health-data: Скилл для анализа данных здоровья

--- name: health-data description: Query Apple Health SQLite database for vitals, activity, sleep, and workouts. Supports Markdown, JSON, and FHIR R4 output formats. This skill should be used when analyzing health metrics, generating health reports, answering questions about fitness or sleep patterns, or exporting health data in standard formats. --- # Apple Health Data Query Skill Query and analyze health data from the local SQLite database containing 6.3M+ records across 43 health metrics. ## Database Location ``` ~/data/health.db ``` ## Query Methods ### 1. Python Script (Recommended for Common Queries) Use `scripts/health_query.py` for pre-built queries with automatic formatting: ```bash # Daily summary python ~/.claude/skills/health-data/scripts/health_query.py --format markdown daily --date 2025-11-29 # Weekly trends python ~/.claude/skills/health-data/scripts/health_query.py --format json weekly --weeks 4 # Sleep analysis python ~/.claude/skills/health-data/scripts/health_query.py --format fhir sleep --days 7 # Latest vitals python ~/.claude/skills/health-data/scripts/health_query.py vitals # Activity rings python ~/.claude/skills/health-data/scripts/health_query.py --format json activity --days 30 # Workout history python ~/.claude/skills/health-data/scripts/health_query.py workouts --days 30 --type Running # Custom SQL python ~/.claude/skills/health-data/scripts/health_query.py --format json query "SELECT * FROM workouts LIMIT 5" ``` **Output formats:** `markdown`, `json`, `fhir`, `ascii` ### 2. Direct SQL (For Custom/Ad-hoc Queries) For flexible queries, run SQL directly against the database. See `references/schema.md` for table structures and query templates. ```bash sqlite3 ~/data/health.db "SELECT AVG(value) FROM health_records WHERE record_type LIKE '%HeartRate%' AND start_date LIKE '2025-11%'" ``` ## Pre-built Queries ### Daily Health Summary Get today's key metrics: ```bash python ~/.claude/skills/health-data/scripts/health_query.py daily ``` Returns: steps, calories, heart rate (avg/min/max), exercise minutes, distance, activity ring status. ### Weekly Trends Compare week-over-week performance: ```bash python ~/.claude/skills/health-data/scripts/health_query.py weekly --weeks 4 ``` Returns: average daily steps, resting HR, exercise minutes, workout count per week. ### Sleep Analysis Analyze sleep patterns: ```bash python ~/.claude/skills/health-data/scripts/health_query.py sleep --days 14 ``` Returns: nightly duration, sleep stages (Core, Deep, REM), average sleep hours. ### Latest Vitals Get most recent vital readings: ```bash python ~/.claude/skills/health-data/scripts/health_query.py vitals ``` Returns: Heart Rate, HRV, Resting HR, Blood Oxygen, Respiratory Rate with timestamps. ### Activity Rings Track ring completion: ```bash python ~/.claude/skills/health-data/scripts/health_query.py activity --days 30 ``` Returns: daily ring values/goals, completion percentages, perfect day count. ### Workout History Review exercise sessions: ```bash python ~/.claude/skills/health-data/scripts/health_query.py workouts --days 30 --type Running ``` Returns: workout type, duration, distance, calories, summary by type. ## Output Formats ### Markdown (default) Human-readable tables and lists. Best for reports and summaries. ### JSON Structured data for programmatic use: ```json { "date": "2025-11-29", "metrics": { "steps": 8542, "active_calories": 450.5, "heart_rate": {"avg": 72.3, "min": 52, "max": 145} } } ``` ### FHIR R4 Healthcare interoperability format. Outputs as FHIR Bundle with Observation resources using LOINC codes. See `references/fhir_mappings.md` for code mappings. ### ASCII Terminal-friendly output with bar charts and statistics: ``` ============================================================ DAILY SUMMARY - 2025-11-29 ============================================================ METRICS ---------------------------------------- steps 2620 active_calories 234.5 heart_rate avg: 67.5 min: 52 max: 108 ACTIVITY RINGS ---------------------------------------- move [███████░░░░░░░░░░░░░] 36.7% (238/650) exercise [░░░░░░░░░░░░░░░░░░░░] 0.0% (0/35) stand [████████████████████] 100.0% (10/10) ``` ## Common SQL Patterns For ad-hoc queries, use these patterns from `references/schema.md`: **Heart rate by hour (circadian pattern):** ```sql SELECT strftime('%H', start_date) as hour, ROUND(AVG(value), 1) as avg_hr FROM health_records WHERE record_type = 'HKQuantityTypeIdentifierHeartRate' AND value BETWEEN 40 AND 200 GROUP BY hour ORDER BY hour; ``` **Steps per day this month:** ```sql SELECT DATE(start_date) as day, SUM(value) as steps FROM health_records WHERE record_type = 'HKQuantityTypeIdentifierStepCount' AND start_date >= DATE('now', 'start of month') GROUP BY day ORDER BY day; ``` **Sleep quality (deep + REM hours):** ```sql SELECT DATE(start_date) as night, ROUND(SUM(duration_minutes)/60.0, 1) as quality_hours FROM sleep_sessions WHERE sleep_stage IN ('Deep', 'REM') GROUP BY night ORDER BY night DESC LIMIT 14; ``` **Workout summary:** ```sql SELECT REPLACE(workout_type, 'HKWorkoutActivityType', '') as type, COUNT(*) as count, ROUND(SUM(duration_minutes)) as total_min FROM workouts WHERE start_date >= DATE('now', '-30 days') GROUP BY type ORDER BY count DESC; ``` ## Record Types Available The database contains 43 health metric types including: **Vitals:** Heart Rate, HRV, Resting HR, Blood Oxygen, Respiratory Rate, Blood Pressure **Activity:** Steps, Distance, Active Calories, Basal Calories, Flights Climbed, Exercise Time, Stand Time **Mobility:** Walking Speed, Step Length, Walking Asymmetry, Stair Speed, Walking Steadiness **Body:** Weight, BMI, Body Fat % **Audio:** Environmental Noise, Headphone Exposure **Other:** VO2 Max, Time in Daylight, UV Exposure ## Data Coverage - **Records:** 6.3M+ measurements - **Date range:** 2015-10-13 to present - **Workouts:** 1,435 sessions - **Sleep sessions:** 40,514 records - **Activity days:** 1,875 daily summaries ## Resources ### scripts/ - `health_query.py` - Main query tool with Markdown/JSON/FHIR output ### references/ - `schema.md` - Database schema, record type mappings, SQL query templates - `fhir_mappings.md` - LOINC codes and FHIR R4 templates ## Troubleshooting **Database not found:** Ensure `~/data/health.db` exists. Run the import script from `/Users/server/apple_health_export/`: ```bash python import_health.py --status ``` **No data for date range:** Check available date range: ```sql SELECT MIN(start_date), MAX(start_date) FROM health_records; ``` **Outlier values:** Filter physiologically valid ranges (e.g., heart rate 40-200 bpm): ```sql WHERE value BETWEEN 40 AND 200 ```