skill-seekers 3.8.0

🧠 The data layer for AI systems. Skill Seekers turns documentation sites, GitHub repos, PDFs, videos, notebooks, wikis, and 10+ more source types 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!

🌐 Ecosystem

Skill Seekers is a multi-repo project. Here's where everything lives:

Repository	Description	Links
Skill_Seekers	Core CLI & MCP server (this repo)	PyPI
skillseekersweb	Website & documentation	Live
skill-seekers-configs	Community config repository
skill-seekers-action	GitHub Action for CI/CD
skill-seekers-plugin	Claude Code plugin
homebrew-skill-seekers	Homebrew tap for macOS

Want to contribute? The website and configs repos are great starting points for new contributors!

🧠 The Data Layer for AI Systems

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-seekerscreatehttps://docs.react.dev/
# or: skill-seekers create facebook/react
# or: skill-seekers create ./my-project

# Export to any AI system
skill-seekerspackageoutput/react--targetclaude# → Claude AI Skill (ZIP)
skill-seekerspackageoutput/react--targetlangchain# → LangChain Documents
skill-seekerspackageoutput/react--targetllama-index# → LlamaIndex TextNodes
skill-seekerspackageoutput/react--targetcursor# → .cursorrules
skill-seekerspackageoutput/react--targetibm-bob# → IBM Bob skill directory

What gets built

Output	Target	What it powers
Claude Skill (ZIP + YAML)	`--target claude`	Claude Code, Claude API
Gemini Skill (tar.gz)	`--target gemini`	Google Gemini
OpenAI / Custom GPT (ZIP)	`--target openai`	GPT-4o, custom assistants
LangChain Documents	`--target langchain`	QA chains, agents, retrievers
LlamaIndex TextNodes	`--target llama-index`	Query engines, chat engines
Haystack Documents	`--target haystack`	Enterprise RAG pipelines
Pinecone-ready (Markdown)	`--target markdown`	Vector upsert
ChromaDB / FAISS / Qdrant	`--target chroma/faiss/qdrant`	Local vector DBs
IBM Bob Skill (directory)	`--target ibm-bob`	IBM Bob project/global skills
Cursor `.cursorrules`	`--target markdown` → copy SKILL.md	Cursor IDE `.cursorrules`
Windsurf / Cline / Continue	`--target claude` → copy	VS Code, IntelliJ, Vim

Why it matters

⚡ 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
🎬 Videos — Extract code, transcripts, and structured knowledge from YouTube and local videos
🔄 Multi-source — Combine 18 source types (docs, GitHub, PDFs, videos, notebooks, wikis, and more) into one knowledge asset
🌐 One prep, every target — Export the same asset to 21 platforms without re-scraping
✅ Battle-tested — 3,700+ tests, 24+ framework presets, production-ready

🚀 Quick Start (3 Commands)

# 1. Install
pipinstallskill-seekers

# 2. Create skill from any source
skill-seekerscreatehttps://docs.django.com/

# 3. Package for your AI platform
skill-seekerspackageoutput/django--targetclaude

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

# Use a different AI agent for enhancement (default: claude)
skill-seekerscreatehttps://docs.django.com/--agentkimi
skill-seekerscreatehttps://docs.django.com/--agentcodex
skill-seekerscreatehttps://docs.django.com/--agent-cmd"my-custom-agent run"

🛰️ AI-driven project scan (new)

Point scan at any project and an AI agent reads its manifests, README, Dockerfile/CI and sampled source imports — then emits one config per detected framework plus a <project>-codebase.json for your own code. Pins the detected version so re-running reports bumps:

skill-seekersscan./my-react-app--out./configs/scanned/
# → react.json, vite.json, tailwind.json, jest.json, my-react-app-codebase.json

# Then build any of them
skill-seekerscreate./configs/scanned/react.json

If a detection has no existing preset, the AI generates a fresh config; on exit you can optionally publish it back to the community registry.

