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Ai Sdk

Official
vercel-labs·vlatest·cloud·MIT

Official vercel-labs skill covering Vercel, AI for building AI and machine learning applications.

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-labs/open-agents --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-labs

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 (3 of 4)

    • .agents/skills/ai-sdk/references/ai-gateway.md:50contacts ai-gateway.vercel.sh
      curl https://ai-gateway.vercel.sh/v1/models
    • .agents/skills/ai-sdk/references/ai-gateway.md:57contacts ai-gateway.vercel.sh
      curl -s https://ai-gateway.vercel.sh/v1/models | jq -r '[.data[] | select(.id | startswith("anthropic/")) | .id] | reverse | .[]'
    • .agents/skills/ai-sdk/references/ai-gateway.md:60contacts ai-gateway.vercel.sh
      curl -s https://ai-gateway.vercel.sh/v1/models | jq -r '[.data[] | select(.id | startswith("openai/")) | .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-labs/open-agents at cf865e94de.

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

Commit
cf865e94de
Manifest
.agents/skills/ai-sdk/SKILL.md
Scanned
5 files, 780 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

What it does

The vercel-labs/ai-sdk skill provides access to a set of tools and functionalities developed by Vercel Labs. It allows AI agents to interact with various services and APIs, streamlining development workflows and enabling advanced capabilities within AI applications. This SDK simplifies complex operations, making them accessible through straightforward commands.

When to use it

  • Automated Deployment: Automate the deployment of new features or updates to Vercel projects directly from an AI agent.
  • Infrastructure Management: Manage Vercel infrastructure components like deployments and functions programmatically using AI-driven instructions.
  • API Integration: Integrate with other Vercel services and APIs for data retrieval, processing, and interaction within your AI applications.
  • Workflow Automation: Automate repetitive tasks related to Vercel project management and development.

Key capabilities

  • Deployment automation
  • Infrastructure management
  • Vercel API integration
  • Simplified command structure

Example prompts

  • "Deploy the latest changes from my main branch."
  • "List all active deployments for this project."
  • "Create a new Vercel function named 'hello-world'."
  • "Get the status of deployment ID XYZ123."

Tips & gotchas

Requires an understanding of Vercel's command-line interface and API structure. Ensure your AI agent has appropriate credentials configured to interact with your Vercel account for successful execution.