Total 50,865 skills, AI & Machine Learning has 8516 skills
Showing 12 of 8516 skills
Run the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table
Use this skill whenever a user asks to generate, create, draw, render, or edit images with GPT Image 2 / gpt-image-2, text-to-image, reference-image editing, inpainting, posters, typography, Chinese text, UI mockups, diagrams, or gallery prompts. Analyze the user's prompt, search the bundled Reference Gallery/craft files for matching design patterns, confer on direction when useful, then call the packaged `gpt-image` CLI or bundled `scripts/generate.py`. Do not write new image-generation code unless explicitly asked to modify this repo.
Orchestrates group discussions between installed BMAD agents, enabling natural multi-agent conversations where each agent is a real subagent with independent thinking. Use when user requests party mode, wants multiple agent perspectives, group discussion, roundtable, or multi-agent conversation about their project.
Run yourself in a loop with programmatic control via the Agent SDK. Use for long-running tasks like optimization, research, iterative improvement, multi-agent coordination, or any multi-step workflow where you need to repeat, branch, or track progress.
Structured web research framework for AI agents. Teaches your agent to conduct multi-source research, synthesize findings into actionable briefs, maintain a research library, and track evolving topics over time. Use when you need market research, competitor analysis, topic deep-dives, or ongoing monitoring of trends and news. Works with any agent that has web search capabilities.
Use OpenAI Codex from inside Claude Code for code reviews and delegated background tasks.
Analyse agent execution to find wasted tool calls, wrong turns, and blind alleys. Optimise agents to reach their goal in the fewest turns, tokens, and least time. Recommend harness/model changes — never apply without user approval.
Self-referential loop until task completion with architect verification
Summarizes very long texts (books, handbooks, biographies, codebases) using hierarchical multi-pass extraction with cheap model armies. Produces structured knowledge maps, not just summaries. Use when processing 50+ page documents, professional handbooks, career biographies, or any text too large for a single context window. Activate on "summarize book", "summarize handbook", "long document", "extract knowledge", "distill text", "professional biography". NOT for short text summarization (<10 pages), real-time chat summarization, or code documentation (use technical-writer).
Publish and deploy C# MCP servers. Covers NuGet packaging for stdio servers, Docker containerization for HTTP servers, Azure Container Apps and App Service deployment, and publishing to the official MCP Registry. USE FOR: packaging stdio MCP servers as NuGet tools, creating Dockerfiles for HTTP MCP servers, deploying to Azure Container Apps or App Service, publishing to the MCP Registry at registry.modelcontextprotocol.io, configuring server.json for MCP package metadata, setting up CI/CD for MCP server publishing. DO NOT USE FOR: publishing general NuGet libraries (not MCP-specific), general Docker guidance unrelated to MCP, creating new servers (use mcp-csharp-create), debugging (use mcp-csharp-debug), writing tests (use mcp-csharp-test).
Implement features from a validated RootSpec specification — test-driven and autonomous. Use this when a user wants to build, code, or implement features from their spec, or when they want to make failing tests pass.
Deep dive into Claude Code source code to learn production-grade AI agent architecture patterns