AI app for it and development · no coding needed
Agent-readable design system library and brand stewardship console
Reduce interface rework while keeping one consistent brand across agent-assisted builds.
Made for: Product teams and agencies building interfaces with AI coding agents
What it does for you
The problem
AI coding agents produce generic, inconsistent interfaces because brand rules and design tokens are scattered across tools and not readable by agents.
What it gives you
Versioned, agent-readable design system linked to preview-tested components
What you give it
Approved design tokensbrand filescomponent catalogsagent task guides
Build your own version of Uiverse Design, Design.MD and more
One app with what these 3 AI tools do, yours to keep and change: Uiverse Design, Design.MD, Once UI 2.0.
Everything these tools do, in one app
- Design system library Provides a collection of ready-made design systems or brand files that define visual styles for projects.Found in Uiverse Design, Design.MD, Once UI 2.0
- Agent-readable documentation Includes markdown files or guides that AI coding agents can read and follow to apply the design system correctly.Found in Uiverse Design, Design.MD, Once UI 2.0
- Design tokens Centralizes visual decisions like color, typography, and spacing so changes propagate consistently.Found in Uiverse Design, Design.MD, Once UI 2.0
- Drop-in components Offers pre-built UI components that can be easily copied and adapted into projects.Found in Uiverse Design, Once UI 2.0
- Open-source availability Provides free and open-source elements or core components that can be inspected and modified.Found in Uiverse Design, Once UI 2.0
- Framework-specific examples Includes code examples in popular frameworks like vanilla CSS, Tailwind, or React.Found in Uiverse Design, Once UI 2.0
- Brand file library Contains a large collection of pre-made brand style files for quick reference and use.Found in Design.MD
- Custom brand generation Allows users to request missing brands or generate custom design system files.Found in Design.MD
- Agent integration Easily integrates with AI coding agents like Cursor, Claude Code, Lovable, v0, and Bolt.Found in Design.MD
- Markdown-based format Uses markdown files that are editable, portable, and easy to version alongside code.Found in Design.MD
- Component catalog Provides a structured catalog of React components backed by design tokens.Found in Once UI 2.0
- Task guides for agents Offers compact documentation and examples to help AI coding agents apply the system correctly.Found in Once UI 2.0
- Layout primitives Provides readable primitives that map directly to visual structure for composing interfaces.Found in Once UI 2.0
- Consistent component APIs Components follow predictable patterns, reducing relearning when switching between manual and agent-assisted coding.Found in Once UI 2.0
- Preview-tested components Components are validated in real product contexts using Vercel Preview Deployments.Found in Once UI 2.0
How it works, step by step
- Browse the design system and brand file library
- Apply design tokens for color, typography and spacing
- Copy drop-in components into projects
- Read agent-readable markdown documentation
- Follow framework-specific examples in vanilla CSS, Tailwind or React
- Inspect and modify open-source elements
- Request or generate custom brand files
- Integrate with Cursor, Claude Code, Lovable, v0 and Bolt
- Version markdown files alongside code
- Search the structured React component catalog
- Apply compact task guides for agents
- Compose layouts with readable primitives
- Use consistent component APIs across manual and agent work
- Validate components in preview deployments
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned, agent-readable design system linked to preview-tested components with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Agent-readable design system library and brand stewardship console with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Agent-readable design system library and brand stewardship console with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links4 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare24 KB
- prompt-vps.mdThe same build on your own server (Docker)24 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria11 KB
- demo/index.htmlThe working demo on sample data196 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce interface rework while keeping one consistent brand across agent-assisted builds. For product teams and agencies building interfaces with AI coding agents, convert approved design tokens, brand files, component catalogs and agent task guides into a versioned, agent-readable design system linked to preview-tested components. The benefit is a testable hypothesis, measured through accepted interface screens per build hour and brand corrections after agent generation; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect approved design tokens, brand files, component catalogs and agent task guides, then follow this sequence: 1. Browse the design system and brand file library. 2. Apply design tokens for color, typography and spacing. 3. Copy drop-in components into projects. 4. Read agent-readable markdown documentation. 5. Follow framework-specific examples in vanilla CSS, Tailwind or React. 6. Inspect and modify open-source elements. 7. Request or generate custom brand files. 8. Integrate with Cursor, Claude Code, Lovable, v0 and Bolt. 9. Version markdown files alongside code. 10. Search the structured React component catalog. 11. Apply compact task guides for agents. 12. Compose layouts with readable primitives. 13. Use consistent component APIs across manual and agent work. 14. Validate components in preview deployments. Resolve uncertain cases with qualified reviewers, approve versioned, agent-readable design system linked to preview-tested components, and measure accepted interface screens per build hour and brand corrections after agent generation against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One approved token schema and component API set; final brand and accessibility checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve brand ownership, source attribution, license accuracy and usage permissions. Design owners approve substantive changes and publication scope. One approved token schema and component API set; final brand and accessibility checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One approved token schema and component API set; final brand and accessibility checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: browse the design system and brand file library; apply design tokens for color, typography and spacing. Support the third module with operator review: copy drop-in components into projects. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Agent-owned repositories, authorized brand files and permitted component sources. Cloud asset storage, design-file import/export and code repository destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Design system library, Editable token and brand console, Agent package and delivery. Use a thumbnail gallery for design systems and brand files, a large central editing canvas for tokens, typography and spacing, and a right-hand panel for agent guides, component previews and comments. Let users compare token versions side by side. Display draft, changes requested and approved states. Provide an agent package link with markdown files anchored to the relevant component. Make the task-specific outcome versioned, agent-readable design system linked to preview-tested components visible beside its evidence, review state and value baseline.
