| name | ui-ux-pro-max |
| description | Passive design-system reference corpus — look up color palettes, font pairings, product-to-style mappings, named visual styles, chart-type selection, icon libraries, landing-page patterns, app-interface and UX guidelines, React performance rules, UI reasoning, and per-stack UI rules by grep/Read over the vendored CSVs. Triggers on "what palette for a fintech app", "font pairing for healthcare", "chart type for time-series", "Next.js UI conventions", "landing page section order". NOT a review gate (use frontend-quality) and NOT the design-craft authority (use impeccable) — this is lookup data only. |
| license | MIT |
UI/UX Pro Max — Design-System Reference Corpus
This skill is a passive reference corpus: a body of structured design data
the agent consults by grep/Read over vendored CSV files. It is not a reviewer,
not a quality gate, and not a second design opinion. It is lookup data.
When to use
Consult this corpus when you need concrete design prior art to ground a
decision: a color palette for a product type ("what palette for a fintech
app"), a font pairing ("font pairing for healthcare"), a chart type ("chart
type for time-series"), per-stack UI conventions ("Next.js UI conventions"),
or landing-page section order. It is lookup data only — for design taste and
the working method use impeccable, and for the WCAG / Core-Web-Vitals gate
use frontend-quality.
What this is (and is not)
- IS: a queryable corpus of palettes, font pairings, product-to-style
patterns, named visual styles, chart-type selection, icon libraries,
landing-page patterns, app-interface and UX guidelines, React performance
rules, UI reasoning, and per-framework UI rules. You grep it to ground
design decisions in concrete prior art.
- IS NOT a review or quality gate — that is
frontend-quality
(WCAG 2.2 AA, Core Web Vitals).
- IS NOT the design-craft authority — that is
impeccable (taste,
anti-AI-slop principles, the working method).
- Think of it as the data layer that
impeccable and ui-ux-polish consult
while applying judgment.
Tooling note (Walter-OS adaptation)
Upstream ships a Python CLI (search.py / core.py / design_system.py) and
a sync script (_sync_all.py). None of the Python is vendored. You consult
this corpus with plain grep and Read over the CSVs — no python3 search.py, no runtime dependency. The data is intentionally CSV so it is
greppable.
This corpus is pinned to the upstream commit below, with Walter-OS adaptations
recorded in docs/specs/ux-skills-adoption.md: unstructured/non-English
upstream files are omitted, a small number of non-English cells were translated,
and data/stacks/threejs.csv was normalized to the shared per-stack No,...
schema. Do not assume every vendored byte can be compared directly to upstream
without applying those documented adaptations.
Some rows contain code-example fields with embedded commas and unescaped double
quotes (e.g. an HTML/JSX snippet), so a strict RFC-4180 CSV parser may reject or
mis-column them. That is expected: this corpus is meant for line-oriented
grep/Read lookup, NOT for parsing as structured CSV.
The corpus
data/*.csv — cross-cutting design data (11 files)
Every CSV has a header row; the column names below are the real headers
(line 1 of each file).
products.csv — product type -> style and palette recommendations.
Columns: No,Product Type,Keywords,Primary Style Recommendation,Secondary Styles,Landing Page Pattern,Dashboard Style (if applicable),Color Palette Focus,Key Considerations
colors.csv — named palettes as full token sets (primary/secondary/accent,
on-colors, background, card, muted, border, destructive, ring) per product
type. Columns: No,Product Type,Primary,On Primary,Secondary,On Secondary,Accent,On Accent,Background,Foreground,Card,Card Foreground,Muted,Muted Foreground,Border,Destructive,On Destructive,Ring,Notes
typography.csv — font pairings (heading + body) with mood, Google Fonts
URL, CSS import, and Tailwind config. This is the font-pairing file.
Columns: No,Font Pairing Name,Category,Heading Font,Body Font,Mood/Style Keywords,Best For,Google Fonts URL,CSS Import,Tailwind Config,Notes
styles.csv — named visual styles with colors, effects, best-for, light/dark
support, accessibility, framework compatibility, and AI-prompt keywords.
Columns: No,Style Category,Type,Keywords,Primary Colors,Secondary Colors,Effects & Animation,Best For,Do Not Use For,Light Mode ✓,Dark Mode ✓,Performance,Accessibility,Mobile-Friendly,Conversion-Focused,Framework Compatibility,Era/Origin,Complexity,AI Prompt Keywords,CSS/Technical Keywords,Implementation Checklist,Design System Variables
charts.csv — chart-type selection by data type, with secondary options,
volume thresholds, color/a11y guidance, and library recommendations.
