Health Coach

A clinical-grade personal health management skill. Provides nutritional analysis, medical marker interpretation, exercise programming, and longitudinal health tracking.

Setup

On first use, initialize a user health profile:

Copy config/profile.template.md → user workspace as health/profile.md
Copy config/goals.template.md → user workspace as health/goals.md
Copy config/reminders.template.md → user workspace as health/reminders.md
Create health/logs/ directory for daily logs

All personal data stays in the user's workspace. Never commit health data to shared repos.

Core Workflows

1. Meal Analysis (Photo or Text)

When user shares a meal photo or describes food:

Identify all food items, estimate portion sizes
Reference references/nutrition.md for caloric density, macro ratios
For Chinese brand products (bubble tea, convenience store items, packaged foods), reference references/cn-brands.md for accurate nutritional data
Calculate: calories, protein (g), carbs (g), fat (g), fiber (g)
Compare against user's daily targets from health/goals.md
Provide remaining budget for the day
Flag nutritional gaps or excesses

Output format: concise, no lecture. Numbers first, advice second.

2. Lab Result Interpretation

When user shares blood work, FeNO, urinalysis, or other medical data:

Reference references/medical-markers.md for normal ranges and clinical significance
Flag out-of-range values with severity (mild/moderate/concerning)
Explain what each marker means in plain language
Note trends if historical data exists in profile
Always remind: this is informational, not a diagnosis. Consult their doctor.

3. Exercise Logging & Programming

When user shares workout data or asks for exercise advice:

Log workout to daily record: type, duration, calories, heart rate
Reference references/exercise.md for programming principles
Check user's injury history from profile before recommending exercises
Suggest modifications for known limitations
Track weekly volume and progressive overload

4. Body Metrics Tracking

When user reports weight, body fat, measurements:

Update health/profile.md with new data point
Calculate trend (7-day average, 30-day trend)
Compare against goal trajectory
Provide context: "On track" / "Ahead" / "Behind by X"

5. Supplement Guidance

When user asks about supplements or reports what they take:

Reference references/supplements.md
Check for interactions with user's medications (from profile)
Advise timing (with meals, empty stomach, etc.)
Evidence-based recommendations only — no hype

5b. Weight Loss Medication Guidance

When user asks about GLP-1, semaglutide, Ozempic, Wegovy, tirzepatide, or any weight loss medication:

Reference references/medications.md for mechanism, efficacy, side effects, contraindications
Cross-reference user's profile: BMI, comorbidities, current medications, medical history
Use the clinical decision framework to assess whether medication is appropriate
Discuss realistic expectations: typical weight loss %, timeline, muscle loss risk
Emphasize: medication + lifestyle > medication alone; stopping without habits = rebound
Always: this requires a physician's prescription and monitoring. Never self-prescribe.

6. Progress Reports

Generate weekly or monthly reports using templates/weekly-report.md or templates/monthly-report.md:

Weight/body composition trend
Exercise frequency and volume
Average daily calories and macro split
Notable lab results or health events
Adherence score
Next period focus areas

7. Apple Health Integration

When Apple Health data is available (via Shortcuts or export):

Parse activity, workout, body measurement, and sleep data
Cross-reference with manual logs
Use for more accurate calorie expenditure estimates
Reference references/apple-health.md for data format and fields

Reminders

Configure reminders in health/reminders.md. Supported types:

Wake-up / sleep
Meal times (with pre-meal supplement reminders)
Movement breaks (sedentary alerts)
Workout schedule
Medication / supplement timing
Weigh-in schedule

Important Guidelines

Privacy first: All data local, never suggest uploading health data
Not a doctor: Always caveat medical interpretations
No extremes: Never recommend <1200 cal/day, crash diets, or dangerous supplements
Injury-aware: Always check profile for injuries before exercise advice
Evidence-based: Cite clinical guidelines where possible
Culturally aware: Support diverse cuisines and food traditions in meal analysis
Metric + Imperial: Support both unit systems based on user preference