Other Sources (18 Supported)

# GitHub repository
skill-seekerscreatefacebook/react

# Local project
skill-seekerscreate./my-project

# PDF document
skill-seekerscreatemanual.pdf

# Word document
skill-seekerscreatereport.docx

# EPUB e-book
skill-seekerscreatebook.epub

# Jupyter Notebook
skill-seekerscreatenotebook.ipynb

# OpenAPI spec
skill-seekerscreateopenapi.yaml

# PowerPoint presentation
skill-seekerscreatepresentation.pptx

# AsciiDoc document
skill-seekerscreateguide.adoc

# Local HTML file (auto-detected by extension)
skill-seekerscreatepage.html

# Whole directory of HTML files (auto-detected for HTML-dominant dirs)
skill-seekerscreate./mirror_output/site/

# Force HTML mode on a mixed/code-heavy directory
skill-seekerscreate./repo/--html-path./repo/docs/build/html/

# RSS/Atom feed
skill-seekerscreatefeed.rss

# Man page
skill-seekerscreatecurl.1

# Video (YouTube, Vimeo, or local file — requires skill-seekers[video])
skill-seekerscreate--video-urlhttps://www.youtube.com/watch?v=...--namemytutorial
# First time? Auto-install GPU-aware visual deps:
skill-seekerscreate--setup

# Confluence wiki
skill-seekerscreate--space-keyTEAM--namewiki

# Notion pages
skill-seekerscreate--database-id...--namedocs

# Slack/Discord chat export
skill-seekerscreate--chat-export-path./slack-export--nameteam-chat

Export Everywhere

# Package for multiple platforms
forplatforminclaudegeminiopenailangchain;do
skill-seekerspackageoutput/django--target$platform
done

What is Skill Seekers?

Skill Seekers is the data layer for AI systems. It transforms 18 source types—documentation websites, GitHub repositories, PDFs, videos, Jupyter Notebooks, Word/EPUB/AsciiDoc documents, OpenAPI specs, PowerPoint presentations, RSS feeds, man pages, Confluence wikis, Notion pages, Slack/Discord exports, and more—into structured knowledge assets for every AI target:

Use Case	What you get	Examples
AI Skills	Comprehensive SKILL.md + references	Claude Code, Gemini, GPT
RAG Pipelines	Chunked documents with rich metadata	LangChain, LlamaIndex, Haystack
Vector Databases	Pre-formatted data ready for upsert	Pinecone, Chroma, Weaviate, FAISS
AI Coding Assistants	Context files your IDE AI reads automatically	Cursor, Windsurf, Cline, Continue.dev

📚 Documentation

I want to...	Read this
Get started quickly	Quick Start - 3 commands to first skill
Understand concepts	Core Concepts - How it works
Scrape sources	Scraping Guide - All source types
Enhance skills	Enhancement Guide - AI enhancement
Export skills	Packaging Guide - Platform export
Look up commands	CLI Reference - All 20 commands
Configure	Config Format - JSON specification
Fix issues	Troubleshooting - Common problems

Complete documentation: docs/README.md

Instead of spending days on manual preprocessing, Skill Seekers:

Ingests — docs, GitHub repos, local codebases, PDFs, videos, notebooks, wikis, and 10+ more source types
Analyzes — deep AST parsing, pattern detection, API extraction
Structures — categorized reference files with metadata
Enhances — AI-powered SKILL.md generation (Claude, Gemini, or local)
Exports — 16 platform-specific formats from one asset

Why Use This?

For AI Skill Builders (Claude, Gemini, OpenAI)

🎯 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

For RAG Builders & AI Engineers

🤖 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 + videos in one pipeline
🌐 Platform-agnostic — Export to any vector DB or framework without re-scraping

For AI Coding Assistant Users

💻 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

Key Features

🌐 Documentation Scraping

✅ Smart SPA Discovery - Three-layer discovery for JavaScript SPA sites (sitemap.xml → llms.txt → headless browser rendering)
✅ 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

📄 PDF Support

✅ 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

🎬 Video Extraction

✅ YouTube & Local Videos - Extract transcripts, on-screen code, and structured knowledge from videos
✅ Visual Frame Analysis - OCR extraction from code editors, terminals, slides, and diagrams
✅ GPU Auto-Detection - Automatically installs correct PyTorch build (CUDA/ROCm/MPS/CPU)
✅ AI Enhancement - Two-pass: clean OCR artifacts + generate polished SKILL.md
✅ Time Clipping - Extract specific sections with --start-time and --end-time
✅ Playlist Support - Batch process all videos in a YouTube playlist
✅ Vision API Fallback - Use Claude Vision for low-confidence OCR frames

