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es3154

Turf-MCP

by es3154

feature_conversion_flatten

Convert complex multi-geometries into simple geometry feature collections for easier geospatial analysis and processing.

Instructions

将复合几何图形展平为简单几何图形。

此功能将多几何图形(如多点、多线、多多边形)展平为对应的简单几何图形特征集合。

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": "MultiPolygon", "coordinates": [[[[102.0, 2.0], [103.0, 2.0], [103.0, 3.0], [102.0, 3.0], [102.0, 2.0]]], [[[100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0]]]]}'

Returns: str: JSON 字符串格式的展平后特征集合 - 类型: GeoJSON FeatureCollection with simple geometry features - 格式: {"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "...", "coordinates": [...]}}, ...]}

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 >>> multi_polygon = '{"type": "MultiPolygon", "coordinates": [[[[102.0, 2.0], [103.0, 2.0], [103.0, 3.0], [102.0, 3.0], [102.0, 2.0]]], [[[100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0]]]]}' >>> result = asyncio.run(flatten(multi_polygon)) >>> print(result) '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[102.0, 2.0], [103.0, 2.0], [103.0, 3.0], [102.0, 3.0], [102.0, 2.0]]]}}, ...]}'

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) - 多几何图形会被展平为对应的简单几何图形集合 - 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 the full burden and does well by disclosing behavioral traits: it specifies the coordinate system (WGS84), notes dependencies (Turf.js and Node.js), and mentions error conditions (JavaScript execution failure, timeout, or input format errors). However, it does not detail rate limits, authentication needs, or side effects, leaving some gaps for a mutation-like tool.

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 for Args, Returns, Raises, Example, and Notes, making it easy to navigate. However, it is somewhat lengthy due to the detailed example and notes; while informative, some sentences could be more condensed without losing clarity, slightly reducing efficiency.

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 conversion), no annotations, and an output schema present, the description is complete: it explains the purpose, parameter details, return format (GeoJSON FeatureCollection), error handling, dependencies, and includes an example. This provides all necessary context for an AI agent to understand and use the tool effectively.

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 schema description coverage is 0%, but the description compensates fully by detailing the 'geojson' parameter: it specifies the type (string in JSON format), format (any valid GeoJSON object), coordinate system (WGS84 with longitude first), and provides an example. This adds significant meaning beyond the basic schema, making the parameter semantics clear and comprehensive.

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 specific verbs ('展平' meaning flatten) and resources ('复合几何图形' meaning composite geometries, '简单几何图形' meaning simple geometries), and it distinguishes from siblings by focusing on conversion of multi-geometries to simple features, unlike other conversion tools like 'feature_conversion_explode' or 'feature_conversion_combine' which handle different operations.

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 implies usage context by specifying it flattens multi-geometries (e.g., MultiPolygon) into simple geometry feature collections, but it does not explicitly state when to use this tool versus alternatives like 'feature_conversion_explode' or other geometric tools. It provides clear input requirements (valid GeoJSON string) but lacks explicit exclusions or comparisons with siblings.

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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