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! 🙏