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design-token-audit

The design-token-audit skill systematically evaluates how consistently design tokens are used throughout a product, identifying hard-coded values, gaps in token coverage, redundant tokens, and areas of inconsistency. Use this skill when implementing or improving a design token system, conducting periodic health checks on token adoption, preparing migration strategies from ad-hoc styling to token-based design, or investigating why design inconsistencies persist across a product despite having tokens defined.

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git clone --depth 1 https://github.com/Owl-Listener/designer-skills /tmp/design-token-audit && cp -r /tmp/design-token-audit/designer-toolkit/skills/design-token-audit ~/.claude/skills/design-token-audit
Después abre una sesión nueva de Claude Code; el skill carga automáticamente.

SKILL.md

# 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