Design Dna

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

1. 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: analyze visual properties directly
• If URL: fetch and analyze the page's visual design

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

Analysis approach per dimension:

Dimension 1: design_system

• color: Extract dominant palette via visual sampling. Primary by area dominance, secondary by supporting role, accent by CTA usage. Map neutral scale from lightest background to darkest text.
• 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 `, WebGL contexts, Three.js/Pixi.js imports, GSAP/Lottie usage, custom shaders, IntersectionObserver scroll triggers, SVG ` 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 observed

Phase 3: Generate — Apply DNA to Content

When the user provides DNA JSON + content to design:

1. Read [references/generation-guide.md](references/generation-guide.md)
2. Parse the DNA JSON and extract all tokens across three dimensions
3. Build CSS custom properties from design_system values
4. Apply design_style qualitative fields to guide subjective design decisions
5. When the design needs assets or source materials, fetch them from the original source whenever possible. If the user provided a URL, retrieve the real asset from that URL instead of recreating, approximating, or substituting it.
6. Implement visual_effects using appropriate technologies:

• Lightweight effects → CSS animations, SVG, vanilla JS
• Medium effects → Canvas 2D, GSAP, Lottie
• Heavy effects → Three.js, custom GLSL shaders, Pixi.js

1. Generate the design output (default: self-contained HTML with inline CSS/JS)
2. Run quality checks from the generation guide

If the user provides only content without DNA JSON, ask whether to:

• Analyze a reference first (go to Phase 2)
• Use a described style (extract DNA from description, then generate)

Phase Combinations

Users may invoke any combination:

• Phase 1 only: "Show me the design structure/schema"
• Phase 2 only: "Analyze this design" (with images/links)
• Phase 2 → 3: "Analyze this design and build me a landing page in the same style"
• Phase 1 → 2 → 3: Full pipeline
• Phase 3 only: User already has DNA JSON

Detect which phase(s) are needed from context and execute accordingly.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: zanwei
• Source: zanwei/design-dna
• License: MIT

Install and usage instructions live in the source repository linked above.