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✅ AI Code Verification Gate
One-line summary description Stop your agent from claiming "done" before it's proven. A verification gate that classifies each change by risk (payment, auth, database, user-facing), picks the tests that actually cover it, demands evidence, maps regression risk, and outputs an honest pass/fail report. Turns "looks good to me" into "here's what I ran, and here's what's still unverified."
$19
· or 95 creditsSecure checkout via Stripe
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.
Details
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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Security Scanned
Passed automated security review
Permissions
File Scopes
Read-only inspection first. The bundled scanner reads change diffs and prints markdown or JSON findings. It classifies change risk; it does not run your test suite for you. It installs nothing, transmits nothing, and modifies nothing. Any write, install, deploy, or live-account action requires explicit user confirmation.
Creator
JustHandled Labs builds focused agent skills for the work nobody wants to do by hand. Each one is a single repeatable job done well: catching the security and data mistakes that quietly ship, keeping docs and tests honest, gating the commands an agent is about to run, sharpening writing, and handling the founder chores around launches, outreach, and brand setup. Not generic AI productivity. Specific workflows that are easy to run, review, and repeat. Maintained by H.J. Westerfield, with a background in communications, editing, project coordination, customer support, and practical AI systems. Tools for people who want useful automation without theatrical complexity.
Frequently Asked Questions
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