Works with the AI tools you already use
AI Code Change Auditor
by John Barros
Verify AI-generated code for scope drift, false completions, and missing tests.
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See it in action
You say
Audit this patch. Request: 'Update the auth middleware to support MFA tokens'. Agent says it's done. Here is the diff and the log from the single test it ran.
Your agent does
Audit verdict: NEEDS_FIX Requested change: MFA token support in auth middleware. Scope compliance: Failed. Agent modified unrelated 'billing.js' files. False-completion check: The diff adds the MFA check but lacks the required 'TokenExpired' error handler mentioned in the docs. Status: NEEDS_FIX
What you get
About this skill
The problem
AI agents often claim a task is complete while leaving behind TODOs, omitting necessary tests, or making unrelated changes to your codebase. Reviewing these "black box" patches manually is time consuming and prone to missing subtle scope drift or false completions.
What it does
- Detects false completions where the AI claims a fix but the diff lacks the actual implementation.
- Identifies scope drift and "overreach" where the agent modified files unrelated to the original ticket.
- Flagging missing validation, such as skipped edge cases, missing migration scripts, or tests that don't actually assert the requested behavior.
- Categorizes patches into actionable states like PASS, NEEDS_FIX, or PRODUCT_REVIEW_REQUIRED.
- Generates a structured Fix Verification Receipt to document evidence, reviewed files, and outstanding risks.
Why this beats prompting it yourself
General prompts often miss "hallucinated" progress where an agent says a test passed that wasn't actually run. This skill enforces a rigorous audit procedure that specifically looks for agentic failure modes like happy-path-only fixes and placeholder code that standard reviews often overlook.
Use cases
- Reviewing a PR generated by an automated coding agent before merging to main.
- Auditing a complex bug fix to ensure the agent didn't break adjacent call sites.
- Verifying that a refactor stayed within the requested architectural boundaries.
- Generating a verification receipt for compliance or team handoff after AI-assisted development.
Known limitations
This is a change auditor, not a deep security or performance profiler. It cannot verify UI behavior without provided screenshots or logs.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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