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

With no annotations, the description carries the full behavioral burden and discloses almost nothing: read-only-ness is only implied by the get_ prefix, and there is no mention of auth requirements, error behavior for an invalid or unknown code (e.g. 2A, 971), or response size. Only the dataset-level scoping adds real 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?

It is a single short clause with the resource front-loaded and zero padding, which is good, but the brevity tips into under-specification rather than tightness. There is no structured layout beyond an em-dash separator.

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?

This is a simple one-parameter lookup with full schema coverage, so the bar is low, but there is no output schema and the description never indicates what the returned fiche includes (scores, population, boundaries). An agent cannot anticipate the result shape from the definition alone.

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% — the departement_code parameter is fully documented in the schema with INSEE examples (69, 2A, 971) and length bounds. The description adds no additional meaning beyond that, so the baseline 3 applies.

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 identifies the resource as a "fiche département" and scopes it with the hint "territoires.level=departement", which implicitly separates it from get_commune. However, it uses no verb ("retrieve"/"return") and never says what a "fiche" contains, so the purpose is only partially pinned down.

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?

There is no when-to-use guidance, no statement of prerequisites, and no explicit routing to or away from siblings such as get_commune or get_territory_scores. The only usage signal is the embedded dataset-level phrase, which an agent must infer from.

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