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Systematic Debugging

Checked
pauloviccs·vlatest·testing

Systematically identifies and resolves software bugs using logical analysis and targeted test case generation.

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 pauloviccs/viccs_antigravity_skillscreator --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

pauloviccs

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 pauloviccs/viccs_antigravity_skillscreator at 3afb8c5f30.

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

Commit
3afb8c5f30
Manifest
.agent/skills/systematic-debugging/SKILL.md
Scanned
1 file, 98 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, pauloviccs-systematic-debugging, helps AI agents systematically identify and resolve errors in code or processes. It breaks down complex issues into smaller, manageable steps, allowing for a more structured debugging approach. The agent can analyze error messages, trace execution paths, and suggest potential fixes based on the identified problem areas.

When to use it

  • Debugging failing scripts: Use when an AI agent's script isn’t producing the expected output or encountering errors.
  • Troubleshooting complex workflows: Employ this skill when a multi-step process is malfunctioning, and pinpointing the source of failure is difficult.
  • Analyzing error logs: When presented with lengthy error messages or log files, use this to extract meaningful insights and identify root causes.
  • Improving code reliability: Integrate into development cycles to proactively find and fix potential issues before deployment.

Key capabilities

  • Error message analysis
  • Execution path tracing
  • Root cause identification
  • Suggestion of fixes

Example prompts

  • "Debug this Python script: [script content]. Explain the error and suggest a solution."
  • "I'm getting 'TypeError: unsupported operand type(s) for +:' in my code. Can you help me find the problem?"
  • "Analyze these log files and identify the cause of the system crash."

Tips & gotchas

The skill’s effectiveness depends on clear error messages or detailed logs being provided to the AI agent. Without sufficient information, it may struggle to accurately diagnose the issue.