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 nws-flood-thresholdsgit 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/nws-flood-thresholds)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/nws-flood-thresholds"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/nws-flood-thresholds/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/nws-flood-thresholds"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/nws-flood-thresholds.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 | $0.00050 | $0.01014 |
| Opus 5 | $0.00025 | $0.00507 |
| Sonnet 5 | $0.00010 | $0.00203 |
| Haiku 4.5 | $0.00005 | $0.00101 |
Grade A, and why
nws-flood-thresholds scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
import urllib.request This is a copy
100% identical to nws-flood-thresholds — 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NWS Flood Thresholds Guide
Overview
The National Weather Service (NWS) maintains flood stage thresholds for thousands of stream gages across the United States. These thresholds define when water levels become hazardous.
Data Sources
Option 1: Bulk CSV Download (Recommended for Multiple Stations)
https://water.noaa.gov/resources/downloads/reports/nwps_all_gauges_report.csv
Option 2: Individual Station Pages
https://water.noaa.gov/gauges/<station_id>
Example: https://water.noaa.gov/gauges/04118105
Flood Stage Categories
| Category | CSV Column | Description |
|---|---|---|
| Action Stage | action stage |
Water level requiring monitoring, preparation may be needed |
| Flood Stage (Minor) | flood stage |
Minimal property damage, some public threat. Use this to determine if flooding occurred. |
| Moderate Flood Stage | moderate flood stage |
Structure inundation, evacuations may be needed |
| Major Flood Stage | major flood stage |
Extensive damage, significant evacuations required |
For general flood detection, use the flood stage column as the threshold.
Downloading Bulk CSV
import pandas as pd
import csv
import urllib.request
import io
nws_url = "https://water.noaa.gov/resources/downloads/reports/nwps_all_gauges_report.csv"
response = urllib.request.urlopen(nws_url)
content = response.read().decode('utf-8')
reader = csv.reader(io.StringIO(content))
headers = next(reader)
data = [row[:43] for row in reader] # Truncate to 43 columns
nws_df = pd.DataFrame(data, columns=headers)
Important: CSV Column Mismatch
The NWS CSV has a known issue: header row has 43 columns but data rows have 44 columns. Always truncate data rows to match header count:
data = [row[:43] for row in reader]
Key Columns
| Column Name | Description |
|---|---|
usgs id |
USGS station ID (8-digit string) |
location name |
Station name/location |
state |
Two-letter state code |
action stage |
Action threshold (feet) |
flood stage |
Minor flood threshold (feet) |
moderate flood stage |
Moderate flood threshold (feet) |
major flood stage |
Major flood threshold (feet) |
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 · 124 lines · 50 tokens per session scan A f0a534dad207
nws-flood-thresholds is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 6d ago), licensed MIT. It adds 50 tokens to every session and 1,014 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to nws-flood-thresholds, differing in 0 lines, and is treated as a copy.
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