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Ai Sdk

Organization
vercel
ai-sdk

Vercel AI SDK expert guidance. Use when building AI-powered features — chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation, or working with any LLM provider.

Overview

Publishervercel
Repositoryvercel-plugin
Skill nameai-sdk
Stars
286
Forks
56
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by vercel on GitHub. Read the source before you install it.

Installation

Install the Ai Sdk AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vercel/vercel-plugin.git /tmp/vercel-plugin
mkdir -p .claude/skills
cp -r /tmp/vercel-plugin/skills/ai-sdk .claude/skills/ai-sdk
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ai Sdk in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ai Sdk on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ai Sdk is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

What the AI SDK Is

The AI SDK by Vercel (the ai package on npm) is a TypeScript toolkit for building AI applications. It provides a unified API across model providers for text generation, structured output, tool calling, agents, embeddings, and framework UI integrations.

Critical: Do Not Trust Your Own Memory

Whatever you remember about the AI SDK is likely outdated. The SDK changes frequently across versions - APIs are renamed, removed, and added. Your training data almost certainly contains obsolete APIs, deprecated patterns, and model IDs that no longer exist. UI hooks like useChat are among the most frequently changed APIs, so be especially careful with client code.

Never write AI SDK code from memory. Always verify every API, option, and pattern against the documentation and source code for the version that is actually installed in the project.

Use the Bundled, Version-Matched Docs

The ai package ships its full documentation and source code inside node_modules. These always match the installed version, so trust them over anything you remember.

  1. Ensure ai is installed. If node_modules/ai/ does not exist, install only the ai package using the project's package manager (e.g. pnpm add ai). Install provider packages (e.g. @ai-sdk/openai) and framework packages (e.g. @ai-sdk/react) later, when the task requires them.
  2. Read and grep the bundled docs at node_modules/ai/docs/ and the source at node_modules/ai/src/.
  3. Provider and framework packages bundle their own docs at node_modules/@ai-sdk/<name>/docs/.
  4. If something isn't in the bundled docs, search https://ai-sdk.dev/docs. You can append .md to any docs page URL to get its markdown, and search via https://ai-sdk.dev/api/search-docs?q=your_query.
  5. If you cannot find support for an answer in the docs or source, say so explicitly — do not guess.

AI Gateway: The Fastest Way to Start

The Vercel AI Gateway is the fastest way to get started with the AI SDK. It provides access to models from OpenAI, Anthropic, Google, and other providers through a single API, without installing provider packages or managing multiple API keys.

To set it up:

  1. Authenticate with OIDC (for Vercel deployments) or get an AI Gateway API key.
  2. Provide it to your app via the AI_GATEWAY_API_KEY environment variable.
  3. Reference models with provider/model strings.

For exact setup, authentication, and usage, read the bundled guide and the AI Gateway docs.

Choosing a Model

Never use model IDs from memory — models are released and retired frequently. Fetch the current list before writing code that references a model. Do not truncate the list (e.g. with head) so you can find the newest models:

bash
# All available models
curl -s https://ai-gateway.vercel.sh/v1/models | jq -r '.data[].id'

# Filter by provider (e.g. anthropic, openai, google)
curl -s https://ai-gateway.vercel.sh/v1/models | jq -r '[.data[] | select(.id | startswith("anthropic/")) | .id] | reverse | .[]'

When multiple versions of a model exist, prefer the one with the highest version number.

Building and Consuming Agents

Use the SDK's built-in agent abstraction (such as ToolLoopAgent) rather than hand-rolling tool-calling loops. For end-to-end type safety, infer the UI message type from your agent definition when consuming it on the client (e.g. with useChat). Consuming an agent is framework-specific: check package.json to detect the stack, then follow the matching quickstart.

Look up the current agent, tool, and type-safety APIs in the bundled docs (node_modules/ai/docs/, especially the agents section) or at https://ai-sdk.dev/docs.

DevTools

AI SDK DevTools captures your AI SDK calls - requests, responses, tool calls, token usage, and multi-step runs - so you can inspect exactly what your agents do. Use it while developing to debug generations. It is a separate package and is intended for local development only.

For setup instructions, read the bundled DevTools documentation.

Keep the SDK Current

Outdated installs are the most common source of errors. Compare the installed version against the latest:

  • Installed: the version field in node_modules/ai/package.json.
  • Latest: run npm view ai version.

If the installed version is a major version (or more) behind the latest, tell the user they are on an old release, and recommend upgrading before continuing. Migration guides are at https://ai-sdk.dev/docs/migration-guides.

After Making Changes

Run the project's type checker. Be minimal — only set options that differ from the defaults, checking docs or source for the defaults rather than over-specifying. Most type errors come from remembered, now-changed APIs; re-check the current docs and source when they occur.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ai Sdk AI skill do?

Vercel AI SDK expert guidance. Use when building AI-powered features — chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation, or working with any LLM provider.

Why use Ai Sdk on TypingMind?

Because you install it once and use it with any model. Ai Sdk is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ai Sdk in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vercel/vercel-plugin/tree/main/skills/ai-sdk. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ai Sdk?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ai Sdk?

As many as you like. As long as a model supports skills, you can use Ai Sdk with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ai Sdk AI skill free?

It is published on GitHub by vercel. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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