Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
No file changes detected in this release. - Version number updated to 1.7.19; no code or documentation changes found. - Behavior and features remain the same as the previous version.
What This Skill Does
Routes incoming tasks to the appropriate AI model via OpenRouter, then delegates execution to a sub-agent through sessions_spawn. Tasks are classified into eight tiers, including code, reasoning, creative, and vision, with configurable primary and fallback models per tier. The orchestrator never answers tasks directly.
Instead of running every task on one expensive model, it classifies work into tiers and selects the cheapest capable model per task, cutting both cost and latency.
When to use it
- Routing a code debugging request to a dedicated coding model
- Splitting a mixed task into parallel sub-agents for faster completion
- Sending screenshot analysis to a vision-capable model automatically
- Using a cheap fast model for simple status checks to reduce cost
- Delegating research queries to a search-optimized model
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: fix the null pointer bug in auth.py and write release notes
- 1Router receives the task and detects two distinct subtasks
- 2Runs router.py with --multi flag to generate separate spawn configs for CODE and CREATIVE tiers
- 3Calls sessions_spawn with the CODE-tier model for the bug fix
- 4Calls sessions_spawn with the CREATIVE-tier model for the release notes
- 5Returns combined results from both sub-agents to the user
Bug fix applied by code model, release notes written by creative model, both results returned together
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.