Total 50,542 skills, AI & Machine Learning has 8483 skills
Showing 12 of 8483 skills
Visualize and manage Claude Code AI agents as pixel art characters in a VS Code extension office interface
Set up the Claude Brain Logseq graph (first-time) or add a new project page. Triggers: "init brain", "setup brain", "init brain project <name>", "add project to brain". Don't fire for loads, saves, or status checks — those are handled by brain-load, brain-save, and brain-status.
A collection of Agent Skills for the Stitch MCP server: generate high-fidelity UI screens, create multi-page websites from a single prompt, produce DESIGN.md documentation, enhance vague UI prompts, convert designs to React/shadcn-ui components, and generate walkthrough videos via Remotion. Use when the user needs AI-assisted UI design generation, prompt refinement, or screen-to-code workflows. Triggers on: stitch, stitch-design, stitch-loop, enhance-prompt, react-components, remotion, shadcn-ui, screen generation, ui generation.
Build and operate multi-agent workflows with OpenAI Agents SDK (Python): define agents/tools/handoffs, add guardrails, run conversations, and debug orchestration behavior. Use when users ask for agent orchestration with OpenAI-native patterns, handoff routing, or production-ready agent loops.
Design enterprise-grade agent systems with Microsoft's agent framework patterns: role separation, workflow control, policy boundaries, and observability. Use when users need robust organizational agent workflows, governance, and maintainable multi-agent architecture.
Manages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations.
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies (supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows, synchronization and consensus, conflict resolution, fault tolerance and retries across agents, cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment (queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents, and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer), strategy-only whiteboard (enterprise-strategist), or PM planning (technical-program-manager). Use for multi-agent system, multi-agent engineer, agent orchestration, supervisor agent, agent topology, fan-out fan-in, agent handoff protocol, multi-agent workflow, agent coordination, blackboard pattern, hierarchical agents, A2A, agent DAG, multi-agent architecture.
Use when planning, running, comparing, or recording computational experiments, benchmarks, ablations, autonomous research loops, overnight runs, training runs, or exploratory variants.
Interactive lesson-level quiz for Claude Code tutorials. Tests understanding of a specific lesson (01-10) with 8-10 questions mixing conceptual and practical knowledge. Use before a lesson to pre-test, during to check progress, or after to verify mastery. Use when asked to "quiz me on hooks", "test my knowledge of lesson 3", "lesson quiz", "practice quiz for MCP", or "do I understand skills".
Migrate supported instruction files, skills, agents, and MCP config into Codex project and global files.
Conversation-first, image-first PPT generation workflow skill using GPT Image 2 for full-page visual slides packaged into PPTX files.