◆ Posecode

Kinematic motion as text. Mermaid gave LLMs a way to draw diagrams.
Posecode gives them a way to show movement — exercises, physiotherapy, posture —
as a tiny human-readable language that renders to an animated 3D figure in the browser.

▶ Live playground · Language spec · Examples · MCP server

pelvis: hinge — deadlift

knees: flex 95 — squat

shoulders: abduct 90 — lateral raise

Ask an LLM to explain a push-up and it can only give you prose or a flat image. The model knows the biomechanics ("elbows flex, shoulders abduct on the descent") — it just has no syntax to express it that a renderer can read. Diffusion-based text-to-motion models exist, but they're heavy, expensive, and give you no fine control over the anatomical phases.

Posecode takes the opposite, lightweight approach (see the research):

• The LLM writes a small .posecode document — semantic phases, not 3D matrices.
• A client-side parser + Three.js renderer animates it. Generation is a fraction of a cent of text; rendering runs at 60fps on a phone.
• Every angle is hard-clamped to a healthy range of motion, so a model hallucinating "knee flex 200°" can't produce an anatomically impossible joint.

posecode exercise "Body-weight squat"
  rig humanoid
  pose start = standing

  step "Descend" 1.6s ease-in-out:
    hips: flex 80
    knees: flex 95
    ankles: dorsiflex 14
    ground-lock: feet
    cue "Sit the hips back, chest proud, knees track over the toes"

  step "Drive up" 1.2s ease-out:
    hips: flex 0
    knees: flex 0
    ankles: dorsiflex 0
    ground-lock: feet
    cue "Drive through the heels to stand tall"

  repeat 8

npm install
npm run dev      # opens the playground (Vite) at http://localhost:5173
npm test         # parser + renderer + eval test suites
npm run eval     # fidelity scorecard: geometric invariants over every example

In the playground: pick an example, watch it animate, edit the text live, and hit Copy LLM prompt to get a system prompt that teaches ChatGPT/Claude to write Posecode for you — or wire up the MCP server so your agent authors, validates, and renders movements natively.

Two safety layers ship with the language:

• ROM clamping — every angle is hard-clamped to healthy range-of-motion tables before rendering; a hallucinated knee: flex 200 renders at its ceiling with a warning, never an impossible joint.
• Fidelity evals — posecode-eval re-runs the real parser → FK → ground-lock pipeline headlessly and scores geometric invariants ("a deadlift pitches the torso ≥ 50° with vertical shins"). Every example must pass every invariant in CI.

The protocol and both libraries are MIT-licensed — the open core. See spec/SPEC.md for the full language and spec/llm-authoring.md for the authoring prompt. For where Posecode spreads fastest and the per-domain go-to-market plan, see docs/market-research.md; for the engine roadmap, ROADMAP.md.

✅ Single-person movement across fitness, physio, desk, dance, education & rehab · Mermaid-style DSL · ROM safety clamping (authored and IK-solved angles) · forward kinematics · ground-lock and ROM-constrained reach-to-target IK · hip-hinge · lying/seated poses · scene props (chair/wall/bar) · a single-DOF hand rig · live playground.

⏳ Deferred: two-person / partner movements + collision detection, deeper props (load, bands, rings), multi-joint fingers, FBX/GLB export, hosted SaaS editor and the expert-verified motion marketplace.

This project follows a design study, "Kinematic Motion Definition Protocols for Large Language Models", which argues for a semantic DSL over diffusion models, specifies ROM-based safety constraints from clinical normative data, and lays out the open-core commercialization path. The spec cross-references its sections (§4 DSL, §5 biomechanics, §6 client rendering, §7 strategy).

⚠️ Posecode's range-of-motion values are general literature data, not medical advice. Consult a qualified professional for physiotherapy or exercise prescription.