yusufkaraaslan

Skill_Seekers

<p align="center"> <img src="docs/assets/logo.png" alt="Skill Seekers" width="200"/> </p> # Skill Seekers English | [简体中文](README.zh-CN.md) | [日本語](README.ja.md) | [한국어](README.ko.md) | [Español](README.es.md) | [Français](README.fr.md) | [Deutsch](README.de.md) | [Português](README.pt-BR.md) | [Türkçe](README.tr.md) | [العربية](README.ar.md) | [हिन्दी](README.hi.md) | [Русский](README.ru.md) [](https://github.com/yusufkaraaslan/Skill_Seekers/releases) [](https://opensource.org/licenses/MIT) [](https://www.python.org/downloads/) [](https://modelcontextprotocol.io) [](tests/) [](https://github.com/users/yusufkaraaslan/projects/2) [](https://pypi.org/project/skill-seekers/) [](https://pypi.org/project/skill-seekers/) [](https://pypi.org/project/skill-seekers/) [](https://skillseekersweb.com/) [](https://x.com/_yUSyUS_) [](https://github.com/yusufkaraaslan/Skill_Seekers) [](https://pepy.tech/projects/skill-seekers) <a href="https://trendshift.io/repositories/18329" target="_blank"><img src="https://trendshift.io/api/badge/repositories/18329" alt="yusufkaraaslan%2FSkill_Seekers | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> **🧠 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](https://skillseekersweb.com/)** - Browse 24+ preset configs, share your configs, and access complete documentation! > 📋 **[View Development Roadmap & Tasks](https://github.com/users/yusufkaraaslan/projects/2)** - 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](https://github.com/yusufkaraaslan/Skill_Seekers)** | Core CLI & MCP server (this repo) | [PyPI](https://pypi.org/project/skill-seekers/) | | **[skillseekersweb](https://github.com/yusufkaraaslan/skillseekersweb)** | Website & documentation | [Live](https://skillseekersweb.com/) | | **[skill-seekers-configs](https://github.com/yusufkaraaslan/skill-seekers-configs)** | Community config repository | | | **[skill-seekers-action](https://github.com/yusufkaraaslan/skill-seekers-action)** | GitHub Action for CI/CD | | | **[skill-seekers-plugin](https://github.com/yusufkaraaslan/skill-seekers-plugin)** | Claude Code plugin | | | **[homebrew-skill-seekers](https://github.com/yusufkaraaslan/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. ```bash # One command → structured knowledge asset skill-seekers create https://docs.react.dev/ # or: skill-seekers create facebook/react # or: skill-seekers create ./my-project # Export to any AI system skill-seekers package output/react --target claude # → Claude AI Skill (ZIP) skill-seekers package output/react --target langchain # → LangChain Documents skill-seekers package output/react --target llama-index # → LlamaIndex TextNodes skill-seekers package output/react --target cursor # → .cursorrules skill-seekers package output/react --target ibm-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** — 3,445+ tests, 24+ framework presets, production-ready ## 🚀 Quick Start (3 Commands) ```bash # 1. Install pip install skill-seekers # 2. Create skill from any source skill-seekers create https://docs.django.com/ # 3. Package for your AI platform skill-seekers package output/django --target claude ``` **That's it!** You now have `output/django-claude.zip` ready to use. ```bash # Use a different AI agent for enhancement (default: claude) skill-seekers create https://docs.django.com/ --agent kimi skill-seekers create https://docs.django.com/ --agent codex skill-seekers create https://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: ```bash skill-seekers scan ./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-seekers create ./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](https://github.com/yusufkaraaslan/skill-seekers-configs). ### Other Sources (18 Supported) ```bash # GitHub repository skill-seekers create facebook/react # Local project skill-seekers create ./my-project # PDF document skill-seekers create manual.pdf # Word document skill-seekers create report.docx # EPUB e-book skill-seekers create book.epub # Jupyter Notebook skill-seekers create notebook.ipynb # OpenAPI spec skill-seekers create openapi.yaml # PowerPoint presentation skill-seekers create presentation.pptx # AsciiDoc document skill-seekers create guide.adoc # Local HTML file (auto-detected by