Openclaw Skills for vector GIS conversion lets you transform spatial data between major geospatial formats with zero external dependencies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install geoskill-vector-convert
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install geoskill-vector-convert using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Vector Format Converter?
Vector Format Converter
Openclaw Skills provides a lightweight, standard-library-only workflow for converting vector GIS data across common spatial formats including Shapefile, GeoJSON, KML, GPX, GeoPackage, and CSV. It is designed for developers and GIS practitioners who need reliable format interoperability without installing heavyweight geospatial stacks.
This skill emphasizes portability, transparency, and control: auto-detect inputs, inspect file metadata, transform coordinate systems, filter attributes, clip by bounding box, and export clean outputs from a single Python CLI. Openclaw Skills makes vector conversion practical in constrained environments where dependency-free execution matters.
Vector Format Converter Use Cases
- Converting legacy Shapefiles into web-friendly GeoJSON for maps and APIs.
- Exporting GeoJSON or KML into GeoPackage for desktop GIS workflows.
- Turning GPX tracks into tabular CSV for analysis and reporting.
- Verifying dataset metadata before conversion using info mode.
- Reprojecting features between EPSG codes such as 4326 and 3857.
- Reducing payload size by rounding coordinates or selecting only needed fields.
- Clipping spatial datasets to a bounding box for regional processing.
- Running GIS conversions in environments where external Python dependencies are not allowed.
How Vector Format Converter Works
- The tool detects the input vector format from the file extension and loads the corresponding parser.
- It reads geometry, attributes, and available projection metadata from formats such as SHP/DBF/SHX/PRJ or GeoPackage.
- You specify the target output format with
--to, along with optional processing flags like--crs,--precision,--fields, or--bbox. - The skill applies any requested transformations, including CRS reprojection, coordinate rounding, property filtering, and spatial clipping.
- It writes the converted dataset to the requested output path in the destination format.
- If
--infois used, it skips conversion and prints dataset summary details such as feature count, CRS, bounds, and field names.
Vector Format Converter Setup
Requirements
- Python 3.8+
- No third-party packages required
Installation
If you have the script available locally, run it directly with Python:
python vector-convert.py --help
Basic conversion examples
python vector-convert.py input.shp --to geojson -o output.geojson
python vector-convert.py input.geojson --to shp -o output.shp
python vector-convert.py input.kml --to gpkg -o output.gpkg
Optional configuration and workflow examples
python vector-convert.py input.shp --info
python vector-convert.py input.shp --to geojson --crs EPSG:3857
python vector-convert.py input.geojson --to csv --precision 4
python vector-convert.py input.geojson --to csv --fields name,type,population
python vector-convert.py input.shp --to geojson --bbox -180 -90 180 90
Testing
pytest tests/ -v
Notes
- Input format is inferred from file extension.
- GeoPackage support uses SQLite-based storage.
- SHP parsing is handled manually for SHP/DBF/SHX/PRJ components.
Vector Format Converter Data Schema & Taxonomy
File and data organization
Openclaw Skills for vector conversion follows a simple file-oriented schema:
| Element | Purpose | Notes |
|---|---|---|
| Input file | Source vector dataset | Format detected by extension |
| Output file | Converted dataset | Extension should match --to target |
| Geometry | Spatial coordinates and shapes | Preserved or reprojected during conversion |
| Attributes | Feature properties | Can be filtered with --fields |
| CRS metadata | Coordinate reference system | Can be transformed with --crs |
| Bounds / bbox | Spatial extent | Exposed in info mode and usable for clipping |
Supported formats
| Format | Extension | Read | Write |
|---|---|---|---|
| Shapefile | .shp |
Yes | Yes |
| GeoJSON | .geojson, .json |
Yes | Yes |
| KML | .kml |
Yes | Yes |
| GPX | .gpx |
Yes | Yes |
| GeoPackage | .gpkg |
Yes | Yes |
| CSV | .csv |
Yes | Yes |
Metadata taxonomy
feature_count: Number of records in the dataset.crs: Spatial reference system, typically expressed as an EPSG code.bounds: Dataset extent for quick inspection and bbox clipping.field_names: Available attribute columns for selection and export.precision: Output coordinate rounding level when specified.bbox: Spatial filter used to include intersecting features only.
Vector Format Converter Advanced Features
- Zero-dependency execution using only the Python standard library.
- Manual binary parsing for SHP/DBF/SHX/PRJ components, enabling low-level control.
- CRS transformation support across common EPSG codes such as 4326 and 3857.
- Precision control for coordinate rounding in exported datasets.
- Attribute field filtering for schema trimming and CSV-focused exports.
- Bounding-box clipping for fast regional subsetting.
- Info mode for rapid dataset inspection without conversion.
- GeoPackage read/write support for SQLite-based spatial workflows.
- Openclaw Skills compatibility for portable CLI-driven automation in constrained environments.
SKILL.md
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