physics-tuning

physics-tuning is a skill for Claude Code from gamedev-skills/awesome-gamedev-agent-skills. It costs 83 tokens per session (1,774 once invoked), scanned A, original, Apache-2.0.

A guide to making game motion stable and responsive by tuning simulation timing, gravity, mass, drag, collisions, and other physics settings. It applies across game engines rather than teaching one engine's API.

In plain words
What is it for?
Use it to separate fixed physics updates from changing display-frame updates and to tune collision detection, solver settings, sleeping, and collision layers.
Why use it?
It helps diagnose jitter, objects passing through walls, unstable stacks, and movement that feels too floaty, sticky, or delayed.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the disciplines plugin — 15 skills shipped together , and of gamedev

Good fit Use it to separate fixed physics updates from changing display-frame updates and to tune collision detection, solver settings, sleeping, and collision layers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gamedev-skills/awesome-gamedev-agent-skills/physics-tuning
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add gamedev-skills/awesome-gamedev-agent-skills --skill physics-tuning
Clone the repo
git clone --depth 1 https://github.com/gamedev-skills/awesome-gamedev-agent-skills

Made for: Claude Code.

Or install disciplines, the plugin that ships this one along with the rest of its 15 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for physics-tuning

README.md
[![agentmods](https://agentmods.dev/badge/skills/gamedev-skills/awesome-gamedev-agent-skills/physics-tuning/github.svg)](https://agentmods.dev/skills/gamedev-skills/awesome-gamedev-agent-skills/physics-tuning)
Your own site
<a href="https://agentmods.dev/skills/gamedev-skills/awesome-gamedev-agent-skills/physics-tuning"><img src="https://agentmods.dev/badge/skills/gamedev-skills/awesome-gamedev-agent-skills/physics-tuning/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for physics-tuning

Your own site · 80×15
<a href="https://agentmods.dev/skills/gamedev-skills/awesome-gamedev-agent-skills/physics-tuning"><img src="https://agentmods.dev/badge/skills/gamedev-skills/awesome-gamedev-agent-skills/physics-tuning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,774 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 8 Aug 2026
  • Snyk pass 8 Aug 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00083 $0.01774
Opus 5 $0.00042 $0.00887
Sonnet 5 $0.00017 $0.00355
Haiku 4.5 $0.00008 $0.00177

Measured 13d ago against content hash faa9a50d465c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

physics-tuning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/disciplines/physics-tuning/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Physics tuning

Most "bad physics" is not a bug in the engine — it's a mismatch between the fixed-timestep simulation and the variable-rate render loop, or untuned mass/drag/CCD/layer settings. This skill covers the engine-neutral knobs that make physics stable and responsive; pair it with godot-physics or unity-physics for the concrete APIs.

When to use

  • Use when motion jitters, objects pass through walls (tunneling), stacks explode, or movement feels floaty/sticky/laggy.
  • Use to decide what goes in the fixed (physics) step vs the render frame, and how to interpolate between them.
  • Use to tune gravity, mass, drag, restitution, solver iterations, sleeping, and collision layers/masks.

When not to use: for an engine's exact physics nodes/components and collision callbacks, use godot-physics or unity-physics. For movement decisions (when to jump, AI steering) use input-systems and game-ai. For platformer jump-feel specifics like coyote time/jump buffering, that's input/ controller territory — see input-systems and the platformer genre.

Core workflow

  1. Run physics on a fixed timestep. Simulate at a constant rate (e.g. 50–60 Hz). A fixed dt makes the simulation deterministic-ish and stable; a variable dt makes integration and collisions inconsistent.
  2. Put physics work in the physics callback, not the render frame. Apply forces/velocities and read collisions in the fixed step (FixedUpdate / _physics_process), using that step's dt.
  3. Interpolate rendering between physics ticks. The render frame rate ≠ the physics rate, so smoothly interpolate transforms toward the latest physics state, or enable the engine's Rigidbody interpolation, to remove visible stutter.
  4. Tune the body, not the scene. Set mass for relative weight, drag for damping, gravity scale per object, and restitution/friction via materials.
  5. Stop tunneling with CCD on small/fast bodies; cap maximum velocity.
  6. Stabilize stacks/joints with more solver iterations, sane mass ratios, and sleeping for resting bodies.
  7. Verify by feel and stress test. Play at low and high frame rates; throw fast objects at thin walls; stack and shove bodies. Report what you observed.

Read the full file on GitHub · 150 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 150 lines · 83 tokens per session scan A faa9a50d465c

Subscribe to this mod's changes

physics-tuning is a skill published in the GitHub repository gamedev-skills/awesome-gamedev-agent-skills (952 stars, last pushed 2d ago), licensed Apache-2.0. It adds 83 tokens to every session and 1,774 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.