Columns: No,Data Type,Keywords,Best Chart Type,Secondary Options,When to Use,When NOT to Use,Data Volume Threshold,Color Guidance,Accessibility Grade,Accessibility Notes,A11y Fallback,Library Recommendation,Interactive Level
icons.csv — icon lookup by category/name with library, import code, and
recommended usage. Columns: No,Category,Icon Name,Keywords,Library,Import Code,Usage,Best For,Style
landing.csv — landing-page patterns: section order, CTA placement, color
strategy, recommended effects, conversion notes.
Columns: No,Pattern Name,Keywords,Section Order,Primary CTA Placement,Color Strategy,Recommended Effects,Conversion Optimization
app-interface.csv — application-interface issues with do/don't and good/bad
code examples, by severity. Columns: No,Category,Issue,Keywords,Platform,Description,Do,Don't,Code Example Good,Code Example Bad,Severity
ux-guidelines.csv — UX rules with do/don't, good/bad code examples, and
severity. Columns: No,Category,Issue,Platform,Description,Do,Don't,Code Example Good,Code Example Bad,Severity
react-performance.csv — React performance issues with do/don't and
good/bad code examples, by severity. Columns: No,Category,Issue,Keywords,Platform,Description,Do,Don't,Code Example Good,Code Example Bad,Severity
ui-reasoning.csv — higher-level UI decision rules: recommended pattern,
style/color/typography priorities, key effects, decision rules, anti-patterns.
Columns: No,UI_Category,Recommended_Pattern,Style_Priority,Color_Mood,Typography_Mood,Key_Effects,Decision_Rules,Anti_Patterns,Severity
Note: upstream's large google-fonts.csv (~745KB) is intentionally not
vendored — use typography.csv for curated font pairings.
data/stacks/*.csv — per-framework UI rules (16 files)
angular, astro, flutter, html-tailwind, jetpack-compose, laravel,
nextjs, nuxt-ui, nuxtjs, react, react-native, shadcn, svelte,
swiftui, threejs, vue.
Each per-stack file shares the same schema — framework-specific guidelines with
rationale and good/bad code examples. Columns: No,Category,Guideline,Description,Do,Don't,Code Good,Code Bad,Severity,Docs URL.
reference/quick-reference.md
A compact, self-contained human-readable digest (the most useful single file
when you want orientation before diving into the CSVs).
How to use it (concrete examples)
Look up the recommended styles and landing pattern for a product type
(matches the Product Type / Keywords columns of products.csv):
grep -i fintech skills/ui-ux-pro-max/data/products.csv
Pull a full palette token set for a product type from colors.csv:
grep -i "healthcare\|saas\|dashboard" skills/ui-ux-pro-max/data/colors.csv
Find a font pairing by mood or use case (typography.csv is the pairing
file — Font Pairing Name / Mood/Style Keywords / Best For):
grep -i "serif\|editorial\|elegant" skills/ui-ux-pro-max/data/typography.csv
Pick a chart type for a given data type from charts.csv:
grep -i "time-series\|comparison\|distribution" skills/ui-ux-pro-max/data/charts.csv
Look up a landing-page section order / CTA placement from landing.csv:
grep -i "hero\|pricing\|testimonial" skills/ui-ux-pro-max/data/landing.csv
Pull the UI conventions for a specific framework (per-stack files share the
Category / Guideline / Severity schema):
grep -i "form\|validation" skills/ui-ux-pro-max/data/stacks/nextjs.csv
Find high-severity UX rules with good/bad code examples (Severity column):
grep -i "critical\|high" skills/ui-ux-pro-max/data/ux-guidelines.csv
Look up React performance pitfalls from react-performance.csv:
grep -i "re-render\|memo\|effect" skills/ui-ux-pro-max/data/react-performance.csv
Workflow positioning
- Consult this corpus to ground a design choice in concrete prior art
(palette, pairing, style, per-stack rule).
- Apply taste and the working method via
impeccable.
- Refine to a professional standard via
ui-ux-polish.
- Gate the result on a11y + performance via
frontend-quality; for native
mobile, use mobile-design-system.
Provenance
Vendored from nextlevelbuilder/ui-ux-pro-max-skill at commit
b7e3af80f6e331f6fb456667b82b12cade7c9d35 (MIT, Copyright (c) 2024 Next Level
Builder). Only the CSV data, the quick-reference digest, and the LICENSE are
vendored; the upstream Python CLI is deliberately excluded. See LICENSE in
this directory.