---
title: "AI search readiness audit | SEO Skill"
description: "Check whether crawlers can access and use important pages in AI search. Find technical blockers without inventing a visibility or citation score."
canonical: "https://seoskill.dev/docs/reports/ai-readiness"
language: "en"
---

# AI search readiness audit

Check whether technical controls could stop important pages being crawled, indexed or shown with useful snippets. This audit covers eligibility evidence, not whether an AI product will mention or cite you.

## Install and run the audit

Install the CLI once, then run `seo start` to connect your site and Google data. After setup you can run this audit yourself or ask your agent to run it.

Install the SEO CLI globally.

```
npm i -g seo
```

Run setup after installation.

```
seo start
```

Review AI search access and page signals from the latest crawl.

```
seo ai-readiness --project example
```

## What you get from this audit

Check whether crawlers can access and use important pages in AI search. Find technical blockers without inventing a visibility or citation score.

Best for

You need a technical readiness review grounded in a crawl.

Needs

Saved or fresh crawl report

You get

Check whether crawlers can access and use important pages in AI search. Find technical blockers without inventing a visibility or citation score.

Use next

Check Google AI search controls

Every report follows the same rules for missing data and outside estimates.[See how report data works](https://seoskill.dev/docs/reports#how-report-data-works).

## What you need before you run it

The report uses the information below. Optional sources are only used when you ask for them.

### Saved or fresh crawl report

Provides response, robots, indexability, snippet, page structure, and optional resource evidence.

### Current Google AI feature guidance

Defines which normal crawl, index, and snippet controls also apply to Google AI search features.

## Use a different report for these jobs

These jobs need a different report or a manual review.

[

### You only need to check the Google crawl, index, canonical, and snippet controls used for AI feature eligibility.

Run Google AI search controls. It narrows the evidence to Google-supported technical eligibility controls and leaves optional page observations outside the blocker list.

Google AI search readiness audit

](https://seoskill.dev/docs/reports/geo-gaps)[

### You need to know whether an AI product will cite, mention, rank, or send traffic to a page.

Run AI mention research for provider-indexed mention and citation evidence. Use fixed prompt observations for current answers and AI referrals for measured visits. None of those sources can guarantee future selection or ranking.

AI mention research report

](https://seoskill.dev/docs/reports/ai-mention-research)

## Use the audit with an agent or in code

The command above is enough for most work. These options let an agent, script or application run the same audit with explicit input and structured output.

### CLI

Use the report catalog when an agent, script or CI job needs predictable JSON instead of the normal terminal output. Check the current input first, then run the audit with the validated parameters.

Check the current input before the agent or script runs the audit.

```
seo reports describe ai-readiness --json
```

Once the input is valid, run the audit through the report catalog.

```
seo reports run ai-readiness --params '{"reportId":"crawl_example_20260710"}' --json
```

### MCP

An MCP agent follows the same two-step flow. It inspects the current schema, fills the required fields and only then runs the audit.

Ask the MCP server for the current audit input.

```
{
  "id": "ai-readiness"
}
```

Run the audit after the agent has checked and filled the input.

```
{
  "id": "ai-readiness",
  "params": {
    "reportId": "crawl_example_20260710"
  }
}
```

### TypeScript

Install the package in a Node 22 project when your application needs to run the audit directly. The result includes the same evidence, warnings and limits returned through the CLI and MCP server.

Add the SEO package to your project.

```
npm install seo
```

Run the audit from your TypeScript application.

```
import { executeReport } from 'seo/mcp'

const result = await executeReport(
  'ai-readiness',
  {
  "reportId": "crawl_example_20260710"
},
)

console.log(result)
```

## What to do next

Start with hard access, indexability or snippet conflicts that work against the publisher's intent. Keep referral traffic and assistant mentions as separate measurements because this audit cannot observe either one.

1.  01Use geo gaps for Google-specific access and snippet controls.
2.  02Use AI referrals for observed referral sessions.

## Related reports

[

Check the crawl, index, canonical and snippet controls used for Google AI search eligibility without predicting whether a page will be selected.

Google AI search readiness audit

](https://seoskill.dev/docs/reports/geo-gaps)[

Check whether schema, authorship and brand details clearly connect the people, organisation and content across your site and find conflicting signals.

Entity SEO audit

](https://seoskill.dev/docs/reports/entity-readiness)[

Find visits from known AI assistants in Google Analytics, see which landing pages received them and keep missing referrers separate from confirmed traffic.

AI referral traffic report

](https://seoskill.dev/docs/reports/ai-referrals)

## Sources used by this audit

These primary sources define the provider data or search controls used by the result.

-   [Google guidance for AI features and websites](https://developers.google.com/search/docs/appearance/ai-features)
-   [Google robots.txt guidance](https://developers.google.com/search/docs/crawling-indexing/robots/intro)
-   [Google robots meta and snippet controls](https://developers.google.com/search/docs/crawling-indexing/robots-meta-tag)