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AI-ready UI documentation gives an AI system enough context to find the right component, understand its purpose, select a valid variant, and follow the design system’s tokens and behavior. The practical difference is explicit guidance: document what a component does, when to use it, what states and properties it actually supports, and how to check generated work. Clear documentation can reduce guesswork; it cannot guarantee correct, accessible output on its own.
Why visual assets alone are not enough
A component’s appearance does not necessarily explain its purpose. An agent might recognize a button, card, or navigation pattern but still choose the wrong one if the system does not say what each is for or how similar options differ. Figma’s component-documentation guidance makes this distinction explicit: an agent may identify what a component looks like without understanding its intended purpose. Figma’s documentation guide recommends human review of AI-drafted component, style, and variable documentation.
The aim is not to write a long essay for every asset. It is to make important decisions legible to people and tools: which component fits a task, which variant is appropriate, which tokens express the intended meaning, and what behavior users should experience.
What to document for each component
Use a compact component contract. Record only properties, variants, states, and behaviors that exist in the system; do not let an AI-generated description invent an API.
| Documentation area | What to state | Why it matters |
|---|---|---|
| Name and purpose | Use a stable, meaningful name and explain the job the component performs. | Names based only on appearance or position provide little guidance about intent. |
| Use and avoid | Say when to choose the component, when not to, and which similar option is preferable in common cases. | These rules help distinguish components that may look alike. |
| Properties and composition | List real variants, properties, slots, nested instances, and dependencies. | The AI can select from supported options instead of assuming capabilities. |
| States and behavior | Describe supported states—such as focus, disabled, loading, success, or error—and relevant interaction and keyboard behavior. | State names alone do not explain what changes or how the component responds. |
| Tokens and layout | Name semantic color, typography, spacing, and sizing roles; explain responsive and layout rules. | Intent is clearer than unexplained values or visual conventions left implicit. |
| Accessibility | Specify expected accessible name, role, state exposure, keyboard behavior, relationships, and relevant contrast requirements. | These details inform implementation, which still needs to be validated. |
| Examples and alternatives | Show a real usage example and, where confusion is likely, a common misuse or better alternative. | Examples make rules concrete and reveal distinctions that a name cannot convey. |
| Ownership and freshness | Identify the source of truth and keep the documentation aligned with the published library and code. | Stale guidance can direct an AI workflow to components or rules that have changed. |
Make names, structure, and tokens carry meaning
Use names that describe a component’s role rather than where it happens to appear or what it looks like. In Figma workflows, the company’s guidance recommends meaningful layer and component names, reusable blocks, auto layout, defined properties and variants, and variables for color, spacing, and typography. Figma also says its agent needs the library to be published to reference it. These are recommendations for that workflow, not universal requirements for every design tool. Figma’s component and variable guidance describes the approach.
Prefer semantic token names that explain a role, such as a surface or text role, over names that expose only a raw color or number. Pair tokens with rules for their use. A token inventory without usage guidance may tell an AI what values exist without telling it which one fits a particular interface decision.
Reusable blocks can also help when a common composition depends on hierarchy, spacing, or nested components. Providing the established composition is more reliable than asking an agent to reconstruct it from isolated parts.
Separate component instructions from library-wide rules
Keep guidance close to where it is most useful. The component description should cover its purpose, supported states, and local usage. Put rules that apply across the library—such as naming conventions, token selection, composition patterns, exceptions, or prohibited patterns—in a library-level guide or equivalent machine-readable documentation.
Figma’s library-guidelines documentation describes using separate files to capture conventions that assets may not communicate, including composition order, distinctions between similarly named components, required variables, and rules shared across screens or platforms. It documents Markdown, plain text, and JSON for this workflow. Its stated combined 200 KB limit and beta status are operational details that may change; check the current library-guidelines documentation before relying on them.
Document accessibility as expected behavior, then validate it
For an interactive component, describe the accessible name, role, state changes, keyboard interaction, and relevant relationships that the implementation is expected to expose. W3C’s WAI-ARIA overview explains how roles, states, properties, names, and descriptions relate to accessibility APIs. A component specification can communicate expected behavior, but it does not prove that the implementation conforms or works correctly for users. Validate the built interface.
Keep standards claims precise. The cited WCAG 3.0 document is a Working Draft and says it is inappropriate to cite it as anything other than work in progress. Do not present that draft as a finalized conformance standard.
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Documentation only helps when the workflow can reach it. Make the published components, variables, and relevant guidance available in the context used by the AI tool, and keep that material discoverable and structured. Figma describes direct context access through its MCP server, including access to components, variables, and Code Connect mappings. That is a documented Figma workflow, not evidence of a neutral comparison among design tools. See the Figma MCP developer documentation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Build the documentation through an audit loop
Start with one common component rather than attempting to document the entire system at once. Write its usage rules and token context, ask the AI workflow to use it, and inspect the result against the library. Use the gaps to decide what to clarify next. Figma’s context-design article frames this work around semantic tokens, specifications that state usage rules, and an audit loop for generated output. Figma’s article on LLM context design attributes a 2025 AI report finding that 91% of developers and 92% of designers said the design-to-code handoff process needed work; the article passage does not provide enough survey-method detail to independently assess those figures.
- Choose a common component. Pick one that appears often or has variants that are easy to confuse.
- Write its contract. Add purpose, use-and-avoid guidance, supported properties and states, relevant tokens, behavior, accessibility expectations, and a real example.
- Make the source available. Ensure the workflow can access the published library and the rules that apply to it.
- Generate a representative result. Ask for a realistic use of the component rather than a description of it alone.
- Audit against the system. Check whether the output used the right component, valid properties and variants, correct tokens, and documented behavior; verify accessibility in the implementation.
- Improve the guidance. When output exposes an ambiguity or missing rule, update the relevant component or library-level documentation and repeat with another common case.
What a useful audit should catch
Review generated work for concrete mismatches, not just whether it looks plausible at first glance. Check the following:
- Does the chosen component fit the documented purpose, or would a similar component be more appropriate?
- Are all properties, variants, slots, and nested instances real and supported?
- Do semantic tokens and layout rules match the documented intent?
- Are the relevant states and interactions present without invented behavior?
- Does the implementation expose the expected accessibility semantics and work with the intended keyboard interaction?
- Is the guidance aligned with the current published library and code?
Figma’s official guidance supports human review of agent-drafted documentation. Treat generated descriptions as drafts, and treat generated UI as work to check against the actual system—not as proof that the system has been followed.
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