domains / families / agent-tooling / multi-agent-architect

multi-agent-architect

authentic

Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI workflows.

When to use

• Use when you need to create a new agent or multi-agent workflow from scratch
• Use when working with LangGraph state graphs, nodes, edges, or conditional routing
• Use when the user asks about agent communication, memory systems, or tool-calling pipelines
• Use when debugging or optimizing an existing LangChain/LangGraph agent system
• Use when architecting supervisor, planner, research, coding, or validation agent roles
• Use when integrating DeepAgents with hierarchical planning and delegation

When not to use

• This skill does not replace environment-specific testing, load testing, or security review before production deployment.
• Generated LangGraph code targets the current stable API — always verify method signatures against your installed version (`pip show langgraph`).
• Stop and ask for clarification if the agent's goal, tool permissions, or routing logic is ambiguous before generating a full architecture.
• DeepAgents integration patterns assume the library is installed and configured in the target environment.

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