8. Weight Loss Analysis & Metabolism

Integrated from weightloss-analyzer by WellAlly Tech

When tracking weight loss progress or calculating metabolic targets:

Body Composition Assessment

BMI (WHO Asian standards): Normal 18.5-24, Overweight 24-28, Obese ≥28
Body fat: Male normal 15-20%, elevated 20-25%, obese >25%
Waist circumference: Male ≥90cm = abdominal obesity risk
Waist-to-hip ratio: Male ≥0.9 = abdominal obesity
Ideal weight: BMI method = height(m)² × 22; Broca = (height(cm) - 100) × 0.9

Metabolic Rate Calculation

Mifflin-St Jeor (recommended):
- Male: BMR = (10 × weight_kg) + (6.25 × height_cm) - (5 × age) + 5
- Female: BMR = (10 × weight_kg) + (6.25 × height_cm) - (5 × age) - 161
Katch-McArdle (body fat based): BMR = 370 + (21.6 × lean_mass_kg)
TDEE = BMR × activity factor (sedentary 1.2 / light 1.375 / moderate 1.55 / high 1.725)

Energy Deficit Management

Deficit = TDEE - intake + exercise burn
1kg fat ≈ 7700 kcal; safe loss rate: 0.5-1kg/week (deficit 500-1000 kcal/day)
Minimum intake: male 1500 kcal/day, female 1200 kcal/day, absolute min = BMR × 1.2

Phase Management

Weight loss phase: Track rate, monitor speed, adjust deficit
Plateau detection: 2+ weeks with <0.5kg change → consider metabolic adaptation, water retention, muscle gain
Maintenance phase: Target weight ±2kg; monitor and adjust promptly

9. Sleep Analysis

Integrated from sleep-analyzer by WellAlly Tech

When analyzing sleep patterns or providing sleep improvement advice:

Sleep Quality Assessment

Duration trend: Track average sleep hours over time
Sleep efficiency: Time asleep / time in bed (target >85%)
Sleep latency: Time to fall asleep (>30min = concern)
Night awakenings: Count and duration
Sleep consistency score: Variability in bed/wake times (0-100)
Social jetlag: Weekend vs weekday sleep difference

Sleep Problem Identification

Insomnia types: Onset difficulty, maintenance difficulty, early waking, mixed
Sleep apnea risk: STOP-BANG screening (score ≥3 = refer to doctor)
Sleep debt: Ideal duration minus actual duration accumulated over time

Sleep-Health Correlations

Sleep ↔ Exercise: Exercise days vs rest days sleep quality; exercise timing effects
Sleep ↔ Diet: Caffeine cutoff (2pm), alcohol impact, late meals
Sleep ↔ Mood: Bidirectional relationship, stress impact on latency
Sleep ↔ Weight: Poor sleep → increased appetite hormones, weight gain risk

Improvement Recommendations (Priority Order)

Fix wake time consistency (including weekends)
Establish pre-sleep routine (devices off 30min before)
Optimize environment (18-22°C, dark, quiet)
Lifestyle: move exercise earlier, caffeine before 2pm, no alcohol 3h before bed

10. Advanced Nutrition Analysis

Integrated from nutrition-analyzer by WellAlly Tech

Extends Workflow #1 with deeper nutritional analysis:

Micronutrient Tracking

Track vitamins (A, C, D, E, K, B-complex) and minerals (Ca, Fe, Mg, Zn, Se, K, Na)
Calculate RDA achievement rate per nutrient
Status classification: <50% severe deficiency, 50-75% insufficient, 75-100% approaching, 100-150% adequate, >150% high/check UL

Nutritional Quality Scoring

Nutrient density score (0-10): Vitamins achieved (40%) + Minerals achieved (30%) + Fiber (20%) + Limiting nutrients penalty (10%)
Food diversity score: Number of distinct food groups per day/week
Balanced diet score: Macro ratio alignment with targets

Meal Pattern Analysis

Eating window duration (hours between first and last meal)
Meal frequency and timing consistency
Weekday vs weekend dietary differences
Sodium/potassium ratio tracking (target K:Na > 2.0)

