接受Karpathy的建议,给AI编程带上紧箍咒

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name: karpathy-guidelines

description: 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.

license: MIT

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# Karpathy Guidelines

Behavioral guidelines to reduce common LLM coding mistakes, derived from [Andrej Karpathy’s observations](https://x.com/karpathy/status/2015883857489522876) 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.