• VERIFIED
  • MISSING
  • INCOMPLETE
  • HUMAN

How to audit AI task completion with your AI

Connect once to give your agent the ability to cross-reference its own work against your original requirements.

Ask AI about this page

Short answer

How can I make sure my AI actually did what I asked?

You use this MCP to force your agent to prove its work. It maps every requirement to a specific file change and flags any missing steps or edge cases it ignored. You get a clear gap analysis of the task's completion.

Where every issue lands.

The audit outcomes

The agent processes your request and sorts its findings into these categories.

VERIFIED

Requirement mapping

The agent uses verify_delivery to link every instruction to a specific code change. You see exactly which lines satisfy which requirements.

MISSING

Unhandled edge cases

The agent identifies logic gaps or scenarios it didn't account for. This highlights where the code might fail in production.

INCOMPLETE

Missing steps

The agent flags any part of your original prompt that wasn't addressed in the file changes. This prevents partial implementations.

HUMAN

Manual review needed

The agent flags high-uncertainty areas where it couldn't confidently map a change to a requirement. You decide if these need a fix.

The workflow

What your AI does when the task arrives.

The agent moves from raw code to a structured integrity report.

  1. Requirement extraction

    The agent parses your prompt to build a checklist of every specific instruction and constraint provided.

    verify_delivery

  2. Change mapping

    The agent inspects the proposed file changes to see if they actually fulfill the extracted requirements.

    verify_delivery

  3. Gap detection

    The agent looks for edge cases or missing logic that the current implementation ignores.

    verify_delivery

  4. Integrity reporting

    The agent compiles the mapping, the gaps, and the missing steps into a final audit summary.

    verify_delivery

Try it

Copy these to start.

Use these prompts to trigger the audit immediately.

Starting points

Swap the bracketed text for your actual repo path or specific task description.

Delivery Integrity Prover Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_47XZJ7Jwbw4wbyoAk0N57vFtYyOnkyNmEkgNiNe8/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 — Delivery Integrity Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "delivery-integrity-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_47XZJ7Jwbw4wbyoAk0N57vFtYyOnkyNmEkgNiNe8/mcp"
    }
  }
}
Copy into chat04

  • Audit the changes in [repo path] against my original requirements.

  • Check if the implementation in [file path] covers all the edge cases I mentioned.

  • Map every requirement in my prompt to a specific line change in [directory].

  • Identify any missing steps in the current PR for [branch name].

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

Start here

Connect Delivery Integrity Prover once, then ask.

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

Connect Delivery Integrity Prover to your AI

FAQ

How this task behaves

  • 01

    Can the AI fix the code itself?

    No. This MCP is for auditing and verification. It identifies the gaps, but you or your agent must perform the actual code edits.

  • 02

    Does it change my files?

    No. The tool only reads the files and the requirements to perform the audit. It does not write or modify your code.

  • 03

    How does it know what I wanted?

    It uses the context of your current chat session and the specific requirements you provided in your prompt.

  • 04

    Can it audit a pull request?

    Yes, as long as the files in that pull request are accessible to your AI client.

  • 05

    What if the AI misses an edge case?

    The audit is a tool for your review. It is designed to catch what the agent missed, but you should always perform a final human check.

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

Connect Delivery Integrity Prover to Claude, Cursor, ChatGPT & more