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es3154

Turf-MCP

by es3154

measurement_pointToLineDistance

Calculate the shortest distance from a point to a line using geospatial coordinates. This tool processes GeoJSON data to determine proximity measurements for mapping and spatial analysis applications.

Instructions

计算点到线的最短距离。

该函数使用 Turf.js 库的 pointToLineDistance 方法,计算点到线的最短距离。

Args: point: 点 GeoJSON 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]}'

line: 线 GeoJSON 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 LineString 规范
    - 坐标系: WGS84 (经度在前,纬度在后)
    - 示例: '{"type": "LineString", "coordinates": [[-74, 40], [-78, 42], [-82, 35]]}'

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'
        - method: 计算方法 (默认: 'geodesic')
            - 有效值: 'geodesic', 'planar'
    - 示例: '{"units": "miles", "method": "geodesic"}'

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": 12.34, "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 >>> point = '{"type": "Point", "coordinates": [-75.343, 39.984]}' >>> line = '{"type": "LineString", "coordinates": [[-74, 40], [-78, 42], [-82, 35]]}' >>> options = '{"units": "miles", "method": "geodesic"}' >>> result = asyncio.run(pointToLineDistance(point, line, options)) >>> print(result) '12.34'

Notes: - 输入参数 point、line 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) - 计算的是点到线的最短球面距离 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pointYes
lineYes
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 underlying library (Turf.js), computational method (shortest spherical distance), dependencies (Node.js environment), error conditions (JavaScript execution failure, timeout, input format errors), and return format. It doesn't mention performance characteristics or rate limits, but covers key 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?

The description is well-structured with clear sections (Args, Returns, Raises, Example, Notes) and front-loaded purpose. It's appropriately sized for a 3-parameter tool with complex requirements, though some redundancy exists (e.g., repeating coordinate order in multiple places).

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 input/output formats), no annotations, and an output schema present, the description is highly complete: it covers purpose, parameters, return values, errors, examples, and implementation details. The output schema handles return structure, so the description appropriately focuses on usage context.

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 semantics: it explains each parameter's type, format, coordinate system, examples, and for options, lists valid values for units and method with defaults. This adds substantial value beyond the bare schema.

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 verb '计算' (calculate) and resource '点到线的最短距离' (shortest distance from point to line). It distinguishes from siblings by specifying it's for point-to-line distance calculation, unlike other measurement tools like measurement_distance (general distance) or measurement_pointOnFeature (finds point on feature).

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 through the example and notes (e.g., coordinates must be WGS84, JSON strings required), but doesn't explicitly state when to use this tool versus alternatives like measurement_distance or misc_nearest_point_on_line. It provides context about input formats but lacks explicit guidance on tool selection.

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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