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

Annotations already declare the read-only, idempotent, non-destructive, open-world profile, so safety is covered. The description adds meaningful behavioral context beyond that: it states that an empty feed is reported via limits[] and that the editorial look is provided, and explicitly says it does not invent products. This honesty guarantee is valuable and not captured by 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 compact sentences, with the core intent stated first and the empty-result behavior second. It is efficient, though the phrasing is slightly cryptic and could be clearer for an agent parsing intent.

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?

An output schema exists, so return values need not be explained, and schema coverage is complete. However, the description never clarifies what a 'piste marchande' actually is in this tool's output (external product links vs editorial recommendations), leaving a gap given the many similar shopping/look siblings.

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 description coverage is 100% and the three parameters (query, limit, include_products) are fully documented in the schema. The description only indirectly alludes to product inclusion ('je n'invente pas de produit') and mentions limits[] as a response field, without adding syntax or format meaning beyond the schema.

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 says it looks for 'pistes proches de l'intention' (leads close to the buying intention), which hints at a shopping search, but 'pistes' is vague about what is returned (products, links, editorial suggestions). It also does not distinguish itself from siblings like shop_the_look, recommend_look, or shopping_criteria.

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 phrase 'proches de l'intention' implies it should be used when the user expresses a purchase intention, which gives some contextual guidance. However, there are no explicit when-not conditions or named alternatives among the many sibling tools, so selection still requires inference.

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