ai-sdk-5
Helps developers implement or migrate to Vercel AI SDK 5 features, including chat streaming and tool calling.
Install
mkdir -p .claude/skills/ai-sdk-5 && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1772" && unzip -o skill.zip -d .claude/skills/ai-sdk-5 && rm skill.zipInstalls to .claude/skills/ai-sdk-5
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Vercel AI SDK 5 patterns. Trigger: When building AI features with AI SDK v5 (chat, streaming, tools/function calling, UIMessage parts), including migration from v4.Key capabilities
- →Migrate chat components from AI SDK v4 to v5
- →Implement chat streaming with DefaultChatTransport
- →Configure tool calling with streamText
- →Handle UI message parts as an array
- →Integrate with LangChain using toUIMessageStream
How it works
The SDK uses a Transport-based messaging architecture where the client sends messages via a transport object and the server processes them using streamText.
Inputs & outputs
When to use ai-sdk-5
- →Migrate existing chat components from AI SDK v4 to v5
- →Implement chat streaming using DefaultChatTransport
- →Set up tool calling with AI SDK 5
- →Debug UI message part rendering in AI SDK 5
About this skill
Breaking Changes from AI SDK 4
// ❌ AI SDK 4 (OLD)
import { useChat } from "ai";
const { messages, handleSubmit, input, handleInputChange } = useChat({
api: "/api/chat",
});
// ✅ AI SDK 5 (NEW)
import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport } from "ai";
const { messages, sendMessage } = useChat({
transport: new DefaultChatTransport({ api: "/api/chat" }),
});
Client Setup
import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport } from "ai";
import { useState } from "react";
export function Chat() {
const [input, setInput] = useState("");
const { messages, sendMessage, isLoading, error } = useChat({
transport: new DefaultChatTransport({ api: "/api/chat" }),
});
const handleSubmit = (e: React.FormEvent) => {
e.preventDefault();
if (!input.trim()) return;
sendMessage({ text: input });
setInput("");
};
return (
<div>
<div>
{messages.map((message) => (
<Message key={message.id} message={message} />
))}
</div>
<form onSubmit={handleSubmit}>
<input
value={input}
onChange={(e) => setInput(e.target.value)}
placeholder="Type a message..."
disabled={isLoading}
/>
<button type="submit" disabled={isLoading}>
Send
</button>
</form>
{error && <div>Error: {error.message}</div>}
</div>
);
}
UIMessage Structure (v5)
// ❌ Old: message.content was a string
// ✅ New: message.parts is an array
interface UIMessage {
id: string;
role: "user" | "assistant" | "system";
parts: MessagePart[];
}
type MessagePart =
| { type: "text"; text: string }
| { type: "image"; image: string }
| { type: "tool-call"; toolCallId: string; toolName: string; args: unknown }
| { type: "tool-result"; toolCallId: string; result: unknown };
// Extract text from parts
function getMessageText(message: UIMessage): string {
return message.parts
.filter((part): part is { type: "text"; text: string } => part.type === "text")
.map((part) => part.text)
.join("");
}
// Render message
function Message({ message }: { message: UIMessage }) {
return (
<div className={message.role === "user" ? "user" : "assistant"}>
{message.parts.map((part, index) => {
if (part.type === "text") {
return <p key={index}>{part.text}</p>;
}
if (part.type === "image") {
return <img key={index} src={part.image} alt="" />;
}
return null;
})}
</div>
);
}
Server-Side (Route Handler)
// app/api/chat/route.ts
import { openai } from "@ai-sdk/openai";
import { streamText } from "ai";
export async function POST(req: Request) {
const { messages } = await req.json();
const result = await streamText({
model: openai("gpt-4o"),
messages,
system: "You are a helpful assistant.",
});
return result.toDataStreamResponse();
}
With LangChain
// app/api/chat/route.ts
import { toUIMessageStream } from "@ai-sdk/langchain";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage, AIMessage } from "@langchain/core/messages";
export async function POST(req: Request) {
const { messages } = await req.json();
const model = new ChatOpenAI({
modelName: "gpt-4o",
streaming: true,
});
// Convert UI messages to LangChain format
const langchainMessages = messages.map((m) => {
