| name | health-coach |
| description | Comprehensive personal health management: body composition tracking, meal photo analysis with clinical-grade nutritional breakdown, exercise logging, medical lab interpretation (blood panels, FeNO, urinalysis, etc.), supplement guidance, and periodic progress reports. Use when: (1) analyzing food photos or meal descriptions for calories/macros, (2) interpreting medical lab results or health markers, (3) tracking body metrics (weight, body fat, waist circumference), (4) planning exercise routines with injury considerations, (5) generating weekly/monthly health reports, (6) setting up health reminders (meals, movement, supplements, sleep), (7) any question about nutrition, exercise science, or wellness optimization. |
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! 🙏
