Open Source: Analyze repos to find documentation gaps and outdated examples

• ✅ 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.
• ✅ 8 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

• ✅ AI-Powered Enhancement - Transforms basic templates into comprehensive guides
• ✅ No API Costs - FREE local enhancement using Claude Code Max
• ✅ MCP Server for Claude Code - Use directly from Claude Code with natural language

• ✅ 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 - 391 tests with comprehensive coverage

---

Skill Seekers is now published on the Python Package Index! Install with a single command:

pip install skill-seekers

Get started in seconds. No cloning, no setup - just install and run. See installation options below.

---

# Install from PyPI (easiest method!)
pip install skill-seekers

# Use the unified CLI
skill-seekers scrape --config configs/react.json
skill-seekers github --repo facebook/react
skill-seekers enhance output/react/
skill-seekers package output/react/

Time: ~25 minutes | Quality: Production-ready | Cost: Free

📖 New to Skill Seekers? Check out our Quick Start Guide or Bulletproof Guide

# Install with uv (fast, modern alternative)
uv tool install skill-seekers

# Or run directly without installing
uv tool run --from skill-seekers skill-seekers scrape --config https://raw.githubusercontent.com/yusufkaraaslan/Skill_Seekers/main/configs/react.json

# Unified CLI - simple commands
skill-seekers scrape --config configs/react.json
skill-seekers github --repo facebook/react
skill-seekers package output/react/

Time: ~25 minutes | Quality: Production-ready | Cost: Free

# Clone and install in editable mode
git clone https://github.com/yusufkaraaslan/Skill_Seekers.git
cd Skill_Seekers
pip install -e .

# Use the unified CLI
skill-seekers scrape --config configs/react.json

# One-time setup (5 minutes)
./setup_mcp.sh

# Then in Claude Code, just ask:
"Generate a React skill from https://react.dev/"
"Scrape PDF at docs/manual.pdf and create skill"

Time: Automated | Quality: Production-ready | Cost: Free

# Install dependencies
pip3 install requests beautifulsoup4

# Run scripts directly (old method)
python3 src/skill_seekers/cli/doc_scraper.py --config configs/react.json

# Upload output/react.zip to Claude - Done!

Time: ~25 minutes | Quality: Production-ready | Cost: Free

# 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

# Password-protected PDFs
skill-seekers pdf --pdf docs/encrypted.pdf --name myskill --password mypassword

Time: ~5-15 minutes (or 2-5 minutes with parallel) | Quality: Production-ready | Cost: Free

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

# Using a config file
skill-seekers github --config configs/react_github.json

# 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
    --include-releases        # Extract GitHub Releases

Time: ~5-10 minutes | Quality: Production-ready | Cost: Free

The Problem: Documentation and code often drift apart. Docs might be outdated, missing features that exist in code, or documenting features that were removed.

The Solution: Combine documentation + GitHub + PDF into one unified skill that shows BOTH what's documented AND what actually exists, with clear warnings about discrepancies.

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

# Or create unified config (mix documentation + GitHub)
cat > configs/myframework_unified.json << 'EOF'
{
  "name": "myframework",
  "description": "Complete framework knowledge from docs + code",
  "merge_mode": "rule-based",
  "sources": [
    {
      "type": "documentation",
      "base_url": "https://docs.myframework.com/",
      "extract_api": true,
      "max_pages": 200
    },
    {
      "type": "github",
      "repo": "owner/myframework",
      "include_code": true,
      "code_analysis_depth": "surface"
    }
  ]
}
EOF

# Run unified scraper
skill-seekers unified --config configs/myframework_unified.json

# Package and upload
skill-seekers package output/myframework/
# Upload output/myframework.zip to Claude - Done!

Time: ~30-45 minutes | Quality: Production-ready with conflict detection | Cost: Free

What Makes It Special:

✅ Conflict Detection - Automatically finds 4 types of discrepancies:

• 🔴 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

✅ Transparent Reporting - Shows both versions side-by-side:

