starbucks.com
This is how AI agents (not browsers) experience starbucks.com. The score weights five categories of machine-readability; the ticks on the arc are the 31 individual checks behind it.
Top fixes
No <link rel="canonical"> tag in <head>. Agents use canonical URLs to dedupe and cite.
Fix · Next.js: Set alternates.canonical in the Metadata API (generateMetadata) for each route.
No JSON-LD blocks found. Add a <script type="application/ld+json"> with a schema.org type for this page.
Fix · Next.js: Emit JSON-LD from a Server Component or the Metadata API: a <script type="application/ld+json"> with Organization / Article / Product for the page.
No HTTP Link: response headers. Emit canonical/alternate/describedby relations so HEAD-only or stream-rendering agents get them without parsing HTML.
Fix: Emit `Link:` headers for canonical, alternate-language, and describedby relations. Agents that fetch HEAD-only or stream-render rely on these.
Visible text is 3.6% of HTML weight (2709/76303 bytes). Low. Markup may be crowding out agent-usable text.
Fix: Heavy ad or navigation markup crowds out agent-usable text. Aim for a text-to-DOM ratio above 15%.
Browser pass unavailable; HTML looks like a JS-shell (e.g. #__next / #root). Likely JS-dependent.
Fix · Next.js: Render primary content on the server: use Server Components (App Router) or getServerSideProps/SSG (Pages Router). Avoid fetching above-the-fold content in a client useEffect, since agents don’t run it.
Consent modal detected (trustarc.com); content still visible. Verify the modal does not block first-paint for screenshot agents.
Fix: Defer cookie consent overlay until after content is visible, or render behind the primary content. Agents without JS or with ad-blocking profiles see a blank page otherwise.
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Generated, ready-to-ship files for the gaps above — copy them or download and drop them into your repo.
This scan shows whether an agent can read the site. One free probe asks a real assistant a real buying question and records who it cited.
This graded your homepage. Your pricing, docs, and checkout live on other pages — the ones assistants actually quote when they recommend you — and a 64/100 here means agents are already missing things on the page you polish most. The $29 Deep Scan audits the whole site against all 31 checks, then emails a PDF with every failing check and its exact fix, ranked by what costs you the most visibility. One-time, delivered in minutes, no subscription.
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This score says whether an AI agent could read starbucks.com. AI traffic analytics says whether one actually came — and which pages turned it away.
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