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

# Tone

The Tone Evaluator is a specialized tool designed to assess the similarity in tone and style between an actual response and an expected response. It uses an LLM (Large Language Model) as a judge to determine how well the tone, formatting, and formality of responses match, without considering the actual content or information provided.

## Purpose

The Tone Evaluator is particularly useful when you need to:

* Ensure consistent communication style across responses
* Maintain appropriate formality levels in automated responses
* Verify proper formatting and presentation of information
* Check for inappropriate use of emojis or special characters
* Maintain brand voice consistency in automated communications

## How It Works

The evaluator uses a 5-point scale to rate responses:

* **Score: 1 (Inappropriate Characters)**: The actual response contains emojis or offensive characters not used in the expected response
* **Score: 2 (Extreme Differences)**: The actual response presents extreme differences in both formatting and formality
* **Score: 3 (Significant Differences)**: The actual response presents extreme differences in either formatting or formality
* **Score: 4 (Minor Differences)**: The actual response does not present extreme differences in formatting or formality
* **Score: 5 (Similar Tone)**: The actual response is similar in tone and complexity compared to the expected response

## Usage Example

```python theme={null}
import asyncio

from trusttest.evaluation_contexts import ExpectedResponseContext
from trusttest.evaluators import ToneEvaluator


async def evaluate():
    evaluator = ToneEvaluator()
    result = await evaluator.evaluate(
        response="The capital of Osona is Vic! 🎉",
        context=ExpectedResponseContext(
            expected_response="The capital of Osona is Vic."
        )
    )
    print(result)

if __name__ == "__main__":
    asyncio.run(evaluate())
```

The evaluator returns a tuple containing:

* A score (1-5) indicating the level of tone similarity
* A list of explanations for the given score

## When to Use

Use the Tone Evaluator when you need to:

* Ensure consistent communication style in customer service responses
* Maintain professional tone in business communications
* Verify appropriate use of formatting and special characters
* Check for consistency in automated response systems
* Evaluate the style and presentation of AI-generated content