debugging

Diagnose bugs in Python or React applications using a structured debugging methodology.

13|Updated Mar 15, 2019

Search Tags:#debugging #troubleshooting #react #fastapi #logging #python #sqlalchemy

Ready to run

npx skills add https://github.com/WTFox/dotfiles --skill debugging-wtfox

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: debugging
Source: https://github.com/WTFox/dotfiles/tree/main/claude/.claude/skills/debugging
Command: npx skills add https://github.com/WTFox/dotfiles --skill debugging-wtfox

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Diagnose bugs in Python or React applications using a structured debugging methodology.

Core Features & Use Cases

Stepwise traceback reading and frame prioritization to identify the genuine cause.
Local reproduction, targeted logging, and systematic assumption checking to isolate failures.
Frontend and backend diagnostic guidance spanning Python (FastAPI, Django) and React codebases.

Quick Start

Apply the debugging methodology to your current traceback to identify the root cause and propose a fix.

Frequently Asked Questions about debugging

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

FAQPage Schema

How do I debug a Python traceback to find the root cause?▼

To debug a Python traceback, read the stack frames stepwise to prioritize the genuine cause, then check local reproduction and assumptions systematically. This structured approach isolates the true failure point rather than treating symptoms.

What is the best way to troubleshoot unexpected behavior in a React application?▼

Troubleshooting React application behavior involves applying a structured methodology with reproducibility checks and targeted logging to isolate failures. This diagnostic process spans frontend codebases to identify the genuine cause of unexpected UI issues.

Can I use this debugging methodology for FastAPI and SQLAlchemy errors?▼

Yes, this debugging methodology supports diagnosing FastAPI and SQLAlchemy errors by applying stepwise traceback reading and systematic assumption checking. It provides backend diagnostic guidance specifically tailored to Python frameworks.

How do I systematically isolate test failures in a Python codebase?▼

Systematically isolating test failures in a Python codebase requires local reproduction, targeted logging, and stepwise assumption checking. This structured debugging methodology verifies reproducibility to pinpoint the genuine cause of the failure.

Does this debugging approach work for both frontend and backend performance anomalies?▼

Yes, this debugging approach works for frontend and backend performance anomalies by providing diagnostic guidance spanning Python and React codebases. It uses reproducibility checks and targeted logging to investigate performance issues systematically.