systematic-debugging

Reproduce software failures, isolate root causes, and verify minimal repairs with regression checks.

Updated Aug 1, 2026
One-click install
npx skills add https://github.com/QuyDu/Skills-Orchestrator --skill systematic-debugging-quydu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/QuyDu/Skills-Orchestrator/tree/main/.github/skills/systematic-debugging
Command: npx skills add https://github.com/QuyDu/Skills-Orchestrator --skill systematic-debugging-quydu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Debugging often devolves into guesswork, unrelated refactoring, and unverified fixes. This Skill enforces a disciplined workflow that turns an observed failure into a reproducible case, an evidence-backed root cause, and the smallest verified repair. ## Core Features & Use Cases - Structured Root-Cause Isolation: Records expected versus actual behavior, forms falsifiable hypotheses, and runs the cheapest discriminating check one variable at a time. - Regression-First Repair: Requires a failing regression check before applying the production fix, then reruns focused and neighboring validation. - Governed Reporting: Produces reports/debugging-result.json and reports/debugging-result.md distinguishing observations, hypotheses, and confirmed conclusions, with redacted sensitive data. - Use Case: A failing API test points to stale data. Use this Skill to reproduce the failure, isolate an incorrect cache key as the root cause, add a regression test, and verify the focused repair. ## Quick Start Use the systematic-debugging skill to reproduce this failing test, find the root cause, and verify the smallest 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 failing test systematically?▼

Reproduce the failure with a focused command, state one falsifiable root-cause hypothesis, and run the cheapest discriminating check while changing one variable at a time. Add a regression test that fails for the confirmed cause before applying the smallest repair.

How to find the root cause of a flaky test?▼

Record the environment, revision, and narrowest reproduction, then trace the code path that directly controls the failure. If reproduction is unavailable, mark conclusions as hypotheses and return a blocked report rather than guessing.

What should I do when a bug cannot be reproduced locally?▼

Return a blocked status report preserving the original failure evidence instead of claiming a cause from correlation. Document the missing diagnostics or telemetry required, and test the next local hypothesis when new evidence arrives.

When should I not use a systematic debugging workflow?▼

Do not use it for broad repository audits or general code quality reviews; it targets specific observed failures. It also requires an observed failure with expected behavior and environment details as inputs.

Does this debugging approach handle sensitive log data?▼

Yes, credentials, tokens, personal data, and unrelated sensitive log content must be redacted from reports. Approval is required before sending sensitive evidence to remote services or performing destructive diagnostics.