Walmart

My e-commerce site is walmart.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 walmart.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://walmart.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 walmart.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://walmart.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://walmart.com/llms.txt