← 返回
数据分析 Key

Whoop

Access Whoop wearable health data (sleep, recovery, strain, HRV, workouts) and generate interactive charts. Use when the user asks about sleep quality, recovery scores, strain levels, HRV trends, workout data, or wants health visualizations/graphs from their Whoop band.
获取Whoop可穿戴健康数据(睡眠、恢复、负荷、HRV、锻炼)并生成互动图表。当用户询问睡眠质量、恢复得分、负荷水平、HRV趋势、锻炼数据,或需要其Whoop手环的健康可视化图表时使用。
rodrigouroz
数据分析 clawhub v1.1.0 1 版本 99451.1 Key: 需要
★ 4
Stars
📥 2,819
下载
💾 77
安装
1
版本
#latest

概述

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 asksAction
-------------------
"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

版本历史

共 1 个版本

  • v1.1.0 当前
    2026-03-28 13:02 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

data-analysis

A股量化 AkShare

mbpz
A股量化数据分析工具,基于AkShare库获取A股行情、财务数据、板块信息等。用于回答关于A股股票查询、行情数据、财务分析、选股等问题。
★ 162 📥 59,674
data-analysis

Stock Analysis

udiedrichsen
{"answer":"基于雅虎财经数据,分析股票与加密货币。支持投资组合管理、自选股预警、股息分析、8维评分、热门趋势扫描及传闻/早期信号探测。适用于股票分析、持仓追踪、财报异动、加密监控、热门股追踪或提前发掘非主流传闻。"}
★ 269 📥 56,891
data-analysis

Excel / XLSX

ivangdavila
创建、检查和编辑 Microsoft Excel 工作簿及 XLSX 文件,支持可靠的公式、日期、类型、格式、重算及模板保留功能。
★ 366 📥 139,963