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search_stations

Find AMeDAS weather stations in Japan by entering station names in Japanese, Kana, or English to access JMA meteorological data.

Instructions

Search AMeDAS stations by name (Japanese, Kana, or English).

Args: name: Station name to search

Returns: List of matching stations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler and registration for 'search_stations'. Calls helper search_stations_by_name(name) and returns formatted dict with count and stations list.
    @mcp.tool()
    async def search_stations(name: str) -> dict:
        """Search AMeDAS stations by name (Japanese, Kana, or English).
    
        Args:
            name: Station name to search
    
        Returns:
            List of matching stations
        """
        stations = search_stations_by_name(name)
        return {"count": len(stations), "stations": stations}
  • Core helper function implementing the station name search logic using substring matching on Japanese, Kana, and English names from loaded station data.
    def search_stations_by_name(name: str) -> list[dict]:
        """Search stations by name (Japanese, Kana, or English)."""
        stations = load_stations()
        results = []
        name_lower = name.lower()
    
        for station in stations.values():
            if (name in station["name"]["ja"] or
                name in station["name"]["kana"] or
                name_lower in station["name"]["en"].lower()):
                results.append(station)
    
        return results
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. It states the tool returns a 'List of matching stations' but doesn't disclose behavioral traits like case sensitivity, partial vs. exact matching, pagination, rate limits, or error handling. For a search tool with zero annotation coverage, this is a significant gap.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by structured 'Args' and 'Returns' sections. Every sentence earns its place with no redundancy or fluff.

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 moderate complexity (search with one parameter) and the presence of an output schema (which covers return values), the description is minimally adequate. However, with no annotations and incomplete behavioral disclosure, it leaves gaps in understanding how the search behaves (e.g., matching rules, result limits).

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?

Schema description coverage is 0%, but the description compensates by explaining the 'name' parameter: 'Station name to search' and specifying language options (Japanese, Kana, or English). This adds meaning beyond the bare schema. However, it doesn't detail format constraints (e.g., minimum length, special characters) or examples.

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: 'Search AMeDAS stations by name' with specific language options (Japanese, Kana, or English). It distinguishes this from siblings like 'list_stations' (which presumably lists all) and 'search_nearby_stations' (which uses location). However, it doesn't explicitly contrast with 'get_station_info' (which might retrieve details for a known station ID).

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. It doesn't mention when to prefer 'search_stations' over 'list_stations' (e.g., for partial matches), 'search_nearby_stations' (e.g., when location is known), or 'get_station_info' (e.g., for a specific station ID). Usage is implied but not articulated.

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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