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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds meaningful behavioral context beyond those annotations: the tool depends on local weather and must never assume Paris as a default. No contradiction with 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?

Three short, purposeful clauses: core purpose first, then input constraints, then the no-default-Paris behavior. Every clause earns its place and there is no filler.

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 output schema and annotations, the description sufficiently covers what the tool returns and how to supply location. The main gap is the lack of sibling differentiation, but the core calling requirements are present.

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 schema documents days, latitude, and longitude, and the description adds semantic value by framing city/postal code OR latitude/longitude as the location selection and confirming that Paris is never assumed. This goes beyond what the schema alone provides.

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 clearly states the resource: looks for morning, midday, and evening based on local weather. It also specifies location input modes. It doesn't explicitly differentiate itself from the sibling 'recommend_weather_look', so it stops short of a 5.

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 gives clear input guidance ('Ville/CP OU latitude+longitude') and an important rule ('Je ne suppose jamais Paris'), but it does not say when to use this tool versus alternatives like recommend_weather_look or get_weather_context. Usage context is implied rather than explicit.

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