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es3154

Turf-MCP

by es3154

measurement_rhumbDestination

Calculate a destination point from a starting location by moving a specified distance along a constant bearing (rhumb line). Useful for navigation and geospatial applications requiring precise location projections.

Instructions

沿恒向线计算目标点。

该函数使用 Turf.js 库的 rhumbDestination 方法,从起点沿着指定恒向线方位角移动指定距离来计算目标点。

Args: origin: 起点 GeoJSON Point 特征或几何图形 - 类型: str (JSON 字符串格式的 GeoJSON) - 格式: 必须符合 GeoJSON Point 规范 - 坐标系: WGS84 (经度在前,纬度在后) - 示例: '{"type": "Point", "coordinates": [-75.343, 39.984]}'

distance: 移动距离
    - 类型: float
    - 描述: 从起点开始移动的距离值
    - 示例: 50.0

bearing: 恒向线方位角
    - 类型: float
    - 描述: 从北方向顺时针测量的恒向线角度
    - 范围: -180 到 180 度
    - 示例: 90.0

options: 可选参数配置
    - 类型: str (JSON 字符串) 或 None
    - 可选字段:
        - units: 距离单位 (默认: 'kilometers')
            - 有效值: 'miles', 'nauticalmiles', 'kilometers', 'meters', 'yards', 'feet', 'inches'
        - properties: 传递给目标点的属性对���
    - 示例: '{"units": "miles", "properties": {"name": "rhumb destination"}}'

Returns: str: JSON 字符串格式的 GeoJSON Point 特征 - 类型: GeoJSON Feature with Point geometry - 格式: {"type": "Feature", "geometry": {"type": "Point", "coordinates": [lng, lat]}} - 示例: '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-74.5, 39.5]}}'

Raises: Exception: 当 JavaScript 执行失败、超时或输入数据格式错误时抛出异常

Example: >>> import asyncio >>> origin = '{"type": "Point", "coordinates": [-75.343, 39.984]}' >>> options = '{"units": "miles", "properties": {"name": "rhumb destination"}}' >>> result = asyncio.run(rhumbDestination(origin, 50.0, 90.0, options)) >>> print(result) '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-74.5, 39.5]}}'

Notes: - 输入参数 origin 和 options 必须是有效的 JSON 字符串 - 坐标顺序为 [经度, 纬度] (WGS84 坐标系) - 恒向线方位角是沿着恒向线(等角航线)的方位角 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originYes
distanceYes
bearingYes
optionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden and does well: it discloses the Turf.js/Node.js dependency, coordinate system (WGS84), input format requirements (valid JSON strings), error conditions (JavaScript execution failures, timeouts, format errors), and return format. It doesn't mention performance characteristics or rate limits, but covers most behavioral aspects.

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?

Well-structured with clear sections (Args, Returns, Raises, Example, Notes) and front-loaded purpose statement. Some technical details in the Notes section could be more concise, but overall information density is high with minimal waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter tool with no annotations and 0% schema coverage, the description provides complete context: clear purpose, detailed parameter semantics, return format (though output schema exists), error conditions, examples, and important technical notes about dependencies and coordinate systems. Nothing essential appears missing.

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?

With 0% schema description coverage, the description fully compensates by providing detailed parameter documentation: origin (format, coordinate system, examples), distance (type, description), bearing (type, description, range), and options (structure, valid values, defaults). Each parameter gets clear semantic meaning beyond just type information.

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 specific action ('计算目标点' - calculate destination point) using a specific method ('沿恒向线' - along rhumb line) with the Turf.js library. It distinguishes itself from sibling tools like 'measurement_destination' (which likely uses great circle) by specifying the rhumb line method.

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 usage context through technical details (rhumb line vs great circle, Turf.js dependency) but doesn't explicitly state when to choose this tool over alternatives like 'measurement_destination'. It mentions the method but not comparative use cases.

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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