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

No annotations are provided, so the description carries the burden. It discloses the legal basis and covered categories, implying a read-only lookup. However, it does not mention output format, potential errors, authentication needs, or whether the data is static. The description is transparent about what it returns but lacks deeper behavioral context.

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?

The description is bilingual and somewhat verbose, but each sentence carries useful information: purpose, legal references, category coverage, and optional filter. It is front-loaded with the main purpose and remains efficient despite the length.

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 description could clarify what fields are returned per category (e.g., multiple temperature types, units). It mentions categories and temperature types but not the exact output structure. Given the simple tool nature and rich sibling context, it is adequate but not fully complete.

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 covers 100% of the parameters, with a full description of the 'categorie' parameter and its allowed values. The description adds regulatory context but does not go beyond the schema in explaining parameter semantics. 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 clearly states the tool returns French regulatory food temperatures for storage, cooling, and service by product category. It uses a specific verb ("Renvoie") and resource, and distinguishes from sibling tools like get_temperatures_cuisson by focusing on non-cooking temperatures.

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?

Usage context is implied through the scope description (regulatory storage/cooling/service temperatures), but there is no explicit comparison to alternatives or when-not-to-use conditions. The sibling tool get_temperatures_cuisson is not mentioned, so the agent lacks explicit guidance for choosing between them.

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