• RECITATION
  • REASONING
  • INCONSISTENT
  • HUMAN

How to detect recitation bias in your AI

Connect the Counterfactual-Variant Prover to your agent to see if it's actually thinking or just spitting out memorized patterns.

Ask AI about this page

Short answer

How can I tell if my AI is just reciting data?

You can use counterfactual testing to swap key variables in a logic problem to see if the agent's answer changes. If the answer stays the same despite a fundamental change in the premises, it's reciting. You'll see the specific failure points in the breakdown below.

Test outcomes

Where the results land.

The agent processes your logic problems and categorizes the findings based on how it handled the changes.

RECITATION

Memorized patterns detected

The agent failed to adapt to the counterfactual change. This shows the model is relying on training data instead of logic.

REASONING

True logic confirmed

The agent correctly adjusted its output based on the new variables. This proves the model is actually processing the logic.

INCONSISTENT

Unstable logic detected

The agent's reasoning breaks under specific variations. This highlights edge cases where the model's logic is brittle.

HUMAN

Manual review needed

The AI flagged a logic loop it couldn't resolve. You'll need to step in to verify the correct logical path.

The workflow

What your AI does when the logic problem arrives.

The agent uses the prover to stress-test the model's understanding of the problem.

  1. Identify core logic

    The agent analyzes the initial problem to find the essential variables that drive the conclusion.

    validate_counterfactual

  2. Generate variations

    The agent creates new versions of the problem by changing one specific fact to see if the logic holds.

    validate_counterfactual

  3. Compare outputs

    The agent checks if the original answer still works under the new conditions.

    validate_counterfactual

  4. Flag the bias

    The agent marks the response as either a reasoned conclusion or a memorized recitation.

    validate_counterfactual

Try it

Copy these to start.

Use these prompts to begin testing your agent.

Starting points

Swap the bracketed text for your actual logic puzzles or math problems.

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

  • Run a counterfactual test on this logic puzzle: [insert puzzle here].

  • Check if my agent is reciting this math problem by changing the variables: [insert problem].

  • Verify the reasoning in this syllogism using counterfactual variants: [insert syllogism].

  • Test this coding logic problem for recitation bias: [insert code snippet].

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

Start here

Connect Counterfactual-Variant Prover once, then ask.

Just link the MCP to your client. Your credentials stay encrypted, and you can start testing immediately.

Connect Counterfactual-Variant Prover to your AI

FAQ

How the testing behaves

  • 01

    Can the AI fix the bias itself?

    No. The AI identifies where the bias occurs, but you have to adjust your prompts or model to fix it.

  • 02

    Does this work on any logic problem?

    Yes, as long as the problem has clear variables that can be changed to test the underlying logic.

  • 03

    Will it change my original training data?

    No. This tool only reads and analyzes the problems you provide; it cannot modify the model's weights or data.

  • 04

    Can the AI delete my test logs?

    No. The tool only performs validation; it has no capability to delete or modify your files or history.

  • 05

    How do I know if a result is accurate?

    The accuracy depends on the counterfactual variation. If the variation is logically sound, the result is reliable.

  • 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