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Systematic Debugging

Checked
xenitv1·vlatest·testing·MIT

Systematically identifies and isolates software bugs through guided analysis and automated 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 xenitv1/antigravity-workflows --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

xenitv1

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 xenitv1/antigravity-workflows at f0a1fa789c.

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

Commit
f0a1fa789c
Manifest
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, xenitv1-systematic-debugging, helps AI agents systematically debug code. It identifies potential errors and suggests fixes based on a structured approach to problem solving. The tool aims to improve the reliability of agent outputs by proactively addressing coding issues.

When to use it

  • When an AI agent produces incorrect or unexpected results from code generation tasks.
  • During development cycles for complex automated workflows where debugging is frequent.
  • To identify and resolve errors in scripts that control external systems or APIs.
  • For improving the robustness of agents performing data manipulation or analysis.

Key capabilities

  • Error identification
  • Fix suggestion
  • Structured problem solving approach
  • Code reliability improvement

Example prompts

  • "Debug this Python code: [code snippet]"
  • "I'm getting an error in my script, can you help me find the issue? Here's the code: [code snippet]"
  • "Systematically debug this Javascript function and suggest improvements: [function definition]"

Tips & gotchas

The skill is most effective when provided with complete and well-formatted code. It assumes a basic understanding of programming concepts; complex or highly specialized code might require more context for accurate debugging.