The skill
Install once. Attach an ASIN catalog export and get a readiness score per product, a top gap, and a fix list ranked by the spend each product carries.
What's inside
Three files, one job: be the product the assistant names
Built for Amazon sellers, not engineers.
Install guide
A two-minute setup, plus the exact columns to export so the score is real instead of unknown.
Plan B prompt
No skills access? Paste the included prompt into any Claude chat with your catalog. Same rubric, same ranking, zero setup.
How it works
Three steps, from a catalog export to a ranked fix list.
Step 1Export your catalog
Pull your ASINs with attributes, bullets, price, review count and recency, and ad spend per product.
Step 2Hand it to Claude
The skill scores the four things an assistant reads, attribute completeness, review signal, claim clarity, and price, and bands each ASIN ready, partial, or invisible.
Step 3Fix the costly ones first
Back comes a fix list ranked by ad spend times the readiness gap, with the specific empty attributes and stale-review dates to address.
No connection to your Seller Central account. You bring the export, the skill does the scoring. The audit improves how legible your listings are, it does not control Amazon's ranking.
How to make your Amazon catalog ready for AI shopping assistants
Amazon's Alexa for Shopping and Rufus increasingly answer a shopper by naming one or two products rather than showing a full results page. The product the assistant names is the one with the cleanest structured data and the freshest reviews. This free Claude skill scores each ASIN for that legibility and tells you exactly what to fix first.
What agent-readiness means
Agent-readiness is how easily an AI shopping assistant can read your listing and match it to a shopper's question. It rests on four things, how complete your category attributes are, how strong and recent your reviews are, how clearly your title and bullets state use case and compatibility, and whether your price is in line. A listing can rank fine in classic search and still be invisible to the assistant if those four are thin.
How the skill scores an ASIN
It reads your catalog export and scores each product on attribute completeness against the category set, review signal weighted toward recency, claim and copy clarity, and price competitiveness. It bands each ASIN as ready, partial, or invisible, marks any field it cannot judge as unknown rather than guessing, and never invents an attribute or a review date.
Why the fix list is ranked by ad spend
A poorly readable listing that carries heavy ad spend is budget feeding a product the assistant will not recommend. The skill ranks fixes by ad spend times the readiness gap, so the heavily promoted, low-readiness products surface first. Each item names the specific gaps, which attributes are empty and how stale the reviews are, so the fix is concrete.
Why now
Amazon has said plainly that the keyword-and-detail-page funnel is being supplemented by an agent-led one, and that mid-size sellers have only a few quarters before the largest brands absorb the agent shelf. The full background, including the two metrics that reveal the shift early, is in the source article, Amazon's Agentic Ads Just Went Live. Make Your Catalog the Product the Assistant Recommends.
Who it is for
Amazon sellers and brands, retail media and marketplace managers, and agencies auditing client catalogs before agentic shopping absorbs more of the demand.