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MarkosWebWeb intelligence for the agentic economy

Methodology

How we measure a website's readiness for AI agents, honestly and reproducibly.

What "agentic readiness" means

An AI agent has to read a page the way a machine does: through the accessibility tree, structured data, and discovery files, not through a rendered screenshot. Agentic readiness measures how well a site supports that, plus the trust signals an agent (or a person) weighs before transacting. Our checks mirror Google's Lighthouse "agentic browsing" scoring.

How we score

Like Lighthouse, we do not emit an invented 0-100. Each page is measured against 30 deterministic checks; every check passes, partially passes, or fails based on the site's real HTML and discovery files. The headline is a fraction of passed checks. Where a signal cannot be assessed from available data, we say so - we never guess.

The checks

Agent interaction

Machine extraction

Structured data

AI discovery

Trust & transparency

Data sources & provenance

Checks are computed from the site's own homepage and its discovery files (llms.txt, robots.txt, sitemap.xml). Every figure on a report is a verifiable fact about the live site. Each report shows a "last checked" date, and that date is what drives the page's freshness signal in our sitemap.

Trust & legitimacy signals

Alongside technical readiness we surface longevity (how long a site has been seen online, as a defensible lower bound), current activity, secure transport, and identifiable technology - the signals that indicate a real, maintained business rather than a throwaway site.

Ownership verification & linking policy

Site owners can verify ownership of their domain for free, by proving control via a DNS TXT record, a homepage meta tag, or a well-known file. Verification is re-checked periodically, and every owner edit re-proves control.

The score reflects the site's readiness, not an opinion. Scores can be improved by the site owner, never bought - and verification never changes a measurement.
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