CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

🎯 Current Status (November 30, 2025)

Version: v2.1.1 (Production Ready - GitHub Analysis Enhanced!) Active Development: Flexible, incremental task-based approach

Recent Updates (November 2025):

🎉 MAJOR MILESTONE: Published on PyPI! (v2.0.0)

📦 PyPI Publication: Install with pip install skill-seekers - https://pypi.org/project/skill-seekers/
🔧 Modern Python Packaging: pyproject.toml, src/ layout, entry points
✅ CI/CD Fixed: All 5 test matrix jobs passing (Ubuntu + macOS, Python 3.10-3.12)
📚 Documentation Complete: README, CHANGELOG, FUTURE_RELEASES.md all updated
🚀 Unified CLI: Single skill-seekers command with Git-style subcommands
🧪 Test Coverage: 427 tests passing (up from 391), 39% coverage
🌐 Community: GitHub Discussion, Release notes, announcements published

🚀 Unified Multi-Source Scraping (v2.0.0)

NEW: Combine documentation + GitHub + PDF in one skill
NEW: Automatic conflict detection between docs and code
NEW: Rule-based and AI-powered merging
NEW: 5 example unified configs (React, Django, FastAPI, Godot, FastAPI-test)
Status: ✅ All 22 unified tests passing (18 core + 4 MCP integration)

✅ Community Response (H1 Group):

Issue #8 Fixed - Added BULLETPROOF_QUICKSTART.md and TROUBLESHOOTING.md for beginners
Issue #7 Fixed - Fixed all 11 configs (Django, Laravel, Astro, Tailwind) - 100% working
Issue #4 Linked - Connected to roadmap Tasks A2/A3 (knowledge sharing + website)
PR #5 Reviewed - Approved anchor stripping feature (security verified, 32/32 tests pass)
MCP Setup Fixed - Path expansion bug resolved in setup_mcp.sh

📦 Configs Status:

✅ 24 total configs available (including unified configs)
✅ 5 unified configs added (React, Django, FastAPI, Godot, FastAPI-test)
✅ Core selectors tested and validated
📝 Single-source configs: ansible-core, astro, claude-code, django, fastapi, godot, godot-large-example, hono, kubernetes, laravel, react, steam-economy-complete, tailwind, vue
📝 Multi-source configs: django_unified, fastapi_unified, fastapi_unified_test, godot_unified, react_unified
📝 Test/Example configs: godot_github, react_github, python-tutorial-test, example_pdf, test-manual

📋 Completed (November 29, 2025):

✅ DONE: PyPI publication complete (v2.0.0)
✅ DONE: CI/CD fixed - all checks passing
✅ DONE: Documentation updated (README, CHANGELOG, FUTURE_RELEASES.md)
✅ DONE: Quality Assurance + Race Condition Fixes (v2.1.0)
✅ DONE: All critical bugs fixed (Issues #190, #192, #193)
✅ DONE: Test suite stabilized (427 tests passing)
✅ DONE: Unified tests fixed (all 22 passing)
✅ DONE: PR #195 merged - Unlimited local repository analysis
✅ DONE: PR #198 merged - Skip llms.txt config option
✅ DONE: Issue #203 - Configurable EXCLUDED_DIRS (19 tests, 2 commits)

📋 Next Up (Post-v2.1.0):

Priority 1: Review open PRs (#187, #186)
Priority 2: Issue #202 - Add warning for missing local_repo_path
Priority 3: Task H1.3 - Create example project folder
Priority 4: Task A3.1 - GitHub Pages site (skillseekersweb.com)

📊 Roadmap Progress:

134 tasks organized into 22 feature groups
Project board: https://github.com/users/yusufkaraaslan/projects/2
See FLEXIBLE_ROADMAP.md for complete task list

🔌 MCP Integration Available

This repository includes a fully tested MCP server with 9 tools:

mcp__skill-seeker__list_configs - List all available preset configurations
mcp__skill-seeker__generate_config - Generate a new config file for any docs site
mcp__skill-seeker__validate_config - Validate a config file structure
mcp__skill-seeker__estimate_pages - Estimate page count before scraping
mcp__skill-seeker__scrape_docs - Scrape and build a skill
mcp__skill-seeker__package_skill - Package skill into .zip file (with auto-upload)
mcp__skill-seeker__upload_skill - Upload .zip to Claude (NEW)
mcp__skill-seeker__split_config - Split large documentation configs
mcp__skill-seeker__generate_router - Generate router/hub skills

Setup: See docs/MCP_SETUP.md or run ./setup_mcp.sh

Status: ✅ Tested and working in production with Claude Code

Overview

Skill Seeker automatically converts any documentation website into a Claude AI skill. It scrapes documentation, organizes content, extracts code patterns, and packages everything into an uploadable .zip file for Claude.

