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karpathy-guidelines

by @forrestchangv
4.5(76)

行動ガイドラインに従い、LLMコーディングにおける一般的なエラーを効果的に削減し、コード品質を向上させます。

andrej-karpathyllm-trainingneural-networksai-best-practicesdeep-learningGitHub
インストール方法
npx skills add forrestchang/andrej-karpathy-skills --skill karpathy-guidelines
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Before / After 効果比較

1
使用前

LLMコードを記述する際、規範の欠如により一般的なエラーが頻繁に発生し、モデルのパフォーマンス低下や異常な動作を引き起こします。デバッグが困難になり、開発効率とモデルの品質に影響を与えます。

使用後

KarpathyのLLMコーディングガイドラインに従うことで、一般的なエラーを効果的に削減できます。これにより、より堅牢で予測可能なLLMコードを記述できるようになり、モデル開発の効率と最終的なパフォーマンスが向上します。

SKILL.md

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.

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統計データ

インストール数12.3K
評価4.5 / 5.0
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更新日2026年5月23日
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タイムライン

作成2026年3月16日
最終更新2026年5月23日