diagnose

Diagnose hard bugs and performance regressions through a structured reproduce-hypothesise-fix loop.

2|Updated Jan 26, 2026
One-click install
npx skills add https://github.com/Nzettodess/Awesome-Agent-Skills --skill diagnose-nzettodess
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: diagnose
Source: https://github.com/Nzettodess/Awesome-Agent-Skills/tree/main/Skills/Engineering%20Skills/skills/engineering/diagnose
Command: npx skills add https://github.com/Nzettodess/Awesome-Agent-Skills --skill diagnose-nzettodess

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? Debugging stubborn bugs and performance regressions often devolves into random log-grepping and guesswork. This Skill enforces a disciplined six-phase loop — build a feedback loop, reproduce, hypothesise, instrument, fix with regression test, and clean up — so bugs get root-caused instead of patched over. ## Core Features & Use Cases - Feedback Loop Construction: Guides you through ten concrete strategies for building a fast, deterministic pass/fail signal, from failing tests and curl scripts to headless browser replays and bisection harnesses. - Ranked Hypothesis Testing: Forces generation of 3-5 falsifiable hypotheses with explicit predictions before any probing, preventing anchoring on the first plausible idea. - Regression Test Discipline: Requires writing the regression test before the fix at a correct seam, and flags architectural problems when no valid seam exists. - Use Case: A user reports that an export endpoint intermittently returns corrupted data. The Skill walks you through building a replay harness from a captured request, ranking hypotheses about concurrency vs serialization, instrumenting with tagged debug logs, and landing a fix with a regression test. ## Quick Start Ask the agent to diagnose the bug where the export endpoint intermittently returns corrupted data and follow the structured diagnosis loop.

Frequently Asked Questions about diagnose

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

FAQPage Schema
How do I debug a bug that only happens intermittently?▼

For non-deterministic bugs, raise the reproduction rate instead of chasing a clean repro: loop the trigger 100 times, parallelise, add stress, or inject sleeps. A 50%-flake bug is debuggable; a 1% flake is not, so keep increasing the rate until hypotheses can be tested against it.

How to reproduce a bug that needs manual UI interaction?▼

Use a headless browser script with Playwright or Puppeteer to drive the UI and assert on DOM, console, or network output. If a human must click, use the included hitl-loop.template.sh script to structure the human-in-the-loop steps and capture results for the agent.

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

Stop and say so explicitly rather than guessing. List what you tried, then ask the user for environment access, a captured artifact like a HAR file or log dump, or permission to add temporary production instrumentation before proceeding to hypotheses.

Why write the regression test before the fix?▼

Writing the test first proves it actually captures the bug by watching it fail, then confirms the fix by watching it pass. If no correct test seam exists, that absence is itself a finding about the codebase architecture and should be flagged.

How do I debug a performance regression differently from a functional bug?▼

For performance regressions, logs are usually the wrong tool. Establish a baseline measurement with a timing harness, profiler, or query plan first, then bisect between measurements — measure first, fix second.