Dispatch tasks across multiple LLMs from chat. Uses AAHP v3 structured handoffs for minimal token overhead.
Split a task into parallel subtasks, each executed by a different model.
A planner model decomposes the task, workers execute in parallel, a reviewer merges results.
/orchestrate --mode fan-out --task "Build a REST API with auth" --planner copilot-opus --workers copilot52c,grokfast --reviewer copilot-sonnet46
Chain models sequentially. Each model refines the previous model's output.
Ideal for plan -> implement -> review -> polish workflows.
/orchestrate --mode pipeline --task "Design and implement a caching layer" --planner copilot-opus --workers copilot52c,copilot-sonnet46 --reviewer copilot-opus
Send the same question to multiple models, then synthesize the best answer.
Identifies agreement, disagreement, and unique insights across models.
/orchestrate --mode consensus --task "What are the security risks of this API design?" --workers copilot-opus,gemini25,sonnet --reviewer copilot-opus
The orchestrator auto-classifies tasks and recommends optimal model combinations:
/orchestrate recommend "Build a REST API with JWT auth"
Returns: task classification, recommended planner/workers/reviewer, reasoning, and a ready-to-run command.
Use help as any flag value for context-aware recommendations:
/orchestrate --task "Audit security" --planner help
Pre-configured model combinations optimized for common task types:
| Profile | Planner | Workers | Reviewer | Use Case |
|---|---|---|---|---|
| --------- | --------- | --------- | ---------- | ---------- |
| coding | copilot-opus | copilot52c, grokfast | copilot-sonnet46 | Feature development |
| research | gemini25 | gemini-flash, copilot-flash | copilot-opus | Analysis, investigation |
| security | copilot-opus | copilot-sonnet46, gemini25 | sonnet | Security audits |
| review | copilot-opus | copilot-sonnet46, copilot-sonnet | copilot-opus | Code/design review |
| bulk | haiku | copilot-flash, gemini25-flash, gpt5mini | haiku | Mass operations |
All model-to-model communication uses structured AAHP v3 handoff objects instead of raw chat history. This achieves up to 98% token reduction compared to naive context passing. Each handoff contains:
| Command | Description |
|---|---|
| --------- | ------------- |
/orchestrate help | Show help and available modes |
/orchestrate models | List all available models with aliases |
/orchestrate recommend "task" | Get model recommendations for a task |
/orchestrate --task "..." [flags] | Execute orchestration |
In openclaw.plugin.json:
{
"config": {
"defaultPlanner": "copilot-opus",
"defaultReviewer": "copilot-sonnet46",
"defaultWorkers": ["copilot52c", "grokfast", "copilot51"],
"maxConcurrent": 4,
"taskProfiles": { ... }
}
}
共 2 个版本