What problem does it solve? Learners often paste errors into Copilot Chat and blindly accept the first fix, which frequently suppresses the symptom instead of resolving the root cause. This Skill trains a disciplined observe → hypothesize → test → fix → verify debugging loop using Copilot Chat on a deliberately buggy Python program. ## Core Features & Use Cases - Guided debugging loop: Walks the learner through four intentional bugs (silent wrong behavior, overdraft, non-atomic transfer, division by zero) in a bank.py program using /explain, /fix, and @workspace. - Symptom-vs-cause training: Demonstrates how Copilot's first fix often silently drops bad input, and teaches the learner to push back and steer toward a loud ValueError fix. - Multi-turn conversation practice: Shows how follow-up questions like "what if the rollback fails?" lead to cleaner atomic transfer implementations. - Use Case: An MSSA learner in the GitHub Copilot track runs the buggy bank simulator, sees Alice's balance go negative, and uses /explain then a steered /fix to raise proper errors instead of silently swallowing bad deposits. ## Quick Start Ask the Mentor to start the ghc-chat-driven-debugging project so you can debug the buggy bank.py program with Copilot Chat.