AI agent readiness

Check whether agents can find and read a clean machine-readable version of every public page. The report tests the content-site contract directly, then keeps unrelated API, application and commerce checks out of the failure count.

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.

Runafter install

Install the SEO CLI globally.

npm i -g seo

Run setup after installation.

seo start

Check the public content-site contract with a fresh limited crawl.

seo agent-readiness https://example.com --max-pages 100 --json

What you get from this audit

Check Markdown alternatives, agent discovery, crawler access and identity across a content site. Find broken routes without inventing a readiness score.

Best for: A documentation, publishing, or content site serves machine-readable versions of its pages.
Needs: Fresh content-site crawl
You get: Check Markdown alternatives, agent discovery, crawler access and identity across a content site. Find broken routes without inventing a readiness score.
Use next: Check AI search technical readiness

Every report follows the same rules for missing data and outside estimates.See 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.

Fresh content-site crawl

Provides the public HTML route inventory, response evidence, crawler policy, and structured identity found during this run.

Agent-facing representations and discovery

Provides Markdown alternatives, negotiated responses, the route manifest, Agent Skills, and llms.txt for direct validation.

Use a different report for these jobs

These jobs need a different report or a manual review.

You want to check technical eligibility for Google AI search features rather than the machine-readable content contract.

Run AI search readiness. It checks crawl, index, canonical, snippet, and page evidence without treating optional agent discovery as a search requirement.

AI search readiness audit

You need observed mentions, citations, prompt coverage, or share of voice inside AI answers.

Use a repeatable external visibility measurement. This audit can prove whether the site delivered its content contract, but it cannot show whether an AI product used it.

AI visibility tracking

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.

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 agent-readiness --json

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

seo reports run agent-readiness --params '{"url":"https://example.com/","maxPages":100}' --json

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": "agent-readiness"
}

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

{
  "id": "agent-readiness",
  "params": {
    "url": "https://example.com/",
    "maxPages": 100
  }
}

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(
  'agent-readiness',
  {
  "url": "https://example.com/",
  "maxPages": 100
},
)

console.log(result)

What to do next

Fix shared representation failures before patching one generated file. Repeat the same route scope after deployment and confirm the explicit Markdown URL, negotiated response, discovery files, and identity evidence now agree.

01Fix shared generation or delivery problems before patching individual Markdown files.
02Repeat the same public route scope after deployment and compare the affected checks.

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

Check whether llms.txt can be fetched and parsed, whether its links work and how well it covers useful pages before you publish or update it.

llms.txt audit

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

Entity SEO audit

Check sitemap URL status, redirects and access first. Run the full technical SEO crawl only when you need page content, links, metadata and affected URLs.

Sitemap health check and technical site crawl