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Amazon Research ST: amazon/product Query API

nexscope_data_st_amazon_product_query
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Amazon Research ST: amazon/product Query API.

Input Schema

NameRequiredDescriptionDefault
pageNoPage numbers; maximum 100 products per page, maximum 200 pages.
queryModeNoQuery method: `1` single condition, `2` multi-condition combination (AND).
queryTypeNoSingle condition query type, range 1-16; invalid when `queryMode=2`. See table below.
queryMonthNoHistorical snapshot month, format `yyyy-MM`; query real-time data if not specified, supported from 2024-01.
queryValueNoQuery value, the format is determined by `queryType`; when `queryMode=2`, the JSON condition array string is passed in.
marketplaceYesAmazon site codes: `us`, `gb`, `de`, `fr`, `in`, `ca`, `jp`, `es`, `it`, `mx`, `ae`, `au`, `br`, `sa`. UK uses `gb`. AU, BR, and IN do not support historical review.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.7/5.0
Behavior1/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, and the description adds nothing beyond that — no mention of pagination limits (only in the schema), no note on historical vs real-time behavior, no coverage of marketplace-specific restrictions. With annotations present the bar is lower, but the description contributes zero additional context.

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?

It is short, but that brevity reflects under-specification rather than efficiency: a single sentence that parrots the title earns no place and provides no front-loaded actionable information.

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

Completeness1/5

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

For a six-parameter tool with a multi-condition query mode, a 1-16 query type table, historical snapshot support, and no output schema, the description is wholly inadequate. An agent has no way to know what results to expect or how the two query modes differ without consulting the schema.

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?

Schema description coverage is 100%, and the schema itself thoroughly documents page limits, queryMode, queryType range, queryMonth format, and marketplace codes. The description adds nothing on top, so baseline 3 is appropriate since the schema carries the entire load.

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

Purpose2/5

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

The description merely restates the title ('Amazon Research ST: amazon/product Query API') without naming a verb, the resource being queried, or what kind of query it performs. An agent cannot distinguish it from siblings like nexscope_data_st_amazon_product_detail or nexscope_data_amazon_product_research based on this text alone.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool, when not to, or which sibling to prefer for product queries. The only navigational signal is the parameter name 'queryType', which the description never explains.

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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