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Systematic Debugging

Checked
schlenks·vlatest·testing·MIT

Schlenks' systematic debugging analyzes code execution paths to pinpoint errors and suggest precise fixes using a structured approach.

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 schlenks/superpowers-bd --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

schlenks

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 schlenks/superpowers-bd at 30e3c5e96a.

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

Commit
30e3c5e96a
Manifest
skills/systematic-debugging/SKILL.md
Scanned
34 files, 2,372 lines
Copies in repo
2 — all of them scanned
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 a structured approach to debugging code, guiding the AI agent through a series of steps to identify and resolve issues. It emphasizes methodical investigation rather than random attempts at fixing errors. The tool helps isolate problems by systematically testing assumptions and narrowing down potential causes.

When to use it

  • When faced with complex bugs that are difficult to trace.
  • During code reviews to proactively identify potential issues.
  • To improve the efficiency of debugging processes within a team.
  • When needing to understand the root cause of unexpected behavior in an application.

Key capabilities

  • Systematic testing approach
  • Assumption verification
  • Root cause analysis
  • Isolation of problematic code sections

Example prompts

  • "Use Schlenks' Systematic Debugging to find the bug in this Python script."
  • "I’m seeing unexpected results. Can you use systematic debugging on this function?"
  • "Apply your systematic debugging process to isolate the cause of this error message: [error message]."

Tips & gotchas

The skill is most effective when provided with clear, concise code snippets and detailed descriptions of the observed behavior. It may require multiple iterations or clarifications to pinpoint the exact source of the problem.