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Ruby Refactor

Checked
pproenca·vlatest·backend·MIT

Automates Ruby code refactoring tasks like method extraction, renaming, and simplifying complex logic blocks.

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 pproenca/dot-skills --skill ruby-refactor -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

pproenca

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 pproenca/dot-skills at cf93c57cac.

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

Commit
cf93c57cac
Manifest
skills/.curated/ruby-refactor/SKILL.md
Scanned
51 files, 3,495 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 enables AI agents to automatically refactor Ruby code, improving readability and maintainability. It analyzes existing scripts to identify patterns that can be optimized or simplified without altering functionality.

When to use it

  • Cleaning up legacy Ruby applications with inconsistent coding styles.
  • Reducing technical debt in complex logic blocks before adding new features.
  • Standardizing codebases across a team to adhere to specific style guides.
  • Simplifying nested loops or conditional statements for easier debugging.

Key capabilities

  • Automatic detection of inefficient Ruby patterns.
  • Refactoring suggestions that preserve original program behavior.
  • Support for various Ruby syntax structures and idioms.
  • Integration into existing development workflows via AI agents.

Example prompts

  • "Refactor this legacy Ruby script to use modern block syntax instead of explicit loops."
  • "Analyze the provided controller logic and suggest ways to reduce code duplication."
  • "Optimize this complex conditional statement for better readability while keeping the same output."

Tips & gotchas

Ensure you provide complete context or full files when asking for refactoring, as isolated snippets may lead to incomplete suggestions. Always review AI-generated changes manually before committing them to production environments to verify logic integrity.