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Ralph Gpu

Official
vercel-labs·vlatest·ai-ml

Ralph GPU accelerates complex computations by leveraging powerful GPUs, boosting performance for demanding tasks and data processing.

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/ralph-gpu --skill ralph-gpu -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 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 vercel-labs/ralph-gpu at 4f47ced574.

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

Commit
4f47ced574
Manifest
SKILLS/ralph-gpu/SKILL.md
Scanned
11 files, 1,679 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 ralph-gpu skill provides access to GPU resources. It allows AI agents to leverage powerful graphics processing units for computationally intensive tasks, accelerating performance and enabling complex operations. This is particularly useful for workloads that benefit from parallel processing.

When to use it

  • Image generation: Generate high-resolution images or videos more quickly than with CPU-only processing.
  • Scientific simulations: Run complex scientific models and simulations requiring significant computational power.
  • Machine learning training: Accelerate the training of machine learning models, especially deep neural networks.
  • Video editing/processing: Perform demanding video editing tasks like rendering or transcoding.

Key capabilities

  • GPU resource access
  • Accelerated computation
  • Parallel processing support

Example prompts

  • "Generate a 4K image of a futuristic cityscape using the GPU."
  • "Run this scientific simulation and provide the results, utilizing available GPU resources."
  • "Train this machine learning model on this dataset, leveraging the GPU for faster iteration."

Tips & gotchas

The ralph-gpu skill requires an environment with access to a compatible GPU. Ensure your AI agent's configuration is set up correctly to utilize the allocated GPU resources.