#### `move_local_x(delta: float)`

⚠️ **Conflict**: Documentation signature differs from implementation

**Documentation says:**

def move_local_x(delta: float)

**Code implementation:**
```python
def move_local_x(delta: float, snap: bool = False) -> None

✅ **Advantages:**
- **Identifies documentation gaps** - Find outdated or missing docs automatically
- **Catches code changes** - Know when APIs change without docs being updated
- **Single source of truth** - One skill showing intent (docs) AND reality (code)
- **Actionable insights** - Get suggestions for fixing each conflict
- **Development aid** - See what's actually in the codebase vs what's documented

**Example Unified Configs:**
- `configs/react_unified.json` - React docs + GitHub repo
- `configs/django_unified.json` - Django docs + GitHub repo
- `configs/fastapi_unified.json` - FastAPI docs + GitHub repo

**Full Guide:** See [docs/UNIFIED_SCRAPING.md](docs/UNIFIED_SCRAPING.md) for complete documentation.

## How It Works

```mermaid
graph LR
    A[Documentation Website] --> B[Skill Seeker]
    B --> C[Scraper]
    B --> D[AI Enhancement]
    B --> E[Packager]
    C --> F[Organized References]
    D --> F
    F --> E
    E --> G[Claude Skill .zip]
    G --> H[Upload to Claude AI]

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 🎯

This guide walks you through EVERYTHING step-by-step (Python install, git clone, first skill creation).

---

Use Skill Seeker directly from Claude Code with natural language!

# Clone repository
git clone https://github.com/yusufkaraaslan/Skill_Seekers.git
cd Skill_Seekers

# One-time setup (5 minutes)
./setup_mcp.sh

# Restart Claude Code, then just ask:

In Claude Code:

List all available configs
Generate config for Tailwind at https://tailwindcss.com/docs
Scrape docs using configs/react.json
Package skill at output/react/

Benefits:

• ✅ No manual CLI commands
• ✅ Natural language interface
• ✅ Integrated with your workflow
• ✅ 9 tools available instantly (includes automatic upload!)
• ✅ Tested and working in production

Full guides:

• 📘 MCP Setup Guide - Complete installation instructions
• 🧪 MCP Testing Guide - Test all 9 tools
• 📦 Large Documentation Guide - Handle 10K-40K+ pages
• 📤 Upload Guide - How to upload skills to Claude

# Clone repository
git clone https://github.com/yusufkaraaslan/Skill_Seekers.git
cd Skill_Seekers

# Create virtual environment
python3 -m venv venv

# Activate virtual environment
source venv/bin/activate  # macOS/Linux
# OR on Windows: venv\Scripts\activate

# Install dependencies
pip install requests beautifulsoup4 pytest

# Save dependencies
pip freeze > requirements.txt

# Optional: Install anthropic for API-based enhancement (not needed for LOCAL enhancement)
# pip install anthropic

Always activate the virtual environment before using Skill Seeker:

source venv/bin/activate  # Run this each time you start a new terminal session

# Make sure venv is activated (you should see (venv) in your prompt)
source venv/bin/activate

# Optional: Estimate pages first (fast, 1-2 minutes)
skill-seekers estimate configs/godot.json

# Use Godot preset
skill-seekers scrape --config configs/godot.json

# Use React preset
skill-seekers scrape --config configs/react.json

# See all presets
ls configs/

skill-seekers scrape --interactive

skill-seekers scrape \
  --name react \
  --url https://react.dev/ \
  --description "React framework for UIs"

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

Benefits:

• ✅ Fully automatic
• ✅ No manual steps
• ✅ Works from command line

Requirements:

• Anthropic API key (get from https://console.anthropic.com/)

# Package skill
skill-seekers package output/react/

# This will:
# 1. Create output/react.zip
# 2. Open the output/ folder automatically
# 3. Show upload instructions

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

Benefits:

