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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so safety is covered. The description adds the useful limitation that weather is not handled yet and the intended next tool, but gives no further behavioral detail such as how incomplete inputs are treated.

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?

Three short sentences, front-loaded with the classification purpose and ending with the next-step instruction. The category list is slightly cryptic but no sentence is wasted.

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?

For a tool with full schema descriptions, an output schema, and rich safety annotations, the description supplies the essential pre-classification role and the handoff to recommend_weather_look. The main missing piece is a clearer statement of what the classification output represents and how it relates to recommend_look.

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%, so all five parameters are already documented with meanings and examples. The description's 'créneau, marche, pièce, ville' adds only loose category language and even mentions 'ville', which is not a schema parameter; baseline 3 is appropriate.

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 ('Je classe') and resource ('une demande') and lists the dimensions it extracts (créneau, marche, pièce, ville), so an agent can tell it is a pre-recommendation classifier. It also separates itself from weather tools with 'Pas encore de météo', though it does not distinguish itself from recommend_look or shop_the_look.

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 tells the agent this is a pre-weather step and to chain into recommend_weather_look, and explicitly excludes weather for now. It does not state when to choose it over recommend_look or other recommendation siblings, so guidance is partial.

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