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es3154

Turf-MCP

by es3154

random_randomLineString

Generate random line features within specified bounding boxes for geospatial testing and simulation. Create custom GeoJSON LineString collections with configurable vertex counts and spatial parameters.

Instructions

生成随机线特征集合。

此功能在指定边界框内生成指定数量的随机线,返回线特征集合。

Args: count: 生成线的数量 - 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])
        - num_vertices: 每条线的顶点数量 (默认: 10)
        - max_length: 顶点与前一个顶点的最大距离 (默认: 0.0001)
        - max_rotation: 线段与前一线段的最大旋转角度 (默认: Math.PI/8)
    - 示例: '{"bbox": [-180, -90, 180, 90], "num_vertices": 10}'

Returns: str: JSON 字符串格式的 GeoJSON FeatureCollection - 类型: GeoJSON FeatureCollection with LineString features - 格式: {"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "LineString", "coordinates": [...]}}, ...]} - 示例: '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "LineString", "coordinates": [[-74, 40], [-78, 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 >>> result = asyncio.run(randomLineString(25)) >>> print(result) '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "LineString", "coordinates": [[-74, 40], [-78, 42], [-82, 35]]}}, ...]}'

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线 - 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 at disclosing behavioral traits. It explains the return format (GeoJSON FeatureCollection), error conditions (JavaScript execution failures, timeouts, input format errors), dependencies (Turf.js and Node.js), coordinate system (WGS84), and default behaviors (global bounding box when unspecified). It doesn't mention performance characteristics or rate limits, but covers most essential operational aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (Args, Returns, Raises, Example, Notes) but is quite lengthy. While all information is relevant, some redundancy exists (e.g., multiple mentions of GeoJSON format). The front-loaded purpose statement is clear, but the overall text could be more streamlined while maintaining completeness.

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 with output schema), the description is remarkably complete. It covers purpose, parameters, return format, errors, examples, dependencies, coordinate systems, and default behaviors. The output schema exists but the description still usefully explains the GeoJSON structure. No significant gaps remain for effective tool use.

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?

With 0% schema description coverage and 2 parameters, the description provides comprehensive parameter documentation beyond the bare schema. It explains 'count' with type, default, and example, and details 'options' with its JSON structure, optional fields (bbox, num_vertices, max_length, max_rotation), their defaults, and examples. This fully compensates for the schema's lack of descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '生成随机线特征集合' (generate random line feature collection) and specifies it operates within a bounding box. It distinguishes from siblings like random_randomPoint and random_randomPolygon by focusing on lines, but doesn't explicitly contrast with them. The verb+resource combination is specific but sibling differentiation is implicit rather than explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. While it mentions generating random lines, it doesn't explain scenarios where this is preferable to other random generation tools (like random_randomPoint) or when to use it within the broader geospatial workflow. There's no mention of prerequisites, dependencies, or typical use cases.

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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