Squatcat

Training sessions on the iPhone: a programme planned on a calendar, each session played step by step with pause and resume, then its summary.

State: On 12 Oct 2026, the date of the last commit, the app plays an eight-week programme with 81 cat animations validated by its author, and its final interface has been picked; on 16 Oct it was renamed Squatcat, formerly Ron-Ron. Nothing is published. m

commits per week, 12 weeks · 39 in the last 7 days · as of 14 Oct

Runs on: iPhone, portrait, iOS 17 or later; not on the App Store
Built with: Swift 6 and SwiftUI, a Swift package for the training logic, XcodeGen; no third-party library
Data: Local only: no account, no server, no network call, no health framework
Code: Private, local repository

Known limits

It is a prototype, and its name and identifiers are provisional. m
The exercise content is a draft, and the animations are drawings checked by eye, not a technical validation of the exercises. m
Voice guidance with the screen locked is experimental: tried for 45 seconds only. m
It has not been used for a real week, and it gives no safety guidance yet. m

16 Oct rename
Ron-Ron, the training-session prototype, is renamed Squatcat. m
12 Oct decision
After building eight interface directions on one engine, the author picked a daily comic-strip home with a sun-shaped timer as the final interface. m
10 Oct rename
The training-session prototype gets its name, Ron-Ron. m
10 Oct milestone
All 81 cat animations were validated one by one by the author over five review passes, after automatic measures and a three-gate protocol replaced eyeballing, and are bundled in the app. m
10 Oct decision
Of five features proposed from a research dossier, four were adopted and built the same day, adjusting or setting aside today's session, logging activity done without the app, an easier entry level and a comeback after ten days, and the safety notice was deferred. m
09 Oct decision
After testing a puppet rig, a video model and generated poses on the same squat, the cat's movement is settled as two to five generated poses per exercise, set on the feet, with 81 animations planned. m
07 Oct measure
Three open voice models read the same eight phrases of the app and a transcription check found 4, 11 and 56 percent of errors; Qwen3-TTS was kept as the coach voice, in two versions of 325 phrases each. m