design-system-audit

Assess design system AI readiness by scanning your codebase against a 5-ring, 6-tier maturity model. The audit scores token systems, component architecture, and design-code bridges to identify gaps and generate a tailored action plan.

A design system maturity model for AI-driven frontend development evaluates infrastructure across 5 rings: Foundation, Design-Code Bridge, AI Automation, Quality & Governance, and Portability, scoring each from tier 0 to 5 to quantify AI code generation capacity.

Audit component library and token systems by analyzing design-code bridges and architecture against AI automation requirements. This process identifies structural gaps and outputs a prioritized roadmap with quick wins tailored to your team size and framework.

You can evaluate design system portability and governance tailored to your specific framework and team size. The assessment scores quality and portability rings, producing a targeted report with actionable steps aligned to your development goals.

The design-code bridge between Figma and a component library directly impacts AI readiness by determining how efficiently tokens and components translate into code. Analyzing this bridge identifies bottlenecks in automated frontend development workflows.

Limitations of auditing a design system for AI automation include the dependence on accurate codebase analysis and user-provided context regarding team size and goals; incomplete token systems or poorly structured component libraries may yield lower maturity scores requiring extensive remediation.