diagnosing-bugs

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

2|Updated Jul 11, 2026
One-click install
npx skills add https://github.com/MoofonLi/dev-ready --skill diagnosing-bugs-moofonli
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: diagnosing-bugs
Source: https://github.com/MoofonLi/dev-ready/tree/main/.agents/skills/diagnosing-bugs
Command: npx skills add https://github.com/MoofonLi/dev-ready --skill diagnosing-bugs-moofonli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? Hard bugs and flaky performance regressions resist casual code reading; without a reproducible failing signal, debugging devolves into guessing. This Skill enforces a disciplined diagnosis loop that builds a tight, deterministic reproduction before any hypothesis is tested. ## Core Features & Use Cases - Feedback Loop Construction: Builds a red-capable, deterministic, fast reproduction command using failing tests, curl scripts, headless browsers, replayed traces, fuzz loops, or bisection harnesses. - Structured Six-Phase Process: Guides reproduction and minimization, ranked falsifiable hypothesis generation, single-variable instrumentation with tagged debug logs, regression-test-first fixing, and cleanup with post-mortem. - Non-Deterministic Bug Handling: Raises reproduction rates for flaky bugs via looped triggers, parallelism, stress, and timing injection until the bug is debuggable. - Use Case: A user reports an intermittent 500 error on the export endpoint. The Skill drives creation of a curl-based loop that reproduces the failure, minimizes the scenario, tests ranked hypotheses one variable at a time, and lands a regression test with the fix. ## Quick Start Ask the agent to diagnose the bug where the export button throws an error, and have it build a failing reproduction loop before proposing any fix.

Frequently Asked Questions about diagnosing-bugs

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

FAQPage Schema
How to reproduce a bug before fixing it?▼

Build a tight feedback loop first: a failing test, curl script, CLI invocation, headless browser script, or replayed trace that goes red on the exact symptom. Then minimize the scenario by removing elements one at a time until every remaining piece is load-bearing.

What should I do when I cannot reproduce a bug at all?▼

Stop and say so explicitly rather than hypothesizing without a loop. Ask the user for environment access, a captured artifact like a HAR file or log dump, or permission to add temporary production instrumentation.

Why write the regression test before the fix?▼

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

How do I debug a performance regression?▼

For performance regressions, skip log-based probing: establish a baseline measurement with a timing harness, profiler, or query plan, then bisect against that baseline. Measure first, fix second.