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Webgpu

Listed
cazala·vlatest·other

WebGPU enables developers to accelerate graphics and compute workloads on modern browsers using GPU hardware, boosting performance for demanding 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 cazala/webgpu-skill --skill webgpu -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

cazala

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 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 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: opencollective.com, tidelift.com.

    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

    github.comsource hostopencollective.comundeclaredtidelift.comundeclared

    What it found (3 of 14)

    • package-lock.json:761contacts opencollective.com
      "url": "https://opencollective.com/parcel"
    • package-lock.json:795contacts opencollective.com
      "url": "https://opencollective.com/parcel"
    • package-lock.json:816contacts opencollective.com
      "url": "https://opencollective.com/parcel"

  • 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 cazala/webgpu-skill at e439805867.

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

Commit
e439805867
Manifest
SKILL.md
Scanned
24 files, 3,039 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 webgpu skill enables AI agents to interact with WebGPU, a modern graphics and compute API designed for the web. It allows developers to leverage GPU acceleration for tasks like rendering 3D graphics, performing complex computations, or processing large datasets efficiently in web environments.

When to use it

  • When building high-performance web applications that require GPU-accelerated rendering or computation.
  • For developing real-time visualizations or simulations that benefit from parallel processing capabilities.
  • When optimizing data-intensive tasks such as image processing or machine learning inference on the client side.

Key capabilities

  • Access to low-level GPU APIs via WebGPU.
  • Support for shader programming and compute shaders.
  • Integration with web technologies like WebGL, allowing migration or enhancement of existing graphics workflows.

Example prompts

  • "Set up a WebGPU context in my browser-based 3D game."
  • "Render a complex scene using WebGPU shaders."
  • "Optimize this image processing algorithm using WebGPU compute shaders."

Tips & gotchas

  • Ensure your environment supports WebGPU, as it is not available on all browsers or devices.
  • Familiarity with shader programming and GPU architecture can greatly improve results when working with this skill.