debug-like-expert

Diagnoses complex bugs using hypothesis-driven, evidence-based workflows.

12|1|Updated May 29, 2026
One-click install
npx skills add https://github.com/qdzsh/gsd-revamp --skill debug-like-expert-qdzsh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: debug-like-expert
Source: https://github.com/qdzsh/gsd-revamp/tree/main/src/resources/skills/debug-like-expert
Command: npx skills add https://github.com/qdzsh/gsd-revamp --skill debug-like-expert-qdzsh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a disciplined, evidence-driven framework for debugging complex software issues. It guides you to gather current-state evidence, formulate testable hypotheses, and verify fixes without premature code changes, improving confidence and reproducibility.

Core Features & Use Cases

  • Evidence-gathering workflow: document the exact reproduction steps, gather logs and traces, and map the system state before acting.
  • Hypothesis-driven reasoning: generate multiple testable explanations and design minimal experiments to prove or disprove them.
  • Verification-first mindset: ensure any fix is minimal, reproducible, and thoroughly validated across environments, with clear rollback criteria.
  • Read-only investigation discipline: avoid modifying code during debugging to preserve evidence and maintain traceability.
  • Suitable for senior debugging on notoriously hard bugs, cross-team incidents, and platform/environment differences.

Quick Start

Document the current state of the issue, gather evidence, and outline hypotheses before making any changes.

Frequently Asked Questions about debug-like-expert

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

FAQPage Schema
How do I debug complex software issues without making premature code changes?

Debug complex software issues by gathering current-state evidence, documenting reproduction steps, and formulating testable hypotheses before modifying code. This evidence-driven workflow preserves traceability and ensures verifiable, minimal fixes.

What is hypothesis-driven root cause analysis and when should I use it?

Hypothesis-driven root cause analysis is a debugging method that generates multiple testable explanations for a bug and designs minimal experiments to prove or disprove them. Use it for notoriously hard bugs and cross-team incidents.

How do I verify a bug fix across different environments?

Verify a bug fix across environments by applying a verification-first mindset. Ensure the fix is minimal, reproducible, thoroughly validated, and includes clear rollback criteria to maintain confidence in the corrected system state.

Does evidence-driven debugging work for cross-team incidents and platform differences?

Evidence-driven debugging works for cross-team incidents and platform differences by enforcing a read-only investigation discipline. It maps system state and gathers logs and traces before acting, ensuring structured verification across diverse codebases.

Why should I avoid modifying code during the investigation phase of debugging?

Avoid modifying code during the investigation phase to preserve evidence and maintain traceability. A read-only debugging discipline ensures you gather logs and traces accurately before applying verifiable, minimal changes.