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How to Build Multi-Agent Workflows

Design and implement multi-agent workflows where specialized AI agents collaborate on complex tasks, each handling a specific aspect of your development pipeline.

  1. 1

    Define Agent Responsibilities

    Break your workflow into discrete tasks and assign each to a specialized agent. For example: one agent for code generation, another for testing, and a third for documentation.

  2. 2

    Create Agent Skills

    Write a SKILL.md for each agent that clearly defines its role, capabilities, and output format. Each skill should be focused on a single responsibility.

  3. 3

    Design the Orchestration Flow

    Define how agents communicate and pass results between each other. Use a coordinator skill that manages the workflow sequence and handles data flow between agents.

  4. 4

    Implement Handoff Protocols

    Establish clear input/output contracts between agents. Each agent should produce structured output that the next agent in the chain can consume without ambiguity.

  5. 5

    Add Error Handling

    Build retry logic and fallback paths into your orchestration. If one agent fails, the coordinator should be able to retry, skip, or route to an alternative agent.

  6. 6

    Monitor and Optimize

    Track agent performance metrics like completion time, success rate, and output quality. Use this data to refine individual agent skills and the overall workflow.