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Systematic Debugging

Checked
guyhoozdis·vlatest·testing·MIT

Systematically identifies and resolves software bugs using guided analysis and automated test case generation.

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 guyhoozdis/superpowers --skill systematic-debugging -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

guyhoozdis

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 guyhoozdis/superpowers at 0b35ec30ec.

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

Scanned
11 files, 1,223 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 systematically debug code, identifying and isolating issues through a structured process. It can analyze error messages, trace execution paths, and suggest potential fixes based on identified patterns. The agent will provide detailed explanations of its debugging steps and reasoning.

When to use it

  • When an AI agent is producing incorrect or unexpected results in a software program.
  • To troubleshoot complex errors that are difficult to diagnose manually.
  • For automated regression testing, ensuring code changes haven't introduced new bugs.
  • When needing assistance understanding the root cause of a specific error message.

Key capabilities

  • Error Message Analysis
  • Execution Path Tracing
  • Pattern Recognition for Bug Identification
  • Suggestion of Potential Fixes
  • Detailed Explanation of Debugging Steps

Example prompts

  • "Debug this Python code and explain the issue: [code snippet]"
  • "I'm getting a 'TypeError: unsupported operand type(s) for +:' error. Can you help me debug it?"
  • "Trace the execution path of this function to find out why it’s returning an incorrect value."

Tips & gotchas

The agent requires access to the relevant code base and any associated logs or documentation to effectively perform debugging. Providing clear context about the expected behavior is crucial for accurate analysis.