What makes a listing buyable.

What "buyable" needs beyond stock.

An AI agent has already checked that a product is in stock. Buyable asks more of it than that: is the price the one that'll actually be charged, and can this specific item reach this specific buyer at all. Miss either and "in stock" stops meaning anything useful.

What makes one listing easier for an agent to sell than another.

Given two nearly identical products, an AI agent recommends the one with fewer unresolved questions, not the one with better marketing copy. The gap between them is almost always one missing, narrow fact, not a missing feature.

What a product feed needs that a product page doesn't.

A product page is written for a person looking at one item. A product feed is what an AI agent reads to compare many at once, and it needs a different kind of precision: structured, decision-relevant fields, not the same copy reflowed into a spreadsheet.

Variants, stock and delivery: what an agent checks before it recommends.

Three facts gate whether an AI agent will recommend a product at all, regardless of anything else about it: does the specific variant exist, is it there right now, and will it arrive in time. Get any one wrong and the rest of the listing doesn't matter.

Returns and sizing: the two questions agents ask that catalogues rarely answer.

Sizing and returns are the two questions that decide whether an AI agent will risk a recommendation at all, and most catalogues answer neither with any real specificity. "True to size" and "easy returns" aren't answers, they're the absence of one.

Multi-brand retailers: keeping every label distinct when an agent is comparing.

A retailer selling forty brands under one site template often ends up saying the same thing about all of them. An AI agent comparing two products from two different brands needs the fact that's true of each one, not a house style that's quietly smoothed the real differences away.