🐙 GitHub Repository Analysis

✅ 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"

🔄 Unified Multi-Source Scraping

✅ 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

🤖 Multi-LLM Platform Support

✅ 12 LLM Platforms - Claude AI, Google Gemini, OpenAI ChatGPT, MiniMax AI, Generic Markdown, OpenCode, Kimi (Moonshot AI), DeepSeek AI, Qwen (Alibaba), OpenRouter, Together AI, Fireworks AI
✅ 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

Platform	Format	Upload	Enhancement	API Key	Custom Endpoint
Claude AI	ZIP + YAML	✅ Auto	✅ Yes	ANTHROPIC_API_KEY	ANTHROPIC_BASE_URL
Google Gemini	tar.gz	✅ Auto	✅ Yes	GOOGLE_API_KEY	-
OpenAI ChatGPT	ZIP + Vector Store	✅ Auto	✅ Yes	OPENAI_API_KEY	-
MiniMax AI	ZIP + Knowledge Files	✅ Auto	✅ Yes	MINIMAX_API_KEY	-
Generic Markdown	ZIP	❌ Manual	❌ No	-	-

# Claude (default - no changes needed!)
skill-seekerspackageoutput/react/
skill-seekersuploadreact.zip

# Google Gemini
pipinstallskill-seekers[gemini]
skill-seekerspackageoutput/react/--targetgemini
skill-seekersuploadreact-gemini.tar.gz--targetgemini

# OpenAI ChatGPT
pipinstallskill-seekers[openai]
skill-seekerspackageoutput/react/--targetopenai
skill-seekersuploadreact-openai.zip--targetopenai

# MiniMax AI
pipinstallskill-seekers[minimax]
skill-seekerspackageoutput/react/--targetminimax
skill-seekersuploadreact-minimax.zip--targetminimax

# Generic Markdown (universal export)
skill-seekerspackageoutput/react/--targetmarkdown
# Use the markdown files directly in any LLM

Installation:

# Install with Gemini support
pipinstallskill-seekers[gemini]

# Install with OpenAI support
pipinstallskill-seekers[openai]

# Install with MiniMax support
pipinstallskill-seekers[minimax]

# Install with all LLM platforms
pipinstallskill-seekers[all-llms]

🔗 RAG Framework Integrations

✅ 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-seekerspackageoutput/django--targetlangchain
# → output/django-langchain.json

# LlamaIndex TextNodes (JSON)
skill-seekerspackageoutput/django--targetllama-index
# → output/django-llama-index.json

# Markdown (Universal)
skill-seekerspackageoutput/django--targetmarkdown
# → output/django-markdown/SKILL.md + references/

Complete RAG Pipeline Guide: RAG Pipelines Documentation

🧠 AI Coding Assistant Integrations

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-seekerscreate--configconfigs/django.json
skill-seekerspackageoutput/django--targetclaude# or --target markdown

# Copy to your project (example for Cursor)
cpoutput/django-claude/SKILL.mdmy-project/.cursorrules

# Or for Windsurf
cpoutput/django-claude/SKILL.mdmy-project/.windsurf/rules/django.md

# Or for Cline
cpoutput/django-claude/SKILL.mdmy-project/.clinerules

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

Integration Hub: All AI System Integrations

🌊 Three-Stream GitHub Architecture

✅ 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)

fromskill_seekers.cli.unified_codebase_analyzerimport 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

🔐 Smart Rate Limit Management & Configuration

✅ 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-seekersconfig--github

# Use specific profile for private repos
skill-seekerscreatemycompany/private-repo--profilework

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

# Resume interrupted job
skill-seekersresume--list
skill-seekersresumegithub_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)

🎯 Bootstrap Skill - Self-Hosting

Generate skill-seekers as a skill to use within your AI agent (Claude Code, Kimi, Codex, etc.):

# Generate the skill
./scripts/bootstrap_skill.sh

# Install to Claude Code
cp-routput/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

🔐 Private Config Repositories

✅ 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

🤖 Codebase Analysis (C3.x)

