geoai-skills
A Claude Code plugin that adds GeoAI-powered skills for geospatial data exploration, satellite imagery download, AI-based object detection, and session memory.
Built on the GeoAI Python library.
Installation
From GitHub
Add the repository as a plugin source and install:
/plugin marketplace add opengeos/geoai-skills
/plugin install geoai-skills@geoai-skills
This registers the GitHub repo as a marketplace and installs the plugin. Skills will be available as /geoai-skills:<skill-name> in all future sessions.
Updating
To pull the latest version, update the marketplace first and then the plugin:
/plugin marketplace update geoai-skills
/plugin update geoai-skills@geoai-skills
Prerequisites
- Python 3.10+ with the
geoai-py package installed (pip install geoai-py)
- For AI models (object detection, segmentation): PyTorch with CUDA (optional, CPU works but is slower)
- For Overture Maps data:
pip install "geoai-py[extra]"
Skills
inspect-geo
Inspect any raster or vector geospatial file -- CRS, bounds, bands, resolution, dtype, attribute summaries, and band statistics. Supports GeoTIFF, Shapefile, GeoJSON, GeoPackage, GeoParquet, and more.
/geoai-skills:inspect-geo dem.tif
/geoai-skills:inspect-geo buildings.gpkg what CRS is this in?
/geoai-skills:inspect-geo landcover.tif how many bands does it have?
download-data
Download NAIP aerial imagery for a bounding box. Specify coordinates as minx,miny,maxx,maxy in WGS84 and optionally a year.
/geoai-skills:download-data -83.5,35.5,-83.4,35.6 --year 2022
/geoai-skills:download-data -122.5,37.7,-122.3,37.8 --output ./naip/
search-stac
Search and download satellite imagery from Microsoft Planetary Computer. Browse collections, search by bbox and time range, and download items.
/geoai-skills:search-stac list
/geoai-skills:search-stac sentinel-2-l2a --bbox -83.5,35.5,-83.4,35.6 --datetime 2023-01-01/2023-06-30
/geoai-skills:search-stac naip --bbox -83.5,35.5,-83.4,35.6 --download
overture-data
Download Overture Maps data (buildings, places, roads, land use, water, etc.) for a bounding box.
/geoai-skills:overture-data building --bbox -83.5,35.5,-83.4,35.6
/geoai-skills:overture-data land_use --bbox -122.5,37.7,-122.3,37.8 --output land_use.gpkg
process-raster
Process raster data: clip by bounding box, stack multiple bands, mosaic GeoTIFFs, or convert between raster and vector formats.
/geoai-skills:process-raster clip input.tif --bbox -83.5,35.5,-83.4,35.6
/geoai-skills:process-raster mosaic ./tiles/ --output mosaic.tif
/geoai-skills:process-raster stack band1.tif band2.tif band3.tif --output stacked.tif
/geoai-skills:process-raster raster-to-vector classification.tif --output polygons.gpkg
detect-objects
Run pre-trained AI models on geospatial imagery. Detect buildings, cars, ships, solar panels, or use text-prompted segmentation with GroundedSAM.
/geoai-skills:detect-objects buildings naip_image.tif
/geoai-skills:detect-objects cars parking_lot.tif --output car_detections.gpkg
/geoai-skills:detect-objects grounded-sam satellite.tif --text "swimming pools"
read-memories
Search past Claude Code session logs to recover context from previous conversations -- past decisions, data paths, CRS info, model configurations, and unresolved work.
/geoai-skills:read-memories naip --here
/geoai-skills:read-memories building detection --geo
install-geoai
Verify that the geoai Python package is installed and functional. Optionally check extra dependencies for deep learning models.
/geoai-skills:install-geoai
/geoai-skills:install-geoai --check
/geoai-skills:install-geoai --extras
Session state
Skills can share state through a JSON file per project (state.json), containing information about recently inspected files, downloaded data paths, and working directories. When state is first needed, you will be asked where to store it:
- In the project directory (
.geoai-skills/state.json) -- colocated with the project, optionally gitignored
- In your home directory (
~/.geoai-skills/<project-id>/state.json) -- keeps the project directory clean
State is used to auto-fill file paths across skills. For example, after downloading NAIP imagery, inspect-geo and detect-objects can reference the downloaded files without re-specifying paths.
How the skills work together
Skills reference each other where it makes sense:
inspect-geo suggests process-raster for processing and detect-objects for AI analysisdownload-data, search-stac, and overture-data suggest inspect-geo for examining resultsdetect-objects suggests inspect-geo for examining detection output- All skills delegate to
install-geoai when the geoai package is not available
read-memories with --geo extracts geospatial-specific context from past sessions
A typical workflow:
/geoai-skills:download-data -83.5,35.5,-83.4,35.6 --year 2022
/geoai-skills:inspect-geo naip_image.tif
/geoai-skills:detect-objects buildings naip_image.tif
/geoai-skills:inspect-geo buildings_detections.gpkg
Local development
To test skills locally from a clone of this repo:
# 1. Clone the repo
git clone https://github.com/opengeos/geoai-skills.git
cd geoai-skills
# 2. Launch Claude Code with the local plugin directory
claude --plugin-dir .
This loads the plugin from disk instead of the marketplace, so any edits to skills/*/SKILL.md take effect immediately -- just start a new conversation (or re-run the slash command) to pick up changes.
Platform support
These skills have been tested on macOS and Linux. Windows is not yet fully supported -- some shell commands and path handling may not work as expected.
Reporting issues
Found a bug or have an idea for improvement? Open an issue at:
https://github.com/opengeos/geoai-skills/issues
For geoai-specific bugs (model loading, data download errors), please include the geoai version (python -c "import geoai; print(geoai.__version__)") and the full error message.
