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ozon_product_rating_by_sku

Retrieve content ratings for provided SKUs to evaluate product listing quality and identify areas for improvement.

Instructions

Content rating of goods (рейтинг контента).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skusYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.5.2

TDQS

D1.7/5.0
Behavior1/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'Content rating of goods'. It does not state whether this is a read-only lookup, what data is returned, whether output is per-SKU, or any pagination, rate-limit, or authorization behavior.

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?

The description is extremely brief, but this is under-specification rather than purposeful conciseness. It does not front-load any actionable information about behavior, input, or output.

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?

There is no output schema, no annotations, and no behavioral description. An agent would not know what the tool returns, how to interpret the result, or how this differs from the many rating and product tools in the sibling list. The description is inadequate for correct invocation and result interpretation.

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

Parameters2/5

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

The single 'skus' parameter is self-descriptive from the tool name and schema, but schema description coverage is 0% and the description adds no explanation of what values are expected, what an SKU refers to, or any constraints like array size or uniqueness.

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 'Content rating of goods (рейтинг контента)' is a noun phrase that restates the tool name without stating a specific operation such as 'get' or 'retrieve'. It does not differentiate this tool from related siblings like ozon_rating_summary or ozon_product_info.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives. There is no discussion of exclusions, prerequisites, or related rating/product tools, so an agent must infer usage entirely from the name and schema.

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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