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-seekersscantests/--quick

# Comprehensive analysis with AI (20-60 min, all features)
skill-seekersscantests/--comprehensive

# With AI enhancement
skill-seekersscantests/--enhance

Full Documentation: docs/features/HOW_TO_GUIDES.md

🔄 Enhancement Workflow Presets

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-seekerscreate./my-project--enhance-workflowsecurity-focus

# Chain multiple workflows (applied in order)
skill-seekerscreate./my-project\
--enhance-workflowsecurity-focus\
--enhance-workflowminimal

# Manage presets
skill-seekersworkflowslist# List all (bundled + user)
skill-seekersworkflowsshowsecurity-focus# Print YAML content
skill-seekersworkflowscopysecurity-focus# Copy to user dir for editing
skill-seekersworkflowsadd./my-workflow.yaml# Install a custom preset
skill-seekersworkflowsremovemy-workflow# Remove a user preset
skill-seekersworkflowsvalidatesecurity-focus# Validate preset structure

# Copy multiple at once
skill-seekersworkflowscopysecurity-focusminimalapi-documentation

# Add multiple files at once
skill-seekersworkflowsadd./wf-a.yaml./wf-b.yaml

# Remove multiple at once
skill-seekersworkflowsremovemy-wf-amy-wf-b

YAML preset format:

name:security-focus
description:"Security-focusedreview:vulnerabilities,auth,datahandling"
version:"1.0"
stages:
-name:vulnerabilities
type:custom
prompt:"ReviewforOWASPtop10andcommonsecurityvulnerabilities..."
-name:auth-review
type:custom
prompt:"Examineauthenticationandauthorisationpatterns..."
uses_history:true

⚡ Performance & Scale

✅ 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

🤖 Agent-Agnostic Skill Generation

✅ Multi-Agent Support - Generate skills for Claude, Kimi, Codex, Copilot, OpenCode, or any custom agent via --agent flag
✅ Custom Agent Commands - Use --agent-cmd to specify a custom agent CLI command for enhancement
✅ Universal Flags - --agent and --agent-cmd available on all commands (create, scrape, github, pdf, etc.)

📦 Marketplace Pipeline

✅ Publish to Marketplace - Publish skills to Claude Code plugin marketplace repos
✅ End-to-End Pipeline - From documentation source to published marketplace entry

✅ Quality Assurance

✅ Fully Tested - 3,700+ tests with comprehensive coverage

📦 Installation

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

# With all LLM platform support
pipinstallskill-seekers[all-llms]

# With MCP server
pipinstallskill-seekers[mcp]

# Everything
pipinstallskill-seekers[all]

Need help choosing? Run the setup wizard:

skill-seekers-setup

Installation Options

Install	Features
`pip install skill-seekers`	Scraping, GitHub analysis, PDF, all platforms
`pip install skill-seekers[gemini]`	+ Google Gemini support
`pip install skill-seekers[openai]`	+ OpenAI ChatGPT support
`pip install skill-seekers[all-llms]`	+ All LLM platforms
`pip install skill-seekers[mcp]`	+ MCP server for Claude Code, Cursor, etc.
`pip install skill-seekers[video]`	+ YouTube/Vimeo transcript & metadata extraction
`pip install skill-seekers[video-full]`	+ Whisper transcription & visual frame extraction
`pip install skill-seekers[jupyter]`	+ Jupyter Notebook support
`pip install skill-seekers[pptx]`	+ PowerPoint support
`pip install skill-seekers[confluence]`	+ Confluence wiki support
`pip install skill-seekers[notion]`	+ Notion pages support
`pip install skill-seekers[rss]`	+ RSS/Atom feed support
`pip install skill-seekers[chat]`	+ Slack/Discord chat export support
`pip install skill-seekers[asciidoc]`	+ AsciiDoc document support
`pip install skill-seekers[all]`	Everything enabled

Video visual deps (GPU-aware): After installing skill-seekers[video-full], run skill-seekers create --setup to auto-detect your GPU and install the correct PyTorch variant + easyocr. This is the recommended way to install visual extraction dependencies.

