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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.

@o11c
o11c / every-vm-tutorial-you-ever-studied-is-wrong.md
Last active September 25, 2026 04:29
Every VM tutorial you ever studied is wrong (and other compiler/interpreter-related knowledge)

Note: this was originally several Reddit posts, chained and linked. But now that Reddit is dying I've finally moved them out. Sorry about the mess.


URL: https://www.reddit.com/r/ProgrammingLanguages/comments/up206c/stack_machines_for_compilers/i8ikupw/ Summary: stack-based vs register-based in general.

There are a wide variety of machines that can be described as "stack-based" or "register-based", but not all of them are practical. And there are a lot of other decisions that affect that practicality (do variables have names or only address/indexes? fixed-width or variable-width instructions? are you interpreting the bytecode (and if so, are you using machine stack frames?) or turning it into machine code? how many registers are there, and how many are special? how do you represent multiple types of variable? how many scopes are there(various kinds of global, local, member, ...)? how much effort/complexity can you afford to put into your machine? etc.)

  • a pure stack VM can only access the top elemen
@kunteinzo
kunteinzo / Windows Activation Script.bat
Last active September 25, 2026 04:29
Windows Activation Bat file
@ECHO OFF
title Windows Activation Script
setlocal EnableDelayedEXpansion
::echo Note: To eXecute this script with Run As Administrator
net session >nul 2>&1
if %errorlevel% == 0 (
::echo Success: Administrative permissions confirmed.
call :Main
@zcourts
zcourts / tmux cheat sheet
Last active September 25, 2026 04:08
tmux cheat sheet image from DuckDuckGo UI
https://duckduckgo.com/?q=tmux+cheat+sheet&atb=v47-1_x&ia=cheatsheet&iax=1
@sundowndev
sundowndev / GoogleDorking.md
Last active September 25, 2026 03:57
Google dork cheatsheet

Google dork cheatsheet

Search filters

Filter Description Example
allintext Searches for occurrences of all the keywords given. allintext:"keyword"
intext Searches for the occurrences of keywords all at once or one at a time. intext:"keyword"
inurl Searches for a URL matching one of the keywords. inurl:"keyword"
allinurl Searches for a URL matching all the keywords in the query. allinurl:"keyword"
intitle Searches for occurrences of keywords in title all or one. intitle:"keyword"
@thumbin-sptc
thumbin-sptc / High_school_standards
Last active September 25, 2026 03:54
고등학교(선택 중심 교육과정) 성취기준 데이터
{
"고1": {
"공통국어1": [
[
"[10공국1-01-01]",
"대화의 원리를 고려하여 대화하고 자신의 듣기⋅말하기 과정과 공동체의 담화 관습을 성찰한다."
],
[
"[10공국1-01-02]",
"논제의 필수 쟁점별로 논증을 구성하고 논증이 타당한지 평가하며 토론한다."
@thumbin-sptc
thumbin-sptc / middle-school-standards
Created May 14, 2026 02:14
중학교(공통교육과정) 성취기준 데이터
{
"중학교": {
"국어": [
[
"[9국01-01]",
"화자의 의도와 관점을 추론하며 듣는다."
],
[
"[9국01-02]",
"설득 전략을 비판적으로 분석하며 듣는다."
@thumbin-sptc
thumbin-sptc / standards.json
Created May 13, 2026 15:56
2022 개정 교육과정 초등 1~6학년 성취기준 데이터
{
"1-2": {
"바른 생활": [
["[2바01-01]", "학교 생활 습관과 학습 습관을 형성하여 안전하고 건강하게 생활한다."],
["[2바01-02]", "나를 이해하고 존중하며 생활한다."],
["[2바01-03]", "가족이나 주변 사람을 배려하며 관계를 맺는다."],
["[2바01-04]", "생태환경에서 더불어 살기 위해 노력한다."],
["[2바02-01]", "공동체에서 내가 할 수 있는 일을 찾아보고 실천한다."],
["[2바02-02]", "우리나라의 소중함을 알고 사랑하는 마음을 기른다."],
["[2바02-03]", "차이나 다양성을 서로 존중하면서 생활한다."],

Beast Mode

Beast Mode is a custom chat mode for VS Code agent that adds an opinionated workflow to the agent, including use of a todo list, extensive internet research capabilities, planning, tool usage instructions and more. Designed to be used with 4.1, although it will work with any model.

Below you will find the Beast Mode prompt in various versions - starting with the most recent - 3.1

Installation Instructions

  • Go to the "agent" dropdown in VS Code chat sidebar and select "Configure Modes".
  • Select "Create new custom chat mode file"
@jinjier
jinjier / javdb-top250.md
Last active September 25, 2026 03:50
JavDB top 250 movies list. [Updated on 2026/01]