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Systematic Debugging

Checked
grnfromdark·vlatest·testing

Systematically identifies and isolates software bugs using automated analysis and targeted test case generation.

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 grnfromdark/autodevskill --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

grnfromdark

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 grnfromdark/autodevskill at 79c05a2134.

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

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," assists AI agents in identifying and resolving software bugs through a structured process. It helps pinpoint root causes by analyzing error messages, stack traces, and code execution paths. The agent can then suggest or implement fixes based on this analysis, improving the reliability of applications.

When to use it

  • When an application is exhibiting unexpected behavior or errors.
  • During automated testing where failures need detailed investigation.
  • To assist developers in understanding complex error scenarios and accelerating debugging workflows.
  • For analyzing crash reports and identifying recurring issues in production environments.

Key capabilities

  • Error message analysis
  • Stack trace interpretation
  • Code execution path tracing
  • Root cause identification
  • Fix suggestion/implementation

Example prompts

  • "Analyze this error message: 'TypeError: Cannot read property 'name' of undefined'"
  • "Explain the stack trace from this crash report."
  • "Trace the code execution leading up to this error."
  • "Suggest a fix for this bug based on the provided information."

Tips & gotchas

The skill's effectiveness depends on providing clear and complete error data, including relevant code snippets or logs. It is intended as an aid to developers, not a replacement for thorough testing practices.