threejs-visual-validation

threejs-visual-validation is a skill for Codex from linegel/threejs-complete-set-of-skill. It costs 43 tokens per session (1,179 once invoked), scanned A, original, ISC.

A testing guide for Three.js WebGPU and TSL implementations, where WebGPU is a browser graphics system and TSL is Three.js's shader-building language.

In plain words
What is it for?
It supports defining measurable tests, freezing rendering conditions, checking mechanisms and temporal behavior, measuring graphics cost, and finding resource or lifecycle failures.
Why use it?
It helps verify specific visual, timing, performance, GPU, resource, and lifecycle claims instead of treating a polished image as proof that the system works.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: $skill-name invocation.

Good fit It supports defining measurable tests, freezing rendering conditions, checking mechanisms and temporal behavior, measuring graphics cost, and finding resource or lifecycle failures.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/linegel/threejs-complete-set-of-skill/threejs-visual-validation
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 linegel/threejs-complete-set-of-skill --skill threejs-visual-validation
Clone the repo
git clone --depth 1 https://github.com/linegel/threejs-complete-set-of-skill

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-visual-validation

README.md
[![agentmods](https://agentmods.dev/badge/skills/linegel/threejs-complete-set-of-skill/threejs-visual-validation/github.svg)](https://agentmods.dev/skills/linegel/threejs-complete-set-of-skill/threejs-visual-validation)
Your own site
<a href="https://agentmods.dev/skills/linegel/threejs-complete-set-of-skill/threejs-visual-validation"><img src="https://agentmods.dev/badge/skills/linegel/threejs-complete-set-of-skill/threejs-visual-validation/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-visual-validation

Your own site · 80×15
<a href="https://agentmods.dev/skills/linegel/threejs-complete-set-of-skill/threejs-visual-validation"><img src="https://agentmods.dev/badge/skills/linegel/threejs-complete-set-of-skill/threejs-visual-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,179 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 $0.00043 $0.01179
Opus 5 $0.00022 $0.00589
Sonnet 5 $0.00009 $0.00236
Haiku 4.5 $0.00004 $0.00118

Measured 10d ago against content hash 79e7519853f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

threejs-visual-validation 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/aligned-readback.mjs), 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.

skills/threejs-visual-validation/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Visual Validation

Validate claims, not polished frames. Keep each verdict scoped to one declared claim so evidence for appearance cannot substitute for mechanism, timing, or lifecycle proof. The owning subject skill defines mechanism truth and failure signatures; this skill defines how to falsify them.

1. Predeclare every claim

For each claim, record:

  • class: visual, mechanism, temporal, performance, GPU attribution, resource, or lifecycle;
  • invariant and truth source;
  • observable and the diagnostic that isolates it;
  • native-domain metric, units, alignment, mask, and aggregation;
  • acceptance gate fixed before candidate inspection;
  • blocking failure and required evidence.

Label every claim-driving number Authored, Derived, Measured, or Gated and record its unit and source. Keep unknown values unknown.

This step is complete when every claim has a direct falsifier and no claim is supported only by the final image.

2. Freeze the run

Freeze the exact Three.js revision, renderer and initialized backend, target, browser/GPU, camera matrices, seed, time or deterministic step, viewport, DPR, quality state, assets, and color/output graph. Construct the renderer with timestamp tracking before initialization whenever a declared claim needs GPU timing:

const renderer = new WebGPURenderer( {
  trackTimestamp: gpuTimingRequirement === 'required'
} );

await renderer.init();

if ( renderer.backend.isWebGPUBackend !== true ) {
  throw new Error( 'Canonical WebGPU validation is unavailable on this target.' );
}

Record the blocker when canonical WebGPU is unavailable. Reach $threejs-compatibility-fallbacks only when the user explicitly asks for that branch.

This step is complete when the run can be repeated from the recorded state and initialized backend truth is captured rather than inferred.

3. Capture the producing mechanism

Capture the real pipeline under the frozen state:

  • for visual or mechanism claims, the final, no-post, and contribution views required to isolate the claimed cause;
  • only the depth, normal, velocity, field, history, mask, resource, or pass diagnostics needed by declared claims;
  • for performance, GPU-attribution, resource, or lifecycle claims without a visual/mechanism claim, only the producing trace and diagnostics required by that claim;
  • the pass/dispatch ownership graph, including histories and reset edges.

Read the full file on GitHub · 137 lines

Files

What ships with it

4 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. 10d ago First seen · 137 lines · 43 tokens per session scan A 79e7519853f9

Subscribe to this mod's changes

threejs-visual-validation is a skill published in the GitHub repository linegel/threejs-complete-set-of-skill (6 stars, last pushed 1mo ago), licensed ISC. It adds 43 tokens to every session and 1,179 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

qa

QA test your code changes by reading your git diff, choosing the right validation path for frontend/browser and backend changes, and reporting pass/fail with evidence.

Skyvern-AI/skyvern · 33 tokens

testing

Verify a Skyvern deployment is working correctly by smoke-testing the backend API, frontend rendering, browser session provisioning, and workflow execution. Use when the user says 'is Skyvern working', 'test my deployment', 'verify the installation', 'smoke test', or needs to check that a self-hosted or local Skyvern…

Skyvern-AI/skyvern · 71 tokens

testing-e2e

End-to-end testing patterns with Playwright — page objects, AI agent testing, visual regression, accessibility testing with axe-core, and CI integration. Use when writing E2E tests, setting up Playwright, implementing visual regression, or testing accessibility.

yonatangross/orchestkit · 55 tokens

pi-validation-flow

Use when validating Pi monorepo changes after editing TypeScript, Svelte, package manifests, built-in registry, tests, repo tooling, skills, or docs.

spences10/my-pi · 37 tokens

ui-data-testid

Add stable data-testid attributes by default for new or refactored UI components. Use when implementing React/TSX views, shadcn/antd-style components, dropdown/menu configs, or interactive UI flows that need reliable selectors for unit/E2E tests.

dtyq/magic · 58 tokens

kdd-accessibility-scan

Guia a cualquier agente (no depende de ningun modelo puntual) para producir un scan de accesibilidad (WCAG) de un producto en el formato de contrato de Capa 3 de KDD -- findings.json -- que despues gatea scripts/validateaccessibilityfindings.py. Usala cuando se pida auditar accesibilidad de una app/pagina, correr…

MauricioPerera/KDD · 146 tokens