• ✅ No API key needed
• ✅ Works for everyone
• ✅ Folder opens automatically

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

# With API key set:
# - Packages the skill
# - Uploads to Claude automatically
# - Done! ✅

# Without API key:
# - Packages the skill
# - Shows where to find the .zip
# - Provides manual upload instructions

Benefits:

• ✅ Natural language
• ✅ Smart auto-detection (uploads if API key available)
• ✅ Works with or without API key
• ✅ No errors or failures

---

doc-to-skill/
├── cli/
│   ├── doc_scraper.py      # Main scraping tool
│   ├── package_skill.py    # Package to .zip
│   ├── upload_skill.py     # Auto-upload (API)
│   └── enhance_skill.py    # AI enhancement
├── mcp/                    # MCP server for Claude Code
│   └── server.py           # 9 MCP tools
├── configs/                # Preset configurations
│   ├── godot.json         # Godot Engine
│   ├── react.json         # React
│   ├── vue.json           # Vue.js
│   ├── django.json        # Django
│   └── fastapi.json       # FastAPI
└── output/                 # All output (auto-created)
    ├── godot_data/        # Scraped data
    ├── godot/             # Built skill
    └── godot.zip          # Packaged skill

skill-seekers estimate configs/react.json

# Output:
📊 ESTIMATION RESULTS
✅ Pages Discovered: 180
📈 Estimated Total: 230
⏱️  Time Elapsed: 1.2 minutes
💡 Recommended max_pages: 280

Benefits:

• Know page count BEFORE scraping (saves time)
• Validates URL patterns work correctly
• Estimates total scraping time
• Recommends optimal max_pages setting
• Fast (1-2 minutes vs 20-40 minutes full scrape)

skill-seekers scrape --config configs/godot.json

# If data exists:
✓ Found existing data: 245 pages
Use existing data? (y/n): y
⏭️  Skipping scrape, using existing data

Automatic pattern extraction:

• Extracts common code patterns from docs
• Detects programming language
• Creates quick reference with real examples
• Smarter categorization with scoring

Enhanced SKILL.md:

• Real code examples from documentation
• Language-annotated code blocks
• Common patterns section
• Quick reference from actual usage examples

Automatically infers categories from:

• URL structure
• Page titles
• Content keywords
• With scoring for better accuracy

# Automatically detects:
- Python (def, import, from)
- JavaScript (const, let, =>)
- GDScript (func, var, extends)
- C++ (#include, int main)
- And more...

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

# Later, just rebuild (instant)
skill-seekers scrape --config configs/react.json --skip-scrape

# Enable async mode with 8 workers (recommended for large docs)
skill-seekers scrape --config configs/react.json --async --workers 8

# Small docs (~100-500 pages)
skill-seekers scrape --config configs/mydocs.json --async --workers 4

# Large docs (2000+ pages) with no rate limiting
skill-seekers scrape --config configs/largedocs.json --async --workers 8 --no-rate-limit

Performance Comparison:

• Sync mode (threads): ~18 pages/sec, 120 MB memory
• Async mode: ~55 pages/sec, 40 MB memory
• Result: 3x faster, 66% less memory!

When to use:

• ✅ Large documentation (500+ pages)
• ✅ Network latency is high
• ✅ Memory is constrained
• ❌ Small docs (< 100 pages) - overhead not worth it

See full guide: ASYNC_SUPPORT.md

# Option 1: During scraping (API-based, requires API key)
pip3 install anthropic
export ANTHROPIC_API_KEY=sk-ant-...
skill-seekers scrape --config configs/react.json --enhance

# Option 2: During scraping (LOCAL, no API key - uses Claude Code Max)
skill-seekers scrape --config configs/react.json --enhance-local

# Option 3: After scraping (API-based, standalone)
skill-seekers enhance output/react/

# Option 4: After scraping (LOCAL, no API key, standalone)
skill-seekers enhance output/react/

What it does:

• Reads your reference documentation
• Uses Claude to generate an excellent SKILL.md
• Extracts best code examples (5-10 practical examples)
• Creates comprehensive quick reference
• Adds domain-specific key concepts
• Provides navigation guidance for different skill levels
• Automatically backs up original
• Quality: Transforms 75-line templates into 500+ line comprehensive guides

