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 xuansenpa1/skillrevise --skill usgs-data-downloadgit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote 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/xuansenpa1/skillrevise/usgs-data-download)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/usgs-data-download"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/usgs-data-download/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/xuansenpa1/skillrevise/usgs-data-download"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/usgs-data-download.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 | $0.00046 | $0.00876 |
| Opus 5 | $0.00023 | $0.00438 |
| Sonnet 5 | $0.00009 | $0.00175 |
| Haiku 4.5 | $0.00005 | $0.00088 |
Grade A, and why
usgs-data-download 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 8d 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.
This is a copy
100% identical to usgs-data-download — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
USGS Data Download Guide
Overview
This guide covers downloading water level data from USGS using the dataretrieval Python package. USGS maintains thousands of stream gages across the United States that record water levels at 15-minute intervals.
Installation
pip install dataretrieval
nwis Module (Recommended)
The NWIS module is reliable and straightforward for accessing gage height data.
from dataretrieval import nwis
# Get instantaneous values (15-min intervals)
df, meta = nwis.get_iv(
sites='<station_id>',
start='<start_date>',
end='<end_date>',
parameterCd='00065'
)
# Get daily values
df, meta = nwis.get_dv(
sites='<station_id>',
start='<start_date>',
end='<end_date>',
parameterCd='00060'
)
# Get site information
info, meta = nwis.get_info(sites='<station_id>')
Parameter Codes
| Code | Parameter | Unit | Description |
|---|---|---|---|
00065 |
Gage height | feet | Water level above datum |
00060 |
Discharge | cfs | Streamflow volume |
nwis Module Functions
| Function | Description | Data Frequency |
|---|---|---|
nwis.get_iv() |
Instantaneous values | ~15 minutes |
nwis.get_dv() |
Daily values | Daily |
nwis.get_info() |
Site information | N/A |
nwis.get_stats() |
Statistical summaries | N/A |
nwis.get_peaks() |
Annual peak discharge | Annual |
Returned DataFrame Structure
The DataFrame has a datetime index and these columns:
| Column | Description |
|---|---|
site_no |
Station ID |
00065 |
Water level value |
00065_cd |
Quality code (can ignore) |
Downloading Multiple Stations
from dataretrieval import nwis
station_ids = ['<id_1>', '<id_2>', '<id_3>']
all_data = {}
for site_id in station_ids:
try:
df, meta = nwis.get_iv(
sites=site_id,
start='<start_date>',
end='<end_date>',
parameterCd='00065'
)
if len(df) > 0:
all_data[site_id] = df
except Exception as e:
print(f"Failed to download {site_id}: {e}")
print(f"Successfully downloaded: {len(all_data)} stations")
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.
- 8d ago First seen · 121 lines · 46 tokens per session scan A 82f0ec56e7bb
usgs-data-download is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 6d ago), licensed MIT. It adds 46 tokens to every session and 876 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to usgs-data-download, differing in 0 lines, and is treated as a copy.
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