debugging

Diagnose software defects through reproduction, hypothesis testing, and verification.

1|Updated Feb 11, 2026
One-click install
npx skills add https://github.com/xiaoshuangLi/aibo --skill debugging-xiaoshuangli
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: debugging
Source: https://github.com/xiaoshuangLi/aibo/tree/main/skills/debugging
Command: npx skills add https://github.com/xiaoshuangLi/aibo --skill debugging-xiaoshuangli

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic debugging methodology provides a repeatable approach to diagnosing and resolving software defects, reducing guesswork and debugging time.

Core Features & Use Cases

  • Structured debugging workflow: reproduce, analyze, hypothesize, test, and verify.
  • Log, stack-trace, and error-message analysis guidance to identify root causes.
  • Use Case: diagnosing flaky tests or performance regressions across a codebase.

Quick Start

Describe the bug with steps to reproduce and attach relevant logs to start a structured debugging session.

Frequently Asked Questions about debugging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze a stack trace to find the root cause of a bug?

To analyze a stack trace for root-cause-analysis, follow a structured debugging workflow that enforces stepwise reproduction, hypothesis formation, targeted testing, and documented verification to resolve software defects reliably.

What is the best way to diagnose flaky tests across my codebase?

Diagnosing flaky tests requires a systematic debugging methodology that reproduces the failure, analyzes logs, forms hypotheses, and runs targeted tests to verify the root cause before applying a fix.

How do I fix performance regressions using log analysis?

Fixing performance regressions through log analysis involves reproducing the regression stepwise, interpreting error messages and logs to form hypotheses, and testing targeted fixes to verify the resolution.

Can I use this structured debugging workflow for any software defect?

Yes, this structured debugging workflow is applicable to bug reproduction, log and stack-trace analysis, flaky tests, and performance regressions across codebases without requiring specific dependencies.

Why should I use a systematic debugging methodology instead of guessing?

A systematic debugging methodology reduces guesswork and debugging time by providing a repeatable, scientific approach to diagnose and resolve software defects through structured reproduction and verification.

What information do I need to start a structured debugging session?

To start a structured debugging session, describe the bug with steps to reproduce and attach relevant logs or stack traces to initiate the workflow.