systematic-debugging

Diagnose software bugs through root cause investigation before writing fixes.

33|1|Updated Mar 4, 2026
One-click install
npx skills add https://github.com/infinition/LaRuche --skill systematic-debugging-infinition
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/infinition/LaRuche/tree/main/laruche/skills/systematic-debugging
Command: npx skills add https://github.com/infinition/LaRuche --skill systematic-debugging-infinition

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Developers often jump straight to patching symptoms, which leads to recurring bugs, layered hacks, and wasted effort. This Skill enforces a disciplined four-phase debugging methodology that finds the actual root cause before any fix is written. ## Core Features & Use Cases - Root Cause Investigation: Read error messages fully, build a tight red/green feedback loop, check recent changes, and trace data flow to its origin. - Hypothesis-Driven Testing: Form 3-5 ranked falsifiable hypotheses, test one variable at a time, and verify with a minimal reproduction before implementing anything. - Regression-First Fixes: Write a failing regression test before the fix, apply a single root-cause change, and escalate to architectural review after three failed attempts. - Use Case: A flaky test fails intermittently in CI. Use this Skill to raise the reproduction rate, isolate the failing component boundary, form ranked hypotheses, and land a verified fix with a regression test. ## Quick Start Use the systematic-debugging skill to investigate why the login endpoint returns a 500 error 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 find the root cause of a bug before fixing it?▼

Start by reading error messages and stack traces completely, then build a tight feedback loop that goes red on the exact symptom. Check recent changes with git log, gather evidence at component boundaries, and trace bad values upstream to their origin before proposing any fix.

How to debug a flaky test that fails intermittently?▼

Raise the reproduction rate first by running the test 100 times, parallelizing, adding stress, or narrowing timing windows. A 50% flake is debuggable while a 1% flake usually is not, so invest in making the failure deterministic before analyzing it.

What is a tight feedback loop in debugging?▼

A tight feedback loop is a fast, deterministic, agent-runnable command that goes red on the exact symptom and green when fixed. Examples include a failing unit test, a curl request against a dev server, a CLI invocation with fixture input, or a git bisect run harness.

When should I stop trying fixes and question the architecture?▼

Stop after three failed fix attempts. If each fix reveals new shared state, requires massive refactoring, or creates symptoms elsewhere, the problem is architectural rather than a simple bug, and the pattern itself should be discussed before continuing.

Why should I write a regression test before fixing a bug?▼

A regression test proves you can reproduce the bug and confirms the fix actually resolves it. Writing the simplest red test first prevents symptom patching and gives you a permanent guard against the bug reappearing.