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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds genuine behavioral context beyond that: it discloses the remaining request quota per source and that attributions are reproduced verbatim as the provider requires, which the annotations do not convey.

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 front-loaded with the return contents and then adds example questions that earn their place by illustrating usage. The long field enumeration is slightly dense but every item is informative rather than filler.

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?

With zero parameters and no output schema, the description carries the full burden of describing the return payload, and it does so thoroughly (license, license link, mandated attribution, link, dataset, DOI, status, processing notes, quota). Nothing an agent needs to invoke and interpret it is missing.

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?

The tool takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to clarify regarding inputs, and it correctly does not attempt to.

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 verb ('Listet') and resource ('alle Datenquellen dieses Servers') and enumerates the exact fields returned (Lizenz, Link, Quellenvermerk, DOI, Stand, Kontingent). This clearly distinguishes it from the sibling tools, which are all data-value queries (Pegel, Wetter, Niederschlag), not metadata.

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?

Three example questions ('Woher stammen die Daten?', 'Unter welcher Lizenz...?', 'Wie viele Wetterabfragen...?') make the usage context concrete. It stops short of naming explicit alternatives or when-not-to-use conditions, so it 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.