Total 56,830 skills, AI & Machine Learning has 9448 skills
Showing 12 of 9448 skills
Instructions for using the ModelMix Node.js library to interact with multiple AI LLM providers through a unified interface. Use when integrating AI models (OpenAI, Anthropic, Google, Groq, Perplexity, Grok, etc.), chaining models with fallback, getting structured JSON from LLMs, adding MCP tools, streaming responses, or managing multi-provider AI workflows in Node.js.
Search data using vector similarity, full-text keywords, or hybrid methods with Reciprocal Rank Fusion (RRF). Use when setting up embeddings for search, configuring full-text indexing, writing vector_search/text_search/rrf SQL queries, using the /v1/search HTTP API, or configuring vector engines like S3 Vectors.
Set up Claude Code context for a project. Analyzes tech stack, installs relevant skills from skills.sh, generates custom skills, and configures MCP servers. Use when starting new project, setting up AI context, or asking "set up project", "configure AI", "what skills do I need".
Self-improve AI Factory skills based on project context, accumulated patches, and codebase patterns. Analyzes what went wrong, what works, and enhances skills to prevent future issues. Use when you want to make AI smarter for your project.
Query the bundled research knowledge graph for methodology guidance. Routes questions through a 3-tier knowledge base — WHY (research claims), HOW (guidance docs), WHAT IT LOOKS LIKE (domain examples) — plus structured reference documents. Returns research-backed answers grounded in specific claims with practical application to the user's system. Triggers on "/ask", "/ask [question]", "why does my system...", "how should I...".
Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and paper discovery/evaluation criteria.
Vertex Ai Deployer - Auto-activating skill for ML Deployment. Triggers on: vertex ai deployer, vertex ai deployer Part of the ML Deployment skill category.
US Stock Investment Research Assistant. Supports Gemini Deep Research or Claude Native Deep Research (7-Phase + GoT). Use when analyzing 10-K/10-Q reports or generating investment research reports.
Expert-level manufacturing systems, Industry 4.0, production optimization, quality control, and smart factory solutions
Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).
Set up and run Ralph Wiggum loop - autonomous AI coding with clean slate iterations, PRD-driven features, and CI quality gates. Use for long-running autonomous coding tasks.
Creates and registers Tambo components - generative (AI creates on-demand) and interactable (pre-placed, AI updates). Use when defining components, working with TamboComponent, withInteractable, propsSchema, or registering components for AI to render or update.