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Runpod

Checked
digitalsamba·vlatest·ai-ml·MIT

This skill lets you seamlessly launch and manage RunPod cloud GPUs for AI development, accelerating your projects with powerful compute resources.

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 digitalsamba/claude-code-video-toolkit --skill runpod -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

digitalsamba

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 digitalsamba/claude-code-video-toolkit at 225c80a1c3.

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

Commit
225c80a1c3
Manifest
.claude/skills/runpod/SKILL.md
Scanned
1 file, 211 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 runpod skill allows AI agents to interact with RunPod, a cloud platform for renting GPUs. It enables users to deploy and manage machine learning workloads on powerful hardware without needing to provision their own infrastructure. This includes launching virtual machines (Pods) pre-configured with specific software and resources.

When to use it

  • Running computationally intensive tasks: Execute large language models, image generation pipelines, or other demanding AI processes that require significant GPU power.
  • Deploying machine learning applications: Quickly deploy trained models as scalable API endpoints on RunPod's infrastructure.
  • Experimenting with different hardware configurations: Easily test and compare the performance of various GPU types and RAM amounts for optimal model training or inference.
  • Automating deployment workflows: Integrate RunPod into existing AI development pipelines to streamline the process of deploying and managing models.

Key capabilities

  • Launching RunPod Pods
  • Managing deployed Pods (starting, stopping)
  • Accessing pre-configured Pod templates
  • Selecting GPU types and RAM configurations

Example prompts

  • "Launch a RunPod with an A100 GPU and 32GB of RAM."
  • "Start the 'my_inference_pod' on RunPod."
  • “Find available RunPod templates for Stable Diffusion.”

Tips & gotchas

  • Requires familiarity with RunPod account setup and API keys. Ensure your AI agent has appropriate credentials to access and manage resources within your RunPod account.