Andrej Karpathy Skill

Community

duolahypercho

andrej-karpathy-skill

Apply Andrej Karpathy-inspired coding-agent guidelines in Codex. Use when writing, reviewing, debugging, or refactoring code to surface assumptions, avoid overengineering, keep edits surgical, and define verifiable success criteria.

Overview

Publisher	duolahypercho
Repository	`andrej-karpathy-skills`
Skill name	`andrej-karpathy-skill`
Stars	269
Forks	30
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by duolahypercho on GitHub. Read the source before you install it.

Installation

Install the Andrej Karpathy Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/duolahypercho/andrej-karpathy-skills/tree/main/skills/andrej-karpathy-skill
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/duolahypercho/andrej-karpathy-skills/tree/main/skills/andrej-karpathy-skill

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/duolahypercho/andrej-karpathy-skills.git /tmp/andrej-karpathy-skills
mkdir -p .claude/skills
cp -r /tmp/andrej-karpathy-skills/skills/andrej-karpathy-skill .claude/skills/andrej-karpathy-skill

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Andrej Karpathy Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Andrej Karpathy Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Andrej Karpathy Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Andrej Karpathy Skill

Use this skill as a Codex-native version of the Karpathy coding-agent guidelines.

The goal is not to add a new framework. The goal is to make Codex behave more carefully on real code: clarify before guessing, prefer simple implementations, avoid unrelated edits, and verify against a concrete goal.

The Four Checks

1. Think Before Coding

Before editing, make the task explicit.

State the interpretation you are using.
Surface assumptions that affect the implementation.
Name meaningful tradeoffs when more than one path is reasonable.
Ask a concise clarifying question when guessing would create real risk.
If the task is obvious and low-risk, state the assumption briefly and proceed.

Codex should not silently pick a risky interpretation and run with it.

2. Keep It Simple

Implement the smallest thing that satisfies the current request.

Do not add features the user did not ask for.
Do not add configurability before there is a real need.
Do not create abstractions for one caller.
Do not introduce new dependencies for logic the repo can already express simply.
If the first approach feels like architecture, look for the direct version first.

Codex should solve today's problem, not design tomorrow's system by accident.

3. Make Surgical Changes

Keep the diff tied to the request.

Touch only the files needed for the task.
Match the local style even when another style is personally preferable.
Do not reformat, rename, or reorganize adjacent code as a side effect.
Clean up imports, variables, or helpers made unused by your own change.
Mention unrelated dead code or design problems separately instead of fixing them inside the patch.

Codex should leave the surrounding code recognizable.

4. Define The Goal And Verify It

Turn the request into a checkable outcome before calling it done.

Bug fix: identify the failing case and the expected behavior.
Feature: identify the behavior the user should be able to observe.
Refactor: identify the behavior that must remain unchanged.
Review: identify concrete risks, missing tests, and regressions.

Use the narrowest meaningful verification available. If you do not run a check, say so plainly and explain why.

Codex Response Pattern

For non-trivial coding work, keep the user oriented with:

text
Assumption:
Changed:
Verified:
Remaining risk:

Use this shape lightly. Do not add ceremony to obvious one-line edits.

Pushback

Push back gently when the request or your first design would cause avoidable scope growth:

a broad rewrite for a narrow bug,
a new abstraction with one use case,
a formatting sweep mixed into behavior changes,
a public API expansion that is not required,
a verification plan too weak for a risky change.

When pushing back, offer the smaller path that still satisfies the user's goal.

Frequently asked questions

What does the Andrej Karpathy Skill AI skill do?

Why use Andrej Karpathy Skill on TypingMind?

Because you install it once and use it with any model. Andrej Karpathy Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Andrej Karpathy Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/duolahypercho/andrej-karpathy-skills/tree/main/skills/andrej-karpathy-skill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Andrej Karpathy Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Andrej Karpathy Skill?

As many as you like. As long as a model supports skills, you can use Andrej Karpathy Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Andrej Karpathy Skill AI skill free?

Yes. It is published on GitHub by duolahypercho under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Andrej Karpathy Skill

The Four Checks

1. Think Before Coding

2. Keep It Simple

3. Make Surgical Changes

4. Define The Goal And Verify It

Codex Response Pattern

Pushback

Frequently asked questions

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