# ProductSchema

> Free tool that checks whether an online store's product page can be read and cited by AI shopping
> assistants, and generates the JSON-LD Product markup it is missing. No account, no API key.

Everything this site publishes is measured from pages fetched live — no estimated numbers.

## Tools

- [Free audit](https://productschema.pages.dev/): paste a store domain or product URL, get a score,
  per-check detail, and a ready-to-paste JSON-LD snippet.
- [MCP server](https://productschema.pages.dev/mcp): the same audit as a Model Context Protocol tool
  (`audit_product_page`, streamable HTTP, no auth). Card:
  https://productschema.pages.dev/.well-known/mcp/server-card.json
- [A2A agent](https://productschema.pages.dev/a2a): the same audit as an Agent2Agent skill
  (JSON-RPC `message/send`, no auth, no streaming). Card:
  https://productschema.pages.dev/.well-known/agent-card.json

## Research

- [We read 168 online stores' product pages](https://productschema.pages.dev/ai-shopping-product-data-study):
  our own study of what product data real stores publish. Of 119 gradeable stores, 99% publish a price
  and 97% availability, but only ~36% a GTIN, ~14% a rating, and ~9% return or shipping policy in
  structured data. Measured twice, with both rounds and our own corrections published.

## Guides

- [Does ChatGPT recommend your store?](https://productschema.pages.dev/does-chatgpt-recommend-your-store):
  how to check in about 10 minutes, by hand.
- [Product schema markup examples](https://productschema.pages.dev/product-schema-markup-examples):
  copy-paste JSON-LD for rating, returns, shipping and GTIN, with the mistakes that get rich results pulled.

## Contact

- hello@snowfeetstore.com