Product reviews

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

Annotations already declare a safe, idempotent, read-only, open-world read, so the burden is light. The description adds genuinely useful context beyond them: reviewer names are omitted (anonymized data), and the exact shape of each review record is disclosed even though no output schema exists. It does not mention review volume, sorting, or result totals.

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 short sentences, front-loaded with what the tool returns and followed by when to use it. Every clause carries information; nothing is repeated from the schema or annotations.

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?

With no output schema, the field enumeration is exactly what an agent needs to know what comes back, and the anonymization note and paging are covered. It leaves minor gaps around total review counts and any ordering of results, which matters somewhat for a paged list.

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%: the `id` parameter already documents the 6-character format and its provenance from ss_search/ss_product, and `page` documents the 10-per-page paging with min/max bounds. The description adds no meaning beyond this, so the baseline of 3 applies.

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 gives a specific verb and resource ('Read buyers' reviews of a product') and enumerates the returned fields (score, title, text, pros/cons, helpful votes, date), which makes the scope unambiguous. It stops short of naming sibling tools such as ss_product or ss_similar to explain the boundary, so it is clear but not fully sibling-differentiated within the description text itself.

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?

'Use to check quality complaints before recommending a product' supplies a concrete decision context for reaching for this tool rather than product metadata tools. There are no explicit exclusions or stated alternatives, so the guidance is clear but one-sided.

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