ai-sdk-6
Vercel AI SDK v6 development, for projects already on ai@6. Use when building or maintaining AI agents, chatbots, tool integrations, streaming apps, or structured output in a v6 codebase. New projects and ai@7 code use ai-sdk-7; an unknown version goes through ai-sdk. Covers ToolLoopAgent, useChat, generateText, streamText, tool approval, smoothStream, provider tools, MCP integration, and Output patterns.
How do I install this agent skill?
npx skills add https://github.com/laguagu/claude-code-nextjs-skills --skill ai-sdk-6Is this agent skill safe to install?
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This skill provides comprehensive documentation and code examples for developing with the Vercel AI SDK v6. It includes patterns for agents, tools, and structured output, and references official examples from Vercel's trusted GitHub repository. No security risks were identified.
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What does this agent skill do?
AI SDK 6 maintenance
Apply this skill only to ai@6 projects. Resolve compatible provider and UI
packages from the existing manifest/lockfile. Use ai-sdk when the major is
unknown and ai-sdk-7 for an authorized upgrade.
Read the resolved ai/docs/, provider docs and source/types for the exact minor
release. In a monorepo, resolve from the app using the dependency. Default web
docs and repository main can describe v7. ai bundles docs/ from 6.0.32; the
tree mirrors the website paths (mapping in ai-sdk). If installed docs are
unavailable, select the ai@<resolved-version> tag in vercel/ai and read
content/docs/.
Feature links here use a checked v6 documentation snapshot
as a fallback; match the project's release when available. This tag selects
documentation, not an application dependency version.
Boundaries that differ from old and new code
- Text functions use
system;ToolLoopAgentusesinstructions. - Loop limits use
stopWhen: stepCountIs(...). Text functions default to one step (tool execution without a follow-up answer);ToolLoopAgentdefaults to 20. convertToModelMessagesis async; await it.- Use text functions with
Outputfor new schema output; legacy object functions are deprecated. - Tools use
inputSchema; SDK-executed approval is tool-levelneedsApproval. V6 does not know v7'stoolApproval: unless a typecheck rejects it, it is ignored and the tool runs without approval. - React
useChatowns messages and stream status, not form input. Use the appropriate transport and UI-message response protocol. - Core completion callbacks are
onFinish; resultusageis final-step usage, whiletotalUsagecovers all steps.
Use a configured model verified for the actual provider. Typecheck and test a multi-turn stream with relevant tool/approval/error states after integration changes.
Core shape
Checked with ai@6.0.298, @ai-sdk/react@3.0.301, zod@4.6.5, React 19 and
TypeScript 5.9: tsc --noEmit, plus a mock-model run through one tool step and
the follow-up answer. A string model resolves through the AI Gateway. In v7,
system, stepCountIs and result.toUIMessageStreamResponse() become
instructions, isStepCount and
createUIMessageStreamResponse({ stream: toUIMessageStream({ stream: result.stream }) }).
// app/api/chat/route.ts
import { convertToModelMessages, stepCountIs, streamText, tool, validateUIMessages,
type InferUITools, type UIDataTypes, type UIMessage } from 'ai';
import { z } from 'zod';
const tools = {
weather: tool({
inputSchema: z.object({ city: z.string() }),
execute: async ({ city }) => ({ city, celsius: 21 }),
}),
};
export type ChatMessage = UIMessage<never, UIDataTypes, InferUITools<typeof tools>>;
export async function POST(req: Request) {
const { messages } = await req.json();
const uiMessages = await validateUIMessages<ChatMessage>({ messages, tools });
const result = streamText({
model: 'provider/model-id', // configured gateway ID, or a provider instance
system: 'Answer briefly.',
messages: await convertToModelMessages(uiMessages),
tools,
stopWhen: stepCountIs(5),
});
return result.toUIMessageStreamResponse();
}
// app/page.tsx
'use client';
import { useChat } from '@ai-sdk/react';
import { DefaultChatTransport } from 'ai';
import type { ChatMessage } from './api/chat/route';
const transport = new DefaultChatTransport<ChatMessage>({ api: '/api/chat' });
export default function Chat() {
const { messages, sendMessage, status } = useChat<ChatMessage>({ transport });
return (
<form action={(form) => void sendMessage({ text: String(form.get('text')) })}>
{messages.map((m) => <div key={m.id}>{m.parts.map((part, i) =>
part.type === 'text' ? <p key={i}>{part.text}</p>
: part.type === 'tool-weather' && part.state === 'output-available'
? <p key={i}>{part.output.city}: {part.output.celsius} °C</p> : null)}</div>)}
<input name="text" disabled={status === 'submitted' || status === 'streaming'} />
</form>
);
}
Read for the feature
- Agents: loop limits, call options and context.
- Core functions: output and stream contracts.
- Tools: execution, approval and typed states.
- UI hooks: transport, restoration and stream lifetime.
- Middleware: provider interception.
- MCP: transport and cleanup.
- Workflows: when a loop needs explicit orchestration.
- Examples: version-matched official implementations.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/laguagu/claude-code-nextjs-skills/ai-sdk-6">View ai-sdk-6 on skillZs</a>