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What does "AI-agent-ready" mean?

A website is AI-agent-ready when crawlers, assistants, and buyer agents can each use it fluently against published, vendor-neutral standards.

The first move is recognising that “AI traffic” is not one audience. A website now serves three.

Three audiences, three jobs

A modern website is read by three categories of software, each with a different job and a different set of standards it expects you to support.

Crawlers

The bots that build the indexes — GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, Google-Extended, Bingbot, Applebot-Extended, CCBot. Their job is to pull your content into a training corpus or a search index. They need clean HTML, a parseable /robots.txt that tells them what they may and may not crawl, a /sitemap.xml listing every canonical URL, and ideally a markdown variant of each page so they can read denser content.

Crawlers are graded by the Discovery, Citation, and Hygiene signal groups of the Checker.

Assistants

The user-facing answer-mode products — ChatGPT, Claude, Perplexity, and the search results that increasingly look like one of these. Their job is to answer a question by citing or quoting your content. They need verifiable identity: a complete Organization JSON-LD, a Person for the founder linked from Organization.founder, reciprocal sameAs verification across LinkedIn, GitHub, and other platforms. They also need an /llms.txt summary so a model can build a mental map of your site in one fetch, and an /.well-known/ai-plugin.json if you have an agent-callable surface.

Assistants are graded by the Identity and Agent Contracts signal groups.

Buyer agents

The newest and least-served audience. These are agents acting on behalf of a user with a credit card and an intent: “book this flight,” “buy this product,” “subscribe me to that newsletter.” They speak emerging protocols — the Agent Commerce Protocol (ACP), the Agent Payments Protocol (AP2), x402-style metered payment challenges, the Model Context Protocol (MCP) for tool calls, the OpenAI Apps SDK manifest for ChatGPT-embedded apps. They need a machine-readable product catalogue, a callable checkout endpoint, and schema.org Offer markup on every commercial page.

Buyer agents are graded by the Commerce signal group — signals covering ACP, AP2, x402, MCP handshakes, the OpenAI Apps SDK manifest, Google WebMCP, and schema.org Offer hygiene.

What “ready” means concretely

Ready does not mean “discovered by AI assistants once in a while.” Ready means “correctly described in the answer when a relevant question is asked.” The bar is observable and verifiable.

You can check it yourself in under ten seconds:

open chatgpt.com, claude.ai, perplexity.ai in fresh signed-out tabs
paste: "what is <your-domain>? what does <your-domain> do?"
read the verbatim response in each

That is the bar. A ready site gets an accurate, useful, three-sentence answer with a citation. A not-ready site gets “I don’t have specific information about your-domain” — the most common opening on launch day for any new brand.

Closing the gap is what GEO (“generative engine optimisation”), AEO (“answer engine optimisation”), and the freshly-named buyer-agent stack exist to solve. The Checker at /check grades a catalog of deterministic signals across the three audiences and returns a letter grade in seconds. A Setup engagement implements the Quick Wins as pull requests against your repository — the code is yours after the work — and a Retainer keeps the grade from decaying as the standards keep moving.

Signal groups in one paragraph each

The catalog spans seven groups, weighted to 100 points total. The breakdown below is the same one the Checker emits, abridged.

Discovery (30 pts)

The signals that decide whether your site is even findable by AI bots: /robots.txt exists and lists each AI-bot user-agent explicitly, /sitemap.xml validates, an AI-sitemap variant exists, /llms.txt and /llms-full.txt are parseable, an IndexNow key file is present, and every public route has a <route>.md companion served to AI UAs.

Identity (15 pts)

The signals that decide whether AI assistants can describe who you are with confidence: clean JSON-LD via ajv, a complete Organization, a linked Person for the founder, reciprocal sameAs to LinkedIn / GitHub / other surfaces, WebSite schema on the homepage, BreadcrumbList on inner pages, OG / Twitter cards, an SVG favicon, hreflang if multilingual.

Agent contracts (20 pts)

The signals that decide whether your site is callable by agents — not just describable: /.well-known/ai-plugin.json validates, OpenAPI 3.1 is linked and valid, operations carry x-llm-tool annotations, /.well-known/agent-actions.json lists high-value actions, MCP is discoverable at /.well-known/mcp.json and a live initialize handshake completes, OpenAPI server URLs respond.

Rendering & access (10 pts)

The signals that decide whether AI bots can retrieve what your humans see: server-side rendering or pre-rendered HTML (the raw fetch matches the headless DOM acceptably), consistent canonical, strong ETag / Last-Modified headers, Brotli compression on machine-readable resources, HTTP/2 or 3, navigation that works without JavaScript.

Citation (10 pts)

The signals that decide whether an assistant will quote your content accurately: high definitional-sentence density, stable claim anchors, a fact-card block on every key page, clean heading hierarchy, alt text on at least 85% of images, FAQPage schema where Q&A is present, Article with dateline on blog posts, statistics tables annotated.

Hygiene (5 pts)

The boring-but-mandatory base layer: HTTPS with HSTS and no mixed content, freshness within 12 months, no accidental noindex, a privacy policy, security.txt, and a /robots.txt that doesn’t accidentally block the AI bots you want indexing your content.

Commerce (10 pts)

The newest group, and the wedge: an ACP feed at the origin root, a working ACP checkout endpoint, an AP2 mandate-verifier that resolves a test Intent Mandate, x402 challenge on at least one paid endpoint, schema.org Offer with price/currency/availability on every commercial page. Two further preview signals — the OpenAI Apps SDK manifest and Google WebMCP manifest — are graded but weighted zero until their underlying specs stabilise.

Why this is a category, not a feature

Three years ago “AI-agent readiness” wasn’t a category. SEO covered crawlers, content marketing covered assistants by accident, and buyer agents didn’t exist. Today each of these audiences uses your site differently, expects different signals, and rewards different work. A single Checker that grades all three in one pass — against published, vendor-neutral standards, not invented “AI Position Intelligence™” trademarks — is the closest thing to a category-defining diagnostic that exists.

That is what the Free Checker is. A Setup engagement is the studio that ships the fixes into your repository, whatever the stack — Next, Astro, Nuxt, Hugo, WordPress, custom — and leaves you owning the code afterwards. A Retainer keeps that grade from decaying as the standards keep changing.

What’s next

Run the Free Checker on your site, read the evidence panel, compare your global and vertical percentile against the corpus, and decide whether the top-three Quick Wins are work you want to do yourselves or work you want to hand to the studio. A Setup engagement (from $5,000, scope-based) ships the fixes as PRs into your repository with a before/after grade; a Retainer ($1,500–$7,500/mo, sold afterwards) keeps the score from decaying and tracks whether your AI citations are actually moving.

There’s no portal, no dashboard to log into, no layer running on your domain that disappears if we go quiet. The code is yours — Setup ships it into your repo, and the retainer maintains it there rather than moving it onto ours. That is the studio model, and it is structurally different from the SaaS GEO platforms.