Skip to content
TrustedSkillsbeta
Back to all skills

Debug:Laravel

Checked
snakeo·vlatest·backend

Identifies and suggests fixes for Laravel application errors using code analysis and debugging best practices.

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 snakeo/claude-debug-and-refactor-skills-plugin --skill debug:laravel -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

snakeo

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 snakeo/claude-debug-and-refactor-skills-plugin at e2e79df88e.

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

Commit
e2e79df88e
Manifest
plugins/debug-and-refactor/skills/debug-laravel/SKILL.md
Scanned
1 file, 617 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 allows AI agents to debug Laravel applications. It can analyze code, identify errors, and suggest solutions based on common Laravel debugging patterns. The agent can also help refactor existing Laravel code for improved readability and maintainability.

When to use it

  • You're encountering a bug in your Laravel application and need assistance identifying the root cause.
  • You want to improve the structure and clarity of your Laravel codebase through refactoring.
  • You’re new to Laravel and need help understanding how to debug common issues.
  • You are experiencing performance bottlenecks within a Laravel application.

Key capabilities

  • Laravel code analysis
  • Error identification
  • Solution suggestions for debugging
  • Code refactoring

Example prompts

  • "I'm getting a 'Class not found' error in my Laravel application. Can you help me debug it?"
  • "Can you review this Laravel controller and suggest any improvements to its structure?"
  • "This Eloquent query is very slow, can you analyze it and recommend optimizations?"

Tips & gotchas

The agent’s effectiveness relies on providing clear and concise code snippets or error messages. Ensure the AI has sufficient context about your project's architecture for accurate debugging and refactoring suggestions.