LOCAL Enhancement (Recommended):

• Uses your Claude Code Max plan (no API costs)
• Opens new terminal with Claude Code
• Analyzes reference files automatically
• Takes 30-60 seconds
• Quality: 9/10 (comparable to API version)

For massive documentation sites like Godot (40K pages), AWS, or Microsoft Docs:

# 1. Estimate first (discover page count)
skill-seekers estimate configs/godot.json

# 2. Auto-split into focused sub-skills
python3 -m skill_seekers.cli.split_config configs/godot.json --strategy router

# Creates:
# - godot-scripting.json (5K pages)
# - godot-2d.json (8K pages)
# - godot-3d.json (10K pages)
# - godot-physics.json (6K pages)
# - godot-shaders.json (11K pages)

# 3. Scrape all in parallel (4-8 hours instead of 20-40!)
for config in configs/godot-*.json; do
  skill-seekers scrape --config $config &
done
wait

# 4. Generate intelligent router/hub skill
python3 -m skill_seekers.cli.generate_router configs/godot-*.json

# 5. Package all skills
python3 -m skill_seekers.cli.package_multi output/godot*/

# 6. Upload all .zip files to Claude
# Users just ask questions naturally!
# Router automatically directs to the right sub-skill!

Split Strategies:

• auto - Intelligently detects best strategy based on page count
• category - Split by documentation categories (scripting, 2d, 3d, etc.)
• router - Create hub skill + specialized sub-skills (RECOMMENDED)
• size - Split every N pages (for docs without clear categories)

Benefits:

• ✅ Faster scraping (parallel execution)
• ✅ More focused skills (better Claude performance)
• ✅ Easier maintenance (update one topic at a time)
• ✅ Natural user experience (router handles routing)
• ✅ Avoids context window limits

Configuration:

{
  "name": "godot",
  "max_pages": 40000,
  "split_strategy": "router",
  "split_config": {
    "target_pages_per_skill": 5000,
    "create_router": true,
    "split_by_categories": ["scripting", "2d", "3d", "physics"]
  }
}

Full Guide: Large Documentation Guide

Never lose progress on long-running scrapes:

# Enable in config
{
  "checkpoint": {
    "enabled": true,
    "interval": 1000  // Save every 1000 pages
  }
}

# If scrape is interrupted (Ctrl+C or crash)
skill-seekers scrape --config configs/godot.json --resume

# Resume from last checkpoint
✅ Resuming from checkpoint (12,450 pages scraped)
⏭️  Skipping 12,450 already-scraped pages
🔄 Continuing from where we left off...

# Start fresh (clear checkpoint)
skill-seekers scrape --config configs/godot.json --fresh

Benefits:

• ✅ Auto-saves every 1000 pages (configurable)
• ✅ Saves on interruption (Ctrl+C)
• ✅ Resume with --resume flag
• ✅ Never lose hours of scraping progress

# 1. Scrape + Build + AI Enhancement (LOCAL, no API key)
skill-seekers scrape --config configs/godot.json --enhance-local

# 2. Wait for new terminal to close (enhancement completes)
# Check the enhanced SKILL.md:
cat output/godot/SKILL.md

# 3. Package
skill-seekers package output/godot/

# 4. Done! You have godot.zip with excellent SKILL.md

Time: 20-40 minutes (scraping) + 60 seconds (enhancement) = ~21-41 minutes

# 1. Use cached data + Local Enhancement
skill-seekers scrape --config configs/godot.json --skip-scrape
skill-seekers enhance output/godot/

# 2. Package
skill-seekers package output/godot/

# 3. Done!

Time: 1-3 minutes (build) + 60 seconds (enhancement) = ~2-4 minutes total

# 1. Scrape + Build (no enhancement)
skill-seekers scrape --config configs/godot.json

# 2. Package
skill-seekers package output/godot/

# 3. Done! (SKILL.md will be basic template)

Time: 20-40 minutes Note: SKILL.md will be generic - enhancement strongly recommended!

