renderoni: Skill for Claude Code

.agents/skills/prompt-to-scene/SKILL.md

prompt-to-scene is a skill for Claude Code, Codex from elemarin/renderoni. It costs 54 tokens per session (1,918 once invoked), scanned A, original, MIT.

A workflow for turning a game description, and optionally a reference image, into a Renderoni 3D scene. It creates a compact scene inventory, reconstructs unique visual objects, and mounts them in the game.

In plain words
What is it for?
Use it to create prompt-to-game or image-to-scene workflows, generate reusable object factories, assemble scene inventories, and add gameplay using Renderoni presets.
Why use it?
It keeps the scene description small and organized instead of putting an entire game into one large code file. It also separates visual objects from gameplay components such as players, physics, and win conditions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is elemarin/renderoni's own configuration. It tells Claude Code and Codex how to work on renderoni itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything renderoni configures →

Reuse

Borrowing it

Nothing to install: this file belongs to elemarin/renderoni. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/elemarin/renderoni/main/.agents/skills/prompt-to-scene/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/elemarin/renderoni

Made for: Claude Code, 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 prompt-to-scene

README.md
[![agentmods](https://agentmods.dev/badge/skills/elemarin/renderoni/prompt-to-scene/github.svg)](https://agentmods.dev/skills/elemarin/renderoni/prompt-to-scene)
Your own site
<a href="https://agentmods.dev/skills/elemarin/renderoni/prompt-to-scene"><img src="https://agentmods.dev/badge/skills/elemarin/renderoni/prompt-to-scene/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 prompt-to-scene

Your own site · 80×15
<a href="https://agentmods.dev/skills/elemarin/renderoni/prompt-to-scene"><img src="https://agentmods.dev/badge/skills/elemarin/renderoni/prompt-to-scene.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,918 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 $0.00054 $0.01918
Opus 5 $0.00027 $0.00959
Sonnet 5 $0.00011 $0.00384
Haiku 4.5 $0.00005 $0.00192

Measured 8d ago against content hash 80548c134a69, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

prompt-to-scene 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 8d 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.

.agents/skills/prompt-to-scene/SKILL.md · 188 lines

How it starts

The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prompt → image → img2threejs → Renderoni

Do not one-shot a whole game as a giant TypeScript file. Keep the agent context small: one prompt, one scene image, one inventory JSON, then reconstruct unique objects independently.

Upstream reconstruction skill: img2threejs. Renderoni only mounts the resulting () => THREE.Group factories.

Token budget (hard rules)

  1. Keep the inventory JSON in context. Target < 800 tokens.
  2. Never paste img2threejs SKILL.md, forge scripts, or generated factory source into the main game conversation after the factory is written to disk.
  3. Reconstruct one unique factory key per isolated pass. Reuse the same factory for repeated props (10 trees = 1 factory).
  4. Gameplay stays in Renderoni presets (kccPlayer, sensor, body, light). Factories are visuals + collider hints only.

Pipeline

prompt
  → one scene image (optional but preferred)
  → compact SceneInventory JSON
  → unique factory list
  → img2threejs per factory (or fallback primitive)
  → mountSceneInventory(engine, inventory, factories)
  → add player / win-lose with presets

1. Inventory first

Write scene-inventory.json using SceneInventory from renderoni/scene:

{
  "version": 1,
  "prompt": "stone courtyard with crate, lantern, tree, well, coin",
  "image": "refs/courtyard.png",
  "seed": 42,
  "elements": [
    {
      "id": "crate",
      "factory": "woodCrate",
      "kind": "prop",
      "position": [-3, 0.55, -2],
      "collider": { "shape": "box", "size": [1.1, 1.1, 1.1] }
    }
  ]
}

kind: terrain | prop | actor | pickup | decor. factory is a registry key, not source code.

2. Scene image (optional)

If the user has no image, generate one wide establishing shot of the whole scene. Then list visible objects. Use imageRegion (normalized 0–1) only when cropping helps reconstruction. Do not generate a separate image per blade of grass.

Read the full file on GitHub · 188 lines

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. 8d ago First seen · 188 lines · 54 tokens per session scan A 80548c134a69

Subscribe to this mod's changes

prompt-to-scene is a skill published in the GitHub repository elemarin/renderoni (0 stars, last pushed 11d ago), licensed MIT. It adds 54 tokens to every session and 1,918 once invoked, about $0.0003 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 2026-08-31.

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