What problem does it solve? LLM-generated code often suffers from overcomplication, silent assumptions, and sprawling edits that touch unrelated code. This Skill provides behavioral guidelines, derived from Andrej Karpathy's observations on LLM coding pitfalls, that keep AI-assisted coding focused, simple, and verifiable. ## Core Features & Use Cases - Think Before Coding: Surfaces assumptions, ambiguities, and tradeoffs explicitly instead of picking interpretations silently. - Simplicity and Surgical Changes: Enforces minimal code for the task and restricts edits to lines that trace directly to the user's request. - Goal-Driven Execution: Transforms vague tasks into verifiable success criteria, such as writing a failing test before fixing a bug. - Use Case: When asking an AI to refactor a function or fix a bug, activate these guidelines so the response states assumptions, avoids unrelated refactors, and defines how success will be verified. ## Quick Start Ask the AI to apply the karpathy-guidelines skill while writing or reviewing your code change.