Configuring Windows Event Logging For Detection
mukul975/Anthropic-Cybersecurity-Skills
Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation.
Detect flood events by comparing water levels to thresholds.
MITAuto-check passed
Install Flood Detection
$ npx skills add benchflow-ai/skillsbench --skill flood-detection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install benchflow-ai/skillsbench flood-detection --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tasks/flood-risk-analysis/environment/skills/flood-detection .claude/skills/flood-detection && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "flood-detection" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/flood-risk-analysis/environment/skills/flood-detection into .claude/skills/flood-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "flood-detection", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/benchflow-ai/skillsbench/tree/main/tasks/flood-risk-analysis/environment/skills/flood-detectionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add benchflow-ai/skillsbench --skill flood-detection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install benchflow-ai/skillsbench flood-detection --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/tasks/flood-risk-analysis/environment/skills/flood-detection .agents/skills/flood-detection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "flood-detection" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/flood-risk-analysis/environment/skills/flood-detection into .agents/skills/flood-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "flood-detection", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add benchflow-ai/skillsbench --skill flood-detection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install benchflow-ai/skillsbench flood-detection --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/tasks/flood-risk-analysis/environment/skills/flood-detection .cursor/skills/flood-detection && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "flood-detection" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/flood-risk-analysis/environment/skills/flood-detection into .cursor/skills/flood-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "flood-detection", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/benchflow-ai/skillsbench.git --path tasks/flood-risk-analysis/environment/skills/flood-detection--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add benchflow-ai/skillsbench --skill flood-detection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install benchflow-ai/skillsbench flood-detection --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/tasks/flood-risk-analysis/environment/skills/flood-detection .gemini/skills/flood-detection && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "flood-detection" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/flood-risk-analysis/environment/skills/flood-detection into .gemini/skills/flood-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "flood-detection", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install benchflow-ai/skillsbench flood-detectionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add benchflow-ai/skillsbench --skill flood-detection -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .github/skills && cp -r skills-src/tasks/flood-risk-analysis/environment/skills/flood-detection .github/skills/flood-detection && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "flood-detection" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/flood-risk-analysis/environment/skills/flood-detection into .github/skills/flood-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "flood-detection", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add benchflow-ai/skillsbench --skill flood-detection -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install benchflow-ai/skillsbench flood-detection --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/tasks/flood-risk-analysis/environment/skills/flood-detection .opencode/skills/flood-detection && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "flood-detection" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/flood-risk-analysis/environment/skills/flood-detection into .opencode/skills/flood-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "flood-detection", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
flood-detection- GitHub stars
- 1.8k
- Token cost
- ~922 tokens
- SKILL.md length
- 219 words
- Files
- 1
- Skills in repo
- 178
- Repo updated
- First seen
- Licence
- MIT
At a glance
Detect flood events by comparing water levels to thresholds.
- Determining if flooding occurred
- SKILL.md covers Overview, Flood Stage Definition, Aggregating Instantaneous Data… and Detecting Flood Days, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Counting flood days
What it does
Flood Detection is an agent skill from benchflow-ai/skillsbench. Detect flood events by comparing water levels to thresholds. Use when determining if flooding occurred, counting flood days, aggregating instantaneous data to daily values, or classifying flood severity.
Its SKILL.md is about 920 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: SkillsBench evaluates how well skills work and how effective agents are at using them. The licence is MIT.
When your agent uses it
- Determining if flooding occurred
- Counting flood days
- Aggregating instantaneous data to daily values
- Classifying flood severity
Example prompts
- “/flood-detection”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 9a1f4dd. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Flood Detection loads about 922 tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 219 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its MIT licence (© benchflow-ai). 219 words, ~922 tokens.
Download SKILL.mdSave it as
.claude/skills/flood-detection/SKILL.md (or your agent's skills folder).- name
- flood-detection
- description
- Detect flood events by comparing water levels to thresholds. Use when determining if flooding occurred, counting flood days, aggregating instantaneous data to daily values, or classifying flood severity.
- license
- MIT
Flood Detection Guide
Overview
Flood detection involves comparing observed water levels against established flood stage thresholds. This guide covers how to process water level data and identify flood events.
Flood Stage Definition
According to the National Weather Service, flood stage is the water level at which overflow of the natural banks begins to cause damage. A flood event occurs when:
water_level >= flood_stage_thresholdAggregating Instantaneous Data to Daily
USGS instantaneous data is recorded at ~15-minute intervals. For flood detection, aggregate to daily maximum:
# df is DataFrame from nwis.get_iv() with datetime index
# gage_col is the column name containing water levels
daily_max = df[gage_col].resample('D').max()Why Daily Maximum?
