ClaudeWave
forrestchang avatar
forrestchang

andrej-karpathy-skills

Ver en GitHub

A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.

Tools92.5k estrellas8.9k forksActualizado 7d ago
ClaudeWave Trust Score
71/100
· OK

A single CLAUDE.md guideline file distilling Karpathy's LLM coding-pitfalls observations into four principles.

Passed
  • Actively maintained (<30d)
  • Healthy fork ratio
  • Clear description
  • Documented (README)
Flags
  • !No license declared
OK to use
Last scanned: 4/14/2026
Install in Claude Desktop
Method detected: Manual
{
  "mcpServers": {
    "andrej-karpathy-skills": {
      "command": "node",
      "args": ["/path/to/andrej-karpathy-skills/dist/index.js"]
    }
  }
}
1. Copy the snippet above.
2. Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows).
3. Replace any <placeholder> values with your API keys or paths.
4. Restart Claude Desktop. The MCP server appears automatically.
💡 Clone https://github.com/forrestchang/andrej-karpathy-skills and follow its README for install instructions.
Casos de uso

Resumen de Tools

# Karpathy-Inspired Claude Code Guidelines

> Check out my new project [Multica](https://github.com/multica-ai/multica) — an open-source platform for running and managing coding agents with reusable skills.
>
> Follow me on X: [https://x.com/jiayuan_jy](https://x.com/jiayuan_jy)

A single `CLAUDE.md` file to improve Claude Code behavior, derived from [Andrej Karpathy's observations](https://x.com/karpathy/status/2015883857489522876) on LLM coding pitfalls.

English | [简体中文](./README.zh.md)

## The Problems

From Andrej's post:

> "The models make wrong assumptions on your behalf and just run along with them without checking. They don't manage their confusion, don't seek clarifications, don't surface inconsistencies, don't present tradeoffs, don't push back when they should."

> "They really like to overcomplicate code and APIs, bloat abstractions, don't clean up dead code... implement a bloated construction over 1000 lines when 100 would do."

> "They still sometimes change/remove comments and code they don't sufficiently understand as side effects, even if orthogonal to the task."

## The Solution

Four principles in one file that directly address these issues:

| Principle | Addresses |
|-----------|-----------|
| **Think Before Coding** | Wrong assumptions, hidden confusion, missing tradeoffs |
| **Simplicity First** | Overcomplication, bloated abstractions |
| **Surgical Changes** | Orthogonal edits, touching code you shouldn't |
| **Goal-Driven Execution** | Leverage through tests-first, verifiable success criteria |

## The Four Principles in Detail

### 1. Think Before Coding

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

LLMs often pick an interpretation silently and run with it. This principle forces explicit reasoning:

- **State assumptions explicitly** — If uncertain, ask rather than guess
- **Present multiple interpretations** — Don't pick silently when ambiguity exists
- **Push back when warranted** — If a simpler approach exists, say so
- **Stop when confused** — Name what's unclear and ask for clarification

### 2. Simplicity First

**Minimum code that solves the problem. Nothing speculative.**

Combat the tendency toward overengineering:

- 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 200 lines could be 50, rewrite it

**The test:** 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 imperative tasks into verifiable goals:

| Instead of... | Transform to... |
|--------------|-----------------|
| "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 the LLM loop independently. Weak criteria ("make it work") require constant clarification.

## Install

**Option A: Claude Code Plugin (recommended)**

From within Claude Code, first add the marketplace:
```
/plugin marketplace add forrestchang/andrej-karpathy-skills
```

Then install the plugin:
```
/plugin install andrej-karpathy-skills@karpathy-skills
```

This installs the guidelines as a Claude Code plugin, making the skill available across all your projects.

**Option B: CLAUDE.md (per-project)**

New project:
```bash
curl -o CLAUDE.md https://raw.githubusercontent.com/forrestchang/andrej-karpathy-skills/main/CLAUDE.md
```

Existing project (append):
```bash
echo "" >> CLAUDE.md
curl https://raw.githubusercontent.com/forrestchang/andrej-karpathy-skills/main/CLAUDE.md >> CLAUDE.md
```

## Using with Cursor

This repository includes a committed Cursor project rule ([`.cursor/rules/karpathy-guidelines.mdc`](.cursor/rules/karpathy-guidelines.mdc)) so the same guidelines apply when you open the project in Cursor. See **[CURSOR.md](CURSOR.md)** for setup, using the rule in other projects, and how this relates to Claude Code.

