agent-orchestration

Activates autonomous code improvement — competing strategies, benchmarking, tournament selection

Cross-session persistent context — remember project decisions, architecture choices, and team conventions

Activates parallel team execution — N coordinated agents working simultaneously on independent subtasks

Evidence-driven tracing — orchestrate competing hypotheses to explain observed outcomes

Activates parallel execution — fires multiple agents simultaneously for independent tasks

Agentic memory system for writers — track characters, relationships, scenes, themes, and maintain consistency

Add educational comments to code files to transform them into effective learning resources. Explains the "why" behind syntax, idioms, and design choices, aligned with the learner's knowledge level and educational goals.

Add persistent memory to AI coding agents — file-based, vector, and semantic search memory systems that survive between sessions. Use when a user asks to "remember this", "add memory to my agent", "persist context between sessions", "build a knowledge base for my agent", "set up…

Run AI agent code safely in isolated sandboxes with resource limits, audit trails, and kill switches. Use when someone asks to "sandbox my agent", "run agent code safely", "add guardrails to AI agent", "isolate agent execution", "audit agent actions", "prevent agent from…

Coordinate multiple AI agents working together on complex tasks — routing, handoffs, consensus, memory sharing, and quality gates. Use when tasks involve building multi-agent systems, coordinating specialist agents in a pipeline, implementing agent-to-agent communication,…

Parallel read-only multi-agent root-cause investigation for bugs and regressions. Use when: investigating bugs, finding root causes, tracing regressions, or diagnosing failures with multi-agent swarm.

Run Codex CLI, Claude Code, or other coding agents as background processes for programmatic control. Use when a user asks to run a coding agent, delegate a task to another AI, spawn a sub-agent, run Claude Code in the background, or orchestrate multiple coding agents on separate…

You are an expert in CrewAI, the framework for orchestrating autonomous AI agents working together as a crew. You help developers define agents with specific roles, goals, and tools, then organize them into crews that collaborate on complex tasks — with sequential, parallel, and…

Build self-improving AI agents using Hermes patterns — agents that learn from interactions, update their own instructions, and adapt their behavior over time. Use when: building agents that improve with usage, creating adaptive AI assistants, implementing agent self-reflection.

AI agent for building, running, and debugging iOS apps on simulator via XcodeBuildMCP. Use when: running iOS apps, inspecting simulator UI, capturing logs, or diagnosing runtime behavior.

Build stateful, multi-step AI agents and workflows with LangGraph. Use when a user asks to create AI agents with complex logic, build multi-agent systems, implement human-in-the-loop workflows, create state machines for LLMs, build agentic RAG, implement tool-calling agents with…

Offload tasks to local LLMs via LM Studio. Use when a user asks to run local models with LM Studio, save API costs by using local LLMs, create subagents with local models, offload summarization or classification to a local model, or use LM Studio's API for batch processing.…

Build Model Context Protocol (MCP) servers that connect AI agents to external services and data sources. Use when a user asks to create an MCP server, build an MCP tool, connect an AI agent to an API, create a tool server for Claude, build MCP resources, or expose a…

Build multi-agent AI systems with Microsoft's Agent Framework (formerly Semantic Kernel Agents). Use when: defining AI agents, orchestrating multi-agent workflows (sequential, parallel, conditional), creating custom agents in Python or .NET, using built-in agents…

Build asynchronous coding agents using LangChain's Open SWE framework — agents that plan, code, test, and iterate on software engineering tasks. Use when: building coding bots, automating issue resolution, creating SWE agents that work on repos asynchronously.

You are an expert in the OpenAI Agents SDK (formerly Swarm), the official framework for building multi-agent systems. You help developers create agents with tool calling, guardrails, agent handoffs, streaming, tracing, and MCP integration — building production-grade AI agents…

Plan and execute large refactor efforts with parallel multi-agent analysis. Use when: refactoring many files, splitting workstreams, or coordinating sub-agents for batch code changes.

Parallel read-only multi-agent code review of git diffs. Use when: reviewing diffs for regressions, security risks, performance issues, or wanting a parallel review swarm.

You are an expert in smolagents, Hugging Face's minimalist agent framework. You help developers build AI agents that write and execute Python code to solve tasks, use tools from the Hugging Face Hub, chain multiple agents together, and run on any LLM (OpenAI, Anthropic, local…

Build AI agent teams that collaborate on projects using Squad framework. Use when: orchestrating multiple specialized agents, building collaborative AI workflows, delegating complex tasks across agent teams.