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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description still adds genuinely useful context: top-10 operators are only listed when a legal form is recognizable with the remainder bundled into a collective item, the time window is the last 5 years, and ambiguous/unknown names return suggestions rather than failing.

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 content is front-loaded and each enumerated field earns its place, but the entire description is repeated verbatim in German and English, roughly doubling the length without adding information for any single reader. The dense run-on enumeration also makes it harder to scan than a short bulleted figure list would be.

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 two-parameter read-only aggregation tool with no output schema, the description does the heavy lifting well by naming the returned figures and the fallback behavior for unresolved names. Only minor gaps remain, such as units for kW classes or whether results are single-region only.

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 both parameters (name, ebene enum) are fully documented in the schema, so the baseline of 3 applies. The description adds only the implication that name is the lookup key subject to ambiguity resolution, which is marginal beyond the schema.

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 states a specific resource (a region) and enumerates exactly which key figures are computed: stations, charge points, total kW, fast-charging share, kW classes, top-10 operators, commissioning per year. That is far more specific than the title 'Regionalstatistik'. It does not explicitly contrast itself with siblings like search_charging_stations, so it stops 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?

Usage is only implied: an agent can infer this is the aggregation tool for a named region versus a raw station search, but the description never says 'use this when you want aggregate figures instead of individual stations' nor names an alternative. The note about ambiguous names returning suggestions is behavioral, not a when-to-use rule.

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