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es3154

Turf-MCP

by es3154

transformation_transformScale

Scale GeoJSON objects by a specified factor from a defined origin point using Turf.js. Adjust geographic features proportionally for spatial analysis and data manipulation.

Instructions

缩放 GeoJSON 对象。

该函数使用 Turf.js 库的 transformScale 方法,从给定点缩放 GeoJSON 对象。

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": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[0,29],[3.5,29],[2.5,32],[0,29]]]}}'

factor: 缩放因子
    - 类型: float
    - 描述: 缩放因子,例如 2 表示放大两倍
    - 示例: 3.0

options: 可选参数配置
    - 类型: str (JSON 字符串) 或 None
    - 可选字段:
        - origin: 缩放原点坐标 (默认: 'centroid')
        - mutate: 是否允许修改输入对象 (默认: false)
    - 示例: '{"origin": [0, 25], "mutate": false}'

Returns: str: JSON 字符串格式的缩放后的 GeoJSON 对象 - 类型: 与输入相同的 GeoJSON 类型 - 格式: 与输入相同的格式 - 示例: '{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[0,29],[10.5,29],[7.5,32],[0,29]]]}}'

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 >>> geojson = '{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[0,29],[3.5,29],[2.5,32],[0,29]]]}}' >>> result = asyncio.run(transformScale(geojson, 3.0)) >>> print(result) '{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[0,29],[10.5,29],[7.5,32],[0,29]]]}}'

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) - 缩放因子为 2 表示尺寸加倍 - 默认从几何图形的质心缩放 - 对于 FeatureCollection,为每个特征单独计算原点 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geojsonYes
factorYes
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 does well by explaining key behaviors: it specifies coordinate system (WGS84 with longitude-first), default scaling origin ('centroid'), mutation behavior via the 'mutate' option, handling of FeatureCollections, and error conditions (JavaScript failures, timeouts, data format errors). However, it doesn't mention performance characteristics or rate limits.

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, some sections could be more concise (e.g., the example includes full import statements). Overall, most sentences earn their place by adding valuable information.

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 transformation with multiple parameters), no annotations, and an output schema present, the description provides excellent completeness. It covers purpose, parameters, return values, errors, examples, and implementation details (Turf.js, Node.js). The output schema handles return format documentation, allowing the description to focus on behavioral context.

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: geojson (format, coordinate system, examples), factor (meaning of values, examples), and options (optional fields, defaults, examples). Each parameter's purpose, format, and constraints are clearly explained 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: '缩放 GeoJSON 对象' (scale GeoJSON objects) using Turf.js transformScale method. It specifies the exact operation (scaling), the resource (GeoJSON objects), and distinguishes it from sibling transformation tools like transformRotate or transformTranslate by focusing specifically on scaling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. While it mentions the Turf.js library and Node.js environment, it doesn't explain when scaling is appropriate compared to other geometric transformations available in the sibling tools list, nor does it mention prerequisites or constraints beyond technical requirements.

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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