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

With no annotations provided, the description carries the full burden and meaningfully discloses behavior: the data source, weekly DMR freshness, and the critical caveat that a month whose as_of is before month-end is PARTIAL. It does not explicitly confirm read-only side effects or rate limits, but for a statistics lookup the main behavioral risk is clearly flagged.

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?

Three compact sentences with no filler; the core resource is front-loaded and the critical partial-data caveat is placed at the end where it reinforces the definition. Every clause adds information and the structure is easy to scan.

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, enum-driven tool with no output schema, the description covers data source, dimensions, kind semantics, and partial-data interpretation. The only real gap is that the shape of the returned data is left implicit, but the dimension names largely convey what will be returned, leaving the agent enough to invoke it 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 description coverage is only 50%, and the description compensates by explaining the meaning of kind=all vs kind=Personbil and clarifying several dimensions such as brands (top 20), imports (top imported makes), and monthly_totals (incl. leasing series). The mention of as_of adds useful output interpretation, though as_of is not a request parameter in the schema, creating minor ambiguity.

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 immediately identifies the resource: Danish new-vehicle registration statistics from bildata.io, and lists the six available dimensions, which distinguishes it from siblings like get_model_stats and get_top_models. It stops short of a full 5 because the statement is a noun phrase rather than an explicit verb like 'retrieves' or 'lists'.

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 explains parameter semantics such as kind=all vs kind=Personbil and the as_of partial-data caveat, but gives no explicit guidance on when to prefer this tool over get_model_stats, get_top_models, or the afgift tools. Tool-selection context is implied by the dimension list and sibling names, not stated.

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