Find the perfect capability for your agent.
Create well-formed Claude Skills with proper YAML frontmatter and clear instructions. Use when user wants to create a new skill, add capabilities to Claude, or needs help structuring a skill definition.
Meta-skill que orquesta todos los skills de prompt engineering y routing. Auto-selección y coordinación de skills basada en domain classification.
Claude Code CLI and development environment. Use for Claude Code features, tools, workflows, MCP integration, configuration, and AI-assisted development.
Expert guidance for Python AI development fundamentals, essential libraries, data structures, async programming, and best practices for AI/ML projects
Generate SQL practice problems using Gemini AI. Use when creating new problems, testing problem generation, or when user mentions "문제 생성", "generate problem".
Generate stunning photorealistic images using advanced AI models. Covers portrait photography, landscapes, product shots, architecture, and cinematic scenes. Includes prompting techniques for lighting, composition, and camera settings. USE WHEN user says 'photorealistic', 'photo realistic', 'realistic image', 'stunning photo', 'cinematic', 'portrait photo', 'product photography', 'landscape photo', 'hyper realistic', 'professional photo', or needs high-quality realistic image generation.
Project organization methodology for AI-assisted development with Claude Code or similar tools. Use when users want to set up a navigation system for large-scale AI code generation projects (10k+ lines), need to help AI maintain architectural consistency across sessions, or want to establish folder-level indexing to help AI understand project structure and locate files efficiently.
Automate all operations for maintaining the claude-skills-worth-using repository. Use when user wants to add skills, update documentation, release versions, check repository status, manage GitHub operations, or maintain the skills repository. Handles skill addition from external sources, README updates, version management, quality assurance, and repository maintenance with 85-95% time savings.
Provides three production-ready ML training examples (sentiment classification, text generation, RedAI trade classifier) with complete training scripts, deployment configs, and datasets. Use when user needs example projects, reference implementations, starter templates, or wants to see working code for sentiment analysis, text generation, or financial trade classification.
Google Gemini API 集成指南：提供 AI 分析、提示词工程、流式响应和多模态处理的最佳实践。 Use when: 需要集成 Gemini API、编写提示词、处理流式响应、多模态输入。 Triggers: "Gemini", "AI", "LLM", "提示词", "prompt", "流式", "streaming", "多模态"
Best-practice prompt engineering using research-backed patterns. Handles: transforming rough prompts into production-ready, debugging prompt issues, creating new prompts from scratch. ALWAYS researches via subagents (keeps main context clean). Triggers on: "improve prompt", "fix prompt", "create prompt", "prompt not working", "write a prompt for", "optimize prompt", "/prompt".
從 YouTube、Apple Podcast 或 Bilibili 的 URL 獲取逐字稿。 當使用者貼上影片或 podcast 連結，或說「幫我拿逐字稿」「轉成文字」時觸發。 使用 aits 命令獲取內容，回傳給使用者後續使用。
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.
This skill should be used when users want to create custom slash commands for Claude Code. It guides the creation of project-specific or personal slash commands with proper frontmatter, argument handling, and Claude Code standards.
Expert in Lighthouse Journey Timeline backend architecture, service patterns, testing, and API development using Express.js, TypeScript, and Drizzle ORM. Use when implementing backend services, APIs, controllers, database queries, authentication, permissions, error handling, testing server code, or writing migrations.
When working with JSON data in LLM prompts (especially large arrays or tabular data), consider the token-efficient TOON (Token-Oriented Object Notation) format which reduces tokens by 30-70% while maintaining lossless JSON representation and structural validation. Use for reading/writing .toon files, converting JSON↔TOON, or optimizing structured data for LLM consumption with guardrails like [N] counts and {field} headers.
Create new Claude Code skills with proper structure, modular organization, and performance optimization. Use when building new skills, refactoring existing skills, or improving skill maintainability.
