karpathy-guidelines

Apply behavioral guidelines to reduce coding mistakes in LLM development.

Updated Dec 5, 2025
One-click install
npx skills add https://github.com/ApothecaryMan/pharmaflow-ai --skill karpathy-guidelines-apothecaryman
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: karpathy-guidelines
Source: https://github.com/ApothecaryMan/pharmaflow-ai/tree/main/.agent/skills/karpathy-guidelines
Command: npx skills add https://github.com/ApothecaryMan/pharmaflow-ai --skill karpathy-guidelines-apothecaryman

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses common coding mistakes in LLM development, promoting clarity, simplicity, and safety.

Core Features & Use Cases

  • Behavioral Guidelines: Offers guidelines based on Andrej Karpathy's observations to avoid overcomplication and make surgical changes.
  • Assumptions and Tradeoffs: Encourages explicit assumptions and tradeoff recognition before coding.
  • Surgical Changes: Promotes minimal changes that directly address the task at hand.
  • Goal-Driven Execution: Emphasizes verifiable success criteria and iterative testing for robustness.

Quick Start

Run the karpathy-guidelines skill to review your code and apply the guidelines for best practices.

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 during LLM development?▼

To reduce coding mistakes during LLM development, apply behavioral guidelines that emphasize minimizing complexity, making surgical changes, and executing goal-driven tasks to maintain code quality.

What are the best practices for making surgical changes in LLM-generated code?▼

Best practices for surgical changes involve making minimal, targeted edits that directly address the task, explicitly recognizing assumptions and tradeoffs before coding to ensure clarity and safety.

How does goal-driven execution improve code review for LLM projects?▼

Goal-driven execution improves code review by establishing verifiable success criteria and emphasizing iterative testing, ensuring the generated code meets robustness and quality benchmarks.

When do I need coding guidelines to prevent overcomplication in software engineering?▼

You need coding guidelines to prevent overcomplication when LLM-generated code becomes overly complex, prioritizing simplicity and explicit tradeoff recognition to maintain safe, maintainable software.

Can I use these behavioral guidelines with my existing code review workflow?▼

Yes, you can integrate these behavioral guidelines into your existing code review workflow to evaluate code quality, check for overcomplication, and verify that changes remain surgical and goal-driven.

Why does my LLM-generated code lack verifiable success criteria?▼

LLM-generated code lacks verifiable success criteria when it is not developed using goal-driven execution, which requires defining explicit assumptions and iterating on tests before deployment.