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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so the safety profile is covered. The description adds value beyond that: it discloses that remaining request quota per source is included, and instructs the agent to reproduce attribution and license verbatim from the list — a behavioral/output constraint not derivable 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?

Front-loaded with the purpose sentence, then examples, then the verbatim-reproduction instruction; each sentence earns its place. The opening sentence is dense with a long field enumeration, but nothing is redundant padding.

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?

No output schema exists, yet the description enumerates the returned fields (license, license link, prescribed attribution, source link, dataset, DOI, status date, processing notes, per-source quota) thoroughly enough that an agent knows what it will receive. It also supplies formatting guidance for the answer.

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 the documented baseline of 4 applies. There is no parameter semantics to explain, and the description correctly spends no words on inputs.

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?

A precise verb + resource: 'Listet alle Datenquellen dieses Servers' and then enumerates exactly what each entry contains (Lizenz, Quellenvermerk, Link, DOI, Stand, Aufbereitung, Restkontingent). This is unmistakably distinct from every sibling, all of which return weather/water/location data rather than server provenance 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 concrete example questions map directly onto when to call it ('Woher stammen die Daten?', license per dataset, remaining quota). That is strong positive guidance, though the description never explicitly names an alternative or states when NOT to use it.

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