Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Acts as a governance layer above other installed skills. It inventories available skills, scores each candidate against the task using a weighted model, applies safety gates, and executes the best option with full user visibility. An optional multi-agent brainstorming module adds business/strategy and market/execution agents for structured idea generation rounds.
The deterministic 0-100 scoring model with visible per-component breakdowns replaces guessing which skill fits a task.
When to use it
- Automatically selecting the right skill for an ambiguous or complex task
- Previewing what would execute with a dry-run before committing
- Comparing scored skill candidates side-by-side before choosing one
- Running structured multi-agent brainstorming sessions for business strategy
- Auditing installed skills, their risk levels, and required permissions
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: route this task automatically — summarize last week's sales data
- 1Normalize the request into goal, constraints, urgency, and risk profile
- 2Inventory installed skills via platform API or directory scan and manifest parsing
- 3Score each candidate on task relevance, environment fit, permission fit, latency, risk alignment, and local history
- 4Apply safety gates and request confirmation if risk level is HIGH or credentials are involved
- 5Execute the top-scoring skill and emit a structured Skill Router Report
A structured report listing scored candidates, the selected skill, safety check result, and execution outcome