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Error Debugger

Checked
jackspace·vlatest·testing·MIT

This Error Debugger analyzes code snippets to identify potential issues and suggests fixes, boosting developer efficiency and reducing debugging time.

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 jackspace/claudeskillz --skill error-debugger -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

jackspace

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 jackspace/claudeskillz at aef4e299d1.

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

Commit
aef4e299d1
Manifest
skills/error-debugger/SKILL.md
Scanned
4 files, 1,135 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

The error-debugger skill helps AI agents identify and correct errors in code or text. It analyzes provided input, pinpoints specific issues like syntax errors or logical flaws, and suggests potential fixes. This allows the agent to improve its output quality and reduce debugging time significantly.

When to use it

  • When an AI agent produces code with syntax errors that need correction.
  • To identify logical errors in a generated text sequence or script.
  • For troubleshooting issues when an AI agent's output doesn’t match the expected behavior.
  • To help understand why an AI agent is generating incorrect results and to improve its reasoning process.

Key capabilities

  • Error identification
  • Syntax error correction
  • Logical flaw detection
  • Suggestion of fixes

Example prompts

  • "Debug this Python code: print("Hello, world)"
  • "I'm getting a 'TypeError' in my JavaScript code. Can you help me find the problem?"
  • "This generated text is incorrect: '[text]'. Please identify and correct any errors."

Tips & gotchas

The skill’s effectiveness depends on providing clear and concise input containing the problematic code or text. Ensure the agent has sufficient context to understand the intended functionality for accurate debugging suggestions.