Prerequisites

Python Version: Python 3.10 or higher (required for MCP integration)

Installation:

Option 1: Install from PyPI (Recommended - Easiest!)

# Install globally or in virtual environment
pip install skill-seekers

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

Option 2: Install from Source (For Development)

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

# Create virtual environment
python3 -m venv venv
source venv/bin/activate  # macOS/Linux (Windows: venv\Scripts\activate)

# Install in editable mode
pip install -e .

# Or install dependencies manually
pip install -r requirements.txt

Why use a virtual environment?

Keeps dependencies isolated from system Python
Prevents package version conflicts
Standard Python development practice
Required for running tests with pytest

Optional (for API-based enhancement):

pip install anthropic
export ANTHROPIC_API_KEY=sk-ant-...

Core Commands

Quick Start - Use a Preset

# Single-source scraping (documentation only)
skill-seekers scrape --config configs/godot.json
skill-seekers scrape --config configs/react.json
skill-seekers scrape --config configs/vue.json
skill-seekers scrape --config configs/django.json
skill-seekers scrape --config configs/laravel.json
skill-seekers scrape --config configs/fastapi.json

Unified Multi-Source Scraping (NEW - v2.0.0)

# Combine documentation + GitHub + PDF in one skill
skill-seekers unified --config configs/react_unified.json
skill-seekers unified --config configs/django_unified.json
skill-seekers unified --config configs/fastapi_unified.json
skill-seekers unified --config configs/godot_unified.json

# Override merge mode
skill-seekers unified --config configs/react_unified.json --merge-mode claude-enhanced

# Result: One comprehensive skill with conflict detection

What makes it special:

✅ Detects discrepancies between documentation and code
✅ Shows both versions side-by-side with ⚠️ warnings
✅ Identifies outdated docs and undocumented features
✅ Single source of truth showing intent (docs) AND reality (code)

See full guide: docs/UNIFIED_SCRAPING.md

First-Time User Workflow (Recommended)

# 1. Install from PyPI (one-time, easiest!)
pip install skill-seekers

# 2. Estimate page count BEFORE scraping (fast, no data download)
skill-seekers estimate configs/godot.json
# Time: ~1-2 minutes, shows estimated total pages and recommended max_pages

# 3. Scrape with local enhancement (uses Claude Code Max, no API key)
skill-seekers scrape --config configs/godot.json --enhance-local
# Time: 20-40 minutes scraping + 60 seconds enhancement

# 4. Package the skill
skill-seekers package output/godot/

# Result: godot.zip ready to upload to Claude

Interactive Mode

# Step-by-step configuration wizard
skill-seekers scrape --interactive

Quick Mode (Minimal Config)

# Create skill from any documentation URL
skill-seekers scrape --name react --url https://react.dev/ --description "React framework for UIs"

Skip Scraping (Use Cached Data)

# Fast rebuild using previously scraped data
skill-seekers scrape --config configs/godot.json --skip-scrape
# Time: 1-3 minutes (instant rebuild)

Async Mode (2-3x Faster Scraping)

# Enable async mode with 8 workers for best performance
skill-seekers scrape --config configs/react.json --async --workers 8

# Quick mode with async
skill-seekers scrape --name react --url https://react.dev/ --async --workers 8

# Dry run with async to test
skill-seekers scrape --config configs/godot.json --async --workers 4 --dry-run

Recommended Settings:

Small docs (~100-500 pages): --async --workers 4
Medium docs (~500-2000 pages): --async --workers 8
Large docs (2000+ pages): --async --workers 8 --no-rate-limit

Performance:

Sync: ~18 pages/sec, 120 MB memory
Async: ~55 pages/sec, 40 MB memory (3x faster!)