🚀 One-Command Install Workflow

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

# Install React skill from official configs (auto-uploads to Claude)
skill-seekersinstall--configreact

# Install from local config file
skill-seekersinstall--configconfigs/custom.json

# Install without uploading (package only)
skill-seekersinstall--configdjango--no-upload

# Preview workflow without executing
skill-seekersinstall--configreact--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), or use --agent to select a different AI agent

📊 Feature Matrix

Skill Seekers supports 12 LLM platforms, 8 RAG/vector targets, 18 source types, and full feature parity across all targets.

Platforms: Claude AI, Google Gemini, OpenAI ChatGPT, MiniMax AI, Generic Markdown, OpenCode, Kimi (Moonshot AI), DeepSeek AI, Qwen (Alibaba), OpenRouter, Together AI, Fireworks AI Source Types: Documentation websites, GitHub repos, PDFs, Word (.docx), EPUB, Video, Local codebases, Jupyter Notebooks, Local HTML, OpenAPI/Swagger, AsciiDoc, PowerPoint (.pptx), RSS/Atom feeds, Man pages, Confluence wikis, Notion pages, Slack/Discord chat exports

See Complete Feature Matrix for detailed platform and feature support.

Quick Platform Comparison

Feature	Claude	Gemini	OpenAI	MiniMax	Markdown
Format	ZIP + YAML	tar.gz	ZIP + Vector	ZIP + Knowledge	ZIP
Upload	✅ API	✅ API	✅ API	✅ API	❌ Manual
Enhancement	✅ Sonnet 4	✅ 2.0 Flash	✅ GPT-4o	✅ M3	❌ None
All Skill Modes	✅	✅	✅	✅	✅

Usage Examples

Documentation Scraping

# Scrape documentation website
skill-seekerscreate--configconfigs/react.json

# Quick scrape without config
skill-seekerscreatehttps://react.dev--namereact

# With async mode (3x faster)
skill-seekerscreate--configconfigs/godot.json--async--workers8

# Use a specific AI agent for enhancement
skill-seekerscreate--configconfigs/react.json--agentkimi

PDF Extraction

# Basic PDF extraction
skill-seekerscreate--pdfdocs/manual.pdf--namemyskill

# Advanced features
skill-seekerscreate--pdfdocs/manual.pdf--namemyskill\
--extract-tables\ # Extract tables
--parallel\ # Fast parallel processing
--workers8# Use 8 CPU cores

# Scanned PDFs (requires: pip install pytesseract Pillow)
skill-seekerscreate--pdfdocs/scanned.pdf--namemyskill--ocr

Video Extraction

# Install video support
pipinstallskill-seekers[video]# Transcripts + metadata
pipinstallskill-seekers[video-full]# + Whisper + visual frame extraction

# Auto-detect GPU and install visual deps (PyTorch + easyocr)
skill-seekerscreate--setup

# Extract from YouTube video
skill-seekerscreate--video-urlhttps://www.youtube.com/watch?v=dQw4w9WgXcQ--namemytutorial

# Extract from a YouTube playlist
skill-seekerscreate--video-playlisthttps://www.youtube.com/playlist?list=...--namemyplaylist

# Extract from a local video file
skill-seekerscreate--video-filerecording.mp4--namemyrecording

# Extract with visual frame analysis (requires video-full deps)
skill-seekerscreate--video-urlhttps://www.youtube.com/watch?v=...--namemytutorial--visual

# With AI enhancement (cleans OCR + generates polished SKILL.md)
skill-seekerscreate--video-urlhttps://www.youtube.com/watch?v=...--visual--enhance-level2

# Clip a specific section of a video (supports seconds, MM:SS, HH:MM:SS)
skill-seekerscreate--video-urlhttps://www.youtube.com/watch?v=...--start-time1:30--end-time5:00

# Use Vision API for low-confidence OCR frames (requires ANTHROPIC_API_KEY)
skill-seekerscreate--video-urlhttps://www.youtube.com/watch?v=...--visual--vision-ocr

# Re-build skill from previously extracted data (skip download)
skill-seekerscreate--from-jsonoutput/mytutorial/video_data/extracted_data.json--namemytutorial

Full guide: See docs/VIDEO_GUIDE.md for complete CLI reference, visual pipeline details, AI enhancement options, and troubleshooting.

