Castlery

www.castlery.com
Last scanned Jun 20, 2026, 6:18 AM
Verdict
Open to AI agents
ARC Score v1.0
67/100Mostly open
How it's computed →
Agent access50/50
Structured data7/25
Protocol files0/15
Scan stability10/10

Agent access

AgentStatusSource
GPTBotAllowedrobots.txt: Allow
ChatGPT-UserAllowedrobots.txt: Allow
ClaudeBotAllowedrobots.txt: Allow
Claude-WebAllowedrobots.txt: Allow
PerplexityBotAllowedrobots.txt: Allow
Google-ExtendedAllowedrobots.txt: Allow
AmazonbotAllowedrobots.txt: Allow
BingbotAllowedrobots.txt: Allow
CCBotAllowedrobots.txt: Allow

Infrastructure

PlatformcustomCDNcloudfrontWAFnone

Data signals

  • JSON-LDNot detected
  • Schema.org ProductNot detected
  • Open GraphYes
  • Product feedYes
  • llms.txtNo

Change history · last 90 days

0 changes
No 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.

No JSON-LD structured datashow prompt
My e-commerce site is castlery.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 sitemap.xmlshow prompt
My e-commerce site is castlery.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://castlery.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 llms.txtshow prompt
My e-commerce site is castlery.com. We don't publish an llms.txt file yet — the emerging convention (llmstxt.org) that gives language models a concise, curated guide to a site.

In this repository:

1. Create /llms.txt (served at https://castlery.com/llms.txt as text/plain or text/markdown) following the llms.txt format:
   - H1 with our brand name,
   - a one-paragraph blockquote summary of what we sell and who we serve,
   - sections linking to our most useful pages for an AI agent: bestsellers/category pages, shipping & returns policy, size guides, FAQ/support, and store locator if any.
2. Write the summary from this repository's real content (README, about page, homepage copy) — keep it factual, no marketing superlatives.
3. Keep it under ~200 lines, every link absolute.
4. Show me the full file content and where you wired it to be served.

Verify after deploy: curl https://castlery.com/llms.txt

Embed this score

ARC Score badge for Castlery
HTML
<a href="https://www.arcreport.ai/brand/castlery"><img src="https://www.arcreport.ai/badge/castlery.svg" alt="ARC Score for Castlery" height="22"></a>
Markdown
[![ARC Score for Castlery](https://www.arcreport.ai/badge/castlery.svg)](https://www.arcreport.ai/brand/castlery)

Updates automatically with each daily scan.

Scanned daily via robots.txt parsing and live HTTP tests for 9 AI agents. Changes are confirmed across two consecutive scans before publishing. Read the full methodology →