See full guide: ASYNC_SUPPORT.md

Enhancement Options

LOCAL Enhancement (Recommended - No API Key Required):

# During scraping
skill-seekers scrape --config configs/react.json --enhance-local

# Standalone after scraping
skill-seekers enhance output/react/

API Enhancement (Alternative - Requires API Key):

# During scraping
skill-seekers scrape --config configs/react.json --enhance

# Standalone after scraping
skill-seekers-enhance output/react/
skill-seekers-enhance output/react/ --api-key sk-ant-...

Package and Upload the Skill

# Package skill (opens folder, shows upload instructions)
skill-seekers package output/godot/
# Result: output/godot.zip

# Package and auto-upload (requires ANTHROPIC_API_KEY)
export ANTHROPIC_API_KEY=sk-ant-...
skill-seekers package output/godot/ --upload

# Upload existing .zip
skill-seekers upload output/godot.zip

# Package without opening folder
skill-seekers package output/godot/ --no-open

Force Re-scrape

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

Estimate Page Count (Before Scraping)

# Quick estimation - discover up to 100 pages
skill-seekers estimate configs/react.json --max-discovery 100
# Time: ~30-60 seconds

# Full estimation - discover up to 1000 pages (default)
skill-seekers estimate configs/godot.json
# Time: ~1-2 minutes

# Deep estimation - discover up to 2000 pages
skill-seekers estimate configs/vue.json --max-discovery 2000
# Time: ~3-5 minutes

# What it shows:
# - Estimated total pages
# - Recommended max_pages value
# - Estimated scraping time
# - Discovery rate (pages/sec)

Why use estimation:

Validates config URL patterns before full scrape
Helps set optimal max_pages value
Estimates total scraping time
Fast (only HEAD requests + minimal parsing)
No data downloaded or stored

Repository Architecture

File Structure (v2.0.0 - Modern Python Packaging)

Skill_Seekers/
├── pyproject.toml              # Modern Python package configuration (PEP 621)
├── src/                        # Source code (src/ layout best practice)
│   └── skill_seekers/
│       ├── __init__.py
│       ├── cli/                # CLI tools (entry points)
│       │   ├── doc_scraper.py      # Main scraper (~790 lines)
│       │   ├── estimate_pages.py   # Page count estimator
│       │   ├── enhance_skill.py    # AI enhancement (API-based)
│       │   ├── package_skill.py    # Skill packager
│       │   ├── github_scraper.py   # GitHub scraper
│       │   ├── pdf_scraper.py      # PDF scraper
│       │   ├── unified_scraper.py  # Unified multi-source scraper
│       │   ├── merge_sources.py    # Source merger
│       │   └── conflict_detector.py # Conflict detection
│       └── mcp/                # MCP server integration
│           └── server.py
├── tests/                      # Test suite (391 tests passing)
│   ├── test_scraper_features.py
│   ├── test_config_validation.py
│   ├── test_integration.py
│   ├── test_mcp_server.py
│   ├── test_unified.py         # Unified scraping tests (18 tests)
│   ├── test_unified_mcp_integration.py  # (4 tests)
│   └── ...
├── configs/                    # Preset configurations (24 configs)
│   ├── godot.json
│   ├── react.json
│   ├── django_unified.json     # Multi-source configs
│   └── ...
├── docs/                       # Documentation
│   ├── CLAUDE.md               # This file
│   ├── ENHANCEMENT.md          # Enhancement guide
│   ├── UPLOAD_GUIDE.md         # Upload instructions
│   └── UNIFIED_SCRAPING.md     # Unified scraping guide
├── README.md                   # User documentation
├── CHANGELOG.md                # Release history
├── FUTURE_RELEASES.md          # Roadmap
└── output/                     # Generated output (git-ignored)
    ├── {name}_data/            # Scraped raw data (cached)
    │   ├── pages/*.json        # Individual page data
    │   └── summary.json        # Scraping summary
    └── {name}/                 # Built skill directory
        ├── SKILL.md            # Main skill file
        ├── SKILL.md.backup     # Backup (if enhanced)
        ├── references/         # Categorized documentation
        │   ├── index.md
        │   ├── getting_started.md
        │   ├── api.md
        │   └── ...
        ├── scripts/            # Empty (user scripts)
        └── assets/             # Empty (user assets)

Key Changes in v2.0.0:

src/ layout: Modern Python packaging structure
pyproject.toml: PEP 621 compliant configuration
Entry points: skill-seekers CLI with subcommands
Published to PyPI: pip install skill-seekers

