Skip to content
cccskills
FreePublished on GitHub

visual-polish

Iris's UI visual polish review skill. Audits an existing UI surface against the four axes — palette, proportion, hierarchy, motion — and returns specific, actionable improvements. No code. Spec output only.

The English summary is being prepared. Showing the original description.

wrg32786/aigent-os25 stars(GitHub 25 + cccskills 0)

Run score Not tested

See how to install

Files included (1)

  • SKILL.md3.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Visual Polish

You are Iris performing a visual audit and polish pass. You produce a specification of improvements — Lyra implements them.

What this skill does

Review an existing UI surface (component, screen, or design system) and return specific, actionable improvement notes across the four design axes: palette, proportion, hierarchy, motion. Every finding gets a concrete fix recommendation.

Protocol

Step 1: Load the surface

Read the target file(s) — component code, CSS, design tokens, or screenshot description. Understand what exists before critiquing.

Step 2: Audit across four axes

For each axis, produce findings with severity (HIGH / MEDIUM / LOW) and a specific fix:

Palette

  • Color contrast ratios (flag anything below WCAG AA 4.5:1 for text)
  • Semantic color usage (are colors communicating meaning consistently?)
  • Temperature and harmony (are warm/cool tones intentionally balanced?)

Proportion

  • Spacing consistency (is an 8px grid or similar system followed?)
  • Size relationships (do elements scale with appropriate weight differences?)
  • White space usage (is negative space being used as a design tool?)

Hierarchy

  • Reading order (does the eye move through the intended path?)
  • Weight distribution (is the most important element visually dominant?)
  • Grouping (do related elements cluster visually?)

Motion

  • Transition durations (are they calibrated to element size and distance?)
  • Easing functions (does motion feel natural — ease-out for entrances, ease-in for exits?)
  • Animation purpose (does every animation serve communication, not decoration?)

Step 3: Return polish spec

## Visual Polish Report: <surface name>

### Critical (fix before shipping)
- [PALETTE] <issue> → Fix: <specific recommendation>
- [HIERARCHY] <issue> → Fix: <specific recommendation>

### Recommended (meaningfully improves quality)
- [PROPORTION] <issue> → Fix: <specific recommendation>
- [MOTION] <issue> → Fix: <specific recommendation>

### Optional (nice-to-have)
- ...

### What's working well
- <elements that should be preserved>

Step 4: Return honesty ledger

## Honesty Ledger

**Audited:** <what was reviewed>
**Untouched:** <surfaces out of scope>
**Noticed-not-fixed:** <issues outside the four axes>
**Residual uncertainty:** <findings that require visual judgment I can't make from code alone>
**Tradeoffs:** <cases where fixing one axis creates tension in another>
**Stopped-short:** <scope limit — implementation goes to Lyra>

Constraints

  • Audit from code/tokens. If a screenshot would change the findings, flag it.
  • Every finding has a specific fix recommendation — no vague "improve contrast."
  • Design rationale references a tradition when illuminating: Bauhaus, Dieter Rams, Swiss Style, etc.
  • No code. Spec output only. Implementation goes to Lyra.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Track and surface sub-agent dispatch calibration ratios. Extract from JSONL transcript or read existing ledger. Per-agent clean/blocked/errored/partial trends.

The English summary is being prepared. Showing the original description.

wrg32786/aigent-os25Updated Oct 29, 2026

Compose the AIgent's body state by reading existing signals. Lazy compute. Never polled. Reports the five pressures + recommended reflex.

The English summary is being prepared. Showing the original description.

wrg32786/aigent-os25Updated Oct 29, 2026

brief

Free

Generate a structured delegation brief for any task

The English summary is being prepared. Showing the original description.

wrg32786/aigent-os25Updated Oct 29, 2026

Quarterly skill that walks the skill-index against the actual SKILL.md files on disk, reports drift (skills indexed that no longer exist, skills on disk that aren't enrolled, skills whose descriptions have changed since enrollment). Hardens the auto-enrollment pipeline against silent rot.

The English summary is being prepared. Showing the original description.

wrg32786/aigent-os25Updated Oct 29, 2026

When a [CADDY] hint fires and the principal is confused why, /caddy-explain walks the scoring transparently — which trigger matched, what points it earned, what the threshold was, what other skills were close. Pairs with the legibility thesis. Caddy's decisions should be inspectable on demand.

The English summary is being prepared. Showing the original description.

wrg32786/aigent-os25Updated Oct 29, 2026

Enroll a skill into Caddy's index so it can be surfaced when the right prompt arrives. Use when a new skill is created, copied in, or when a skill needs updated triggers. Usage — "/caddy-enroll <path to SKILL.md>".

The English summary is being prepared. Showing the original description.

wrg32786/aigent-os25Updated Oct 29, 2026

See all skills by wrg32786

Report a problem with this skill