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

# Introduction

> Agentrail tests how AI agents find, choose and use your product, and shows you what to fix.

More and more people ask an AI agent to pick a product, read its docs or get a task done. Agentrail shows you what those agents see when they reach your product: whether they can read your site, whether they recommend you over your competitors, and whether they can finish the tasks your customers care about.

## What you can do

<CardGroup cols={2}>
  <Card title="Agent readiness" icon="gauge" href="/docs/guides/agent-readiness">
    Scan your website, docs and API the way agents read them, and get a score with the findings behind it.
  </Card>

  <Card title="Agent Preference" icon="scale" href="/docs/guides/agent-preference">
    Ask agents the questions your buyers ask, and see which products they recommend.
  </Card>

  <Card title="Agent Experience" icon="list-checks" href="/docs/guides/agent-experience">
    Give agents a real task on your product and check whether they complete it.
  </Card>

  <Card title="Feedback" icon="message-square" href="/docs/guides/feedback">
    Let the agents that use your product tell you what went wrong.
  </Card>
</CardGroup>

## Start here

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/docs/quickstart">
    From signing up to your first result.
  </Card>

  <Card title="Core concepts" icon="book-open" href="/docs/concepts">
    Organizations, workspaces and the parts of Agentrail.
  </Card>
</CardGroup>

## Public API

Anyone can read the agent-readiness leaderboard, start a scan of a site, and send a report to a feedback project, with no account. See the [API reference](/docs/api-reference/introduction).


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