Data Flow

Scrape Phase (scrape_all() in src/skill_seekers/cli/doc_scraper.py):
- Input: Config JSON (name, base_url, selectors, url_patterns, categories)
- Process: BFS traversal from base_url, respecting include/exclude patterns
- Output: output/{name}_data/pages/*.json + summary.json
Build Phase (build_skill() in src/skill_seekers/cli/doc_scraper.py):
- Input: Scraped JSON data from output/{name}_data/
- Process: Load pages → Smart categorize → Extract patterns → Generate references
- Output: output/{name}/SKILL.md + output/{name}/references/*.md
Enhancement Phase (optional via enhance_skill.py or enhance_skill_local.py):
- Input: Built skill directory with references
- Process: Claude analyzes references and rewrites SKILL.md
- Output: Enhanced SKILL.md with real examples and guidance
Package Phase (via package_skill.py):
- Input: Skill directory
- Process: Zip all files (excluding .backup)
- Output: {name}.zip
Upload Phase (optional via upload_skill.py):
- Input: Skill .zip file
- Process: Upload to Claude AI via API
- Output: Skill available in Claude

Configuration File Structure

Config files (configs/*.json) define scraping behavior:

{
  "name": "godot",
  "description": "When to use this skill",
  "base_url": "https://docs.godotengine.org/en/stable/",
  "selectors": {
    "main_content": "div[role='main']",
    "title": "title",
    "code_blocks": "pre"
  },
  "url_patterns": {
    "include": [],
    "exclude": ["/search.html", "/_static/"]
  },
  "categories": {
    "getting_started": ["introduction", "getting_started"],
    "scripting": ["scripting", "gdscript"],
    "api": ["api", "reference", "class"]
  },
  "rate_limit": 0.5,
  "max_pages": 500
}

Config Parameters:

name: Skill identifier (output directory name)
description: When Claude should use this skill
base_url: Starting URL for scraping
selectors.main_content: CSS selector for main content (common: article, main, div[role="main"])
selectors.title: CSS selector for page title
selectors.code_blocks: CSS selector for code samples
url_patterns.include: Only scrape URLs containing these patterns
url_patterns.exclude: Skip URLs containing these patterns
categories: Keyword mapping for categorization
rate_limit: Delay between requests (seconds)
max_pages: Maximum pages to scrape
skip_llms_txt: Skip llms.txt detection, force HTML scraping (default: false)
exclude_dirs_additional: Add custom directories to default exclusions (for local repo analysis)
exclude_dirs: Replace default directory exclusions entirely (advanced, for local repo analysis)

Key Features & Implementation

Auto-Detect Existing Data

Tool checks for output/{name}_data/ and prompts to reuse, avoiding re-scraping (check_existing_data() in doc_scraper.py:653-660).

Configurable Directory Exclusions (Local Repository Analysis)

When using local_repo_path for unlimited local repository analysis, you can customize which directories to exclude from analysis.

Smart Defaults: Automatically excludes common directories: venv, node_modules, __pycache__, .git, build, dist, .pytest_cache, htmlcov, .tox, .mypy_cache, etc.

Extend Mode (exclude_dirs_additional): Add custom exclusions to defaults

{
  "sources": [{
    "type": "github",
    "local_repo_path": "/path/to/repo",
    "exclude_dirs_additional": ["proprietary", "legacy", "third_party"]
  }]
}

Replace Mode (exclude_dirs): Override defaults entirely (advanced)

{
  "sources": [{
    "type": "github",
    "local_repo_path": "/path/to/repo",
    "exclude_dirs": ["node_modules", ".git", "custom_vendor"]
  }]
}

Use Cases:

Monorepos with custom directory structures
Enterprise projects with non-standard naming
Including unusual directories (e.g., analyzing venv code)
Minimal exclusions for small/simple projects

See: should_exclude_dir() in github_scraper.py:304-306

Language Detection

Detects code languages from:

CSS class attributes (language-*, lang-*)
Heuristics (keywords like def, const, func, etc.)

See: detect_language() in doc_scraper.py:135-165

Pattern Extraction

Looks for "Example:", "Pattern:", "Usage:" markers in content and extracts following code blocks (up to 5 per page).

