Dutch elevation (AHN / NAP height) — $0.010 per call (x402, USDC on Base). Ground height above NAP, surface height and derived object height for a Dutch postcode or coordinate, from the AHN 0.5 m height model via PDOK.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | WGS84 latitude; use with lon instead of postcode. | |
| lon | No | WGS84 longitude; use with lat instead of postcode. | |
| postcode | No | Dutch postcode, e.g. 3511LM (resolved to its centroid). |
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 adds useful context: the $0.010 per call cost, the data source (AHN via PDOK), and the types of heights returned. Since this is a read-only lookup, lack of side-effect warnings is appropriate, though it doesn't mention output format or error handling.
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 a single, front-loaded sentence that conveys the core purpose, data source, and cost without waste. Every part adds value, and it is appropriately sized for the tool's simplicity.
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?
The tool is simple with only three optional parameters and no output schema. The description covers the essential inputs, outputs, source, and cost, which is sufficient for a read-only API. It could mention that lat/lon are WGS84 (though schema does), but overall it is complete enough.
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 each parameter (lat, lon, postcode) with constraints and usage. The description adds little beyond summarizing that postcode or coordinate can be used, which is already implied by the schema descriptions. Baseline 3 is appropriate.
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 states the tool provides Dutch elevation data (AHN/NAP height) and specifies the exact outputs: ground height, surface height, and derived object height. It also names the data source and model (AHN 0.5m via PDOK), making it distinct from sibling tools like nl_address or nl_building.
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 usage for Dutch locations via postcode or coordinate, and is naturally scoped to the Netherlands. However, it does not explicitly mention alternatives or when not to use this tool, relying on the name and purpose to differentiate from siblings.
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.
Each tool targets a distinct data source or function: address lookup, building info, demographics, elevation, school holidays, vehicle lookup, validation, currency conversion, plus meta-tools for catalog and sample responses. There is no meaningful overlap between any pair of tools.
The Dutch-specific tools all follow a consistent 'nl_<subject>' pattern (nl_address, nl_building, etc.), and all names use snake_case. However, three tools (catalog, global_fx, sample) break the prefix pattern, creating a minor inconsistency but remaining clear and readable.
With 11 tools, the server is well-scoped for a Dutch open data API. Each tool covers a distinct data domain, and the count is within the ideal range without feeling excessive or sparse.
The tool surface covers a broad range of Dutch open data lookups, including addresses, buildings, demographics, elevation, holidays, and vehicles, along with validation and a sample mechanism. Minor gaps exist (e.g., no weather or property value data), but the core domain is well represented.