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Crawlora MCP

chewy_product_reviews

Read-only

One page of a Chewy product's customer reviews -- rating, title, body, author, submission date, helpful count, incentivized flag and contributor badge -- with sorting and positive/negative filtering. chewy_product embeds only the first 20 reviews with no way to page past them; this reaches the whole set, and products routinely carry thousands. id is the numeric id from any chewy.com PDP URL; reviews are shared across a product's variants, so any variant's id returns the same set. sort accepts MOST_RELEVANT, NEWEST, OLDEST, HIGHEST_RATING, LOWEST_RATING, PHOTOS; filter accepts POSITIVE (4-5 star) or NEGATIVE (1-3 star). total reflects the current filter, while rating_count stays the product's overall tally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesRequired. The numeric id from a chewy.com PDP URL, e.g. 767806 from https://www.chewy.com/<any-slug>/dp/767806. Reviews are shared across a product's variants, so any variant's id returns the same set.
pageNoOptional, 1-based, defaults to 1.
sortNoOptional. One of MOST_RELEVANT, NEWEST, OLDEST, HIGHEST_RATING, LOWEST_RATING, PHOTOS. Defaults to Chewy's own ordering when omitted.
limitNoOptional, 1 to 50, defaults to 20. How many reviews to return per page.
filterNoOptional. One of POSITIVE (4-5 star) or NEGATIVE (1-3 star). Omit for all reviews.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds real behavioral context beyond that: reviews are shared across variants, results are one page, total reflects the active filter while rating_count is the product's overall tally, and products routinely carry thousands of reviews. Only the response/pagination mechanics are left implicit.

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?

Front-loaded with the purpose, then field list, then sibling differentiation, then parameter details. Dense but every sentence carries information; the field enumeration is slightly verbose but not wasteful.

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?

An output schema exists, so return values need not be re-explained, yet the description still maps the fields and clarifies the total vs rating_count distinction. For a paginated read tool with full schema coverage, nothing an agent needs 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 would be 3, but the description adds meaning beyond the schema by listing the accepted sort values (MOST_RELEVANT, NEWEST, ...) and filter values (POSITIVE/NEGATIVE with star ranges), which the schema does not enumerate (0 enums declared). This closes a real gap.

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 ('One page of a Chewy product's customer reviews'), enumerates the returned fields, and explicitly distinguishes itself from chewy_product, which only embeds the first 20. An agent can tell exactly what this returns and how it differs from the sibling.

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

Usage Guidelines5/5

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

Gives an explicit when-to-use rule and names the alternative: chewy_product embeds only the first 20 reviews with no paging, while this reaches the whole set. The condition that selects this tool over the sibling is stated outright.

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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