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sleep-bundle-skill

Analyze athlete sleep architecture, respiratory issues, and recovery metrics from HealthAutoExport JSON data.

Updated Aug 27, 2026
Search Tags:#sleep analysis#athlete#sleep architecture#respiratory forensics#recovery metrics#illness warnings
One-click install
npx skills add https://github.com/JJDevPro/senpai-ai-chat --skill sleep-bundle-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sleep-bundle-skill
Source: https://github.com/JJDevPro/senpai-ai-chat/tree/main/.claude/skills/sleep-bundle-skill
Command: npx skills add https://github.com/JJDevPro/senpai-ai-chat --skill sleep-bundle-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides in-depth sleep analysis for athletes, offering a detailed sleep architecture, respiratory forensics, recovery metrics, illness warnings, and correlation analysis.

Core Features & Use Cases

  • Sleep Architecture: Analyzes sleep duration, efficiency, deep sleep, and REM sleep.
  • Respiratory Forensics: Examines respiratory rate, breathing disturbances, and oxygen saturation.
  • Recovery Metrics: Assesses heart rate variability and wrist temperature for recovery analysis.
  • Illness Warnings: Identifies early signs of illness or discomfort.
  • Correlation Analysis: Correlates sleep quality with pollen levels, casein consumption, and other factors.
  • Use Case: Athletes can use this Skill to gain insights into their sleep patterns and make informed decisions about their training and recovery.

Quick Start

Analyze the sleep data for the past two nights using the 'sleep-bundle-skill'.

Frequently Asked Questions about sleep-bundle-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze sleep architecture and recovery metrics from HealthAutoExport data?▼

Respiratory forensics examines respiratory rate, breathing disturbances, and oxygen saturation within HealthAutoExport JSON data to detect anomalies and identify early illness warnings for athletes.

Can I correlate sleep quality with external factors like pollen levels or diet?▼

Illness warnings are identified by detecting early signs of discomfort through anomalies in respiratory rate, breathing disturbances, oxygen saturation, and heart rate variability during sleep analysis.

Does this sleep analysis approach work for non-athletes?▼

This sleep analysis is specifically tailored for athletes, focusing on recovery metrics, training decisions, and performance optimization, though the underlying HealthAutoExport data parsing can assess general sleep architecture.

What data format do I need to run a comprehensive sleep analysis?▼

Comprehensive sleep analysis requires HealthAutoExport JSON data containing sleep duration, respiratory rate, heart rate variability, and wrist temperature metrics to execute the Python scripts for structured output generation.

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