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amazon_product

Retrieve product details, pricing, reviews, and ratings from any Amazon product page using its ASIN. Supports 20+ global domains with localization.

Instructions

Retrieves comprehensive product data from any Amazon product page using its ASIN. Supports 20+ Amazon domains globally with localization options. [Credits: 1 API credit per successful request when country=us. 5 API credits per request for any other country (per the country parameter's own credit note).] Notes: domain and country are independent: domain selects the Amazon TLD to scrape, country affects marketplace localization/pricing and credit cost. No pagination applicable (single product lookup). Returns: { title, location, search_filter, product_information: {Brand Name, UPC, ASIN, Customer Reviews:{ratings_count,stars}, ...}, parent_asin, description, is_prime_exclusive, aplus, main_image, images: [], product_category, average_rating, feature_bullets: [], total_reviews, ratings_distribution: [{rating, distribution}], customer_reviews: [{customer_name, rating, review_title, date, review_snippet}] }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinYesAmazon product ID (ASIN), found in the product URL (e.g. B00AP877FS).
domainYesTLD extension of the Amazon domain to scrape. Examples: com, in, de, fr, co.uk. See Amazon Supported TLDs doc for the full list.
countryYesISO country code for targeting a specific Amazon marketplace. Costs 5 credits per request except USA which costs 1 credit. See Amazon Supported Countries doc for the full list. (default: us)
languageNoStandard ISO 639-1 language code (e.g. en, de, fr) to specify the language for product data.
postal_codeNoTo get data from a particular postal code.
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses credit costs (1 vs 5 credits), explains domain/country independence, notes no pagination, and outlines return fields. Missing details like error handling or rate limits but adequate for a read tool.

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?

The description is well-structured with a main purpose sentence, then notes on credits and domain/country, and a return structure summary. It is informative without being overly verbose, though slightly long due to the return format details.

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

Completeness4/5

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

Given 5 parameters, no annotations, and no output schema, the description provides significant context: return structure (partial), credit costs, domain/country semantics, and no pagination. It could be more complete with error handling but covers the essentials for a product lookup.

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

Parameters4/5

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

Schema coverage is 100%, baseline is 3. The description adds value by explaining the domain/country interaction and credit cost implications, which go beyond the schema descriptions. This extra context justifies a score of 4.

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 tool retrieves comprehensive product data from any Amazon product page using its ASIN. This specific verb+resource+identifier distinguishes it from sibling tools like amazon_offers, amazon_reviews, and amazon_search which focus on specific subsets of data.

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

Usage Guidelines4/5

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

The description provides clear context on when to use this tool (single product lookup) and explains the relationship between domain and country parameters. However, it does not explicitly contrast with sibling tools or state when not to use it, leaving room for improvement.

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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