design-extract — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited design-extract (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Extract a live website's design system and write the results into brain/brand-guide/brand-guide.md.
Uses designlang — a headless-browser tool that reads the design system off the live DOM and emits structured tokens.
designlang CLI (installed automatically if missing)Ask the user:
What website URL should I extract the design system from?
If they already provided a URL in their message, confirm it.
Optional follow-ups:
--dark flag)--cookie flag)Check if designlang is available:
command -v designlang || npm list -g designlang 2>/dev/nullIf not installed, use npx to avoid global install permission issues:
npx -y designlang <url> ...Alternatively, if the user prefers a global install:
npm i -g designlangRun designlang's brand subcommand against the URL. This generates a full editorial brand-guidelines document (13 chapters, print-ready) along with design tokens:
designlang brand <url> --out ./design-extract-output --name brand --verboseIf the brand subcommand fails or produces insufficient output, fall back to the default extraction:
designlang <url> --out ./design-extract-output --name brand --full --verboseFlags to consider based on user input:
--dark — if they want dark mode tokens--depth 2 — if they want to crawl beyond the homepage--cookie "name=value" — if pages require authRead the generated files from ./design-extract-output/:
Extract and organize:
Present the extracted design system in a summary table format:
Extracted from: [url]
Colors:
Primary Background #1a1a2e
Card Background #16213e
Primary Text #ffffff
Body Text #a8b2d1
Primary Accent #0f3460 (buttons, CTAs)
Secondary Accent #e94560 (highlights)
Typography:
Headings Inter 700 fallback: system-ui
Body Inter 400 fallback: system-ui
Code JetBrains Mono 400 fallback: monospace
Spacing: 4px base unit (4, 8, 12, 16, 24, 32, 48, 64)
Buttons:
Primary #0f3460 bg, #fff text, 8px radius
Secondary transparent bg, #0f3460 borderAsk: "Does this look right? Anything to adjust before I write the brand guide?"
Write the extracted values into brain/brand-guide/brand-guide.md, replacing [FILL IN] placeholders with real values. Preserve the template structure exactly — only replace placeholders.
If the extraction found values not covered by the template (gradients, shadows, z-index), add them as new sections at the bottom following the same formatting conventions.
Remove the design-extract-output/ directory:
rm -rf ./design-extract-outputTell the user:
Brand guide updated at brain/brand-guide/brand-guide.md. All visual skills (brand-design, web-design, hubspot-email, etc.) will now use these values.If brand-voice.json contained tone/voice data, mention:
I also found voice/tone data. Run /tone-mapping to build a full voice profile.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.