Best for
- Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
mxyhi/ok-skills/ai-elements/SKILL.md
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
Decision brief
AI Elements is a component library and custom registry built on top of shadcn/ui to help you build AI-native applications faster. It provides pre-built components like conversations, messages and more.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/mxyhi/ok-skills --skill "ai-elements"Inspect the Agent Skill "ai-elements" from https://github.com/mxyhi/ok-skills/blob/b493166396eb6bf7694ec842fb2679014e26a7c4/ai-elements/SKILL.md at commit b493166396eb6bf7694ec842fb2679014e26a7c4. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Once an AI Elements component is installed, you can import it and use it in your application like any other React component. The components are added as part of your codebase (not hidden in a library), so the usage feels very natural.
Before installing AI Elements, make sure your environment meets the following requirements:
You can install AI Elements components using either the AI Elements CLI or the shadcn/ui CLI. Both achieve the same result: adding the selected component’s code and any needed dependencies to your project.
After installing AI Elements components, you can use them in your application like any other React component. For example:
All AI Elements components take as many primitive attributes as possible. For example, the Message component extends HTMLAttributes, so you can pass any props that a div supports. This makes it easy to extend the component with your own styles or functionality.
Permission review
The documentation asks the agent to run terminal commands or scripts.
**IMPORTANT:** Run all CLI commands using the project's package runner: `npx ai-elements@latest`, `pnpm dlx ai-elements@latest`, or `bunx --bun ai-elements@latest` — based on the project's `packageManager`. Examples below use `npx ai-elemenThe documentation asks the agent to read local files, directories, or repositories.
In the example above, we import the `Message` component from our AI Elements directory and include it in our JSX. Then, we compose the component with the `MessageContent` and `MessageResponse` subcomponents. You can style or configure the cThe documentation asks the agent to run terminal commands or scripts.
npx ai-elements@latestEvidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 84/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 458 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
AI Elements is a component library and custom registry built on top of shadcn/ui to help you build AI-native applications faster. It provides pre-built components like conversations, messages and more.
Installing AI Elements is straightforward and can be done in a couple of ways. You can use the dedicated CLI command for the fastest setup, or integrate via the standard shadcn/ui CLI if you've already adopted shadcn's workflow.
IMPORTANT: Run all CLI commands using the project's package runner:
npx ai-elements@latest,pnpm dlx ai-elements@latest, orbunx --bun ai-elements@latest— based on the project'spackageManager. Examples below usenpx ai-elements@latestbut substitute the correct runner for the project.
Before installing AI Elements, make sure your environment meets the following requirements:
AI_GATEWAY_API_KEY to your env.local so you don't have to use an API key from every provider. AI Gateway also gives $5 in usage per month so you can experiment with models. You can obtain an API key here.You can install AI Elements components using either the AI Elements CLI or the shadcn/ui CLI. Both achieve the same result: adding the selected component’s code and any needed dependencies to your project.
The CLI will download the component’s code and integrate it into your project’s directory (usually under your components folder). By default, AI Elements components are added to the @/components/ai-elements/ directory (or whatever folder you’ve configured in your shadcn components settings).
After running the command, you should see a confirmation in your terminal that the files were added. You can then proceed to use the component in your code.
Once an AI Elements component is installed, you can import it and use it in your application like any other React component. The components are added as part of your codebase (not hidden in a library), so the usage feels very natural.
After installing AI Elements components, you can use them in your application like any other React component. For example:
"use client";
import {
Message,
MessageContent,
MessageResponse,
} from "@/components/ai-elements/message";
import { useChat } from "@ai-sdk/react";
const Example = () => {
const { messages } = useChat();
return (
<>
{messages.map(({ role, parts }, index) => (
<Message from={role} key={index}>
<MessageContent>
{parts.map((part, i) => {
switch (part.type) {
case "text":
return (
<MessageResponse key={`${role}-${i}`}>
{part.text}
</MessageResponse>
);
}
})}
</MessageContent>
</Message>
))}
</>
);
};
export default Example;
In the example above, we import the Message component from our AI Elements directory and include it in our JSX. Then, we compose the component with the MessageContent and MessageResponse subcomponents. You can style or configure the component just as you would if you wrote it yourself – since the code lives in your project, you can even open the component file to see how it works or make custom modifications.
All AI Elements components take as many primitive attributes as possible. For example, the Message component extends HTMLAttributes<HTMLDivElement>, so you can pass any props that a div supports. This makes it easy to extend the component with your own styles or functionality.
After installation, no additional setup is needed. The component’s styles (Tailwind CSS classes) and scripts are already integrated. You can start interacting with the component in your app immediately.
For example, if you'd like to remove the rounding on Message, you can go to components/ai-elements/message.tsx and remove rounded-lg as follows:
export const MessageContent = ({
children,
className,
...props
}: MessageContentProps) => (
<div
className={cn(
"flex flex-col gap-2 text-sm text-foreground",
"group-[.is-user]:bg-primary group-[.is-user]:text-primary-foreground group-[.is-user]:px-4 group-[.is-user]:py-3",
className
)}
{...props}
>
<div className="is-user:dark">{children}</div>
</div>
);
Make sure your project is configured correctly for shadcn/ui in Tailwind 4 - this means having a globals.css file that imports Tailwind and includes the shadcn/ui base styles.
Double-check that:
package.json lives).npx ai-elements@latest
If all else fails, feel free to open an issue on GitHub.
Ensure your app is using the same data-theme system that shadcn/ui and AI Elements expect. The default implementation toggles a data-theme attribute on the <html> element. Make sure your tailwind.config.js is using class or data- selectors accordingly.
Check the file exists. If it does, make sure your tsconfig.json has a proper paths alias for @/ i.e.
{
"compilerOptions": {
"baseUrl": ".",
"paths": {
"@/*": ["./*"]
}
}
}
If none of these answers help, open an issue on GitHub and someone will be happy to assist.
See the references/ folder for detailed documentation on each component.
Alternatives
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