extension) skill-seekers create page.html # Whole directory of HTML files (auto-detected for HTML-dominant dirs) skill-seekers create ./mirror_output/site/ # Force HTML mode on a mixed/code-heavy directory skill-seekers create ./repo/ --html-path ./repo/docs/build/html/ # RSS/Atom feed skill-seekers create feed.rss # Man page skill-seekers create curl.1 # Video (YouTube, Vimeo, or local file — requires skill-seekers[video]) skill-seekers create --video-url https://www.youtube.com/watch?v=... --name mytutorial # First time? Auto-install GPU-aware visual deps: skill-seekers create --setup # Confluence wiki skill-seekers create --space-key TEAM --name wiki # Notion pages skill-seekers create --database-id ... --name docs # Slack/Discord chat export skill-seekers create --chat-export-path ./slack-export --name team-chat ``` ### Export Everywhere ```bash # Package for multiple platforms for platform in claude gemini openai langchain; do skill-seekers package output/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](docs/getting-started/02-quick-start.md) - 3 commands to first skill | | **Understand concepts** | [Core Concepts](docs/user-guide/01-core-concepts.md) - How it works | | **Scrape sources** | [Scraping Guide](docs/user-guide/02-scraping.md) - All source types | | **Enhance skills** | [Enhancement Guide](docs/user-guide/03-enhancement.md) - AI enhancement | | **Export skills** | [Packaging Guide](docs/user-guide/04-packaging.md) - Platform export | | **Look up commands** | [CLI Reference](docs/reference/CLI_REFERENCE.md) - All 20 commands | | **Configure** | [Config Format](docs/reference/CONFIG_FORMAT.md) - JSON specification | | **Fix issues** | [Troubleshooting](docs/user-guide/06-troubleshooting.md) - Common problems | **Complete documentation:** [docs/README.md](docs/README.md) Instead of spending days on manual preprocessing, Skill Seekers: 1. **Ingests** — docs, GitHub repos, local codebases, PDFs, videos, notebooks, wikis, and 10+ more source types 2. **Analyzes** — deep AST parsing, pattern detection, API extraction 3. **Structures** — categorized reference files with metadata 4. **Enhances** — AI-powered SKILL.md generation (Claude, Gemini, or local) 5. **Exports** — 16 platform-specific formats from one asset ## 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 | - | - | ```bash # Claude (default - no changes needed!) skill-seekers package output/react/ skill-seekers upload react.zip # Google Gemini pip install skill-seekers[gemini] skill-seekers package output/react/ --target gemini skill-seekers upload react-gemini.tar.gz --target gemini # OpenAI ChatGPT pip install skill-seekers[openai] skill-seekers package output/react/ --target openai skill-seekers upload react-openai.zip --target openai # MiniMax AI pip install skill-seekers[minimax] skill-seekers package output/react/ --target minimax skill-seekers upload react-minimax.zip --target minimax # Generic Markdown (universal export) skill-seekers package output/react/ --target markdown # Use the markdown files directly in any LLM ``` <details> <summary>🔧 <strong>Use your own AI provider (OpenAI-compatible endpoints + subscriptions, no Anthropic credits needed)</strong></summary> The optional AI **enhancement** step (used by `create`, `scan`, and `enhance`) does **not** require an Anthropic key. You have three ways to power it: **1. Use a subscription you already pay for — no API credits at all (LOCAL agent mode)** Skill Seekers can shell out to a coding-agent CLI you're already logged into, so enhancement runs on your existing plan instead of metered API tokens: ```bash skill-seekers create <source> --agent codex # OpenAI Codex CLI → your ChatGPT Plus skill-seekers create <source> --agent claude # Claude Code → your Claude Pro/Max ``` Supported agents: `claude`, `codex`, `copilot`, `opencode`, `kimi`, and `custom` (pair `--agent custom` with `--agent-cmd "<your-cli> ..."