systematic-debugging

Diagnose and isolate root causes of software bugs and test failures.

2|1|Updated Apr 3, 2026
One-click install
npx skills add https://github.com/GACLove/feishu-aily-skills --skill systematic-debugging-gaclove
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/GACLove/feishu-aily-skills/tree/main/skills/systematic-debugging
Command: npx skills add https://github.com/GACLove/feishu-aily-skills --skill systematic-debugging-gaclove

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents wasted time and recurring regressions by forcing an evidence-driven approach to bugs, test failures, flaky behavior, build and integration problems, and production incidents so you fix the root cause instead of masking symptoms.

Core Features & Use Cases

  • Structured four-phase process: clear Phase 1 (investigation), Phase 2 (pattern analysis), Phase 3 (single-hypothesis testing), and Phase 4 (implementation) to ensure disciplined progress.
  • Evidence-first techniques: reproduce reliably, add instrumentation at component boundaries, trace data flow back to the original trigger, and create minimal failing tests before changing behavior.
  • Guardrails and escalation rules: single-hypothesis testing, stop-and-reanalyze mandates, limits on consecutive fixes, and guidance to question architecture when multiple fixes fail.
  • Use cases: on-call production incident triage, flaky test elimination, multi-component integration debugging, and preventing symptom-driven hotfixes.

Quick Start

Load the systematic-debugging skill and start Phase 1 by reproducing the issue consistently, collecting diagnostic evidence across layers, then form a single testable hypothesis and validate it with the smallest possible change.

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 flaky test failures?

Isolate flaky test root causes by reproducing the failure reliably, tracing data flow across component boundaries with targeted instrumentation, and validating a single testable hypothesis before applying minimal changes.

What is the best way to debug production incidents across multi-component systems?

Triage production incidents by collecting diagnostic evidence across multi-component layers, analyzing failure patterns, and testing single hypotheses with minimal-change validation to fix root causes instead of masking symptoms.

How do I stop recurring regressions when multiple fixes fail?

Halt recurring regressions by triggering stop-and-reanalyze guardrails after consecutive failed fixes, questioning multi-component architecture, and validating minimal changes against minimal failing tests.

Why do I need to create minimal failing tests before changing behavior?

Creating minimal failing tests before changing behavior ensures evidence-driven root cause isolation, preventing symptom-driven hotfixes and verifying that integration or build failures are genuinely resolved.

Does systematic debugging work for build failures and performance issues?

Systematic debugging applies to build failures and performance issues by deploying layered instrumentation across multi-component boundaries and testing single hypotheses to trace triggers back to their original source.