AG Jeans

My e-commerce site is agjeans.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.

My e-commerce site is agjeans.com. A scan could not find a sitemap.xml, so crawlers and AI agents have no reliable way to discover our product pages. 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. 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://agjeans.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.

My e-commerce site is agjeans.com. A scan found no machine-readable product feed, which feed-based AI shopping agents (ChatGPT Shopping, Klarna, Google AI Mode) rely on. 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. 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.