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Systematic Debugging

Checked
poletron·vlatest·testing·CC0-1.0

Systematically identifies and isolates software bugs using automated tests and analysis within Poletron environments.

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 odjaramillo/custom-rules --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

poletron

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 poletron/custom-rules at aba6668777.

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

Commit
aba6668777
Manifest
registry/skills/systematic-debugging/SKILL.md
Scanned
22 files, 2,510 lines
Copies in repo
2 — all of them scanned
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 poletron-systematic-debugging skill provides a structured approach to debugging code. It helps identify and isolate issues through methodical testing and analysis, rather than relying on guesswork or random changes. This skill aims to improve the reliability of AI agent actions by ensuring thorough verification of their underlying logic.

When to use it

  • Debugging complex workflows: When an AI agent's sequence of steps produces unexpected results, this skill can systematically pinpoint the source of the error.
  • Reproducing intermittent failures: If a problem only occurs occasionally, poletron-systematic-debugging assists in creating controlled tests to consistently trigger and resolve it.
  • Validating new code changes: After implementing modifications to an AI agent's logic, this skill ensures that the changes haven’t introduced regressions or unintended side effects.
  • Analyzing failing unit tests: When existing unit tests fail, use this skill to methodically investigate the root cause of the failure.

Key capabilities

  • Systematic testing methodology
  • Error isolation techniques
  • Reproducible test case generation
  • Regression prevention

Example prompts

  • "Debug the following Python function and identify why it's returning incorrect results."
  • "Create a systematic test suite for this AI agent workflow to ensure reliability."
  • "Analyze these error logs and pinpoint the root cause of the failure using a structured debugging approach."

Tips & gotchas

This skill is most effective when applied to code or workflows with clear, defined steps. It may require some initial setup to define test parameters and expected outcomes.