` to drive any other tool). **2. Any OpenAI-compatible provider (OpenRouter, Groq, Cerebras, Mistral, NVIDIA NIM, …)** All of these expose an OpenAI-compatible `/v1` endpoint. Point Skill Seekers at one with three env vars — it detects `OPENAI_API_KEY`, and the OpenAI SDK honors `OPENAI_BASE_URL` automatically: ```bash export OPENAI_API_KEY="<your provider key>" export OPENAI_BASE_URL="https://openrouter.ai/api/v1" # provider endpoint (see table) export OPENAI_MODEL="<a model that provider offers>" # required — default gpt-4o won't exist elsewhere skill-seekers create <source> ``` | Provider | `OPENAI_BASE_URL` | |--------------|--------------------------------------------| | OpenRouter | `https://openrouter.ai/api/v1` | | Groq | `https://api.groq.com/openai/v1` | | Cerebras | `https://api.cerebras.ai/v1` | | Mistral | `https://api.mistral.ai/v1` | | NVIDIA NIM | `https://integrate.api.nvidia.com/v1` | > Provider detection picks the **first** API-key env var it finds (`ANTHROPIC_API_KEY` → `MOONSHOT_API_KEY` → `GOOGLE_API_KEY` → `OPENAI_API_KEY`). If you want the OpenAI-compatible route, make sure the higher-priority keys are unset. **3. Claude-compatible endpoints (e.g. GLM, proxies)** ```bash export ANTHROPIC_API_KEY="your-key" export ANTHROPIC_BASE_URL="https://your-claude-compatible-endpoint/v1" ``` Google Gemini (`GOOGLE_API_KEY`) and Kimi/Moonshot (`MOONSHOT_API_KEY`) are also supported natively. See **[Environment Variables Reference](docs/reference/ENVIRONMENT_VARIABLES.md#llm-provider-selection)** for the full list, including per-provider model overrides. </details> **Installation:** ```bash # Install with Gemini support pip install skill-seekers[gemini] # Install with OpenAI support pip install skill-seekers[openai] # Install with MiniMax support pip install skill-seekers[minimax] # Install with all LLM platforms pip install skill-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](examples/langchain-rag-pipeline/) - Guide: [LangChain Integration](docs/integrations/LANGCHAIN.md) - ✅ **LlamaIndex TextNodes** - Export to `TextNode` format with unique IDs + embeddings - Perfect for: Query engines, chat engines, storage context - Example: [LlamaIndex Query Engine](examples/llama-index-query-engine/) - Guide: [LlamaIndex Integration](docs/integrations/LLAMA_INDEX.md) - ✅ **Pinecone-Ready Format** - Optimized for vector database upsert - Perfect for: Production vector search, semantic search, hybrid search - Example: [Pinecone Upsert](examples/pinecone-upsert/) - Guide: [Pinecone Integration](docs/integrations/PINECONE.md) **Quick Export:** ```bash # LangChain Documents (JSON) skill-seekers package output/django --target langchain # → output/django-langchain.json # LlamaIndex TextNodes (JSON) skill-seekers package output/django --target llama-index # → output/django-llama-index.json # Markdown (Universal) skill-seekers package output/django --target markdown # → output/django-markdown/SKILL.md + references/ ``` **Complete RAG Pipeline Guide:** [RAG Pipelines Documentation](docs/integrations/RAG_PIPELINES.md) --- ### 🧠 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](docs/integrations/CURSOR.md) - Example: [Cursor React Skill](examples/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](docs/integrations/WINDSURF.md) - Example: [Windsurf FastAPI Context](examples/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](docs/integrations/CLINE.md) - Example: [Cline Django Assistant](examples/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](docs/integrations/CONTINUE_DEV.md) - Example: [Continue Universal Context](examples/continue-dev-universal/) **Quick Export for AI Coding Tools:** ```bash # For any AI coding assistant (Cursor, Windsurf, Cline, Continue.dev) skill-seekers create --config configs/django.json skill-seekers package output/django --target claude # or --target markdown # Copy to your project (example for Cursor) cp output/django-claude/SKILL.md my-project/.cursorrules # Or for Windsurf cp output/django-claude/SKILL.md my-project/.windsurf/rules/django.md # Or for Cline cp output/django-claude/SKILL.md my-project/.clinerules # Or for Continue.dev (HTTP server) python examples/continue-dev-universal/context_server.py # Configure in ~/.continue/config.json ``` **Integration Hub:** [All AI System Integrations](docs/integrations/INTEGRATIONS.md) --- ### 🌊 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) ```python from skill_seekers.cli.unified_codebase_analyzer import UnifiedCodebaseAnalyzer # Analyze GitHub repo with all three streams analyzer = UnifiedCodebaseAnalyzer() result = analyzer.analyze( source="https://github.com/facebook/react", depth="c3x", # or "basic" for fast analysis fetch_github_metadata=True ) # Access code stream (C3.x analysis) print(f"Design patterns: {len(result.code_analysis['c3_1_patterns'])}") print(f"Test examples: {result.code_analysis['c3_2_examples_count']}") # Access docs stream (repository docs) print(f"README: {result.github_docs['readme'][:100]}") # Access insights stream (GitHub metadata) print(f"Stars: {result.github_insights['metadata']['stars']}") print(f"Common issues: {len(result.github_insights['common_problems'])}") ``` **See complete documentation**: [Three-Stream Implementation Summary](docs/archive/historical/IMPLEMENTATION_SUMMARY_THREE_STREAM.md) ### 🔐 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:** ```bash # One-time configuration (5 minutes) skill-seekers config --github # Use specific profile for private repos skill-seekers create mycompany/private-repo --profile work # CI/CD mode (fail fast, no prompts) skill-seekers create owner/repo --non-interactive # Resume interrupted job skill-seekers resume --list skill-seekers resume github_react_20260117_143022 ``` **Rate Limit Strategies Explained:** - **prompt** (default) - Ask what to do when rate limited (wait, switch, setup token, cancel) - **wait** - Automatically wait with countdown timer (respects timeout) - **switch** - Automatically try next available profile (for multi-account setups) - **fail** - Fail immediately with clear error (perfect for CI/CD) ### 🎯 Bootstrap Skill - Self-Hosting Generate skill-seekers as a skill to use within your AI agent (Claude Code, Kimi, Codex, etc.): ```bash # Generate the skill ./scripts/bootstrap_skill.sh # Install to Claude Code cp -r output/skill-seekers ~/.claude/skills/ ``` **What you get:** - ✅ **Complete skill documentation** - All CLI commands and usage patterns - ✅ **CLI command reference** - Every tool and its options documented - ✅ **Quick start examples** - Common workflows and best practices - ✅ **Auto-generated API docs** - Code analysis, patterns, and examples ### 🔐 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:** ```bash # Quick analysis (1-2 min, basic features only) skill-seekers scan tests/ --quick # Comprehensive analysis with AI (20-60 min, all features) skill-seekers scan tests/ --comprehensive # With AI enhancement skill-seekers scan tests/ --enhance ``` **Full Documentation:** [docs/features/HOW_TO_GUIDES.md](docs/features/HOW_TO_GUIDES.md#ai-enhancement-new) ### 🔄 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 ```bash # Apply a single workflow skill-seekers create ./my-project --enhance-workflow security-focus # Chain multiple workflows (applied in order) skill-seekers create ./my-project \ --enhance-workflow security-focus \ --enhance-workflow minimal # Manage presets skill-seekers workflows list # List all (bundled + user) skill-seekers workflows show security-focus # Print YAML content skill-seekers workflows copy security-focus # Copy to user dir for editing skill-seekers workflows add ./my-workflow.yaml # Install a custom preset skill-seekers workflows remove my-workflow # Remove a user preset skill-seekers workflows validate security-focus # Validate preset structure # Copy multiple at once skill-seekers workflows copy security-focus minimal api-documentation # Add multiple files at once skill-seekers workflows add ./wf-a.yaml ./wf-b.yaml # Remove multiple at once skill-seekers workflows remove my-wf-a my-wf-b ``` **YAML preset format:** ```yaml name: security-focus description: "Security-focused review: vulnerabilities, auth, data handling" version: "1.0" stages: - name: vulnerabilities type: custom prompt: "Review for OWASP top 10 and common security vulnerabilities..." - name: auth-review type: custom prompt: "Examine authentication and authorisation patterns..." uses_history: true ``` ### ⚡ 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** - 3,445+ tests with comprehensive coverage --- ## 📦 Installation ```bash # Basic install (documentation scraping, GitHub analysis, PDF, packaging) pip install skill-seekers # With all LLM platform support pip install skill-seekers[all-llms] # With MCP server pip install skill-seekers[mcp] # Everything pip install skill-seekers[all] ``` **Need help choosing?