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es3154

Turf-MCP

by es3154

helper_multiPolygon

Create GeoJSON MultiPolygon features from coordinate arrays to represent complex geographic areas with multiple polygons for spatial analysis.

Instructions

创建多多边形特征对象。

此功能根据多组多边形坐标数组创建多多边形特征,用于表示包含多个多边形的复杂区域要素。

Args: coordinates: 多多边形坐标数组 - 类型: str (JSON 字符串格式的数组) - 格式: [[[[lng1, lat1], [lng2, lat2], ...]], [[[lng3, lat3], [lng4, lat4], ...]]] - 示例: '[[[[[0, 0], [0, 10], [10, 10], [10, 0], [0, 0]]]], [[[[10, 0], [10, 5], [15, 5], [15, 0], [10, 0]]]]]'

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

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": [-1, -1, 16, 11], "id": "multi_polygon1"}'

Returns: str: JSON 字符串格式的 GeoJSON MultiPolygon Feature - 类型: GeoJSON Feature with MultiPolygon geometry - 格式: {"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [...]}, "properties": {...}} - 示例: '{"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [[[[0, 0], [0, 10], [10, 10], [10, 0], [0, 0]]], [[[10, 0], [10, 5], [15, 5], [15, 0], [10, 0]]]]}, "properties": {"name": "multi area"}}'

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 = '[[[[[0, 0], [0, 10], [10, 10], [10, 0], [0, 0]]]], [[[[10, 0], [10, 5], [15, 5], [15, 0], [10, 0]]]]]' >>> properties = '{"name": "multi area"}' >>> result = asyncio.run(multiPolygon(coordinates, properties)) >>> print(result) '{"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [...]}, "properties": {"name": "multi area"}}'

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) - 多多边形特征包含多个独立的多边形 - 每个多边形必须形成闭合环 - 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 the full burden of behavioral disclosure. It effectively describes key traits: it creates a GeoJSON MultiPolygon Feature, specifies input requirements (valid JSON strings, coordinate order [lng, lat] in WGS84), notes dependencies (Turf.js and Node.js), and mentions error conditions (raises Exception for execution failure, timeout, or format errors). However, it lacks details on performance aspects like rate limits or resource usage.

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 sections (Args, Returns, Raises, Example, Notes), making it easy to navigate. It is appropriately sized, with each sentence adding value (e.g., explaining coordinate order, dependencies). However, some redundancy exists (e.g., repeating JSON string details), slightly reducing efficiency, but overall it remains front-loaded and informative.

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 complexity (3 parameters, no annotations, 0% schema coverage, but has output schema), the description is complete. It explains inputs, outputs (GeoJSON format with example), error handling, dependencies, and usage notes. The output schema is present, so the description correctly focuses on input semantics and behavioral context without needing to detail return values, covering all necessary aspects 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?

The schema description coverage is 0%, so the description must fully compensate. It adds comprehensive meaning beyond the schema by detailing each parameter: coordinates (type, format, example), properties (type, format, example), and options (type, optional fields, example). This includes JSON string formats, coordinate structures, and usage notes, providing clear semantics that the schema alone does not.

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: '创建多多边形特征对象' (creates a multi-polygon feature object), specifying the verb ('创建') and resource ('多多边形特征对象'). It distinguishes from siblings by focusing on multi-polygon creation, unlike other helper tools (e.g., helper_polygon for single polygons), making it specific and differentiated.

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 context (e.g., '用于表示包含多个多边形的复杂区域要素' - for representing complex area features with multiple polygons), but does not explicitly state when to use this tool versus alternatives like helper_polygon or other geometry tools. No exclusions or prerequisites are mentioned, leaving usage guidance implicit rather than explicit.

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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