0xjac

The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.

The correct way of creating a private frok by duplicating the repo is documented here.

For this assignment the commands are:

1. Create a bare clone of the repository. (This is temporary and will be removed so just do it wherever.)

git clone --bare git@github.com:usi-systems/easytrace.git

kriegalex

Install Battle.net on CachyOS Linux Using Steam & Proton

Tested on: CachyOS (Arch-based) · KDE Plasma 6.5 / 6.6 · Wayland · Steam (native pacman package)

Last updated: March 2026

Games confirmed working: World of Warcraft, Diablo IV, Diablo II: Resurrected, StarCraft Remastered, Hearthstone, Overwatch 2, Call of Duty

Why This Method?

LukaPrebil

PostgreSQL Major Version Upgrades (Docker)

Major PostgreSQL upgrades (e.g., 14→18) require a full dump and restore — the data files are not compatible across major versions.

Note: Immich requires vector extensions, and they supply an image with them bundled in as ghcr.io/immich-app/postgres:18-vectorchord0.5.3-pgvector0.8.1

Procedure

1. Dump: docker exec -t <container> pg_dumpall --clean --if-exists --username=<user> | gzip > dump.sql.gz
2. Stop the stack: docker compose down

lewixlabs

# Credits:
# - https://www.hackster.io/thatiotguy/enable-monitor-mode-in-tp-link-tl-wn722n-v2-v3-128fc6
# - https://github.com/aircrack-ng/rtl8188eus/issues/234
# Tested on Kali Linux 2022.3
# Commands used to Setup the Adapter from aircrack repository
sudo apt update
sudo apt install bc -y
sudo rmmod r8188eu.ko
git clone https://github.com/gglluukk/rtl8188eus
cd rtl8188eus

haydenmc

; Alternate GCode for the Stealthbrush Prusa Core One Mod
; Intended to be slightly more "aggressive" when brushing the nozzle,
; inspired by the Bambu A1 wipe pattern.
;
; Paste after `G29 G ; absorb heat` in Core One Printer "Start G-code"
;
; ---  PREP NOZZLE FOR WIPE ---
M109 S180 ; heat nozzle to soften residue, wait
M104 S{((filament_type[0] == "PC" or filament_type[0] == "PA") ? (first_layer_temperature[0] - 25) : (filament_type[0] == "FLEX") ? 210 : 170)} ; set passive (no-wait) MBL target for temp to settle to during wipe
; --- /PREP NOZZLE FOR WIPE ---

octocat

class HelloWorld
   def initialize(name)
      @name = name.capitalize
   end
   def sayHi
      puts "Hello #{@name}!"
   end
end

hello = HelloWorld.new("World")

gioxx

#!/bin/bash
# Proxmox: Shutdown VMs and LXCs (GSolone, 2025)
# This script stops all running VMs and LXC containers, excluding specified IDs, and logs the operation.
# In DEBUG mode, it only stops one VM and one LXC container for testing purposes, ignoring exclusions.

export PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
logfile="/var/log/proxmox_shutdown.log"
LOCKFILE="/tmp/proxmox_shutdown.lock"

# Timestamp helper

JonnyWong16

Updated script link:
    https://github.com/blacktwin/JBOPS/blob/master/utility/hide_episode_spoilers.py

arianvp

Native Secure Enclave backed ssh keys on MacOS

It turns out that MacOS Tahoe can generate and use secure-enclave backed SSH keys! This replaces projects like https://github.com/maxgoedjen/secretive

There is a shared library /usr/lib/ssh-keychain.dylib that traditionally has been used to add smartcard support to ssh by implementing PKCS11Provider interface. However since recently it also implements SecurityKeyProivder which supports loading keys directly from the secure enclave! SecurityKeyProvider is what is normally used to talk to FIDO2 devices (e.g. libfido2 can be used to talk to your Yubikey). However you can now use it to talk to your Secure Enclave instead!

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.