** Run the setup wizard: ```bash 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:** ```bash # Install React skill from official configs (auto-uploads to Claude) skill-seekers install --config react # Install from local config file skill-seekers install --config configs/custom.json # Install without uploading (package only) skill-seekers install --config django --no-upload # Preview workflow without executing skill-seekers install --config react --dry-run ``` **Time:** 20-45 minutes total | **Quality:** Production-ready (9/10) | **Cost:** Free **Phases executed:** ``` 📥 PHASE 1: Fetch Config (if config name provided) 📖 PHASE 2: Scrape Documentation ✨ PHASE 3: AI Enhancement (MANDATORY - no skip option) 📦 PHASE 4: Package Skill ☁️ PHASE 5: Upload to Claude (optional, requires API key) ``` **Requirements:** - ANTHROPIC_API_KEY environment variable (for auto-upload) - Claude Code Max plan (for local AI enhancement), 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](docs/reference/FEATURE_MATRIX.md) 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 ```bash # Scrape documentation website skill-seekers create --config configs/react.json # Quick scrape without config skill-seekers create https://react.dev --name react # With async mode (3x faster) skill-seekers create --config configs/godot.json --async --workers 8 # Use a specific AI agent for enhancement skill-seekers create --config configs/react.json --agent kimi ``` ### PDF Extraction ```bash # Basic PDF extraction skill-seekers create --pdf docs/manual.pdf --name myskill # Advanced features skill-seekers create --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 create --pdf docs/scanned.pdf --name myskill --ocr ``` ### Video Extraction ```bash # Install video support pip install skill-seekers[video] # Transcripts + metadata pip install skill-seekers[video-full] # + Whisper + visual frame extraction # Auto-detect GPU and install visual deps (PyTorch + easyocr) skill-seekers create --setup # Extract from YouTube video skill-seekers create --video-url https://www.youtube.com/watch?v=dQw4w9WgXcQ --name mytutorial # Extract from a YouTube playlist skill-seekers create --video-playlist https://www.youtube.com/playlist?list=... --name myplaylist # Extract from a local video file skill-seekers create --video-file recording.mp4 --name myrecording # Extract with visual frame analysis (requires video-full deps) skill-seekers create --video-url https://www.youtube.com/watch?v=... --name mytutorial --visual # With AI enhancement (cleans OCR + generates polished SKILL.md) skill-seekers create --video-url https://www.youtube.com/watch?v=... --visual --enhance-level 2 # Clip a specific section of a video (supports seconds, MM:SS, HH:MM:SS) skill-seekers create --video-url https://www.youtube.com/watch?v=... --start-time 1:30 --end-time 5:00 # Use Vision API for low-confidence OCR frames (requires ANTHROPIC_API_KEY) skill-seekers create --video-url https://www.youtube.com/watch?v=... --visual --vision-ocr # Re-build skill from previously extracted data (skip download) skill-seekers create --from-json output/mytutorial/video_data/extracted_data.json --name mytutorial ``` > **Full guide:** See [docs/VIDEO_GUIDE.md](docs/VIDEO_GUIDE.md) for complete CLI reference, > visual pipeline details, AI enhancement options, and troubleshooting. ### GitHub Repository Analysis ```bash # Basic repository scraping skill-seekers create facebook/react # With authentication (higher rate limits) export GITHUB_TOKEN=ghp_your_token_here skill-seekers create facebook/react # Customize what to include skill-seekers create django/django \ --include-issues \ # Extract GitHub Issues --max-issues 100 \ # Limit issue count --include-changelog # Extract CHANGELOG.md ``` ### Unified Multi-Source Scraping **Combine documentation + GitHub + PDF into one unified skill with conflict detection:** ```bash # Use existing unified configs skill-seekers create --config configs/react_unified.json skill-seekers create --config configs/django_unified.json # Or create unified config cat > configs/myframework_unified.json << 'EOF' { "name": "myframework", "merge_mode": "rule-based", "sources": [ { "type": "documentation", "base_url": "https://docs.myframework.com/", "max_pages": 