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Crawlora MCP

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xbox_reviews

Retrieve Xbox product ratings and reviews, including average, total, and per-star counts, plus written reviews with optional sorting and star filtering. Returns empty results for products without reviews.

Instructions

Get ratings and reviews for an Xbox catalog product. Returns a product's aggregate star-rating breakdown (average, total, and per-star counts) and up to item_count written reviews, optionally sorted and/or filtered to one star rating. A product with no reviews yet (e.g. a pre-order) returns a null ratings summary and an empty reviews list, not an error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNoDisplay locale (BCP-47)
order_byNoReview sort order
item_countNoNumber of reviews to return (1-25)
product_idYesXbox catalog product id
star_filterNoOnly return reviews with this exact star rating (1-5); omit for all ratings

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It goes beyond a simple 'get' by disclosing the no-reviews edge case (null ratings summary, empty reviews list, not an error) and clearly describing the return components. It does not mention authentication or rate limits, but for a read-only review retrieval this is not a major gap.

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 two well-structured sentences. It front-loads the primary purpose, then details the return payload and a key edge case. Every sentence earns its place with no repetition or filler.

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?

There is no output schema, so the description appropriately explains the return structure: aggregate star-rating breakdown, up to item_count reviews, optional sort/filter, and the no-reviews behavior. Minor details like locale defaults or item_count defaults are not covered, but the essential calling context is present.

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%, so the structured schema already documents all five parameters. The description only restates parameter-related concepts (item_count, optional sorting, star filtering) without adding new details or clarifying defaults, which aligns with the baseline score of 3.

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 starts with a concrete verb and resource ('Get ratings and reviews for an Xbox catalog product') and clearly enumerates the return values: aggregate star-rating breakdown, per-star counts, and a variable number of written reviews. This makes it easily distinguishable from sibling tools like xbox_game or xbox_search by the explicit ratings/reviews focus.

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?

Usage is implied rather than stated: if you need ratings and reviews for a specific Xbox product, this is the tool. It does not explicitly name sibling tools or provide when-to-use versus when-not-to-use guidance, so an agent must infer the appropriate context from the name and description.

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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