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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond them by disclosing the shape of the response — each list comes with its item count and fields — which matters because there is no output schema. It does not mention ordering or pagination, which keeps it below a 5.

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?

A single front-loaded sentence: verb and resource first, then the parenthetical examples, then the returned attributes. Every clause carries information 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?

For a zero-parameter read tool with full annotation coverage and no output schema, the definition supplies the essentials: what is listed and what each entry contains. The remaining gap is return-shape detail (ordering, total counts, whether all lists or a subset are returned), which is minor at this complexity.

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 tool takes zero parameters, so the schema-vs-description comparison is moot and the baseline of 4 applies. The description introduces no phantom parameter expectations, which is consistent with the empty 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?

States a specific verb and resource ('Lister les listes') and clarifies the domain with concrete examples (courses, à regarder, recettes, envies), so an agent knows this enumerates user lists rather than their contents. It stops short of naming siblings like dandori_get_list_items or dandori_list_wishes, so differentiation is inferred from the examples rather than stated.

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 is implied: this is the enumeration entry point, and mentioning 'nombre d'éléments' signals it returns counts rather than items, which indirectly distinguishes it from dandori_get_list_items. There is no explicit when-to-use/when-not guidance and no alternative is named.

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