deonna

The prompt that removes 15 AI design tells

Paste this into Claude Code, Cursor, Codex, Lovable, Bolt, or whatever you build with. It has your agent install Impeccable (free and open source) and run it, then fix the 15 tells.

First, set up Impeccable, a free, open-source design skill for AI coding agents (github.com/pbakaus/impeccable, Apache 2.0). If you can run terminal commands:

1. From the project root, run: npx impeccable install --scope=project
   If it asks which tools to install for, pick the one you're running in.
2. Run /impeccable init so it records who the site is for and how it should feel. If the /impeccable command isn't available until I restart you, tell me and keep going with step 3.

winstonleedev

;Dvorak with Korean support, pause when Korean IME is detected or Scroll lock is on

Loop {
   If GetKeyState("ScrollLock", "T")
   or (DllCall("GetKeyboardLayout", Int,DllCall("GetWindowThreadProcessId", int,WinActive("A"), Int,0)) == 68289554) {
      Suspend On
   } else {
      Suspend Off
   }
   Sleep, 50

mylamour

#!/bin/bash

#Script From https://github.com/Nyr/openvpn-install

# OpenVPN road warrior installer for Debian, Ubuntu and CentOS

# This script will work on Debian, Ubuntu, CentOS and probably other distros
# of the same families, although no support is offered for them. It isn't
# bulletproof but it will probably work if you simply want to setup a VPN on
# your Debian/Ubuntu/CentOS box. It has been designed to be as unobtrusive and

go-hyperlink

15 Elite Sites to Rewire Your Brain 🧠 (for polymath)

A collection of 15 underrated websites for learning, research, critical thinking, curiosity, and exploration featured in the Hyperlink video:

The Internet’s Hidden Brain: 15 Elite Sites You’ve Never Seen

These are not the usual websites you see on every “best websites” list. Explore them, bookmark the ones you love, and share this list with someone who enjoys learning across different fields.

---

ogzhanolguncu

name

socratic-code-mentor

description

Mentor a user who builds a project to learn how it works. They write the core; you do all other work and keep it fun. Use when the user says "teach me", "guide me", "mentor me", "hints only", "no spoilers", "Socratic", or "help me learn X by building it", or when a project file says the project is for learning. Do not use for normal feature work. Do not use when the first request is "just fix it" or "write it for me".

ocoyawale

This page is a curated collection of Jupyter/IPython notebooks that are notable for some reason. Feel free to add new content here, but please try to only include links to notebooks that include interesting visual or technical content; this should not simply be a dump of a Google search on every ipynb file out there.

Important contribution instructions: If you add new content, please ensure that for any notebook you link to, the link is to the rendered version using nbviewer, rather than the raw file. Simply paste the notebook URL in the nbviewer box and copy the resulting URL of the rendered version. This will make it much easier for visitors to be able to immediately access the new content.

Note that Matt Davis has conveniently written a set of bookmarklets and extensions to make it a one-click affair to load a Notebook URL into your browser of choice, directly opening into nbviewer.

scripting

Markdown Browser

Goal

Build a very simple web browser whose native document format is Markdown.

This is not a Markdown editor inside a conventional web app.

It is a browser for a simpler web.

karpathy

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

khalidhalba-jhu

🎮 Run LLMs on your Intel Mac's AMD GPU — llama.cpp + Vulkan/MoltenVK on macOS (Radeon Pro 5500M, 4× faster than CPU). Confirmed working !.

🎮 llama.cpp + AMD GPU on Intel Mac (macOS) — Vulkan/MoltenVK Guide

TL;DR: Yes, GPU-accelerated llama.cpp works under macOS on Intel MacBook Pro with AMD Radeon — via Vulkan/MoltenVK. But two flags are mandatory: -fa 0 (RDNA correctness bug) and -c 4096 (VRAM oversubscription trap). Without the second one you get a soul-crushing 0.6 tokens/sec and will wrongly blame the driver. With both: 46–54 t/s generation — ~4× faster than CPU.

Companion guide for Linux/ROCm on the same hardware (zero-fuss option): Ollama + ROCm on T2 MacBook Pro

📊 Results (the short version)