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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, covering safety and idempotency. The description adds no contradictory information and lists return fields, but does not disclose additional behavior beyond what annotations convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no fluff, front-loaded with the most important information (what the tool returns), followed by input options. Every sentence is essential.

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

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

For a read-only tool with annotations, the description covers return fields and input flexibility. No output schema, but the field list compensates. It omits error handling or edge cases, but the context is sufficient for typical use.

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

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

Schema coverage is 100% with an adequate description. The tool description adds value by listing the specific return fields, which the schema does not include. Input types are already in schema description.

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

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

The description clearly states it retrieves full details for a single product, lists specific fields returned (price, rating, seller, images, etc.), and differentiates from sibling tools (ozon_product_reviews for reviews, ozon_search for search results).

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

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

The description implies when to use (to get product details) and provides accepted input formats (SKU, URL, slug). It does not explicitly state when not to use or mention alternatives, but sibling tool names are provided, allowing inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Description adds context beyond annotations (readOnlyHint true) by detailing returned fields and accepted input formats (SKU, URL, slug). No contradictions, but omits potential behavioral traits like pagination or ordering.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two efficient sentences: first states purpose and output fields, second specifies input flexibility. No wasted words, front-loaded with core action.

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

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

Given the tool simplicity (2 params, simple data), description covers all needed context: output fields, input types, and limits (via schema). No output schema required; completeness is appropriate.

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

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

Schema already has 100% description coverage for both parameters. Description reiterates input types for 'product' but adds no new semantics beyond schema. Baseline 3 maintained.

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

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

Description clearly states it reads reviews for an Ozon product, listing specific data fields (author, score, pros/cons, etc.). This distinguishes it from siblings: ozon_product_details (product info) and ozon_search (search results).

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

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

Description implies usage for retrieving reviews but does not explicitly contrast with siblings or specify when to choose this over ozon_product_details or ozon_search. No when-not or alternative guidance provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, so the description doesn't need to repeat that. It adds some behavioral context (returns specific fields, currency RUB, numeric price), but nothing beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, compact and front-loaded. First sentence states purpose and output; second gives usage guidance. No wasted words.

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

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

Given 5 well-described parameters, complete annotations, and no output schema, the description provides sufficient high-level context and usage advice. It lists output fields but not detailed structure, which is acceptable.

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

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

Schema coverage is 100%, so all parameters are described in the schema. The tool description does not add new parameter information beyond the schema, meeting the baseline for high coverage.

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

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

The description clearly states the tool searches products on Ozon marketplace, returning specific fields like name, price, rating, etc. It distinguishes from sibling tools (ozon_product_details, ozon_product_reviews) by focusing on search and price comparison.

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

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

The description explicitly says 'Use this to find products and compare prices, then hand the URLs to the user.' It gives clear when-to-use context, though it doesn't explicitly mention alternatives for details/reviews.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.