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

# JSON score

> Learn how to use the JSON score test

## Definition

The JSON score test measures how close the output is to a valid JSON format, evaluating the structural correctness of generated JSON data.

## Taxonomy

* **Task types**: LLM.
* **Availability**: <Tooltip tip="Continuously evaluate your models and datasets as you iterate on their versions.">development</Tooltip>
  and <Tooltip tip="Monitor a model in production, measure its health, check for drifts and set up alerts.">monitoring</Tooltip>.

## Why it matters

* JSON score is crucial for applications that require structured data output, such as API responses, configuration files, or data extraction tasks.
* This metric helps ensure that your LLM generates properly formatted JSON that can be parsed and used by downstream systems.
* It's particularly important for applications where malformed JSON could cause system failures or data processing errors.

## Required columns

To compute this metric, your dataset must contain the following columns:

* **Outputs**: The generated text from your LLM (expected to be JSON format)

<Note>
  This metric evaluates the structural validity of JSON output and doesn't
  require ground truth data for comparison.
</Note>

## Test configuration examples

If you are writing a `tests.json`, here are a few valid configurations for the JSON score test:

<CodeGroup>
  ```json Development theme={null}
  [
    {
      "name": "Mean JSON score above 0.95",
      "description": "Ensure that the mean JSON score is above 0.95 for valid JSON structure",
      "type": "performance",
      "subtype": "metricThreshold",
      "thresholds": [
        {
          "insightName": "metrics",
          "insightParameters": null,
          "measurement": "meanJsonScore",
          "operator": ">",
          "value": 0.95
        }
      ],
      "subpopulationFilters": null,
      "mode": "development",
      "usesValidationDataset": true,
      "usesTrainingDataset": false,
      "usesMlModel": false,
      "syncId": "b4dee7dc-4f15-48ca-a282-63e2c04e0689"
    }
  ]
  ```

  ```json Monitoring theme={null}
  [
    {
      "name": "Mean JSON score above 0.95",
      "description": "Ensure that the mean JSON score is above 0.95 for valid JSON structure",
      "type": "performance",
      "subtype": "metricThreshold",
      "thresholds": [
        {
          "insightName": "metrics",
          "insightParameters": null,
          "measurement": "meanJsonScore",
          "operator": ">",
          "value": 0.95
        }
      ],
      "subpopulationFilters": null,
      "mode": "monitoring",
      "usesProductionData": true,
      "evaluationWindow": 3600,
      "delayWindow": 0,
      "syncId": "b4dee7dc-4f15-48ca-a282-63e2c04e0689"
    }
  ]
  ```
</CodeGroup>

## Related

* [Exact match test](/tests/catalog/exact-match) - Assess identical string matches.
* [Edit distance test](/tests/catalog/edit-distance) - Measure character-level similarity.
* [Aggregate metrics](/tests/performance/aggregate-metrics) - Overview of all available metrics.