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## MIDI_rich_data_v2.htm
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
  <title>Multi-Track Audio to MIDI Analyzer</title>
  <style>
    :root {
      --bg: #0f1220;
      --panel: #161b2e;

## CLAUDE.md

      
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                minimaxir
                / CLAUDE.md
            
            
              Created
              January 2, 2026 01:53
            
              
                Python CLAUDE.md (20260101)
              
          
    Agent Guidelines for Python Code Quality

This document provides guidelines for maintaining high-quality Python code. These rules MUST be followed by all AI coding agents and contributors.
Your Core Principles

All code you write MUST be fully optimized.
"Fully optimized" includes:

  
## llm-wiki.md

      
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                karpathy
                / llm-wiki.md
            
            
              Created
              April 4, 2026 16:25
            
              
                llm-wiki
              
          
    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.

  
## SKILL.md

      
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                k16shikano
                / SKILL.md
            
            
              Last active
              June 17, 2026 02:31
            
              
                japanese-tech-writing/SKILL
              
          
    name
    japanese-tech-writing
  
  
    description
    日本語の技術文書・書籍原稿の文章規範。整形（一文一行、引用ブロック、脚注、コラム記法）、段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。
  
  
日本語技術文書の文章規範

日本語で技術的な原稿（書籍の章、記事、解説文）を書く・推敲するときは、以下の規範に従う。
整形


## stop-using-jwts.md

      
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                samsch
                / stop-using-jwts.md
            
            
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              June 17, 2026 02:21
            
              
                Stop using JWTs
              
          
    Stop using JWTs!

TLDR: JWTs should not be used for keeping your user logged in. They are not designed for this purpose, they are not secure, and there is a much better tool which is designed for it: regular cookie sessions.
If you've got a bit of time to watch a presentation on it, I highly recommend this talk: https://www.youtube.com/watch?v=pYeekwv3vC4 (Note that other topics are largely skimmed over, such as CSRF protection. You should learn about other topics from other sources. Also note that "valid" usecases for JWTs at the end of the video can also be easily handled by other, better, and more secure tools. Specifically, PASETO.)
A related topic: Don't use localStorage (or sessionStorage) for authentication credentials, including JWT tokens: https://www.rdegges.com/2018/please-stop-using-local-storage/
The reason to avoid JWTs comes down to a couple different points:

The JWT specification is specifically designed only for very short-live tokens (~5 minute or less). Sessions


## latency.txt
Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8" />
	<meta name="viewport" content="width=device-width, initial-scale=1.0" />
	<title>Multi-Track Audio to MIDI Analyzer</title>
	<style>
	:root {
	--bg: #0f1220;
	--panel: #161b2e;
	Latency Comparison Numbers (~2012)
	----------------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD