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Systematic Debugging

Listed
bobmatnyc·vlatest·testing·MIT

Systematically identifies and isolates software bugs using structured analysis and automated reproduction techniques.

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 bobmatnyc/claude-mpm-skills --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

bobmatnyc

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No credential access: failed

    Touches credential material in 1 place.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

    What it found

    • universal/debugging/systematic-debugging/references/examples.md:373OS keychain / credential manager
      # "~/Library/Keychains/login.keychain-db"

  • 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 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 bobmatnyc/claude-mpm-skills at 718070a7d6.

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

Commit
718070a7d6
Manifest
universal/debugging/systematic-debugging/SKILL.md
Scanned
6 files, 1,798 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 enables AI agents to perform methodical troubleshooting by breaking down complex technical issues into smaller, manageable components. It focuses on isolating root causes through a structured, step-by-step analysis rather than guessing or applying random fixes.

When to use it

  • Diagnosing intermittent failures in production environments where the cause is unclear.
  • Debugging intricate code logic errors that standard linting tools miss.
  • Analyzing system logs to pinpoint the exact sequence of events leading to a crash.
  • Resolving configuration conflicts between multiple integrated services or libraries.

Key capabilities

  • Decomposes vague error messages into specific, actionable investigation steps.
  • Simulates a human debugger's thought process to hypothesize and test potential causes.
  • Generates targeted diagnostic commands or code snippets to verify assumptions.
  • Maintains context of previous debugging attempts to avoid circular reasoning.

Example prompts

  • "My API returns 500 errors sporadically; use systematic debugging to identify the likely trigger."
  • "I'm getting a deadlock in my multithreaded script. Break this down step-by-step to find the lock contention point."
  • "Analyze these error logs systematically to determine if the failure is due to network latency or application logic."

Tips & gotchas

Ensure you provide sufficient context, such as relevant code snippets or log excerpts, so the agent can form accurate hypotheses. This skill works best for logical and software-related issues; it may not be effective for hardware malfunctions without specific sensor data.