karpathy-guidelines

Guide LLM coding with minimal changes and explicit success criteria.

3|1|Updated Jan 14, 2026
One-click install
npx skills add https://github.com/heyAyushh/stacc --skill karpathy-guidelines
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: karpathy-guidelines
Source: https://github.com/heyAyushh/stacc/tree/main/configs/skills/karpathy-guidelines
Command: npx skills add https://github.com/heyAyushh/stacc --skill karpathy-guidelines

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Karpathy-inspired behavioral guidelines help developers reduce common LLM coding mistakes by encouraging explicit thinking, surfacing tradeoffs, and avoiding overcomplicated or speculative changes.

Core Features & Use Cases

  • Think before coding: surface confusion, surface assumptions, and present multiple interpretations when uncertain.
  • Surgical changes: limit edits to what's necessary, avoid unnecessary refactors, and maintain existing style.
  • Verifiable outcomes: define clear success criteria and create testable steps for multi-phase tasks.

Quick Start

Instruct the AI to apply Karpathy-style guidelines to a coding task, e.g., "Refactor function foo to be simpler and safer following Karpathy guidelines."

Frequently Asked Questions about karpathy-guidelines

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

FAQPage Schema
How do I stop LLM coding assistants from making unnecessary refactors?

To stop LLM coding assistants from making unnecessary refactors, apply surgical change guidelines that limit edits to what is strictly necessary and maintain existing code style. This prevents overcomplication during AI-assisted coding.

What are verifiable goals in LLM code generation?

Verifiable goals in LLM code generation are clearly defined success criteria that create testable steps for multi-phase tasks. They ensure AI-generated code produces explicit, measurable outcomes rather than speculative changes.

How do I prompt an LLM to surface tradeoffs before writing code?

To prompt an LLM to surface tradeoffs before writing code, instruct it to apply guidelines that enforce thinking before coding, surfacing assumptions, and presenting multiple interpretations when uncertain. This reduces risky code generation.

Can I use refactoring guidelines for reviewing existing LLM-generated code?

Yes, you can use refactoring guidelines for reviewing existing LLM-generated code. The guidelines are explicitly applicable during code review to identify overcomplication, surface hidden tradeoffs, and verify that minimal changes were made.

What is the best way to limit AI code edits to surgical changes?

The best way to limit AI code edits to surgical changes is to enforce explicit assumptions and minimal change requirements. This confines the LLM to necessary modifications, avoiding unnecessary refactors and maintaining existing style.