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    ✅ AI Code Verification Gate

    1

    Standard AI prompting often leads to agents overlooking edge cases or claiming a task is done when tests haven't actually passed.

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    ✅ AI Code Verification Gate

    ✅ AI Code Verification Gate

    Example session with this skill installed

    Run the AI verification gate on my last few commits to ensure the new auth logic hasn't introduced any regression risks.

    • Read your context and instructions
    • Compiled the ai code verification

    Verification Report

    Findings:

    • [High] CSRF protection missing on /api/login/update (Evidence: routes/auth.js:42)
    • [Medium] Redundant DB call in session lookup (Evidence: auth-service.ts:108)

    Status: 2 verified fixes, 1 high-risk item pending manual review of session headers.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    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.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Trust & safety

    Security scan

    Security scan passed 4 months ago

    Requires

    Python
    macOS

    Listed4 months ago

    What's inside

    Frequently Asked Questions