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es3154

Turf-MCP

by es3154

helper_point

Create GeoJSON point features from coordinates to represent geographic locations in geospatial analysis.

Instructions

创建点特征对象。

此功能根据坐标点创建点特征,用于表示具体的地理位置点。

Args: coordinates: 坐标点 - 类型: str (JSON 字符串格式的数组) - 格式: [lng, lat] - 示例: '[-75.343, 39.984]'

properties: 属性对象
    - 类型: str (JSON 字符串) 或 None
    - 格式: 键值对对象
    - 示例: '{"name": "Location A", "type": "city"}'

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]
        - id: 特征的标识符
    - 示例: '{"bbox": [-75.5, 39.5, -75, 40], "id": "point1"}'

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

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 >>> coordinates = '[-75.343, 39.984]' >>> properties = '{"name": "Location A"}' >>> result = asyncio.run(point(coordinates, properties)) >>> print(result) '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.343, 39.984]}, "properties": {"name": "Location A"}}'

Notes: - 输入参数 coordinates、properties 和 options 必须是有效的 JSON 字符串 - 坐标顺序为 [经度, 纬度] (WGS84 坐标系) - 点特征是地理信息系统中最基本的要素类型 - 依赖于 Turf.js 库和 Node.js 环境

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coordinatesYes
propertiesNo
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 the full burden. It discloses key behavioral traits: it creates a GeoJSON Point Feature, specifies input/output formats, notes dependencies (Turf.js, Node.js), lists exceptions (JavaScript execution failure, timeout, input format errors), and provides an example. However, it doesn't mention rate limits, authentication needs, or side effects beyond creation.

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), front-loading the purpose. It is appropriately sized but includes some redundant details (e.g., repeating JSON string format in multiple places). Every sentence adds value, though it could be slightly more concise.

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 (3 parameters, creation operation), no annotations, and an output schema exists (implied by Returns section), the description is complete. It covers purpose, parameters, return values, errors, examples, and notes, providing all necessary context for an agent to use the tool correctly.

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 compensate. It fully documents all 3 parameters (coordinates, properties, options) with types, formats, examples, and optional fields. This adds significant meaning beyond the basic schema, providing clear semantics and usage details for each parameter.

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: '创建点特征对象' (create point feature object) and elaborates that it '根据坐标点创建点特征,用于表示具体的地理位置点' (creates point features based on coordinate points, used to represent specific geographic location points). This is specific (verb+resource), distinguishes it from sibling tools like helper_featureCollection or helper_lineString, and avoids tautology.

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 examples and notes (e.g., coordinates in WGS84, JSON string requirements), but does not explicitly state when to use this tool versus alternatives. It mentions dependencies (Turf.js, Node.js) and basic use cases, but lacks explicit guidance on when to choose this over other helper_* tools or when not to use it.

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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