systematic-debugging
Systematic Debugging enforces a disciplined four-phase approach to troubleshooting: start with root cause investigation, then research external context, analyze patterns, and test hypotheses before implementing any fix. The skill prevents the common trap of patching symptoms, ensuring you understand what actually broke and why.
Systematic Debugging guides you through structured root cause investigation before attempting any bug fix.
AI-generated summary based on this skill's SKILL.md
Decision gist · record as of 2026-07-25
Systematic Debugging guides you through structured root cause investigation before attempting any bug fix. Systematic Debugging enforces a disciplined four-phase approach to troubleshooting: start with root cause investigation, then research external context, analyze patterns, and test hypotheses before implementing any fix. The skill prevents the common trap of patching symptoms, ensuring you understand what actually broke and why.
Use it when
- Systematic Debugging applies the same disciplined methodology to production troubleshooting: begin by gathering diagnostic evidence.
- Systematic Debugging enforces questioning your architecture early and systematically tracing unexpected behavior.
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Read SKILL.md below before installing (11 files). Open directory: indexed for reading, not audited.
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jamditis/claude-skills-journalism/systematic-debugging · repository language: Python
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Frequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How do I debug a failing test systematically?
Systematic Debugging guides you through a four-phase approach: first investigate the root cause by isolating what actually broke, then research external context to understand dependencies and recent changes, analyze patterns to spot recurring issues, and finally test hypotheses with minimal changes before implementing a full fix. This prevents the trap of patching symptoms without understanding the real problem.
What's the Systematic Debugging process for production issues?
Systematic Debugging applies the same disciplined methodology to production troubleshooting: begin by gathering diagnostic evidence to pinpoint which system layer is failing, research the surrounding context and recent deployments, look for patterns in error logs and timing, then verify your hypothesis with a small test change before rolling out a full fix. This approach avoids repeated failed attempts.
How does Systematic Debugging help me avoid guessing at fixes?
Systematic Debugging enforces questioning your architecture early and systematically tracing unexpected behavior through multiple components before attempting any repair. By investigating root cause first, researching context, analyzing patterns, and testing hypotheses with minimal changes, you gather the evidence needed to understand what broke and why—eliminating guesswork and preventing the cycle of failed fix attempts.
Why do my fixes keep failing and how does Systematic Debugging help?
Systematic Debugging breaks the cycle by forcing you to investigate root cause before implementing fixes. Many failed attempts stem from patching symptoms rather than understanding the real problem. The skill's four-phase approach—root cause investigation, context research, pattern analysis, and hypothesis testing—ensures you've identified the actual failure point across your system layers before committing to a solution.
How does Systematic Debugging help debug flaky tests?
Systematic Debugging applies its disciplined methodology to flaky test failures by first investigating what conditions trigger the failure, researching external factors like timing or resource contention, analyzing patterns across test runs to spot intermittent behavior, and testing hypotheses with minimal test changes. This systematic tracing through multiple components reveals whether the issue lies in test setup, application code, or environmental factors.
What makes Systematic Debugging different from random troubleshooting?
Systematic Debugging enforces a structured four-phase framework rather than ad-hoc patching: root cause investigation, external context research, pattern analysis, and hypothesis verification. This prevents wasted effort on symptoms, ensures you understand architecture before fixing, and gathers diagnostic evidence to pinpoint the actual failing layer. The MIT-licensed skill transforms debugging from guessing into disciplined problem-solving.
SKILL.md
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<!-- Adapted from obra/superpowers systematic-debugging skill (v5.0.7), MIT-licensed, copyright 2025 Jesse Vincent. Modifications copyright 2026 Joe Amditis. v0.3.0 adds a research phase between Phase 1 (Root Cause Investigation) and Phase 2 (Pattern Analysis) per the v0.2.0 architecture's research-at-entry-point rule (debugging is an entry-point stage — the work begins from a bug report, not an upstream artifact). See CREDITS.md. -->
Systematic Debugging
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File tree — 11 files
superjawn/skills/systematic-debugging/CREATION-LOG.md
superjawn/skills/systematic-debugging/SKILL.md
superjawn/skills/systematic-debugging/condition-based-waiting-example.ts
superjawn/skills/systematic-debugging/condition-based-waiting.md
superjawn/skills/systematic-debugging/defense-in-depth.md
superjawn/skills/systematic-debugging/find-polluter.sh
superjawn/skills/systematic-debugging/root-cause-tracing.md
superjawn/skills/systematic-debugging/test-academic.md
superjawn/skills/systematic-debugging/test-pressure-1.md
superjawn/skills/systematic-debugging/test-pressure-2.md
superjawn/skills/systematic-debugging/test-pressure-3.md
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Related skills
Systematic Debugging teaches a disciplined 4-phase approach: root cause investigation, pattern analysis, hypothesis testing, and implementation. Rather than attempting quick fixes, this skill enforces tracing issues back to their source through careful error analysis, data flow tracking, and minimal testing before any code change.
Systematic Debugging enforces a disciplined four-phase approach to troubleshooting: investigate the root cause through error analysis and evidence gathering, analyze patterns by comparing working and broken code, form and test hypotheses scientifically, then implement fixes. The skill emphasizes that symptom-level repairs fail—you must trace data flow, instrument multi-component systems, and stop after three failed attempts to question architectural soundness.
Systematic Debugging teaches a disciplined four-phase process for tackling any technical issue—from test failures to production bugs. By enforcing root cause investigation before attempting fixes, it eliminates guesswork and the cycle of symptom-patching that creates new problems. The framework emphasizes evidence gathering, pattern analysis, hypothesis testing, and architectural questioning when multiple fixes fail.
This skill enforces a disciplined debugging process: establish a tight feedback loop that reproduces the exact symptom, gather evidence across system boundaries, trace data flow to its source, and form testable hypotheses before proposing any fix. By completing each phase sequentially—root cause investigation, pattern analysis, hypothesis testing, and verification—you eliminate guesswork and prevent quick patches from masking deeper issues.
This skill guides you through a disciplined five-phase debugging workflow designed to eliminate guesswork and prevent band-aid fixes. Start by reliably reproducing the issue, then systematically narrow down the failing component, trace the chain of causation, apply a minimal fix at the root cause, and finally verify the solution works without introducing new problems. The methodology emphasizes understanding *why* a bug occurs before attempting repairs.
Systematic Debugging guides you through a proven 4-phase process: reproduce the issue reliably, isolate its source, analyze root causes using techniques like the 5 Whys, and verify your fix works without introducing new problems. This skill prevents random troubleshooting and ensures you understand what's broken before attempting repairs.