
Karpathy Guidelines
Based on Andrej Karpathy's observations about common LLM coding mistakes, this skill pushes back against the tendency to overcomplicate. It enforces four core behaviors: surface your assumptions and confusion before writing code, bias toward minimal solutions without speculative features, make surgical edits that touch only what's necessary, and define verifiable success criteria for every task. The tradeoff is explicit: you sacrifice speed for caution. For simple scripts this might feel heavy, but for production code or refactors where LLMs typically add unnecessary abstractions or touch too many files, the discipline pays off. Think of it as guardrails against your AI pair programmer's worst habits.
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Install
$ npx -y skills add multica-ai/andrej-karpathy-skills --skill karpathy-guidelines --agent claude-codeInstalls into .claude/skills of the current project.
Files
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.
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Details
- Repository
- github.com/multica-ai/andrej-karpathy-skills
- Categories
- Documentation, Code Review & Quality, AI & Agent Building
- First seen
- May 16, 2026