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Hotwire Patterns

Checked
dchuk·vlatest·backend·MIT

Analyzes complex data streams to identify hidden patterns and anomalies, enabling rapid response and predictive action.

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 dchuk/rails_ai_agents --skill hotwire-patterns -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

dchuk

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 dchuk/rails_ai_agents at e3f5bd8229.

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

Scanned
5 files, 933 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 provides access to Hotwire patterns, a modern approach to building web applications with Rails. It allows AI agents to understand and generate code leveraging Turbo, Stimulus, and other components of the Hotwire stack. The agent can assist in creating interactive user interfaces and streamlining development workflows within a Rails environment.

When to use it

  • Generating Turbo Streams for real-time updates on a dashboard.
  • Creating Stimulus controllers to handle complex client-side interactions.
  • Developing new features using Hotwire's approach to full-stack web development.
  • Refactoring existing Rails views to utilize Turbo and Stimulus components.

Key capabilities

  • Turbo integration
  • Stimulus controller generation
  • Understanding of Hotwire conventions
  • Rails application context awareness

Example prompts

  • "Generate a Turbo Stream action for updating the status of a task."
  • "Create a Stimulus controller to handle form validation on this page."
  • "Show me an example of using Hotwire to build a live-updating chat interface."

Tips & gotchas

This skill is most effective when used within a Rails project. A basic understanding of Ruby and web development principles will improve the quality of generated code.