See: extract_patterns() in doc_scraper.py:167-183

Smart Categorization

Scores pages against category keywords (3 points for URL match, 2 for title, 1 for content)
Threshold of 2+ for categorization
Auto-infers categories from URL segments if none provided
Falls back to "other" category

See: smart_categorize() and infer_categories() in doc_scraper.py:282-351

Enhanced SKILL.md Generation

Generated with:

Real code examples from documentation (language-annotated)
Quick reference patterns extracted from docs
Common pattern section
Category file listings

See: create_enhanced_skill_md() in doc_scraper.py:426-542

Common Workflows

First Time (With Scraping + Enhancement)

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

# 2. Wait for enhancement terminal to close (~60 seconds)

# 3. Verify quality
cat output/godot/SKILL.md

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

# Result: godot.zip ready for Claude
# Time: 20-40 minutes (scraping) + 60 seconds (enhancement)

Using Cached Data (Fast Iteration)

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

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

# Time: 1-3 minutes (build) + 60 seconds (enhancement)

Without Enhancement (Basic)

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

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

# Note: SKILL.md will be basic template - enhancement recommended
# Time: 20-40 minutes

Creating a New Framework Config

Option 1: Interactive

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

Option 2: Copy and Modify

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

# Edit it
nano configs/myframework.json

# Test with limited pages first
# Set "max_pages": 20 in config

# Use it
skill-seekers scrape --config configs/myframework.json

Testing & Verification

Finding the Right CSS Selectors

Before creating a config, test selectors with BeautifulSoup:

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"]'))
print(soup.select_one('div.content'))

# Test code block selector
print(soup.select('pre code'))
print(soup.select('pre'))

Verify Output Quality

After building, verify the skill quality:

# Check SKILL.md has real examples
cat output/godot/SKILL.md

# Check category structure
cat output/godot/references/index.md

# List all reference files
ls output/godot/references/

# Check specific category content
cat output/godot/references/getting_started.md

# Verify code samples have language detection
grep -A 3 "```" output/godot/references/*.md | head -20

Test with Limited Pages

For faster testing, edit config to limit pages:

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

Troubleshooting

No Content Extracted

Problem: Pages scraped but content is empty

Solution: Check main_content selector in config. Try:

article
main
div[role="main"]
div.content

Use the BeautifulSoup testing approach above to find the right selector.

Poor Categorization

Problem: Pages not categorized well

Solution: Edit categories section in config with better keywords specific to the documentation structure. Check URL patterns in scraped data:

# See what URLs were scraped
cat output/godot_data/summary.json | grep url | head -20

Data Exists But Won't Use It

Problem: Tool won't reuse existing data

Solution: Force re-scrape:

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

Rate Limiting Issues

Problem: Getting rate limited or blocked by documentation server

Solution: Increase rate_limit value in config:

{
  "rate_limit": 1.0  // Change from 0.5 to 1.0 seconds
}

Package Path Error

Problem: doc_scraper.py shows wrong cli/package_skill.py path

Expected output:

skill-seekers package output/godot/

Not:

python3 /mnt/skills/examples/skill-creator/scripts/cli/package_skill.py output/godot/

The correct command uses the local cli/package_skill.py in the repository root.

Key Code Locations (v2.0.0)

Documentation Scraper (src/skill_seekers/cli/doc_scraper.py):

URL validation: is_valid_url()
Content extraction: extract_content()
Language detection: detect_language()
Pattern extraction: extract_patterns()
Smart categorization: smart_categorize()
Category inference: infer_categories()
Quick reference generation: generate_quick_reference()
SKILL.md generation: create_enhanced_skill_md()
Scraping loop: scrape_all()
Main workflow: main()

Other Key Files:

GitHub scraper: src/skill_seekers/cli/github_scraper.py
PDF scraper: src/skill_seekers/cli/pdf_scraper.py
Unified scraper: src/skill_seekers/cli/unified_scraper.py
Conflict detection: src/skill_seekers/cli/conflict_detector.py
Source merger: src/skill_seekers/cli/merge_sources.py
Package tool: src/skill_seekers/cli/package_skill.py
Upload tool: src/skill_seekers/cli/upload_skill.py
MCP server: src/skill_seekers/mcp/server.py
Entry points: pyproject.toml (project.scripts section)

Enhancement Details

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)
Backs up original SKILL.md to SKILL.md.backup

API Enhancement (Alternative)

Uses Anthropic API (~$0.15-$0.30 per skill)
Requires ANTHROPIC_API_KEY
Same quality as LOCAL
Faster (no terminal launch)
Better for automation/CI

What Enhancement Does:

Reads reference documentation files
Analyzes content with Claude
Extracts 5-10 best code examples
Creates comprehensive quick reference
Adds domain-specific key concepts
Provides navigation guidance for different skill levels
Transforms 75-line templates into 500+ line comprehensive guides

