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smithery-ai-national-weather-service

find_weather_stations

Find weather observation stations near a location in the United States. Useful for getting station-specific data, finding data sources, or understanding which stations provide weather data for an area. Includes ASOS, AWOS, and other automated weather stations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of stations to return (1-20, default 10). Stations are returned ordered by distance from the specified location.
locationYesUS location as coordinates (lat,lng) in decimal degrees. Example: '40.7128,-74.0060' for New York City. Must be within US boundaries including states, territories (PR, VI, AS, GU, MP), and coastal waters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description must carry full behavioral disclosure. It successfully adds context about what station types are included (ASOS, AWOS, automated stations) and geographic boundaries (US including territories/coastal waters). However, it fails to confirm the read-only/safe nature of the operation or describe what data structure gets returned, which is critical information given the lack of output schema or annotations.

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

Conciseness5/5

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

The description consists of three efficiently structured sentences: the first establishes core purpose, the second provides usage context, and the third specifies station types. Every sentence earns its place without redundancy or verbosity; the information is front-loaded and appropriately sized for the tool's complexity.

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?

Given the absence of an output schema, the description should ideally explain what constitutes a 'station' in the results (IDs, names, distances, etc.), but it omits this. The parameter documentation is complete thanks to the comprehensive schema, and the geographic/station-type coverage is adequate. However, the missing return value documentation creates a gap for an agent trying to predict the output format.

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?

The input schema has 100% description coverage (both location and limit are well-documented in the schema). The description reinforces the location concept ('near a location') but does not add semantic detail beyond what the schema already provides. With high schema coverage, the baseline score of 3 is appropriate—the description meets but does not exceed the schema's explanatory value.

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 description clearly states the tool 'Find[s] weather observation stations near a location in the United States'—specific verb (find), resource (weather observation stations), and geographic scope (US). It effectively distinguishes from siblings like get_current_weather by emphasizing station discovery/metadata rather than weather data retrieval, and specifies station types (ASOS, AWOS) to clarify scope.

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 provides positive usage guidance ('Useful for getting station-specific data...') suggesting when to use it, but lacks explicit negative guidance or sibling differentiation. It does not clarify when NOT to use this (e.g., 'do not use for current weather readings, use get_current_weather instead'), leaving the agent to infer the distinction from the purpose statement alone.

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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