Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze CGM blood glucose data from Nightscout. Use this skill when asked about current glucose levels, blood sugar trends, A1C estimates, time-in-range statistics, glucose variability, or diabetes management insights.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill provides tools for fetching and analyzing Continuous Glucose Monitor (CGM) data from Nightscout.
Always run tests before and after modifying cgm.py:
cd <skill-path>
python -m pytest tests/ -q # Quick check (255+ tests)
python -m pytest tests/ --cov=scripts # With coverage
Run the cgm.py script from this skill's scripts/ directory:
python <skill-path>/scripts/cgm.py <command> [options]
Where <skill-path> is the location where this skill is installed (e.g., ~/.copilot/skills/nightscout-cgm, .github/skills/nightscout-cgm, or .claude/skills/nightscout-cgm).
| Command | Description |
|---|---|
current | Get the latest glucose reading |
analyze [--days N] | Analyze CGM data (default: 90 days) |
report [--days N] [--open] | Generate interactive HTML report with charts |
compare --period1 P1 --period2 P2 | Compare two time periods side-by-side |
alerts [--days N] | Get trend alerts for recurring patterns |
refresh [--days N] | Fetch latest data from Nightscout |
patterns [--days N] | Find interesting patterns (best/worst times, problem areas) |
query [options] | Query with filters (day of week, time range) |
day <date> [options] | View all readings for a specific date |
worst [options] | Find your worst days for glucose control |
chart [options] | Terminal visualizations (heatmap, sparkline, day chart) |
pump | Get current pump status (IOB, COB, predicted glucose) * |
treatments [--hours N] | Get recent treatments (boluses, temp basals, carbs) * |
profile | Get pump profile settings (basal rates, ISF, carb ratios) * |
* Pump commands require Loop, OpenAPS, or similar closed-loop system. The skill auto-detects pump capabilities on first use. CGM-only users won't see errors—commands simply report that pump data isn't available.
Generate a comprehensive, self-contained HTML report with interactive charts:
--days N - Number of days to include (default: 90)--output PATH - Custom output path (default: nightscout_report.html)--open - Open report in browser after generatingAuto-Sync: Reports automatically sync from Nightscout if local data is more than 30 minutes old.
Report Features:
View detailed readings for a specific date:
day <date> - Date can be 'today', 'yesterday', '2026-01-16', or 'Jan 16'--hour-start H - Start hour for time window (0-23)--hour-end H - End hour for time window (0-23)Find your worst days ranked by peak glucose:
--days N - Number of days to search (default: 21)--hour-start H - Start hour for time window (0-23)--hour-end H - End hour for time window (0-23)--limit N - Number of worst days to show (default: 5)The query command supports flexible filtering:
--days N - Number of days to analyze (default: 90)--day NAME - Filter by day of week (e.g., Tuesday, or 0-6 where 0=Monday)--hour-start H - Start hour for time window (0-23)--hour-end H - End hour for time window (0-23)The chart command creates terminal visualizations:
--sparkline - Compact trend line using Unicode blocks (▁▂▃▄▅▆▇█)--hours N - Hours of data for sparkline (default: 24)--date DATE - Specific date for sparkline (e.g., today, yesterday, 2026-01-16)--hour-start H - Start hour for sparkline time window (0-23)--hour-end H - End hour for sparkline time window (0-23)--heatmap - Weekly grid showing time-in-range by day and hour--day NAME - Hourly breakdown for a specific day of week--color - Use ANSI colors (for direct terminal, not inside Copilot)These commands require a closed-loop system (Loop, OpenAPS, AndroidAPS, etc.) uploading to Nightscout. The skill auto-detects pump capabilities—CGM-only users won't be bothered with errors.
pump - Get current pump/loop status:
treatments [--hours N] - Get recent treatments:
profile - Get pump profile settings:
# Get current glucose
python scripts/cgm.py current
# Generate interactive HTML report (opens in browser)
python scripts/cgm.py report --days 90 --open
# Analyze last 30 days
python scripts/cgm.py analyze --days 30
# Find patterns automatically (best/worst times, problem areas)
python scripts/cgm.py patterns
# What happened yesterday during lunch (11am-2pm)?
python scripts/cgm.py day yesterday --hour-start 11 --hour-end 14
# Find my worst lunch days in the last 3 weeks
python scripts/cgm.py worst --days 21 --hour-start 11 --hour-end 14
# What happens on Tuesdays after lunch?
python scripts/cgm.py query --day Tuesday --hour-start 12 --hour-end 15
# How are my overnight numbers on weekends?
python scripts/cgm.py query --day Saturday --hour-start 22 --hour-end 6
python scripts/cgm.py query --day Sunday --hour-start 22 --hour-end 6
# Morning analysis across all days
python scripts/cgm.py query --hour-start 6 --hour-end 10
# Show sparkline of last 24 hours (compact visual trend)
python scripts/cgm.py chart --sparkline --hours 24
# Show sparkline for a specific date and time range (with colors)
python scripts/cgm.py chart --date yesterday --hour-start 11 --hour-end 15 --color
# Show heatmap of time-in-range by day/hour
python scripts/cgm.py chart --heatmap
# Show hourly breakdown for a specific day
python scripts/cgm.py chart --day Saturday
# Generate interactive HTML report (opens in browser)
python scripts/cgm.py report --days 90 --open
# Compare two time periods
python scripts/cgm.py compare --period1 "last 7 days" --period2 "previous 7 days"
python scripts/cgm.py compare --period1 "this week" --period2 "last week"
# Get trend alerts (recurring patterns)
python scripts/cgm.py alerts --days 30
# Refresh data from Nightscout
python scripts/cgm.py refresh
With the pattern analysis capabilities, you can ask natural questions like:
Set the NIGHTSCOUT_URL environment variable to your Nightscout API endpoint:
# Linux/macOS
export NIGHTSCOUT_URL="https://your-nightscout-site.com/api/v1/entries.json"
# Windows PowerShell
$env:NIGHTSCOUT_URL = "https://your-nightscout-site.com/api/v1/entries.json"
# Windows (persistent)
[Environment]::SetEnvironmentVariable("NIGHTSCOUT_URL", "https://your-nightscout-site.com/api/v1/entries.json", "User")
The script will not run without this environment variable configured.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
日本語の概要は準備中です。原文の説明を表示しています。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
日本語の概要は準備中です。原文の説明を表示しています。
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
日本語の概要は準備中です。原文の説明を表示しています。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
日本語の概要は準備中です。原文の説明を表示しています。