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kalcifield

ovf-data-mcp

by kalcifield

find_stations

Find Hungarian water-management gauges by registry ID, name, watercourse, or municipality across surface, wells, deep-wells, and precipitation networks.

Instructions

Find gauges by registry ID, name, watercourse, or municipality.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
metricNo
networkNosurface
watercourseNo
municipalityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It doesn't mention what the output looks like, whether this is a safe read operation, any pagination or result limits, or what 'find' means in terms of matching behavior (exact vs fuzzy). The network enum listing helps somewhat, but the tool's behavior around the query parameter and how filters combine is left unexplained. For a search tool with no annotations, this is a significant gap.

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

Conciseness4/5

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

The description is compact and front-loaded with the key purpose in the first line. The network enumeration is useful and efficiently formatted. It doesn't waste space, though it could have used the structure better by explaining metric and query semantics in the remaining space.

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?

The tool has 6 parameters, no annotations, and no schema description coverage — a moderate complexity tool where the description needs to compensate. The description covers the network field well and hints at search dimensions but leaves metric entirely unexplained and gives no sense of result format. With an output schema present, return values don't need detailing, which helps, but the missing metric semantics and lack of behavioral guidance on filtering combination leave meaningful gaps for an agent to navigate this multi-parameter search tool.

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 all 6 parameters are undocumented in the schema. The description adds meaning to network by enumerating its valid values, and implicitly explains query, watercourse, and municipality search filters. However, the 'metric' and 'limit' parameters are not explained at all in the description, and there's no clarity on what the metric filter does or how it relates to network. This partial coverage earns a middle score.

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 clearly states the tool finds gauges by registry ID, name, watercourse, or municipality. The verb 'find' plus the resource 'gauges' and the search criteria provide good purpose clarity. It doesn't explicitly distinguish from siblings like nearest_stations, but it names the search dimensions clearly enough to establish its distinct role as a general lookup tool.

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 explains what the tool does and lists the search dimensions, but provides no when-to-use versus alternatives guidance. Given siblings include nearest_stations and get_observations, guidance on when to choose this over those alternatives would be valuable. The network field enumeration offers some implicit selection context, but there's no explicit statement about when this tool is the right choice.

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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