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.