whoop-2

Whoop

Query health metrics from the Whoop API and generate interactive HTML charts.

Setup (first time only)

1. Create a Whoop Developer App

1. Go to developer-dashboard.whoop.com
2. Sign in with your Whoop account credentials
3. Create a Team if prompted (any name works)
4. Click Create App (or go to apps/create)
5. Fill in:
   • App name: anything (e.g., "Clawdbot")
   • Scopes: select ALL: read:recovery, read:cycles, read:workout, read:sleep, read:profile, read:body_measurement
   • Redirect URI: http://localhost:9876/callback
6. Click Create — you'll get a Client ID and Client Secret

2. Authenticate

Run the OAuth login flow with your credentials:

python3 scripts/whoop_auth.py login \
  --client-id YOUR_CLIENT_ID \
  --client-secret YOUR_CLIENT_SECRET

This opens a browser for Whoop authorization. Log in and approve access. Tokens are stored in ~/.clawdbot/whoop-tokens.json and auto-refresh.

Check status: python3 scripts/whoop_auth.py status

Fetching Data

Use scripts/whoop_data.py to get JSON data:

# Sleep (last 7 days default)
python3 scripts/whoop_data.py sleep --days 14

# Recovery scores
python3 scripts/whoop_data.py recovery --days 30

# Strain/cycles
python3 scripts/whoop_data.py cycles --days 7

# Workouts
python3 scripts/whoop_data.py workouts --days 30

# Combined summary with averages
python3 scripts/whoop_data.py summary --days 7

# Custom date range
python3 scripts/whoop_data.py sleep --start 2026-01-01 --end 2026-01-15

# User profile / body measurements
python3 scripts/whoop_data.py profile
python3 scripts/whoop_data.py body

Output is JSON to stdout. Parse it to answer user questions.

Generating Charts

Use scripts/whoop_chart.py for interactive HTML visualizations:

# Sleep analysis (performance + stages)
python3 scripts/whoop_chart.py sleep --days 30

# Recovery bars (color-coded green/yellow/red)
python3 scripts/whoop_chart.py recovery --days 30

# Strain & calories trend
python3 scripts/whoop_chart.py strain --days 90

# HRV & resting heart rate trend
python3 scripts/whoop_chart.py hrv --days 90

# Full dashboard (all 4 charts)
python3 scripts/whoop_chart.py dashboard --days 30

# Save to specific file
python3 scripts/whoop_chart.py dashboard --days 90 --output ~/Desktop/whoop.html

Charts open automatically in the default browser. They use Chart.js with dark theme, stat cards, and tooltips.

Answering Questions

User asks	Action
"How did I sleep?"	whoop_data.py summary --days 7, report sleep performance + hours
"How's my recovery?"	whoop_data.py recovery --days 7, report scores + trend
"Show me a chart for the last month"	whoop_chart.py dashboard --days 30
"Is my HRV improving?"	whoop_data.py recovery --days 30, analyze trend
"How much did I train this week?"	whoop_data.py workouts --days 7, list activities

Key Metrics

• Recovery (0-100%): Green ≥67%, Yellow 34-66%, Red <34%
• Strain (0-21): Daily exertion score based on HR
• Sleep Performance: Actual sleep vs. sleep needed
• HRV (ms): Higher = better recovery, track trend over time
• RHR (bpm): Lower = better cardiovascular fitness

Health Analysis

When the user asks about their health, trends, or wants insights, use references/health_analysis.md for:

• Science-backed interpretation of HRV, RHR, sleep stages, recovery, strain, SpO2
• Normal ranges by age and fitness level
• Pattern detection (day-of-week effects, sleep debt, overtraining signals)
• Actionable recommendations based on data
• Red flags that suggest medical consultation

Analysis workflow

1. Fetch data: python3 scripts/whoop_data.py summary --days N
2. Read references/health_analysis.md for interpretation framework
3. Apply the 5-step analysis: Status → Trends → Patterns → Insights → Flags
4. Always include disclaimer that this is not medical advice

References

• references/api.md — endpoint details, response schemas, pagination
• references/health_analysis.md — science-backed health data interpretation guide