Agent skill
ai-elements
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.
Install this agent skill to your Project
npx add-skill https://github.com/mxyhi/ok-skills/tree/main/ai-elements
SKILL.md
AI Elements
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.
Prerequisites
Before installing AI Elements, make sure your environment meets the following requirements:
- Node.js, version 18 or later
- A Next.js project with the AI SDK installed.
- shadcn/ui installed in your project. If you don't have it installed, running any install command will automatically install it for you.
- We also highly recommend using the AI Gateway and adding
AI_GATEWAY_API_KEYto yourenv.localso you don't have to use an API key from every provider. AI Gateway also gives $5 in usage per month so you can experiment with models. You can obtain an API key here.
Installing Components
You can install AI Elements components using either the AI Elements CLI or the shadcn/ui CLI. Both achieve the same result: adding the selected component’s code and any needed dependencies to your project.
The CLI will download the component’s code and integrate it into your project’s directory (usually under your components folder). By default, AI Elements components are added to the @/components/ai-elements/ directory (or whatever folder you’ve configured in your shadcn components settings).
After running the command, you should see a confirmation in your terminal that the files were added. You can then proceed to use the component in your code.
Usage
Once an AI Elements component is installed, you can import it and use it in your application like any other React component. The components are added as part of your codebase (not hidden in a library), so the usage feels very natural.
Example
After installing AI Elements components, you can use them in your application like any other React component. For example:
"use client";
import {
Message,
MessageContent,
MessageResponse,
} from "@/components/ai-elements/message";
import { useChat } from "@ai-sdk/react";
const Example = () => {
const { messages } = useChat();
return (
<>
{messages.map(({ role, parts }, index) => (
<Message from={role} key={index}>
<MessageContent>
{parts.map((part, i) => {
switch (part.type) {
case "text":
return (
<MessageResponse key={`${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.
Extensibility
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.
Customization
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>
);
Troubleshooting
Why are my components not styled?
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.
I ran the AI Elements CLI but nothing was added to my project
Double-check that:
- Your current working directory is the root of your project (where
package.jsonlives). - Your components.json file (if using shadcn-style config) is set up correctly.
- You’re using the latest version of the AI Elements CLI:
npx ai-elements@latest
If all else fails, feel free to open an issue on GitHub.
Theme switching doesn’t work — my app stays in light mode
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.
The component imports fail with “module not found”
Check the file exists. If it does, make sure your tsconfig.json has a proper paths alias for @/ i.e.
{
"compilerOptions": {
"baseUrl": ".",
"paths": {
"@/*": ["./*"]
}
}
}
My AI coding assistant can't access AI Elements components
- Verify your config file syntax is valid JSON.
- Check that the file path is correct for your AI tool.
- Restart your coding assistant after making changes.
- Ensure you have a stable internet connection.
Still stuck?
If none of these answers help, open an issue on GitHub and someone will be happy to assist.
Available Components
See the references/ folder for detailed documentation on each component.
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
opensrc
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
test-driven-development
Use when implementing any feature or bugfix, before writing implementation code
dogfood
Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.
minimax-pdf
Use this skill when visual quality and design identity matter for a PDF. CREATE (generate from scratch): "make a PDF", "generate a report", "write a proposal", "create a resume", "beautiful PDF", "professional document", "cover page", "polished PDF", "client-ready document". FILL (complete form fields): "fill in the form", "fill out this PDF", "complete the form fields", "write values into PDF", "what fields does this PDF have". REFORMAT (apply design to an existing doc): "reformat this document", "apply our style", "convert this Markdown/text to PDF", "make this doc look good", "re-style this PDF". This skill uses a token-based design system: color, typography, and spacing are derived from the document type and flow through every page. The output is print-ready. Prefer this skill when appearance matters, not just when any PDF output is needed.
get-api-docs
Use this skill when you need documentation for a third-party library, SDK, or API before writing code that uses it — for example, "use the OpenAI API", "call the Stripe API", "use the Anthropic SDK", "query Pinecone", or any time the user asks you to write code against an external service and you need current API reference. Fetch the docs with chub before answering, rather than relying on training knowledge.
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
Didn't find tool you were looking for?