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es3154

Turf-MCP

by es3154

measurement_centerOfMass

Calculate the center of mass for GeoJSON shapes to identify geographic balance points for spatial analysis and mapping applications.

Instructions

计算 GeoJSON 对象的质心。

该函数使用 Turf.js 库的 centerOfMass 方法,计算给定 GeoJSON 对象的质心。

Args: geojson: GeoJSON 对象 - 类型: str (JSON 字符串格式的 GeoJSON) - 格式: 任何有效的 GeoJSON 对象 - 坐标系: WGS84 (经度在前,纬度在后) - 示例: '{"type": "Polygon", "coordinates": [[[-81, 41], [-88, 36], [-84, 31], [-80, 33], [-77, 39], [-81, 41]]]}'

options: 可选参数配置
    - 类型: str (JSON 字符串) 或 None
    - 可选字段:
        - properties: 传递给质心的属性对象
    - 示例: '{"properties": {"name": "center of mass"}}'

Returns: str: JSON 字符串格式的 GeoJSON Point 特征 - 类型: GeoJSON Feature with Point geometry - 格式: {"type": "Feature", "geometry": {"type": "Point", "coordinates": [lng, lat]}} - 示例: '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-82.5, 35.5]}}'

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 >>> polygon = '{"type": "Polygon", "coordinates": [[[-81, 41], [-88, 36], [-84, 31], [-80, 33], [-77, 39], [-81, 41]]]}' >>> options = '{"properties": {"name": "center of mass"}}' >>> result = asyncio.run(centerOfMass(polygon, options)) >>> print(result) '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-82.5, 35.5]}}'

Notes: - 输入参数 geojson 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) - 质心是基于几何形状的质量分布计算的中心点 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geojsonYes
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. It effectively discloses key behavioral traits: the tool uses Turf.js library and Node.js environment, requires valid JSON strings as input, uses WGS84 coordinate system with longitude-first ordering, and raises exceptions for execution failures, timeouts, or malformed data. It also explains what the tool calculates ('质心是基于几何形状的质量分布计算的中心点').

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 statement. While comprehensive, some sections like the detailed example could be slightly more concise, but overall the information earns its place given the technical nature of the tool.

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 (geospatial calculation), lack of annotations, and 0% schema coverage, the description provides excellent completeness. It covers purpose, parameters, return format, error conditions, examples, and technical dependencies. The existence of an output schema reduces the need to explain return values in detail, which the description handles appropriately.

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 rich parameter semantics. It clearly explains both parameters: 'geojson' as a JSON string with format requirements, coordinate system, and examples; 'options' as an optional JSON string with specific fields and examples. The description adds significant value beyond the bare 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 specific action ('计算质心' - calculate center of mass) on a specific resource ('GeoJSON 对象' - GeoJSON object). It explicitly mentions using the Turf.js library's centerOfMass method, which distinguishes it from other measurement tools like 'measurement_center' or 'measurement_centroid' in the sibling list.

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 the function's purpose (calculating center of mass for GeoJSON objects) but doesn't explicitly state when to use this tool versus alternatives like 'measurement_center' or 'measurement_centroid'. It provides technical context about coordinate systems and dependencies, but lacks explicit guidance on tool selection.

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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