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es3154

Turf-MCP

by es3154

grid_hexGrid

Generate hexagonal grids within bounding boxes for spatial analysis and visualization. Create uniform spatial coverage using specified cell sizes and coordinate systems.

Instructions

在边界框内生成六边形网格。

此功能在指定的边界框内创建六边形网格,用于空间分析和可视化。

Args: bbox: 边界框数组 - 类型: str (JSON 字符串格式的数组) - 格式: [minX, minY, maxX, maxY] - 示例: '[-180, -90, 180, 90]'

cell_size: 网格单元大小
    - 类型: float
    - 描述: 六边形外接圆的半径
    - 示例: 50.0

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'
        - properties: 传递给所有六边形的属性对象
        - mask: 用于裁剪网格的多边形特征
    - 示例: '{"units": "miles", "properties": {"type": "hexagon"}}'

Returns: str: JSON 字符串格式的 GeoJSON FeatureCollection - 类型: GeoJSON FeatureCollection with Polygon features - 格式: {"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [...]}, "properties": {...}}, ...]} - 示例: '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [...]}, "properties": {"type": "hexagon"}}, ...]}'

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 >>> bbox = '[-180, -90, 180, 90]' >>> result = asyncio.run(hexGrid(bbox, 50.0, '{"units": "miles"}')) >>> print(result) '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [...]}, "properties": {...}}, ...]}'

Notes: - 输入参数 bbox 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) - 六边形网格提供均匀的空间覆盖,常用于地理分析 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxYes
cell_sizeYes
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 well by: specifying the return type (GeoJSON FeatureCollection), mentioning dependencies ('依赖于 Turf.js 库和 Node.js 环境' - depends on Turf.js library and Node.js environment), and documenting error conditions ('当 JavaScript 执行失败、超时或输入数据格式错误时抛出异常' - throws exceptions for JavaScript execution failure, timeout, or input data format errors). It also notes coordinate system (WGS84) and input format requirements. However, it doesn't mention performance characteristics like computational cost or memory 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 clear sections (Args, Returns, Raises, Example, Notes), making it easy to navigate. It's appropriately sized for a tool with three parameters and complex behavior. However, some information in the Notes section (e.g., about Turf.js dependency) could be integrated earlier, and the Example includes Python code that may not be directly relevant to all users, slightly reducing efficiency.

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 (spatial grid generation with multiple parameters), no annotations, and an output schema present (though not detailed in the context), the description is highly complete. It covers purpose, parameters, return format, errors, examples, and important notes about dependencies and coordinate systems. The presence of an output schema means the description doesn't need to exhaustively explain return values, and it provides all necessary context for effective 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, the description fully compensates by providing detailed parameter documentation. It explains all three parameters (bbox, cell_size, options) with types, formats, examples, and for options, lists optional fields with valid values for 'units'. This adds substantial meaning beyond the bare schema, making parameter usage clear despite the schema's lack of descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '在边界框内生成六边形网格' (generate a hexagonal grid within a bounding box). It specifies the verb ('生成' - generate) and resource ('六边形网格' - hexagonal grid), and distinguishes it from siblings like grid_pointGrid, grid_squareGrid, and grid_triangleGrid by specifying the hexagonal shape. However, it doesn't explicitly contrast with these siblings in the description text itself.

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 context through the Notes section ('六边形网格提供均匀的空间覆盖,常用于地理分析' - hexagonal grids provide uniform spatial coverage, commonly used in geographic analysis), suggesting it's for spatial analysis and visualization. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like grid_squareGrid or grid_triangleGrid, nor does it mention any prerequisites or exclusions.

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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