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Darshan972

Scrapingdog MCP Server

by Darshan972

Amazon Product API

amazon_product

Get Amazon product price, specs, and ratings by entering an ASIN. Extracts data from the product page.

Instructions

Scrape a single Amazon product page (price, specs, ratings) by ASIN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinYesAmazon Standard Identification Number (ASIN) of the product.
domainNoAmazon TLD, e.g. com, in, de, co.uk. (API default: com)
countryNoTwo-letter ISO marketplace country code. (API default: us)
postal_codeNoPostal/ZIP code to localize price and availability.
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions the scraping action and basic data types, but does not disclose potential rate limits, anti-bot challenges, error handling, or the structure of the response. This leaves significant behavioral aspects undocumented.

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

Conciseness5/5

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

The description is a single, focused sentence that front-loads the core action and target. It contains no redundant information and every word contributes to understanding the tool's function.

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?

For a simple tool with a well-documented schema, the description covers the primary purpose and output content. However, the lack of an output schema and annotations means the description should explain more about return values, error cases, and usage constraints. It is minimally adequate but leaves gaps for complex scenarios.

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?

The schema already provides 100% parameter documentation, so the description need not repeat it. The description adds 'by ASIN' reinforcing the required parameter, but does not explain the optional domain, country, or postal_code parameters beyond what the schema already states. This meets the baseline for a well-documented schema.

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

Purpose5/5

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

The description clearly states the action ('Scrape'), the resource ('a single Amazon product page'), the key input ('by ASIN'), and the data captured ('price, specs, ratings'). This distinguishes it from sibling tools like amazon_search (search) and amazon_reviews (reviews), making the purpose explicit and 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?

The description implies usage for retrieving details of a specific product via ASIN, but it does not explicitly mention when to choose this over alternatives like amazon_search or amazon_reviews. There are no exclusions or alternative references, so the guidance is only implied, not stated.

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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