GitHub Repository Analysis

# Basic repository scraping
skill-seekerscreatefacebook/react

# With authentication (higher rate limits)
exportGITHUB_TOKEN=ghp_your_token_here
skill-seekerscreatefacebook/react

# Customize what to include
skill-seekerscreatedjango/django\
--include-issues\ # Extract GitHub Issues
--max-issues100\ # Limit issue count
--include-changelog# Extract CHANGELOG.md

Unified Multi-Source Scraping

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

# Use existing unified configs
skill-seekerscreate--configconfigs/react_unified.json
skill-seekerscreate--configconfigs/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-seekerscreate--configconfigs/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/features/UNIFIED_SCRAPING.md for complete documentation.

Private Config Repositories

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/reference/GIT_CONFIG_SOURCES.md for complete documentation.

How It Works

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

Detect llms.txt - Checks for llms-full.txt, llms.txt, llms-small.txt first (part of Smart SPA Discovery)
Scrape: Extracts all pages from documentation
Categorize: Organizes content into topics (API, guides, tutorials, etc.)
Enhance: AI analyzes docs and creates comprehensive SKILL.md with examples (supports multiple agents via --agent)
Package: Bundles everything into a platform-ready .zip file

Architecture

The system is organized into 8 core modules and 5 utility modules (~200 classes total):

👁 Package Overview

Module	Purpose	Key Classes
CLICore	Git-style command dispatcher	`CLIDispatcher`, `SourceDetector`, `CreateCommand`
Scrapers	18 source-type extractors	`DocToSkillConverter`, `DocumentSkillBuilder` (shared build layer), `UnifiedScraper`
Adaptors	20+ output platform formats	`SkillAdaptor` (ABC), `ClaudeAdaptor`, `LangChainAdaptor`
Analysis	C3.x codebase analysis pipeline	`UnifiedCodebaseAnalyzer`, `PatternRecognizer`, 10 GoF detectors
Enhancement	AI-powered skill improvement via `AgentClient`	`AgentClient`, `AIEnhancer`, `UnifiedEnhancer`, `WorkflowEngine`
Packaging	Package, upload, install skills	`PackageSkill`, `InstallAgent`
MCP	FastMCP server (40 tools)	`SkillSeekerMCPServer`, 10 tool modules
Sync	Doc change detection	`ChangeDetector`, `SyncMonitor`, `Notifier`

Utility modules: Parsers (28 CLI parsers), Storage (S3/GCS/Azure), Embedding (multi-provider vectors), Benchmark (performance), Utilities (16 shared helpers).

Full UML diagrams: docs/UML_ARCHITECTURE.md | StarUML project: docs/UML/skill_seekers.mdj | HTML API reference: docs/UML/html/

📋 Prerequisites

Before you start, make sure you have:

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

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

📤 Uploading Skills to Claude

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

Option 1: Automatic Upload (API-based)

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

# Package and upload automatically
skill-seekerspackageoutput/react/--upload

# OR upload existing .zip
skill-seekersuploadoutput/react.zip

Option 2: Manual Upload (No API Key)

# Package skill
skill-seekerspackageoutput/react/
# → Creates output/react.zip

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

Option 3: MCP (Claude Code)

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

🤖 Installing to AI Agents

Skill Seekers can automatically install skills to 19 AI coding agents.

# Install to specific agent
skill-seekersinstall-agentoutput/react/--agentcursor

# Install to IBM Bob (project-local .bob/skills/)
skill-seekersinstall-agentoutput/react/--agentbob

# Install to all agents at once
skill-seekersinstall-agentoutput/react/--agentall

# Preview without installing
skill-seekersinstall-agentoutput/react/--agentcursor--dry-run

Supported Agents

Agent	Path	Type
Claude Code	`~/.claude/skills/`	Global
Cursor	`.cursor/skills/`	Project
VS Code / Copilot	`.github/skills/`	Project
Amp	`~/.amp/skills/`	Global
Goose	`~/.config/goose/skills/`	Global
OpenCode	`~/.opencode/skills/`	Global
Windsurf	`~/.windsurf/skills/`	Global
Roo Code	`.roo/skills/`	Project
Cline	`.cline/skills/`	Project
Aider	`~/.aider/skills/`	Global
Bolt	`.bolt/skills/`	Project
Kilo Code	`.kilo/skills/`	Project
Continue	`~/.continue/skills/`	Global
Kimi Code	`~/.kimi/skills/`	Global
IBM Bob	`.bob/skills/`	Project

