Measure adoption with real data

"We think we have 60% adoption" isn't good enough. Buoy gives you the actual numbers.

Get started free

What You'll Measure

Component Coverage

Percentage of components using design system primitives vs custom implementations

Token Adoption

Percentage of style values using design tokens vs hardcoded values

Per-Directory Breakdown

See which parts of your codebase are adopting fastest (and slowest)

Component Usage

Track which design system components are used most, and which are ignored

Trend Tracking

See adoption improve over time with historical charts (Pro feature)

Team Attribution

Track adoption by team or code owner for targeted improvement

See it in action

buoy-cli
$
Design System Coverage
═══════════════════════════════════════
Components: 47% ████████░░░░░░░░░░
Tokens: 63% ████████████░░░░░░
Overall: 52% ██████████░░░░░░░░
By Source:
├─ src/components/ 78% ███████████████░
├─ src/features/ 34% ██████░░░░░░░░░
└─ src/pages/ 23% ████░░░░░░░░░░░
Component Usage:
├─ Button 156 uses
├─ Card 89 uses
└─ Input 12 uses

Why Coverage Matters

Without Metrics

  • "We think adoption is around 60%"
  • No way to prove ROI of design system
  • Can't identify which teams need help
  • Don't know if things are improving

With Buoy

  • "We have 47% component coverage, 63% token adoption"
  • Show leadership exactly where you stand
  • See src/pages/ is at 23% — focus there
  • Track improvement: +8% this month

Ready to catch design drift?

Free. Open source. No signup required.

Related Features

CI Integration

Enforce coverage thresholds in your CI pipeline

GitHub Action

Get coverage reports on every PR

Drift Detection

Find what's causing low coverage