systematic-debugging

Diagnose software bugs through a four-phase root cause investigation workflow.

Updated Aug 21, 2026
One-click install
npx skills add https://github.com/TylerSimons1127/vibe --skill systematic-debugging-tylersimons1127
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/TylerSimons1127/vibe/tree/main/skills/software-development/systematic-debugging
Command: npx skills add https://github.com/TylerSimons1127/vibe --skill systematic-debugging-tylersimons1127

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Random fixes and guess-and-check patches waste hours and introduce new bugs. This Skill enforces a disciplined four-phase debugging process that finds the root cause before any fix is attempted, preventing symptom-masking patches and repeated failed fix attempts. ## Core Features & Use Cases - Four-Phase Process: Root cause investigation, pattern analysis, hypothesis testing, and implementation, each with explicit completion criteria. - Tight Feedback Loops: Builds fast, deterministic, red-capable reproduction commands (failing tests, curl scripts, Playwright checks, bisection harnesses) before forming theories. - Rule of Three: After three failed fixes, stops and questions the underlying architecture instead of attempting a fourth patch. - Use Case: A production API returns intermittent 500 errors. Instead of guessing, you build a high-repetition repro loop, trace data flow across the service boundary, form ranked hypotheses, and land a single verified fix with a regression test. ## Quick Start Use the systematic-debugging skill to investigate why the checkout test fails before proposing any fix.

Frequently Asked Questions about systematic-debugging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug a bug systematically instead of guessing?▼

Follow four phases: investigate the root cause by reading errors and reproducing the issue, analyze patterns against working code, form and test ranked hypotheses one variable at a time, then implement a single fix with a regression test. Never propose fixes before completing the investigation phase.

How to reproduce a flaky test for debugging?▼

Raise the reproduction rate by running the trigger 100 times, parallelizing, adding stress, or narrowing timing windows. A 50% flake is debuggable while a 1% flake usually is not. Pin time, seed randomness, and isolate filesystem and network to make the loop more deterministic.

What should I do after multiple fix attempts fail?▼

Stop after three failed fixes and question the architecture rather than attempting a fourth. Repeated failures where each fix reveals new coupling or creates new symptoms elsewhere indicate an architectural problem that needs refactoring discussion, not another patch.

Does systematic debugging work for production incidents under time pressure?▼

Yes, the process is designed especially for emergencies because systematic investigation is faster than guess-and-check thrashing. Reported sessions show 15-30 minute fixes with a 95% first-time fix rate versus hours of random attempts.

When should I not use a full debugging process?▼

The process applies to any technical issue, including seemingly simple bugs, since simple issues have root causes too. Skipping investigation for quick fixes sets a bad pattern and typically causes rework and new bugs.