blv_get_nutrition_data_children

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

Annotations already provide readOnlyHint, idempotentHint, and openWorldHint. The description adds valuable context about the specific dataset (menuCH-Kids) and the intended use case, going beyond the annotations without contradicting them. It does not detail behavioral traits like pagination or data size, but the annotations cover safety and idempotency.

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 highly concise, consisting of two short sentences that front-load the resource name and use case. Every word adds value, with no redundant or filler content.

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 tool's low complexity (2 optional parameters, no required, has output schema), the description fully contextualizes the tool. It specifies the dataset (Swiss national survey), the domain (children's nutrition), and the use case (comparison against recommendations). The presence of an output schema eliminates the need to describe return values.

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 coverage is 100%, with both parameters fully described in the input schema. The description does not add any additional meaning or syntax details beyond what the schema provides, so the baseline score of 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 clearly states it provides Swiss national children's nutrition survey data (menuCH-Kids) and specifies the use case of examining nutrient intake by age group against recommendations. It is distinct from all sibling tools, which cover animal health, antibiotics, etc., with no overlap.

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?

The description gives a clear use case (examine children's nutrient intake by age group against dietary recommendations) but does not explicitly state when not to use or mention alternatives. However, no sibling tool serves a similar purpose, so the context is sufficient for selection.

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