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## dechapon25-workflow.mg
## Workflow Orchestration

### 1. Plan Node Default

* Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions).
* If something goes sideways, STOP and re-plan immediately—don't keep pushing.
* Use plan mode for verification steps, not just building.
* Write detailed specs upfront to reduce ambiguity.

### 2. Subagent Strategy

## windows-keys.md

      
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                rvrsh3ll
                / windows-keys.md
            
            
              Created
              February 18, 2024 22:44
            
              
                Windows Product Keys
              
          
    NOTE

These are NOT product / license keys that are valid for Windows activation.

These keys only select the edition of Windows to install during setup, but they do not activate or license the installation.
Index


Windows 11
RTM Generic Keys


## script.py
import re


strings = set()

with open('texts.txt', mode='r', encoding='utf-8') as file_input:
    content = file_input.read()
    regExStr = r'^\s*\d string title = "(?:tooltip\d+|Name|Dialogue Text)"\n\s*\d string value = "((?!(START|input|\w+\(\)|\!\(\w+\(\)\))).+)"$'
    compiled = re.compile(regExStr, re.MULTILINE)
    matched = compiled.finditer(content)

## cloud-optimized-hdf5.ipynb

      
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                betolink
                / cloud-optimized-hdf5.ipynb
            
            
              Created
              January 30, 2024 20:33
            
              
                cloud optimized HDF5
              
          
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## 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.

  
## index.html
<!doctype html>
<html lang="fr">
  <head>
    <meta charset="utf-8" />
    <meta name="viewport" content="width=device-width,initial-scale=1" />
    <meta name="color-scheme" content="light dark" />
    <link
      rel="icon"
      href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 64 64%22><circle cx=%2232%22 cy=%2232%22 r=%2230%22 fill=%22%235b7fe5%22/><circle cx=%2224%22 cy=%2228%22 r=%225%22/><circle cx=%2240%22 cy=%2228%22 r=%225%22/></svg>"
    />

## java_keytool_cheat_sheet.md

      
              1 file
            
          
              33 forks
            
          
                8 comments
              
            
              96 stars
            
          
                Hakky54
                / java_keytool_cheat_sheet.md
            
            
              Last active
              August 12, 2026 17:30
            
              
                Keytool Cheat Sheet
              
          
    Keytool CheatSheet 🔐

Some history

This cheat sheet came into life when I started working on a tutorial of setting up one way tls and two way tls, which can be found here: GitHub - Mutual TLS SSL
Creation and importing

Generate a Java keystore and key pair
keytool -genkeypair -keyalg RSA -keysize 2048 -keystore keystore.jks -alias server -validity 3650
	## Workflow Orchestration

	### 1. Plan Node Default

	* Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions).
	* If something goes sideways, STOP and re-plan immediately—don't keep pushing.
	* Use plan mode for verification steps, not just building.
	* Write detailed specs upfront to reduce ambiguity.

	### 2. Subagent Strategy
	import re


	strings = set()

	with open('texts.txt', mode='r', encoding='utf-8') as file_input:
	content = file_input.read()
	regExStr = r'^\s\d string title = "(?:tooltip\d+\|Name\|Dialogue Text)"\n\s\d string value = "((?!(START\|input\|\w+\(\)\|\!\(\w+\(\)\))).+)"$'
	compiled = re.compile(regExStr, re.MULTILINE)
	matched = compiled.finditer(content)
	<!doctype html>
	<html lang="fr">
	<head>
	<meta charset="utf-8" />
	<meta name="viewport" content="width=device-width,initial-scale=1" />
	<meta name="color-scheme" content="light dark" />
	<link
	rel="icon"
	href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 64 64%22><circle cx=%2232%22 cy=%2232%22 r=%2230%22 fill=%22%235b7fe5%22/><circle cx=%2224%22 cy=%2228%22 r=%225%22/><circle cx=%2240%22 cy=%2228%22 r=%225%22/></svg>"
	/>