apiguru-amazon-data

Feedback reviews for a seller

seller_reviews

Read-onlyIdempotent

Fetch paginated Amazon seller feedback filtered by star rating to evaluate seller reputation and customer satisfaction.

Instructions

Returns paginated seller feedback, optionally filtered to a star-rating window. Price: $0.003 per call. from_rating and to_rating are optional; omit both for unfiltered feedback. A page holds 5 reviews and the answer carries current_page and has_next_page; Amazon exposes no total, so page until has_next_page is false (up to page 100).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`geo`	No	Marketplace country code.	US
`page`	No	Result page, 1-based, 5 reviews a page; has_next_page in the answer says whether another exists.
`limit`	No	How many seller reviews to return from this page (0 = all of them). A full page is up to 48 rows and about 54 KB, which most clients spill to a file instead of showing inline. The answer carries _truncated with the true count when it trims.
`fields`	No	Comma-separated row fields to return instead of the light set, e.g. "asin,product_title,product_price". Rows list what they left out under _omitted_fields.
`compact`	No	Return light rows: identity, price, rating, badges and one delivery_date, dropping the long delivery prose that repeats itself across three fields. false returns every field the REST API sends (roughly 3x the size).
`seller_id`	Yes	Amazon seller ID. Required.
`to_rating`	No	Highest star rating to include, 1-5.
`from_rating`	No	Lowest star rating to include, 1-5.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`success`	No
`request_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 27, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds important behavioral context: per-call pricing, page size, current_page/has_next_page, no total count, and the upper page limit.

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?

Three efficient sentences, front-loaded with the core return behavior, then pricing and pagination details. Every sentence contributes useful information without repetition.

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

Completeness5/5

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

With rich annotations, full schema descriptions, and an output schema, the description covers the remaining agent-relevant concerns: cost, filtering behavior, pagination mechanics, and the page cap. Nothing critical for correct invocation is missing.

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%, so the baseline is 3. The description adds meaning for from_rating/to_rating by noting they are optional and that omitting both yields unfiltered feedback, plus it adds the undocumented page 100 limit.

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?

States a specific verb and resource: returns paginated seller feedback, optionally filtered to a star-rating window. This distinguishes it from sibling product_reviews because it targets seller feedback rather than product reviews.

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?

Explains when to omit rating filters for unfiltered feedback and how to page until has_next_page is false, including the page 100 cap. It gives clear usage context but does not explicitly compare against alternatives such as product_reviews.

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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