Reusable Token-to-Code Pipelines for Dual-Theme Design Systems

Using Figma token specs and Claude Code build loops to derive production-ready components

  • spec-driven development
  • design ops
  • claude code

Created for one of India’s largest streaming and DTH platforms (under NDA; a flexible drawer component is shown here to demonstrate the methodology).

overview

A scalable design system engine built for a DTH platform

Built a spec-driven generation pipeline in Claude Code that converts hand-built Figma token systems into verified React components.

challenge

Fragmented architecture and code-design drift across multi-product surfaces

An enterprise product ecosystem lacked a unified design system, causing code-design drift, duplicate component variants, and inconsistent thematic styling.

Light and dark theme product surfaces showing fragmented UI patterns

try it

Try it. Reconfigure the drawer and watch it rebuild.

Theme

Content

footer

Body

show checkbox
show radio button
show toggle

approach

Automating component generation through closed-loop rules and AI specs

Rather than building components manually one by one, I engineered a reusable spec-and-generation pipeline. By feeding hand-crafted Figma token schemas and strict system constraints CLAUDE.md into Claude Code, the pipeline derives verified React components, Storybook stories, and accessibility checks directly from the design spec.

Spec-driven pipeline diagram from Figma source through tokens, specs, rules, generate, and ship
  • Token Architecture: Hand-built primitive and semantic tokens in Figma; exported to tokens.json and tokens.css with native light/dark mode support in a single layer.

  • System Rules CLAUDE.md:

    Strict constraints injected into every generation pass—zero hardcoded values, strict token usage, single-file component outputs, and mandatory dual-theme compliance.

  • Reusable Skill (component-from-spec): Encapsulated design rules into a reusable Claude routine that handles component scaffolding, Storybook story generation, and accessibility checks.

  • Verification Loop: Visual and token diffing against Figma reference specs, logging deltas directly to the spec until achieving 100% parity.

Build and correction loop diagram: generate, render, compare, log deltas, refine until parity

solution

Replacing static variant sprawl with one flexible API

To demonstrate the pipeline at scale, I consolidated an entire family of static drawers into a single component API. By leveraging flexible props and content slots, this single implementation powers every drawer use case across the application.

variantbody
messageheader + buttons
confirmationstatus icon + header + buttons
listheader + cards (icon + title + subtitle)
selectionheader + description + radio options + buttons
editheader + text input + buttons (keyboard aware)
metadataheader + cards

impact & system governance

Enforcing zero-hardcode quality, built-in accessibility, and repeatable scale

  • 100% Token Compliance: Programmatically verified zero hardcoded colours across generated codebases using automated search scripts.

  • Reduced Code Surface: Consolidated a full variant family into a single configurable API, significantly lowering governance and maintenance overhead.

  • In-Contract Accessibility & Theming: Baked native accessibility and dual-theme switching directly into the component spec, ensuring first-pass compliance without retrofits.

  • Upstream Quality Control: Identified and resolved pre-existing Figma token discrepancies at the build-log stage, catching design debt before it reached production.

  • Repeatable Architecture: Standardised the spec-and-loop framework across the library, establishing a scalable blueprint for all future component generation.