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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description contributes additional context about the age group (15-24) and data source. It does not contradict annotations. However, it could be more transparent about data limitations, update frequency, or seasonality effects.

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 moderately concise, with three sentences covering purpose and use cases. It uses both German and English, which is acceptable but slightly redundant. The core action is stated in the first sentence, and the rest provides relevant context. It could be trimmed to be more front-loaded.

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 presence of an output schema and comprehensive annotations, the description provides sufficient context for educational planning and career counseling applications. It adds use-case detail beyond what structured fields provide. However, it could mention that data is likely aggregated over time and note any potential missing values or data freshness.

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 adds minimal new semantic detail beyond the schema; it mentions 'canton' and 'response_format' implicitly but provides no additional constraints or examples. Baseline 3 is appropriate given high schema coverage.

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 that the tool retrieves youth unemployment data (ages 15-24) from SECO/AMSTAT, specifically for educational planning and career guidance. It is specific about the resource (youth unemployment data) and the source, but could better differentiate from sibling tools like seco_get_unemployment_overview which may cover all ages.

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 implies usage for educational planning and vocational guidance, but lacks explicit guidance on when to use this tool versus siblings such as seco_get_unemployment_overview or seco_get_job_seekers. No alternative tools are mentioned, and there are no conditions provided for when not to use this tool.

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