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debugger

Diagnose software bugs from symptom triage to root-cause verification.

Updated Mar 25, 2026
Search Tags:#debugging#investigation#root-cause-analysis#log-analysis#hypothesis-generation#regression-testing
One-click install
npx skills add https://github.com/ouakar/ubinarys-dental --skill debugger-ouakar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: debugger
Source: https://github.com/ouakar/ubinarys-dental/tree/main/skills/forgewright/skills/debugger
Command: npx skills add https://github.com/ouakar/ubinarys-dental --skill debugger-ouakar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Software debugging often stalls product delivery due to scattered evidence collection and ad-hoc fixes. This Skill provides a structured, end-to-end debugging workflow that guides teams from symptoms to verified root causes and regression tests.

Core Features & Use Cases

  • Systematic symptom triage and evidence gathering across frontend, API, and data layers.
  • Hypothesis generation and ranking using evidence, with parallel investigation where possible.
  • Stepwise root-cause verification, fix implementation, and regression validation.
  • Generates investigation reports and regression tests to prevent regressions in future releases.
  • Use Case: A flaky API endpoint that intermittently times out can be diagnosed with Phase 2 hypotheses and Phase 3 evidence gathering, followed by a documented fix and regression test.

Quick Start

Start a debugging session by outlining the observed symptom and initiating Phase 1: Triage to gather symptoms and context for hypothesis generation.

Frequently Asked Questions about debugger

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

FAQPage Schema
How do I find the root cause of an intermittent API timeout?▼

Structured root-cause analysis for intermittent API timeouts involves systematic symptom triage, parallel hypothesis generation, and stepwise evidence verification across frontend, API, and data layers.

What is the best way to structure a debugging workflow for complex software projects?▼

A structured debugging workflow progresses from symptom triage and parallel hypothesis generation to stepwise root-cause verification, fix implementation, and regression validation in complex software projects.

How do I generate and test debugging hypotheses using log analysis?▼

Hypothesis generation uses structured logs and clear symptom descriptions to drive deterministic investigation, ranking hypotheses by evidence to support parallel investigation across system layers.

Can I use this debugging workflow across frontend, API, and data layers?▼

Yes, the debugging workflow operates across frontend, API, and data layers, requiring structured logs, code repository access, and clear symptom descriptions to drive deterministic investigation and verification.

What do I need to start a structured debugging investigation?▼

Starting a debugging session requires outlining observed symptoms and initiating triage, which needs structured logs, code repository access, and clear symptom descriptions to gather context for hypothesis generation.

How do I prevent software regressions after implementing a bug fix?▼

Preventing software regressions involves stepwise root-cause verification, fix implementation, and regression validation, generating investigation reports and regression tests to secure future releases.

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