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es3154

Turf-MCP

by es3154

random_randomPoint

Generate random geographic point features within a specified bounding box. Create custom point collections for testing, sampling, or simulation in geospatial applications.

Instructions

生成随机点特征集合。

此功能在指定边界框内生成指定数量的随机点,返回点特征集合。

Args: count: 生成点的数量 - 类型: int - 默认: 1 - 示例: 25

options: 可选参数配置
    - 类型: str (JSON 字符串) 或 None
    - 可选字段:
        - bbox: 边界框数组 [minX, minY, maxX, maxY] (默认: [-180, -90, 180, 90])
    - 示例: '{"bbox": [-180, -90, 180, 90]}'

Returns: str: JSON 字符串格式的 GeoJSON FeatureCollection - 类型: GeoJSON FeatureCollection with Point features - 格式: {"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [lng, lat]}}, ...]} - 示例: '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.343, 39.984]}}, ...]}'

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 >>> result = asyncio.run(randomPoint(25)) >>> print(result) '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.343, 39.984]}}, ...]}'

Notes: - 输入参数 options 必须是有效的 JSON 字符串或 None - 坐标顺序为 [经度, 纬度] (WGS84 坐标系) - 如果未指定边界框,默认在全球范围内生成随机点 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
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 disclosing: coordinate system (WGS84 with [lng, lat] order), default behavior (global bounding box if unspecified), dependencies (Turf.js and Node.js), error conditions (JavaScript execution failures, timeouts, input format errors), and return format details. It doesn't mention performance characteristics like rate limits or computational cost.

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?

Well-structured with clear sections (Args, Returns, Raises, Example, Notes), but somewhat verbose. The Python example and detailed JSON format specifications could be simplified. Most sentences earn their place by providing necessary information, though some redundancy exists in the Returns section.

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 (2 parameters, no annotations, but has output schema), the description is highly complete. It covers purpose, parameters, return format, errors, examples, and implementation notes. The output schema exists, so the description appropriately focuses on explaining the GeoJSON format rather than just restating it.

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 fully compensate. It provides comprehensive parameter documentation: 'count' with type, default, and example; 'options' with type details, optional fields (bbox with format and default), and JSON string requirement. The description adds significant value beyond the minimal input 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 with specific verb ('生成随机点特征集合' - generate random point feature collection) and resource ('在指定边界框内' - within specified bounding box). It distinguishes from siblings like random_randomLineString and random_randomPolygon by specifying it generates points, not lines or polygons.

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 context through parameter explanations (e.g., '如果未指定边界框,默认在全球范围内生成随机点' - if no bounding box specified, defaults to global range), but doesn't explicitly state when to use this tool versus alternatives like random_randomPosition or grid_pointGrid. No explicit when-not-to-use guidance is provided.

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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