> ## 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.

# Basic Accuracy

> Example showing how to check how complete, correct and accurate an Agno Agent's response is.

<Steps>
  <Step title="Create a Python file">
    ```python basic.py theme={null}
    from typing import Optional

    from agno.agent import Agent
    from agno.eval.accuracy import AccuracyEval, AccuracyResult
    from agno.models.openai import OpenAIResponses
    from agno.tools.calculator import CalculatorTools

    evaluation = AccuracyEval(
        name="Calculator Evaluation",
        model=OpenAIResponses(id="gpt-5.2"),
        agent=Agent(
            model=OpenAIResponses(id="gpt-5.2"),
            tools=[CalculatorTools()],
        ),
        input="What is 10*5 then to the power of 2? do it step by step",
        expected_output="2500",
        additional_guidelines="Agent output should include the steps and the final answer.",
        num_iterations=3,
    )

    result: Optional[AccuracyResult] = evaluation.run(print_results=True)
    assert result is not None and result.avg_score >= 8
    ```
  </Step>

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U openai agno
    ```
  </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 Agent">
    ```bash theme={null}
    python basic.py
    ```
  </Step>
</Steps>