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

# Right Answers

Generally, our platform works by defining an input, and a set of operator/criteria pairs. However, there's also another way to do evaluations, where you define an input and a "right answer". You compare the right answer to the LLM output and see if it matches.

We support this workflow in the platform.

## Using Right Answers in the Web App

To add a Right Answer, in the Add Test pane, press "Add Right Answer".

<img src="https://mintcdn.com/valsai/wQjTO96-HXTL4O8a/images/right_answers/example.png?fit=max&auto=format&n=wQjTO96-HXTL4O8a&q=85&s=334fe3866cc732a1da9c36d13723f40b" alt="Right Answer Example" width="2560" height="1324" data-path="images/right_answers/example.png" />

## How Right Answer Comparison Works

First, you add a right answer to each test (see below how to this in the web app and SDK).

<Warning>
  **Important**: When you add a Right Answer, our system automatically generates **three checks** for every test:

  * `golden_check_content` - Content similarity comparison
  * `golden_check_style` - Style similarity comparison
  * `golden_check_format` - Format structure comparison

  These will appear in addition to any manual checks you've defined.
</Warning>

When you run the test suite, our system will then compare the LLM output to your right answer on three axes:

* **Content**: It will compare to the golden answer based on the content similarity - passing if the contents are similar, failing if they are not.
* **Style**: It will do a comparison based on the style of the text, passing only if the styles are similar.
* **Format**: It will ensure that the outputs are formatted the same.