Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add opengeos/geoai-skills --skill download-datagit clone --depth 1 https://github.com/opengeos/geoai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/opengeos/geoai-skills/download-data)<a href="https://agentmods.dev/skills/opengeos/geoai-skills/download-data"><img src="https://agentmods.dev/badge/skills/opengeos/geoai-skills/download-data/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/opengeos/geoai-skills/download-data"><img src="https://agentmods.dev/badge/skills/opengeos/geoai-skills/download-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.01013 |
| Opus 5 | $0.00016 | $0.00507 |
| Sonnet 5 | $0.00007 | $0.00203 |
| Haiku 4.5 | $0.00003 | $0.00101 |
Grade A, and why
download-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 117 lines · 33 tokens per session scan A 73c9b3c9d9fb
download-data is a skill published in the GitHub repository opengeos/geoai-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 1,013 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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