---
title: "GitHub - multica-ai/andrej-karpathy-skills"
url: https://stacklist.com/card/af44b3ca-5d85-4b0e-8a56-9b91ea5cb6cb
source_url: "https://github.com/multica-ai/andrej-karpathy-skills?mcp_token=eyJwaWQiOjI1MDY1MzMsInNpZCI6NDA3MjM1NDM0LCJheCI6IjY0YTRiMjM2NGFjZjE3MDYwNzk3ZmVhMDQyM2RmODE4IiwidHMiOjE3ODY1MDcwNzksImV4cCI6MTc4ODkyNjI3OX0.FcCwEo-s0z28PnDCR_qNjUjnzIn23cwa3RhCX9QufYg"
stack: https://stacklist.com/stack/67b59b54-8aa2-4460-bdb8-fa13669f687d
summary: "Andrej Karpathy's Skills Repository provides a CLAUDE.md file with four principles to improve Claude Code behavior and address common LLM coding pitfalls. The guidelines emphasize thinking before coding, simplicity, surgical changes, and goal-driven execution with verifiable success criteria."
tags: "llm-coding, claude-guidelines, code-quality, best-practices, andrej-karpathy, prompt-engineering, ai-agents"
key_entities: "Andrej Karpathy (person), Jiayuan (person), Claude Code (technology), Multica (technology), LLM (technology), Think Before Coding (concept), Simplicity First (concept), Surgical Changes (concept), Goal-Driven Execution (concept), Anthropic (organization)"
classification: "framework"
content_hash: "sha256:cda15c4f81a475e2e0b4060bf799af46b464413e3d236fd0dfcf2273b4381e77"
acp_version: "0.2"
token_counts_approximate: 1388
visibility: public
agent_accessible: true
status: "final"
---

# GitHub - multica-ai/andrej-karpathy-skills

Karpathy-Inspired Claude Code Guidelines Check out my new project Multica — an open-source platform for running and managing coding agents with reusable skills. Follow me on X: https://x.com/jiayuan_jy A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls. English | 简体中文 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: curl -o CLAUDE.md https://raw.githubusercontent.com/forrestchang/andrej-karpathy-skills/main/CLAUDE.md Existing project (append): 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 ) so the same guidelines apply when you open the project in Cursor. See 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: ## 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