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Found 48 Skills
Design and coordinate multi-agent systems where specialized agents work together to solve complex problems. Covers agent communication, task delegation, workflow orchestration, and result aggregation. Use when building coordinated agent teams, complex workflows, or systems requiring specialized expertise across domains.
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
OpenMAIC — Open Multi-Agent Interactive Classroom platform for generating immersive AI-powered learning experiences with slides, quizzes, simulations, and multi-agent discussions.
Guide for giving your AI agents capabilities through tools. Helps you identify what your AI needs to do, create tool definitions, and attach them in a way that makes sense for your framework.
Build autonomous RAG agents that reason, plan, and use tools for complex retrieval tasks. Use this skill when simple retrieve-and-generate isn't enough. Activate when: agentic RAG, RAG agent, multi-step retrieval, tool-using RAG, autonomous retrieval, query decomposition.
Advanced RAG with Self-RAG, Corrective-RAG, and knowledge graphs. Use when building agentic RAG pipelines, adaptive retrieval, or query rewriting.
ADHD-optimized task state machine with abandonment detection and interventions. Use when: (1) user initiates any task, (2) providing solutions to problems, (3) detecting context switches, (4) user says "done", "completed", "finished", (5) session ends with pending tasks, (6) >30 minutes since solution provided. Tracks complexity, clarity, domain (BUSINESS/MICHAEL/FAMILY/PERSONAL), and triggers interventions.
Orchestrates single user-invocable skill across 3 parallel scenarios with synchronized state and progressive difficulty. Use when running multi-scenario demos, comparative testing, or progressive validation workflows.
Chain multiple AI steps into one reliable pipeline. Use when your AI task is too complex for one prompt, you need to break AI logic into stages, combine classification then generation, do multi-step reasoning, build a compound AI system, orchestrate multiple models, or wire AI components together. Powered by DSPy multi-module pipelines.
Multi-agent orchestration and state management.
Use when analyzing repositories, conducting deep research on codebases, performing architecture reviews, or exploring large projects. Use when the user wants to research or analyze a git repo, a GitHub link, or a repository URL.
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.