sbb_get_passenger_frequency

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable context beyond this: the dataset is updated annually, contains specific average metrics, and the return includes pagination information. This enriches the behavioral understanding without contradicting annotations.

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 well-structured and concise: a lead sentence on purpose, a brief dataset context, an Args list, and a Returns schema. Every section earns its place without redundancy. It is front-loaded and not overly verbose.

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?

The description is complete for a read-only data retrieval tool: it specifies the dataset scope, update frequency, available metrics, all input parameters with defaults, and a return schema (despite no output schema). Combined with strong annotations, the agent has everything needed to select and invoke the tool correctly.

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?

Although the schema already describes each parameter, the description's Args section adds practical examples and constraints (e.g., 'ZH', '2024', partial search for station_name, default limit 20, response_format options). Since schema coverage is contextually marked as 0% (though schema has descriptions), the description effectively compensates by providing detailed parameter semantics.

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 begins with a clear, specific verb-resource pair: 'Ruft Passagierfrequenzdaten (Ein-/Aussteigende) für SBB-Bahnhöfe ab' (retrieves passenger frequency data for SBB stations). It further specifies the contained metrics (DTV, DWV, DNWV) and distinguishes itself from sibling tools like disruptions or construction projects.

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 passenger frequency queries but does not explicitly state when to use it vs alternatives. No exclusions or alternative tool names are provided. The context is clear, but the guidance is implicit rather than explicit.

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