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es3154

Turf-MCP

by es3154

grid_squareGrid

Generate square grids within a bounding box for spatial analysis and area partitioning. Specify cell size and units to create GeoJSON FeatureCollections for geographic data processing.

Instructions

在边界框内生成正方形网格。

此功能在指定的边界框内创建正方形网格,用于空间分析和区域划分。

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: 正方形的边长
    - 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: 传递给所有正方形的属性对象
        - mask: 用于裁剪网格的多边形特征
    - 示例: '{"units": "miles", "properties": {"type": "square"}}'

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": "square"}}, ...]}'

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(squareGrid(bbox, 50.0, '{"units": "miles"}')) >>> print(result) '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [...]}, "properties": {"type": "square"}}, ...]}'

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) - 正方形网格提供规则的矩形区域,常用于统计和聚合 - 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 this well by explaining the return format (GeoJSON FeatureCollection), error conditions (JavaScript execution failure, timeout, input format errors), dependencies (Turf.js and Node.js environment), and coordinate system details (WGS84, longitude-latitude order). It also notes that the grid provides regular rectangular areas for statistics and aggregation.

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 with the core purpose. While comprehensive, it's appropriately sized for a tool with three parameters and complex output. Some sentences in the Notes section could be more concise, 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 (spatial grid generation with three parameters), no annotations, and an output schema present, the description is complete. It covers purpose, parameters, return values, errors, examples, and important notes about JSON format, coordinate system, and dependencies. The output schema is described in detail, making the description fully adequate.

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', it lists all optional fields with their valid values and defaults. This adds substantial meaning beyond what the bare schema provides.

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: '在边界框内生成正方形网格' (generate a square grid within a bounding box). It specifies the verb ('生成' - generate) and resource ('正方形网格' - square grid), and distinguishes from siblings like 'grid_hexGrid' and 'grid_triangleGrid' by explicitly mentioning '正方形' (square).

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: for spatial analysis and regional division ('用于空间分析和区域划分'). It doesn't explicitly mention when not to use it or name alternatives, but the context is sufficient for an agent to understand its application in grid-based spatial operations.

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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