AI Readiness report
Example Apparel
Merino Crew Sweater — Example Apparel
example-apparel.com/products/merino-crewHigher than 72% of top 500 apparel brands on Shopify.
Strong structured data and server-side schema. The biggest opportunity is conversational content — adding Q&A and usage detail would lift how confidently agents recommend these products.
This product is already in good shape for AI shoppers — the hard part is staying there. AI models and data standards shift constantly, and one product isn't a catalog. Lumio monitors every product as the landscape moves, manages your product feeds across channels, and re-scores automatically, so a strong score holds.
See what Lumio keeps watch on →Scored by Lumio's AI-readiness algorithm · v2.2
Where this product stands
Lumio benchmarks this score against a live research set — real product pages from the top brands in each category and platform, all scored on the same 16 signals. Your standing is exactly where this product lands in that field. It's the same field ChatGPT, Perplexity, and Claude pull from, so the ranking is the one that actually matters.At 78 out of 100, this product scores higher than 72% of top 500 apparel brands on Shopify.
Fix these first
-
llms.txt file Missing
Publish an llms.txt file at your site root pointing AI agents to your most important pages.
-
Q&A and use-case content Needs work
Add Q&A pairs, usage scenarios, and compatibility notes an agent can quote back to a shopper.
-
Structured data completeness Needs work
Fill in the recommended fields: GTIN, MPN, ratings, price validity, and return and shipping policy.
-
Site-wide structured data Needs work
Add organization, site-search, breadcrumb, and FAQ structured data across the site — not only on the product page.
-
Image readiness Needs work
Add descriptive alt text, image structured data, and responsive image sizes so agents can use your product photos.
-
Availability detail Needs work
Give exact stock levels, handling time, and restock dates rather than a bare in-stock / out-of-stock flag.
-
Internal linking Needs work
Link the product to its category, related products, and brand pages so agents can navigate your catalog.
The 16 dimensions
The full scorecard. Lumio measures structured-data and crawlability signals deterministically, then grades content quality with an AI pass. Expand any dimension to see what it measures and how to improve it.
Structured data & crawlability
-
AI crawler visibility 100
Whether your product's structured data is in the page's initial HTML or only appears after JavaScript runs. ChatGPT, Claude, and Perplexity read the initial HTML — anything that needs JavaScript is invisible to them.
-
Structured data validity 88
Whether your structured data is valid: it parses cleanly, required fields are present, values are the right type, and nothing contradicts the visible page.
-
Structured data completeness 71
How complete your structured data is beyond the basics — product ID (GTIN), manufacturer part number (MPN), ratings, price validity, and return and shipping policy.
-
Site-wide structured data 64
Structured data across the rest of the site, not just the product page — your organization details, site search, breadcrumbs, and FAQ markup.
-
Content visible after load 82
How much real product text remains once JavaScript has run. Copy hidden inside tabs or accordions can be invisible to AI agents.
-
Page and data agree 90
Whether the page a shopper sees and your structured data agree on price, availability, brand, and title. Mismatches read as a trust problem to an agent.
-
Image readiness 70
How usable your product images are to AI: enough images, descriptive alt text, image structured data, and responsive sizes. Agents increasingly read images, not just text.
-
Freshness 50 Informational
Signals about how recently the page was updated. Informational for now (not scored) until a reliable signal lands.
-
Internal linking 66
Whether the product page links out to its category, related products, and brand pages — the trail an agent follows to understand your catalog.
-
llms.txt file 0
Whether the site publishes an llms.txt file — an emerging convention for pointing AI agents to your key pages. Low weight while adoption is early.
-
agents.md file Detected Informational
Whether the site publishes an /agents.md file — an emerging convention, alongside llms.txt, for pointing AI agents to a site's real agent endpoint. Informational for now while the standard is nascent.
-
MCP endpoint Detected Informational
Whether the storefront exposes a reachable Model Context Protocol (MCP) endpoint — the emerging way for AI agents to query a catalog and act on it directly. Informational for now while the standard is nascent.
Content quality (AI-graded)
-
Title quality 85
Whether product titles are structured and descriptive — brand, product type, a key attribute, and the variant — rather than a bare product name.
-
Description depth 78
Whether descriptions are rich with real attributes and answer the questions a shopper actually asks, rather than marketing fluff.
-
Q&A and use-case content 55
Whether the page has the question-and-answer pairs, usage scenarios, and compatibility notes an AI agent can quote back to a shopper.
-
Product identifiers 80
Whether the core product identifiers — GTIN, MPN, brand, and model number — are present and actually valid.
-
Availability detail 72
Whether availability is specific — exact stock, handling time, and restock dates — rather than a bare in-stock / out-of-stock flag.
Fix it with Lumio
Lumio just analyzed one of your products.
Now let it analyze and fix your entire catalog.
Every gap above becomes an automatic fix — richer structured data, sharper titles and descriptions, complete identifiers — across all your products. Then Lumio keeps watching, so you stay ahead as AI shopping shifts.
- Automatic enrichment
- Continuous monitoring
- Re-score anytime
