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NulightJensNulightJens/jensai-skills/extract-design/SKILL.md

extract-design

Skill9 starsChanged 3 months agoMITView on GitHub

Reverse-engineer a DESIGN.md file (per the google-labs-code/design.md spec) from an existing source — HTML page, screenshot, live URL, or design exports. Produces YAML token frontmatter (colors, typography, rounded, spacing, components) plus prose sections (Overview, Colors, Typography, Layout, Elevation & Depth, Shapes, Components, Do's and Don'ts) so the visual identity becomes portable across coding agents. Use when the user says "extract design," "make a DESIGN.md from this page," "/extract-design," "turn this into design.md," "reverse engineer the design system from this site/HTML/screenshot," or asks to capture an existing visual identity in a structured, AI-readable format.

7 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

11 rules. 0 are common, 5 are distinctive, and 6 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  • could be automatic: a setting could enforce it
  1. Distinctive:

    Read references/spec.md for the full normative spec.

    line 27
  2. Very specific:

    Use scripts/extract_primitives.py to harvest raw values from the source.

    line 43
  3. Very specific:

    Run this from the skill's own directory, or prefix the script with the install path (for example …

    line 49
  4. Distinctive:

    After writing, audit the file against the spec:

    line 81
  5. Very specific:

    Every token reference ({colors.foo}) resolves to a defined token

    line 84
  6. Very specific:

    All component backgroundColor/textColor pairs hit WCAG AA (4.5:1) — flag any that do not

    line 85
  7. Distinctive:

    Every color token is referenced by at least one component or is a documented role color

    line 86
  8. Very specific:

    If the user has npx available, validate with the official linter:

    line 89
  9. Very specific:

    Extract, don't invent: Every token must trace back to evidence in the source.

    line 99
  10. Distinctive:

    One DESIGN.md per visual identity: If sources differ, produce separate files.

    line 104
  11. Distinctive:

    Write the file to disk. Confirm the path back to the user with one sentence on what was extracted.

    line 108

“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

extract-design

Turn an existing visual identity into a DESIGN.md file that conforms to the google-labs-code/design.md spec — YAML token frontmatter plus markdown rationale.

When to use

User asks to:

  • Extract a design system from one or more HTML files
  • Turn a live URL or screenshot into a DESIGN.md
  • Reverse-engineer tokens from a Figma export, Webflow export, or static site
  • Generate DESIGN.md so other agents can rebuild the same visual identity

What you produce

For each source the user provides, output one DESIGN.md file. If the user gives multiple sources representing distinct designs, produce one DESIGN.md per source and name them descriptively (DESIGN-<source-slug>.md). Default output location: same directory as the source, unless the user specifies otherwise.

Each DESIGN.md must contain:

  1. YAML frontmatter — name, optional description, then colors, typography, rounded, spacing, components (in that order). All values must follow the spec types (Color = #hex, Dimension = <num>px|em|rem, Typography = object).
  2. Markdown body — ## Overview, ## Colors, ## Typography, ## Layout, ## Elevation & Depth, ## Shapes, ## Components, ## Do's and Don'ts, in that order. Skip a section only if the source provides no signal for it.

Read references/spec.md for the full normative spec. Read references/example-atmospheric-glass.md, references/example-paws-and-paths.md, or references/example-totality-festival.md when you need a calibration example for the prose voice.

Workflow

1. Identify the source(s)

Sources may be:

  • Local HTML file(s) — most common
  • Local CSS file(s)
  • Live URL — fetch with WebFetch or Playwright MCP
  • Screenshot — Read the image, then describe tokens visually
  • Multiple files representing one design — merge before extracting
  • Multiple files representing different designs — extract separately

2. Run the primitive extractor (HTML/CSS sources only)

Use scripts/extract_primitives.py to harvest raw values from the source. The script returns a JSON object with frequency-ranked candidates for colors, font-families, font-sizes, font-weights, border-radii, spacing values, and shadows.

python3 scripts/extract_primitives.py <path-to-html-or-css> [more-paths...]

Run this from the skill's own directory, or prefix the script with the install path (for example <path-to-skill>/scripts/extract_primitives.py).

The script is the data-gathering step, not the answer. Its output is a denormalized inventory; you must normalize it into a token system. Do not paste the raw output into the DESIGN.md.

For non-HTML sources (screenshots, live URLs you cannot scrape), skip the script and observe directly.

3. Normalize into a token system

Apply the heuristics in references/extraction-heuristics.md to convert the raw inventory into a coherent token system:

  • Pick a name that captures the brand personality (e.g., "Atmospheric Glass," "Heritage," "Boston Newsroom").
  • Reduce the color inventory to a small palette (primary, secondary, tertiary, neutral, plus surface/on-surface roles). Do not export every observed color — pick the ones that carry semantic weight, then express variants as references.
  • Build a typography scale of 6–12 levels using the most-used font families and sizes. Name them semantically (display-lg, headline-lg, body-md, label-sm).
  • Build a spacing scale (4 / 8 / 16 / 24 / 32 / 64 are common bases). Quantize raw values to the nearest scale step.
  • Build a rounded scale from the observed border-radii (typically none, sm, md, lg, full).
  • Pick 4–10 components that anchor the system: button-primary, button-secondary, button-ghost, card, input-field, plus any obvious patterns (testimonial-card, hero-cta, pricing-card, etc.). Each component must reference tokens ({colors.primary}), not literal values where a token exists.

4. Write prose sections

Voice: confident, specific, present tense. Match the cadence in the calibration examples — short paragraphs, descriptive color names ("Boston Clay," "Limestone"), explicit why behind every choice.

  • Overview — 2–4 sentences naming the personality, target feel, and emotional register.
  • Colors — bullet each named color with hex + role + usage rule.
  • Typography — explain font choice rationale, then describe each tier.
  • Layout — grid model, base unit, container behavior.
  • Elevation & Depth — how depth is conveyed (shadows, borders, blur, tonal layers).
  • Shapes — corner radius philosophy + how it varies by component type.
  • Components — describe the patterns referenced by component tokens.
  • Do's and Don'ts — 4–8 actionable rules. These are guardrails, not platitudes.

5. Validate

After writing, audit the file against the spec:

  • Section order matches: Overview → Colors → Typography → Layout → Elevation & Depth → Shapes → Components → Do's and Don'ts
  • Every token reference ({colors.foo}) resolves to a defined token
  • All component backgroundColor/textColor pairs hit WCAG AA (4.5:1) — flag any that do not
  • Every color token is referenced by at least one component or is a documented role color
  • name field is set; it is the first signal an agent reads

If the user has npx available, validate with the official linter:

npx @google/design.md lint <output-path>

This is optional — your manual audit catches most issues. Only suggest the linter if the user asks for verification or the file is going into production.

Key principles

  • Extract, don't invent. Every token must trace back to evidence in the source. If the source lacks a tertiary color, do not invent one.
  • Tokens over literals. Inside components, prefer {colors.primary} over #1A1C1E. Literal values in components are a smell.
  • Compress, don't enumerate. A page with 47 distinct grays still needs only 5–7 surface tokens. Pick the load-bearing ones.
  • Name like a designer. boston-clay beats red-1. The prose should make the names feel inevitable.
  • Prose explains why. Token values are the what; sections like Overview and Do's and Don'ts justify them.
  • One DESIGN.md per visual identity. If sources differ, produce separate files. Do not merge incompatible systems.

Output format

Write the file to disk. Confirm the path back to the user with one sentence on what was extracted. Do not paste the full DESIGN.md back unless the user asked to see it inline.

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