Top-selling car models (and variants) in Denmark for a given month, from bildata.io's top-50 statistics (passenger cars, monthly, 12-month rolling window). Default: latest month, top 10. as_of is the data cutoff — if it is before month-end, the month is PARTIAL, not complete.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Rows per list, default 10, max 50 | |
| month | No | YYYY-MM; default latest available |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It usefully mentions the 12-month rolling window, default behavior, and the partial-month caveat, but it also references 'as_of' as a data cutoff even though no such parameter exists in the input schema, which could confuse an agent.
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 concise and front-loaded with the tool's purpose and data source, followed by defaults and a caveat. The 'as_of' reference is somewhat out of place given the schema, but overall the text avoids redundancy and stays compact.
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 simple list tool with optional parameters, the description covers source, defaults, and data completeness warnings. However, there is no output schema to clarify return shape, and the description does not mention behavior for empty results or the formatting of month/limit, so some contextual gaps remain.
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 100%, so the schema already documents limit and month adequately. The description adds no parameter-level semantics beyond that, and its mention of 'as_of' refers to a cutoff that is not an actual input parameter, creating potential 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 clearly identifies the resource and operation: returning top-selling car models/variants in Denmark for a month, with a specific source and scope. It does not explicitly contrast itself with siblings like get_model_stats or get_market_stats, 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?
The description implies when to use the tool by explaining the data source, monthly scope, and defaults (latest month, top 10). However, it never explicitly states when to prefer this tool over alternatives or when not to use it, leaving usage guidance mostly implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tax tools (calculate vs forecast) are distinguished by current vs future years, and the stats tools are clearly separated into broad market stats, specific model stats, and top-model rankings. Slight overlap exists between get_market_stats and get_top_models, but the descriptions explicitly call out the difference.
All tools follow a snake_case verb_noun pattern and are consistently lowercase. However, naming mixes Danish and English, and the tax term appears both as the full 'registreringsafgift' and the abbreviated 'afgift' in get_afgift_rates.
Six tools is well-scoped for the domain: two tax calculation/projection tools, one rates tool, and three complementary market-statistics tools. Each tool earns its place without redundancy or bloat.
The server covers current and future registration tax calculation, machine-readable rates, and multiple levels of Danish market statistics. Minor gaps exist, such as no historical pre-2026 rates and no general model-search/discovery tool, but core workflows are not blocked.
