What happens if multiple fix attempts fail?

After three failed fix attempts, the skill triggers a shift in strategy to question the underlying architecture rather than continuing to treat symptoms.

How does this skill handle multi-layer systems?

It implements diagnostic instrumentation at component boundaries to trace data flow, logging exactly what enters and exits each layer to identify the specific failing component.

When should I use the Systematic Debugging skill?

It should be used for any technical issue including test failures, production bugs, build errors, or whenever a 'simple' fix has already failed to solve the problem.

What is the primary rule of the Systematic Debugging skill?

The core 'Iron Law' is that no fixes should be proposed or implemented until a thorough root cause investigation is completed and the issue is consistently reproduced.

Is this skill compatible with Test-Driven Development (TDD)?

Yes, it specifically requires the creation of a failing test case in Phase 4 to verify the fix and ensure the bug does not regress in the future.

Systematic Debugging

Name: Systematic Debugging
Author: SkogAI

bySkogAI

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보안 및 테스팅

Enforces a rigorous four-phase framework to identify root causes and implement stable fixes for any technical issue.

소개

This skill provides a structured methodology to eliminate guesswork in software debugging by mandating a thorough root cause investigation before any fix is proposed. By guiding Claude through a sequence of investigation, pattern analysis, hypothesis testing, and implementation, it prevents the introduction of new bugs and ensures that even complex multi-component failures are resolved permanently. It is particularly effective for troubleshooting intermittent failures, architectural flaws, and performance regressions where random patching would otherwise lead to technical debt.

주요 기능

Mandatory root cause investigation phase before code changes
Evidence-based pattern analysis and reference comparison
1 GitHub stars
Diagnostic instrumentation for multi-component system boundaries
Scientific hypothesis testing with minimal variable changes
Architectural re-evaluation triggers after repeated fix failures

사용 사례

Debugging intermittent CI/CD pipeline or build failures
Resolving complex bugs in multi-layer API and database architectures
Troubleshooting performance regressions and unexpected production behavior

소개

주요 기능

Mandatory root cause investigation phase before code changes
Evidence-based pattern analysis and reference comparison
1 GitHub stars
Diagnostic instrumentation for multi-component system boundaries
Scientific hypothesis testing with minimal variable changes
Architectural re-evaluation triggers after repeated fix failures

사용 사례

Debugging intermittent CI/CD pipeline or build failures
Resolving complex bugs in multi-layer API and database architectures
Troubleshooting performance regressions and unexpected production behavior