> ## 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.

# Experiments

> Run a prompt or agent over a dataset and score the results.

An **experiment** runs your task over a [dataset](/app/datasets), records each
output, and scores it — so you can compare versions and catch regressions.

## Create an experiment

In **Experiments → New experiment**, choose a dataset and set:

* **Prompt template** — e.g. `Answer concisely. {{input}}`
* **Task model** — e.g. `claude-opus-4-8`
* **Scorers** — the [evaluation](/concepts/evaluations) methods to apply.

## Run it

Trigger the run from the experiment page. The eval worker executes the task for
each dataset item, writes a **run item** (input, output, latency, tokens, cost,
and any error), and applies the scorers.

## Compare

The experiment view shows per-scorer averages and counts. Set a **baseline**
experiment on the project to diff a new run against it — e.g. "faithfulness
0.94, −1 case vs main".

<Card title="Datasets" icon="database" href="/app/datasets">
  Experiments run against a specific, versioned dataset.
</Card>