| Aggregation | Use Case |
|---|---|
max() | Flood detection - captures peak water level |
mean() | Long-term trends - may miss short flood peaks |
min() | Low flow analysis |
Detecting Flood Days
Compare daily maximum water level against flood threshold:
flood_threshold = <threshold_from_nws> # feet
# Count days with flooding
flood_days = (daily_max >= flood_threshold).sum()
# Get specific dates with flooding
flood_dates = daily_max[daily_max >= flood_threshold].index.tolist()Processing Multiple Stations
flood_results = []
for site_id, site_data in all_data.items():
daily_max = site_data['water_levels'].resample('D').max()
threshold = thresholds[site_id]['flood']
days_above = int((daily_max >= threshold).sum())
if days_above > 0:
flood_results.append({
'station_id': site_id,
'flood_days': days_above
})
# Sort by flood days descending
flood_results.sort(key=lambda x: x['flood_days'], reverse=True)Flood Severity Classification
If multiple threshold levels are available:
def classify_flood(water_level, thresholds):
if water_level >= thresholds['major']:
return 'major'
elif water_level >= thresholds['moderate']:
return 'moderate'
elif water_level >= thresholds['flood']:
return 'minor'
elif water_level >= thresholds['action']:
return 'action'
else:
return 'normal'Output Format Examples
Simple CSV Output
import csv
with open('flood_results.csv', 'w', newline='') as f:
writer = csv.writer(f)
writer.writerow(['station_id', 'flood_days'])
for result in flood_results:
writer.writerow([result['station_id'], result['flood_days']])JSON Output
import json
output = {
'flood_events': flood_results,
'total_stations_with_flooding': len(flood_results)
}
with open('flood_report.json', 'w') as f:
json.dump(output, f, indent=2)Common Issues
| Issue | Cause | Solution |
|---|---|---|
| No floods detected | Threshold too high or dry period | Verify threshold values |
| All days show flooding | Threshold too low or data error | Check threshold units (feet vs meters) |
| NaN in daily_max | Missing data for entire day | Check data availability |
Best Practices
- Use daily maximum for flood detection to capture peaks
- Ensure water level and threshold use same units (typically feet)
- Only report stations with at least 1 flood day
- Sort results by flood severity or duration for prioritization
© benchflow-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in tasks/flood-risk-analysis/environment/skills/flood-detection of benchflow-ai/skillsbench.
Open the folder on GitHubat commit 9a1f4dd
Compare with similar skills
Flood Detection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Flood Detection this skillbenchflow-ai/skillsbench | 1.8k | — | ~922 | Automated safety check: Pass | MIT | |
| Configuring Windows Event Logging For Detectionmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Detecting Ntlm Relay With Event Correlationmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~8.7k | Automated safety check: Pass | Apache-2.0 | |
| Detecting Broken Object Property Level Authorizationmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~4k | Automated safety check: Pass | Apache-2.0 | |
| Eventscoreyhaines31/marketingskills | 54k | — | ~3k | Automated safety check: Pass | MIT | |
| Event Sourcing Architectdavila7/claude-code-templates | 32k | 4 repos | ~659 | Automated safety check: Pass | MIT |
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Questions about Flood Detection
What does Flood Detection do?
Detect flood events by comparing water levels to thresholds. Flood Detection is an agent skill from benchflow-ai/skillsbench. Detect flood events by comparing water levels to thresholds.
When should I use Flood Detection?
Flood Detection fits situations like: determining if flooding occurred; counting flood days; aggregating instantaneous data to daily values; classifying flood severity.
How do I install Flood Detection in Claude Code?
Run `npx skills add benchflow-ai/skillsbench --skill flood-detection -a claude-code`. Or copy the skill folder (tasks/flood-risk-analysis/environment/skills/flood-detection in benchflow-ai/skillsbench) into .claude/skills/flood-detection in your project. Claude Code loads it when a task matches its description.
How do I install Flood Detection in Codex?
Run `npx skills add benchflow-ai/skillsbench --skill flood-detection -a codex`. Or copy the skill folder (tasks/flood-risk-analysis/environment/skills/flood-detection in benchflow-ai/skillsbench) into .agents/skills/flood-detection in your project. Codex loads it when a task matches its description.
Can I use Flood Detection in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add benchflow-ai/skillsbench --skill flood-detection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/flood-detection, .gemini/skills/flood-detection, .github/skills/flood-detection and .opencode/skills/flood-detection in your project.
What does Flood Detection need to run?
SKILL.md names no scripts, command-line tools or credentials: Flood Detection is instructions for the agent only. Our summary lists: Python 3.
Does Flood Detection access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Flood Detection safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Flood Detection use?
Flood Detection is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Flood Detection use?
About 922 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Flood Detection?
Skills that share tags, products or a category with Flood Detection: Configuring Windows Event Logging For Detection (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Detecting Ntlm Relay With Event Correlation (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Detecting Broken Object Property Level Authorization (mukul975/Anthropic-Cybersecurity-Skills, 34k stars) and Events (coreyhaines31/marketingskills, 54k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Flood Detection?
benchflow-ai (a GitHub organization) maintains it in benchflow-ai/skillsbench, which has 1,832 GitHub stars. The repository holds 178 skills in this directory. The repository was last updated on July 23, 2026.
Source: benchflow-ai/skillsbench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.