claude-code-wsl2-setup

Delegate a heavy or mechanical coding task to the configured Codex CLI model via a low-effort Sonnet wrapper, so Codex's large transcript stays OUT of the main orchestrator context. Trigger when the user says "delegate to codex", "hand this to codex", "let codex do X", or when a well-specified implementation/refactor/migration/bulk task is large enough that doing it inline would flood context with tool round-trips. Do NOT use for small tasks you can one-shot.

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.

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.

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