What it does

The AI Code Verification Gate is a professional-grade safety layer that prevents AI agents from "hallucinating success." It forces your agent to perform a structured, evidence-based audit of its own code changes before delivery. Instead of just assuming code works because it looks correct, this skill implements a rigorous QA workflow including risk classification, heuristic scanning, and regression mapping.

Why use this skill

Standard AI prompting often leads to agents overlooking edge cases or claiming a task is done when tests haven't actually passed. This skill bridges that reliability gap by providing a formal verification report. It includes a local read-only scanner and a remediation framework that ensures every claim of "fixed" is backed by cited evidence, logs, or test output. It's an essential tool for developers using AI in production environments where "it looks right" isn't good enough.

Supported tools

• Local heuristic scanner (Python-based)
• Manual audit checklists and remediation templates
• Git diff and runtime log analysis
• Compatibility with modern CI/CD patterns and test runners

The Output

The agent produces a detailed Verification Report including: a scope summary, severity-ranked findings (Critical to Info), evidence-backed fixes, a list of untested hypotheses, and clear manual review items for the human-in-the-loop.