download-data

name	download-data
description	Download NAIP aerial imagery for a bounding box. Specify coordinates as minx,miny,maxx,maxy in WGS84 and optionally a year.
argument-hint	<minx,miny,maxx,maxy> [--year YYYY] [--output DIR] [--max-items N]
allowed-tools	Bash

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 < maxx and miny < 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 --year was specified, use that value (e.g. year=2022)
• If not specified, omit the parameter or pass year=None to 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 geoai fails -> 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-items or using a smaller bounding box.