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Ai Sdk

Official
vercel·vlatest·cloud

Helps with Vercel, AI as part of building AI and machine learning applications workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add vercel/vercel-plugin --skill ai-sdk -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

vercel

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: ai-gateway.vercel.sh.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    ai-gateway.vercel.shundeclared

    What it found

    • skills/ai-sdk/SKILL.md:356contacts ai-gateway.vercel.sh
      curl -s https://ai-gateway.vercel.sh/v1/models | jq -r '.data[].id'
    • skills/ai-sdk/SKILL.md:359contacts ai-gateway.vercel.sh
      curl -s https://ai-gateway.vercel.sh/v1/models | jq -r '[.data[] | select(.id | startswith("anthropic/")) | .id] | reverse | .[]'

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned vercel/vercel-plugin at c632a50838.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
c632a50838
Manifest
skills/ai-sdk/SKILL.md
Scanned
2 files, 698 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

vercel-ai-sdk

What it does

This skill enables AI agents to interact with the Vercel AI SDK, allowing them to generate and stream responses from various large language models. It provides a standardized interface for handling chat completions and managing model interactions efficiently within serverless environments.

When to use it

  • Building real-time chat interfaces that require low-latency streaming responses from LLMs.
  • Integrating multiple AI providers into a single application using a unified SDK pattern.
  • Developing serverless functions that need to process natural language inputs and outputs without heavy infrastructure.
  • Creating scalable conversational agents that leverage Vercel's edge network for faster model inference.

Key capabilities

  • Streamlined generation of chat completions across supported models.
  • Native support for streaming responses to improve user experience.
  • Simplified integration with Vercel's ecosystem and serverless architecture.
  • Standardized API patterns for consistent AI agent behavior.

Example prompts

  • "Set up a chat interface using the Vercel AI SDK that streams responses from an LLM in real-time."
  • "Create a serverless function to handle user queries via the vercel-ai-sdk and return formatted JSON responses."
  • "Integrate multiple language models into my application using the standardized patterns provided by this skill."

Tips & gotchas

Ensure your environment is configured with valid API keys for the target LLM providers before initializing the SDK. While the SDK simplifies integration, complex model-specific configurations may still require manual adjustments outside the standard skill parameters.