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

Annotations already cover read-only, non-destructive, open-world. The description adds important behavioral context: classification comes from source data, no own warning levels are computed, no official warning, and the response must cite data source with license. It also describes what is returned, which is valuable without an 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?

Front-loads the core purpose, then no-data cases, caveats, examples, and citation instruction. Every part serves an agent need; length is justified by the tool's complexity, though it could be slightly tightened.

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 no output schema, the description adequately explains returned content (grouped stations with tendency, no-data stations with name/water body/municipality). It also includes data provenance and warning caveats. An agent has enough to call and interpret the tool correctly.

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% and the single optional parameter is fully documented in the schema. The description only implies regional filtering through an example question ('Niederösterreich') and adds no syntax or semantics beyond the schema, so 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?

States a specific resource (Pegelmessstellen reporting at least erhöhte Wasserführung) and the grouping/conditions, plus no-data stations. It does not name any sibling tool or explicitly contrast with alternatives like pegel_an_gewaesser or lage_am_ort, so it is clear but lacks sibling differentiation.

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?

Provides example questions that imply when to use (nationwide flood situation, state-level, no-data stations). It does not state when not to use or point to sibling tools for local gauge queries, so guidance is clear but not exhaustive.

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