Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
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.
[](https://agentmods.dev/skills/hassancs91/claude-image-generation/level-2-image-generator)<a href="https://agentmods.dev/skills/hassancs91/claude-image-generation/level-2-image-generator"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/level-2-image-generator/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.
<a href="https://agentmods.dev/skills/hassancs91/claude-image-generation/level-2-image-generator"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/level-2-image-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00185 | $0.01462 |
| Opus 5 | $0.00093 | $0.00731 |
| Sonnet 5 | $0.00037 | $0.00292 |
| Haiku 4.5 | $0.00018 | $0.00146 |
Grade A, and why
3d-image-renderer 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
3D Image Renderer
Renders a text prompt into a PNG by writing a Three.js scene and capturing one frame with headless-gl under Xvfb. Think of every image as frame 0 of a TSX animation composition: deterministic, seeded, time = 2.0s.
Inputs
- prompt — what to render
- aspect ratio — one of
1:1(1080×1080),16:9(1920×1080),9:16(1080×1920). Default16:9if unspecified. No custom sizes.
Workflow (follow in order)
1. Setup
bash <skill_dir>/scripts/setup.sh
Idempotent; instant when cached. Installs npm deps into
/home/claude/scene-render/ and drops the bundled prebuilt gl binary in
place (compiles from source only if the binary fails its smoke test). It also
copies pipeline.mjs and validate.mjs into the workdir. If it prints
SETUP FAILED, report the error to the user — do not hand-roll a fallback.
2. Plan the scene
- Pick ONE style preset → read
references/style-presets.mdnow. - List the hero elements: every concrete noun in the prompt ("headphones", "tree", "flowers") is a hero element.
- Read
references/geometry-recipes.mdfor any element it covers before inventing geometry.
3. Write the scene
Create /home/claude/scene-render/scene.mjs. Import ONLY from the local
pipeline — never re-implement renderer setup, pixel readback, or PNG writing:
import {
THREE, createRenderer, captureFrame, addStudioEnvironment,
seededRandom, visibleHeightAt,
} from './pipeline.mjs';
const time = 2.0; // the captured "frame"
const { renderer, glContext, W, H, OUT_W, OUT_H } =
createRenderer('16:9', { exposure: 1.15 /* from style preset */ });
const scene = new THREE.Scene();
// ... build: sky, lights, ground, hero elements (per preset + recipes) ...
await captureFrame({
renderer, glContext, scene, camera, W, H, OUT_W, OUT_H,
outPath: '/home/claude/scene-render/out.png',
});
console.log('DONE');
Scene-authoring rules:
- All randomness via
seededRandom(seed)— neverMath.random(). InstancedMeshfor anything repeated 50+ times; per-instance color viasetColorAt+instanceColor.needsUpdate = true.- Bake rotations into geometry (
geometry.rotateZ(...)) — do not stack Euler rotations on meshes for construction. - Validate every horizon/background element with
visibleHeightAt(the FOV rule in geometry-recipes.md) BEFORE rendering. - No post-processing. Glow = emissive + additive blending + fog.
- WebGL1 only: no
transmission, no WebGL2-only features, three stays at 0.152.2 (pinned by setup — do not upgrade).
What ships with it
6 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.
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.
- 10d ago First seen · 136 lines · 185 tokens per session scan A f369f2a465db
3d-image-renderer is a skill published in the GitHub repository hassancs91/claude-image-generation (91 stars, last pushed 23d ago), licensed MIT. It adds 185 tokens to every session and 1,462 once invoked, about $0.0009 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.
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