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es3154

Turf-MCP

by es3154

feature_conversion_explode

Convert GeoJSON geometries into individual point features by extracting all vertex coordinates from polygons, lines, or other shapes for detailed spatial analysis.

Instructions

将几何图形分解为单独的点特征。

此功能将给定的 GeoJSON 特征分解为所有顶点坐标的单独点特征集合。

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]]]}'

Returns: str: JSON 字符串格式的点特征集合 - 类型: GeoJSON FeatureCollection with Point features - 格式: {"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [lng, lat]}}, ...]}

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]]]}' >>> result = asyncio.run(explode(polygon)) >>> print(result) '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-81, 41]}}, ...]}'

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) - 返回所有几何图形顶点的点特征集合 - 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 returns a FeatureCollection of Points, specifies coordinate order (longitude, latitude), notes dependencies on Turf.js and Node.js, and mentions potential exceptions for execution failures, timeouts, or bad input. It could improve by detailing performance or memory implications for large inputs.

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 sections (Args, Returns, Raises, Example, Notes), but includes some redundancy (e.g., repeating coordinate order). Most sentences earn their place by clarifying behavior or parameters, though it could be slightly more concise by merging similar points.

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 (geometric conversion), no annotations, and an output schema (though not provided in context, described in Returns), the description is highly complete: it covers purpose, parameters, return format, errors, examples, dependencies, and coordinate specifics, leaving little ambiguity for an AI agent.

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, but the description fully compensates: it defines 'geojson' as a JSON string in GeoJSON format, specifies WGS84 coordinate system with [lng, lat] order, provides a detailed example, and notes it must be valid JSON. This adds significant meaning 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 tool's purpose: '将几何图形分解为单独的点特征' (decompose geometric shapes into separate point features). It specifies the verb (decompose/explode) and resource (geometric shapes/GeoJSON features), and distinguishes from siblings by focusing on vertex extraction rather than aggregation, conversion to other formats, or boolean operations listed in sibling tools.

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 when needing point features from geometric vertices, but does not explicitly state when to use this tool versus alternatives like 'feature_conversion_combine' or 'feature_conversion_flatten'. It provides context about input format and coordinate system, but lacks explicit comparisons or exclusions for sibling tools.

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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