env_hydro_current

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

The description adds substantial behavioral context beyond the readOnlyHint: data source is LINDAS, values update every 10 minutes, and unknown station IDs are explicitly reported with no fallback. It also details the return content (Pegel, Abfluss, Wassertemperatur, 24h min/max) and the timestamp. This goes well beyond annotations, covering potential edge cases and data freshness.

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 with clear sections (intro, return values, station list, use case, important notes, Args, Returns) and is front-loaded with the core action. It is slightly redundant (10-minute update appears twice) and the station list is somewhat niche, but every section contributes to usability. 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?

For a simple read-only tool, the description is complete: it explains what data is returned, how to get station IDs, the update frequency, and error behavior for unknown IDs. Given the output schema exists (though not shown), the brief 'Returns' line suffices. It covers usage, parameters, and edge cases effectively.

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?

Despite the schema description coverage being 0% according to context, the description's 'Args' section explains both parameters: station_id as 'BAFU-Stationsnummer' with examples, and response_format as 'markdown' or 'json'. It also provides a list of known Zürich station IDs, which adds real-world context. However, it could explain the effect of response_format on the output structure in more depth.

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 the tool's function: 'Ruft aktuelle Messwerte einer hydrologischen BAFU-Messstation ab' (retrieves current measurements). It specifies the resource (hydrological BAFU measuring station) and the scope (current values, with units listed). It distinguishes itself from siblings like env_hydro_history by focusing on current data and includes known station IDs.

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 provides specific usage context via the '<use_case>' tag (e.g., flood situation check) and important notes (station ID via env_hydro_stations). It implicitly differentiates from historical data by stating 'aktuelle Messwerte', but it does not explicitly name alternatives like env_hydro_history. This is clear guidance, but lacks an explicit 'when not to use'.

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