physics-rendering-expert
Real-time rope/cable physics using Position-Based Dynamics (PBD), Verlet integration, and constraint solvers. Expert in quaternion math, Gauss-Seidel/Jacobi solvers, and tangling detection. Activate on 'rope simulation', 'PBD', 'Position-Based Dynamics', 'Verlet', 'constraint solver', 'quaternion', 'cable dynamics', 'cloth simulation', 'leash physics'. NOT for fluid dynamics (SPH/MPM), fracture simulation (FEM), offline cinematic physics, molecular dynamics, or general game physics engines (use Unity/Unreal built-ins).
Best use case
physics-rendering-expert is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Real-time rope/cable physics using Position-Based Dynamics (PBD), Verlet integration, and constraint solvers. Expert in quaternion math, Gauss-Seidel/Jacobi solvers, and tangling detection. Activate on 'rope simulation', 'PBD', 'Position-Based Dynamics', 'Verlet', 'constraint solver', 'quaternion', 'cable dynamics', 'cloth simulation', 'leash physics'. NOT for fluid dynamics (SPH/MPM), fracture simulation (FEM), offline cinematic physics, molecular dynamics, or general game physics engines (use Unity/Unreal built-ins).
Teams using physics-rendering-expert should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/physics-rendering-expert/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How physics-rendering-expert Compares
| Feature / Agent | physics-rendering-expert | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Real-time rope/cable physics using Position-Based Dynamics (PBD), Verlet integration, and constraint solvers. Expert in quaternion math, Gauss-Seidel/Jacobi solvers, and tangling detection. Activate on 'rope simulation', 'PBD', 'Position-Based Dynamics', 'Verlet', 'constraint solver', 'quaternion', 'cable dynamics', 'cloth simulation', 'leash physics'. NOT for fluid dynamics (SPH/MPM), fracture simulation (FEM), offline cinematic physics, molecular dynamics, or general game physics engines (use Unity/Unreal built-ins).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Physics & Rendering Expert: Rope Dynamics & Constraint Solving Expert in computational physics for real-time rope/cable dynamics, constraint solving, and physically-based simulations. ## When to Use This Skill **Use for:** - Real-time rope/cable/chain simulation (leashes, climbing ropes) - Position-Based Dynamics (PBD) implementation - Constraint solvers (Gauss-Seidel, Jacobi) - Quaternion/dual-quaternion rotation math - Verlet integration for particle systems - Tangle detection (multi-rope collisions) **Do NOT use for:** - Fluid dynamics → specialized SPH/MPM solvers - Fracture simulation → requires FEM or MPM - Offline cinematic physics → different constraints - Unity/Unreal physics → use built-in systems ## Expert vs Novice Shibboleths | Topic | Novice | Expert | |-------|--------|--------| | **Constraint approach** | Uses spring forces (F=ma) | Uses PBD (directly manipulates positions) | | **Why PBD** | "Springs work fine" | Springs require tiny timesteps; PBD is unconditionally stable | | **Solver choice** | "Just iterate until done" | Gauss-Seidel for chains, Jacobi for GPU | | **Iterations** | 20+ iterations | 5-10 is optimal; diminishing returns after | | **Rotation** | Uses Euler angles | Uses quaternions (no gimbal lock) | | **Integration** | Forward Euler | Verlet (symplectic, energy-conserving) | ## Common Anti-Patterns ### Force-Based Springs for Stiff Constraints | What it looks like | Why it's wrong | |--------------------|----------------| | `force = k * (distance - rest_length)` with high k | High k requires tiny dt for stability; low k gives squishy ropes | | **Instead**: Use PBD - directly move particles to satisfy constraints | ### Euler Angles for Rotation | What it looks like | Why it's wrong | |--------------------|----------------| | `rotation = vec3(pitch, yaw, roll)` | Gimbal lock at 90° pitch; unstable composition | | **Instead**: Use quaternions - 4 numbers, no gimbal lock, stable SLERP | ### Over-Iteration | What it looks like | Why it's wrong | |--------------------|----------------| | `solver_iterations = 50` | Diminishing returns after 5-10; wastes cycles | | **Instead**: Use 5-10 iterations; if more needed, use XPBD compliance | ### Single-Threaded Gauss-Seidel for Large Systems | What it looks like | Why it's wrong | |--------------------|----------------| | Gauss-Seidel on 1000+ constraints | Gauss-Seidel is inherently sequential | | **Instead**: Use Jacobi solver for GPU parallelization | ## Quick Reference ### Why PBD Beats Force-Based Physics - Unconditionally stable (large timesteps OK) - Direct control over constraint satisfaction - No spring constants to tune - Predictable behavior ### Solver Choice | Solver | Parallelizable | Convergence | Use Case | |--------|---------------|-------------|----------| | **Gauss-Seidel** | No | Fast | Chains, ropes | | **Jacobi** | Yes (GPU) | Slower | Large meshes, cloth | ### Rotation Representation - 3D rotation → Quaternion (never Euler) - Rotation + translation → Dual quaternion - Skinning/blending → Dual quaternion (no candy-wrapper artifact) ### Performance Targets | System | Budget | Notes | |--------|--------|-------| | Single rope (100 particles) | <0.5ms | 5 iterations sufficient | | Three-dog leash (60 particles) | <0.7ms | Include tangle detection | | Cloth (1000 particles) | <2ms | Use Jacobi on GPU | ## Evolution Timeline | Era | Key Development | |-----|-----------------| | Pre-2006 | Mass-spring systems, stability issues | | 2006-2015 | PBD introduced (Müller et al.), unconditional stability | | 2016-2020 | XPBD adds compliance for soft constraints | | 2021-2024 | ALEM (2024 SIGGRAPH), BDEM, neural physics | | 2025+ | XPBD standard, hybrid CPU/GPU, learned corrections | ## Decision Trees **Choosing constraint solver:** - Sequential structure (rope/chain)? → Gauss-Seidel - Large parallel system (cloth/hair)? → Jacobi (GPU) - Need soft constraints? → XPBD with compliance **Choosing integration:** - Position-only needed? → Basic Verlet - Need velocity for forces? → Velocity Verlet - High accuracy required? → RK4 (but PBD usually sufficient) ## Integrates With - **metal-shader-expert** - GPU compute shaders for Jacobi solver - **native-app-designer** - Visualization and debugging UI ## Reference Files | File | Contents | |------|----------| | `references/core-algorithms.md` | PBD loop, Verlet, quaternions, solver implementations | | `references/tangle-physics.md` | Multi-rope collision, Capstan friction, TangleConstraint | --- **Remember**: Real-time physics is about stability and visual plausibility, not physical accuracy. PBD with 5-10 iterations at 60fps looks great and runs fast.
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