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Systematic Debugging

Checked
practicalswan·vlatest·testing·MIT

Systematically identifies and resolves software bugs using structured analysis and automated testing techniques.

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 practicalswan/agent-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

practicalswan

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 practicalswan/agent-skills at ff6d12f61e.

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

Commit
ff6d12f61e
Manifest
systematic-debugging/SKILL.md
Scanned
12 files, 1,418 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 practicalswan-systematic-debugging skill assists in identifying and resolving issues within AI agent workflows. It provides a structured approach to debugging, helping users pinpoint the root cause of errors by systematically analyzing logs and code execution paths. This skill focuses on improving the reliability and predictability of AI agents through methodical troubleshooting.

When to use it

  • Debugging unexpected behavior: When an AI agent produces incorrect or undesirable outputs, this skill can help isolate the source of the problem.
  • Analyzing error logs: The skill assists in interpreting complex error messages and identifying patterns that indicate underlying issues.
  • Reproducing intermittent failures: By guiding a systematic investigation, it aids in recreating infrequent errors to facilitate debugging.
  • Improving agent reliability: Regularly using this skill can proactively identify potential weaknesses in an AI agent's design or implementation.

Key capabilities

  • Log analysis and interpretation
  • Code execution path tracing
  • Error pattern identification
  • Systematic troubleshooting workflow guidance

Example prompts

  • "Analyze the attached error log and suggest possible causes."
  • "Trace the execution flow for this agent task, highlighting potential failure points."
  • "I'm seeing intermittent errors in my agent. Can you help me systematically debug it?"

Tips & gotchas

This skill is most effective when provided with detailed logs or access to the AI agent’s code. It assumes a basic understanding of programming concepts and debugging techniques; complex scenarios may require additional context for optimal results.