agentsclimarketplace

Download data

Skill opengeos/geoai-skills/skills/download-data

A Claude Code plugin that adds GeoAI-powered skills for data exploration and session memory.

Install
npx -y skills add opengeos/geoai-skills --skill download-data

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 24 stars24 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Download NAIP aerial imagery for a bounding box. Specify coordinates as minx,miny,maxx,maxy in WGS84 and optionally a year.

SKILL.md

3.7 KB, as published. Nobody here has run it

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.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.