Design tokens are not a theming solution. They are a communication protocol. The distinction matters because it changes what you design for: not just visual consistency across products, but the ability for any system, human or machine, to understand and apply the design intent.
Most token architectures are built for the first problem. A global color palette, a type scale, a spacing system. These get encoded as variables and consumed by components. The system works until it needs to do something the token schema didn't anticipate. Then someone overrides it, the override propagates, and the architecture starts to drift.
The Semantic Layer Problem
Raw values (hex codes, pixel measurements, named weights) are not semantically meaningful to a system that needs to reason about design decisions. To say that --color-neutral-700 should be used for body text requires a human to know that convention and remember to apply it.
Semantic tokens solve part of this. --color-text-body is more meaningful than --color-neutral-700. But most semantic token layers stop at naming. They don't describe why the token exists, what constraints govern its use, or what it means for the interface to apply it correctly.
Tokens as Agent-Readable Spec
When the consuming system is not just a component but an intelligent workflow (a code generation agent, a design-to-code pipeline, a constraint engine), the token schema needs to carry more information. Not just the value and the semantic name, but the intent, the constraints, and the relationships between tokens.
What This Requires
Tokens that carry their own documentation. Descriptions that explain the design decision, not just label the output. A schema architecture that makes the intent legible to any system that needs to apply it.
This is the difference between a token system that supports human designers and one that supports the full pipeline, from Figma to code to deployed interface. The architecture has to be designed for both from the start.
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