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yukit7s
by yukit7s

get_all_tokyo_locations

Retrieve WBGT (heat index) forecast data for all observation points across Tokyo to support heat stroke prevention planning and safety measures.

Instructions

東京都内の全WBGT観測地点の予測値を一括取得します

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler function that invokes the WBGT service to get all Tokyo locations data and formats it as MCP response content with JSON string.
    private async handleGetAllTokyoLocations(): Promise<any> {
      const data = await this.wbgtService.getAllTokyoLocations();
      
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(data, null, 2),
          },
        ],
      };
    }
  • Tool schema definition in the ListTools response, specifying name, description, and empty input schema (no parameters).
    {
      name: "get_all_tokyo_locations",
      description: "東京都内の全WBGT観測地点の予測値を一括取得します",
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
  • src/index.ts:94-95 (registration)
    Registration of the tool handler in the CallToolRequest switch statement, dispatching calls to handleGetAllTokyoLocations.
    case "get_all_tokyo_locations":
      return await this.handleGetAllTokyoLocations();
  • Core helper function in WBGTService that fetches the all-Tokyo WBGT forecast CSV from API and parses it into WBGTData array.
    async getAllTokyoLocations(): Promise<WBGTData[]> {
      const url = `${WBGT_API_BASE_URLS.forecast}yohou_tokyo.csv`;
      
      try {
        const response = await fetch(url);
        if (!response.ok) {
          throw new Error(`HTTP error! status: ${response.status}`);
        }
        
        const csvData = await response.text();
        return parseAllTokyoCSV(csvData);
      } catch (error) {
        throw new Error(`Failed to fetch all Tokyo WBGT data: ${error instanceof Error ? error.message : String(error)}`);
      }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves predicted values in bulk, implying a read-only operation, but doesn't cover aspects like rate limits, authentication needs, data freshness, or error handling. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence in Japanese that front-loads the key information: it specifies the resource (all Tokyo WBGT observation points), the data type (predicted values), and the action (bulk retrieval). There is no wasted text, making it highly concise and well-structured.

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 complexity (simple retrieval with no parameters) and lack of annotations or output schema, the description is minimally adequate. It covers the basic purpose but misses behavioral details like response format or limitations. Without an output schema, it should ideally hint at return values, but the simplicity of the tool keeps it from being severely incomplete.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds no parameter information, which is appropriate here. Baseline is 4 for tools with zero parameters, as there's nothing to compensate for.

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: '一括取得します' (retrieves in bulk) for '東京都内の全WBGT観測地点の予測値' (predicted values for all WBGT observation points in Tokyo). It specifies both the action (retrieve) and resource (WBGT observation point predictions), though it doesn't explicitly differentiate from sibling tools like 'get_tokyo_realtime_data' or 'get_tokyo_wbgt_forecast' beyond the 'all locations' scope.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'all locations' and 'predictions,' but it doesn't specify contexts, prerequisites, or exclusions relative to sibling tools like 'get_tokyo_realtime_data' (which might fetch real-time data) or 'get_tokyo_wbgt_forecast' (which could be for forecasts).

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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