Total 30,738 skills, AI & Machine Learning has 4962 skills
Showing 12 of 4962 skills
Comprehensive guide to AI SDK v6 for agent development, tool definitions, multi-step agentic workflows, and result extraction patterns
Progressive context refinement pattern for subagents. Solves the problem of agents not knowing what context they need until they start working. Uses a 4-phase loop: DISPATCH, EVALUATE, REFINE, LOOP.
Browse and search the Hence gallery (hence.sh) to discover projects built with AI coding agents. Use when the user wants inspiration, wants to see what others have built, asks about projects on Hence, or mentions searching for AI-built projects. Triggers on queries like "show me cool projects", "search Hence", "find CLI tools on Hence", or "what are people building with Claude Code".
Analyze and correct previous responses when questioned or when contradictions are detected. Use this skill when the user challenges your reasoning, points out inconsistencies, or asks 'what makes you think that?' to help you review your logic, identify errors in your previous statements, and provide accurate corrections. Useful for maintaining consistency, admitting mistakes, and rebuilding trust through transparent self-evaluation.
Model Context Protocol (MCP) server development and AI/ML integration patterns. Covers MCP server implementation, tool design, resource handling, and LLM integration best practices. Use when developing MCP servers, creating AI tools, integrating with LLMs, or when asking about MCP protocol, prompt engineering, or AI system architecture.
Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.
Multi-AI Parallel Deep Research. Triggered when users need comprehensive research, in-depth study, multi-party comparison, or comprehensive analysis covering multiple dimensions and sources for a certain topic. Suitable for complex topics (technical selection, competitor analysis, industry trends, controversial topics, etc.), not suitable for simple fact queries. Conduct parallel research through multiple AI services, cross-validate, and output a comprehensive report with citations.
Comprehensive research toolkit for discovering patterns, best practices, and technical knowledge across Web search, MCP servers, GitHub repositories, and documentation. Use when researching technologies, exploring codebases, finding examples, or gathering requirements for skill development.
LLM deployment strategies including vLLM, TGI, and cloud inference endpoints.
Generate shareable paper summaries for Discord/Slack/Twitter. Use when user provides arxiv paper(s) and wants a digestible summary to share. Triggers on phrases like "논문 요약", "paper summary", "share this paper", "디스코드에 공유", "summarize for sharing". Produces insight-centered single-paragraph summaries that explain WHY research matters, not just WHAT it does.
Advanced Gemini 3 Pro features including function calling, built-in tools (Google Search, Code Execution, File Search, URL Context), structured outputs, thought signatures, context caching, batch processing, and framework integration. Use when implementing tools, function calling, structured JSON output, context caching, batch API, LangChain, Vercel AI, or production features.
Use when building networks that grow, prune, or adapt topology during training. Routes to continual learning, gradient isolation, modular composition, and lifecycle orchestration skills.