• CRITICAL
  • STUBS
  • DEBT
  • HUMAN

How to audit AI generated pull requests with your AI

Connect this MCP to your AI client to catch sloppy code before it hits human review. It scans for the specific shortcuts AI models tend to take.

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Short answer

How do I audit AI generated pull requests with my AI?

Your AI uses the Code Integrity Prover to scan incoming PRs for type evasions, stubs, and technical debt. This catches the lazy patterns AI often uses to satisfy a prompt without actually solving the logic. You'll see exactly where the code is brittle or incomplete.

Findings and outcomes

Where every issue lands.

The AI categorizes every finding so you know what to fix and what to ignore.

CRITICAL

Type evasions found

The AI identifies where the code uses 'any' or ignores type safety to bypass errors. You get a list of specific lines that break your type constraints.

STUBS

Empty logic detected

It flags 'TODO' comments or empty function bodies that the AI inserted to avoid writing complex logic. You'll see exactly which functions are just placeholders.

DEBT

Technical debt warnings

The AI spots patterns that increase complexity or violate your existing architecture. These are flagged as warnings for your review.

HUMAN

Review required

The AI marks PRs that contain too many stubs or type evasions as high-risk. These go straight to your attention for manual verification.

The workflow

What your AI does when a PR arrives.

The AI acts as a first-pass gatekeeper, running deep checks that standard linters often miss.

  1. Scan the diff

    Your AI pulls the changes from the pull request to analyze the specific lines added or modified.

    validate_code_integrity

  2. Identify evasions

    It looks for instances where the AI bypassed strict typing to make the code compile quickly.

    validate_code_integrity

  3. Detect stubs

    The agent finds empty implementations or placeholder logic that lacks actual functionality.

    validate_code_integrity

  4. Flag debt

    The AI highlights code that introduces unnecessary complexity or breaks established patterns.

    validate_code_integrity

Try it

Copy these to start.

Use these prompts to kick off an audit in your AI client.

Starting points

Swap the repository names and branch details with your actual project info.

Code Integrity Prover Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_jFZoweIYKxgCWa80Y8BDR5PM7selSnPLkB3gfPHH/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Code Integrity Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "code-integrity-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jFZoweIYKxgCWa80Y8BDR5PM7selSnPLkB3gfPHH/mcp"
    }
  }
}
Copy into chat04

  • Audit the latest pull request in the backend-api repo for any type evasions.

  • Check the changes in the auth-service branch for empty stubs or TODOs.

  • Scan the current PR in the frontend-app repo and list any technical debt it introduces.

  • Review the diff for the user-service PR and tell me if the AI used 'any' to bypass types.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Code Integrity Prover once, then ask.

One click connects this MCP to your client. Your credentials stay encrypted, and you can start auditing code immediately.

Connect Code Integrity Prover to your AI

FAQ

How the audit behaves

  • 01

    Can the AI automatically merge the PR if it passes?

    No. The AI only identifies issues. You must manually review the findings and perform the merge yourself.

  • 02

    Does the AI change my code directly?

    No. The AI only reads the code and reports its findings. It does not write or commit changes to your repository.

  • 03

    What is the difference between this and a standard linter?

    Standard linters check syntax and style. This MCP specifically looks for the logical shortcuts and 'lazy' patterns that LLMs use to avoid complex implementation.

  • 04

    Can I use this with Cursor or VS Code?

    Yes, as long as your client is MCP-compatible, you can use this tool within your existing IDE workflow.

  • 05

    Will it catch logic errors in my business rules?

    No. The tool focuses on code integrity, such as type safety and stubs. It does not understand your specific business logic or domain requirements.

  • More questions about Code Integrity Prover? The Connector page answers them. See everything the Code Integrity Prover Connector can do

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