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Glama

Extract Product

extract_product

Extract title, price, currency, and availability from any product page via Shopify JSON, schema.org JSON-LD, OpenGraph, or headless-browser fallback.

Instructions

Title, price, currency, availability from any product page: Shopify JSON, schema.org JSON-LD, OpenGraph, then a headless-browser fallback.

Input Schema

NameRequiredDescriptionDefault
urlYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden, and it does disclose a real behavioral trait: the extraction ladder (Shopify JSON → JSON-LD → OpenGraph → headless browser). That tells the agent there is a gradual fallback and that the call may be slow when the browser path is used. It does not cover failure modes, timeouts, rate limits, or auth requirements, which is a notable gap for a scraper with zero annotation coverage.

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

Conciseness4/5

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

One compact sentence that front-loads the extracted fields and appends the strategy chain. No filler, though it reads as a clipped fragment rather than a polished directive.

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?

The output schema is provided, so return values need no explanation, and the method is covered. What remains missing is input qualification—what constitutes a valid product page URL—and any behavioral caveats around the browser fallback. Adequate but not complete for a tool with no annotations and an undocumented parameter.

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

Parameters2/5

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

There is one parameter (url) at 0% schema description coverage, and the description never names or describes it. 'From any product page' only loosely implies a page URL; it does not say whether non-product URLs are accepted or what the expected URL format is. Minimal compensation for an undocumented required parameter.

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?

The description enumerates exactly what is returned (title, price, currency, availability) and from what (a product page), which clearly separates it from siblings like search_products, compare_prices, and get_price_history. It is a fragment rather than a full verb+resource statement, but the name supplies the verb and the scope is unambiguous.

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?

Usage is implied: you call this when you have a concrete product URL to scrape. However, there is no explicit when-to-use guidance, no stated prerequisites, and no mention of when this is preferable to the price/comparison siblings.

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