Data & analysis

KML Toolkit

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Inspect, validate, summarize, and extract data from KML and KMZ files, including Placemark geometry counts, Folder structure, coordinate ranges, bbox generat...

What it does

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

The skill document

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
  6. 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.

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