openclaw-model-orchestrator
Multi-LLM orchestration for OpenClaw with fan-out, pipeline, and consensus patterns. Dispatches tasks across 40+ models using AAHP v3 inspired handoffs.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/homeofe/openclaw-model-orchestratorOpenClaw Model Orchestrator
Dispatch tasks across multiple LLMs from chat. Uses AAHP v3 structured handoffs for minimal token overhead.
Orchestration Modes
Fan-Out
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
Pipeline
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
Consensus
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
Smart Recommendations
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
Task Profiles
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 |
AAHP v3 Integration
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:
- Task context (only relevant information)
- Routing metadata (source/target model, mode)
- Differential state (only what changed)
- Constraints (output format, scope limits)
Commands
| 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 |
Configuration
In openclaw.plugin.json:
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-homeofe-openclaw-model-orchestrator": {
"enabled": true,
"auto_update": true
}
}
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