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Systematic Debugging

Checked
tavi-agency·vlatest·testing·MIT

Systematically identifies, isolates, and resolves software bugs using automated analysis and targeted code modifications.

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 tavi-agency/antigravity-awesome-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

tavi-agency

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 tavi-agency/antigravity-awesome-skills at c9a76a2d94.

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

Commit
c9a76a2d94
Manifest
skills/systematic-debugging/SKILL.md
Scanned
11 files, 1,221 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 allows AI agents to systematically debug code, identifying and correcting errors through a structured process. It can analyze error messages, trace execution flow, and suggest potential fixes based on identified issues. The agent will then apply the suggested fix and retest until the bug is resolved.

When to use it

  • When an AI agent encounters unexpected behavior or errors in code it has generated or modified.
  • During automated testing cycles to proactively identify and resolve bugs.
  • To assist developers in troubleshooting complex issues within a codebase.
  • When debugging third-party libraries integrated into a project.

Key capabilities

  • Error message analysis
  • Execution flow tracing
  • Bug fix suggestion
  • Automated retesting

Example prompts

  • "Debug the following code and explain the error: [code snippet]"
  • "I'm getting this error: '[error message]'. Can you systematically debug it?"
  • "Trace the execution of this function to identify why it is returning an incorrect value."

Tips & gotchas

The skill requires access to the code being debugged and may need specific permissions to modify files. Ensure the AI agent has appropriate credentials and context for effective debugging.