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Systematic Debugging

Checked
julianromli·vlatest·testing

Systematically identifies and resolves code errors using structured debugging techniques and comprehensive error analysis.

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 julianromli/opencode-template --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

julianromli

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 julianromli/opencode-template at 37ceab2d64.

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

Commit
37ceab2d64
Manifest
skill/systematic-debugging/SKILL.md
Scanned
11 files, 1,218 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, systematic-debugging, helps AI agents systematically identify and resolve issues in code. It allows the agent to break down complex problems into smaller, manageable steps, test hypotheses, and pinpoint the root cause of errors. The skill facilitates a more structured debugging process compared to trial-and-error approaches.

When to use it

  • When an AI agent is producing incorrect or unexpected results in code.
  • During automated testing phases where failures need thorough investigation.
  • To debug complex algorithms or systems with multiple interacting components.
  • When facing obscure errors that are difficult to diagnose through standard debugging techniques.

Key capabilities

  • Systematic error isolation
  • Hypothesis generation and testing
  • Root cause analysis
  • Structured debugging process

Example prompts

  • "Debug this code and explain the systematic steps you took."
  • "I'm getting an unexpected output; can you systematically debug it?"
  • "This function is failing. Use your systematic debugging skill to find the error."

Tips & gotchas

The agent’s effectiveness depends on its underlying coding knowledge. While this skill provides a structured approach, it cannot compensate for a lack of fundamental programming understanding.