Health Data Integrator

The night before a doctor's appointment, you spend forty minutes pulling screenshots from Whoop, exporting sleep data from Oura, hunting for last quarter's lab results PDF, and trying to reconstruct what symptoms you mentioned at your last visit. Your doctor gets six minutes with you. You arrive with fragments. The fix is not another health app. It is teaching your AI agent to hold the full picture — across every data source, across every visit — and produce a structured summary before you walk in the door. Health Data Integrator synthesizes inputs from Whoop, Oura, Apple Health exports, lab results PDFs, and doctor visit notes into a single running health timeline. It flags changes that cross configurable thresholds, identifies patterns across sleep, recovery, and lab data, and generates pre-appointment summaries formatted for clinical handoff — not for your own reading, but for a doctor who has six minutes. The skill never interpolates missing data. If a gap exists in your wearable export, it flags the gap and holds the record open rather than estimating. In a health context, a fabricated data point is worse than no data point — it buries the flag you needed to see. What you get: HEALTH_DATA_INTEGRATOR.md — core synthesis protocol and agent instructions. INTAKE_TEMPLATE.md — structured input format for each supported data source (Whoop, Oura, Apple Health, labs, doctor notes). APPOINTMENT_SUMMARY.md — pre-appointment summary template with clinical handoff formatting. TREND_FLAGS.md — configurable threshold and alert logic with default concern boundaries. Requires Apple Health XML export, Whoop or Oura CSV/PDF exports, and lab results as uploaded PDFs.