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TerraMCP

tide_stations

Read-only

Find EA tidal level stations near a point, using qualifier=Tidal Level. Observed levels, not tide predictions. 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.
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

A4.1/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=true), and the description goes well beyond them: no API key required, anonymous rate limits (60/hour, 300/day), key-based higher limits with anonymous fallback, SI normalisation, and licence warnings. That is rich operational context an agent needs before calling.

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 purpose and the key distinction are front-loaded in the first two sentences, followed by genuinely useful operational facts. The 'TerraMCP is a Wrench AI service' branding sentence earns its place least but is brief; overall the text is tight for the amount of value it carries.

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 steps in to say it returns source data and provenance, and it covers units, auth, rate limits and licensing. It is close to complete for a read-only spatial lookup, though the shape of returned station records could be sketched a little more.

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% and all four parameters (lat, lon, limit, radius_km) are already documented with ranges and defaults in the schema. The description adds no parameter-level syntax or format detail beyond the schema, 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?

The opening clause gives a precise verb+resource+scope: 'Find EA tidal level stations near a point.' The clarification 'Observed levels, not tide predictions' distinguishes it from a prediction-style sibling, so an agent can separate it from tide_readings without opening either schema.

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 'observed levels, not tide predictions' note and the 'qualifier=Tidal Level' hint imply when this tool is appropriate, and 'near a point' implies a spatial lookup. However, it never names tide_readings as the alternative for actual readings or states explicit when-not-to-use conditions, leaving the routing to inference.

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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