Color Expert

A comprehensive knowledge base for color-related work. See

references/INDEX.md

for 140+ detailed reference files; this skill file contains the essential knowledge to answer most questions directly.

Color Spaces — What to Use When

Task

Use

Why

Perceptual color manipulation

OKLCH

Best uniformity for lightness, chroma, hue. Fixes CIELAB's blue problem.

CSS gradients & palettes

OKLCH

or

color-mix(in oklab)

No mid-gradient darkening like RGB/HSL

Gamut-aware color picking

OKHSL / OKHSV

Ottosson's picker spaces — cylindrical like HSL but perceptually grounded

Normalized saturation (0-100%)

HSLuv

CIELUV chroma normalized per hue/lightness. HPLuv for pastels.

Print workflows

CIELAB D50

ICC standard illuminant

Screen workflows

CIELAB D65

or OKLAB

D65 = screen standard

Cross-media appearance matching

CAM16 / CIECAM02

Accounts for surround, adaptation, luminance, and viewing conditions

HDR

Jzazbz / ICtCp

Designed for extended dynamic range

Pigment/paint mixing simulation

Kubelka-Munk

(Spectral.js, Mixbox)

Spectral reflectance mixing, not RGB averaging

Color difference (precision)

CIEDE2000

Gold standard perceptual distance

Color difference (fast)

Euclidean in OKLAB

Good enough for most applications

Video/image compression

YCbCr

Luma+chroma separation enables chroma subsampling

Understanding HSL's Limitations

HSL isn't "bad" — it's a simple, fast geometric rearrangement of RGB into a cylinder. It's fine for quick color picking and basic UI work. But its three channels don't correspond to human perception:

Lightness (L):

fully saturated yellow (

hsl(60,100%,50%)

) and fully saturated blue (

hsl(240,100%,50%)

) have the same L=50% but vastly different perceived brightness. L is a mathematical average, not a perceptual measurement.

Hue (H):

non-uniform spacing. A 20° shift near red produces a dramatic change; the same 20° near green is barely visible. The green region is compressed, reds are stretched.

Saturation (S):

doesn't correlate with perceived saturation. A color can have S=100% and still look muted (e.g., dark saturated blue).

When HSL is fine:

simple color pickers, quick CSS tweaks, situations where perceptual accuracy doesn't matter.

When to use something better:

Generating palettes or scales →

OKLCH

(uniform lightness across hues)

Creating gradients →

OKLAB

or

color-mix(in oklab)

(no mid-gradient darkening)

Gamut-aware picking with HSL-like UX →

OKHSL

(Ottosson's perceptual HSL)

Normalized saturation 0–100% →

HSLuv

(CIELUV-based, no out-of-bounds)

Named Hue (HSL/HSV) Ranges

Use these degree ranges when generating or constraining colors by hue name. Source:

random-display-p3-color

by mrmrs / mrmrs.cc.

Name

Degrees

red

345–360, 0–15

orange

15–45

yellow

45–70

green

70–165

cyan

165–195

blue

195–260

purple

260–310

pink

310–345

warm

0–70

cool

165–310

Key Distinctions

Chroma

= colorfulness relative to a same-lightness neutral reference

Saturation

= perceived colorfulness relative to the color's own brightness

Lightness

= perceived reflectance relative to a similarly lit white

Brightness

= perceived intensity of light coming from a stimulus

Same chroma ≠ same saturation. These are different dimensions.

Implementation Guidance — Code and CSS

When using colors in a program or CSS, add a semantic layer between raw color values and UI roles.

The examples below are pseudocode, not literal CSS requirements. They express the decision structure an agent should preserve even if the target stack uses different syntax.

Across CSS, JS/TS, Swift, design-token JSON, templates, or pseudocode, default to the same structure:

Reference tokens/palette values

for concrete colors

Semantic tokens/roles

that map meaning onto those colors

Component usage

that consumes semantic tokens rather than raw literals

Raw color literals should usually appear only in palette/reference definitions, conversions, diagnostics, or deliberately one-off examples.

Use reference tokens for concrete colors

:

ref.red = #f00

Use semantic tokens for meaning/role

:

semantic.warning = ref.red

Prefer semantic tokens in components

so themes can swap meaning without rewriting component code.

This default applies in any language

; translate to the target system's equivalent alias/reference mechanism (CSS custom properties, Swift enums, design-token JSON, etc.).

