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profullstack-mcp

Get Weather

weather
Read-onlyIdempotent

Weather data and imagery module using the National Weather Service API

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "weather"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful provenance by naming the National Weather Service API, implying an official and geographically limited data source, but it says nothing about rate limits, response shape, or how data versus imagery is selected.

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?

The description is a single short sentence fragment, front-loaded with the resource and backend API. It is concise and readable, though slightly under-specified rather than wordy.

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?

For a simple, no-parameter, read-only tool whose annotations cover safety, the description is close to adequate but still missing output expectations and geographic scope. An agent cannot tell what specific weather data or imagery it will receive or whether location is somehow implicit.

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?

With zero parameters, the baseline is 4, and the schema requires no parameter documentation. However, the description does not clarify that no parameters are accepted or explain how location is determined, which is a meaningful gap for a weather tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource ('weather data and imagery') and the backend API, but uses the vague noun 'module' instead of a specific verb and does not state what operation is performed (current conditions, forecast, alerts, imagery retrieval). The name and title imply retrieval, but the description alone is only broadly indicative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives, nor any when-not-to-use condition. It also omits any instruction about location handling or coverage, despite the National Weather Service API being primarily US-focused.

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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