Retrieve all 16 MeteoSwiss automatic pollen monitoring stations in Switzerland, including station codes, names, cantons, altitude, and coordinates, with optional filtering by canton.
List all 16 MeteoSwiss automatic pollen monitoring stations in Switzerland. Returns station codes, names, cantons, altitude, and coordinates. Source: MeteoSwiss.
| Name | Required | Description | Default |
|---|---|---|---|
| canton | No | Filter by canton abbreviation (e.g. ZH, BE, GE, TI) |
Changes observed during successful MCP inspections.
v0.8.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It usefully enumerates the returned fields (codes, names, cantons, altitude, coordinates), which is real value since no output schema exists, but it says nothing about response size limits, pagination, or completeness guarantees beyond the static count of 16.
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?
Front-loaded with scope, then return fields, then source. Two clauses are slightly redundant since 'MeteoSwiss' and the return-field list are inferred from the first sentence, but overall it is tight with no wasted prose.
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 one-optional-parameter, no-output-schema inventory tool, the description covers scope, return shape, and data source, which is essentially everything needed to call it. The only missing element is how this list relates to the pollen measurement tools.
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% and the single canton parameter is fully documented in the schema, including format examples. The description adds no filtering detail (e.g. case sensitivity, behavior when no stations match), so the baseline 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?
A specific verb ('List') plus a precisely scoped resource ('all 16 MeteoSwiss automatic pollen monitoring stations in Switzerland'). The resource is unambiguous against siblings such as list_weather_stations, list_air_quality_stations and list_snow_stations, so an agent can select it without opening the schema.
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 listing nature and the fixed scope imply when it applies, but there is no explicit guidance on when to use it versus get_pollen_current or get_pollen_daily (station inventory vs measurements). No exclusions or prerequisites are stated, leaving the agent to infer the pipeline role.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.