Inspect Geo

You are helping the user inspect a geospatial data file.

Filename given: $0 Question: ${1:-describe the data}

Follow these steps in order, stopping and reporting clearly if any step fails.

Step 1 -- Resolve the file path

If $0 looks like an absolute path, use it directly. Otherwise search for it:

find "$PWD" -name "$0" -not -path '*/.git/*' 2>/dev/null

• Zero results -> tell the user the file was not found and stop.
• More than one result -> list all matches, ask the user to re-run with a fuller path, and stop.
• Exactly one result -> use that full path as RESOLVED_PATH.

Step 2 -- Classify the file type

Determine whether the file is raster or vector based on its extension:

• Raster: .tif, .tiff, .img, .jp2, .vrt, .nc, .hdf
• Vector: .geojson, .json, .shp, .gpkg, .parquet, .geoparquet, .fgb, .kml

If the extension is ambiguous, try raster first, then vector.

Step 3 -- Run the appropriate inspection

Raster files

python3 -c "
import geoai

info = geoai.get_raster_info('RESOLVED_PATH')
for k, v in info.items():
    print(f'{k}: {v}')

print('---')
print('Band Statistics:')
stats = geoai.get_raster_stats('RESOLVED_PATH')
for k, v in stats.items():
    print(f'{k}: {v}')
"

Vector files

python3 -c "
import geoai

info = geoai.get_vector_info('RESOLVED_PATH')
for k, v in info.items():
    print(f'{k}: {v}')
"

Replace RESOLVED_PATH with the actual absolute path before running.

Step 4 -- Answer the user's question

Using the metadata retrieved in Step 3, answer:

${1:-describe the data: summarize the file type, CRS, extent, and any notable properties.}

For vector files, if the question references a specific attribute, run an additional analysis:

python3 -c "
import geoai
result = geoai.analyze_vector_attributes('RESOLVED_PATH')
print(result)
"

Step 5 -- Update state

Resolve the state directory:

STATE_DIR=""
test -f .geoai-skills/state.json && STATE_DIR=".geoai-skills"
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD")"
PROJECT_ID="$(echo "$PROJECT_ROOT" | tr '/' '-')"
test -f "$HOME/.geoai-skills/$PROJECT_ID/state.json" && STATE_DIR="$HOME/.geoai-skills/$PROJECT_ID"

If STATE_DIR is set, update it with the inspected file info:

python3 -c "
import json, os
state_file = 'STATE_DIR/state.json'
state = {}
if os.path.exists(state_file):
    with open(state_file) as f:
        state = json.load(f)
state['last_inspected'] = {
    'path': 'RESOLVED_PATH',
    'type': 'TYPE',
}
with open(state_file, 'w') as f:
    json.dump(state, f, indent=2)
"

Replace STATE_DIR, RESOLVED_PATH, and TYPE (raster or vector) with actual values.

If no state directory exists yet, skip this step silently.

Step 6 -- Suggest next steps

After reporting, briefly mention:

• For raster files: "To process this raster (clip, mosaic, stack bands), use /geoai-skills:process-raster. To run AI detection on it, use /geoai-skills:detect-objects."
• For vector files: "To download more vector data for this area, use /geoai-skills:overture-data."

Keep suggestions brief and show them only once.

Error handling

• If python3 is not found or import geoai fails, delegate to /geoai-skills:install-geoai.
• If rasterio or geopandas fails to read the file, try the GDAL/OGR fallback:

python3 -c "
import geoai
info = geoai.get_raster_info_gdal('RESOLVED_PATH')
for k, v in info.items():
    print(f'{k}: {v}')
"

Or for vectors:

python3 -c "
import geoai
info = geoai.get_vector_info_ogr('RESOLVED_PATH')
for k, v in info.items():
    print(f'{k}: {v}')
"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: opengeos
• Source: opengeos/geoai-skills
• License: MIT

Install and usage instructions live in the source repository linked above.