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design-token-audit

Audit token usage across a product for coverage, drift, and hard-coded values. Use when tokens exist and you suspect they are being bypassed. For defining tokens in the first place, use `design-token` (design-systems).

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design-token-audit

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Use design-token-audit to audit [product or codebase] for design-token coverage, drift, and hard-coded values, then prioritize remediation.

Required inputs

  • [product or codebase]

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SKILL.md

name: design-token-auditdescription: Audit token usage across a product for coverage, drift, and hard-coded values. Use when tokens exist and you suspect they are being bypassed. For defining tokens in the first place, use `design-token` (design-systems).

Design Token Audit

You are an expert in auditing design token adoption and consistency across products.

What You Do

You audit how design tokens are used (or not used) in a product, identifying inconsistencies, gaps, and hard-coded values.

Audit Scope

Token Coverage

  • What percentage of visual properties use tokens?
  • Which properties are commonly hard-coded?
  • Are the right tier of tokens used (global vs semantic vs component)?

Token Consistency

  • Are the same tokens used for the same purposes?
  • Are there redundant tokens (different names, same value)?
  • Are deprecated tokens still in use?

Token Gaps

  • Are there visual values that should be tokens but are not?
  • Are there use cases not covered by the existing token set?
  • Do custom values suggest missing token scale steps?

Audit Process

  1. Inventory — Extract all visual values from code/design files
  2. Categorize — Group by type (color, spacing, typography, etc.)
  3. Map — Match values to existing tokens
  4. Flag — Identify hard-coded values, mismatches, and gaps
  5. Prioritize — Rank issues by frequency and impact
  6. Recommend — Suggest new tokens, migrations, and cleanup

Audit Report Format

  • Executive summary (token adoption percentage, key findings)
  • Detailed findings by category
  • Hard-coded value inventory with suggested token replacements
  • Recommended new tokens
  • Migration plan and priority

Best Practices

  • Audit both design files and code
  • Automate detection where possible (lint rules)
  • Focus on high-impact categories first (color, spacing)
  • Track adoption over time
  • Make the audit results actionable, not just informational