Google Search Central, applied

Google AI Search readiness

Google's AI Overviews and AI Mode still start with normal Search systems: crawlability, indexing, quality and snippets. The SEO checker turns that into practical checks instead of dressing old myths up as GEO.

What changed in the checker

The tool now has a dedicated readiness layer for Google's generative AI features, built around the official guidance published by Google Search Central.

Google source Run the checker

Eligibility firstThe page must return successfully, allow Googlebot, avoid noindex and remain eligible for snippets before Google AI features can use it.
Query fan-out coverageThe checker generates adjacent intents from the target query so the page can answer the related questions Google may retrieve for grounding.
Non-commodity contentThe audit looks for evidence, named examples, methodology, first-hand detail, dates and a clear point of view rather than generic filler.
Agentic UXSemantic landmarks, labelled controls and readable page structure help browser agents and assistive technology interpret the page.
Lighthouse agentic browsingThe checker now separates Search visibility from agent readiness: llms.txt is optional for Google Search, but useful to monitor because Chrome Lighthouse checks its fetch behaviour for browser agents.
WebMCP hintsAction-heavy pages are checked for static WebMCP-style form tool names and descriptions, with a link to validate richer dynamic registration in Lighthouse.

Useful tools to add next

Search Console importer: pull queries, pages, clicks and impressions into the public dashboard so AI Search changes can be correlated with real visibility.

Fan-out gap tracker: store generated fan-out prompts per audited URL and mark which ones are answered on-page after edits.

Agentic browsing report: run Lighthouse after the server-side audit to verify WebMCP registration, accessibility tree quality, cumulative layout shift and llms.txt behaviour in Chrome.

Commodity risk queue: flag pages that look like generic guides and push them into a rewrite queue with required evidence fields.

PageSpeed Insights hook: call PSI after crawl blockers are fixed and show Core Web Vitals beside the readiness score.

What not to sell as magic

Google says there is no special markup or llms.txt requirement for generative AI features in Search. Chrome Lighthouse now treats llms.txt as an optional agent-discovery surface, so the honest position is simple: it is useful infrastructure for agents, not a ranking lever.

The same applies to chunking, fake mentions and schema overuse. The cleaner pitch is better: build useful, source-backed, crawlable pages that people would actually want to read.

How this helps CopeCheck

CopeCheck has a natural advantage because the useful pages are sourced records with verdicts, links and a point of view. The risk is thin repetition. The readiness layer is designed to keep the network on the programmatic side of the line, not the scaled-content-abuse side.

Marketable product angle

This can be sold as a Google AI Search readiness check: not a promise of AI Overview placement, but a practical audit of whether a page is discoverable, snippet-eligible, useful, structured and competitive enough to be retrieved.

Reference points

The public rationale is aligned with current search guidance: helpful source-backed pages, readable sitemaps, clear topical structure and no mass publishing purely to manipulate rankings.

Google Search: optimizing for generative AI features Chrome Lighthouse: agentic browsing scoring Chrome Lighthouse: llms.txt audit Chrome Lighthouse: registered WebMCP tools Google Search: AI-generated content guidance Google Search spam policies: scaled content abuse Google Search sitemap guidance Bing Webmaster: sitemaps and AI-powered search discovery