Ozon Product Reviews

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

The description goes well beyond the annotations by disclosing the Tier-1/Tier-2 fallback strategy, automatic page walking, 30 reviews per page, deduplication by review UUID, a hard cap of 10 pages, and detailed partial-success semantics. It also explains exactly when errors are raised versus when failures degrade to partial results. This is exceptionally transparent and does not contradict the readOnly/idempotent 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?

The description is long but every section earns its place: purpose, transport fallback, pagination behavior, return format, and error semantics are all directly relevant to invoking the tool correctly. The use of headings and front-loaded key information keeps it navigable despite its length.

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's complexity, the description is remarkably complete. It covers input normalization, pagination, dedupe, hard limits, exact return fields, partial success conditions, and error types. The presence of an output schema further reduces the need to describe return values, so nothing important is missing for correct invocation.

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?

The input schema already covers all three parameters at 100% coverage, so a baseline of 3 is appropriate. The description adds real value by explaining how `limit` interacts with pagination: pages are walked until `limit` texts are collected, with deduplication and a hard page cap. This gives the agent a more accurate mental model of what `limit` means in practice.

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 opening sentence states a specific verb and resource: 'Fetch Ozon product review texts + star distribution'. It clearly distinguishes itself from sibling tools like ozon_card or ozon_search by focusing on reviews plus the distribution, and it even references the same fetch path as ozon_card for technical context. An agent can understand exactly what this tool does.

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 makes the intended use case obvious: retrieving Ozon product review texts and star distributions. It also explains pagination behavior and partial-success semantics, which guide the agent when interpreting results. However, it does not explicitly state when to choose this tool over a sibling such as ozon_card or ozon_search, so the guidance is clear but not exhaustive.

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