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Product Catalog Extractor — Ecommerce Products (AI)

product_catalog_extractor
Read-only

Extract a store's full product catalog into clean structured rows — title…. Extract a store's full product catalog into clean structured rows — title, price, variants, SKU, availability, images. Uses Shopify's public products.json…

Input Schema

NameRequiredDescriptionDefault
inputNoInput for Product Catalog Extractor — Ecommerce Products (AI). See https://apify.com/noniner/product-catalog-extractor.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds useful mechanism context (it reads Shopify's public products.json, meaning it only succeeds against Shopify stores), but stops before any limits, pagination, rate, or failure behavior, and is cut off mid-sentence.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening sentence is literally repeated with an ellipsis and the description ends mid-sentence, so it is both malformed and wastes its first clause. Content that survives is reasonably front-loaded but the artifact damage is severe.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does list returned fields (title, price, variants, SKU, availability, images), which is valuable. But it never explains how to point the tool at a store, nor scope limits, leaving an agent without enough to invoke it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter with 100% schema coverage, so the baseline of 3 applies. However, the description never says the input is a store URL/domain, and the schema's own parameter text is just a documentation link, so nothing in prose compensates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Extract a store's full product catalog') plus the exact fields returned, and the mention of Shopify's products.json scopes it relative to siblings like etsy_scraper or amazon_reviews_scraper. The purpose is clear, though the text is duplicated/truncated with an ellipsis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The Shopify reliance implies usage (only works on Shopify storefronts) but there is no explicit when-to-use or when-not guidance, and no mention of the closer sibling shopify_store_analyzer or when to prefer it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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