/design-dna

name: design-dna
description: >-
  Extract, define, and apply design DNA across three dimensions: design system
  (tokens), design style (qualitative feel), and visual effects (Canvas, WebGL,
  3D, particles, shaders, scroll effects, etc.). Use this skill when: (1) a user
  wants to see the full 3-dimension design structure/schema, (2) a user provides
  images, screenshots, or URLs of reference designs and wants them analyzed into
  a structured JSON profile covering all three dimensions, (3) a user has a
  Design DNA JSON and content and wants a design generated from it, or (4) any
  combination of these phases. Triggers on "design DNA", "extract design style",
  "analyze design", "design tokens from reference", "generate design from JSON",
  "design system from screenshot", "design profile", "style guide JSON",
  "visual effects analysis", "design with effects", "3d design analysis".

Design DNA

A 3-phase workflow for extracting, structuring, and applying design identity across three dimensions:

1. **Design System** — measurable tokens (color, typography, spacing, layout, shape, elevation, motion, components) 2. **Design Style** — qualitative perception (mood, visual language, composition, imagery, interaction feel, brand voice) 3. **Visual Effects** — special rendering (Canvas, WebGL, 3D, particles, shaders, scroll effects, cursor effects, SVG animations, glassmorphism, etc.)

Phases

Phase 1: Structure — Output the Schema

When the user asks for the structural dimensions or schema:

1. Read [references/schema.md](references/schema.md) 2. Present the full schema with field descriptions 3. Explain the three dimensions and their roles:

• **design_system**: What you can measure — exact hex values, pixel sizes, rem scales
• **design_style**: What you can feel — mood, personality, composition strategy
• **visual_effects**: What you can see but can't express in CSS alone — WebGL scenes, particle systems, shader distortions, scroll-driven animations

4. Ask if the user wants to customize or extend any dimensions

Phase 2: Analyze — Extract DNA from References

When the user provides images, screenshots, or links representing a target design style:

1. Read [references/schema.md](references/schema.md) for the full field list 2. For each reference provided:

• If image/screenshot: **first run the deterministic color measurement** (see below), then analyze the remaining visual properties directly
• If URL: fetch and analyze the page's visual design

3. For every field in the schema, extract or infer a value from the references 4. When multiple references conflict, note the dominant pattern and mention variants 5. Output a complete Design DNA JSON — every field populated, no empty strings 6. After output, ask: "Want to adjust any values before using this for generation?"

**Analysis approach per dimension:**

Dimension 1: design_system

• **color**: Do not estimate hex values by eye — perceived colors drift toward familiar palette defaults (often by a ΔE of 10+). When the reference is an image file, measure instead. Resolve `SKILL_ROOT` to the absolute directory containing this `SKILL.md`; never assume the current project directory contains the skill's `scripts/` folder. Use absolute paths for the reference and output, and keep one uniquely named measurement file per reference:

  npm install --prefix "$SKILL_ROOT/scripts" --silent
  node "$SKILL_ROOT/scripts/measure-colors.mjs" "$REFERENCE_IMAGE" > "$MEASUREMENT_JSON"

Use the measured hexes verbatim in the DNA JSON: map the `background` role to `surface.background`; map `text` to the end of `neutral.scale` that contrasts with the measured background and document that foreground use in `neutral.usage`; and map `accent` to `accent.hex`. Keep both the measured palette and its `measurement` configuration in `design_system.color.measured_palette` and `design_system.color.measurement` so verification can reuse the same clustering configuration. Coverage values are fractions from `0` to `1`. Only fall back to visual sampling when measurement is impossible (for example, a URL-only reference that cannot be screenshotted). Choose primary and secondary colors by semantic role, use accent for CTA emphasis, and order the neutral scale from lightest to darkest regardless of theme.

• **typography**: Identify font families by visual characteristics (geometric, humanist, serif class). Estimate scale ratios from heading/body size relationships.
• **spacing**: Assess density by element proximity. Measure rhythm by section gap consistency.
• **layout**: Identify grid by content alignment patterns. Note max-width, column count, asymmetry.
• **shape**: Measure border-radius by comparing to element height. Note border and divider presence.
• **elevation**: Classify shadow softness, spread, and layering approach.
• **motion**: If observable (video/interactive), note easing curves and duration feel.

Dimension 2: design_style

• Synthesize holistic impressions — mood, personality, composition strategy
• Compare against genre archetypes (SaaS, editorial, brutalist, etc.)
• Note ornamentation level and whitespace philosophy

Dimension 3: visual_effects

• **From code**: Scan for `<canvas>`, WebGL contexts, Three.js/Pixi.js imports, GSAP/Lottie usage, custom shaders, IntersectionObserver scroll triggers, SVG `<animate>` elements
• **From screenshots**: Describe visible effects that go beyond standard CSS — glowing particles, 3D object renders, noise textures, gradient animations, parallax depth, cursor trails, text distortions, glassmorphic surfaces. Note these in `composite_notes` when exact implementation can't be determined.
• **From video/interaction demos**: Note scroll behaviors, hover distortions, transition choreography, loading sequences
• Set `enabled: false` for any effect category not present in the reference
• Rate `overview.effect_intensity` and `overview.performance_tier` based on what's observ