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

Annotations already cover read-only/idempotent safety. Beyond that, the description discloses non-obvious behavior: series are downsampled to ≤200 points and history is capped at 90 days with a 7-day default. These operational constraints would not be discoverable from the structured fields.

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 core constraints are front-loaded, but the Swiss-gauge / Neusiedler See aside and the valueCentimeters digression make the sentence dense and harder to scan. Information earns its place, but the packaging is heavy for a single paragraph.

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 4-parameter read tool with full schema coverage and an output schema, the description is nearly complete: it covers depth, downsampling, units, and default type. Only the choice against sibling retrieval tools is left implicit.

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 coverage is 100%, so the baseline is 3, but the description goes further by explaining what 'level' and 'discharge' actually mean, including unit semantics (centimetres above gauge zero, elevation ×100, divide by valueDivisor, m³/s), which the schema only labels.

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?

Opens with a specific resource and scope: 'Time series for a station', which clearly distinguishes it from siblings like get_station, get_forecast and get_flood_situation. It does not explicitly name an alternative though, so it falls short of a 5.

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 supplies useful contextual constraints (history depth 90 days on this tier, default 7 days, downsampling to ≤200 points) but never states when to choose this over get_forecast or search_stations. Usage is implied by the resource rather than directed.

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