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es3154

Turf-MCP

by es3154

helper_geometryCollection

Combine multiple geometry types into a single GeoJSON feature for complex spatial scenarios. This tool merges points, lines, and polygons into a unified geometry collection with custom properties.

Instructions

创建几何图形集合特征。

此功能将多个不同类型的几何图形组合成一个几何集合特征,适用于包含多种几何类型的复杂场景。

Args: geometries: 几何图形数组 - 类型: str (JSON 字符串格式的数组) - 格式: 包含 GeoJSON 几何图形的数组 - 示例: '[{"type": "Point", "coordinates": [100, 0]}, {"type": "LineString", "coordinates": [[101, 0], [102, 1]]}]'

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

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": [99, -1, 103, 2], "id": "geometry_collection"}'

Returns: str: JSON 字符串格式的 GeoJSON Feature with GeometryCollection - 类型: GeoJSON Feature with GeometryCollection geometry - 格式: {"type": "Feature", "geometry": {"type": "GeometryCollection", "geometries": [...]}, "properties": {...}} - 示例: '{"type": "Feature", "geometry": {"type": "GeometryCollection", "geometries": [{"type": "Point", "coordinates": [100, 0]}, ...]}, "properties": {"name": "mixed geometries"}}'

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 >>> geometries = '[{"type": "Point", "coordinates": [100, 0]}, {"type": "LineString", "coordinates": [[101, 0], [102, 1]]}]' >>> properties = '{"name": "mixed geometries"}' >>> result = asyncio.run(geometryCollection(geometries, properties)) >>> print(result) '{"type": "Feature", "geometry": {"type": "GeometryCollection", "geometries": [...]}, "properties": {"name": "mixed geometries"}}'

Notes: - 输入参数 geometries、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) - 几何集合可以包含不同类型的几何图形 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geometriesYes
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 does an excellent job describing key behaviors: it explains the return format in detail, mentions error conditions (JavaScript execution failure, timeout, input format errors), specifies coordinate order requirements, notes JSON string requirements for inputs, and discloses the dependency on Turf.js and Node.js. This provides comprehensive behavioral context beyond basic functionality.

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, it maintains efficiency with no wasted sentences - each section serves a clear purpose. The length is appropriate for a tool with complex parameters and no annotations.

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), the description provides complete context. It thoroughly documents parameters, return values, error conditions, dependencies, and usage notes. The presence of an output schema reduces the need to explain return values, but the description still adds valuable context about the GeoJSON format and examples.

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. Each parameter (geometries, properties, options) gets clear explanations of type, format, examples, and optional fields. The description adds substantial semantic value beyond the bare schema, making parameter usage completely understandable.

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: '创建几何图形集合特征' (create a geometry collection feature). It specifies the verb ('创建' - create) and resource ('几何图形集合特征' - geometry collection feature), and distinguishes it from siblings like helper_feature or helper_featureCollection by focusing specifically on GeometryCollection type features.

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: '适用于包含多种几何类型的复杂场景' (suitable for complex scenarios containing multiple geometry types). It doesn't explicitly mention when not to use it or name specific alternatives, but the context is sufficiently clear for an agent to understand its application domain.

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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