200 }, { "type": "github", "repo": "owner/myframework", "code_analysis_depth": "surface" } ] } EOF skill-seekers create --config configs/myframework_unified.json ``` **Conflict Detection automatically finds:** - 🔴 **Missing in code** (high): Documented but not implemented - 🟡 **Missing in docs** (medium): Implemented but not documented - ⚠️ **Signature mismatch**: Different parameters/types - ℹ️ **Description mismatch**: Different explanations **Full Guide:** See [docs/features/UNIFIED_SCRAPING.md](docs/features/UNIFIED_SCRAPING.md) for complete documentation. ### Private Config Repositories **Share custom configs across teams using private git repositories:** ```bash # 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](docs/reference/GIT_CONFIG_SOURCES.md) for complete documentation. ## How It Works ```mermaid 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] ``` 0. **Detect llms.txt** - Checks for llms-full.txt, llms.txt, llms-small.txt first (part of Smart SPA Discovery) 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 (supports multiple agents via `--agent`) 4. **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):  | Module | Purpose | Key Classes | |--------|---------|-------------| | **CLICore** | Git-style command dispatcher | `CLIDispatcher`, `SourceDetector`, `CreateCommand` | | **Scrapers** | 18 source-type extractors | `DocToSkillConverter`, `GitHubScraper`, `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](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:** 1. **Python 3.10 or higher** - [Download](https://www.python.org/downloads/) | Check: `python3 --version` 2. **Git** - [Download](https://git-scm.com/) | Check: `git --version` 3. **15-30 minutes** for first-time setup **First time user?** → **[Start Here: Bulletproof Quick Start Guide](BULLETPROOF_QUICKSTART.md)** 🎯 --- ## 📤 Uploading Skills to Claude Once your skill is packaged, you need to upload it to Claude: ### Option 1: Automatic Upload (API-based) ```bash # 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 ``` ### Option 2: Manual Upload (No API Key) ```bash # Package skill skill-seekers package output/react/ # → Creates output/react.zip # Then manually upload: # - Go to https://claude.ai/skills # - Click "Upload Skill" # - Select output/react.zip ``` ### 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. ```bash # Install to specific agent skill-seekers install-agent output/react/ --agent cursor # Install to IBM Bob (project-local .bob/skills/) skill-seekers install-agent output/react/ --agent bob # Install to all agents at once skill-seekers install-agent output/react/ --agent all # Preview without installing skill-seekers install-agent output/react/ --agent cursor --dry-run ``` ### 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. ```bash # stdio mode (Claude Code, VS Code + Cline) python -m skill_seekers.mcp.server_fastmcp # HTTP mode (Cursor, Windsurf, IntelliJ) python -m skill_seekers.mcp.server_fastmcp --transport http --port 8765 # Auto-configure all agents at once ./setup_mcp.sh ``` **All 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](docs/guides/MCP_SETUP.md) --- ## ⚙️ Configuration ### Available Presets (24+) ```bash # 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 ```bash # Option 1: Interactive skill-seekers create --interactive # Option 2: Copy and edit a preset cp configs/react.json configs/myframework.json nano configs/myframework.json skill-seekers create --config configs/myframework.json ``` ### Config File Structure ```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 } ``` ### Where to Store Configs The tool searches in this order: 1. Exact path as provided 2. `./configs/` (current directory) 3. `~/.config/skill-seekers/configs/` (user config directory) 4. SkillSeekersWeb.com API (preset configs) --- ## 📊 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? ```bash # Force re-scrape rm -rf output/myframework_data/ skill-seekers create --config configs/myframework.json ``` ### Categories Not Good? Edit the config `categories` section with better keywords. ### Want to Update Docs? ```bash # Delete old data and re-scrape rm -rf output/godot_data/ skill-seekers create --config configs/godot.json ``` ### Enhancement Not Working? ```bash # Check if API key is set echo $ANTHROPIC_API_KEY # Try LOCAL mode instead (uses Claude Code Max, no API key needed) skill-seekers enhance output/react/ --mode LOCAL # Monitor background enhancement status skill-seekers enhance-status output/react/ --watch ``` ### GitHub Rate Limit Issues? ```bash # Set a GitHub token (5000 req/hour vs 60/hour anonymous) export GITHUB_TOKEN=ghp_your_token_here # Or configure multiple profiles skill-seekers config --github ``` --- ## 📈 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`: ```bash skill-seekers create https://docs.react.dev/ --preset quick # Fast, surface-level skill-seekers create https://docs.react.dev/ --preset standard # Balanced (default) skill-seekers create https://docs.react.dev/ --preset comprehensive # Deep, exhaustive ``` ### Lifecycle Flags ```bash skill-seekers create https://docs.react.dev/ --dry-run # Preview without scraping skill-seekers create https://docs.react.dev/ --fresh # Ignore cache, full re-scrape skill-seekers create https://docs.react.dev/ --resume # Resume interrupted job skill-seekers create https://docs.react.dev/ --skip-scrape # Re-package existing output ``` ### Health Check & Utilities ```bash skill-seekers doctor # Diagnose installation & environment skill-seekers sync-config # Detect config drift skill-seekers stream <source> # Streaming ingestion for large docs skill-seekers update output/react/ # Incremental update skill-seekers multilang <source> # Multi-language skill generation skill-seekers quality output/react/ # Quality scoring ``` ### RAG Chunking Options (package) ```bash skill-seekers package output/react/ --chunk-for-rag --chunk-tokens 512 --chunk-overlap-tokens 50 ``` ### Marketplace Publishing ```bash skill-seekers package output/react/ --marketplace --marketplace-category frontend ``` ### 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](BULLETPROOF_QUICKSTART.md)** - 🎯 **START HERE** if you're new! - **[QUICKSTART.md](docs/archive/legacy/QUICKSTART.md)** - Quick start for experienced users - **[TROUBLESHOOTING.md](TROUBLESHOOTING.md)** - Common issues and solutions - **[docs/archive/legacy/QUICK_REFERENCE.md](docs/archive/legacy/QUICK_REFERENCE.md)** - One-page cheat sheet ### Architecture - **[docs/UML_ARCHITECTURE.md](docs/UML_ARCHITECTURE.md)** - UML architecture overview with 14 diagrams - **[docs/UML/exports/](docs/UML/exports/)** - PNG diagram exports (package overview + 13 class diagrams) - **[docs/UML/html/](docs/UML/html/index.html/index.html)** - Full HTML API reference (all classes, operations, attributes) - **[docs/UML/skill_seekers.mdj](docs/UML/skill_seekers.mdj)** - StarUML project file (open with [StarUML](https://staruml.io/)) ### Guides - **[docs/reference/LARGE_DOCUMENTATION.md](docs/reference/LARGE_DOCUMENTATION.md)** - Handle 10K-40K+ page docs - **[docs/features/ENHANCEMENT_MODES.md](docs/features/ENHANCEMENT_MODES.md)** - AI enhancement modes guide - **[docs/guides/MCP_SETUP.md](docs/guides/MCP_SETUP.md)** - MCP integration setup - **[docs/features/UNIFIED_SCRAPING.md](docs/features/UNIFIED_SCRAPING.md)** - Multi-source scraping - **[docs/VIDEO_GUIDE.md](docs/VIDEO_GUIDE.md)** - Video extraction guide ### Integration Guides - **[docs/integrations/LANGCHAIN.md](docs/integrations/LANGCHAIN.md)** - LangChain RAG - **[docs/integrations/CURSOR.md](docs/integrations/CURSOR.md)** - Cursor IDE - **[docs/integrations/WINDSURF.md](docs/integrations/WINDSURF.md)** - Windsurf IDE - **[docs/integrations/CLINE.md](docs/integrations/CLINE.md)** - Cline (VS Code) - **[docs/integrations/RAG_PIPELINES.md](docs/integrations/RAG_PIPELINES.md)** - All RAG pipelines --- ## 📝 License MIT License - see [LICENSE](LICENSE) file for details --- Happy skill building! 🚀 --- ## 🔒 Security [](https://mseep.ai/app/yusufkaraaslan-skill-seekers) --- ## 💛 Sponsors <p align="center"> <a href="https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=skill_seekers"> <img src="docs/assets/atlas-cloud-logo.png" alt="Atlas Cloud" width="200"> </a> </p> [Atlas Cloud](https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=skill_seekers) — a full-modal, OpenAI-compatible AI inference platform. Skill Seekers supports it as a packaging/enhancement target via `--target atlas` with `ATLAS_API_KEY`.