SRF Meteo – 24-Stunden-Prognose

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, establishing a safe read-only operation. The description adds valuable behavioral constraints: it works only for Swiss coordinates (latitude/longitude ranges) and returns at most 24 hourly data points. It also notes that geolocation_id can be omitted and will be resolved from coordinates. These details go beyond the annotations and help the agent set expectations.

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 compact and front-loaded: the core purpose is in the first sentence, followed by clearly structured XML-style tags for use cases, important notes, and an example. There is no redundancy or filler; every section adds distinct value. This is an exemplary structure for a tool description.

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 a rich input schema and an output schema, the description covers the essential context: geographic constraints, data point limit, and a usage example. It does not mention units, timezone, or the exact response format, but those are likely defined in the output schema. The description is sufficiently complete for an agent to call the tool correctly and interpret the results, though a note about timezone could have been included.

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 0%, meaning the description does not repeat parameter explanations. However, the input schema itself provides detailed descriptions for latitude, longitude, and geolocation_id, so the agent can rely on the schema. The description adds a concrete example (latitude=47.3769, longitude=8.5417) which illustrates usage but does not explain parameter semantics beyond that. Since the schema already covers the parameters thoroughly, a score of 3 is appropriate, though the description could have added a note about the optional geolocation_id resolution.

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 states the tool's purpose clearly: it delivers the hourly weather forecast for the next 24 hours from SRF Meteo. The verb 'Liefert' and the specific resource 'Wettervorhersage der nächsten 24 Stunden' are explicit. It distinguishes from siblings like srgssr_weather_current (current weather) and srgssr_weather_forecast_7day (7-day forecast) by the time frame, and from srgssr_weather_search_location by purpose.

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 use_case tag provides practical contexts (Tagesplanung, Veranstaltungsorganisation, kurzfristige Wetterwarnungen) that indicate when this tool is appropriate. It does not explicitly compare with alternatives or state when not to use it, but the use cases and the time-frame specificity offer clear guidance for selection. The important_notes also constrain valid input, which indirectly guides usage.

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