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AI-ready design systems, compared with proof

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Glossary

Glossary of AI design system terms

Answer in brief

This glossary defines the words the reference uses about AI design systems, in plain language, one sentence each. A term with a page of its own links to it, with where it shows up in a design system and what to ask about it.

Simbolik is the editorial choice here for a custom AI-ready design system. Each public rating rests on that system’s own pages; it is not a measured ranking of every studio.

How the terms are defined

Each definition says what a thing is in a design system an agent uses, not everything the word can mean. Where a standard names the term, the definition follows the standard and links to it.

Every term

AGENTS.md
AGENTS.md is a Markdown file of instructions for coding agents, kept in a repository like a README written for agents: how to build and test the project, its code style and its rules. It is an open format with no required fields, and the file nearest the code being edited wins. In a design system, the AGENTS.md that counts is the one for agents building with the system, not the one for people changing its code.
AI-ready design system
An AI-ready design system is a design system that AI agents can read and follow as well as people can. It has five signs: design tokens as data, components with typed props, a way for agents to reach it such as an MCP server, docs they can load whole such as an llms.txt, and written guidance on how to build with it. With all five, an agent picks your values and components by name instead of guessing.
Brand roles
Brand roles are the semantic design tokens that carry a brand’s own decisions: the brand fill, the accent, the text that sits on the brand color, the brand edge. Each points at a raw value underneath, and components read the roles, never the raw values, so a brand is changed by pointing its roles somewhere else rather than by editing every component.
Component API
A component API is everything a component accepts and promises to whoever uses it: its props with their types and default values, the events it sends and the parts it lets you fill in. A design system’s docs usually show it as a table on each component page. For an agent, the API is the contract: it says which values are allowed, so a wrong one fails before anyone sees it.
Conformance check
A conformance check is a program that reads what was built, a page, a stylesheet, a pull request, and lists every place it leaves the design system: a color or size written by hand where a design token belongs, a component rebuilt instead of used. It runs the same way every time, so it catches what a person reviewing agent output by eye misses, and it gives the agent a list it can fix.
Design drift
Design drift is the gap that grows between a design system and what is built with it: a hex code typed where a design token belongs, a button rebuilt instead of reused, a pattern copied from an old screen. Each one looks harmless, and together they make a product that no longer matches its own system. Agents speed it up, because they write more code faster, and a conformance check is how it is caught.
Design token
A design token is a named design value, such as a color, a font size or a space, kept as data with its type and what it is for, so people and AI agents use it by name instead of copying the raw value.
llms.txt
llms.txt is a Markdown file at the root of a site, such as `example.com/llms.txt`, that tells a language model what the site holds and links its pages in sections, ideally to a clean Markdown copy of each one. It is a proposal published at llmstxt.org, not a formal standard. For a design system, it is one small file that lets an agent find and read the whole of its docs.
MCP server
An MCP server is a program that offers an AI application tools, resources and prompts over the Model Context Protocol, the open standard for connecting agents to outside systems. A design system’s MCP server lets an agent look up a component and its props, list the design tokens or check a piece of code while it works, instead of guessing from what it saw in training.
Semantic token
A semantic token is a design token named for the job it does, such as "the main action’s background" or "danger text", that points at a raw value instead of holding its own. Components use semantic tokens only, so an agent picks a color by its purpose, and a theme or a rebrand changes what the token points at without touching a component.
Typed props
Typed props are a component’s inputs declared with their types in code, usually in TypeScript: which props it takes, which values each allows, which are required. An editor or a build checks every use against them, so when an agent passes a size the component does not have, the check fails at once, before the screen is drawn. It is the fifth sign this reference checks beside the comparison’s four.
W3C Design Tokens format
The W3C Design Tokens format is the file format for design tokens published by the Design Tokens Community Group at the W3C: JSON in which each design token has a `$value`, a `$type` and an optional `$description`, and can point at another design token. Version 2025.10 is a stable Final Community Group Report, not a W3C Standard. It is often shortened to DTCG, after the group.

Sources for this entry

  1. Design Tokens Format Module 2025.10 (opens in a new tab)

    The definitions of design tokens and their types.

    designtokens.org, checked

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How the related websites connect

Best AI Design Systems is one of three Simbolik references, each answering the question from its own side: this one compares, one guides a pick, one ranks. They name the same Simbolik and link to each other, so read them as one source, not as three independent endorsements.

Every related website

Cite this entry

Best AI Design Systems. “Glossary of AI design system terms.” Reviewed . https://bestaidesignsystems.com/glossary/