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es3154

Turf-MCP

by es3154

helper_lineString

Create GeoJSON LineString features from coordinate arrays to represent paths, boundaries, and linear geographic elements in spatial analysis.

Instructions

创建线特征对象。

此功能根据坐标点数组创建线特征,用于表示路径、边界等线性地理要素。

Args: coordinates: 坐标点数组 - 类型: str (JSON 字符串格式的数组) - 格式: [[lng1, lat1], [lng2, lat2], ...] - 示例: '[[-74, 40], [-78, 42], [-82, 35]]'

properties: 属性对象
    - 类型: str (JSON 字符串) 或 None
    - 格式: 键值对对象
    - 示例: '{"name": "route", "type": "highway"}'

options: 可选参数配置
    - 类型: str (JSON 字符串) 或 None
    - 可选字段:
        - bbox: 边界框数组 [minX, minY, maxX, maxY]
        - id: 特征的标识符
    - 示例: '{"bbox": [-83, 34, -73, 43], "id": "line1"}'

Returns: str: JSON 字符串格式的 GeoJSON LineString Feature - 类型: GeoJSON Feature with LineString geometry - 格式: {"type": "Feature", "geometry": {"type": "LineString", "coordinates": [...]}, "properties": {...}} - 示例: '{"type": "Feature", "geometry": {"type": "LineString", "coordinates": [[-74, 40], [-78, 42], [-82, 35]]}, "properties": {"name": "route"}}'

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 >>> coordinates = '[[-74, 40], [-78, 42], [-82, 35]]' >>> properties = '{"name": "route"}' >>> result = asyncio.run(lineString(coordinates, properties)) >>> print(result) '{"type": "Feature", "geometry": {"type": "LineString", "coordinates": [[-74, 40], [-78, 42], [-82, 35]]}, "properties": {"name": "route"}}'

Notes: - 输入参数 coordinates、properties 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) - 至少需要两个坐标点才能创建有效的线 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coordinatesYes
propertiesNo
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 that the tool creates new features (implying mutation), specifies coordinate order ([longitude, latitude]), minimum point requirements (at least two), JSON format constraints, dependencies (Turf.js, Node.js), and error conditions (exceptions for failures). It doesn't mention rate limits or authentication needs, but covers essential 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. However, it's moderately long due to comprehensive parameter details, which are justified given the 0% schema coverage. Some redundancy exists (e.g., repeating JSON string requirements), but overall it's efficient.

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 (3 parameters, no annotations, 0% schema coverage) and the presence of an output schema, the description is highly complete. It covers purpose, parameters, return values, errors, examples, and technical notes. The output schema is described in detail, making the tool fully understandable for an AI agent.

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%, so the description must fully compensate. It provides detailed semantics for all 3 parameters: coordinates (format, example), properties (format, example), and options (optional fields, examples). Each parameter's type, format, and usage are clearly explained beyond the basic 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 tool's purpose: '创建线特征对象' (create line feature object) with specific details about creating linear geographic features from coordinate arrays. It distinguishes itself from siblings like helper_point or helper_polygon by focusing exclusively on LineString features.

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 examples and notes (e.g., '用于表示路径、边界等线性地理要素'), but doesn't explicitly state when to use this tool versus alternatives like helper_multiLineString or random_randomLineString. It provides technical prerequisites but lacks comparative guidance.

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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