Design Audit Orchestration

SkillMedia

Use this skill when aggregating design audit findings across multiple dimensions, deduplicating related issues, or synthesizing results into executive summaries with remediation roadmaps

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Design Audit Orchestration skill

What this skill tells your AI

The instructions your AI receives, as published by tan-yong-sheng/ai-vision-mcp in plugins/design-eval/skills/design-audit-orchestration/SKILL.md and read by ahel’s review.

Guidance for orchestrating comprehensive design audits across multiple dimensions and synthesizing findings into actionable reports.

When to Use

Use this skill when:

  • Aggregating findings from multiple analysis dimensions (heuristics, accessibility, visual, components)
  • Deduplicating and cross-referencing related findings
  • Prioritizing findings by severity and impact
  • Creating executive summaries and remediation roadmaps
  • Synthesizing insights that span multiple dimensions

Multi-Dimensional Analysis Framework

Design audits analyze 4 independent dimensions:

1. Usability Heuristics (Nielsen's 10)

  • Visibility of system status
  • Match between system and real world
  • User control and freedom
  • Error prevention and recovery
  • Recognition vs recall
  • Flexibility and efficiency
  • Aesthetic and minimalist design
  • Help and documentation
  • Error messages
  • Emergency exits

2. Accessibility Compliance (WCAG)

  • Color contrast and visual perception
  • Keyboard navigation and focus management
  • Semantic HTML and heading hierarchy
  • ARIA patterns and landmarks
  • Form accessibility and error handling
  • Motion and animation preferences
  • Text alternatives and captions

3. Visual Consistency (Design Tokens)

  • Color palette usage and deviations
  • Typography consistency (fonts, sizes, weights)
  • Spacing patterns (margins, padding, gaps)
  • Shape and border radius consistency
  • Shadow and elevation patterns
  • Motion and transition properties

4. Component Reusability (Design System)

  • Component duplication and near-duplicates
  • Composition patterns and nesting depth
  • API/prop consistency across similar components
  • Naming conventions and clarity
  • Documentation completeness

Finding Aggregation Patterns

Deduplication Strategy

Same issue found by multiple dimensions:

  • Heuristic + Accessibility: "Error message not visible" (heuristic: error prevention) + "error message lacks color contrast" (accessibility: WCAG 1.4.3)
  • Visual + Component: "Button color inconsistent" (visual: color token) + "button component has multiple implementations" (component: duplication)

Action: Merge into single finding with cross-dimensional impact

Cross-Referencing Strategy

Finding in one dimension affects another:

  • Accessibility finding: "Form labels not associated" → impacts Heuristic: "Recognition vs recall" (users can't remember what field is what)
  • Component finding: "Button component duplicated" → impacts Visual: "Inconsistent button colors" (each implementation uses different color)

Action: Link findings and explain cascading impact

Severity Calculation

Combine severity from multiple dimensions:

  • Critical: Blocks user task completion (accessibility + heuristic)
  • High: Significantly impacts user experience (visual + component)
  • Medium: Noticeable but workaround exists (single dimension)
  • Low: Polish/refinement (minor inconsistency)

Synthesis Patterns

Executive Summary Structure

  1. Overall Health Score (0-100)

    • Weighted average across dimensions
    • Heuristics: 30% (user experience)
    • Accessibility: 40% (compliance + inclusion)
    • Visual: 15% (consistency)
    • Components: 15% (maintainability)
  2. Critical Issues (top 3-5)

    • Issues blocking user tasks
    • Compliance violations
    • High-impact duplications
  3. Dimension Breakdown

    • Summary for each dimension
    • Key findings per dimension
    • Dimension-specific recommendations
  4. Remediation Roadmap

    • Phase 1: Critical (accessibility, blocking issues)
    • Phase 2: High (visual consistency, component consolidation)
    • Phase 3: Medium (heuristics refinement)
    • Phase 4: Low (polish)

Remediation Roadmap Template

Phase 1: Critical (Week 1-2)
- [Finding 1]: [Remediation] - Effort: [hours]
- [Finding 2]: [Remediation] - Effort: [hours]

Phase 2: High (Week 3-4)
- [Finding 3]: [Remediation] - Effort: [hours]

Phase 3: Medium (Week 5-6)
- [Finding 4]: [Remediation] - Effort: [hours]

Phase 4: Low (Ongoing)
- [Finding 5]: [Remediation] - Effort: [hours]

Output Structure

{
  "audit_summary": {
    "overall_health_score": 72,
    "total_findings": 24,
    "critical_count": 3,
    "high_count": 8,
    "medium_count": 10,
    "low_count": 3
  },
  "dimension_summaries": {
    "heuristics": {
      "score": 68,
      "key_findings": [...],
      "recommendations": [...]
    },
    "accessibility": {
      "score": 65,
      "key_findings": [...],
      "recommendations": [...]
    },
    "visual_consistency": {
      "score": 82,
      "key_findings": [...],
      "recommendations": [...]
    },
    "components": {
      "score": 75,
      "key_findings": [...],
      "recommendations": [...]
    }
  },
  "cross_dimensional_insights": [
    {
      "title": "Error handling affects both heuristics and accessibility",
      "findings": ["heuristic-5", "accessibility-3"],
      "impact": "Users cannot recover from errors effectively"
    }
  ],
  "remediation_roadmap": [
    {
      "phase": 1,
      "priority": "critical",
      "items": [...]
    }
  ]
}

Signals

GitHub stars
78
Forks
16
Last commit
Apr 2026
Advanced
Catalog kind
skill
Gateway key
design-audit-orchestration
Source
github.com/tan-yong-sheng/ai-vision-mcp