Health Coach

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:

1. Copy config/profile.template.md → user workspace as health/profile.md
2. Copy config/goals.template.md → user workspace as health/goals.md
3. Copy config/reminders.template.md → user workspace as health/reminders.md
4. 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:

1. Identify all food items, estimate portion sizes
2. Reference references/nutrition.md for caloric density, macro ratios
3. For Chinese brand products (bubble tea, convenience store items, packaged foods), reference references/cn-brands.md for accurate nutritional data
4. Calculate: calories, protein (g), carbs (g), fat (g), fiber (g)
5. Compare against user's daily targets from health/goals.md
6. Provide remaining budget for the day
7. 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:

1. Reference references/medical-markers.md for normal ranges and clinical significance
2. Flag out-of-range values with severity (mild/moderate/concerning)
3. Explain what each marker means in plain language
4. Note trends if historical data exists in profile
5. 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:

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

4. Body Metrics Tracking

When user reports weight, body fat, measurements:

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

5. Supplement Guidance

When user asks about supplements or reports what they take:

1. Reference references/supplements.md
2. Check for interactions with user's medications (from profile)
3. Advise timing (with meals, empty stomach, etc.)
4. 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:

1. Reference references/medications.md for mechanism, efficacy, side effects, contraindications
2. Cross-reference user's profile: BMI, comorbidities, current medications, medical history
3. Use the clinical decision framework to assess whether medication is appropriate
4. Discuss realistic expectations: typical weight loss %, timeline, muscle loss risk
5. Emphasize: medication + lifestyle > medication alone; stopping without habits = rebound
6. 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):

1. Parse activity, workout, body measurement, and sleep data
2. Cross-reference with manual logs
3. Use for more accurate calorie expenditure estimates
4. 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)

1. Fix wake time consistency (including weekends)
2. Establish pre-sleep routine (devices off 30min before)
3. Optimize environment (18-22°C, dark, quiet)
4. 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! 🙏