get_reviews

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

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds genuinely non-obvious behavior beyond those annotations: statistics are only computed on unfiltered requests, the response indicates whether the card merges several models, and reviewer names are never returned. This is exactly the kind of contextual detail an agent needs before invoking the tool.

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 compact and front-loaded with the core output, then adds the conditional statistics behavior and a privacy caveat. There is no filler, and every sentence contributes operational value without requiring the agent to parse a long block of prose.

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 rich input schema, output schema, and annotations, the description is complete: it covers what the reviews contain, the conditional statistics behavior, the multicard scope implication, and the reviewer-name privacy constraint. Nothing essential for an agent to call and interpret this tool is missing.

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 describes all 11 parameters with high coverage (100%), so the baseline is 3. The description adds no per-parameter syntax or format details; its extra notes about unfiltered requests and scope are behavior-level observations rather than parameter semantics. The schema carries the weight here.

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 immediately identifies the resource as buyer reviews from dns-shop.ru and enumerates the concrete fields returned (date, stars, pros, cons, comment, usage period, bought variant, votes). This clearly distinguishes get_reviews from sibling tools like search_products, get_product, and compare_products, which are about product discovery and comparison rather than reviews.

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 use case is implied by the tool name and content: use this when you need buyer reviews or their statistics. However, the description never explicitly says when to use this instead of a sibling, nor does it mention any exclusions or alternative tools. The guidance is present but only by implication.

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