threejs-gameplay-systems

threejs-gameplay-systems is a skill for Codex from valkor-ai/loom. It costs 89 tokens per session (1,125 once invoked), scanned A, original, Apache-2.0.

A guide for creating and improving playable browser games with Three.js, a JavaScript library for 3D graphics. It covers the game loop, player input, cameras, collisions, physics, scoring, levels, and game feel.

In plain words
What is it for?
It helps scaffold a Vite and TypeScript game, design levels and encounters, add entities and controls, and tune gameplay systems.
Why use it?
It gives the project structure and design steps needed to turn a game idea into a working playable slice instead of disconnected features.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit It helps scaffold a Vite and TypeScript game, design levels and encounters, add entities and controls, and tune gameplay systems.

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Install with agentmods
npx agentmods add skills/valkor-ai/loom/threejs-gameplay-systems
About the project

Loom is a delivery harness that guides coding agents through defining, planning, implementing, checking, repairing, previewing, and handing off software changes. It is used with Claude Code, Codex, OpenCode, and other coding agents when work must be continued or inspected across sessions. The catalogue skills, hooks, commands, instructions, and plugin extend or operate this workflow.

valkor-ai/loom · 1,251 stars · on GitHub

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 valkor-ai/loom --skill threejs-gameplay-systems
Clone the repo
git clone --depth 1 https://github.com/valkor-ai/loom

Made for: Codex.

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 threejs-gameplay-systems

README.md
[![agentmods](https://agentmods.dev/badge/skills/valkor-ai/loom/threejs-gameplay-systems/github.svg)](https://agentmods.dev/skills/valkor-ai/loom/threejs-gameplay-systems)
Your own site
<a href="https://agentmods.dev/skills/valkor-ai/loom/threejs-gameplay-systems"><img src="https://agentmods.dev/badge/skills/valkor-ai/loom/threejs-gameplay-systems/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 threejs-gameplay-systems

Your own site · 80×15
<a href="https://agentmods.dev/skills/valkor-ai/loom/threejs-gameplay-systems"><img src="https://agentmods.dev/badge/skills/valkor-ai/loom/threejs-gameplay-systems.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,125 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.
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 $0.00089 $0.01125
Opus 5.5 $0.00036 $0.00450
Sonnet 5.5 $0.00018 $0.00225
Haiku 4.5 $0.00009 $0.00112

Measured 1mo ago against content hash a58960f58072, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

threejs-gameplay-systems 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 1mo ago.

The scan reads SKILL.md. This mod also ships 22 executable files (assets/threejs-vite-game/playwright.config.ts, assets/threejs-vite-game/scripts/inspect-threejs-canvas.mjs, assets/threejs-vite-game/src/core/InputController.ts, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/shared/loom/skills/threejs/threejs-gameplay-systems/SKILL.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Three.js Gameplay Systems

Create or evolve a playable browser game loop with clear ownership, responsive controls, deterministic update order, and a space that shapes player decisions.

Resolve <this-skill-dir> and local references from the actual loaded skill file; resolve sibling skills beside it before using runner-discovered alternatives.

References

File Read it when
references/game-feel.md tuning feel, juice, impact, hitstop, screenshake, or claiming polished gameplay
references/genre-design.md designing levels, arenas, tracks, waves, holes, puzzles, encounters, or difficulty curves
references/physics-engine-selection.md adding or changing physics, collision-heavy gameplay, vehicles, rolling balls, character controllers, sensors, moving platforms

Start here

python3 <this-skill-dir>/scripts/create_threejs_game.py ./my-game

Copies assets/threejs-vite-game/, rewrites the project name, and gives the game its own visual test and canvas inspector. --force overwrites an existing directory.

Design first

For broad game creation or a substantial design change, write three short artifacts or update the existing ones. A narrow mechanic fix uses the existing design and preserves unrelated systems:

Design brief. Player promise (the fantasy in one sentence) · target feeling · primary verb · secondary verbs · what the player repeats every 5–30 seconds · what changes across 1–5 minutes · how they lose, learn, and restart · what is rewarded and what creates risk · what a better player does differently · how the next decision is communicated · non-goals for this slice.

Core loop contract. Player does [verb] to achieve [objective] while [pressure] creates risk; success gives [reward], failure causes [cost/retry]. Then prove each clause in code: the verb is mapped to real input, the objective is visible in world or HUD, pressure exists inside the first playable minute, reward changes state rather than only visuals, failure teaches what happened, and restart is fast enough to invite another attempt.

Read the full file on GitHub · 65 lines

Files

What ships with it

32 files 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. 1mo ago First seen · 65 lines · 89 tokens per session scan A a58960f58072

Subscribe to this mod's changes

threejs-gameplay-systems is a skill published in the GitHub repository valkor-ai/loom (1,251 stars, last pushed 3d ago), licensed Apache-2.0. It adds 89 tokens to every session and 1,125 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-15.

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