Total 50,988 skills, AI & Machine Learning has 8537 skills
Showing 12 of 8537 skills
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the `deepagents` package. Use when users need to create agents with built-in planning/filesystem/subagents, configure middleware/backends/checkpointing/HITL, migrate from `create_react_agent` or `create_agent`, scaffold projects with repo scripts, validate agent config files, and confirm compatibility with current LangChain/LangGraph/LangSmith docs.
Create, list, remove, and run scheduled autonomous Claude Code agents. Agents run on a timer via macOS launchd, execute any prompt headlessly, and deliver results via Beeper messages and macOS notifications. Use for recurring research, monitoring, overnight builds, or any task you want Claude to do on autopilot.
Generate sprites and game assets using the SpriteCook MCP tools. Use when building games and the user needs sprites, pixel art, characters, items, tilesets, textures, icons, or UI elements. Also use when asked to create, generate, or make game art assets.
Complete guide for calling AI models with CloudBase - covers JS/Node SDK and WeChat Mini Program. Text generation, streaming, and image generation.
Generate AGENTS.md and AI configuration files for your project. Use when the user wants to create agent instructions, set up AI configs, or says "create AGENTS.md", "configure my AI assistant", or "generate agent files".
Use when building MCP servers in TypeScript, Python, or C#; when implementing tools, resources, or prompts; when configuring Streamable HTTP transport; when migrating from SSE; when adding OAuth authentication; when seeing MCP protocol errors
Agent Script DSL development skill for Salesforce Agentforce. Enables writing deterministic agents in a single .agent file with FSM architecture, instruction resolution, and hybrid reasoning. Covers syntax, debugging, testing, and CLI deployment.
Comprehensive knowledge of amplihack framework architecture, patterns, and usage
Structured multi-perspective debate for important architectural decisions and complex trade-offs
Fork terminal sessions to spawn parallel AI agents or CLI commands in new terminal windows. Supports git worktrees for isolated parallel development.
Apply quantization to reduce memory by 4-32x. Enable HNSW indexing for 150x faster search. Configure caching strategies and implement batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors. Deploy these optimizations to achieve 12,500x performance gains.
Analyze how competitors would rank in AI search results for a given topic or query. Triggers on "analyze competition", "competitor analysis", "what ranks for", "who would rank", "competitive landscape".