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Agent-readiness: what AI agents need to use your website

AI agents already browse ordinary websites on people’s behalf. An agent that cannot parse your structure, prices or contact route recommends a competitor it can parse. These are the ten signals that decide it.

Last reviewed 2026-09-04 · AgentProof, Harmony Future Holdings Limited, Dublin

What this page is

A plain-English account of the ten signals we measure, with the weight we give each and why. It is free, and it is the same corpus our paid report is built from. Unlike our sibling sites this is not a legal obligation — no law requires any of it, and we are not going to pretend otherwise.

Why this matters now

AI agents already browse ordinary websites on users’ behalf — Claude in Chrome since December 2025, ChatGPT agent mode, Gemini in Chrome. An agent that cannot parse a site’s structure, prices or contact route recommends a competitor it can parse.

Agent-readiness is 2026’s version of mobile-readiness in 2010: early, measurable, and cheapest to fix before the traffic arrives.

The ten signals, by weight

Weights follow the evidence, not the fashion. We re-based them in August 2026 after a market scan, and the re-basing moved things in directions that were commercially inconvenient for us.

SignalWeightWhat a pass means
Labelled form inputs14Every form input has a label or aria-label.
Valid JSON-LD15Valid schema.org JSON-LD is present and parseable.
Real buttons and links12Interactive elements are real <button> and <a> elements, not bare clickable <div>s.
Organization or Product schema10The JSON-LD declares an Organization, Product, Service or LocalBusiness with real fields.
An explicit AI-crawler policy8robots.txt takes a deliberate position on GPTBot, ClaudeBot and Google-Extended rather than staying silent.
Title and meta description8A real <title> and meta description exist.
A machine-readable contact route8A mailto:, tel: or schema contactPoint exists.
Exactly one h16One <h1> states what the page is.
An llms.txt file6An /llms.txt file exists and describes the site for language models.
Declared language4<html lang> is declared.

The two that carry the most weight

Labelled form inputs (14)

The highest-evidence lever on the list. Measured agent task-completion runs at roughly 78% on accessible sites versus 42% on inaccessible ones. An unlabelled input is an abandoned checkout in the agent economy.

Valid JSON-LD (15)

Structured data is the difference between an agent knowing your price and guessing it. It scores highest because it is the only signal that conveys facts rather than structure.

The useful surprise here

The two heaviest interaction signals — labelled inputs and real buttons — are accessibility work. If you have been putting off an accessibility pass, agent-readiness is the same job with a commercial return attached, and the evidence for it is stronger than for anything fashionable on this page.

Why llms.txt scores only 6

We weight this low on purpose, and it costs us to

llms.txt is the artefact everyone wants to sell you. The measured picture is thin: Google states it has no effect on Search, and Ahrefs measured 97% of llms.txt files receiving zero bot requests (May 2026).

It stays in our pack as a cheap hedge — it costs nothing, Lighthouse 13.3 audits for it, and it is the one site summary you fully control. But it is sold as exactly that, and it scores 6 out of 91. A vendor leading with llms.txt is selling you the easiest thing to deliver, not the thing that works.

Deciding about AI crawlers

The check is not “allow the crawlers”. It is take a deliberate position on GPTBot, ClaudeBot and Google-Extended rather than staying silent. Silence is a policy by accident.

One combination we flag as a warning: blanket-blocking AI crawlers while wanting agent customers. It is self-defeating, and it is usually the result of a copy-pasted robots.txt rather than a decision anyone made.

WebMCP, and why absence is not a failure

WebMCP lets a page register tools an agent can call directly, rather than making the agent drive the interface. It is a W3C Web Machine Learning Community Group draft, in Chrome origin trial through roughly Q1 2027.

Scored as INFO, never as a FAIL

Absence is normal today and we do not score a site down for it. Presence is being early to the interface agents will probably prefer. Anyone marking you down in 2026 for not shipping an origin-trial API is inventing a problem.

How the grade is worked out

Each check passes, warns or fails. A pass earns its full weight, a warn earns half, a fail earns nothing. INFO checks — WebMCP — are excluded from the denominator entirely, so they can never drag a score down. The percentage maps to a band:

ScoreGrade
85 and aboveA
70–84B
55–69C
40–54D
below 40F

The honest limits

This measures observable signals on the pages supplied, against conventions current agents and crawlers are documented to read, as at the corpus version shown on the report.

The audit on your real pages, and the fix pack

The self-check below scores what you can see by eye. The audit runs the same checks against your actual pages, and the fix pack gives you paste-ready markup plus a retest.

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