karpathy-guideline

Provide behavioral coding guidelines for LLM-assisted development.

Updated Apr 1, 2026
One-click install
npx skills add https://github.com/moonshineTP/ATTT-20252 --skill karpathy-guideline
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: karpathy-guideline
Source: https://github.com/moonshineTP/ATTT-20252/tree/main/.gemini/skills/karpathy-guideline
Command: npx skills add https://github.com/moonshineTP/ATTT-20252 --skill karpathy-guideline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses common mistakes in coding with Large Language Models (LLMs), promoting cleaner, more efficient code.

Core Features & Use Cases

  • Code Best Practices: Offers guidelines for avoiding overcomplication, making surgical changes, and defining verifiable success criteria.
  • Surgical Changes: Emphasizes touching only necessary code and not improving adjacent code without cause.
  • Goal-Driven Execution: Encourages setting clear success criteria and verifying each step until the goal is achieved.
  • Use Case: Ideal for coders looking to review, refactor, or write code, aiming to maintain simplicity and avoid pitfalls common in LLM development.

Quick Start

Use the karpathy-guideline skill to follow Andrej Karpathy's guidelines when coding with LLMs to minimize mistakes.

Frequently Asked Questions about karpathy-guideline

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

FAQPage Schema
What are the best practices for coding with LLMs to avoid common mistakes?

Coding with LLMs requires behavioral guidelines to minimize errors, adopting a minimalist approach, making surgical changes, and defining verifiable success criteria to improve overall code quality.

How do I ensure LLM coding generates clean and efficient code?

To ensure clean and efficient LLM coding, apply goal-driven execution by setting clear success criteria and verifying each step until the goal is achieved, while actively avoiding overcomplication.

How do I perform surgical changes when refactoring code with an LLM?

Performing surgical changes when refactoring code with an LLM means touching only the necessary code without improving adjacent code without cause, maintaining simplicity and preventing overcomplication.

Does goal-driven execution improve LLM code review outcomes?

Goal-driven execution improves LLM code review outcomes by encouraging the definition of clear success criteria and verifying each development step until the specific goal is achieved.

When should I not use an LLM to improve adjacent code during refactoring?

You should not use an LLM to improve adjacent code during refactoring without a specific cause, as surgical changes emphasize touching only necessary code to prevent overcomplication and maintain simplicity.