What it does

This skill provides a comprehensive security and governance audit for AI agent systems. It analyzes tool inventories, authentication models, connector scopes, and execution logs to identify over-privileged tools and risky permission combinations.

Why use this skill

Manual security reviews for LLM agents are prone to oversight, especially when tracking complex tool-calling boundaries. This skill automates the detection of "Shadow AI" risks and governance gaps by mapping your agent's actual capabilities against your defined security policies. It goes beyond simple prompting by cross-referencing multi-source evidence—including run logs and credential models—to ensure your safety guardrails are actually effective.

Supported Tools

The skill integrates with standard development environments using Python and PowerShell. It consumes JSON-based tool inventories, auth configurations, and policy documentation to generate machine-readable JSON audits and client-ready Markdown reports.

The Output

You receive a detailed privilege matrix and structured hardening plan. Findings are categorized by severity and tied directly to specific tool metadata or policy violations, providing a clear roadmap for securing your agent pilots.