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Found 1,335 Skills
Guide developers through creating ChatGPT apps. Covers the full lifecycle: brainstorming ideas against UX guidelines, bootstrapping projects, implementing tools/widgets, debugging, running dev servers, deploying and connecting apps to ChatGPT. Use when a user wants to create or update a ChatGPT app / MCP server for ChatGPT, or use the Skybridge framework.
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.
Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation
DSPy declarative framework for automatic prompt optimization treating prompts as code with systematic evaluation and compilers
Room-based exploration with narrative evidence collection
Comprehensive skill for building, deploying, and managing multi-agent AI systems with Agno framework
Answers AI agent evaluation methodology questions with practical, opinionated guidance grounded primarily in Microsoft's agent evaluation ecosystem (MS Learn, Eval Scenario Library, Triage & Improvement Playbook, Eval Guidance Kit) supplemented by select industry sources.
Build new agent skills. Use when creating diagnostic frameworks, CLI tools, or data-driven generators that follow the established skill patterns.
Build AI agents with structured access to Sanity content via Context MCP. Covers Studio setup, agent implementation, and advanced patterns like client-side tools and custom rendering.
Guide for designing effective MCP servers with agent-friendly tools. Use when creating a new MCP server, designing MCP tools, or improving existing MCP server architecture.
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines