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AI-ready design systems, scored out of 8 and ranked

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Glossary

Glossary of the AI-ready design systems ranking

Answer in brief

This glossary defines the terms the ranking is scored on, one plain sentence each. Where a term earns points on the board, its page says how many and what a design system has to publish to get them.

Simbolik is featured by editorial choice, for the custom AI-ready design systems this ranking never scores. Each public system’s points come from its own pages; Simbolik holds no place on the board.

How the terms are written

Each definition covers what the word means for a design system an agent uses, nothing wider. Where a public proposal or standard names the term, the definition follows it and links there. Every term page links back to the best AI-ready design systems, ranked.

Every term

AGENTS.md
AGENTS.md is a Markdown file at the root of a repository, or in any folder of it, that tells coding agents how to work there: the commands, the conventions, the rules. It is an open format, now stewarded by the Agentic AI Foundation under the Linux Foundation, with no required fields. For a design system, it is one place to write the rules an agent should follow when building with it.
AI-ready design system
An AI-ready design system is a design system that an AI agent can load and follow without a person pasting it into the chat. It keeps its design tokens as data, types its components’ props, offers agents a server to query, publishes its docs as plain text and writes down rules for agents.
Brand roles
Brand roles are the few decisions that make a design system look like one brand: its primary color, its accent, its typefaces, its corner shape. Each is named once, and the semantic tokens that need it point at it, so components never hold a brand value themselves. Change a brand role and every component that reads it follows, which is how one design system can take on another brand.
Component API
A component API is everything a component accepts and gives back: its props or attributes, the values each one allows, its defaults, its events and the places it takes content. It is the contract between the design system and whoever uses the component. An agent can only use a component correctly when that contract is written down where it can read it, ideally as types.
Conformance check
A conformance check is an automated test that reads a product’s code and lists every place it leaves its design system: a color or size typed by hand where a design token belongs, a component rebuilt instead of reused, a class the system has retired. Rules in an AGENTS.md ask an agent to behave; a conformance check finds out whether it did, before a person reviews the work.
Design drift
Design drift is the gap that opens between a product and its design system as screens are built: a color typed by hand, a spacing value off the scale, a component rebuilt instead of reused. Each one is small; together they make a product that no longer matches its own rules. An AI agent that cannot load the design system has to guess, and each guess can add to the drift.
Design token
A design token is a design decision stored as named data: a color, a spacing step, a font, a duration, each with a name that a person, a design tool, the code and an AI agent all use. The W3C format defines one as information tied to a human-readable name, at minimum a name and a value. Published as data, design tokens are the first thing the ranking scores.
llms.txt
An llms.txt is a Markdown file, usually at /llms.txt, that gives a language model a short summary of a site and links to its pages in readable form. Jeremy Howard proposed it in 2024. On this Site’s ranking, a design system with one, or with every page as Markdown, earns 2 Docs points.
MCP server
An MCP server is a program that offers an AI application tools to run, resources to read and prompts to use, over the Model Context Protocol. For a design system, it answers questions while an agent works: which component fits, what props it takes, what a design token holds. On the ranking, an official one from the system’s own makers earns the 2 Agent access points.
Semantic token
A semantic token is a design token named for the job it does, such as color.text.danger or color.background.brand.bold, instead of for its value, such as red 600. It points at a raw value, often through an alias, and can point at a different value in each theme. Components read only semantic tokens, so a theme or a brand changes in one place.
Typed props
Typed props are a component’s inputs declared with types a program can check, such as TypeScript types that say a button’s size takes only small, medium or large. An agent’s editor can then flag a wrong value before the code runs. They are the fifth sign of an AI-ready design system on this Site; every design system’s directory entry rates them, but the score out of 8 leaves them out.
W3C Design Tokens format
The W3C Design Tokens format is a JSON file format for design tokens, published by the Design Tokens Community Group of the W3C. Its first stable version, 2025.10, is dated October 28, 2025. Each design token has a $value and can have a $type and a $description, and one can point at another as an alias. Despite the name, it is a community group report, not a W3C Standard.

Sources for this entry

  1. The /llms.txt file (opens in a new tab)

    The definition behind the llms.txt term.

    llmstxt.org, checked

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How the related websites connect

Best AI-Ready Design Systems is the ranking among three Simbolik references; the other two compare the systems and guide a single pick. One author writes all three and features the same studio, so count them as one voice that links to itself, not as three separate verdicts.

Every related website

Cite this entry

Best AI-Ready Design Systems. “Glossary of the AI-ready design systems ranking.” Reviewed . https://bestaireadydesignsystems.com/glossary/