🔌 MCP Integration (40 Tools)

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-mskill_seekers.mcp.server_fastmcp

# HTTP mode (Cursor, Windsurf, IntelliJ)
python-mskill_seekers.mcp.server_fastmcp--transporthttp--port8765

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

All 40 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/guides/MCP_SETUP.md

⚙️ Configuration

Available Presets (24+)

# List all presets
# skill-seekers list-configs # Not available in v3.7.0

Category	Presets
Web Frameworks	`react`, `vue`, `angular`, `svelte`, `nextjs`
Python	`django`, `flask`, `fastapi`, `sqlalchemy`, `pytest`
Game Development	`godot`, `pygame`, `unity`
Tools & DevOps	`docker`, `kubernetes`, `terraform`, `ansible`
Unified (Docs + GitHub)	`react-unified`, `vue-unified`, `nextjs-unified`, and more

Creating Your Own Config

# Option 1: Interactive
skill-seekerscreate--interactive

# Option 2: Copy and edit a preset
cpconfigs/react.jsonconfigs/myframework.json
nanoconfigs/myframework.json
skill-seekerscreate--configconfigs/myframework.json

Config File Structure

{
"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
}

Where to Store Configs

The tool searches in this order:

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

📊 What Gets Created

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)

🐛 Troubleshooting

No Content Extracted?

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

Data Exists But Won't Use It?

# Force re-scrape
rm-rfoutput/myframework_data/
skill-seekerscreate--configconfigs/myframework.json

Categories Not Good?

Edit the config categories section with better keywords.

Want to Update Docs?

# Delete old data and re-scrape
rm-rfoutput/godot_data/
skill-seekerscreate--configconfigs/godot.json

Enhancement Not Working?

# Check if API key is set
echo$ANTHROPIC_API_KEY

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

# Monitor background enhancement status
skill-seekersenhance-statusoutput/react/--watch

GitHub Rate Limit Issues?

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

# Or configure multiple profiles
skill-seekersconfig--github

📈 Performance

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 rebuild from cache
Re-building	<1 min	With `--skip-scrape`
Enhancement (LOCAL)	30-60 sec	Uses Claude Code Max
Enhancement (API)	20-40 sec	Requires API key
Video (transcript)	1-3 min	YouTube/local, transcript only
Video (visual)	5-15 min	+ OCR frame extraction
Packaging	5-10 sec	Final .zip creation

🆕 New in v3.6.0

Workflow Presets

Control analysis depth with --preset:

skill-seekerscreatehttps://docs.react.dev/--presetquick# Fast, surface-level
skill-seekerscreatehttps://docs.react.dev/--presetstandard# Balanced (default)
skill-seekerscreatehttps://docs.react.dev/--presetcomprehensive# Deep, exhaustive

Lifecycle Flags

skill-seekerscreatehttps://docs.react.dev/--dry-run# Preview without scraping
skill-seekerscreatehttps://docs.react.dev/--fresh# Ignore cache, full re-scrape
skill-seekerscreatehttps://docs.react.dev/--resume# Resume interrupted job
skill-seekerscreatehttps://docs.react.dev/--skip-scrape# Re-package existing output

Health Check & Utilities

skill-seekersdoctor# Diagnose installation & environment
skill-seekerssync-config# Detect config drift
skill-seekersstream<source># Streaming ingestion for large docs
skill-seekersupdateoutput/react/# Incremental update
skill-seekersmultilang<source># Multi-language skill generation
skill-seekersqualityoutput/react/# Quality report (add --threshold 7 to gate: non-zero exit below 7/10)

RAG Chunking Options (package)

skill-seekerspackageoutput/react/--chunk-for-rag--chunk-tokens512--chunk-overlap-tokens50

