106 lines
2.8 KiB
Markdown
106 lines
2.8 KiB
Markdown
# OpenClaw Multi-Agent Workflows - 4 Levels Explained
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**Source:** https://www.reddit.com/r/openclaw/comments/1r2euvp/this_is_how_ive_learned_to_create_multiagent/
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**Summarized:** 2026-02-23
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---
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## TL;DR
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OpenClaw has **4 levels of multi-agent support** built-in, from simple persistent agents to full A2A Protocol orchestration. No Docker required for levels 1-3—they all run in a single gateway process.
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---
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## Level 1: Multiple Persistent Agents (Built-in)
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Define isolated agents in config, each with their own workspace, system prompt, model, and tools:
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```yaml
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agents:
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list:
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- id: researcher
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default: true
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workspace: ~/.openclaw/workspace-research
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- id: coder
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workspace: ~/.openclaw/workspace-code
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bindings:
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- agentId: researcher
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match: { channel: telegram, accountId: research-bot }
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- agentId: coder
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match: { channel: discord, guildId: "123456" }
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```
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Each agent has **full isolation**: separate session history, model config, tool permissions.
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---
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## Level 2: Agent-to-Agent Communication (Built-in)
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Enable `tools.agentToAgent` for agents to talk via `sessions_send`:
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```yaml
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tools:
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agentToAgent:
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enabled: true
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allow: ["researcher", "coder", "writer"]
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```
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- Ping-pong conversations (up to 5 turns by default)
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- `sessions_spawn` for background sub-agents that report back
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- Closest to "orchestrator delegates to specialist" pattern
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---
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## Level 3: Cross-Agent Delegation (3-Level Hierarchy)
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Work around single-level limits:
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```
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Orchestrator (main agent)
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├─ sessions_send → Specialist A (sibling main agent)
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│ ├─ sessions_spawn → subagent A1
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│ └─ sessions_spawn → subagent A2
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└─ sessions_send → Specialist B (sibling main agent)
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├─ sessions_spawn → subagent B1
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└─ sessions_spawn → subagent B2
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```
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Config uses `subagents.allowAgents` for cross-agent spawning.
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---
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## Level 4: True Multi-Agent Orchestration (A2A Protocol)
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For advanced use cases with intelligent routing, review, retries, synthesis:
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- **a2a-adapter**: Wraps OpenClaw agents as A2A Protocol servers
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- Mix-and-match: OpenClaw + CrewAI + LangChain + n8n
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- Can run as local Python processes or remote agents
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Example:
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```python
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from a2a_adapter import load_a2a_agent, serve_agent
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adapter = await load_a2a_agent({
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"adapter": "openclaw",
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"agent_id": "researcher",
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"thinking": "low",
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"async_mode": True,
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})
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serve_agent(agent_card=agent_card, adapter=adapter, port=9001)
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```
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---
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## Key Takeaways
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| Level | Complexity | Setup |
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|-------|-----------|-------|
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| 1 | Low | Config only |
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| 2 | Low-Medium | Config + enable tool |
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| 3 | Medium | Config + cross-agent permissions |
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| 4 | High | A2A Protocol + external orchestrator |
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**Bottom line:** OpenClaw's built-in multi-agent (levels 1-3) requires only `~/.openclaw/config.yaml` changes—no additional infrastructure needed.
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