skills/ai-sdk-6/SKILL.md
Vercel AI SDK v6 development. Use when building AI agents, chatbots, tool integrations, streaming apps, or structured output with the ai package. Covers ToolLoopAgent, useChat, generateText, streamText, tool approval, smoothStream, provider tools, MCP integration, and Output patterns.
npx skillsauth add laguagu/claude-code-nextjs-skills ai-sdk-6Install this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill when developing AI-powered features using Vercel AI SDK v6 (ai package).
Docs location: bundled in
node_modules/ai/docs/. In Bun/pnpm/Yarn workspace monorepos deps aren't hoisted — useapps/*/node_modules/ai/docs/orpackages/*/node_modules/ai/docs/instead.
bun add ai @ai-sdk/openai zod # or @ai-sdk/anthropic, @ai-sdk/google, etc.
| Function | Purpose |
| -------------- | ----------------------------------------------------------------- |
| generateText | Non-streaming text generation (+ structured output with Output) |
| streamText | Streaming text generation (+ structured output with Output) |
v6 Note:
generateObject/streamObjectare deprecated. UsegenerateText/streamTextwithoutput: Output.object({ schema })instead.
import { generateText, Output } from "ai";
import { z } from "zod";
const { output } = await generateText({
model: anthropic("claude-sonnet-4-6"),
output: Output.object({
schema: z.object({
sentiment: z.enum(["positive", "neutral", "negative"]),
topics: z.array(z.string()),
}),
}),
prompt: "Analyze this feedback...",
});
Output types: Output.object(), Output.array(), Output.choice(), Output.json(), Output.text() (default)
import { ToolLoopAgent, tool, stepCountIs } from "ai";
import { anthropic } from "@ai-sdk/anthropic";
import { z } from "zod";
const myAgent = new ToolLoopAgent({
model: anthropic("claude-sonnet-4-6"),
instructions: "You are a helpful assistant.",
tools: {
getData: tool({
description: "Fetch data from API",
inputSchema: z.object({
query: z.string(),
}),
execute: async ({ query }) => {
return { result: "data" };
},
}),
},
stopWhen: stepCountIs(20),
});
// Usage
const { text } = await myAgent.generate({ prompt: "Hello" });
const stream = await myAgent.stream({ prompt: "Hello" });
// app/api/chat/route.ts
import { createAgentUIStreamResponse } from "ai";
import { myAgent } from "@/agents/my-agent";
export async function POST(request: Request) {
const { messages } = await request.json();
return createAgentUIStreamResponse({
agent: myAgent,
uiMessages: messages,
});
}
import { createAgentUIStreamResponse, smoothStream } from "ai";
return createAgentUIStreamResponse({
agent: myAgent,
uiMessages: messages,
experimental_transform: smoothStream({
delayInMs: 15,
chunking: "word", // "word" | "line" | RegExp | Intl.Segmenter | callback
}),
});
"use client";
import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport } from "ai";
import { useState } from "react";
export function Chat() {
const [input, setInput] = useState("");
const { messages, sendMessage, status } = useChat({
transport: new DefaultChatTransport({
api: "/api/chat",
}),
});
return (
<>
{messages.map((msg) => (
<div key={msg.id}>
{msg.parts.map((part, i) =>
part.type === "text" ? <span key={i}>{part.text}</span> : null
)}
</div>
))}
<form
onSubmit={(e) => {
e.preventDefault();
if (input.trim()) {
sendMessage({ text: input });
setInput("");
}
}}
>
<input
value={input}
onChange={(e) => setInput(e.target.value)}
disabled={status !== "ready"}
/>
<button type="submit" disabled={status !== "ready"}>
Send
</button>
</form>
</>
);
}
v6 Note:
useChatno longer manages input state internally. UseuseStatefor controlled inputs.
For detailed information, see:
For the latest information, see AI SDK docs.
testing
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development
PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector indexing, hybrid FTS/BM25 + RRF, ParadeDB, reranking, halfvec, multilingual search, query translation, and domain evals. Triggers: pgvector, vector search, semantic search, hybrid search, embedding search, PostgreSQL RAG, BM25, RRF, HNSW index, similarity search, ParadeDB, pg_search, reranking, Cohere rerank, Voyage rerank, graceful fallback, iterative_scan, filtered HNSW, websearch_to_tsquery, unaccent, multilingual FTS, pg_trgm, trigram, fuzzy search, LIKE, ILIKE, autocomplete, typo tolerance, fuzzystrmatch, evaluation, benchmarking, Hit@K, MRR, halfvec cast, cross-lingual retrieval, non-English corpus, per-language indexing, query translation, RRF fusion across languages
tools
OpenAI Agents SDK (Python) development. Use when building AI agents, multi-agent handoffs, function tools, guardrails, sessions, streaming, or tracing with the `openai-agents` / `agents` Python package — including Azure OpenAI via LiteLLM. Triggers on imports from `agents`, uses of `Runner.run_sync`/`Runner.run_streamed`, `@function_tool`, `AgentOutputSchema`, `SQLiteSession`, or questions about the openai-agents-python SDK.
development
Creates Next.js frontends with shadcn/ui. Use when building React UIs, components, pages, or applications with shadcn, Tailwind, or modern frontend patterns. Also use when the user asks to create a new Next.js project, add UI components, style pages, or build any web interface — even if they don't mention shadcn explicitly.