Karpathy Guidelines

作者 multica-ai2c606141936fMIT收录于 2026年10月8日更新于 2026年10月8日

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

AI 生成的概览

一套行为准则,引导 AI 编程代理做出更简单、更克制、可验证的代码改动。

功能
该技能为编写、审查或重构代码的 AI 代理提供一组行为规则。内容包括:在实现前明确说明假设、保持代码最小化且不做投机性设计、只改动请求所要求的范围,以及把任务转化为带成功标准的可验证目标。它不产出任何文件或成品,只影响代理处理编程工作的方式。
适用场景
当代理即将编写、审查或重构代码,且风险在于过度复杂、改动超出请求范围或成功标准不明确时使用。也适用于需要给出简短计划并附带验证步骤的多步骤编程任务。
运行要求
无需任何工具、软件包、运行时、凭据或网络访问。它仅为指令,不附带脚本。

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.

来源与署名

来源:multica-ai/andrej-karpathy-skills位于skills/karpathy-guidelines提交2c60614

许可证: MIT

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