Multi-Agent Routing is the 📝OpenClaw orchestration system that enables multiple isolated agent instances to operate within a single gateway process, with inbound messages routed to the right agent based on channel, account, or peer identity.

Multi-Agent Routing is the mechanism that turns OpenClaw from a single-agent runtime into a coordinated ecosystem. Each agent in the system maintains its own workspace files (📝SOUL.md, 📝IDENTITY.md, 📝TOOLS.md, 📝SKILLS.md, 📝MEMORY.md, 📝USER.md, 📝HEARTBEAT.md, 📝BOOTSTRAP.md, 📝AGENTS.md), authentication profile, and session store. The routing layer ensures that a message arriving via Slack lands at the right agent, that responses go back through the right channel, and that no agent sees state from another agent's conversations unless explicit delegation occurs.

Key Facts

Category: Distributed agent orchestration
Parent system: OpenClaw
Routing dimensions: Channel, account, peer identity, message content
Isolation model: Per-agent workspace, authentication, and session state
Documentation: docs.openclaw.ai/concepts/multi-agent

How Routing Works

Inbound messages flow through a deterministic binding layer that decides which agent should handle them. Bindings can be defined by:

Channel — Slack workspace, WhatsApp number, Telegram chat, Discord server
Account — which OpenClaw account the message belongs to
Peer identity — who sent the message (user ID, email, phone)
Message content — keyword or pattern-based routing for specialized agents

Once an agent is selected, the gateway spawns a session with that agent's full workspace configuration loaded. The session inherits the agent's personality, tool set, and memory — no cross-contamination from other agents in the system.

Why It Matters

Most agent frameworks force a choice between scale and isolation: either you run many agents as separate processes (operationally expensive, hard to coordinate) or you run a single agent serving many users (no per-user isolation, no specialization). Multi-Agent Routing splits the difference — one gateway process, many isolated agents, with deterministic routing keeping each conversation in the right hands.

This is what makes large multi-agent ecosystems operationally tractable. Each specialist agent has its own SOUL, IDENTITY, and TOOLS, but they all share infrastructure, MCP connections, and a single observability surface.

FAQ

Can agents share state across the gateway?

Selectively, yes. Each agent has its own MEMORY.md and session store, but shared resources like 📝MCP servers, common skills, and read-only knowledge bases can be accessed by multiple agents. State sharing requires explicit configuration; the default is isolation.

How does routing handle agent-to-agent delegation?

When a primary agent invokes a sub-agent (per AGENTS.md), the gateway spawns a child session for the sub-agent and returns the result to the primary. The routing layer treats delegations as internal calls rather than new inbound messages.

What happens if no binding matches?

A fallback agent (typically the primary) handles unrouted messages. AGENTS.md can also define escalation rules for ambiguous routing.

Is Multi-Agent Routing OpenClaw-specific?

The pattern generalizes — any agent framework can implement deterministic routing. OpenClaw's specific implementation pairs it tightly with the markdown-file agent definition system (workspace files, personality config), which is what makes spawning isolated agents cheap.

📝OpenClaw — the platform Multi-Agent Routing is built on
📝AGENTS.md — registry of sub-agents available for delegation
📝SKILLS.md — capability registry (different abstraction layer)
📝MCP — protocol for shared tool access across agents

📝Brian Bot's implementation extends this architecture to coordinate specialized agents across One Inc's venture studio operations and my personal workflows — context-aware automation that runs across organizational scope without losing the per-domain personality that makes each agent useful.