Can AI replace Fitbod?

Build a personal replacement for Fitbod in an empty repository.
Use React Native with Expo, TypeScript, SQLite, and HealthKit or Health Connect only when explicitly enabled; do not offer alternative stacks.
The core loop is: log workouts and recovery notes, plan moderate routines from user-selected equipment, and show trends without diagnosing, shaming, or enforcing restrictive goals.
Make the first run work locally with one documented command.
Store all user data locally by default and make export straightforward.
Put secrets in .env, ship .env.example, and never commit credentials.
Create optional logs for activity, sleep, mood, energy, and personal notes with editable units.
Let the user build moderate routines and rest days without weight-loss targets, punishment, or competitive pressure.
Request health-platform permissions per data type and work fully without granting them.
Show weekly patterns and consistency with neutral language and no diagnostic or body-image judgments.
Add reminders that can be muted, data export, account-free local use, and full deletion.
Include a clear statement that the app is not medical care and should not replace qualified advice.
Include clear empty, loading, success, and recoverable error states.
Add input validation, safe filenames, and graceful handling of unavailable APIs.
Write focused tests for the core transformation and one end-to-end happy path.
Create a README with setup, architecture, permissions, data location, and backup steps.
Do not add accounts, billing, telemetry, analytics, or a hosted control plane.
Deliberately leave out medical diagnosis or treatment.
Deliberately leave out extreme exercise or restrictive-eating coaching.
Deliberately leave out wearable hardware, human coaching, and a large social network.
Finish by running the tests and listing the exact commands used.