What happens if the proposed fixes don't work?

If three or more fix attempts fail, the skill stops the debugging process to question the underlying architecture, preventing 'thrashing' and identifying fundamental design flaws.

When should I use this skill instead of standard debugging?

Use this skill for any technical issue where the cause isn't immediately obvious, especially under time pressure, when previous fixes have failed, or when dealing with multi-component systems.

How does the skill handle complex, multi-layer systems?

It implements diagnostic instrumentation at component boundaries to log data entry/exit and verify environment propagation, revealing exactly which layer the failure originates in.

What is the 'Iron Law' of systematic debugging?

The Iron Law dictates that no fixes should be proposed or implemented until the root cause of the issue has been thoroughly investigated and confirmed through evidence.

Systematic Debugging

Name: Systematic Debugging
Author: Kingly-Agency

byKingly-Agency

Security & Testing

Applies a rigorous four-phase framework to diagnose root causes and implement verified fixes for complex software bugs.

About

Systematic Debugging provides a structured methodology for Claude to handle bugs, test failures, and unexpected behaviors by enforcing an investigation-first policy. It guides the AI through four distinct phases—root cause investigation, pattern analysis, hypothesis testing, and implementation—ensuring that every fix is evidence-based and verified through failing test cases. This skill is specifically designed to prevent 'guess-and-check' workflows, making it indispensable for troubleshooting multi-layered systems, production emergencies, and persistent technical issues that resist simple patches.

Key Features

Seamless integration with Test-Driven Development (TDD) and data flow tracing
Multi-component diagnostic instrumentation for tracing errors across system boundaries
Evidence-based 'Iron Law' that prohibits fixes before root cause identification
Automated architectural health checks triggered after three failed fix attempts
0 GitHub stars
Mandatory four-phase debugging framework (Investigation, Analysis, Hypothesis, Implementation)

Use Cases

Identifying the source of intermittent production bugs in complex, multi-service architectures
Troubleshooting environment-specific build and deployment failures in CI/CD pipelines
Resolving deep-seated test failures that have persisted through multiple previous fix attempts

About

Key Features

Seamless integration with Test-Driven Development (TDD) and data flow tracing
Multi-component diagnostic instrumentation for tracing errors across system boundaries
Evidence-based 'Iron Law' that prohibits fixes before root cause identification
Automated architectural health checks triggered after three failed fix attempts
0 GitHub stars
Mandatory four-phase debugging framework (Investigation, Analysis, Hypothesis, Implementation)

Use Cases

Identifying the source of intermittent production bugs in complex, multi-service architectures
Troubleshooting environment-specific build and deployment failures in CI/CD pipelines
Resolving deep-seated test failures that have persisted through multiple previous fix attempts