Alexander H cheeseonamonkey

Python code scout: metrics + locally-generated summaries.

It’s useful for AI-agent priming because it extracts code into a dense signal - enough context for an agent to start acting like it “read the code.”

The summaries are actually quite lit; runs locally on your CPU (the model is <200MB) and is good at explaining what the code does, not just what it’s called.

Scout on itself compresses 5,123 source tokens into 1,628.

In another larger project: 22,962 into just 6,372! The agent could describe the whole thing technically, predict bugs, and suggest refactors with no additional context from source.

curl -fsSL "https://gist.githubusercontent.com/cheeseonamonkey/38d6464c26332d73743144fc771d3c0f/raw/206180318661c451b976d9fe47425e5a930d7f74/bootstrap_fresh_host.sh" | bash

	# === ULTIMATE METRIC MINER (EXTENDED FOR MINING & BANDWIDTH APPS) ===
	Clear-Host
	$H = "Cyan"; $V = "White"; $L = "DarkGray"; $W = "Yellow"

	# 1. CPU DEEP DIVE + INSTRUCTION SETS
	Write-Host "--- [1] CPU METRICS + INSTRUCTION SETS ---" -ForegroundColor $H
	$cpu = Get-CimInstance Win32_Processor
	$cpuCache = Get-CimInstance Win32_CacheMemory
	$l2 = ($cpuCache \| Where-Object { $_.Level -eq 4 -or $_.Purpose -eq "L2 Cache" } \| Measure-Object -Property MaxCacheSize -Sum).Sum
	$l3 = ($cpuCache \| Where-Object { $_.Level -eq 5 -or $_.Purpose -eq "L3 Cache" } \| Measure-Object -Property MaxCacheSize -Sum).Sum

	netcheck() {
	emulate -L zsh
	setopt local_options no_monitor no_notify

	local R=$'\e[0m' B=$'\e[1m' G=$'\e[32m' E=$'\e[31m' D=$'\e[90m'
	local OK="${B}${G}✓${R}" NO="${B}${E}✗${R}" WAIT="${D}…${R}"
	local host=google.com url=http://connectivitycheck.gstatic.com/generate_204

	local dns=$WAIT http=$WAIT dp hp dr hr
	draw(){ print -nr -- $'\r\e[2K'"DNS [$dns] \| HTTP [$http]"; }

	#!/usr/bin/env zsh
	# Quick diagnostics for the EasyTether USB path.

	set -u

	header() {
	printf '\n== %s ==\n' "$1"
	}

	status() {

	#!/usr/bin/env python3
	import re, time, json, gzip, argparse, hashlib, logging
	from urllib.parse import urljoin, urlparse, parse_qs
	from xml.etree import ElementTree as ET

	from curl_cffi import requests
	from curl_cffi.requests.exceptions import Timeout, RequestException

	BASE = "https://www.choicehotels.com"
	BROWSERS = ["chrome120", "chrome110", "safari17"]


	<style>
	body::after{
	content:attr(data-q);
	position:absolute;
	top:10px;
	right:-30px;
	color:#e5e7eb;
	font-size:13px;
	font-weight:600;

	echo "deb http://repo.vivaldi.com/stable/deb/ stable main" \| sudo tee /etc/apt/sources.list.d/vivaldi.list > /dev/null
	wget -O - http://repo.vivaldi.com/stable/linux_signing_key.pub \| sudo apt-key add -
	sudo apt update && sudo apt install vivaldi-stable

	import csv, json, os, random, re, time
	from typing import Optional
	from curl_cffi import requests # pip install curl_cffi
	from bs4 import BeautifulSoup

	# --- CONFIGURATION ---
	BATCH_SIZE = 500 # Lowered slightly to be safe
	MIN_DELAY, MAX_DELAY = 12, 40
	LONG_DELAY_CHANCE = 0.08 # 8% chance of a "coffee break"
	LONG_DELAY_RANGE = (120, 300) # 2-5 minutes

	#!/usr/bin/env zsh
	set -euo pipefail

	SRC="/tmp/testfile.dat"
	DEV="/dev/disk/by-id/scsi-0Linode_Volume_blk_vol"
	MNT="/blk"
	TMP="$MNT/.bench_tmp"

	OPTS=("none" "lzo" "zlib:1" "zlib:5" "zlib:9" "zstd:1" "zstd:3" "zstd:6" "zstd:9" "zstd:15")