Claude Code Wsl2 Setup

Tutor the user toward deep understanding of a topic, codebase, paper, artifact, or concept through incremental explanation, active recall, and verification. Use when the user asks to be taught, wants to understand something deeply, says "teach me", "walk me through", "explain until I get it", "quiz me", asks for ELI5/ELI14/intern-level teaching, or needs a learning session instead of a one-off answer. Skip for simple factual answers or implementation tasks where teaching is not requested.

PyTorch model-building conventions and a neural-net training debug checklist. Use this skill whenever writing or reviewing PyTorch code that defines a model (nn.Linear, nn.Conv2d, BatchNorm) or trains one (training loop, optimizer, LR schedule), and ESPECIALLY when debugging training problems — loss not converging, loss stuck or flat, suspiciously slow learning, "hockey stick" loss curves, or a model that seems to ignore its inputs. Also consult it before starting any from-scratch training run, even if the user doesn't mention debugging.