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← State of Agentic Commerce
Agentic Commerce Score · scanned 2026-07-23 · rubric v0.2

hiutdenim.co.uk

43/100
grade D
not yet agent-buyable
platform: shopify

Can an AI shopping agent buy from hiutdenim.co.uk?

As of 2026-07-23, no: hiutdenim.co.uk scores 43/100 (grade D) on the Agentic Commerce Score and does not meet the agent-buyable bar. The failing checks are: Machine-readable product catalog, Required fields (title/image/price/description), Product JSON-LD (Offer: price/currency/availability), and 6 more.

95
Discover — can agents fetch + read the store? (30%)
0
Evaluate — can agents parse + trust the products? (45%)
56
Transact — can an agent complete a purchase? (25%)

Discover — can agents fetch + read the store?

AI crawlers allowed (robots.txt)
No AI shopping crawler is root-blocked in robots.txt.
Homepage readable without JavaScript
Homepage serves ~431 visible words of real HTML (no JS needed).
Sitemap discoverable
Sitemap found.
! llms.txt present
No /llms.txt (emerging convention — counted as a soft gap, not a blocker).

Evaluate — can agents parse + trust the products?

Machine-readable product catalog
No open product feed, and only 0/3 sampled product pages carry complete Product JSON-LD — agents have no reliable catalog surface.
Required fields (title/image/price/description)
No feed; from 3 sampled product page(s), Product JSON-LD carries 0% of the four required fields on average.
Product JSON-LD (Offer: price/currency/availability)
0/3 sampled product page(s) carry Product JSON-LD with a complete Offer (price + priceCurrency + availability); 0/3 carry any Product schema.
Brand + product identifier (sku/gtin/mpn)
0/3 sampled product page(s) expose both brand and an identifier (sku/gtin/mpn); brand alone on 0/3.
AggregateRating in Product JSON-LD
0/3 sampled product page(s) expose machine-readable review ratings.
Product image alt text
0% of content images on sampled product page(s) carry non-empty alt text.
Description depth (≥120 chars)
0/3 sampled product page(s) expose a quotable description (≥120 chars) in Product JSON-LD.

Transact — can an agent complete a purchase?

Agentic-checkout rail (platform prerequisite)
Platform: shopify. Shopify asset/runtime markers in homepage HTML.
Machine-readable price + availability
No feed; 0/3 sampled product page(s) expose price + availability via Offer schema.
Per-variant stock readable
No feed and no per-variant availability exposed — an agent cannot tell which size/colour it can actually order.
Shipping + returns policies (with terms)
Shipping and returns policies fetched, with an explicit return window an agent can read.

Highest-impact fixes

  1. Fill the four required catalog fields on every product: title, image, price, description — a product missing one drops out of agent answers.
  2. Add complete Product JSON-LD on product pages: an Offer with price + priceCurrency + availability.
  3. Publish brand plus a product identifier (sku / gtin / mpn) in Product JSON-LD — agents match, dedupe and price-compare products by identifier; without one your listing is an orphan.
  4. Expose machine-readable price AND availability per product (feed fields or Offer schema) — agents will not guess stock.
  5. Give agents a machine-readable catalog: keep an open product feed (on Shopify, /products.json) or at minimum ship complete Product JSON-LD on crawlable product pages.
  6. Expose reviews as AggregateRating in Product JSON-LD (ratingValue + reviewCount) — agents quote ratings when ranking options, and skip products that have none they can read.

Is this your store?

This is a point-in-time scan of public signals (2026-07-23) — if you have shipped fixes since, re-run it in ten seconds: npx agentic-commerce-score hiutdenim.co.uk.

ACS covers whether agents can buy from you. The other half is whether AI assistants recommend you over competitors — run Arenza's free Agentic Visibility Score or write to hello@arenza.ai.

Think a check is wrong? Every result carries the evidence it was based on, and the scanner is open source — so a disputed score is a reproducible question, not an opinion. Mail hello@arenza.ai and we will re-scan, correct the published page if we got it wrong, and note the correction. Fixed the gap instead? Tell us and we will re-scan and update this page.