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kml公里

Agent Skill

kml 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,602

周安装

188

GitHub Stars

公开资料未说明

下载量

1,474
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:kml(公里)
来源仓库:https://github.com/jvy/kml
安装命令:
openclaw skills install kml
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install kml

简介

kml 用于检查和提取 KML/KMZ 文件中的地理数据。

  • 提供地标几何计数、文件夹结构和坐标范围等信息。
  • 适合在 OpenClaw 中处理地理空间数据或验证文件完整性时使用。
  • 可结合来源仓库和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围和维护状态。kml 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
kml
description
Inspect, validate, summarize, and extract data from KML and KMZ files, including Placemark geometry counts, Folder structure, coordinate ranges, bbox generation, altitude tuples, Google Earth packaging issues, and conversion guidance. Use when the user asks about KML, KMZ, Google Earth placemarks, coordinate extraction, KML cleanup, KMZ debugging, or KML data processing. 中文触发:KML、KMZ、谷歌地球、地标、坐标提取、KML 校验、KMZ 解包、KML 数据处理。
metadata
openclaw
emoji
🌐
requires
bins
["python3"]
install
kind
brew
formula
python
bins
["python3"]
label
Install Python 3 (brew)

KML

Use this skill for practical KML and KMZ inspection, validation, and lightweight data extraction.

This skill is optimized for safe analysis of KML structure and coordinates. For deterministic reprojection, clipping, format conversion, or batch GIS processing on files, hand off to qgis.

What This Skill Does

  • Inspect .kml and .kmz files.
  • Summarize document name, placemark count, geometry types, folder count, and bbox.
  • Validate coordinate tuples and flag obvious longitude/latitude range problems.
  • Extract placemark-level summaries for downstream review or cleanup.
  • Explain common KML/KMZ issues such as missing doc.kml, malformed XML, empty Placemark, or suspicious coordinate order.

Standard Workflow

  1. Confirm whether the input is a .kml file or a .kmz archive.
  2. Parse the XML and detect the main KML document inside KMZ when needed.
  3. Count placemarks, geometry types, folders, overlays, and coordinates.
  4. Compute bbox from parsed coordinates when possible.
  5. Flag likely issues:

- malformed XML - KMZ archive without a readable KML payload - coordinate tuples outside lon/lat range - empty placemarks without geometry

  1. If the user needs reprojection, clipping, or deterministic file conversion, switch to qgis.

Practical Commands

Summarize a KML or KMZ file

python3 {baseDir}/scripts/kml_tool.py summary --file ./data/sample.kml

Validate a KML or KMZ file

python3 {baseDir}/scripts/kml_tool.py validate --file ./data/sample.kmz

List placemark summaries

python3 {baseDir}/scripts/kml_tool.py placemarks --file ./data/sample.kml

Decision Rules

  • Treat KML coordinates as lon,lat[,alt] unless the source explicitly says otherwise.
  • KML is commonly used with WGS84-style geographic coordinates; if precision matters, confirm the source workflow instead of guessing.
  • Do not silently rewrite malformed coordinates; report the exact problem.
  • Prefer writing derived outputs to a new path when a later task requires edits or conversion.
  • If the user wants GeoJSON, Shapefile, reprojection, clipping, or batch cleanup, route execution to qgis.

What To Return

  • Source type: kml or kmz.
  • Document name when present.
  • Placemark count and geometry type counts.
  • Folder and overlay counts.
  • Bounding box when coordinates are present.
  • Specific validation errors or suspicious patterns when found.

When Not To Use

  • Reverse geocoding or coordinates-to-address lookup: use geocode.
  • WGS84-specific CRS reasoning: use wgs84.
  • Deterministic GIS conversion, reprojection, clipping, or raster/vector processing: use qgis.
  • Web map rendering logic: use leaflet, mapbox, or cesium as appropriate.

OpenClaw + ClawHub Notes

  • Keep examples generic and portable.
  • Do not hardcode private datasets, machine paths, or secrets.
  • For clawhub.ai publication, keep examples standards-based and version/changelog updates semver-driven.

Reference Docs In This Skill

  • Read {baseDir}/references/patterns.md for KML/KMZ structure notes, common failures, and escalation guidance.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

96.3%
按下载量换算1,419

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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