TokenFlow was developed during my work as a Design System Lead at HP Indigo, in response to challenges common to large-scale design systems. As systems grow across multiple teams, products, and platforms, maintaining clarity and control over thousands of variables becomes a critical issue.
Most design platforms - including Figma - provide limited visibility into how tokens relate to each other. Teams can define variables, aliases, and modes, but they cannot easily see how those relationships behave or change over time.
TokenFlow was built to fill that gap.
Role:
Research, Development and deployment.
Industry:
Design system management
Duration:
2025
Challenges
In mature design systems, the number of tokens and aliases grows exponentially. DS managers and developers often face:
Lack of visibility: No way to trace variable dependencies across layers, components, or modes.
Redundancy and inconsistency: Duplicate tokens and conflicting alias chains that cause unpredictable behavior.
Limited QA control: Manual validation of color and mode consistency is slow and error-prone.
Versioning risks: Changes to core tokens may unintentionally affect multiple components or themes.
The challenge was how to manage and track existing tokens.
My Approach
TokenFlow was envisioned as a governance and analytics layer for any large design system - a tool that exposes the invisible relationships between design tokens, variables, and components.
Core Goals:
Visualize token relationships and dependencies across all layers.
Provide multi-mode support (Light, Dark, and any custom brand modes).
Trace variable connections from primitive to specified uses.
Detect duplicates, orphans, and circular references.
Support DS managers in maintaining clean, scalable variable structures.
Results
Originally developed as part of my role at HP Indigo, TokenFlow quickly proved its value beyond that context.
It serves as a universal governance tool for any DS team aiming to scale responsibly.
Benefits observed:
Improved transparency and maintainability of variable structures.
Faster QA validation through visual analysis.
Early detection of redundant or conflicting tokens.
Stronger collaboration between design and development teams through shared visibility.