Performance

Task	Time	Notes
Scraping	15-45 min	First time only
Building	1-3 min	Fast!
Re-building	<1 min	With --skip-scrape
Enhancement (LOCAL)	30-60 sec	Uses Claude Code Max
Enhancement (API)	20-40 sec	Requires API key
Packaging	5-10 sec	Final zip

Available Configs (24 Total)

Single-Source Documentation Configs (14 configs)

Web Frameworks:

✅ react.json - React (article selector, 7,102 chars)
✅ vue.json - Vue.js (main selector, 1,029 chars)
✅ astro.json - Astro (article selector, 145 chars)
✅ django.json - Django (article selector, 6,468 chars)
✅ laravel.json - Laravel 9.x (#main-content selector, 16,131 chars)
✅ fastapi.json - FastAPI (article selector, 11,906 chars)
✅ hono.json - Hono web framework NEW!

DevOps & Automation:

✅ ansible-core.json - Ansible Core 2.19 (div[role='main'] selector, ~32K chars)
✅ kubernetes.json - Kubernetes (main selector, 2,100 chars)

Game Engines:

✅ godot.json - Godot (div[role='main'] selector, 1,688 chars)
✅ godot-large-example.json - Godot large docs example

CSS & Utilities:

✅ tailwind.json - Tailwind CSS (div.prose selector, 195 chars)

Gaming:

✅ steam-economy-complete.json - Steam Economy (div.documentation_bbcode, 588 chars)

Development Tools:

✅ claude-code.json - Claude Code documentation NEW!

Unified Multi-Source Configs (5 configs - NEW v2.0!)

✅ react_unified.json - React (docs + GitHub + code analysis)
✅ django_unified.json - Django (docs + GitHub + code analysis)
✅ fastapi_unified.json - FastAPI (docs + GitHub + code analysis)
✅ fastapi_unified_test.json - FastAPI test config
✅ godot_unified.json - Godot (docs + GitHub + code analysis)

Test/Example Configs (5 configs)

📝 godot_github.json - GitHub-only scraping example
📝 react_github.json - GitHub-only scraping example
📝 python-tutorial-test.json - Python tutorial test
📝 example_pdf.json - PDF extraction example
📝 test-manual.json - Manual testing config

Note: All configs verified and working! Unified configs fully tested with 22 passing tests. Last verified: November 29, 2025 (Post-v2.1.0 bug fixes)

Additional Documentation

User Guides:

README.md - Complete user documentation
BULLETPROOF_QUICKSTART.md - Complete beginner guide
QUICKSTART.md - Get started in 3 steps
TROUBLESHOOTING.md - Comprehensive troubleshooting

Technical Documentation:

docs/CLAUDE.md - Detailed technical architecture
docs/ENHANCEMENT.md - AI enhancement guide
docs/UPLOAD_GUIDE.md - How to upload skills to Claude
docs/UNIFIED_SCRAPING.md - Multi-source scraping guide
docs/MCP_SETUP.md - MCP server setup

Project Planning:

CHANGELOG.md - Release history and v2.0.0 details UPDATED!
FUTURE_RELEASES.md - Roadmap for v2.1.0+ NEW!
FLEXIBLE_ROADMAP.md - Complete task catalog (134 tasks)
NEXT_TASKS.md - What to work on next
TODO.md - Current focus
STRUCTURE.md - Repository structure

Notes for Claude Code

Project Status (v2.0.0):

✅ Published on PyPI: Install with pip install skill-seekers
✅ Modern Python Packaging: pyproject.toml, src/ layout, entry points
✅ Unified CLI: Single skill-seekers command with Git-style subcommands
✅ CI/CD Working: All 5 test matrix jobs passing (Ubuntu + macOS, Python 3.10-3.12)
✅ Test Coverage: 391 tests passing, 39% coverage
✅ Documentation: Complete user and technical documentation

Architecture:

Python-based documentation scraper with multi-source support
Main scraper: src/skill_seekers/cli/doc_scraper.py (~790 lines)
Unified scraping: Combines docs + GitHub + PDF with conflict detection
Modern packaging: PEP 621 compliant with proper dependency management
MCP Integration: 9 tools for Claude Code Max integration

Development Workflow:

Install: pip install -e . (editable mode for development)
Run tests: pytest tests/ (391 tests)
Build package: uv build or python -m build
Publish: uv publish (PyPI)

Key Points:

Output is cached and reusable in output/ (git-ignored)
Enhancement is optional but highly recommended
All 24 configs are working and tested
CI workflow requires pip install -e . to install package before running tests

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