## Key Insight

From Andrej:

> "LLMs are exceptionally good at looping until they meet specific goals... Don't tell it what to do, give it success criteria and watch it go."

The "Goal-Driven Execution" principle captures this: transform imperative instructions into declarative goals with verification loops.

## How to Know It's Working

These guidelines are working if you see:

- **Fewer unnecessary changes in diffs** — Only requested changes appear
- **Fewer rewrites due to overcomplication** — Code is simple the first time
- **Clarifying questions come before implementation** — Not after mistakes
- **Clean, minimal PRs** — No drive-by refactoring or "improvements"

## Customization

These guidelines are designed to be merged with project-specific instructions. Add them to your existing `CLAUDE.md` or create a new one.

For project-specific rules, add sections like:

```markdown
## Project-Specific Guidelines

- Use TypeScript strict mode
- All API endpoints must have tests
- Follow the existing error handling patterns in `src/utils/errors.ts`
```

## Tradeoff Note

These guidelines bias toward **caution over speed**. For trivial tasks (simple typo fixes, obvious one-liners), use judgment — not every change needs the full rigor.

The goal is reducing costly mistakes on non-trivial work, not slowing down simple tasks.

## License

MIT

Lo que la gente pregunta sobre andrej-karpathy-skills

¿Qué es forrestchang/andrej-karpathy-skills?

+

forrestchang/andrej-karpathy-skills es tools para el ecosistema de Claude AI. A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls. Tiene 92.5k estrellas en GitHub y se actualizó por última vez 7d ago.

¿Cómo se instala andrej-karpathy-skills?

+

Puedes instalar andrej-karpathy-skills clonando el repositorio (https://github.com/forrestchang/andrej-karpathy-skills) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar forrestchang/andrej-karpathy-skills?

+

Nuestro agente de seguridad ha analizado forrestchang/andrej-karpathy-skills y le ha asignado un Trust Score de 71/100 (tier: OK). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene forrestchang/andrej-karpathy-skills?

+

forrestchang/andrej-karpathy-skills es mantenido por forrestchang. La última actividad registrada en GitHub es de 7d ago, con 73 issues abiertos.

¿Hay alternativas a andrej-karpathy-skills?

+

Sí. En ClaudeWave puedes explorar tools similares en /categories/tools, ordenados por popularidad o actividad reciente.

Despliega andrej-karpathy-skills en tu cloud

Lleva este repo a producción en minutos. Cada plataforma genera su propio entorno con variables de entorno editables.

¿Mantienes este repo? Añade un badge a tu README

Pega el badge en tu README de GitHub para mostrar que está auditado por ClaudeWave. Cada badge enlaza de vuelta a esta página y muestra el Trust Score actual.

Featured on ClaudeWave — forrestchang/andrej-karpathy-skills
[![Featured on ClaudeWave](https://claudewave.com/api/badge/forrestchang-andrej-karpathy-skills)](https://claudewave.com/repo/forrestchang-andrej-karpathy-skills)
<a href="https://claudewave.com/repo/forrestchang-andrej-karpathy-skills"><img src="https://claudewave.com/api/badge/forrestchang-andrej-karpathy-skills" alt="Featured on ClaudeWave — forrestchang/andrej-karpathy-skills" width="320" height="64" /></a>

Más Tools

anthropics
claude-code
2d ago

Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.

118.4k19.7kShell
Tools
nextlevelbuilder
ui-ux-pro-max-skill
24d ago

An AI SKILL that provide design intelligence for building professional UI/UX multiple platforms

71.1k7.3kPython
Toolsai-skillsantigravity
gsd-build
get-shit-done
today

A light-weight and powerful meta-prompting, context engineering and spec-driven development system for Claude Code by TÂCHES.

57.7k4.9kJavaScript
Toolsclaude-codecontext-engineering
JuliusBrussee
caveman
9d ago

🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman

47.6k2.5kPython
Toolsaianthropic
jeecgboot
JeecgBoot
2d ago

一款 AI 驱动的低代码平台,提供"零代码"与"代码生成"双模式——零代码模式一句话搭建系统,代码生成模式自动输出前后端代码与建表 SQL,生成即可运行。平台内置 AI 聊天助手、AI大模型、知识库、AI流程编排、MCP 与插件体系,兼容主流大模型,支持一句话生成流程图、设计表单、聊天式业务操作,解决 Java 项目 80% 重复工作,高效且不失灵活。

46k16kJava
Toolsactivitiagent
BerriAI
litellm
today

Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM]

44.9k7.6kPython
Toolsai-gatewayanthropic