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

# Model-Graded Evaluations

> Use AI to automatically score your AI outputs based on evaluation criteria you define.

Model-graded evaluations (also called LLM judges or auto-evaluations) use AI to automatically score your AI outputs based on criteria you define. This is the foundation of automated quality assessment in Freeplay.

## How it works

When you configure a model-graded evaluation:

1. You define the evaluation criteria with a name, question, and scoring type (Yes/No, 1-5 scale, etc.)
2. You write instructions explaining what the LLM should evaluate and provide a rubric with scoring guidelines
3. Freeplay generates a structured prompt that includes your criteria, the completion being evaluated, and relevant context

The LLM then scores each completion according to your rubric and provides an explanation for its decision.

## Use cases

* **Production monitoring**: Automatically sample and evaluate a subset of production traffic
* **Batch testing**: Run evaluations across entire datasets during test runs
* **Quality gates**: Identify outputs that fail specific quality thresholds

## Configuration

Model-graded evaluations are configured at the prompt template or agent level:

1. Select the **Evaluations** tab from the menu and then select **New Evaluation**
2. Set the target to your **prompt/agent** to evaluate and the type to **Model-graded**
3. Create your own or select from a pre-configured example
4. Write instructions that reference your prompt variables (e.g., `{{inputs.context}}`, `{{output}}`)
5. Define a rubric that maps scores to specific behaviors

<Tip>
  Use Freeplay's alignment tools to compare auto-evaluation scores against human labels and iteratively improve your evaluation prompts.
</Tip>

**Best practice:** Model-graded evaluations are the foundation for many other AI features. Prompt optimization and Evaluation Insights both work better when you have well-configured evaluations generating data. Start here before enabling other AI features.

[Learn more about model-graded evaluations →](/core-concepts/evaluations/model-graded-evaluations)