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design-token-audit

Audit how a product uses design tokens, shared settings for visual properties such as color and spacing. Identify hard-coded values, inconsistent usage, and missing tokens, then recommend replacements and prioritize migration work.

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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).

Run score Not tested

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Good for

  • Finding hard-coded colors and spacing values
  • Checking duplicate or deprecated token usage
  • Identifying gaps in existing design tokens
  • Prioritizing token replacements and migration work

Files included (1)

  • SKILL.md1.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

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