debug-helper_skill

This skill guides systematic debugging to reproduce, collect data, narrow down causes, and verify fixes across logs, environment, and code.
  • Python

0

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill enoch-robinson/agent-skill-collection --skill debug-helper

  • SKILL.md1.9 KB

Overview

This skill is a Debug Helper that provides a systematic methodology to find and fix bugs, errors, exceptions, and performance issues. It guides you through reproducibility, targeted information collection, scope reduction, root-cause analysis, and verification of fixes. It produces a concise diagnostic report template to communicate findings and preventive measures.

How this skill works

The skill inspects error messages, stack traces, logs, environment and recent code changes to build a clear problem picture. It recommends targeted commands and patterns for log analysis, uses divide-and-conquer (binary search) to localize faults, and suggests minimal reproducible cases and rubber-duck debugging to expose logic errors. Finally, it outlines verification steps and a report format for remediation and prevention.

When to use it

  • When you encounter runtime errors, crashes, or uncaught exceptions.
  • When performance is degraded (slow responses, high CPU or memory).
  • When logs are noisy and you need to trace request or error origins.
  • When a bug is intermittent and you must establish reproducible steps.
  • When you need a clear remediation plan and preventive actions.

Best practices

  • Start by reproducing the issue and capturing a minimal test case.
  • Collect full error messages, stack traces, environment and dependency versions.
  • Use binary search (log/feature toggles) to narrow the failing region quickly.
  • Analyze logs with focused grep/time filters and follow request IDs.
  • Validate fixes with tests and a repeatable verification procedure.

Example use cases

  • Investigating a null reference or index-out-of-range runtime exception in production.
  • Tracing a slow API to an N+1 database query or blocking I/O inside a loop.
  • Locating memory leak sources by comparing heap usage across deployments.
  • Building a minimal reproducible example to share with teammates or issue trackers.
  • Generating a concise problem diagnostic report for postmortem or release notes.

FAQ

Provide the full error and stack trace, minimal reproducible steps, environment details (OS, language and dependency versions), and recent code changes.

How do I narrow down where the bug lives?

Apply a binary search strategy: add logging or toggles at midpoints, determine which half contains the fault, and iterate until you isolate the offending code line or module.

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