Comprehensive list of rotur (https://rotur.dev) websites and stuff!
This is maintained by @darkdot on Rotur
"Rotur" is often stylized as "rotur" on its pages, while lowercase is widely used, "Rotur" with titlecase was suggested by the founder of the platform name - therefore, we are using it on this document.
warning: Many are vibe coded.
| RAR registration data | |
| WinRAR | |
| Unlimited Company License | |
| UID=4b914fb772c8376bf571 | |
| 6412212250f5711ad072cf351cfa39e2851192daf8a362681bbb1d | |
| cd48da1d14d995f0bbf960fce6cb5ffde62890079861be57638717 | |
| 7131ced835ed65cc743d9777f2ea71a8e32c7e593cf66794343565 | |
| b41bcf56929486b8bcdac33d50ecf773996052598f1f556defffbd | |
| 982fbe71e93df6b6346c37a3890f3c7edc65d7f5455470d13d1190 | |
| 6e6fb824bcf25f155547b5fc41901ad58c0992f570be1cf5608ba9 |
| SQL Server 2017 | |
| ---------------- | |
| Enterprise Core - 6GPYM-VHN83-PHDM2-Q9T2R-KBV83 | |
| Developer - 22222-00000-00000-00000-00000 | |
| Enterprise - TDKQD-PKV44-PJT4N-TCJG2-3YJ6B | |
| Standard - PHDV4-3VJWD-N7JVP-FGPKY-XBV89 | |
| Web - WV79P-7K6YG-T7QFN-M3WHF-37BXC | |
| https://www.teamos-hkrg.com/index.php?threads/microsoft-sql-server-english-2017-rtm-teamos.42103/ |
| =============================================================================== | |
| = W e l c o m e t o t h e V I M T u t o r - Version 1.5 = | |
| =============================================================================== | |
| Vim is a very powerful editor that has many commands, too many to | |
| explain in a tutor such as this. This tutor is designed to describe | |
| enough of the commands that you will be able to easily use Vim as | |
| an all-purpose editor. | |
| The approximate time required to complete the tutor is 25-30 minutes, |
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.
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.
Reconstructed from Danny Postma's talk How I Built My Own AgentOS on Claude's Agent SDK (So You Can Too) (2026). This document is both a product spec for a human and an implementation prompt for an AI coding agent. Build exactly this system. Do not invent features that are not specified here.
Role contracts and prompts in this file are reconstructed from the talk, not his verbatim files. Mark every reconstructed prompt in code comments and docs as such.
| #!/usr/bin/env bash | |
| ################ Description: ################### | |
| # This script will disable all opt-out under | |
| # Ubuntu 22.04 (Codename: Jammy Jellyfish). | |
| # At first the telemetry domains will be resolved | |
| # to the local host and second all telemetry services | |
| # will be removed from the system. | |
| # The following work has a system-wide effect not just |
