rzen
669ecf1259
Library detail screens now lead with the user's recorded machine settings (per-split when they disagree, empty-state card for machine-based entries) and append the weight progression chart. Starter seeds mark machine exercises with an empty machineSettings list so the settings UI lights up before first use. The figure rig gains a frontal body profile for face-on machines, props that can ride mid joints (knees/elbows), and an alternating four-frame Bird Dog loop. Claude-Session: https://claude.ai/code/session_01LEoff8bXGBS83tK1c55Mf7
Exercise Library
Reference material for exercises the app knows about — one folder per exercise, named exactly as the exercise appears in the app.
Each entry contains:
info.md— the details, always in this order: a one-line summary, quick facts (Category, Type, Targets, Prescription), then Setup, Execution, Cues, Common Mistakes, and Progression (easier → harder — get strong by making the move harder, not by endless reps).motion.json— the exercise scripted as key frames of joint angles on the shared rig (proportions in the library-levelbody.json), with IK pins for planted hands/feet and tween timings. This is the canonical source for all visuals and for the in-app animation planned for the lower half of the exercise screen.- Generated from it by
render.py(never hand-edited):frames/frame-N.svg(one per key frame),preview.gif(the tweened loop), andvisual.svg(the primary frame, for static contexts).
The rig and the visual language — right limbs dark / left limbs light with an
embedded R/L legend, nose tick for facing, teal on the working parts, timing
that encodes tempo, plus figure profiles, flipping, and theming — are defined
in SYSTEM.md, along with the motion.json schema and rendering
instructions.
The library lives at the repo root, deliberately outside the app targets' source folders, and is not bundled into the app yet — the in-app presentation format is still being worked out.