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karpathy-guidelines

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Karpathy Guidelines

Karpathy 准则

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.
这是一套用于减少常见LLM编码错误的行为准则，源自Andrej Karpathy关于LLM编码陷阱的观察。
权衡说明： 这些准则更偏向谨慎而非速度。对于琐碎任务，请自行判断是否适用。

1. Think Before Coding

1. 编码前先思考

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.
不要想当然，不要掩盖困惑，要明确权衡。
在实现之前：
  • 明确阐述你的假设。如果不确定，就提问。
  • 如果存在多种解读方式，要一一列出，不要默默选择其中一种。
  • 如果有更简单的方案，要提出来。在必要时提出反对意见。
  • 如果有不清楚的地方，停下来。指出困惑点，然后提问。

2. Simplicity First

2. 优先追求简洁

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.
用最少的代码解决问题，不做任何投机性的实现。
  • 不添加超出需求的功能。
  • 不为单次使用的代码做抽象。
  • 不添加未被要求的“灵活性”或“可配置性”。
  • 不为不可能出现的场景做错误处理。
  • 如果你写了200行代码，但其实50行就能解决问题，那就重写。
问问自己：“资深工程师会认为这太复杂吗？”如果答案是肯定的，就简化。

3. Surgical Changes

3. 精准修改

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.
只修改必须修改的部分。只清理自己造成的混乱。
在编辑现有代码时：
  • 不要“优化”无关的代码、注释或格式。
  • 不要重构没有问题的代码。
  • 匹配现有代码风格，即使你有不同的偏好。
  • 如果你发现了无关的死代码，只需提及它，不要删除。
当你的修改产生了无用的代码时：
  • 删除因你的修改而变得无用的导入/变量/函数。
  • 除非被要求，否则不要删除原本就存在的死代码。
检验标准：每一行修改都应直接对应用户的需求。

4. Goal-Driven Execution

4. 目标导向的执行

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.
定义成功标准，循环执行直到验证通过。
将任务转化为可验证的目标：
  • “添加验证” → “为无效输入编写测试，然后让测试通过”
  • “修复bug” → “编写能复现bug的测试，然后让测试通过”
  • “重构X” → “确保重构前后测试都能通过”
对于多步骤任务，列出简要计划：
1. [步骤] → 验证：[检查项]
2. [步骤] → 验证：[检查项]
3. [步骤] → 验证：[检查项]
明确的成功标准让你可以独立循环执行。模糊的标准（如“让它正常工作”）需要不断澄清。