BeClaude

nwiki-skills

New
GitHub TrendingGeneralby BestNathan

nathan wiki skills based on Karpathy's llm-wiki.md

First seen 5/29/2026

Summary

md, covering topics like LLMs, AI, and software development.

  • It helps developers quickly access structured insights and best practices without leaving the terminal.

Install & Usage

1
Create the skills directory
mkdir -p .claude/skills
2
Download the skill file
mkdir -p .claude/skills && curl -o .claude/skills/nwiki-skills.md https://raw.githubusercontent.com/BestNathan/nwiki-skills/main/SKILL.md
3
Invoke in Claude Code
/nwiki-skills

Use Cases

Quickly look up key concepts from Karpathy's LLM wiki while coding.
Get best practices for training or fine-tuning large language models.
Understand common pitfalls in AI development and how to avoid them.
Find recommended resources for deep learning and neural networks.
Reference Nathan's personal notes on AI research and tools.

Usage Examples

1

/nwiki-skills what is the attention mechanism?

2

/nwiki-skills summarize the key points from Karpathy's LLM wiki

3

Using nwiki-skills, list the top 5 tips for training LLMs

View source on GitHub

Security Audits

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Frequently Asked Questions

What is nwiki-skills?

This skill provides a curated knowledge base of Nathan's wiki, inspired by Karpathy's llm-wiki.md, covering topics like LLMs, AI, and software development. It helps developers quickly access structured insights and best practices without leaving the terminal.

How to install nwiki-skills?

To install nwiki-skills: create the skills directory (mkdir -p .claude/skills), then run: mkdir -p .claude/skills && curl -o .claude/skills/nwiki-skills.md https://raw.githubusercontent.com/BestNathan/nwiki-skills/main/SKILL.md. Finally, /nwiki-skills in Claude Code.

What is nwiki-skills best for?

nwiki-skills is a skill categorized under General. Created by BestNathan.

What can I use nwiki-skills for?

nwiki-skills is useful for: Quickly look up key concepts from Karpathy's LLM wiki while coding.; Get best practices for training or fine-tuning large language models.; Understand common pitfalls in AI development and how to avoid them.; Find recommended resources for deep learning and neural networks.; Reference Nathan's personal notes on AI research and tools..