Skip to content

Instantly share code, notes, and snippets.

@North-West-Wind
North-West-Wind / extract_splash_screen.py
Created November 18, 2023 05:41
Extract splash screen from Atmosphere's package3
from PIL import Image
import sys, os
from struct import pack as pk
from math import floor
SPLASH_SCREEN_WIDTH = 1280
SPLASH_SCREEN_HEIGHT = 720
SPLASH_SCREEN_STRIDE = 768
@rudolphos
rudolphos / StopAdobe.bat
Last active March 5, 2026 04:50
A bat script that stops all Adobe / Adobe CC background services and programs on Windows.
TASKKILL /F /IM "Creative Cloud.exe" /T
TASKKILL /F /IM "AcroRd32.exe" /T
TASKKILL /F /IM "AdobeARM.exe" /T
TASKKILL /F /IM "Adobe Desktop Service.exe" /T
TASKKILL /F /IM "Adobe CEF Helper.exe" /T
TASKKILL /F /IM "Adobe Installer.exe" /T
TASKKILL /F /IM "AdobeUpdateService.exe" /T
TASKKILL /F /IM "CoreSync.exe" /T
TASKKILL /F /IM "AdobeIPCBroker.exe" /T
TASKKILL /F /IM "Adobe Installer.exe" /T

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.

@zwaldowski
zwaldowski / Extra Logging for My Great App.mobileconfig
Last active April 18, 2026 03:45
Apple Configuration Profile for Logging in iOS 10 and macOS Sierra
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<!-- iOS 10, macOS Sierra, and friends bring a new logging subsystem that's
supposed to scale from the kernel, up to frameworks, and up to apps. It defaults
to a more regimented, privacy-focused approach that large apps and complex
systems need.
It, along with Activity Tracing introduced in iOS 8 and macOS Yosemite and the
Console app in macOS Sierra, hope to help you graduate from caveman debugging to
@jonlabelle
jonlabelle / go_language_cheatsheet.md
Last active April 18, 2026 03:40
Go language cheatsheet, written to be something you can actually keep open while coding.

Go (Golang) Language Cheatsheet

Comprehensive Go language cheatsheet, written to be something you can actually keep open while coding.

It includes core syntax, language rules, standard patterns, and essential "Go-isms".


Table of Contents

@Makeshift
Makeshift / tutorial.md
Last active April 18, 2026 03:37
Tutorial for automatically syncing an Obsidian vault with Git on an Android device

How to sync Obsidian with Git on Android

Limitations

  • If Termux is closed in the background by Android, the cron service will stop updating your repository and you must open Termux again. Refer to instructions for your device model to disable the killing of certain background applications.
  • This may negatively affect your devices battery life. I'm not entirely sure yet.

Setup

Codex Reviewer

You are a code reviewer agent powered by OpenAI Codex. Your job is to review code changes and provide actionable feedback.

Workflow

  1. Receive a review request (diff, file paths, or a description of changes).
  2. Use the mcp__codex__codex tool to start a Codex review session with the relevant code context.
  3. If follow-up analysis is needed, use mcp__codex__codex-reply with the thread ID from step 2.
  4. Summarize Codex's findings into a clear, structured review for the user.