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es3154

Turf-MCP

by es3154

measurement_envelope

Convert geographic objects to bounding box polygons for spatial analysis. Calculates the minimum rectangular area containing all input features and outputs a GeoJSON polygon geometry.

Instructions

将地理对象转换为边界框多边形。

此功能计算给定地理对象的边界框,并将其转换为完整的多边形几何图形,便于进行多边形操作。

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": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.343, 39.984]}}, ...]}'

Returns: str: JSON 字符串格式的 GeoJSON Polygon 特征 - 类型: GeoJSON Feature with Polygon geometry - 格式: {"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [...]}} - 示例: '{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-82, 35], [-74, 35], [-74, 42], [-82, 42], [-82, 35]]]}}'

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": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.343, 39.984]}}]}' >>> result = asyncio.run(envelope(geojson)) >>> print(result) '{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-82, 35], [-74, 35], [-74, 42], [-82, 42], [-82, 35]]]}}'

Notes: - 输入参数 geojson 必须是有效的 JSON 字符串 - 坐标顺序为 [经度, 纬度] (WGS84 坐标系) - 包络多边形是包含所有输入特征的最小边界框多边形 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geojsonYes

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. It discloses that the tool calculates the minimal bounding box, converts to polygon geometry, depends on Turf.js/Node.js, and raises exceptions for execution failures, timeouts, or malformed input. It doesn't mention performance characteristics or rate limits, but covers key behavioral aspects.

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 details in the Notes could be more concise, but every sentence adds value for understanding the tool's behavior and constraints.

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 moderate complexity (geospatial transformation), no annotations, 0% schema coverage, but with output schema provided, the description is remarkably complete. It covers purpose, parameters, return format, error conditions, examples, dependencies, and coordinate system details - everything needed for correct tool invocation.

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?

Schema description coverage is 0%, so the description must compensate fully. It provides extensive parameter semantics: geojson must be a valid JSON string in WGS84 coordinate system with [longitude, latitude] order, includes format requirements, and gives a concrete example. This goes far beyond the basic schema type information.

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: '将地理对象转换为边界框多边形' (convert geographic objects to bounding box polygons). It specifies the exact transformation (bounding box calculation and polygon conversion) and distinguishes from siblings like 'measurement_bbox' (which likely returns just the bbox coordinates) by emphasizing the polygon output format.

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 converting geographic objects to polygon geometries for polygon operations. It doesn't explicitly mention when NOT to use it or name specific alternatives among siblings, but the purpose inherently suggests it's for polygon output rather than raw bbox coordinates.

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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