Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Analyzes AI agent skill code to detect mismatches between a skill's declared purpose and what it actually accesses. Flags sensitive path reads, environment variable access, network calls, and subprocess spawning that fall outside stated functionality. Outputs a risk rating and itemized mismatch list.
Manual code review doesn't score the gap between what a skill claims to do and what it actually touches, so automated mismatch detection catches over-permissioned skills that look harmless from their descriptions alone.
When to use it
- Auditing a third-party skill before adding it to an agent
- Checking if a code formatter reads credential files
- Scanning marketplace skills for undeclared network calls
- Reviewing community-submitted skills before deployment
- Catching hidden data exfiltration in utility tools
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: scan this 'indent-fixer' skill that claims to fix Python indentation to 4 spaces
- 1Parses skill name, summary, and description to extract declared scope
- 2Scans code for file reads, environment variable access, network calls, and subprocess usage
- 3Compares declared scope against observed access patterns
- 4Scores mismatch severity and identifies sensitive path violations
- 5Generates risk rating with per-finding explanations
OVER-PERMISSIONED report listing 3 mismatches: ~/.env read, OPENAI_API_KEY extraction, and HTTP exfiltration with the key passed in the URL