# The AI agent readiness checklist: 24 checks for your website

Your website is ready for AI when an assistant can parse who you are, quote what you claim, and complete a purchase without a human decoding anything. This checklist turns that into 24 concrete checks, grouped under [the eight dimensions](/resources/the-8-dimensions-of-ai-legibility) the Legible Readiness Index scores. Each check is pass/fail on purpose — work top to bottom, the highest-weight dimensions come first.

## 1. Structured data

- **Ship Organization JSON-LD on your homepage.** It's the machine-readable answer to "who is this?" — the question every model asks first.
- **Add Product or Service schema with price and availability to every offer page.** Agents compare structured fields, not prose.
- **Add FAQPage schema to pages that answer real questions.** Q&A pairs are the most liftable format an answer engine sees.
- **Validate all of it and fix every error.** Broken JSON-LD is worse than none; a parser that fails once may skip the block entirely.

## 2. Entity & identity

- **Write one canonical brand description and use it verbatim everywhere.** Models build consensus from repetition; five variants read as five uncertainties.
- **Publish a `sameAs` graph linking your official profiles.** LinkedIn, Wikidata, and social profiles tied together let models confirm you're one entity.
- **Ground the brand in [Wikidata](https://www.wikidata.org/) (and Wikipedia where you qualify).** Third-party grounding is what turns "a company claims" into "a known entity."

## 3. Citability

- **Restructure key pages to one idea per heading.** Models extract sections, not pages; a heading that matches a question gets lifted.
- **Convert marketing paragraphs into short, data-bearing sentences.** "Cuts onboarding from 14 days to 3" is quotable; "world-class solutions" is filtered out.
- **Attribute every statistic to a named source.** Unsourced numbers lower model trust in the whole page.

## 4. Commerce readiness

- **Put final price, shipping cost, delivery window, and return terms on the product page in machine-readable form.** [nShift's research](https://nshift.com/delivery-management/agentic-commerce) on agent legibility is blunt: when delivery and return terms are unclear, the agent skips the offer without a human ever seeing it.
- **Keep stock status accurate and in schema.** An agent that gets burned by a phantom "in stock" deprioritizes the whole domain.
- **Move policies out of PDFs and JavaScript-only FAQ widgets.** If the terms only exist inside a PDF or a rendered widget, they don't exist to most agents.
- **Give agents a path to transact — or at least to a clean handoff.** "Contact sales" with no structured next step is where agent journeys die.

## 5. Machine access

- **Serve your core content as server-rendered HTML.** Content that appears only after JavaScript runs never reaches many crawlers.
- **Allow AI search and fetcher bots in robots.txt.** Blocking OAI-SearchBot or PerplexityBot removes you from AI answers outright.
- **Publish an llms.txt file.** It's the machine-readable front door: what you are, where to look.
- **Offer a lean, low-token version of key pages.** When [Cloudflare shipped markdown conversion for agent requests](https://blog.cloudflare.com/markdown-for-agents/), its example page dropped from 16,180 tokens as HTML to 3,150 as markdown — roughly 80% less for the agent to wade through.
- **Keep latency low and your sitemap current.** Slow, unmapped sites get sampled, not read.

## 6. Multilingual

- **Add `hreflang` for every locale you sell in.** AI answers differ sharply by language; models need the map between versions.
- **Check parity: your schema and key claims exist in every locale, not just English.** A German buyer's assistant reads your German pages.

## 7. Verification

- **Back every claim with evidence a machine can follow.** A linked source or named study; unsupported superlatives read as noise.
- **Make the publisher unambiguous.** Clear authorship, contact details, and legal identity separate you from the content farms models learn to discount.

## 8. Freshness

- **Emit accurate `dateModified` on every page.** Models prefer dated, maintained content and discount the stale.
- **Audit your top-cited pages quarterly for dead facts.** Old prices and discontinued products actively damage trust once an agent catches one.

## What this checklist can't cover

Passing all 24 checks makes you legible — it doesn't make you *complete*. For most companies, roughly 20% of what makes a product the right choice lives in structured data; the rest is [tribal knowledge](/resources/the-tribal-knowledge-problem-what-ai-cant-see) sitting in your best salesperson's head, and no validator will flag its absence.

Rather than self-scoring 24 boxes, you can measure them in one pass: [run a free Legible report](/) and get the failing checks ranked by how much score they're costing you.