Design System Problems

Token Consolidation Strategy

January 15, 2026 • 5 min read

Token Consolidation Strategy

A token consolidation strategy systematically reduces token proliferation by identifying and merging duplicate or redundant tokens. As token systems grow, duplicates accumulate through parallel development, legacy migrations, and insufficient governance. Consolidation reclaims simplicity and improves maintainability.

What Is Token Consolidation

Token consolidation is the process of reducing token count by merging tokens that serve the same purpose or contain the same values. This includes eliminating exact duplicates, merging near-duplicates, and creating semantic tokens that replace multiple specific-use tokens.

Consolidation improves the system by reducing cognitive load, simplifying maintenance, and establishing clearer token purposes.

How Token Consolidation Works

Identifying consolidation opportunities:

Exact value duplicates:

/* Before: Same value, different tokens */
{
  "header-bg": "#ffffff",
  "sidebar-bg": "#ffffff",
  "card-bg": "#ffffff",
  "modal-bg": "#ffffff"
}

/* After: Single semantic token */
{
  "color.surface.primary": "#ffffff"
}

Near-value duplicates:

/* Before: Nearly identical values */
{
  "blue-primary": "#3B82F6",
  "action-blue": "#3B83F6",  // 1 digit different
  "brand-blue": "#3B82F7"    // Likely typo
}

/* After: Single authoritative value */
{
  "color.brand.primary": "#3B82F6"
}

Purpose-equivalent tokens:

/* Before: Different names, same purpose */
{
  "btn-padding": "16px",
  "button-spacing": "16px",
  "interactive-padding": "16px"
}

/* After: Single purposeful token */
{
  "spacing.interactive.md": "16px"
}

Consolidation process:

  1. Audit for duplicates and near-duplicates
  2. Analyze usage patterns
  3. Design consolidated tokens
  4. Create deprecation mapping
  5. Migrate consumers
  6. Remove deprecated tokens

Key Considerations

Common Questions

How should duplicate tokens be identified?

Identification combines automated detection with human judgment.

Automated value analysis:

function findDuplicates(tokens) {
  const valueMap = new Map();
  const duplicates = [];

  tokens.forEach(token => {
    const normalizedValue = normalizeValue(token.value);
    const existing = valueMap.get(normalizedValue);

    if (existing) {
      duplicates.push({
        value: normalizedValue,
        tokens: [...existing, token.name]
      });
      valueMap.set(normalizedValue, [...existing, token.name]);
    } else {
      valueMap.set(normalizedValue, [token.name]);
    }
  });

  return duplicates.filter(d => d.tokens.length > 1);
}

Near-duplicate detection:

function findNearDuplicates(colorTokens, threshold = 5) {
  const nearDuplicates = [];

  for (let i = 0; i < colorTokens.length; i++) {
    for (let j = i + 1; j < colorTokens.length; j++) {
      const distance = colorDistance(
        colorTokens[i].value,
        colorTokens[j].value
      );
      if (distance < threshold) {
        nearDuplicates.push({
          tokens: [colorTokens[i].name, colorTokens[j].name],
          distance
        });
      }
    }
  }

  return nearDuplicates;
}

Usage pattern analysis:

Token usage review:
- header-bg: 12 usages (headers only)
- card-bg: 45 usages (cards, modals, dropdowns)
- sidebar-bg: 8 usages (sidebars only)

Insight: card-bg is used broadly;
others might consolidate into it or a new semantic token.

How should consolidation decisions be made?

Decisions require understanding token purposes and usage contexts.

Decision criteria:

Consolidate when:
- Tokens have identical values
- Tokens serve the same semantic purpose
- Usage contexts are equivalent
- Maintaining separate tokens adds no value

Keep separate when:
- Same value but different semantic meaning
- Likely to diverge in the future
- Different contexts with different requirements
- Accessibility requires distinction

Example decision:

Candidate: header-bg, card-bg, sidebar-bg

Analysis:
- All are #ffffff (white)
- All represent "surface" concept
- No indication they should differ

Decision: Consolidate to color.surface.primary

Exception case: error-bg (#fff) vs success-bg (#fff)
- Same value but different semantic meaning
- Might diverge (error could become light red)
- Keep separate: color.status.error.surface, color.status.success.surface

How should governance prevent re-proliferation?

After consolidation, governance prevents returning to the previous state.

Contribution guidelines:

## Adding Tokens

Before adding a new token:
1. Check if an existing token serves the purpose
2. Search for tokens with similar values
3. Consult token catalog documentation

New tokens require:
- Justification for why existing tokens don't work
- Review by design system team
- Documentation of intended use

Automated checks:

// CI check for potential duplicates
function checkNewTokens(newTokens, existingTokens) {
  const warnings = [];

  newTokens.forEach(newToken => {
    const similar = findSimilarTokens(newToken, existingTokens);
    if (similar.length > 0) {
      warnings.push({
        token: newToken.name,
        similar: similar.map(s => s.name),
        message: 'Review: similar tokens exist'
      });
    }
  });

  return warnings;
}

Regular audits:

Quarterly token audit:
- Run duplicate detection
- Review token growth rate
- Identify consolidation opportunities
- Update governance if patterns emerge

Summary

Token consolidation strategy reduces token proliferation by merging duplicates and near-duplicates. Automated detection identifies candidates through value analysis and near-duplicate comparison. Human judgment determines which candidates should consolidate based on semantic purpose and usage context. Post-consolidation governance through contribution guidelines, automated checks, and regular audits prevents re-proliferation.

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