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schlpbch

Aareguru MCP Server

by schlpbch

get_forecasts

Fetch current temperature, 2-hour forecast, and trend for multiple Swiss cities simultaneously.

Instructions

Get forecasts for multiple cities.

Fetches all forecasts concurrently.

Args: cities: List of city identifiers (e.g., ['Bern', 'Thun'])

Returns: Dictionary mapping city names to forecast data: - forecasts (dict): Map of city to forecast data with current temp, 2-hour forecast, and trend

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
citiesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so description carries full burden. Discloses concurrent fetching and return structure. Lacks error handling or rate limits, but adequate for this simple tool.

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?

Well-structured with Args/Returns sections, but includes some redundancy. Concise enough while being informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (1 parameter, clear output schema), description covers purpose, parameters, and return values completely. Output schema rich, so return description is adequate.

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?

Input schema has 0% description coverage, but description adds examples (e.g., ['Bern', 'Thun']) and explains city identifiers, providing context beyond schema.

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?

Description clearly states 'Get forecasts for multiple cities' and specifies concurrency, distinguishing it from sibling single-city tools like get_current_conditions.

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?

No explicit guidance on when to use versus alternatives; only states what the tool does. Implicitly, it's for multiple cities, but no exclusions or comparisons.

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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