diagnosing-bugs

Diagnose hard bugs and performance regressions through a structured feedback-loop workflow.

2|Updated Jun 21, 2026
One-click install
npx skills add https://github.com/IsKenKenYa/skills --skill diagnosing-bugs-iskenkenya
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: diagnosing-bugs
Source: https://github.com/IsKenKenYa/skills/tree/main/skills/engineering/diagnosing-bugs
Command: npx skills add https://github.com/IsKenKenYa/skills --skill diagnosing-bugs-iskenkenya

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? Hard bugs and performance regressions resist casual debugging: staring at code rarely finds the cause. This Skill enforces a disciplined six-phase diagnostic loop that builds a tight, deterministic pass/fail signal first, then reproduces, minimizes, hypothesizes, instruments, fixes, and cleans up. ## Core Features & Use Cases - Feedback Loop Construction: Builds a red-capable, deterministic, fast reproduction command using failing tests, curl scripts, CLI fixtures, headless browsers, trace replay, fuzz loops, or bisection harnesses. - Structured Hypothesis Testing: Generates 3-5 ranked, falsifiable hypotheses and instruments one variable at a time with tagged debug logs for easy cleanup. - Regression Lockdown: Writes a regression test at a correct seam before the fix, verifies the original scenario, and removes all debug instrumentation. - Use Case: A user reports that an export endpoint intermittently returns corrupted data. The Skill guides building a replay harness from a captured request, minimizing the failing input, testing ranked hypotheses, and landing a fix with a regression test. ## Quick Start Use the diagnosing-bugs skill to diagnose why the export endpoint intermittently returns corrupted data and build a reproduction loop for it.

Frequently Asked Questions about diagnosing-bugs

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

FAQPage Schema
How do I debug an intermittent or flaky bug?

Raise the reproduction rate instead of chasing a clean repro: loop the trigger 100 times, parallelize, add stress, and narrow timing windows. A bug that fails 50% of the time is debuggable; one at 1% is not, so keep increasing the rate until a feedback loop can catch it.

How to build a reproduction loop for a hard bug?

Start with a failing test at whatever seam reaches the bug, then try curl scripts, CLI invocations with fixtures, headless browser scripts, or replaying captured traces. The loop must assert the user's exact symptom, run deterministically in seconds, and be executable unattended.

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

Stop and say so explicitly rather than guessing. Ask the user for access to the reproducing environment, a redacted captured artifact such as a HAR file or log dump, or permission to add temporary production instrumentation before forming hypotheses.

Why write a regression test before fixing a bug?

Writing the test first proves it actually catches the bug by watching it fail, then confirms the fix by watching it pass. If no correct seam exists for the test, that absence itself is a finding about the codebase architecture worth flagging.

How do I diagnose a performance regression?

Establish a baseline measurement first using a timing harness, profiler, or query plan, then bisect to find the cause. Logging is usually the wrong tool for performance work; measure first and fix second.