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es3154

Turf-MCP

by es3154

measurement_centroid

Calculate the geometric center point of any GeoJSON object by averaging all vertex coordinates. Returns a GeoJSON Point feature with WGS84 coordinates.

Instructions

计算几何对象的中心点。

此功能计算给定几何对象的几何中心,通过平均所有顶点坐标确定中心位置。

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: 传递给几何中心的属性对象
    - 示例: '{"properties": {"name": "centroid"}}'

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": "centroid"}}' >>> result = asyncio.run(centroid(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) - 几何中心是通过平均所有顶点坐标计算的中心点 - 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 and delivers substantial behavioral information. It discloses: coordinate system requirements (WGS84 with longitude-first), input format constraints (valid JSON strings), dependency on Turf.js and Node.js, error conditions (JavaScript execution failures, timeouts, malformed data), and return format details. The only gap is lack of performance/rate limit information.

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 could be more concise - the example includes unnecessary Python import statements and the Notes section repeats coordinate information already stated in Args. Overall, most content earns its place.

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 (geometric calculation with specific coordinate system requirements), no annotations, and 0% schema coverage, the description provides excellent completeness. It covers purpose, parameters, return format, error conditions, examples, dependencies, and technical constraints. The presence of an output schema reduces need for return value explanation, which the description appropriately supplements rather than duplicates.

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 comprehensive parameter documentation. It details both parameters: 'geojson' (type, format, coordinate system, examples) and 'options' (type, optional fields, examples). The description adds significant value beyond the bare schema, explaining JSON string requirements, coordinate ordering, and property passing mechanisms.

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: '计算几何对象的中心点' (calculates the centroid of a geometric object). It specifies the exact method ('通过平均所有顶点坐标确定中心位置' - determines center position by averaging all vertex coordinates) and distinguishes it from sibling tools like 'measurement_center' and 'measurement_centerOfMass' by focusing specifically on geometric centroid calculation.

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 parameter details and examples, but doesn't explicitly state when to use this tool versus alternatives like 'measurement_center' or 'measurement_centerOfMass'. It provides technical prerequisites (valid JSON strings, WGS84 coordinate system) but lacks explicit guidance on tool selection scenarios.

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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