One of OpenClaw's most powerful features is the ability to orchestrate multiple AI agents that work together. In this guide, we'll explore how to build a multi-agent system.
What Are Multi-Agent Systems?
Instead of relying on a single AI agent, multi-agent systems use specialized agents:
- Research Agent — Gathers and synthesizes information
- Writer Agent — Creates content based on research
- Review Agent — Checks quality and accuracy
- Publisher Agent — Formats and distributes content
Architecture Overview
# agent-config.yaml
orchestrator:
type: sequential
agents:
- name: researcher
model: claude-sonnet
skills: [web-search, document-reader]
- name: writer
model: claude-opus
skills: [content-writer, seo-optimizer]
- name: reviewer
model: claude-sonnet
skills: [grammar-check, fact-checker]
- name: publisher
model: claude-haiku
skills: [wordpress-api, social-media]Communication Patterns
- Sequential — Each agent passes output to the next in a pipeline
- Parallel — Multiple agents work simultaneously on different tasks
- Collaborative — Agents discuss and iterate on shared output
Building Your First Multi-Agent Workflow
openclaw workflow create content-pipeline --agents researcher,writer,reviewer,publisher --pattern sequential --trigger "manual"Monitoring and Debugging
- Real-time agent activity dashboard
- Message flow visualization
- Per-agent cost tracking
- Error handling and retry policies
Best Practices
- Start with 2-3 agents and add complexity gradually
- Use the right model size for each agent's task
- Implement clear error handling between agents
- Monitor costs per agent to optimize spending
- Test each agent independently before orchestrating