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Agent Builder Vercel Sdk

Checked
guaderrama·vlatest·cloud

Provides Vercel guidance and assistance for orchestrating AI agents and multi-step workflows.

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 guaderrama/cabo-health-ai --skill agent-builder-vercel-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

guaderrama

Taken from the source listing. We haven't verified who controls this account.

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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 guaderrama/cabo-health-ai at 356b9f1b58.

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

Scanned
1 file, 341 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 guaderrama-agent-builder-vercel-sdk skill provides tools for building and deploying AI agents. It simplifies the process of creating agents, likely offering pre-built components or templates. The SDK appears to be designed for integration with Vercel's platform, suggesting a focus on serverless deployments and potentially edge functions.

When to use it

  • Rapid Agent Prototyping: Quickly create and test agent ideas without extensive coding.
  • Vercel-Based Deployments: Easily deploy agents as part of a Vercel project for scalability and performance.
  • Agent Component Integration: Incorporate pre-built components or templates to accelerate development.
  • Serverless Agent Architecture: Build agents designed to run within a serverless environment.

Key capabilities

  • Agent building tools
  • Vercel SDK integration
  • Pre-built agent components/templates (implied)
  • Simplified deployment process

Example prompts

  • "Create an agent that summarizes news articles."
  • "Build a chatbot for customer support, deploying it to Vercel."
  • "Generate an agent using the 'sales assistant' template."

Tips & gotchas

The skill is designed for use with Vercel; familiarity with Vercel deployment processes will be beneficial. While simplifying agent creation, some coding knowledge may still be required depending on the complexity of the desired agent functionality.