karpathy-guidelines

Name: karpathy-guidelines
Availability: InStock
Author: louderthanthunderx1

Provide decision-making guidelines for LLM-assisted coding tasks.

Updated May 21, 2026

Search Tags:#guidelines #surgical-changes #verifiable-goals #goal-driven #karpathy #llm-coding #think-before-coding

Ready to run

npx skills add https://github.com/louderthanthunderx1/loki-skills --skill karpathy-guidelines-louderthanthunderx1

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: karpathy-guidelines
Source: https://github.com/louderthanthunderx1/loki-skills/tree/main/skills/general/karpathy-guidelines
Command: npx skills add https://github.com/louderthanthunderx1/loki-skills --skill karpathy-guidelines-louderthanthunderx1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Behavioral guidelines to reduce common LLM coding mistakes, surfacing assumptions, pushing for simplicity, surgical changes, and defining verifiable success criteria to guide engineering tasks.

Core Features & Use Cases

Think Before Coding: surface assumptions, surface tradeoffs, ask clarifying questions, and present multiple interpretations.
Simplicity First: favor minimal, direct implementations and avoid premature abstractions.
Surgical Changes: touch only what is necessary and preserve existing style and behavior.
Goal-Driven Execution: define verifiable success criteria and iterate with tests for measurable outcomes.
Real-world usage: teams applying guidelines to improve reliability, reduce review cycles, and accelerate safe iteration.

Quick Start

State assumptions, choose the simplest solution, make surgical changes, and define verifiable goals before coding.

Frequently Asked Questions about karpathy-guidelines

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

FAQPage Schema

How do I reduce coding mistakes when using LLMs for automated code generation?▼

Reduce LLM coding mistakes by applying behavioral guidelines that surface hidden assumptions, enforce simplicity, make surgical changes, and define verifiable success criteria before writing code.

What is the best way to enforce simplicity and avoid premature abstractions in LLM-assisted coding?▼

Enforce simplicity first by favoring minimal, direct implementations over complex architectures, ensuring the language model outputs only the necessary code without unnecessary abstractions.

How do I make surgical changes to existing code without breaking current behavior?▼

Make surgical changes by touching only what is strictly necessary for the task, preserving existing code style and behavior, and avoiding widespread refactoring during LLM-assisted modifications.

How do I define verifiable goals for goal-driven execution in software engineering?▼

Define verifiable goals by establishing explicit success criteria and iterating with tests, ensuring measurable outcomes guide the code generation and review process.

Why should I think before coding when refactoring code with language models?▼

Think before coding to surface tradeoffs, ask clarifying questions, and present multiple interpretations, preventing the language model from implementing incorrect assumptions during refactoring.

Do I need explicit frontmatter metadata to use these guidelines for code review?▼

Explicit frontmatter metadata is required to apply these guidelines, providing structured context that ensures assumptions and verifiable success criteria are documented before code review.