kml

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

Security Scan

The skill's code, instructions, and install steps are coherent with its described purpose (KML/KMZ inspection and validation); it requires only python3, has no credentials, and contains no network or surprising behavior.

Purpose & Capability

Name/description match the included script and examples. Required binary is python3 and the code implements summary, validation, and placemark extraction as described — nothing requests unrelated services or credentials.

Instruction Scope

SKILL.md instructs the agent to parse local .kml/.kmz files and to read the bundled reference docs. The runtime instructions and example commands only reference local paths and the included script; they do not instruct the agent to read unrelated system files or send data to external endpoints.

Install Mechanism

Install uses a standard brew formula for Python (python). This is a low-risk, conventional install path and the skill itself is a pure Python script bundled in the package (no remote downloads or exec of fetched binaries).

Credentials

No environment variables, credentials, or config paths are requested. The tool only needs local file access to whatever KML/KMZ file is supplied, which is proportional to the stated tasks.

Persistence & Privilege

always is false and the skill does not modify other skills or system config. The provided agents/openai.yaml sets allow_implicit_invocation: true (normal for skills) so the agent could call it autonomously; this is expected but worth noting if you prefer to restrict implicit invocations.

Assessment

This skill appears to do exactly what it says: local parsing and reporting of KML/KMZ files using a bundled Python script. Before installing, confirm you are comfortable allowing the agent to run python3 on local files. Do not feed sensitive files containing secrets or private data unless you trust the agent environment, since the tool prints parsed contents (JSON) to stdout and those logs could be recorded. If you prefer to avoid autonomous use, disable implicit/automatic invocation in agent settings. Finally, be aware that extremely large or pathological XML/KMZ files could cause resource consumption when parsed — consider testing with a sample file first.

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.