get_station_passengers

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

Annotations already declare readOnly/idempotent/non-destructive, so safety needs no restating. The description does add useful context beyond them: it identifies the source dataset, enumerates the returned metrics (average daily, weekday, weekend boardings and alightings), and states the ordering (newest year first) — meaningful because there is no output schema.

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?

Three tight sentences with the payload (passenger counts) front-loaded and no filler. The German parenthetical (Ein- und Aussteigende) is justified as a domain synonym for a Swiss dataset, though it is the one element that could be trimmed.

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?

With no output schema, the description carries the burden of explaining return values and does so by naming the metrics and the row ordering. The one remaining gap is moderate: it doesn't say what happens when a station name matches nothing or how the station text is resolved against the SBB gazetteer.

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%, so all four parameters are already documented with examples and defaults. The description only reinforces the default ordering implied by the year parameter's 'Omit to return the newest years' wording; it adds no new syntax or matching semantics for `station`, `contains`, or `limit`.

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+resource (passenger counts for an SBB station) and names the underlying dataset, plus what figures come back. It does not, however, distinguish itself from data-adjacent siblings such as get_station_punctuality or get_station_accessibility, so an agent must infer the distinction from the resource name alone.

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 only implied: you call it when you want ridership figures for a named station. There is no explicit when-to-use, when-not-to-use, or named alternative (e.g. that this is not a live departures or punctuality tool), so routing among the many station tools depends on the name rather than the text.

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