roc-cwa-mcp

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get_1_week_weather

Retrieve 1-week weather forecast data for any county or city in Taiwan, including time series of temperature, precipitation, and other weather elements.

Instructions

Get 1-week weather forecast data for the specified county/city

Args: location_name: County/city name, must be a valid Taiwan county/city name Valid county/city names: 宜蘭縣, 花蓮縣, 臺東縣, 澎湖縣, 金門縣, 連江縣, 臺北市, 新北市, 桃園市, 臺中市, 臺南市, 高雄市, 基隆市, 新竹縣, 新竹市, 苗栗縣, 彰化縣, 南投縣, 雲林縣, 嘉義縣, 嘉義市, 屏東縣

Returns: list: Cleaned weather data containing various weather elements and their time series

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "location_name": "<location_name>"
    },
    "name": "get_1_week_weather"
  }
}

Input Schema

Name	Required	Description	Default
`location_name`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 31, 2026

TDQS

A3.7/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states basic functionality without disclosing data source, update frequency, accuracy, or any side effects. The absence of any behavioral context beyond 'get' is insufficient.

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 structured with Args and Returns sections, is mostly concise, and front-loaded. The list of valid names is necessary for usability but slightly lengthy; still efficient overall.

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?

The description explains the parameter and return type, but the return structure is vague ('various weather elements and their time series'). Given no output schema, more detail on the return format would improve completeness. Adequate for a simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the tool description exhaustively lists all valid Taiwan county/city names for the 'location_name' parameter and explains its meaning. This fully compensates for the schema gap.

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

Purpose5/5

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

The description clearly states the tool gets a 1-week weather forecast for a specified location. It distinguishes from sibling tools (get_3_days_weather and get_historical_rainfall) by specifying the time range and data type.

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

Usage Guidelines3/5

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

The description implies the tool is for obtaining a 1-week forecast but does not provide explicit guidance on when to use it vs. alternatives or any prerequisites. Usage is inferred from the tool name and sibling context.

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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