Marketplace Publishing

skill-seekerspackageoutput/react/--marketplace--marketplace-categoryfrontend

Additional Optional Dependencies

Extra	Install	Purpose
`browser`	`pip install "skill-seekers[browser]"`	Headless Playwright for SPA sites
`embedding`	`pip install "skill-seekers[embedding]"`	Embedding server support
`s3` / `gcs` / `azure`	`pip install "skill-seekers[s3]"` etc.	Cloud storage upload
`rag-upload`	`pip install "skill-seekers[rag-upload]"`	Combined vector DB upload deps

📚 Documentation

Getting Started

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

Architecture

docs/UML_ARCHITECTURE.md - UML architecture overview with 14 diagrams
docs/UML/exports/ - PNG diagram exports (package overview + 13 class diagrams)
docs/UML/html/ - Full HTML API reference (all classes, operations, attributes)
docs/UML/skill_seekers.mdj - StarUML project file (open with StarUML)

Guides

docs/reference/LARGE_DOCUMENTATION.md - Handle 10K-40K+ page docs
docs/features/ENHANCEMENT_MODES.md - AI enhancement modes guide
docs/guides/MCP_SETUP.md - MCP integration setup
docs/features/UNIFIED_SCRAPING.md - Multi-source scraping
docs/VIDEO_GUIDE.md - Video extraction guide

Integration Guides

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

📝 License

MIT License - see LICENSE file for details

Happy skill building! 🚀

🔒 Security

👁 MseeP.ai Security Assessment Badge

💛 Sponsors

👁 Atlas Cloud

Atlas Cloud — a full-modal, OpenAI-compatible AI inference platform. Skill Seekers supports it as a packaging/enhancement target via --target atlas with ATLAS_API_KEY.

Project details

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yusyus

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Project links

Classifiers

Development Status
- 4 - Beta
Intended Audience
- Developers
License
- OSI Approved :: MIT License
Natural Language
- Chinese (Simplified)
- English
Operating System
- OS Independent
Programming Language
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⇱ skill-seekers · PyPI

skill-seekers 3.8.0

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Verified details

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Unverified details

Project links

Meta

Classifiers

Project description

Skill Seekers

🌐 Ecosystem

🧠 The Data Layer for AI Systems

What gets built

Why it matters

🚀 Quick Start (3 Commands)

🛰️ AI-driven project scan (new)

Other Sources (18 Supported)

Export Everywhere

What is Skill Seekers?

📚 Documentation

Why Use This?

For AI Skill Builders (Claude, Gemini, OpenAI)

For RAG Builders & AI Engineers

For AI Coding Assistant Users

Key Features

🌐 Documentation Scraping

📄 PDF Support

🎬 Video Extraction

🐙 GitHub Repository Analysis

🔄 Unified Multi-Source Scraping

🤖 Multi-LLM Platform Support

🔗 RAG Framework Integrations

🧠 AI Coding Assistant Integrations

🌊 Three-Stream GitHub Architecture

🔐 Smart Rate Limit Management & Configuration

🎯 Bootstrap Skill - Self-Hosting

🔐 Private Config Repositories

🤖 Codebase Analysis (C3.x)

🔄 Enhancement Workflow Presets

⚡ Performance & Scale

🤖 Agent-Agnostic Skill Generation

📦 Marketplace Pipeline

✅ Quality Assurance

📦 Installation

Installation Options

🚀 One-Command Install Workflow

📊 Feature Matrix

Quick Platform Comparison

Usage Examples

Documentation Scraping

PDF Extraction

Video Extraction

GitHub Repository Analysis

Unified Multi-Source Scraping

Private Config Repositories

How It Works

Architecture

📋 Prerequisites

📤 Uploading Skills to Claude

Option 1: Automatic Upload (API-based)

Option 2: Manual Upload (No API Key)

Option 3: MCP (Claude Code)

🤖 Installing to AI Agents

Supported Agents

🔌 MCP Integration (40 Tools)

⚙️ Configuration

Available Presets (24+)

Creating Your Own Config

Config File Structure

Where to Store Configs

📊 What Gets Created

🐛 Troubleshooting

No Content Extracted?

Data Exists But Won't Use It?

Categories Not Good?

Want to Update Docs?

Enhancement Not Working?

GitHub Rate Limit Issues?