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Git Log Exploration Cheatsheet

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git log --graph --patch --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset%n%n%w(80,2,2)%B%n'

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x8r

A native CLI + shared library that answers two questions fast: "how many tokens is this file?" and "where do I cut it at ≤N tokens without slicing a function in half?"

What it is

single-purpose token-aware chunker for LLM agent tools
drop-in replacement for calling tiktoken in a subprocess loop
emits byte offsets [start, end) + token counts + boundary kind

Why

yt-dlp Cheatsheet: Metadata, Playlists & Lists

(No downloads — just metadata extraction)

All commands below use simulation mode by default (no video/audio is ever downloaded).
Add > output.txt (or > output.csv) at the end to save to a file, just like your example.

1. Core Flags You’ll Use Most

Flag	Purpose
`--flat-playlist`	Treat playlist as a flat list of videos (fast, no deep expansion)

	tar \
	--exclude='.git' \
	--exclude='node_modules' \
	--exclude='__pycache__' \
	--exclude='.venv' \
	--exclude='venv' \
	--exclude='.next' \
	--exclude='dist' \
	--exclude='build' \
	--exclude='target' \

	# Windows 11 Pro 25H2 -- AI and Telemetry Lockdown Cheatsheet

	Tested on build 26200.x. Assumes Windows 11 Pro (gpedit.msc access required for Group Policy sections).

	---

	## 1. Settings App

	### Privacy & Security > General


	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8" />
	<meta name="viewport" content="width=device-width, initial-scale=1.0" />
	<title>Reliability HTML Whitepaper Template</title>
	<style>
	:root {
	--paper: #fcfcfa;

	#!/usr/bin/env python3
	# i found a rinky dink python2 version of this in my old files. bringing it to 2026 for the hell of it.

	import os

	ksm_path = '/sys/kernel/mm/ksm/'

	def get_val(name):
	try:
	with open(os.path.join(ksm_path, name), 'r') as f:

	{
	"mcpServers": {
	"dumb_shell": {
	"command": "python",
	"args": [
	"-u",
	"C:/Users/<username>/<directory>/gitbash_mcp.py"
	],
	"cwd": "C:/Users/<username>/<directory>/",
	"env": {

	{
	"mcpServers": {
	"windows_gitbash_mcp": {
	"url": "http://127.0.0.1:3001/sse"
	}
	}
	}

	import numpy as np

	# --- Parameters ---
	num_neurons = 5
	timesteps = 100
	threshold = 1.0
	decay = 0.95
	learning_rate = 0.01

	# --- State ---