systematic-debugging

Enforce root-cause investigation before proposing fixes for bugs and test failures.

1|1|Updated Apr 20, 2026

Search Tags:#debugging #root cause analysis #test failures #hypothesis testing #code verification #failure reproduction #error trace analysis

Ready to run

npx skills add https://github.com/svssdeva/agentic-skills --skill systematic-debugging-svssdeva

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/svssdeva/agentic-skills/tree/main/engineering/systematic-debugging
Command: npx skills add https://github.com/svssdeva/agentic-skills --skill systematic-debugging-svssdeva

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents wasting time on guesswork by enforcing root-cause investigation before any bug or failure fix is suggested.

Core Features & Use Cases

Root-cause first: Establishes a strict rule that fixes are forbidden until Phase 1 evidence identifies where the issue originates.
Repeatable investigation: Guides reproduction steps, error-message reading, and trace-based data flow analysis in multi-component systems.
Hypothesis-driven resolution: Requires single-hypothesis testing and minimal changes, then verifies with a failing test case before implementation.

Quick Start

Use the systematic-debugging skill when you hit a failing test or unexpected runtime behavior, and ask the AI to walk through Phase 1 to identify the root cause using the full error output and reproduction steps.

Frequently Asked Questions about systematic-debugging

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

FAQPage Schema

How do I find the root cause of test failures before applying code fixes?▼

To find the root cause of test failures, you must gather reproduction evidence and trace error outputs in Phase 1 before proposing fixes. This systematic debugging approach enforces root-cause investigation through evidence gathering, pattern analysis against working examples, and minimal hypothesis testing.

What is the best way to debug production defects without guessing?▼

The best way to debug production defects without guessing is hypothesis-driven resolution. You establish a strict rule forbidding fixes until root-cause evidence identifies where the issue originates, then verify a single-fix implementation with a failing test case.

How do I analyze error traces for multi-component integration problems?▼

To analyze error traces for multi-component integration problems, perform trace-based data flow analysis during the evidence gathering phase. This systematic approach guides reproduction steps and error-message reading to pinpoint exactly where the failure originates across integrated components.

Why should I use hypothesis testing for code verification instead of immediate patches?▼

Hypothesis testing for code verification prevents wasting time on guesswork. It requires testing a single minimal hypothesis and verifying it with a failing test case before implementation, ensuring your patch addresses the actual failure reproduction rather than masking symptoms.

Does root cause analysis work for build failures and performance regressions?▼

Yes, root cause analysis works for build failures and performance regressions. This systematic debugging skill is applicable to any technical issue, enforcing evidence gathering and pattern analysis against working examples before proposing any fix.