ShelfReadable

Commerce merchants can expose inconsistent product, offer, availability and policy facts across storefront markup, feeds and documents. ShelfReadable maps declared source fields into structured catalog data, a hosted product feed, a crawler-guidance file and machine-readable policy summaries, then requires merchant review before publication and refreshes from source changes. The supplied research confirms that a large commerce platform already deployed default llms.txt files across roughly 7.3 million stores, weakening the original generation wedge. It also reports that those defaults are generic and omit rich catalog and policy data, while no major AI crawler has confirmed use. Zero referenced APIs are verified. The product therefore focuses on governed structured data and feed consistency, not a one-afternoon promise to make a store agent-shoppable. Generated policy text is a summary candidate, never legal interpretation; catalog mappings can be wrong even when syntactically valid. Source observation, mapping candidate, merchant approval, publication, fetch observation, agent behavior, transaction capability and commercial outcome remain separate. Success is current, reproducible machine-readable data—not discovery, recommendation, checkout compatibility or revenue.

A small or mid-sized ecommerce merchant that lacks reliable structured catalog and policy feeds across its storefront surfaces.