const text = m.parts
.filter((p) => p.type === "text")
.map((p) => p.text)
.join("");
return m.role === "user"
? new HumanMessage(text)
: new AIMessage(text);
});
const stream = await model.stream(langchainMessages);
return toUIMessageStream(stream).toDataStreamResponse();
}
Streaming with Tools
import { openai } from "@ai-sdk/openai";
import { streamText, tool } from "ai";
import { z } from "zod";
const result = await streamText({
model: openai("gpt-4o"),
messages,
tools: {
getWeather: tool({
description: "Get weather for a location",
parameters: z.object({
location: z.string().describe("City name"),
}),
execute: async ({ location }) => {
// Fetch weather data
return { temperature: 72, condition: "sunny" };
},
}),
},
});
useCompletion (Text Generation)
import { useCompletion } from "@ai-sdk/react";
import { DefaultCompletionTransport } from "ai";
const { completion, complete, isLoading } = useCompletion({
transport: new DefaultCompletionTransport({ api: "/api/complete" }),
});
// Trigger completion
await complete("Write a haiku about");
Error Handling
const { error, messages, sendMessage } = useChat({
transport: new DefaultChatTransport({ api: "/api/chat" }),
onError: (error) => {
console.error("Chat error:", error);
toast.error("Failed to send message");
},
});
// Display error
{error && (
<div className="error">
{error.message}
<button onClick={() => sendMessage({ text: lastInput })}>
Retry
</button>
</div>
)}
When not to use it
- →When using AI SDK v4 without migration plans
- →When building non-chat AI features
Prerequisites
Limitations
- →Requires migration of message structure from string to parts array
How it compares
Unlike the v4 useChat hook, v5 requires explicit transport configuration and handles message content as an array of parts rather than a single string.
Compared to similar skills
ai-sdk-5 side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| ai-sdk-5 (this skill) | 3 | 7mo | No flags | Intermediate |
| landing-page-guide-v2 | 48 | 8mo | Review | Intermediate |
| frontend-prompt-generator | 6 | 9mo | Review | Intermediate |
| prowler-ui | 1 | 2mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by prowler-cloud
View all by prowler-cloud →You might also like
landing-page-guide-v2
bear2u
Create distinctive, high-converting landing pages that combine proven conversion elements with exceptional design quality. Build beautiful, memorable landing pages using Next.js 14+ and ShadCN UI that avoid generic AI aesthetics while following the 11 essential elements framework.
frontend-prompt-generator
gharam1234
Generate structured prompts for frontend development tasks following established patterns. Use when the user requests prompts for wireframes, UI implementation, data binding, or routing functionality in React/Next.js projects with specific formatting requirements (Cursor rules, file paths, test-driven development).
prowler-ui
prowler-cloud
Prowler UI-specific patterns. For generic patterns, see: typescript, react-19, nextjs-15, tailwind-4. Trigger: When working inside ui/ on Prowler-specific conventions (shadcn vs HeroUI legacy, folder placement, actions/adapters, shared types/hooks/lib).
react-nextjs-development
netbarros
React and Next.js 14+ application development with App Router, Server Components, TypeScript, Tailwind CSS, and modern frontend patterns.
implementing-figma-ui-tempad-dev
ecomfe
Implement integration-ready UI code from a Figma selection or a provided nodeId using TemPad Dev MCP as the only source of design evidence (code snapshot, structure, screenshot, assets, tokens, codegen config). Detect the target repo stack and conventions first, then translate TemPad Dev’s Tailwind-like JSX/Vue IR into project-native code without adding new dependencies. Never guess key styles or measurements; avoid screenshot tuning loops. If required evidence is missing/contradictory or assets cannot be handled under repo policy, stop or ship a safe base with explicit warnings and omissions.
nextjs-developer
zenobi-us
Expert Next.js developer mastering Next.js 14+ with App Router and full-stack features. Specializes in server components, server actions, performance optimization, and production deployment with focus on building fast, SEO-friendly applications.