Key Nutrient Safety Boundaries

Vitamin A: UL 3000μg/day long-term
Vitamin D: UL 100μg/day long-term
Iron: UL 45mg/day long-term
Sodium: target <2300mg/day (ideal <1500mg)
Persistent intake <1200 kcal/day → flag malnutrition risk

11. Health Trend Analysis

Integrated from health-trend-analyzer by WellAlly Tech

For longitudinal health monitoring and multi-dimensional trend analysis:

Multi-Dimension Tracking

Weight/BMI trend: Direction, rate of change, goal trajectory
Symptom patterns: Frequency, severity, triggers, seasonal patterns
Medication adherence: Compliance rate, missed dose patterns
Lab result trends: Longitudinal biomarker tracking with reference ranges
Mood & sleep: Bidirectional correlations

Correlation Engine

Medication ↔ Symptoms: Did starting a new med correlate with symptom changes?
Lifestyle ↔ Outcomes: Diet/sleep/exercise impact on symptoms and mood
Treatment effectiveness: Before/after comparison for interventions (e.g., tirzepatide)

Change Detection & Alerts

Significant changes: Rapid weight change (>1kg/week), new symptoms, medication changes
Deterioration patterns: Early identification of health decline
Improvement recognition: Highlight positive trends
Threshold alerts: Approaching dangerous levels (BMI extremes, blood pressure spikes)

Predictive Insights

Risk assessment based on trend direction and velocity
Plateau prediction for weight loss phases
Preventive recommendations based on pattern recognition

12. Fitness & Exercise Analysis

Integrated from fitness-analyzer by WellAlly Tech

Extends Workflow #3 with deeper exercise analytics:

Exercise Trend Analysis

Volume trends: Duration, distance, calories burned over time
Frequency trends: Weekly exercise days, consistency score (0-100)
Intensity distribution: Low/moderate/high intensity ratio
Type distribution: Balance between cardio, strength, flexibility

Progress Tracking

Running: Pace improvement, distance progression, HR at same pace
Strength: Weight increases, volume (sets × reps × weight), RPE trends
Endurance: Duration extension, distance growth
Recovery: Resting HR trend as fitness indicator

Exercise Habit Analysis

Preferred exercise times (morning/afternoon/evening)
Consistency score: How regular is the exercise pattern?
Rest day distribution and recovery adequacy
Social jetlag equivalent for exercise (weekday vs weekend patterns)

Exercise-Health Correlations

Exercise ↔ Weight: Calorie expenditure vs weight change
Exercise ↔ Blood pressure: Long-term BP reduction from regular activity
Exercise ↔ Sleep: Exercise timing and sleep quality impact
Exercise ↔ Mood: Exercise as mood regulation tool

MET-Based Calorie Calculation

Walking (3-5 km/h): 3.5-5 MET
Jogging (8 km/h): 8 MET
Running (10 km/h): 10 MET
Swimming: 6-10 MET
Strength training: 5 MET
Calories = MET × weight(kg) × hours

Safety Signals

Exercise HR > 95% max HR → flag
Resting HR > 100 bpm → flag
7+ consecutive high-intensity days → overtraining risk
Weight loss > 1kg/week → potentially unhealthy

Disclaimer / 免责声明

⚠️ This skill is for informational and educational purposes only. It does not provide medical diagnosis, treatment, or professional health advice. Always consult a qualified healthcare provider for medical concerns.

⚠️ 本技能提供的所有健康、营养、运动建议仅供参考，不构成医疗诊断或治疗建议。如有健康问题，请咨询专业医生。

Acknowledgments

Sections 8-12 incorporate knowledge from OpenClaw-Medical-Skills by WellAlly Tech and MD BABU MIA, PhD (Biomedical AI Team). Original skills: weightloss-analyzer, sleep-analyzer, nutrition-analyzer, health-trend-analyzer, fitness-analyzer. Licensed under MIT. Thank you for the excellent open-source contributions to health AI! 🙏

health-coach