check-accessibility

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Source-first architecture

AgnosticUI components are copied into your project at install time.

They live in your repo (not hidden inside node_modules):

• Full control over the source
• Native integration with your framework
• AI-readable, high-fidelity context

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You own the source (and the Context)

cd your-project
npx agnosticui-cli init --framework vue  # or react, lit, svelte
npx agnosticui-cli add Button Card Input

The component source lands directly in your project. Readable, editable, and yours.

src/
components/
ag/
Button/
Button.vue ← your file now
Button.css ← your tokens now
Button.test.ts ← your tests now

Components land under src/components/ag/ by default: a dedicated namespace that keeps AgnosticUI components separate from your own. Configurable if you prefer otherwise.

🤖 AI-Native by Design

Because the code is local, it solves the "Black Box" problem of traditional libraries hidden in node_modules.

Cursor · Claude · Copilot · Windsurf · Aider · Gemini · Replit · Kiro · Antigravity

Every tool sees the raw source. This creates a high-fidelity environment for Generative UI and Agent-driven interfaces:

• Reduce Hallucination: No more "invented" props or APIs. Since the LLM reads local files like any other code, it knows exactly what is possible.
• Better Token Efficiency: Using semantic HTML and standard CSS provides "clean context." Agents spend fewer tokens to understand the UI, leading to faster, more accurate generations.
• Agent Skills: Treat AgnosticUI Playbooks as pre-defined skills. Use them to prompt an agent to scaffold complex, accessible workflows (Login, Onboarding, Discovery Dashboard, Support Center, Data Grids) using the local components it already "sees."

This is the architecture for the next era of development: context-aware, framework-agnostic, and AI-ready.

The schema-driven layer ships with three companion documents:

• v2/docs/sdui-architecture.md — full system architecture: codegen pipeline, node graph model, renderers, CI gates, and key design decisions
• v2/docs/llm-prompt-guide.md — copy-paste system prompt template and few-shot examples for generating valid AgNode[] graphs
• v2/docs/schema-coverage.md — per-component SDUI coverage registry, renderer parity status, and omission reasons

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Built once. Runs everywhere.

AgnosticUI's components are authored as Lit Web Components, a standards-based layer over native Custom Elements. The CLI wraps them for your framework at copy time.

Your design system doesn't fork when your tech stack does. Supports agent-generated UI workflows directly from Playbooks.

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AI Playbooks: AI-Prompt-Driven UI Components

Playbooks (Login Form, Onboarding Wizard, Discovery Dashboard, Support Center, Data Grid, Blog / Article Reader, Landing / Marketing Page) demonstrate modular, prompt-driven UI components. Each Playbook can be used in agent systems, for context-aware applications, or to create generative UI patterns.

Each Playbook on the docs site includes live StackBlitz examples for React, Vue, and Lit, and ships with:

• PROMPT-3-FRAMEWORKS.md: one prompt to generate the pattern across all three frameworks
• Skin switcher to preview your theme tokens instantly

Fully prompt-ready for agent-driven UI generation. Drop a Playbook prompt into Cursor, Claude Code, or Copilot and watch it assemble Input, Button, Card, and FormGroup correctly on the first try — because it has the full recipe, not just a component reference.

The prompts are yours to adapt. Feed one to your LLM as a crash course in AgnosticUI's patterns, fork it for your own stack, or use it as a blueprint for writing Playbooks aro