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saurabhherwadkar

MCP Python Server & Client

get_weather

Retrieve current weather conditions or forecast for any city. Specify the city name and optionally forecast days up to 7.

Instructions

Get current weather or forecast for a city.

Args: city: The city name to get weather for forecast_days: Number of days for forecast (0 for current weather only, max 7)

Returns: Weather information as a formatted string

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes
forecast_daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It states the return is a formatted string, but does not disclose potential side effects, required authentication, rate limits, or caching behavior. For a simple read operation this is acceptable but could be improved.

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 extremely concise with no wasted words. It uses a clear structure with Args and Returns sections, front-loading the core purpose. Every sentence adds value.

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?

The tool is simple with two parameters and an existing output schema. The description covers the main functionality and return format. Minor omissions like units or timezone could be added, but the description is largely complete for an agent to use correctly.

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?

Schema description coverage is 0%, but the description adds thorough meaning: 'city' is clearly defined as the city name, and 'forecast_days' includes its purpose, default behavior (0 for current weather), and maximum value (7). This exceeds what the schema provides.

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 explicitly states it gets current weather or forecast for a city, providing a specific verb and resource. It is clearly distinct from sibling tools (calculate, string_operation) which have no weather-related functionality.

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 description clearly indicates when to use the tool (to get weather information) and the parameters control current vs forecast. While it does not explicitly state when not to use it, the context is straightforward and alternatives are unnecessary given the distinct sibling tools.

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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