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acxelerator

mcp-tenki

by acxelerator

get_forecast

Retrieve weather forecasts for Japanese prefectures to plan activities and prepare for conditions.

Instructions

Get forecast for a location in Japan

Args:
    prefecture: Name of the prefecture of Japan (in English alphabets, e.g.) "Hokkaido", "Tokyo", "Osaka", etc.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prefectureYes

Implementation Reference

  • The get_forecast tool handler implementation which fetches weather data from the tsukumijima API.
    @mcp.tool()
    async def get_forecast(prefecture: str) -> str:
        """
        Get forecast for a location in Japan
    
        Args:
            prefecture: Name of the prefecture of Japan (in English alphabets, e.g.) "Hokkaido", "Tokyo", "Osaka", etc.)
        """
        location = convert_pref_to_id(prefecture=prefecture)
        if location is None:
            return "Unable to locate"
        url = f"https://weather.tsukumijima.net/api/forecast?city={location.id_}"
        res = await make_nws_request(url=url)
    
        if not res:
            return "Unable to fetch forecast data for this location."
        forecasts = [WeatherForecast(**f) for f in res["forecasts"]]
        return "\n------\n".join([f.format_forecast() for f in forecasts])
    
    
    def main():
        mcp.run(transport="stdio")
    
    
    if __name__ == "__main__":
        main()
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what the tool does but doesn't describe how it behaves—no information about rate limits, authentication needs, error handling, or what the forecast output contains. This leaves significant gaps for an agent to understand the tool's operation.

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 appropriately sized and front-loaded, with the main purpose stated first followed by parameter details. It avoids unnecessary fluff, though the structure could be slightly improved by separating the purpose and parameter sections more clearly.

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?

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and parameter semantics but lacks behavioral details and output information, leaving some gaps for complete understanding.

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 description adds meaningful context for the single parameter 'prefecture' by specifying it must be a name in English alphabets and providing examples like 'Hokkaido', 'Tokyo', 'Osaka'. This compensates well for the 0% schema description coverage, giving the agent practical guidance on valid input values.

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

Purpose4/5

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('forecast for a location in Japan'), making it immediately understandable. However, it doesn't distinguish from siblings since none exist, so it can't achieve the highest score for sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or context. It simply states what the tool does without any usage instructions or exclusions.

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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