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Creative rendering audit

Skill sarveshsea/design-skills/skills/creative-rendering-audit

Practical design judgment for AI coding agents: 78 installable skills for craft, research, generation, Figma, and Memoire.

Install

npx -y skills add sarveshsea/design-skills --skill creative-rendering-audit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Audit shaders, GPU-driven effects, dithering, particles, and creative rendering for visual intent, correctness, performance, accessibility, fallbacks, evidence quality, and source licensing.

SKILL.md

3.7 KB, as published. Nobody here has run it

Creative Rendering Audit

Audit the supplied implementation and rendered behavior. Keep the audit read-only unless the user separately authorizes fixes.

Workflow

Establish the intended visual behavior, target platforms, supported hardware, quality tiers, fallback, and user-facing acceptance criteria.
Map the rendering path from host inputs to shader stages, textures, render targets, compositing, and final presentation.
Gather evidence:
- Read shader and host-language source with file and line anchors.
- Capture compilation, validation, and device-loss messages.
- Exercise deterministic frames with a fixed seed and clock.
- Compare the full effect, reduced-motion path, unsupported-renderer path, and static fallback.
- Profile realistic content at the stated resolution on named hardware.
Review every dimension in references/audit-rubric.md.
Use references/platform-evidence.md for surface-specific evidence and failure modes.
Reproduce or directly observe every high-severity finding. Mark code-only inferences as hypotheses.
Report missing evidence as unassessed. Do not award a pass for a dimension that could not be tested.

Scoring

Score only verified evidence.

Dimension	Points
Visual intent and interaction fit	15
Coordinate, sampling, color, and alpha correctness	20
Dither and temporal stability	15
Performance and resource bounds	20
Accessibility, fallback, and failure behavior	20
Provenance, licensing, and reproducible evidence	10

Apply these caps:

Missing or incompatible source or asset license: maximum 49.
No accessible or unsupported-renderer fallback: maximum 69.
No rendered runtime evidence: maximum 79.
No named-device performance evidence for an animated effect: maximum 89.

Include a confidence value derived from assessed points divided by 100. Unknown dimensions score zero and lower confidence.

Required output

Start with a findings table ordered by severity:

Severity	Evidence	Finding	User impact	Required correction

Use critical, high, medium, or low. Cite file:line and attach runtime evidence when available.

Then provide:

score, confidence, assessed dimensions, and applied caps;
platform, device, resolution, seed, clock, and quality tier;
checks that passed with evidence;
unassessed behavior and the exact evidence needed;
a verdict of Block, Conditional pass, or Pass.

Verdict rules

Block for unsafe or incompatible licensing, inaccessible essential content, persistent rendering failure, unbounded sampling, or a reproducible severe performance regression.
Conditional pass when the bounded effect works but platform, accessibility, or named-device evidence is incomplete.
Pass only when all required dimensions have verified evidence and no critical or high finding remains.

Boundaries

Do not treat a deterministic fixture as live integration proof.
Do not infer visual quality from a successful build.
Do not hide performance variance behind an average alone; include worst observed behavior or a percentile where tooling permits.
Do not recommend copying restricted reference implementations.

Maintenance

Review platform evidence and reference links at least every 180 days. Refresh the registry and provenance verification dates only after inspection, then run the repository validator.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.