systematic-debugging

Enforce a four-phase debugging workflow to identify root causes before fixes.

3|Updated May 31, 2024

Search Tags:#debugging #evidence #software-quality #root-cause #reproduction #phase-based #hypothesis-testing

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npx skills add https://github.com/hugo-berendi/yomi --skill systematic-debugging-hugo-berendi

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Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/hugo-berendi/yomi/tree/main/.opencode/skills/systematic-debugging
Command: npx skills add https://github.com/hugo-berendi/yomi --skill systematic-debugging-hugo-berendi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic debugging solves the problem of guessing and patching without understanding root causes.

Core Features & Use Cases

Four-Phase Framework: Root Cause Investigation, Pattern Analysis, Hypothesis and Testing, and Implementation ensure methodical debugging.
Evidence-Driven: Emphasizes reproduction, data gathering, and traceability across components.
Real-World Use Case: When a bug appears in a CI pipeline, this skill guides you to reproduce, measure, and confirm root cause before fixes.

Quick Start

Follow Phase 1 steps on a new issue: reproduce the bug, collect errors and logs, and begin Root Cause Investigation.

Frequently Asked Questions about systematic-debugging

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

FAQPage Schema

What is systematic debugging and when should I use it?▼

Systematic debugging is a structured workflow that identifies root causes before proposing fixes. You should use it for any technical issue, including test failures, production bugs, and unexpected behavior, to avoid guessing and patching without understanding.

How do I debug a CI pipeline failure using a root cause investigation approach?▼

To debug a CI pipeline failure, start by reproducing the bug, collecting errors and logs, and beginning Root Cause Investigation. This structured approach guides you to reproduce, measure, and confirm the root cause before applying any fixes.

What are the phases of a structured debugging workflow?▼

A structured debugging workflow implements four phases: Root Cause Investigation, Pattern Analysis, Hypothesis and Testing, and Implementation. These phases enforce methodical debugging through error review, reproducibility, data gathering, and validated fixes.

How do I test a hypothesis when debugging unexpected software behavior?▼

To test a hypothesis when debugging unexpected software behavior, follow the Hypothesis and Testing phase, which requires thorough analysis and evidence gathering to validate the root cause before you proceed to the Implementation phase with confirmed fixes.

Does systematic debugging work for production bugs and test failures?▼

Yes, systematic debugging applies to any technical issue, including production bugs and test failures. It enforces an evidence-driven process requiring reproduction, data gathering, and traceability across components to ensure root causes are confirmed.

Why should I gather evidence before fixing a software bug?▼

You should gather evidence before fixing a software bug because systematic debugging solves the problem of guessing and patching without understanding root causes. Evidence-driven reproduction and data gathering ensure traceability and validated fixes.