ls-skill-vetter

Assess AI agent skills for security and privacy risks before installation.

3|2|Updated Dec 25, 2025
One-click install
npx skills add https://github.com/CruxExperts/localsetup --skill ls-skill-vetter
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ls-skill-vetter
Source: https://github.com/CruxExperts/localsetup/tree/main/_localsetup/skills/ls-skill-vetter
Command: npx skills add https://github.com/CruxExperts/localsetup --skill ls-skill-vetter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Modern AI skills can introduce security and compliance risks when integrated into repos or toolchains. Vetting skills before installation minimizes exposure to malicious code, misconfigurations, and over-permissive access.

Core Features & Use Cases

  • Red-flag scanning and permission-scope evaluation against known risks.
  • Code-review guidance and risk categorization to guide human approvals.
  • Reproducible, audit-friendly vetting reports for registry or GitHub sources.

Quick Start

Run the vetting checklist on a candidate skill and generate a structured report.

Frequently Asked Questions about ls-skill-vetter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is AI skill vetting and why do I need it before installation?

Vetting AI agent skills before installation prevents security and privacy risks by scanning for red flags, evaluating permission scopes, and reviewing code to yield a clear risk classification and human approval verdict.

How do I vet an AI skill from a public registry or GitHub repository?

You vet an AI skill by running a structured protocol that performs source checks, code review, permission evaluation, and risk classification, generating a reproducible, audit-friendly report for registry or GitHub sources.

Can I use this vetting process to check for over-permissive access scopes?

Yes, this process evaluates permission scopes against known risks to detect over-permissive access, scanning for red flags and categorizing risks to guide human approvals before toolchain integration.

Does the vetting protocol generate an audit-friendly report for compliance?

The vetting protocol generates reproducible, audit-friendly reports that document red-flag scanning, permission-scope evaluation, and risk categorization to support compliance reviews for registry or GitHub sources.

What are the limitations of automated AI skill risk assessment?

Automated risk assessment provides structured guidance and risk categorization for human approvals, but it cannot replace manual code review judgment when identifying subtle red flags or complex data exposure vulnerabilities.