Stradivarius
www.stradivarius.comLast scanned Jun 20, 2026, 6:21 AM
Verdict
Closed to AI agents
ARC Score v1.0
33/100Restricted
Agent access16.7/50
Structured data0/25
Protocol files6/15
Scan stability10/10
Agent access
| Agent | Status | Source |
|---|---|---|
| GPTBot | Blocked | UA test: blocked by site defenses |
| ChatGPT-User | Blocked | UA test: blocked by site defenses |
| ClaudeBot | Blocked | UA test: blocked by site defenses |
| Claude-Web | Allowed | robots.txt: no rule (default allow) |
| PerplexityBot | Blocked | UA test: blocked by site defenses |
| Google-Extended | Blocked | UA test: blocked by site defenses |
| Amazonbot | Blocked | UA test: blocked by site defenses |
| Bingbot | Blocked | UA test: blocked by site defenses |
| CCBot | Blocked | UA test: blocked by site defenses |
Infrastructure
PlatformcustomCDN—WAFnone
Data signals
- JSON-LDNot detected
- Schema.org ProductNot detected
- Open GraphNo
- Product feedNo
- llms.txtYes
Change history · last 90 days
0 changesNo confirmed changes in the last 90 days — this brand's agent access posture has been stable.
The free public window is 90 days. Multi-year history, watchlists, and change alerts are part of Pro.
Fix it with Claude Code
Each failed check below has a ready-made prompt tailored to this scan's findings. Run it in Claude Code from your site's repository.
✗WAF/CDN blocks 8 agents despite robots.txt allowing themshow prompt
My e-commerce site is stradivarius.com. Our robots.txt does not block these AI agents, but live HTTP tests show our WAF/CDN returns 403s or challenge pages to them: - GPTBot (OpenAI — ChatGPT training) - ChatGPT-User (OpenAI — ChatGPT live browsing) - ClaudeBot (Anthropic — Claude training) - PerplexityBot (Perplexity — Perplexity / Comet) - Google-Extended (Google — AI Mode / Gemini) - Amazonbot (Amazon — Buy For Me) - Bingbot (Microsoft — Copilot / Bing) - CCBot (Common Crawl — Open training data) This means our stated policy (allow) and our enforcement (block) disagree, and AI assistants silently fail on our store. In this repository and our infrastructure config: 1. Search for bot-management or firewall configuration (Cloudflare rules in code/terraform, vercel.json, middleware that filters user-agents, security headers config). 2. Where we control it in code, add allowlist entries for the user-agents above — scoped to product, category, and content pages only; keep protections on /cart, /checkout, /account, and admin routes. 3. Show me the diff, and flag any rule you find that blanket-blocks "bot-like" traffic. 4. If the blocking happens in a dashboard we don't keep in code (e.g. Cloudflare Super Bot Fight Mode, DataDome, PerimeterX), tell me the exact product setting to change and what to set it to. After deploy, verify with: curl -A "GPTBot/1.0" -I https://stradivarius.com/ (expect 200, not 403).
✗No JSON-LD structured datashow prompt
My e-commerce site is stradivarius.com. A scan found no JSON-LD structured data at all, so AI shopping agents can't reliably read our product names, prices, availability, or images. In this repository: 1. Find the product page template/component and add a JSON-LD <script type="application/ld+json"> block with Schema.org Product markup: name, description, image, sku, brand, and an Offer with price, priceCurrency, availability (use schema.org/InStock | OutOfStock), and url. Populate every field from our real product data — no placeholders. 2. Add an Organization JSON-LD block to the base layout (name, url, logo) if missing. 3. If we have category/listing pages, add ItemList markup referencing the product URLs. 4. Show me one fully rendered example of the JSON-LD for a real product, then validate the shape against Google's Rich Results requirements for Product and fix any warnings you can detect statically. Verify after deploy with https://search.google.com/test/rich-results on a product URL.
✗No Open Graph tagsshow prompt
My e-commerce site is stradivarius.com. A scan found no Open Graph meta tags, so link previews and many AI agents see untitled, imageless pages. In this repository: 1. Add og:title, og:description, og:image, og:url, and og:type to the base layout's <head>, with sensible site-wide defaults. 2. On product pages, override them per product: og:type "product", the product image as og:image (absolute URL, ≥1200×630 where available), and the live price in og:description. 3. Add twitter:card "summary_large_image" alongside. 4. Show me the diff and one rendered <head> for a real product page.
✗No sitemap.xmlshow prompt
My e-commerce site is stradivarius.com. A scan could not find a sitemap.xml, so crawlers and AI agents have no reliable way to discover our product pages.
In this repository:
1. Generate a sitemap.xml covering the homepage, category pages, and every product page, with <lastmod> from each product's updated-at where available.
2. If the catalog is large, split into a sitemap index with child sitemaps of ≤50,000 URLs.
3. Reference the sitemap from robots.txt ("Sitemap: https://stradivarius.com/sitemap.xml").
4. Make it regenerate automatically (build step or on-demand route) rather than a one-off static file, and show me the diff.✗No machine-readable product feedshow prompt
My e-commerce site is stradivarius.com. A scan found no machine-readable product feed, which feed-based AI shopping agents (ChatGPT Shopping, Klarna, Google AI Mode) rely on. In this repository: 1. Determine where product data lives (database models, CMS, platform API) and add a product feed endpoint — Google Merchant–compatible XML (RSS 2.0 with the g: namespace) at /feeds/products.xml, or JSON if that's more idiomatic here. 2. Include per item: id, title, description, link, image_link, price with currency, availability, brand, and gtin/mpn when we have them. 3. Paginate or stream if the catalog is large; cache for ~1 hour. 4. Link the feed from robots.txt or a <link rel="alternate"> in the layout, show me the diff, and print the first two feed items rendered from real data.
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