sleep-analyzer

name: sleep-analyzer description: "Analyzes sleep data to compute efficiency, quality score (0-100), and stage distribution. Detects patterns like irregular schedules, chronic short sleep, and weekend oversleep. Use when the user provides sleep records, imports Apple Health data, or asks about sleep quality." version: 1.0.0 user-invocable: false allowed-tools: Read, Grep, Glob, Write, Edit metadata: {"openclaw":{"emoji":"😴","category":"health"}}

Sleep Analyzer

Records and analyzes sleep data: computes sleep efficiency and a composite quality score (0-100), evaluates stage distribution, detects multi-day patterns, cross-references caffeine data, and supports Apple Health CSV import.

Capabilities

1. Sleep Data Recording

Extract from natural-language input:

2. Sleep Efficiency

Sleep Efficiency = (TST / TIB) * 100%

• TIB (Time In Bed) = waketime - bedtime (minutes)
• SOL (Sleep Onset Latency) = sleep_onset - bedtime (default 15 min)
• TST (Total Sleep Time) = TIB - SOL - WASO

3. Composite Sleep Score (0-100)

Score = Efficiency(40%) + Duration(30%) + Consistency(20%) + Latency(10%)

3.1 Efficiency Sub-score (weight 40%)

Use linear interpolation within adjacent bands.

3.2 Duration Sub-score (weight 30%)

3.3 Consistency Sub-score (weight 20%)

Standard deviation of bedtime and waketime over the last 7 days:

Time-to-minutes conversion: use midnight (00:00) as zero; times before midnight are negative (e.g. 23:00 = -60). Average the bedtime SD and waketime SD. If fewer than 7 days available, compute on existing data and note the limitation.

3.4 Latency Sub-score (weight 10%)

4. Sleep Stage Analysis

Normal ranges (adult, 8 h sleep):

Flags: Deep < 13%, REM < 20%, Awake > 10%, Light > 65%.

5. Pattern Detection (7-30 days)

6. Caffeine Correlation

Read caffeine-tracker data from health-memory. Analyze:

• Bedtime residual vs. sleep onset latency
• Daily total caffeine vs. sleep efficiency
• Last caffeine time vs. sleep quality
• Describe correlation direction (positive/negative/none).

7. Apple Health CSV Import

Required columns (case-insensitive): bedtime, waketime. Optional columns: duration, deep, rem, light, awake.

Steps: read CSV, compute efficiency and score per row, batch-write to health-memory, output summary (count, date range, average score).

Output Format

Single-Night Report

## Sleep [sleep-analyzer · HH:MM]

### Overview
- Bedtime: 23:00 -> Waketime: 07:00
- Time in bed: 8h 0min
- Sleep onset latency: ~20 min
- Total sleep time: 7h 25min
- Awakenings: 1 (15 min)

### Efficiency
- Efficiency: 92.7%
- Rating: Excellent

### Sleep Score: 83 / 100
| Dimension | Raw | Sub-score | Weight | Weighted |
|-----------|-----|-----------|--------|----------|
| Efficiency | 92.7% | 90 | 40% | 36.0 |
| Duration | 7h25min | 100 | 30% | 30.0 |
| Consistency | SD=45min | 50 | 20% | 10.0 |
| Latency | 20min | 70 | 10% | 7.0 |
| **Total** | | | | **83.0** |

### Stages (if available)
| Stage | Duration | % | Normal Range | Status |
|-------|----------|---|-------------|--------|
| Light | 3h 55min | 53% | 50-60% | Normal |
| Deep | 1h 20min | 18% | 13-23% | Normal |
| REM | 1h 45min | 24% | 20-25% | Normal |
| Awake | 25min | 5% | <5% | Slightly high |

### Insights
- Excellent efficiency; fell asleep quickly
- Schedule consistency needs improvement (SD 45 min)
- Recommend fixing bedtime around 23:00

Weekly Summary

## Weekly Sleep Summary (MM-DD ~ MM-DD)

### Key Metrics
| Metric | This Week | Last Week | Change |
|--------|-----------|-----------|--------|
| Score | 78 | 72 | +6 |
| Duration | 7h 10min | 6h 45min | +25min |
| Efficiency | 89% | 86% | +3% |
| Latency | 18min | 25min | -7min |

### Daily Detail
| Date | Bedtime | Waketime | Duration | Efficiency | Score |
|------|---------|----------|----------|------------|-------|
| Mon | 23:15 | 07:00 | 7h15min | 91% | 85 |
| Tue | 00:30 | 07:30 | 6h30min | 84% | 68 |
| ... | | | | | |

### Patterns
- [Notice] Late bedtimes on Tue and Fri (>00:00) lowered consistency score
- [Good] Average deep sleep 17%, within normal range
- [Suggestion] Fix bedtime at 23:00 to improve consistency

### Caffeine Correlation (if data available)
- Average daily caffeine: 220 mg
- Average last-caffeine time: 15:30
- High-caffeine days (>300 mg) avg score: 71 vs low-caffeine days: 82

Data Persistence

Daily File (memory/health/daily/YYYY-MM-DD.md)

## Sleep [sleep-analyzer · HH:MM]
- Score: 83/100
- Duration: 7h 25min (23:00-07:00)
- Efficiency: 92.7%
- Latency: 20min
- Awakenings: 1 (15min)
- Stages: Light 53%, Deep 18%, REM 24%, Awake 5%

Item File (memory/health/items/sleep.md)

---
item: sleep
unit: score (0-100)
updated_at: YYYY-MM-DDTHH:MM:SS
---

# Sleep Records

## Recent Status
- Latest: Score 83, 7h25min, Efficiency 92.7% (YYYY-MM-DD)
- 7-day average score: 78
- 7-day average duration: 7h 10min
- Trend: Improving

## History
| Date | Score | Duration | Efficiency | Latency | Bedtime | Waketime | Notes |
|------|-------|----------|------------|---------|---------|----------|-------|
| 2026-03-10 | 83 | 7h25min | 92.7% | 20min | 23:00 | 07:00 | |
| 2026-03-09 | 71 | 6h30min | 85.4% | 25min | 00:15 | 07:00 | Late night |

Write Steps

1. Glob memory/health/daily/ for the target date file; create if absent.
2. Read the daily file.
3. Grep ## .* \[sleep-analyzer · for existing section.
4. Edit to replace existing section, or insert before ## Health Files if new.
5. Update frontmatter updated_at.
6. Read memory/health/items/sleep.md (create if absent).
7. Update ## Recent Status (including 7-day averages) and prepend new row to ## History.
8. Remove rows older than 90 days.

Formulas and Reference Data

Trend Determination

Linear regression on last 7 days of scores:

• Slope > 1: Improving
• Slope < -1: Declining
• Otherwise: Stable

Standard Deviation (Consistency)

SD = sqrt( (1/N) * SUM[(x_i - mean)^2] )

Alerts and Safety

Medical Disclaimer

This skill is for health reference only and does not constitute medical advice. It does not diagnose sleep disorders or replace polysomnography (PSG).

Consult a doctor if:

• Sleep onset latency consistently > 45 min
• Frequent awakenings (>= 5 per night)
• Partner reports loud snoring or breathing pauses
• Severe daytime sleepiness affecting work or driving safety
• Sleep problems persist > 1 month without improvement