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Rails Ai:Debugging Rails

Checked
zerobearing2·vlatest·backend·MIT

Helps with AI, debugging as part of developing backend services and APIs workflows.

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 zerobearing2/rails-ai --skill rails-ai:debugging-rails -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

zerobearing2

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 zerobearing2/rails-ai at 8ece0d4398.

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

Commit
8ece0d4398
Manifest
skills/debugging/SKILL.md
Scanned
1 file, 239 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 assists in debugging Rails applications. It can analyze stack traces, identify potential causes of errors based on code context, and suggest solutions or relevant documentation. The AI agent using this skill is designed to understand common Rails error patterns and provide targeted assistance for resolving them.

When to use it

  • You're encountering a cryptic error message in your Rails application and need help understanding the root cause.
  • A test fails, and you want the AI to analyze the stack trace and suggest possible fixes.
  • You’re unsure how to interpret a complex stack trace involving multiple layers of middleware or gems.
  • You've already tried some debugging steps but are still stuck and need fresh perspective.

Key capabilities

  • Stack trace analysis
  • Error cause identification
  • Solution suggestions
  • Relevant documentation lookup

Example prompts

  • "Analyze this stack trace: [paste stack trace here]"
  • "I'm getting a NoMethodError in my Rails app, can you help me understand why?"
  • "This test is failing with an ActiveRecord::RecordNotFound error. What could be the problem?"

Tips & gotchas

  • Ensure the AI agent has access to relevant parts of your Rails application’s codebase for accurate analysis. Providing more context improves results.