debug-like-expert

Diagnose complex software bugs by testing hypotheses and tracing execution paths.

1|Updated Jul 13, 2026
One-click install
npx skills add https://github.com/vh2224/forge-executor --skill debug-like-expert-vh2224
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: debug-like-expert
Source: https://github.com/vh2224/forge-executor/tree/main/src/resources/skills/debug-like-expert
Command: npx skills add https://github.com/vh2224/forge-executor --skill debug-like-expert-vh2224

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you diagnose complex bugs and unexpected behavior when quick troubleshooting has failed. It replaces guesswork with disciplined investigation, so you can identify the real root cause instead of applying speculative fixes.

Core Features & Use Cases

  • Systematic Evidence Gathering: Collect exact errors, reproduction steps, and observed behavior before proposing any solution.
  • Hypothesis Testing: Form multiple falsifiable explanations, then test each one against the code and runtime behavior.
  • Root Cause Analysis: Trace execution paths, compare competing explanations, and isolate the failure mechanism with confidence.
  • Verification Planning: Define how to confirm a fix, check adjacent functionality, and avoid regressions after implementation.
  • Use Case: A production bug only appears after a restart and standard debugging has failed; this Skill guides a methodical, evidence-based investigation from observation to verified recommendation.

Quick Start

Use the debug-like-expert skill to investigate the failure, gather evidence, test competing hypotheses, and report the root cause without changing any code.

Frequently Asked Questions about debug-like-expert

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

FAQPage Schema
How do I find the root cause of a complex software bug when standard troubleshooting fails?

To find the root cause of a complex software bug, you must gather exact reproduction steps and observed errors, form falsifiable hypotheses, and trace execution paths to isolate the failure mechanism. This disciplined investigation replaces guesswork with evidence.

What is the best way to debug a production failure that only appears after a restart?

Debugging an intermittent production failure requires systematic evidence gathering and hypothesis testing against runtime behavior. By comparing competing explanations and tracing the execution path, you can isolate the failure mechanism without modifying code.

How do I verify a software fix without causing regressions in adjacent functionality?

Verifying a software fix without regressions requires defining a verification plan that confirms the resolution and checks adjacent functionality. This ensures reliable recommendations and prevents new issues after implementation by validating execution paths.

Can I diagnose an unclear software failure mechanism without modifying the risky code?

Yes, you can diagnose unclear software failure mechanisms without modifying risky code by gathering reproducible observations and testing hypotheses. This evidence-based approach identifies the root cause through execution-path tracing rather than speculative fixes.

When should I use hypothesis testing for software debugging instead of applying quick fixes?

You should use hypothesis testing for software debugging when failures resist standard troubleshooting and code changes are risky. It allows you to form multiple falsifiable explanations, test them against runtime behavior, and isolate the true failure mechanism.