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Systematic Debugging

Checked
sebas-aikon-intelligence·vlatest·testing·MIT

Systematically identifies and resolves software bugs through automated analysis and targeted code adjustments.

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 sebas-aikon-intelligence/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

sebas-aikon-intelligence

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 sebas-aikon-intelligence/antigravity-awesome-skills at 0f4a1b2fd7.

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

Commit
0f4a1b2fd7
Manifest
skills/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

The Systematic Debugging skill helps AI agents systematically identify and resolve errors in code or processes. It analyzes error messages, traces execution paths, and suggests potential fixes based on identified patterns. This skill aims to reduce debugging time and improve the reliability of automated tasks.

When to use it

  • Troubleshooting failing automation scripts: When a script designed for data processing consistently fails with unclear errors.
  • Debugging complex workflows: When an AI agent is executing a multi-step process that encounters unexpected issues.
  • Analyzing error logs: To quickly understand the root cause of recurring errors reported in system logs.
  • Improving code quality: Proactively identify and fix potential bugs before they impact production systems.

Key capabilities

  • Error message analysis
  • Execution path tracing
  • Pattern identification for common errors
  • Suggestion of potential fixes

Example prompts

  • "Analyze this error log: [paste error log here]"
  • "Trace the execution path that led to this failure: [describe the scenario and error]"
  • "Suggest a fix for this code snippet based on the following error message: [code snippet and error message]"

Tips & gotchas

The skill's effectiveness depends on providing clear and detailed information about the errors encountered. It is most useful when dealing with structured logs or code that can be easily analyzed by an AI agent.