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MCP Weather Agent

geocode_location

Resolve any city, landmark, or region into candidate coordinates. Provide a location name to receive matching latitude and longitude options.

Instructions

Resolve a place name (city, landmark, region) into candidate coordinates.

Args: location_name: Free-text place name, e.g. "Charlotte, NC" or "Kyoto". max_results: Maximum number of candidate matches to return (1-10).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_resultsNo
location_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
resultsYes
match_countYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It discloses that the tool returns candidate coordinates rather than a single definitive result, which is a meaningful trait. However, it does not mention potential failure modes, ambiguity resolution, or service-side behavior such as rate limits or geographic coverage.

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 is compact and well structured: a one-sentence purpose statement followed by a minimal Args section. Every sentence adds value, and there is no redundant or filler content.

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?

For a simple two-parameter geocoding lookup with an output schema present, the description is nearly complete: it defines the purpose and all parameters. The only notable omissions are explicit usage guidance and edge-case behavior, but these are minor given the tool's simplicity and the existing output schema.

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

Parameters5/5

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

The input schema provides no per-parameter descriptions (0% coverage), so the description is the only source of parameter meaning. It fully compensates by defining location_name as a free-text place name with concrete examples ('Charlotte, NC' or 'Kyoto') and max_results with a clear 1-10 range and its role in limiting candidate matches.

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 opens with a specific verb and resource: 'Resolve a place name ... into candidate coordinates.' This clearly identifies the tool as a geocoder and distinguishes it from the weather-focused sibling tools, get_current_weather and get_forecast.

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?

Usage context is implied rather than stated: an agent can infer this tool is for turning free-text place names into coordinate candidates. However, the description gives no explicit when-to-use instructions, exclusions, or alternatives, even though the sibling tools make the distinction fairly obvious.

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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