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jayaraj-kannan

Weather MCP Server

get_weather

Get current weather for any city by name, returning temperature, humidity, and conditions to help plan your day.

Instructions

Get current weather for a city.

Args: city: City name (e.g. London, Chennai, New York)

Returns: Weather details including temperature, humidity, and conditions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It does disclose that the result includes temperature, humidity, and conditions, but it does not mention units, city-resolution behavior, possible errors, or whether the operation is strictly read-only. This is acceptable but minimal.

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: one clear purpose sentence, an Args block, and a Returns block. Every sentence earns its place and the main purpose is front-loaded.

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 one-parameter tool with an output schema available, this description is sufficient for an agent to select and invoke the tool correctly. It could add minor caveats like units or error behavior, but those are not necessary for basic correct use.

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

Parameters4/5

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

The JSON schema provides only the parameter title 'City' with 0% description coverage, so the description's Args section adds crucial meaning by explaining that it expects a city name and giving concrete examples. It could add disambiguation guidance for duplicate city names, but for a single required parameter it compensates well.

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 sentence 'Get current weather for a city' uses a specific verb and resource and immediately communicates the tool's purpose. It also clearly identifies the input (a city) and expected output, making the tool easy to distinguish even without siblings.

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?

The phrase 'current weather' makes the intended use case clear: this tool is for real-time conditions, not forecasts or historical data. There are no sibling tools and no exclusions to document, so the usage context is sufficiently clear.

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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