> For the complete documentation index, see [llms.txt](https://docs.raga.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/additional-metrics/evaluation/grade-score.md).

# Grade Score

**Objective**: The Grade Score Test calculates the Flesch-Kincaid Grade Level of a text, which indicates the number of years of education generally required to understand the text

**Required Parameters**:

* Prompt (str): The initial question or statement provided to the model.
* Response (str): The model's generated answer or reaction to the prompt.

**Interpretation**:

* The grade score indicates the reading level required to understand the text.
* Lower scores indicate texts that are easier to read and understand, typically requiring fewer years of education.
* Higher scores indicate texts that are more complex and may require a higher level of education to understand.

**Result Interpretation**:

* The test result is determined by comparing the grade score against a predefined threshold.
* Scores below the threshold indicate that the text is at or below the specified grade level ("Passed"), while scores above it indicate that the text is above the specified grade level ("Failed").
* The threshold can be adjusted based on the desired grade level for the text.

```python
# test expected to pass
evaluator.add_test(
    test_names=["grade_score_test"],
    data={
        "prompt": "What is the capital of France?",
        "response": "Paris is the capital of France"
    },
    arguments={"model": "gpt-4", "threshold": 6},
).run()

evaluator.print_results()
```


---

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