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vercel/ai-sdk

vercel

ai-sdk

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

NewUpdated Sep 23, 2026

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Whatever you remember about the AI SDK is likely outdated.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. Check node_modules/ai/ or locate the workspace package in a monorepo that depends on ai (e.g. apps/<name>/node_modules/ai/). If ai is not installed anywhere in the project, install only the ai package into the target package using the project's package manager (e.g. pnpm add ai --filter <pkg> or npm install 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/ (or <package>/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/ (or <package>/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:

# 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.

Files1
1 files · 552 B

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Overall Score

78/100

Grade

B

Good

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

82

Quality

76

Clarity

82

Completeness

72

Summary

This skill guides AI agents through using the Vercel AI SDK, a TypeScript toolkit for building AI applications. It emphasizes version-aware development by directing agents to consult bundled documentation and source code rather than relying on memory, and provides patterns for fetching current model lists, working with the AI Gateway, and building agents with type-safe patterns.

Static Analysis Findings

1 finding

Patterns detected by deterministic static analysis before AI scoring. Hover over any finding code for detailed information and remediation guidance.

Remote Code Execution
SEC-031Script Download2x in 1 file

Dynamic script download for execution

SKILL.mdcurl -s https://ai-gateway.vercel.sh2x

Detected Capabilities

http requestcode readingpackage inspectionenvironment variable accessdocumentation lookup

Trigger Keywords

Phrases that agents use to match this skill to user intent.

build AI chatbotAI SDK setupadd AI to appfetch AI modelstool callingagent developmentuseChat hookAI Gateway authentication

Risk Signals

INFO

Dynamic script download via curl for model list retrieval (curl -s https://ai-gateway.vercel.sh/v1/models | jq)

SKILL.md, 'Choosing a Model' section

Referenced Domains

External domains referenced in skill content, detected by static analysis.

ai-gateway.vercel.shai-sdk.devgithub.comwww.apache.org

Use Cases

  • Build AI chatbots or text generation features using the AI SDK
  • Set up and authenticate with Vercel AI Gateway
  • Fetch current available models before writing SDK code
  • Integrate AI into React apps using hooks like useChat
  • Build type-safe agents using ToolLoopAgent or similar abstractions
  • Debug AI SDK calls and token usage with DevTools
  • Migrate to newer versions of the AI SDK safely

Quality Notes

  • Excellent emphasis on version-aware development — explicitly warns against relying on memory and directs agents to bundled docs
  • Clear, step-by-step installation and setup guidance for the AI package and dependencies
  • Good contextual scope: limits itself to the AI SDK ecosystem, does not attempt generic AI guidance
  • Well-structured sections with clear headings and logical flow
  • Includes concrete migration guidance and links to current documentation
  • Helpful examples of curl + jq for fetching model lists without hardcoding IDs
  • Strong documentation of guardrails: explicitly says 'if you cannot find support, say so explicitly — do not guess'
  • Could be more concrete on error handling patterns (e.g., what to do if API key is missing, if models endpoint is unreachable)
Model: claude-haiku-4-5-20251001Analyzed: Sep 23, 2026

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Version History

  1. v1.3

    Content updated

    ✦ AIExtends docs-location guidance for monorepo and workspace structures where `ai` may be nested.

    2026-09-23

    LATEST
  2. v1.2

    Content updated

    ✦ AIRemoves 4 reference files and updates SKILL.md content; resolves 6 security findings in ai-gateway.md.

    2026-09-09

    View This Version
  3. v1.1

    Content updated

    ✦ AIAdds version check against `node_modules/ai/package.json` in Prerequisites section.

    2026-06-28

    View This Version
  4. v1.0

    2026-05-02

    View This VersionInitial version

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