> ## 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.

# URL Correctness

The URL Correctness Evaluator is a specialized tool designed to assess the relevance of webpage or document content to a user's question. It uses an LLM (Large Language Model) as a judge to determine if the content of provided URLs is relevant and contains the information needed to answer the user's query.

## Purpose

The URL Correctness Evaluator is particularly useful when you need to:

* Verify if linked content is relevant to the user's question
* Ensure referenced documents contain the necessary information
* Validate the accuracy of URL-based responses
* Check if web resources support the provided answers
* Evaluate the quality of information sources in responses

## How It Works

The evaluator uses a 3-point scale to rate URL relevance:

* **Score: 0 (Unrelated/Broken)**: Content is completely unrelated to the question or the link is broken
* **Score: 1 (Partially Relevant)**: Content shares the same domain but either:
  * Addresses different aspects than asked
  * Only partially addresses required aspects
* **Score: 2 (Fully Relevant)**: Content fully addresses all specific aspects in the question

The evaluator analyzes both the content and the user's intent to determine relevance, providing detailed explanations for its scoring decisions.

## Usage Example

```python theme={null}
import asyncio

from trusttest.evaluation_contexts import QuestionContext
from trusttest.evaluators import UrlCorrectnessEvaluator


async def evaluate():
    evaluator = UrlCorrectnessEvaluator()
    result = await evaluator.evaluate(
        response="You can find more information about credit card cancellation at https://example.com/cancel-card",
        context=QuestionContext(
            question="How do I cancel my credit card?"
        )
    )
    print(result)

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

The evaluator returns a tuple containing:

* A score (0-2) indicating the level of URL relevance
* A list of explanations for the given score, including specific references to relevant content

## When to Use

Use the URL Correctness Evaluator when you need to:

* Validate the relevance of linked resources in responses
* Ensure information sources are appropriate and accurate
* Check if referenced documents contain the required information
* Verify the quality of web-based answers
* Evaluate the completeness of URL-based responses