problem-solver-debugger

Enumerate hypotheses and identify evidence for systematic debugging.

Updated Feb 3, 2026

Search Tags:#debugging #problem solving #root cause analysis #hypothesis testing #incident analysis #bias awareness

Ready to run

npx skills add https://github.com/brennancheung/CourseAI --skill problem-solver-debugger

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: problem-solver-debugger
Source: https://github.com/brennancheung/CourseAI/tree/main/codex/skills/problem-solver-debugger
Command: npx skills add https://github.com/brennancheung/CourseAI --skill problem-solver-debugger

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps when you're stuck on a persistent bug, the obvious solutions haven't worked, the root cause is elusive, or you're repeatedly debugging the same issue. It's also valuable for post-mortems and incident analysis where jumping to conclusions is risky.

Core Features & Use Cases

Systematic Hypothesis Enumeration: Forces a structured approach to identifying potential causes before diving into solutions.
Bias Awareness: Explicitly considers common cognitive biases like survivorship, selection, and hindsight bias.
Conditional Reasoning: Frames guidance based on specific conditions rather than offering single "best" answers.
Use Case: Debugging a complex intermittent API failure where multiple factors could be at play, ensuring all plausible causes are considered before implementing a fix.

Quick Start

Use the problem-solver-debugger skill to help diagnose a recurring intermittent bug in the user authentication service.

Frequently Asked Questions about problem-solver-debugger

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

FAQPage Schema

How do I perform root cause analysis for a persistent software bug?▼

Root cause analysis for a persistent software bug requires systematically enumerating potential hypotheses and identifying necessary evidence to validate them, preventing premature conclusions. This structured approach ensures complex or intermittent issues are fully diagnosed before attempting fixes.

What is the best way to debug a complex intermittent API failure?▼

The best way to debug a complex intermittent API failure is to apply conditional reasoning and explicit bias awareness, evaluating all plausible causes rather than jumping to obvious solutions. This method forces comprehensive hypothesis enumeration before implementing changes.

How do I avoid cognitive bias during incident analysis and post-mortems?▼

To avoid cognitive bias during incident analysis, explicitly account for common biases like survivorship, selection, and hindsight bias throughout your investigation. Structured hypothesis testing with uncertainty assessment prevents skewed conclusions in post-mortems.

Can I use hypothesis testing for recurring issues in software development?▼

Yes, you can use hypothesis testing for recurring issues in software development by framing guidance based on specific conditions and assessing explicit uncertainty. This prevents repeatedly debugging the same issue by ensuring all potential causes are systematically evaluated.

When should I not use systematic debugging for problem solving?▼

You should avoid systematic debugging when the root cause is immediately obvious and jumping to a quick solution poses minimal risk, because the strict output structure and conditional reasoning add overhead best reserved for complex or elusive problems.