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Karpathy Guidelines

  • 1.6k installs
  • 1 repo stars
  • Updated January 28, 2026
  • szkocot/andrej-karpathy-skills

This is a copy of karpathy-guidelines by forrestchang - installs and ranking accrue to the original listing.

karpathy-guidelines is an agent behavior skill that embeds Andrej Karpathy's coding principles into Claude workflows so developers who want simpler, more deliberate code output avoid common LLM overengineering mistakes.

About

karpathy-guidelines is a MIT-licensed agent skill derived from Andrej Karpathy's observations on LLM coding pitfalls. It instructs agents to think before coding, surface assumptions and tradeoffs, make surgical edits instead of sweeping rewrites, and define verifiable success criteria before implementation. The skill applies during writing, reviewing, and refactoring sessions when an agent might otherwise hide confusion or overcomplicate solutions. Developers reach for karpathy-guidelines when they want caution-biased output quality on non-trivial changes, accepting slower deliberation in exchange for cleaner diffs. The guidelines explicitly note a speed-versus-caution tradeoff and recommend judgment on trivial tasks.

  • 7 core behavioral guidelines derived from Andrej Karpathy’s LLM coding observations
  • Explicit assumption surfacing before any implementation begins
  • Enforces surgical changes and forbids speculative refactoring
  • Requires verifiable success criteria and simplicity-first mindset
  • Reduces overcomplicated code, hidden confusion, and unnecessary abstractions

Karpathy Guidelines by the numbers

  • 1,638 all-time installs (skills.sh)
  • +151 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/szkocot/andrej-karpathy-skills --skill karpathy-guidelines

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Listed on Skillselion
Installs1.6k
repo stars1
Last updatedJanuary 28, 2026
Repositoryszkocot/andrej-karpathy-skills

How do you stop LLM agents from overcomplicating code changes?

Embed Andrej Karpathy’s coding principles directly into their agent’s behavior for cleaner, simpler, and more deliberate code output.

Who is it for?

Developers using AI coding agents who want Karpathy-style restraint, clarity, and minimal diffs on non-trivial implementation or review work.

Skip if: Developers who need maximum generation speed on throwaway prototypes where broad rewrites and implicit assumptions are acceptable.

When should I use this skill?

The agent is about to implement, review, or refactor non-trivial code and risks overengineering, hidden assumptions, or unverifiable changes.

What you get

Documented assumptions, smaller surgical diffs, explicit tradeoff notes, and verifiable success criteria before code edits.

Files

SKILL.mdMarkdownGitHub ↗

Karpathy Guidelines

Behavioral guidelines to reduce common LLM coding mistakes, derived from Andrej Karpathy's observations on LLM coding pitfalls.

Tradeoff: These guidelines bias toward caution over speed. For trivial tasks, use judgment.

1. Think Before Coding

Don't assume. Don't hide confusion. Surface tradeoffs.

Before implementing:

  • State your assumptions explicitly. If uncertain, ask.
  • If multiple interpretations exist, present them - don't pick silently.
  • If a simpler approach exists, say so. Push back when warranted.
  • If something is unclear, stop. Name what's confusing. Ask.

2. Simplicity First

Minimum code that solves the problem. Nothing speculative.

  • No features beyond what was asked.
  • No abstractions for single-use code.
  • No "flexibility" or "configurability" that wasn't requested.
  • No error handling for impossible scenarios.
  • If you write 200 lines and it could be 50, rewrite it.

Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.

3. Surgical Changes

Touch only what you must. Clean up only your own mess.

When editing existing code:

  • Don't "improve" adjacent code, comments, or formatting.
  • Don't refactor things that aren't broken.
  • Match existing style, even if you'd do it differently.
  • If you notice unrelated dead code, mention it - don't delete it.

When your changes create orphans:

  • Remove imports/variables/functions that YOUR changes made unused.
  • Don't remove pre-existing dead code unless asked.

The test: Every changed line should trace directly to the user's request.

4. Goal-Driven Execution

Define success criteria. Loop until verified.

Transform tasks into verifiable goals:

  • "Add validation" → "Write tests for invalid inputs, then make them pass"
  • "Fix the bug" → "Write a test that reproduces it, then make it pass"
  • "Refactor X" → "Ensure tests pass before and after"

For multi-step tasks, state a brief plan:

1. [Step] → verify: [check]
2. [Step] → verify: [check]
3. [Step] → verify: [check]

Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.

Related skills

How it compares

Pick karpathy-guidelines over generic style linters when the problem is agent behavior—overbuilding, hidden confusion, or unverifiable changes—rather than syntax or formatting violations.

FAQ

When should karpathy-guidelines be used?

karpathy-guidelines should be used when writing, reviewing, or refactoring code with an AI agent. The skill instructs the agent to state assumptions, compare tradeoffs, and define verifiable success criteria before making edits.

Does karpathy-guidelines slow down AI coding?

karpathy-guidelines biases agents toward caution over speed. The skill's readme explicitly recommends using judgment on trivial tasks while applying full deliberation on non-trivial implementation and review work.

Code Review & Qualitytestingintegrations

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