Config	Framework	Description
godot.json	Godot Engine	Game development
react.json	React	UI framework
vue.json	Vue.js	Progressive framework
django.json	Django	Python web framework
fastapi.json	FastAPI	Modern Python API
ansible-core.json	Ansible Core 2.19	Automation & configuration

# Godot
skill-seekers scrape --config configs/godot.json

# React
skill-seekers scrape --config configs/react.json

# Vue
skill-seekers scrape --config configs/vue.json

# Django
skill-seekers scrape --config configs/django.json

# FastAPI
skill-seekers scrape --config configs/fastapi.json

# Ansible
skill-seekers scrape --config configs/ansible-core.json

skill-seekers scrape --interactive
# Follow prompts, it will create the config for you

# Copy a preset
cp configs/react.json configs/myframework.json

# Edit it
nano configs/myframework.json

# Use it
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
}

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)

# Interactive mode
skill-seekers scrape --interactive

# Use config file
skill-seekers scrape --config configs/godot.json

# Quick mode
skill-seekers scrape --name react --url https://react.dev/

# Skip scraping (use existing data)
skill-seekers scrape --config configs/godot.json --skip-scrape

# With description
skill-seekers scrape \
  --name react \
  --url https://react.dev/ \
  --description "React framework for building UIs"

Edit max_pages in config to test:

{
  "max_pages": 20  // Test with just 20 pages
}

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

# Rebuild multiple times (instant)
skill-seekers scrape --config configs/react.json --skip-scrape
skill-seekers scrape --config configs/react.json --skip-scrape

# Test in Python
from bs4 import BeautifulSoup
import requests

url = "https://docs.example.com/page"
soup = BeautifulSoup(requests.get(url).content, 'html.parser')

# Try different selectors
print(soup.select_one('article'))
print(soup.select_one('main'))
print(soup.select_one('div[role="main"]'))

# After building, check:
cat output/godot/SKILL.md  # Should have real examples
cat output/godot/references/index.md  # Categories

• 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
rm -rf output/godot_data/

# Re-scrape
skill-seekers scrape --config configs/godot.json

Task	Time	Notes
Scraping (sync)	15-45 min	First time only, thread-based
Scraping (async)	5-15 min	2-3x faster with --async flag
Building	1-3 min	Fast!
Re-building	<1 min	With --skip-scrape
Packaging	5-10 sec	Final zip

One tool does everything:

1. ✅ Scrapes documentation
2. ✅ Auto-detects existing data
3. ✅ Generates better knowledge
4. ✅ Creates enhanced skills
5. ✅ Works with presets or custom configs
6. ✅ Supports skip-scraping for fast iteration

Simple structure:

• doc_scraper.py - The tool
• configs/ - Presets
• output/ - Everything else

Better output:

• Real code examples with language detection
• Common patterns extracted from docs
• Smart categorization
• Enhanced SKILL.md with actual examples

• BULLETPROOF_QUICKSTART.md - 🎯 START HERE if you're new!
• QUICKSTART.md - Quick start for experienced users
• TROUBLESHOOTING.md - Common issues and solutions

• docs/LARGE_DOCUMENTATION.md - Handle 10K-40K+ page docs
• ASYNC_SUPPORT.md - Async mode guide (2-3x faster scraping)
• docs/ENHANCEMENT.md - AI enhancement guide
• docs/TERMINAL_SELECTION.md - Configure terminal app for local enhancement
• docs/UPLOAD_GUIDE.md - How to upload skills to Claude
• docs/MCP_SETUP.md - MCP integration setup

• docs/CLAUDE.md - Technical architecture
• STRUCTURE.md - Repository structure

# Try Godot
skill-seekers scrape --config configs/godot.json

# Try React
skill-seekers scrape --config configs/react.json

# Or go interactive
skill-seekers scrape --interactive

MIT License - see LICENSE file for details

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Happy skill building! 🚀