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es3154

Turf-MCP

by es3154

measurement_area

Calculate polygon area in square meters from GeoJSON coordinates using WGS84 coordinate system. Accepts Polygon or MultiPolygon geometry types and returns area with units.

Instructions

计算多边形区域的面积。

此功能计算给定多边形区域的面积,返回以平方米为单位的数值结果。

Args: polygon: GeoJSON 多边形特征或几何图形 - 类型: str (JSON 字符串格式的 GeoJSON) - 格式: 必须符合 GeoJSON Polygon 规范 - 坐标系: WGS84 (经度在前,纬度在后) - 示例: '{"type": "Polygon", "coordinates": [[[125, -15], [113, -22], [154, -27], [144, -15], [125, -15]]]}'

Returns: str: JSON 字符串格式的面积结果对象 - 类型: 包含 value 和 units 的对象 - 格式: {"value": 面积数值, "units": "square meters"} - 示例: '{"value": 1234567.89, "units": "square meters"}'

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": [[[125, -15], [113, -22], [154, -27], [144, -15], [125, -15]]]}' >>> result = asyncio.run(area(polygon)) >>> print(result) '{"value": 1234567.89, "units": "square meters"}'

Notes: - 输入参数 polygon 必须是有效的 JSON 字符串 - 坐标顺序为 [经度, 纬度] (WGS84 坐标系) - 返回的面积单位为平方米 - 依赖于 Turf.js 库和 Node.js 环境 - 支持 Polygon 和 MultiPolygon 几何类型

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
polygonYes

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 an excellent job describing what the tool does (calculates area), the return format (JSON with value and units), error conditions (JavaScript execution failures, timeouts, input format errors), dependencies (Turf.js and Node.js), and supported geometry types (Polygon and MultiPolygon). The only minor gap is 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-loaded with the core purpose. While comprehensive, some sections like the detailed coordinate specification and dependencies could be slightly more concise. Overall, most sentences earn their place by adding valuable information beyond basic functionality.

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 with specific format requirements), no annotations, 0% schema coverage, but with an output schema (implied by Returns section), the description is remarkably complete. It covers input format, coordinate system, return format, error conditions, examples, dependencies, and supported geometry types. The agent has all necessary context to use this tool correctly without needing additional documentation.

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?

The input schema has 0% description coverage (just 'type': 'string'), so the description must fully compensate. It provides extensive parameter semantics: the 'polygon' parameter must be a JSON string in GeoJSON Polygon format, using WGS84 coordinates with longitude-first ordering, and includes a complete example. This goes far beyond what the schema provides and gives the agent everything needed to construct valid input.

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 with a specific verb ('计算' meaning 'calculate') and resource ('多边形区域的面积' meaning 'area of a polygon region'). It distinguishes itself from sibling tools like 'measurement_length' or 'measurement_distance' by focusing specifically on area calculation for polygons, not linear measurements or other geometric properties.

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 by specifying it calculates polygon area, but doesn't explicitly state when to use this tool versus alternatives like 'measurement_square' or other measurement tools. It provides technical constraints (e.g., GeoJSON format, WGS84 coordinate system) which give some context, but lacks explicit guidance on scenarios where this tool is preferred over others or when it should not be used.

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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