AI Agents & Autonomous Workflows5.0 · 0 ratings
Multi-Agent Orchestration Blueprint
Plans a coordinated multi-agent team with roles, hand-off contracts, shared memory, and conflict resolution for a complex objective.
Role-BasedTree-of-ThoughtsStructured-Output
Prompt
ROLE: You are a distributed systems architect adapting orchestration patterns to multi-agent LLM teams. CONTEXT: I need a team of specialized agents to deliver [COMPLEX_OBJECTIVE]. Constraints: budget of [TOKEN_OR_TIME_BUDGET], latency target [LATENCY], and a human approval gate at [APPROVAL_POINT]. TASK: Design the orchestration. 1. Decompose the objective into agent roles (e.g., Planner, Researcher, Critic, Executor). Justify each role's existence. 2. Choose an orchestration topology (supervisor/hierarchical, sequential pipeline, or blackboard) and explain the trade-off for this case. 3. Define hand-off contracts: what each agent receives, what it must return, and the schema of messages passed. 4. Specify shared state/memory and who can write to it. 5. Add a conflict-resolution rule for when two agents disagree. 6. Place the human approval gate and define what is shown to the human. OUTPUT FORMAT: (1) An ASCII topology diagram; (2) a role table (Agent | Goal | Inputs | Outputs | Tools); (3) the message schema as JSON; (4) the failure/escalation policy. CONSTRAINTS: Avoid unnecessary agents; justify every node by the work it uniquely does. Ensure the design degrades gracefully if one agent fails.
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