chore(sync): mirror docs from openclaw/openclaw@7686136419

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---
summary: "Run parallel specialist agents without clogging shared model and tool capacity"
title: "Parallel specialist lanes"
sidebarTitle: "Specialist lanes"
read_when:
- You route group chats to dedicated agents
- You want parallel work without one long task blocking every chat
- You are designing a multi-agent operations setup
status: active
---
Parallel specialist lanes let one Gateway route different chats or rooms to
different agents, while keeping the user experience fast. The trick is to treat
parallelism as a scarce-resource design problem, not just as "more agents".
## First principles
A specialist lane only improves throughput when it reduces contention for the
real bottlenecks:
- **Session locks**: only one run should mutate a given session at a time.
- **Global model capacity**: all visible chat runs still share provider limits.
- **Tool capacity**: shell, browser, network, and repository work can be slower
than the model turn itself.
- **Context budget**: long transcripts make every future turn slower and less
focused.
- **Ownership ambiguity**: duplicate agents doing the same job waste capacity.
OpenClaw already serializes runs per session and caps global parallelism through
the [command queue](/concepts/queue). Specialist lanes add policy on top:
which agent owns which work, what stays in chat, and what becomes background
work.
## Recommended rollout
### Phase 1: lane contracts + background heavy work
Give every lane a written contract in its workspace and system prompt:
- **Purpose**: the work this lane owns.
- **Non-goals**: work it should hand off instead of attempting.
- **Chat budget**: quick answers stay in chat; long tasks should acknowledge
briefly, then run in a background sub-agent or task.
- **Handoff rule**: when another lane owns the work, say where it should go and
provide a compact handoff summary.
- **Tool-risk rule**: prefer the smallest tool surface that can do the job.
This is the cheapest phase and fixes most clogging: one coding job no longer
turns the research lane into molasses, and each chat keeps its own context clean.
### Phase 2: priority and concurrency controls
Tune queue and model capacity around the business value of each lane:
```json5
{
agents: {
defaults: {
maxConcurrent: 4,
subagents: { maxConcurrent: 8 },
},
},
messages: {
queue: {
mode: "collect",
debounceMs: 1000,
cap: 20,
drop: "summarize",
},
},
}
```
Use direct/personal chats and production-ops agents for high-priority work. Let
research, drafting, and batch coding move to background tasks when the system is
busy.
### Phase 3: coordinator / traffic controller
Add a small coordinator pattern once multiple lanes are active:
- Track active lane tasks and owners.
- Detect duplicate requests across groups.
- Route handoff summaries between lanes.
- Surface only blockers, completed results, and decisions the human must make.
Do not start here. A coordinator without lane contracts just coordinates chaos.
## Minimal lane contract template
```md
# Lane contract
## Owns
- <job this lane is responsible for>
## Does not own
- <work to hand off>
## Chat budget
- Answer quick questions directly.
- For multi-step, slow, or tool-heavy work: acknowledge briefly, spawn/background
the work, then return the result when complete.
## Handoff
If another lane owns the request, reply with:
- target lane
- objective
- relevant context
- exact next action
## Tool posture
Use the smallest tool surface that can complete the task. Avoid broad shell or
network work unless this lane explicitly owns it.
```
## Related
- [Multi-agent routing](/concepts/multi-agent)
- [Command queue](/concepts/queue)
- [Sub-agents](/tools/subagents)

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