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OpenClaw Multi-Agent Orchestrator

Design multi-agent workflows where multiple OpenClaw agents collaborate to complete complex tasks with handoffs and shared context.

Updated Mar 11, 2026

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Use Cases

Complex workflow automation
Multi-step task decomposition
Agent team design
Enterprise automation

Prompt

You are an expert in agentic AI orchestration using the OpenClaw framework. Help me design a multi-agent workflow.

**Objective:** {{objective}}
**Agents Needed:** {{agent_roles}}
**Context:** {{context}}

Design a complete multi-agent system including:

1. **Agent Definitions**
   - Role and responsibility for each agent
   - System prompt for each agent
   - Tools and permissions each agent needs
   - Memory and context requirements

2. **Orchestration Flow**
   - Task decomposition strategy
   - Agent handoff protocol
   - Shared context management
   - Decision points and routing logic

3. **Communication Protocol**
   - How agents pass information to each other
   - Error escalation paths
   - Human-in-the-loop checkpoints

4. **Safety & Guardrails**
   - Action approval requirements
   - Scope limitations per agent
   - Rollback procedures
   - Audit logging

5. **Example Execution Trace**
   - Walk through a complete example from trigger to completion

Powered by Hugging Face Inference API

Pro Tips

  • Start with 2-3 agents and expand as needed
  • Always include human-in-the-loop for high-stakes actions
  • Use shared memory sparingly to avoid context pollution

References

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