---
title: "Google AI search readiness audit | SEO Skill"
description: "Check the crawl, index, canonical and snippet controls used for Google AI search eligibility without predicting whether a page will be selected."
canonical: "https://seoskill.dev/docs/reports/geo-gaps"
language: "en"
---

# Google AI search readiness audit

Check the technical controls Google documents for AI search features. This audit can find access or snippet restrictions, but selection still depends on systems the page cannot observe.

## 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
```

Run check google ai search controls through the report catalog.

```
seo reports run geo-gaps --params '{"reportId":"crawl_example_20260710","limit":25}' --json
```

## What you get from this audit

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

Best for

You need a Google-specific eligibility review grounded in published controls.

Needs

Saved or fresh crawl evidence

You get

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

Use next

Find URLs affected by a crawl issue

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 evidence

Provides response, robots, indexability, canonical, and page-level snippet controls.

### Google AI feature guidance

Defines the supported relationship between normal search controls and AI feature eligibility.

## Use a different report for these jobs

These jobs need a different report or a manual review.

[

### You want a broader AI readiness review that also covers page structure, structured data, and optional agent resources.

Run AI readiness. It includes the supported Google controls and adds separate observations for structure and optional resources without treating them as visibility requirements.

AI search readiness audit

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

### You need to know whether Google will show a page in an AI Overview or how often it already appears there.

No report can predict whether Google will select a page. Run AI mention research for limited provider-indexed Google AI Overview evidence, then inspect its coverage, market, question samples, and citations before describing visibility.

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 geo-gaps --json
```

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

```
seo reports run geo-gaps --params '{"reportId":"crawl_example_20260710","limit":25}' --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": "geo-gaps"
}
```

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

```
{
  "id": "geo-gaps",
  "params": {
    "reportId": "crawl_example_20260710",
    "limit": 25
  }
}
```

### 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(
  'geo-gaps',
  {
  "reportId": "crawl_example_20260710",
  "limit": 25
},
)

console.log(result)
```

## What to do next

Open the affected URLs for any restrictive Google access or snippet control and check whether the rule is intentional. Use AI referral data separately when you need evidence of visits rather than technical eligibility.

1.  01Use affected URLs for any restrictive rule.
2.  02Use AI referrals for separate observed traffic evidence.

## Related reports

[

Find every URL affected by a technical SEO issue, inspect the crawl evidence on each page and turn one broad finding into a practical fix list.

Technical SEO affected URLs

](https://seoskill.dev/docs/reports/affected-urls)[

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

AI search readiness audit

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