Download data
A Claude Code plugin that adds GeoAI-powered skills for data exploration and session memory.
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Download NAIP aerial imagery for a bounding box. Specify coordinates as minx,miny,maxx,maxy in WGS84 and optionally a year.
SKILL.md
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You are helping the user download NAIP aerial imagery using geoai.
Input: $@
Follow these steps in order.
Step 1 -- Parse arguments
Extract the bounding box from the first argument (comma-separated minx,miny,maxx,maxy).
Parse optional flags from remaining arguments:
--year YYYY-> download year (default: most recent available)--output DIR-> output directory (default:./naip_data/)--max-items N-> maximum number of items to download (default: 10)
If the input is natural language (e.g. "download NAIP imagery for Knoxville, TN"), extract or infer the bounding box. If you cannot determine the bbox, ask the user for coordinates.
Step 2 -- Validate the bounding box
Confirm the bounding box has 4 numeric values and represents a valid geographic extent:
minx < maxxandminy < maxy- Longitude values within -180 to 180
- Latitude values within -90 to 90
- The area is not unreasonably large (warn if the bbox spans more than 1 degree in either direction)
If validation fails, report the issue and ask for corrected coordinates.
Step 3 -- Run the download
python3 -c "
import geoai, os
bbox = (MINX, MINY, MAXX, MAXY)
output_dir = 'OUTPUT_DIR'
os.makedirs(output_dir, exist_ok=True)
result = geoai.download_naip(
bbox=bbox,
output_dir=output_dir,
year=YEAR,
max_items=MAX_ITEMS,
)
if isinstance(result, list):
for f in result:
size_mb = os.path.getsize(f) / (1024 * 1024) if os.path.exists(f) else 0
print(f'{f} ({size_mb:.1f} MB)')
print(f'Total files: {len(result)}')
elif isinstance(result, str):
size_mb = os.path.getsize(result) / (1024 * 1024) if os.path.exists(result) else 0
print(f'{result} ({size_mb:.1f} MB)')
else:
print(f'Result: {result}')
"
Replace MINX, MINY, MAXX, MAXY, OUTPUT_DIR, YEAR, and MAX_ITEMS with actual values.
For the year parameter:
- If
--yearwas specified, use that value (e.g.year=2022) - If not specified, omit the parameter or pass
year=Noneto get the most recent available
Step 4 -- Update state
If a state directory exists, update it with the downloaded file paths:
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:
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.setdefault('downloaded_files', [])
state['downloaded_files'].extend(DOWNLOADED_FILES)
with open(state_file, 'w') as f:
json.dump(state, f, indent=2)
"
Step 5 -- Report results
Summarize the download:
- Number of files downloaded
- File paths and sizes
- Coverage area (bounding box)
- Year of imagery
Then suggest: "Use /geoai-skills:inspect-geo to examine the downloaded imagery, or /geoai-skills:detect-objects to run AI models on it."
Error handling
import geoaifails -> delegate to/geoai-skills:install-geoai.- Network error -> report the error and suggest retrying.
- No data available for the specified region/year -> suggest trying a different year or expanding the bounding box.
- Timeout -> suggest reducing
--max-itemsor using a smaller bounding box.