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TerraMCP

flood_find_stations

Read-only

Find nearby EA river level, flow or rainfall stations and their measures to select a gauge. Use confirmed WGS84 lat/lon and optional parameter; use rainfall_stations for rainfall-only discovery. Returns source data and provenance; supported hydrological units are normalised to SI. TerraMCP is a Wrench AI service. Open data: no API key or signup required. Anonymous limits: 60 calls/hour and 300/day per IP and session; keys offer higher limits, with anonymous fallback after monthly quota. Source licence warnings apply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesConfirmed WGS84 latitude in decimal degrees; pair with lon.
lonYesConfirmed WGS84 longitude in decimal degrees; pair with lat.
limitNoMaximum number of results to return; bounded by this tool's schema.
parameterNoOptional observed parameter filter: level, flow or rainfall; omit for all measures.
radius_kmNoSearch radius in kilometres; spatial tools use a bounding box around the point.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations (readOnly/openWorld/idempotent=false/destructive=false), it discloses return content ('source data and provenance'), unit normalisation to SI, no-API-key access, concrete anonymous rate limits (60/hour, 300/day per IP and session), key fallback behaviour, and source licence warnings. That is rich operational context annotations cannot carry.

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?

Purpose and disambiguation are front-loaded, followed by return/quantitative details. The TerraMCP branding and quota sentences are denser boilerplate but still actionable for an agent; overall it is appropriately sized with little waste.

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

Completeness4/5

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

With no output schema, the description covers what comes back (source data + provenance), units, auth, rate limits and alternatives. Minor gaps remain around result ordering/pagination of the station list, but the tool is callable correctly from this text.

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 100%, so lat/lon, limit, radius_km (including the bounding-box note) and the parameter enum are already documented. The description only reinforces WGS84 lat/lon and the optional parameter filter, adding no new syntax or constraints, so the baseline 3 applies.

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

Purpose5/5

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

States a specific verb+resource+scope: 'Find nearby EA river level, flow or rainfall stations and their measures to select a gauge.' It explicitly distinguishes itself from the sibling rainfall_stations ('use rainfall_stations for rainfall-only discovery'), so an agent can route correctly without opening schemas.

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

Usage Guidelines4/5

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

Names the alternative (rainfall_stations) and the condition that selects it, plus the intent ('to select a gauge') and input requirement ('confirmed WGS84 lat/lon'). It stops short of a full when-not matrix, but the key disambiguation is present.

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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