When should I use this Claude Code skill?

Use it for any technical issue, especially complex test failures, production bugs, or when multiple previous fix attempts have failed to resolve an issue.

What happens if a fix doesn't work?

The skill includes a safety mechanism: if three fix attempts fail, it triggers an architectural review to determine if the underlying system pattern is fundamentally flawed.

Does it work with multi-component systems?

Yes, it includes specific protocols for adding diagnostic instrumentation across component boundaries like APIs, build scripts, and databases to find exactly where data flow breaks.

What makes this different from regular debugging?

It enforces a strict 'no-fix-without-root-cause' policy, preventing wasted time on symptom-masking patches and ensuring the AI fully understands the failure before touching the code.

Does this skill require other plugins?

For maximum effectiveness, it integrates with root-cause-tracing and test-driven-development skills to provide a complete end-to-end debugging ecosystem.

Systematic Debugging

Name: Systematic Debugging
Author: franroa

byfranroa

Security & Testing

Implements a rigorous four-phase framework to identify root causes and resolve complex bugs without guesswork.

About

This skill provides a disciplined engineering workflow for troubleshooting technical issues, moving away from 'guess-and-check' patches toward scientific root cause analysis. It guides the debugging process through four mandatory phases: evidence-based investigation, pattern analysis, hypothesis testing, and test-driven implementation. By enforcing the 'Iron Law' of understanding the root cause before proposing any code changes, this skill helps developers solve persistent test failures, production bugs, and architectural flaws more efficiently while preventing the introduction of secondary regressions.

Key Features

Evidence gathering protocols for multi-component systems (CI, Build, API, DB)
Integration with Test-Driven Development (TDD) for verified, permanent resolutions
Four-phase scientific debugging framework: Investigation, Analysis, Hypothesis, and Implementation
0 GitHub stars
Mandatory root cause tracing to prevent symptom-masking 'quick fixes'
Architectural review triggers that stop 'fix-thrashing' after three failed attempts

Use Cases

Debugging deep data flow issues across multi-layered architectures and service boundaries
Resolving recurring regression bugs where previous attempts failed to address the underlying problem
Identifying the source of non-deterministic or flaky test failures in complex CI/CD pipelines

About

Key Features

Evidence gathering protocols for multi-component systems (CI, Build, API, DB)
Integration with Test-Driven Development (TDD) for verified, permanent resolutions
Four-phase scientific debugging framework: Investigation, Analysis, Hypothesis, and Implementation
0 GitHub stars
Mandatory root cause tracing to prevent symptom-masking 'quick fixes'
Architectural review triggers that stop 'fix-thrashing' after three failed attempts

Use Cases

Debugging deep data flow issues across multi-layered architectures and service boundaries
Resolving recurring regression bugs where previous attempts failed to address the underlying problem
Identifying the source of non-deterministic or flaky test failures in complex CI/CD pipelines