Get the official MeteoLux forecast for a place in Luxembourg: current conditions, 24 hours, 5 days, UV index, sunrise and sunset.
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": "get_weather_forecast"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| language | No | en | |
| latitude | No | ||
| longitude | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the data source and included fields, but it does not disclose behaviors such as coordinate semantics, defaults for latitude/longitude, update frequency, units, limitations, or output format. This is a meaningful gap for a data-returning tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-structured sentence that front-loads the action and scope, then efficiently enumerates the forecast contents. Every part earns its place and there is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema or annotations, the description should explain how to specify a place, whether defaults apply, and what the response looks like. It lists the returned data categories but omits essential invocation context, leaving an agent under-informed for a tool with three undocumented parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate. It does not explain how latitude and longitude map to 'a place', what units are expected, or what the language parameter controls. The only hint is 'a place in Luxembourg,' which is too vague to support accurate invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Get the official MeteoLux forecast for a place in Luxembourg.' It also lists the exact contents (current conditions, 24 hours, 5 days, UV index, sunrise and sunset), which clearly differentiates it from sibling tools like get_weather_observations and get_weather_alerts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The word 'forecast' implies this tool is for forecast data rather than observations or alerts, and 'for a place in Luxembourg' gives context. However, the description never explicitly names alternatives or states when not to use this tool, leaving selection partially to inference.
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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