This is a sample report for an illustrative business. No real company is described.
How to read this report
- The score (0–100) and grade sum six weighted categories of what AI agents can reach and understand.
- Findings are grouped by severity; "+N pts" is how much the score would rise if that one issue were fixed.
- Generated fixes are ready-made files built from the findings — they come with Pro.
- A blocked site has no score: access must be restored before anything else counts.
Sample audit report · point-in-time example · Online store
trailhead-outfitters.example
CAudit overview
Scored as: Online store · What this means · Methodology
Crawlable, but its products are invisible to shopping agents: no Product markup, prices only as styled text, no machine-readable stock.
Category scores
Commerce readiness only counts if you sell online. If you don't, that 20 points is spread across the other five categories so your score reflects what actually matters for your site.
Crawl & Bot Access
Weight: 20 pts
1 issue
Structured Data
Weight: 25 pts
1 issue
Commerce Readiness
Weight: 20 pts
2 issues
Content Machine-Readability
Weight: 15 pts
1 issue
Policy & Trust
Weight: 10 pts
1 issue
Entity Signals
Weight: 10 pts
1 issue
Highest-impact fixes
- 1.No Product schema on product pages+13 ptsCritical
Add the missing JSON-LD structured data.
- 2.No llms.txt file+7 ptsMedium
Publish an llms.txt file at your site root.
- 3.Prices are shown visually but not in structured data+5 ptsHigh
Add the missing JSON-LD structured data.
Fix these three and your score moves from 67 to ~92. (estimate — re-audit to confirm)
Findings (7)
Critical 1
No Product schema on product pages
Product pages have no schema.org Product or Offer markup, so agents can't reliably read name, price or availability.
High 2
Prices are shown visually but not in structured data
Prices appear only as rendered text. Agents comparing products may skip or misquote them.
Availability not machine-readable
There's no availability field, so agents can't tell if an item can be bought now.
Medium 3
No llms.txt file
There's no curated map of key pages for AI agents at /llms.txt (an emerging convention, not a ratified standard).
Homepage has no meta description
Agents have no concise page summary to help interpret the store's purpose.
No machine-readable return policy
Agents acting for a shopper look for return terms before recommending a purchase.
Low 1
Organization schema missing logo
Organization markup exists but has no logo, which weakens brand recognition.
Generated fixes (preview)
Ready-to-use files built from the findings. REPLACE_WITH_… marks anything we didn't observe.
Product + Offer schema
Paste inside <head> on each product page and replace every REPLACE_WITH_… value with that product's real data.
New · 18 lines added
Added: <!-- Product: paste inside <head> on each product page. -->Added: <script type="application/ld+json">Added: {Added: "@context": "https://schema.org",Added: "@type": "Product",Added: "name": "REPLACE_WITH_PRODUCT_NAME",Added: "sku": "REPLACE_WITH_SKU",Added: "image": "REPLACE_WITH_ABSOLUTE_IMAGE_URL",Added: "brand": { "@type": "Brand", "name": "REPLACE_WITH_BRAND" },Added: "offers": {Added: "@type": "Offer",Added: "url": "https://trailhead-outfitters.example/REPLACE_WITH_PRODUCT_PATH",Added: "price": "REPLACE_WITH_PRICE",Added: "priceCurrency": "REPLACE_WITH_CURRENCY",Added: "availability": "https://schema.org/InStock"Added: }Added: }Added: </script>
- Paste the <script type="application/ld+json"> block inside the <head> of the matching page.
- Replace any REPLACE_WITH_… placeholders first, then check it with a structured-data testing tool.
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