> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Binary Agent as Judge

> Binary pass/fail evaluation without numeric scoring

This example demonstrates binary PASS/FAIL evaluation mode without numeric scoring.

<Steps>
  <Step title="Add the following code to your Python file">
    ```python agent_as_judge_binary.py theme={null}
    from agno.agent import Agent
    from agno.db.sqlite import SqliteDb
    from agno.eval.agent_as_judge import AgentAsJudgeEval
    from agno.models.openai import OpenAIResponses

    # Setup database to persist eval results
    db = SqliteDb(db_file="tmp/agent_as_judge_binary.db")

    agent = Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        instructions="You are a customer service agent. Respond professionally.",
        db=db,
    )

    response = agent.run("I need help with my account")

    evaluation = AgentAsJudgeEval(
        name="Professional Tone Check",
        criteria="Response must maintain professional tone without informal language or slang",
        db=db,
    )

    result = evaluation.run(
        input="I need help with my account",
        output=str(response.content),
        print_results=True,
        print_summary=True,
    )

    print(f"Result: {'PASSED' if result.results[0].passed else 'FAILED'}")

    ```
  </Step>

  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
        export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
        $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    ```bash theme={null}
    python agent_as_judge_binary.py
    ```
  </Step>
</Steps>