agentic-commerce-catalog-audit

Purpose

Audits every product in a Shopify store against the Agentic Commerce Spec v1.0 — an open scoring standard for AI shopping agent visibility. Returns a 0-100 score per product, a per-dimension breakdown (title, description, images, metadata, taxonomy, variants, reviews, structured data), and a ranked list of issues by predicted impact on AI agent recommendation probability.

Use this skill when you want to know which of your products will get skipped by ChatGPT, Gemini, Claude, Mistral, and DeepSeek when they generate shopping recommendations, and which fixes would lift visibility fastest.

Prerequisites

• Authenticated Shopify CLI session: shopify auth login --store <domain>
• API scopes: read_products, read_product_listings

Parameters

Workflow Steps

1. OPERATION: products — query Inputs: first: 50 per page, pagination via cursor until limit reached or no more products Expected output: Product nodes with title, descriptionHtml, productType, vendor, tags, images, media, variants, metafields, seo

2. For each product, compute the Agentic Commerce Spec v1.0 score using the reference scorer in @commerce-agentic/spec. The scorer is deterministic, runs locally, no network calls. Output per product:

   {
     "productId": "gid://shopify/Product/12345",
     "title": "...",
     "totalScore": 67,
     "grade": "C",
     "dimensions": {
       "title": 14, "description": 9, "images": 7,
       "metadata": 10, "taxonomy": 6, "variants": 8,
       "reviews": 5, "structured_data": 8
     },
     "issues": ["Missing google_product_category metafield", "Alt text on 1/6 images"],
     "aiVisibilityIndex": 0.62
   }