Encode color decisions when possible

instead of freezing one manual choice into a literal.

Pseudocode examples:

ref.red := closest('red', generatedPalette)

semantic.warning := ref.red

semantic.onSurface := mostReadableOn(surface)

Good pattern: palette/reference tokens define available colors; semantic tokens map those colors to roles like surface, text, accent, success, warning, and danger.

If a system can derive a decision from constraints, encode that derivation. Examples: nearest named hue in a generated palette, foreground chosen by APCA/WCAG target, hover state computed from the base token in OKLCH instead of hand-picking a second unrelated hex.

For larger systems, prefer a

token graph

over a flat token dump: references, semantic roles, derived functions, and scope inheritance. This makes theme changes, accessibility guarantees, and multi-platform export auditable and easier to maintain.

Accessibility — Key Numbers

Of ~281 trillion hex color pairs (research by @mrmrs_, computed via a Rust brute-force run):

Threshold

% passing

Odds

WCAG 3:1 (large text)

26.49%

~1 in 4

WCAG 4.5:1 (AA body text)

11.98%

~1 in 8

WCAG 7:1 (AAA)

3.64%

~1 in 27

APCA 60

7.33%

~1 in 14

APCA 75 (fluent reading)

1.57%

~1 in 64

APCA 90 (preferred body)

0.08%

~1 in 1,250

APCA is far more restrictive than WCAG at comparable readability. At APCA 90, only 239 billion of 281 trillion pairs work. JPEG compression exploits the same biology: chroma subsampling (4× less color data) is invisible because human vision resolves brightness at higher resolution than color.

Color Harmony — What Actually Works

Hue-first harmony is a weak standalone heuristic

Complementary, triadic, tetradic intervals are weak predictors of mood, legibility, or accessibility on their own. Every hue plane has a different shape in perceptual space, so geometric hue intervals do not guarantee perceptual balance.

Character-first harmony works (Ellen Divers' research)

Organize by character (pale/muted/deep/vivid/dark), not hue. Finding:

hue is usually a weaker predictor of emotional response than chroma and lightness

— a muted palette often reads as calm across many hues. Relaxed vs intense is driven more by chroma + lightness than hue alone.

Legibility = lightness variation

Grayscale is a quick sanity check for lightness separation, not an accessibility proof. You still need to verify contrast with WCAG/APCA and consider text size, weight, polarity, and CVD. Same character + varied lightness is often more readable. Same lightness regardless of hue is usually illegible.

The 60-30-10 rule

60% dominant color, 30% secondary, 10% accent. One color dominates to prevent "three equally-sized gorillas fighting."

Pigment Mixing — Not What You Think

Pigment mixing is not well described by the simple subtractive model alone

— "integrated mixing" (Küppers/Briggs) is a better practical description. It behaves like a compromise between subtractive and additive averaging.

CMY mixing paths curve outward

(retain chroma = vivid secondaries) — "extroverted octopus"

RGB mixing paths curve inward

(lose chroma = dull browns) — "introverted octopus"

Mixing is non-linear

proportion of paint ≠ proportional hue change. You "turn a corner" at certain ratios.

Blue→yellow is a LONG road

, red→yellow is SHORT. Traditional wheel massively misrepresents distances.

Tinting strength varies

blues are concentrated/strong, yellows are weak.

White doesn't just lighten

— it shifts hue AND kills chroma.

For spectral/K-M mixing in code

use Spectral.js (open source) or Mixbox (commercial).

Color Temperature

Temperature ≠ hue

— it's a systematic shift of BOTH hue AND saturation, dependent on starting hue

Spectral bias

which end of the spectrum a light favors (short λ = cool, long λ = warm)

