Beardbrand

My e-commerce site is beardbrand.com. Our robots.txt currently disallows these AI agents, which prevents AI assistants from reading, recommending, or buying our products:

- Amazonbot (Amazon — Buy For Me)

Find where robots.txt is generated or stored in this repository (static file in public/, a robots route/handler, or platform config). The site runs on magento, so prefer that platform's idiomatic way of serving these files/markup (theme templates, app settings, or metafields) over hand-rolled middleware where it exists. Then:

1. Add an explicit "Allow: /" rule for each agent above (keep any existing Disallow rules for genuinely private paths like /cart, /checkout, /account).
2. Do NOT loosen rules for any user-agent we haven't listed, and preserve the existing sitemap reference.
3. Show me a diff of the change and list each agent whose effective access changes from blocked to allowed.
4. If robots.txt is managed by the e-commerce platform rather than this repo, tell me exactly where in the platform's admin to change it instead.

Context: this was flagged by ARC Report (arcreport.ai/brand) — verify after deploy by fetching https://beardbrand.com/robots.txt and checking the rules for each agent listed above.

My e-commerce site is beardbrand.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:

- ChatGPT-User (OpenAI — ChatGPT live browsing)
- ClaudeBot (Anthropic — Claude training)
- PerplexityBot (Perplexity — Perplexity / Comet)
- CCBot (Common Crawl — Open training data)
- Bingbot (Microsoft — Copilot / Bing)

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://beardbrand.com/ (expect 200, not 403).

My e-commerce site is beardbrand.com. A scan found JSON-LD on the site but no Schema.org Product markup, so AI shopping agents can't reliably read our product names, prices, availability, or images. The site runs on magento, so prefer that platform's idiomatic way of serving these files/markup (theme templates, app settings, or metafields) over hand-rolled middleware where it exists.

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.