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threejs-visual-validation

threejs-visual-validation

github.com/scottsttsTesting & quality951111 installsUpdated 1w ago
Repository

About threejs-visual-validation

A validation skill for visual implementations that tests the mechanisms behind rendered results, not just a single polished image. It specifies reproducible inputs, diagnostic captures, camera and seed tests, temporal checks, budgets, and regression evidence.

Key features

  1. 01Freezes deterministic inputs
  2. 02Requires baseline and diagnostic captures
  3. 03Tests camera ranges and seed variation
  4. 04Checks motion and temporal stability
  5. 05Records image and performance budgets
  6. 06Maintains visual regression evidence

Use cases

  1. 01Validating procedural graphics changes
  2. 02Finding failures hidden by a hero image
  3. 03Testing effects across seeds and camera distances
  4. 04Tracking temporal artifacts and render budgets

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/scottstts/threejs-awesome-graphics-agent-skills --skill threejs-visual-validation

After installing, type/threejs-visual-validationin Claude Code to confirm it loaded.

Bundled filesagents/openai.yamlreferences/graphics-validation-protocol.md

Details

From the project README

Visual Validation

Evaluate the mechanism that creates the image. A beautiful hero screenshot can hide unstable fields, broken depth, seed failures, or post-processing dependence.

Validation sequence

  1. Freeze deterministic inputs.
  2. Capture the no-post baseline.
  3. Capture system-specific diagnostic views.
  4. Test the intended camera-distance envelope.
  5. Sweep representative seeds and parameter extremes.
  6. Test motion and temporal stability.
  7. Record image, geometry, memory, and timing budgets.
  8. Keep a small regression set tied to visual invariants.

Read references/graphics-validation-protocol.md for visual contracts, required inspection controls, mechanism-specific evidence, temporal checks, budgets, and explicit rejection criteria.

Required evidence

  • fixed camera and seed manifest;
  • final and no-post captures;
  • field/pass diagnostic mosaic;
  • near, design, and far camera views;
  • at least one stress seed;
  • frame-time and render-target inventory;
  • written invariants and known compromises.

Failure conditions

  • approval relies on a single frame;
  • post-processing cannot be disabled per pass;
  • random seeds are not reproducible;
  • GPU time is inferred only from CPU frame time;
  • temporal artifacts are judged from still images;
  • comparison thresholds ignore intentional stochastic pixels without stabilizing them.

Routing boundary

This skill evaluates an implementation; it does not supply the implementation mechanism. Load the subject or image-effect skill first, then use this protocol to decide whether the result is acceptable.

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