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es3154

Turf-MCP

by es3154

measurement_rhumbDistance

Calculate rhumb line distance between two geographic points using GeoJSON coordinates. Returns distance in customizable units for navigation and spatial analysis.

Instructions

计算两点之间的恒向线距离。

该函数使用 Turf.js 库的 rhumbDistance 方法,计算两个 GeoJSON 点特征之间的恒向线距离。

Args: point1: 第一个 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]}'

point2: 第二个 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": [-75.534, 39.123]}'

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'
    - 示例: '{"units": "miles"}'

Returns: str: JSON 字符串格式的距离结果对象 - 类型: 包含 value 和 units 的对象 - 格式: {"value": 距离数值, "units": "距离单位"} - 示例: '{"value": 123.45, "units": "miles"}'

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 >>> point1 = '{"type": "Point", "coordinates": [-75.343, 39.984]}' >>> point2 = '{"type": "Point", "coordinates": [-75.534, 39.123]}' >>> options = '{"units": "miles"}' >>> result = asyncio.run(rhumbDistance(point1, point2, options)) >>> print(result) '123.45'

Notes: - 输入参数 point1、point2 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) - 计算的是两点之间的恒向线距离(等角航线距离) - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
point1Yes
point2Yes
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 an excellent job disclosing behavioral traits. It explains the coordinate system (WGS84 with longitude-first), input format requirements (valid JSON strings), dependencies (Turf.js and Node.js), error conditions (JavaScript execution failures, timeouts, format errors), and output format. The only minor gap is lack of explicit rate limit or performance characteristics, but overall provides comprehensive behavioral context.

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 well-structured with clear sections (Args, Returns, Raises, Example, Notes) and front-loads the core purpose. While comprehensive, some sections like the detailed parameter documentation could be slightly more concise, but every sentence adds value. The example is particularly helpful for understanding usage.

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?

Given the tool's complexity (geospatial calculation with specific format requirements), no annotations, and 0% schema coverage, the description provides complete context. It covers purpose, parameters, return values (though output schema exists, the description clarifies the structure), error conditions, dependencies, coordinate system, and includes a practical example. Nothing essential appears missing for effective tool use.

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 (schema only specifies string types), the description fully compensates by providing extensive parameter documentation. It explains each parameter's purpose, format requirements (GeoJSON Point specification), coordinate order, valid units with enumeration, examples, and default values. The description adds significant value beyond the minimal schema 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 tool's purpose: '计算两点之间的恒向线距离' (calculates the rhumb line distance between two points). It specifies the exact mathematical operation (rhumb distance), distinguishes it from other measurement tools like 'measurement_distance' (great-circle distance) and 'measurement_greatCircle', and mentions the underlying Turf.js library. This provides specific verb+resource differentiation from siblings.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool: for calculating rhumb line distances between GeoJSON points in WGS84 coordinates. It doesn't explicitly state when NOT to use it or name alternatives like 'measurement_distance', but the specificity of '恒向线距离' (rhumb distance) versus other distance calculations implies appropriate usage scenarios. No misleading guidance is present.

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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