• LOGIC
  • ERRORS
  • STABILITY
  • HUMAN

How to audit agentic reasoning with your AI

Connect this MCP to your agent to stop it from hallucinating logic. It forces the AI to defend its decisions through structured, first-principles testing.

Ask AI about this page

Short answer

How can I check if my AI's reasoning is actually sound?

You use the Counterfactual-Variant Prover to run logic tests that force your agent to defend its conclusions. This process exposes hidden assumptions and proves whether a solution holds up under pressure. You'll see exactly where the logic breaks.

The audit results.

Where your logic lands.

The agent processes your request and delivers these specific outcomes.

LOGIC

Verified reasoning paths

The AI identifies which logical steps are necessary and which are just assumptions. You get a clean derivation of the solution.

ERRORS

Detected reasoning gaps

The tool flags where the agent's logic fails when a variable changes. This shows you where the agent is prone to hallucinating.

STABILITY

Constraint adherence

You see if the agent stays within your specific rules even when pushed. It proves the agent won't drift from its instructions.

HUMAN

Manual review needed

The AI flags high-uncertainty paths that require you to step in. You decide if the counterfactual proof is strong enough to trust.

The workflow

What your AI does when the audit arrives.

The agent uses these steps to tear apart a solution and rebuild it from scratch.

  1. Isolate the logic

    The agent extracts the core reasoning chain from your current task to prepare for testing.

    validate_counterfactual

  2. Generate variants

    The AI creates alternative scenarios to test the strength of the original conclusion.

    validate_counterfactual

  3. Test the constraints

    The agent runs the logic against different versions of the same problem to see if the answer holds.

    validate_counterfactual

  4. Report the proof

    The final output provides a structured derivation that proves the solution follows first principles.

    validate_counterfactual

Try it

Copy these to start.

Use these prompts to trigger the audit immediately.

Starting points

Swap the bracketed text for your specific logic or data source.

Counterfactual-Variant Prover Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_DsoSPwZEWSeSBTBSQCX8U58BqAbjy82WIsWBk6Wg/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 — Counterfactual-Variant Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "counterfactual-variant-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_DsoSPwZEWSeSBTBSQCX8U58BqAbjy82WIsWBk6Wg/mcp"
    }
  }
}
Copy into chat04

  • Audit the reasoning in this Python script: [paste code]

  • Validate the logic used in this project plan: [paste plan]

  • Check if this decision follows my constraints: [paste constraints]

  • Run a counterfactual test on this customer support response: [paste response]

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

Start here

Connect Counterfactual-Variant Prover once, then ask.

One click connects this MCP to your client. Your credentials stay encrypted and the setup is handled on our end.

Connect Counterfactual-Variant Prover to your AI

FAQ

How the audit behaves.

  • 01

    Can the AI change my original code or files?

    No. The AI only reads your data to perform the validation; it does not have permission to write or modify your files.

  • 02

    Does this tool fix the agent's mistakes automatically?

    No. It identifies the flaws in reasoning and provides the proof, but you must decide how to fix the agent's instructions.

  • 03

    What kind of data can I audit?

    You can audit any text-based reasoning, including code, project plans, or logical arguments provided in your chat.

  • 04

    Will this work with any AI client?

    Yes, as long as your client is MCP-compatible, like Claude, Cursor, or Windsurf.

  • 05

    Does the AI need to be autonomous to use this?

    No. You can use this to audit a single response from a standard chat agent or a fully autonomous loop.

  • More questions about Counterfactual-Variant Prover? The Connector page answers them. See everything the Counterfactual-Variant Prover Connector can do

Connect Counterfactual-Variant Prover to Claude, Cursor, ChatGPT & more