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

paireyewear.com

54/100
grade D
not yet agent-buyable
platform: shopify

Can an AI shopping agent buy from paireyewear.com?

As of 2026-07-23, no: paireyewear.com scores 54/100 (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 4 more.

100
Discover — can agents fetch + read the store? (30%)
22
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 ~1051 visible words of real HTML (no JS needed).
✓ Sitemap discoverable
Sitemap found.
✓ llms.txt present
/llms.txt found.

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 50% 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); 3/3 carry any Product schema.
✓ Brand + product identifier (sku/gtin/mpn)
3/3 sampled product page(s) expose both brand and an identifier (sku/gtin/mpn); brand alone on 3/3.
✗ AggregateRating in Product JSON-LD
0/3 sampled product page(s) expose machine-readable review ratings.
✓ Product image alt text
100% 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. Expose machine-readable price AND availability per product (feed fields or Offer schema) — agents will not guess stock.
  4. 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.
  5. 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.
  6. Expose stock per variant (size/colour), not just per product — an agent that cannot tell which variant is in stock will not complete the order.

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 paireyewear.com.

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.