ai-elements

Build AI chat interfaces with ai-elements components for Next.js and shadcn UIs.

Updated Jul 18, 2026
One-click install
npx skills add https://github.com/farzanmrz/beat-radar-agent --skill ai-elements-farzanmrz
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-elements
Source: https://github.com/farzanmrz/beat-radar-agent/tree/main/.claude/skills/ai-elements
Command: npx skills add https://github.com/farzanmrz/beat-radar-agent --skill ai-elements-farzanmrz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires nanoid, lucide-react, zod, react, ai, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you assemble polished, production-ready AI user interfaces without starting from scratch, reducing the time spent wiring together chat layouts, tool displays, and media-rich assistant experiences.

Core Features & Use Cases

  • Conversation Surfaces: Build chat UIs with messages, responses, checkpoints, and streaming-friendly layouts.
  • AI Interaction Primitives: Add prompt inputs, agent summaries, chain-of-thought views, artifacts, and attachment handling.
  • Media and Utility Components: Support code blocks, audio playback, canvas interactions, and other UI patterns common in AI products.
  • Use Case: A product team can use this Skill to quickly prototype and ship an AI assistant with chat history, file attachments, tool output, and rich response cards.

Quick Start

Use the ai-elements skill to design an AI chat interface with conversation messages, tool outputs, and attachment previews.

Frequently Asked Questions about ai-elements

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an AI chat interface with streaming outputs in Next.js?

You build AI chat interfaces in Next.js using reusable component primitives for conversation surfaces, messages, and streaming-friendly layouts. This approach assembles production-ready UI with rich assistant interactions without wiring chat layouts from scratch.

Can I use shadcn components to display AI tool outputs and attachments?

Yes, shadcn-based product UIs can display AI tool outputs and attachments using interaction primitives. The components handle file attachment previews, tool output displays, and media-rich response cards natively within the chat interface.

What's the best way to add audio playback and code blocks to an AI assistant UI?

The best way to add audio playback and code blocks is using dedicated media and utility components. These primitives support code display, audio playback, and canvas interactions common in AI products alongside standard chat message layouts.

Do I need the Vercel AI SDK to render chain-of-thought and reasoning views?

You need an AI SDK-style data structure integration to render chain-of-thought and reasoning views. The components require client-side React usage and integrate with AI SDK-style data structures for chat, tools, and generated content.

Does this approach support agent summaries and artifacts for complex AI workflows?

Yes, the approach supports agent summaries, chain-of-thought views, and artifacts. These AI interaction primitives allow product teams to quickly prototype and ship an AI assistant with chat history, tool output, and rich response cards.