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

With no annotations, the description carries the full behavioral burden and does well: it discloses that only 2026 is curated, that announced 2027 increases are intentionally separated from in-force changes, and that every entry was verified against municipal statutes. It does not cover every edge case, such as exact behavior for non-curated years, but the core limits and semantics are explicit.

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 core purpose, then gives concrete dataset details, the outlook distinction, and a source-verification guarantee. Every sentence adds operational value; no filler or schema repetition.

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 read-style tool with one parameter and no output schema, the description covers what it returns, what the default is, what data is curated, how announced vs in-force changes are kept apart, and data quality. An agent has enough to select and invoke it correctly; the only missing items (exact response shape) are not needed given the described semantics.

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 schema only defines an integer year with range/default, so the description's statement that 'given year' is the filter and that 2026 is the only curated/default year adds essential meaning. It also explains the fixed outlook_2027 output facet. It could still spell out what happens if a year outside 2026 is requested, but it compensates well for the 0% schema coverage.

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 opening phrase identifies a specific verb and resource: list German cities that changed their Hundesteuer rate in a given year. It further positions this as the 'fresh-news angle' for city comparison, which distinguishes it from ranking/state/lookup siblings without needing their schemas.

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 clearly states when the tool is relevant (annual comparison, change-focused, fresh-news) and gives the critical constraint that only 2026 is curated and is the default. It stops short of explicitly naming alternative tools or when not to use it, so it earns a 4 rather than 5.

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