diagnosing-bugs

Name: diagnosing-bugs
Availability: InStock
Author: CarbonTails

Guide software engineers through structured phases to diagnose bugs and performance regressions.

Updated Jun 15, 2026

Search Tags:#debugging #systematic approach #hypothesis testing #bug diagnosis #performance regression

Ready to run

npx skills add https://github.com/CarbonTails/Di-Vincis-Atelier --skill diagnosing-bugs-carbontails

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: diagnosing-bugs
Source: https://github.com/CarbonTails/Di-Vincis-Atelier/tree/main/.cursor/skills/diagnosing-bugs
Command: npx skills add https://github.com/CarbonTails/Di-Vincis-Atelier --skill diagnosing-bugs-carbontails

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a structured approach to diagnose hard-to-find bugs and performance regressions, ensuring a systematic and efficient debugging process.

Core Features & Use Cases

Diagnosis Loop: Offers a comprehensive loop for identifying and diagnosing bugs, including bisection, hypothesis-testing, and instrumentation.
Phase-Based Approach: Breaks down the debugging process into manageable phases (Build Feedback Loop, Reproduce + Minimise, Hypothesise, Instrument, Fix + Regression Test, Cleanup + Post-mortem).
Minimal Reproducible Scenario: Focuses on creating a minimal scenario that still triggers the bug for easier analysis.
Hypothesis Testing: Encourages the creation of falsifiable hypotheses to guide the debugging process.
Instrumentation and Logging: Provides guidelines for effective logging and instrumentation to aid in debugging.

Quick Start

Use the 'diagnosing-bugs' skill to start diagnosing a bug by building a feedback loop that will help you identify its cause.

Frequently Asked Questions about diagnosing-bugs

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

FAQPage Schema

What is a systematic approach to diagnosing hard-to-find software bugs?▼

A systematic approach to diagnosing hard bugs involves a structured loop: building a feedback loop, reproducing and minimizing the bug, formulating falsifiable hypotheses, instrumenting, fixing, and regression testing.

How do I reproduce and minimise a bug for easier debugging?▼

To reproduce and minimise a bug, focus on creating a minimal reproducible scenario that still reliably triggers the issue, which narrows down the problem space and makes analysis significantly easier.

How does hypothesis testing work when debugging performance regressions?▼

Hypothesis testing for performance regressions involves creating falsifiable hypotheses about the cause, then using instrumentation and logging to gather data that either confirms or eliminates each potential theory.

What is the best way to structure a complex debugging workflow?▼

The best way to structure a debugging workflow is through a phase-based approach: build a feedback loop, reproduce and minimise, hypothesise, instrument, fix with regression testing, and end with cleanup and a post-mortem.

Can I use bisection to find the source of a performance regression?▼

Yes, bisection is part of the comprehensive diagnosis loop, allowing you to systematically narrow down commits or changes that introduced the performance regression by repeatedly testing subsets of your codebase.

What should I do if my initial bug hypothesis is wrong?▼

If your initial bug hypothesis is wrong, the systematic approach encourages creating falsifiable hypotheses, meaning you use the disproven theory to refine your instrumentation and guide the next debugging phase.