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diagnosing-bugs

Diagnose hard bugs by building a red-capable reproduction loop.

Updated May 28, 2026
Search Tags:#performance#debugging#regression#bisection#instrumentation#reproduction#tests
One-click install
npx skills add https://github.com/haryelramalho/skills --skill diagnosing-bugs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: diagnosing-bugs
Source: https://github.com/haryelramalho/skills/tree/main/skills/community/diagnosing-bugs
Command: npx skills add https://github.com/haryelramalho/skills --skill diagnosing-bugs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps you diagnose hard bugs and performance regressions by forcing a tight, red-capable feedback loop before you guess at causes.

Core Features & Use Cases

  • Feedback-loop first debugging: Build a failing test, curl check, CLI repro, browser script, trace replay, harness, fuzz loop, or bisect workflow that catches the exact symptom.
  • Reproduction and minimization: Confirm the issue reliably, then shrink it to the smallest scenario that still fails so the true cause becomes easier to isolate.
  • Hypothesis-driven investigation: Rank falsifiable explanations, instrument one variable at a time, and use targeted logs or debugging tools to separate competing causes.
  • Regression protection: Turn the minimized repro into a regression test when the seam is correct, then verify the fix against the original scenario and clean up debug artifacts.
  • Use Case: A flaky export failure, a slow API endpoint, or a branch-specific regression can be reduced to a deterministic command that proves the bug before any fix is attempted.

Quick Start

Use the diagnosing-bugs skill to build a tight reproduction loop for the failing behavior, confirm it goes red, and minimize it to the smallest reliable case.

Frequently Asked Questions about diagnosing-bugs

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

FAQPage Schema
How do I debug a flaky test or intermittent failure that is hard to reproduce?▼

To debug an intermittent failure, you build a tight reproduction loop using CLI commands, curl checks, or trace replays to generate deterministic signals. This reliably confirms the exact symptom before you attempt any fix.

What is the best way to isolate a performance regression in a slow API endpoint?▼

The best way to isolate a performance regression is hypothesis-driven investigation. You rank falsifiable explanations, instrument one variable at a time, and minimize the failing scenario to expose the true cause.

How do I minimize a failing test case to find the root cause?▼

You minimize a failing test case by shrinking the reproduction scenario to the smallest input that still triggers the bug. This process isolates the true cause by systematically removing irrelevant variables.

Does this debugging approach work with browser automation and fuzzing loops?▼

Yes, this debugging approach works with browser automation and fuzzing loops by applying bisection and targeted instrumentation. It supports diverse reproduction methods to catch exact symptoms across various testing workflows.

What should I do after isolating a bug to prevent future regressions?▼

After isolating a bug, you turn the minimized reproduction case into a regression test. You verify the fix against the original scenario and clean up debug artifacts to ensure continuous regression protection.

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