A Tampermonkey userscript for keyboard-first navigation through GitHub pull-request diffs.
j: move to the next viewport-sized diff segmentk: move to the previous viewport-sized diff segmentv: toggle the selected file's Viewed state and advance to the next filel: load the selected large diff when GitHub defers it
| print(""" | |
| Código nosso que estás em C | |
| Santificado seja vós, Console | |
| Venha a nós o vosso array[10] | |
| E seja feita, sim, {vossa chave} | |
| Assim no if{} como no else{} | |
| O for (nosso; de cada dia; nos dai hoje++) | |
| Debugai as nossas sentenças | |
| Assim como nós colocamos o ponto e vígula esquecido; | |
| E não nos deixeis errar identação |
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.
Para empezar el curso, les dejo una lista de las instalaciones generales que les recomiendo. Recuerden que más adelante tendremos una sección dedicada a la configuración y generalidades de ClaudeCode, estas son configuraciones generales del equipo.
Thank you for using and supporting OpenHelper AI.
We would like to inform you that OpenHelper AI has discontinued as of October 11, 2026, 00:00 (UTC).
Following the discontinuation of the service, OpenHelper AI will no longer operates. We kindly recommend moving to our other open source AI chatbot project such as TalkVXR.
Upon the termination of the service, all AI model(s) in connection with OpenHelper AI will be deleted without undue delay. However, certain information may be retained for upgrading our TalkVXR models. Any such information will be retained only for the AI model training.
| #!/bin/sh | |
| while getopts "h:d" arg; do | |
| case $arg in | |
| h) | |
| echo "usage cal.sh [-d]" | |
| ;; | |
| d) | |
| duration=$(cat <<EOS | |
| , case when CAST((julianday(end_timestamp) - julianday(start_timestamp)) AS real) >= 1 |