Cool daylight

blue atmospheric scatter fills shadows; paint neutral highlights, blue shadows

Warm incandescent

favors long wavelengths including infrared (literally felt as heat) Green and purple do not map cleanly to warm/cool in the same way as red-orange or blue-cyan; perceived temperature depends strongly on context Color Naming — Multiple Systems for Different Registers System Register Example ISCC-NBS Scientific precision "vivid yellowish green" Munsell Systematic notation "5GY 7/10" XKCD Common perception "ugly yellow", "hospital green" Traditional Japanese Cultural/poetic "wasurenagusa-iro" (forget-me-not) RAL Industrial reproducibility RAL 5002 Ridgway (1912) Ornithological 1,115 named colors, public domain CSS Named Colors Web standard 147 named colors color-description lib Emotional adjectives "pale, delicate, glistening" Use color-name-lists npm package for 18 naming systems in one import. Historical Corrections Moses Harris (1769) was first to place RYB at equal 120° — Newton, Boutet, Schiffermüller didn't. His own wheel needed a 4th pigment. The origin of bad color theory. Von Bezold (1874) killed "indigo" as a spectral color — Newton's "blue" ≈ modern cyan, Newton's "indigo" ≈ modern blue. The word "magenta" wasn't used for the subtractive primary until 1907 (Carl Gustav Zander). Before: "pink" (Benson 1868), "crimson," "purpur." Amy Sawyer (1911) patented a CMY wheel (primrose/rose/turquoise) decades before it became mainstream. Elizabeth Lewis (1931) married trichromatic + opponent process on one wheel, anticipating CIE Lab by 30 years. Recommended Tools Palette Generation (actual algorithms, not pre-made swatches) Note: coolors.co does not generate palettes — it picks randomly from 7,821 pre-made palettes hardcoded in its JS bundle. RampenSau — hue cycling + easing, color space agnostic Poline — anchor points + per-axis position functions (1.2K stars); ships a web component for interactive controls pro-color-harmonies — adaptive OKLCH harmony, muddy-zone avoidance, 4 styles × 4 modifiers dittoTones — extract Tailwind/Radix "perceptual DNA", apply to your hue FarbVelo — random palettes with dark→light structure IQ Cosine Formula — color(t) = a + bcos(2π(ct+d)) , 12 floats = infinite palette Palette Analysis & Linting Color Buddy — 38 lint rules (WCAG, CVD, distinctness, fairness, affect) Censor — Rust CLI, CAM16UCS analysis, 20+ viz widgets Color Palette Shader — WebGL2 Voronoi, 30+ color models, 11 distance metrics PickyPalette — interactive sculpting on color space canvas Color Libraries (code) Culori — 30 spaces, 10 distance metrics, gamut mapping, CVD sim @texel/color — 5–125× faster than Color.js, minimal, for real-time Spectral.js — open-source K-M pigment mixing (blue+yellow=green) RYBitten — RGB↔RYB with 26 historical color cubes colorgram — 1 kB image palette extraction; 64-bucket HLS+luminance quantization, ~15 ms for 340×340, fixed memory Art Palette — JS palette extraction from ImageData + Python/TensorFlow perceptual palette embeddings for search-by-color (Google Arts & Culture, Apache 2.0) random-display-p3-color — generate random Display P3 colors constrained by named hue/saturation/lightness, zero deps, ESM (by mrmrs / mrmrs.cc) Key Online Tools oklch.com — OKLCH picker Huetone — accessible color system builder (LCH/OKLCH), by Ardov Ardov Color Lab — gamut mapping playground, P3 space explorer, harmony generator, 3D color space visualizations, themer (lab.ardov.me) Components.ai Color Scale — parametric scale generator: 6 spaces, 4 curve methods, WCAG contrast (by mrmrs / mrmrs.cc) View Color — real-time analysis, WCAG + APCA, CVD preview APCA Calculator — apcacontrast.com Deep References See references/INDEX.md for the detailed files organized as: historical/ — Ostwald, Helmholtz, Bezold, Ridgway 1912, ISCC-NBS, Munsell, Albers, Caravaggio's pigments, Moses Harris, Lewis/Ladd-Franklin contemporary/ — Ottosson's OKLAB articles, Briggs lectures, Fairchild, Hunt, CIECAM02, MacAdam ellipses, Koenderink 2026 empirical 3D metric field (RGB supports ~1,000 qualitative regions; cool side coarser than warm; chromatic circle is not well-tempered), Pointer's gamut, CIE 1931/standard observer, Pixar Color Science, Acerola, Juxtopposed, Computerphile, bird tetrachromacy, OLO, GenColor paper. Full scrapes: huevaluechroma.com and colorandcontrast.com techniques/ — All tools above documented in detail, plus: CSS Color 4/5, ICC workflows, Tyler Hobbs generative color, Harvey Rayner Fontana approach, Goethe edge colors as design hack, mattdesl workshop + K-M simplex, CSS-native generation, IQ cosine presets, Erika Mulvenna interview, Bruce Lindbloom math reference, image extraction tools, Aladdin color analysis