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

# Datasets

> Curated inputs and expected outputs to evaluate against.

A **dataset** is a versioned collection of items — each an `input` and an
optional `expected` output — that you run experiments against.

## Building a dataset

* Create a dataset in **Datasets → New dataset**.
* Add items manually (`input` as JSON or text, plus `expected`), or capture them
  from real traces you want to turn into regression cases.
* Datasets are **versioned**, so an experiment records exactly which version it
  ran against.

## Using a dataset

Run an [experiment](/app/experiments) over a dataset: RunAgain executes your
prompt/agent for each item, records the output as a run item, and scores it with
your chosen method(s). Compare the result against your baseline to catch
regressions before shipping.

<Card title="Experiments" icon="flask-conical" href="/app/experiments">
  Score a dataset run and diff it against the baseline experiment.
</Card>