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Algorithmic Art

Checked
prat011·vlatest·frontend

Generates unique, evolving artwork based on algorithms, offering a dynamic and visually stimulating creative experience.

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 prat011/awesome-llm-skills --skill algorithmic-art -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

prat011

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 prat011/awesome-llm-skills at 35e1ea23b6.

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

Commit
35e1ea23b6
Manifest
algorithmic-art/SKILL.md
Scanned
4 files, 618 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

This skill generates visual art using algorithms. It can produce a wide variety of images based on textual prompts, allowing for creative exploration and unique artwork generation. The output is intended to be visually appealing and potentially abstract or representational depending on the prompt provided.

When to use it

  • Creating custom illustrations for blog posts or presentations.
  • Generating visual assets for social media campaigns.
  • Exploring artistic styles and generating novel image concepts.
  • Producing unique wallpapers or digital art pieces.

Key capabilities

  • Generates images from text prompts.
  • Supports a variety of artistic styles (implied).
  • Produces visually appealing artwork.

Example prompts

  • "Generate an abstract landscape in the style of Kandinsky."
  • "Create a portrait of a cat wearing a hat, digital art."
  • "Produce a geometric pattern with vibrant colors."

Tips & gotchas

The quality and relevance of the generated images heavily depend on the clarity and specificity of the text prompts. Experimentation with different phrasing and artistic styles is encouraged to achieve desired results.