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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description usefully adds what is returned (id, title, URL) despite there being no output schema, plus the market/language coupling. It omits result limits, ranking, and pagination, which keeps it below 5.

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?

A single front-loaded sentence that names the action, the scope, and the return payload with no filler. The parenthetical Amazon.fr/en français detail slightly repeats what the schema already says.

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?

Missing: it never distinguishes this tool from 'search_models' or explains how results are limited or ordered, which matters for correct selection among six siblings. Return fields and market behavior are covered, but the sibling ambiguity leaves a real gap.

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 50%: 'market' is well documented in the schema, while 'query' is undocumented there and the description only adds the minimal '(texte libre)' hint. That partially compensates for the gap but gives no matching semantics (exact vs fuzzy, language expectations, syntax).

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?

States a specific verb and resource: 'Cherche des lave-vaisselle dans le comparateur WashyDish', and adds the scope (France/US markets, free-text query) plus the returned fields (id, titre, adresse). It does not differentiate itself from the sibling 'search_models', which an agent could easily mistake for this tool.

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?

It clarifies the two market contexts and that queries are free text, and the schema explains that each market has its own catalogue. However, there is no explicit when-to-use/when-not guidance relative to 'search_models' or 'compare_models', so the choice among the siblings is left to inference.

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