download-data
SkillDev toolsDownload NAIP aerial imagery for a bounding box. Specify coordinates as minx,miny,maxx,maxy in WGS84 and optionally a year.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the download-data skill
What this skill tells your AI
The instructions your AI receives, as published by opengeos/geoai-skills in skills/download-data/SKILL.md and read by ahel’s review.
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.
Signals
- GitHub stars
- 30
- Forks
- 4
- Last commit
- Jul 2026
Advanced
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- skill
- Gateway key
download-data- Source
- github.com/opengeos/geoai-skills