The method · version 1
We measure what is on a site: what an automated visitor can fetch, read and reach. We never measure what AI products answer. Each check says how we know it matters: a platform’s own document, an independent study, or neither, in which case it is recorded as a fact and never offered as advice.
What we measure
When an AI system reads your site for someone, can it get in, does it take away the right facts, and can it reach the page where they act? Each layer is one part of that question, answered by the checks listed under it.
Can an AI crawler fetch your pages and understand what is on them?
7 checksAre your name, phone number, address and hours the same on every page an AI crawler reads, and in the business details your site declares?
4 checksCan an automated visitor reach contact, booking or checkout, and use the form there?
9 checksWhat can an automated visitor see that a careful person would check before acting?
11 checksWe do not track what AI answers say about a site. Those answers are sampled from systems we do not run, and they do not repeat. SparkToro’s study () found that two of the AI tools it tested, asked the same question 100 times, gave the same list of brands in any two answers less than 1 time in 100.
A reading that changes every time it is taken is one nobody else can check. What is on the site can be: the same site, read the same way, gives the same reading, so an owner, an agency or anyone else can repeat it.
Evidence grades
The grade says how we know an AI system reads what the check looks at. It describes the evidence, never the site.
A platform’s own published document or code says this is read: a standard the crawlers follow, or the documentation or source code of the company that runs the system.
12 checks at present.
An independent study observed it. No platform’s own document says so.
1 check at present.
No platform document and no independent study says it matters. We record it because it is true of the site, so it is never offered as advice about AI.
18 checks at present.
Every source carries the day we last re-checked it and is due again within 30 days; our own test suite goes red the day one is overdue. A grade we cannot back at its source drops to fact only.
Every check
Each check has its own page: the question it answers, what we observe, what we cannot see, and a fix where the evidence supports one.
Can an AI crawler fetch your pages and understand what is on them?
Are your name, phone number, address and hours the same on every page an AI crawler reads, and in the business details your site declares?
Can an automated visitor reach contact, booking or checkout, and use the form there?
What can an automated visitor see that a careful person would check before acting?
The yardstick
Lighthouse is Google’s own page test, and its Agentic Browsing checks are what Chrome’s team says an AI agent needs from a page.
agent-accessibility-treeApplied to the home page, read at phone size: Lighthouse’s own rule (the check is not met when any of its axe-core rules finds a problem) over our axe-core run, configured the way Lighthouse configures it.webmcp-form-coverageWebMCP needs a browser feature we do not run.webmcp-registered-toolsWebMCP needs a browser feature we do not run.webmcp-schema-validityWebMCP needs a browser feature we do not run.cumulative-layout-shiftLighthouse measures this in a lab test on a simulated phone, which we do not run. The real-visitor figure we read is a different measure, so we do not use it here.llms-txtApplied when the site has the file: we request /llms.txt once and apply Lighthouse’s three format checks. With no file, Lighthouse counts the check as not applying, and so do we.ard-schemaApplied when the site has an agent resource list: we request /.well-known/ard.json once and run Lighthouse’s validator over it. With no list, the check does not apply.Our reading of Lighthouse’s accessibility-tree check (agent-accessibility-tree) matched Lighthouse 13.4.0 on 8 of 8 hand-built test pages, on the verdict and on the failing rules alike (). The calibration against real sites is pending. Until it is done we print no number for this area, only which of Lighthouse’s checks are met.
Where we go further: We look at what an automated visitor receives on every page we read, and we keep the record week to week. Where we do less: Lighthouse says these checks are still being developed: its newest version has seven, its current release six. From what we read we can apply up to three of them: the accessibility check on your home page at phone size, and the two that read your llms.txt and agent resource list when you have them.
Lighthouse’s check is not met when axe-core finds a problem under any of these rules. We run axe-core 4.12.1 with Lighthouse’s own configuration and apply the same list, read from Lighthouse’s source at commit 21501c1 (the category itself: its configuration).
button-nameinput-button-nameinput-image-altlabellink-nameselect-namedocument-titlearia-allowed-attraria-allowed-rolearia-command-namearia-conditional-attraria-dialog-namearia-hidden-bodyaria-hidden-focusaria-input-field-namearia-prohibited-attraria-required-attraria-required-childrenaria-required-parentaria-rolesaria-textaria-toggle-field-namearia-tooltip-namearia-treeitem-namearia-valid-attraria-valid-attr-valueduplicate-id-ariadefinition-listtable-duplicate-nametabindexautocomplete-validpresentation-role-conflictsvg-img-alt
Levels
Each level asks one question and is answered by its own set of checks. A report prints, for each level, how many of its checks raised a finding, were checked with nothing found, were not seen or were not measured. It never says a site is at a level.
Can an automated visitor that says who it is get your pages and read them?
Is what it reads about your business the same everywhere, and can it find where to act?
Can it get all the way to the submit button?
It runs only once the owner confirms the site is theirs, because we only click through a site with permission. It stops at the submit button: we never send a form, so it never shows whether a booking or a message goes through.
The other 13 checks sit in no level. New formats such as llms.txt and the content-use lines stay facts until they are an agreed standard, because requiring them would fail nearly every site on something nobody has agreed on; most of the rest are Trust checks, which belong to their own areas.
What we never do
What this is, and isn’t. Invara reports observable technical facts about a website with a confidence level for each finding. It does not determine legal compliance, does not assert violations of any law, and is not legal advice. Items we can’t observe from the outside (such as whether you have a contract with a vendor) are flagged to verify, never asserted. Remediation offers are technical changes, not legal outcomes.
Version
7b9fc43ace94 — it changes whenever any check, grade, source, date or level on this page changes.Cite as: Invara, “How AI sees your site”, method version 1, evidence re-checked November 6, 2026 (fingerprint 7b9fc43ace94). https://clearsitedigital.com/how-ai-sees-sites
When a platform changes what it documents, the grade changes when we re-check that source, and the version and fingerprint change with it. Each check’s own page has its own address.
Free and read-only: your home page’s text with and without JavaScript, and in a free account, what we checked in each of the four layers.
Free and read-only: we only look, and there is nothing to install. By pressing the button you confirm this is your site or you have permission to check it, and you agree we may keep the results, with your site’s name removed, for research on websites in general (how we handle it). See a sample report.