health-dashboard

name	health-dashboard
description	Aggregate health data from Oura (sleep/readiness), Apple Health (activity/vitals), wger/Fitbod (strength and nutrition), and Peloton (class/performance detail) into a unified health dashboard. Use for daily check-ins, weekly health reviews, or trend analysis across health domains.

Health Dashboard

Data Sources

Domain	Server	Key Data
Sleep & Recovery	oura	Sleep score, stages, HRV, readiness, temperature
Activity & Vitals	apple-health	Steps, active energy, heart rate, weight, blood pressure
Workouts	wger + Fitbod CSV + peloton	Exercise logs, sets/reps/weight, workout frequency, class metadata, interval structure
Nutrition	wger	Calorie intake, macros (protein, carbs, fat)
Genome & Clinical	health-graph	PGx recommendations, curated assertions, labs, coverage context
Drug Reference	medical	FDA drug info, PubMed literature, clinical guidelines, WHO stats
Document Provenance	paperless	Retrieval and verification of source documents only

Daily Health Check

Step 1: Sleep (Oura)

Pull last night's data:

• Sleep score and contributors (total sleep, efficiency, latency, timing)
• Sleep stages: deep, REM, light, awake — duration and percentages
• HRV: overnight average, trend vs 14-day baseline
• Resting heart rate: value and trend
• Body temperature deviation

Step 2: Readiness (Oura)

• Readiness score and contributors
• Recovery index
• Activity balance (not too much, not too little)
• Flag if readiness < 70 — recommend lighter activity day

Step 3: Activity (Apple Health)

Query via SQL (DuckDB):

• Steps: today vs 7-day average
• Active energy burned
• Exercise minutes
• Stand hours (if tracked)
• Resting heart rate (if tracked by Apple Watch)

Step 4: Workout Status (wger + Fitbod + Peloton)

• Pull wger first:
  • get_workout_sessions
  • get_workout_log
  • get_routines
• If wger is empty or stale, parse the latest Fitbod export for weight training only:
  • fitbod_parse_csv for last lifting date, exercise list, sets/reps/load, and recent strength volume
  • fitbod_preview_mapping or fitbod_list_exercise_aliases only when you need confidence for exercise mapping or muscle-group rollups
  • fitbod_import_csv with dry_run=true is allowed when you need a date-bounded workout slice, coverage verification, or an unresolved-exercise queue without writing to wger
  • Only treat muscle-group rollups as reliable when trailing-365d weighted mapping coverage is at least 90%
  • Never persist a Fitbod import during normal dashboard/check-in runs unless the user explicitly wants an import or repair workflow
  • Exclude Fitbod cardio rows from reporting when a matching Peloton workout exists with the same local start time and duration; treat those rows as synced duplicates
  • Prefer session-level lifting detail like Pull Up 3 x 11 or Dumbbell Bicep Curl 3 x 8 @ 13.6 kg
• If recent Peloton workouts exist:
  • peloton_get_workouts
  • peloton_get_workout_detail for the latest or most notable session to capture class title, instructor, duration, difficulty, tracked metrics, and muscle emphasis
  • peloton_get_performance_graph when interval structure, pace targets, or compliance adds signal
  • Treat Peloton as the cardio source of truth
• Use Apple Health workout summaries as fallback coverage when direct sources are unavailable
• Report:
  • Last workout: date, type, duration
  • Days since last workout — flag if > 3 days
  • This week's workout count vs target
  • Notable direct-source workout detail when it changes the interpretation

Step 5: Nutrition (wger)

• Yesterday's intake: total calories, protein, carbs, fat
• Protein target check: aim for 1g per lb bodyweight (or user's target)

Weekly Health Review

Aggregate 7 days of data:

## Weekly Health Review — [Date Range]

### Sleep
- Avg score: X/100 | Avg duration: Xh Xm
- Avg HRV: X ms (trend: ↑/↓/→)
- Best night: [date] | Worst: [date]
- Consistency: bedtime variation ± X min

### Activity
- Avg daily steps: X (target: Y)
- Total active energy: X kcal
- Exercise days: X/7

### Workouts
- Sessions completed: X
- Muscle groups covered: [list]
- Progressive overload: [any PRs or weight increases]
- Peloton highlights: [class mix, instructor, difficulty, interval structure]

### Nutrition
- Avg daily calories: X
- Avg protein: Xg (target: Yg)
- Avg macro split: P%/C%/F%

### Recovery
- Avg readiness: X/100
- Rest days taken: X
- HRV trend: [improving/declining/stable]

### Recommendations
1. [Specific, actionable recommendation based on data]
2. ...

Trend Analysis

For longer-term analysis (30d, 90d):

• Sleep quality trend (are scores improving?)
• HRV baseline trend (proxy for fitness/recovery)
• Weight trend (if tracked)
• Workout frequency and volume progression
• Correlation: sleep quality vs next-day readiness vs workout performance

Guidelines

• All metrics from MCP tool calls — never estimate or fabricate
• Prefer direct Fitbod CSV for strength detail and Peloton MCP for cardio detail; use Apple Health workout summaries as fallback coverage
• If Fitbod mapping coverage is below 90% weighted coverage on the trailing 365-day window, report exercise-level detail and explicitly mark muscle-group rollups as partial
• Avoid persisting fitbod_import_csv during standard dashboard/review flows unless the task is explicitly an import or sync workflow
• health-graph is authoritative for genome/clinical availability and recommendation context
• If genome-informed guidance is included in a dashboard or weekly summary, make it answer "so what?" directly:
  • Lead with the plain-English takeaway for the subject
  • State whether anything needs to happen now; if not, say that explicitly
  • State what future decision this could affect, if any
  • Avoid unexplained jargon such as metabolizer labels, star alleles, or rsids unless translated immediately
  • For Tier 3 and Tier 4 items, state clearly that they are watchlist or research context and should not drive treatment or behavior changes on their own
• paperless is document-only in this workflow; do not use it as a proxy for genomic data availability
• Flag anomalies: HRV drop > 15% from baseline, sleep score < 60, readiness < 60
• Recovery-first: recommend rest when readiness is low
• When reviewing medications or supplements, use medical.search_drugs for drug interaction context and medical.get_drug_details for dosing reference
• Not medical advice: flag concerning trends but recommend doctor consultation