Total 50,552 skills, AI & Machine Learning has 8484 skills
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Optimize AGENTS.md and rules for token efficiency. Auto-invoked when user asks about improving agent instructions, compressing AGENTS.md, or making rules more effective.
Simulate a senior high school Grade 3 liberal arts tutor, using heuristic teaching methods to tutor comprehensive liberal arts problems in politics, history, and geography. Focus on cultivating students' abilities of understanding, memory, and analysis. Applied when students raise liberal arts questions, request explanations of historical events, geographical phenomena, or political principles.
Meta-skill for designing orchestrator+phases structured workflow skills. Creates SKILL.md coordinator with progressive phase loading, TodoWrite patterns, and data flow. Triggers on "design workflow skill", "create workflow skill", "workflow skill designer".
Use this skill when building AI applications with OpenAI Agents SDK for JavaScript/TypeScript. The skill covers both text-based agents and realtime voice agents, including multi-agent workflows (handoffs), tools with Zod schemas, input/output guardrails, structured outputs, streaming, human-in-the-loop patterns, and framework integrations for Cloudflare Workers, Next.js, and React. It prevents 9+ common errors including Zod schema type errors, MCP tracing failures, infinite loops, tool call failures, and schema mismatches. The skill includes comprehensive templates for all agent types, error handling patterns, and debugging strategies. Keywords: OpenAI Agents SDK, @openai/agents, @openai/agents-realtime, openai agents javascript, openai agents typescript, text agents, voice agents, realtime agents, multi-agent workflows, agent handoffs, agent tools, zod schemas agents, structured outputs agents, agent streaming, agent guardrails, input guardrails, output guardrails, human-in-the-loop, cloudflare workers agents, nextjs openai agents, react openai agents, hono agents, agent debugging, Zod schema type error, MCP tracing failure, agent infinite loop, tool call failures, schema mismatch agents
Complete guide for OpenAI's Assistants API v2: stateful conversational AI with built-in tools (Code Interpreter, File Search, Function Calling), vector stores for RAG (up to 10,000 files), thread/run lifecycle management, and streaming patterns. Both Node.js SDK and fetch approaches. ⚠️ DEPRECATION NOTICE: OpenAI plans to sunset Assistants API in H1 2026 in favor of Responses API. This skill remains valuable for existing apps and migration planning. Use when: building stateful chatbots with OpenAI, implementing RAG with vector stores, executing Python code with Code Interpreter, using file search for document Q&A, managing conversation threads, streaming assistant responses, or encountering errors like "thread already has active run", vector store indexing delays, run polling timeouts, or file upload issues. Keywords: openai assistants, assistants api, openai threads, openai runs, code interpreter assistant, file search openai, vector store openai, openai rag, assistant streaming, thread persistence, stateful chatbot, thread already has active run, run status polling, vector store error
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining).
Advanced sub-skill for scikit-learn focused on model interpretability, feature importance, and diagnostic tools. Covers global and local explanations using built-in inspection tools and SHAP/LIME integrations.
Agent Orchestration Rules
Write structured VGL (Visual Generation Language) JSON prompts for Bria's FIBO image generation models. Use this skill when creating detailed image descriptions in JSON format for text-to-image generation, image editing, inpainting, outpainting, background generation, or captioning. Triggers include requests to write structured prompts, create VGL JSON, describe images for AI generation, or work with Bria/FIBO's structured_prompt format. Also use when converting natural language image requests into the deterministic JSON schema required by FIBO models.
Use when generating visual assets with Bria.ai - product photos, hero images, icons, backgrounds. Includes batch generation (multiple images concurrently), pipeline workflows (generate → edit → remove background), and parallel API patterns. Use for websites, presentations, e-commerce catalogs, or any task needing multiple AI-generated images.
View Langfuse prompts. Use when checking prompt contents, comparing versions, or debugging prompt issues.
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.