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kalcifield

ovf-data-mcp

by kalcifield

nearest_stations

Find the closest public water gauges to any WGS84 latitude/longitude, with network filters for surface water, wells, or precipitation.

Instructions

Find public gauges nearest a WGS84 latitude/longitude.

network: "surface" (rivers and lakes), "wells" (shallow groundwater), "deep-wells" (confined/layer aquifer), or "precipitation".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
metricNo
networkNosurface
latitudeYes
longitudeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It does not state what the response contains (station metadata, distances?), whether results are sorted by distance, how many results max (limit default is in schema but not described), or any rate limits or access constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short, but the network value explanations are oddly embedded in the description rather than the schema. The opening line is good and front-loaded, but the trailing network bullet feels like it belongs in the schema, making the description slightly mis-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a geospatial lookup tool with 5 parameters and 0% schema coverage, the description does not fully compensate. It explains the network parameter but leaves latitude/longitude format, metric, and limit semantics unexplained. Having an output schema helps, but the input semantics are not complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so none of the 5 parameters are described in the schema, but the description does explain the network values (surface, wells, deep-wells, precipitation) which is genuinely useful. However, latitude, longitude, limit, and metric parameters have no explanation in either the schema or description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it finds public gauges nearest given coordinates, which is specific and clear. The network parameter explanation (surface, wells, deep-wells, precipitation) helps differentiate from siblings like get_observations and find_stations, though it doesn't explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage (find nearest stations to a coordinate) but gives no explicit guidance on when to prefer this over siblings like find_stations or inspect_coverage. No when/when-not exclusions are stated.

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

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