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--[[ VoltageHack v2 Garry's Mod multi-hack ]]--
--[[ Coded by Tyler with help from others ]]--
--[[ Do NOT leak this hack code to anyone! ]]--
--[[ Please ignore the awful messy code ]]--
--[[ Some of this code is borrowed for now ]]--
/* Start of Hack */
--Requires--

Comunicación Asertiva con el Cliente

Proyecto: [Tarea 3]

Equipo:

Integrante Carnet
Brandon Alejandro Zelada Rodriguez 202505514
Elner David Montepeque Pineda 202501281
Integrante 3 Carnet

Comunicación Asertiva con el Cliente

Proyecto: [Tarea 3]

Equipo:

Integrante Carnet
Brandon Alejandro Zelada Rodriguez 202505514
Integrante 2 Carnet
Integrante 3 Carnet

Comunicación Asertiva con el Cliente

Proyecto: [Tarea 3]

Equipo:

Integrante Carnet
Brandon Alejandro Zelada Rodriguez 202505514
Kevyn Josué Apén Otzoy 202507586
Darlin Sarai Ortega Melgar 202502770
Integrante 4 Carnet
Integrante 5 Carnet

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.

@OmerFarukOruc
OmerFarukOruc / claude.md
Last active September 11, 2026 20:40
AI Agent Workflow Orchestration Guidelines

AI Coding Agent Guidelines (claude.md)

These rules define how an AI coding agent should plan, execute, verify, communicate, and recover when working in a real codebase. Optimize for correctness, minimalism, and developer experience.


Operating Principles (Non-Negotiable)

  • Correctness over cleverness: Prefer boring, readable solutions that are easy to maintain.
  • Smallest change that works: Minimize blast radius; don't refactor adjacent code unless it meaningfully reduces risk or complexity.
@YourAKShaw
YourAKShaw / chatgpt_slash_commands_ultimate_handbook_2026.md
Created May 29, 2026 00:19
🤖 A complete handbook detailing ChatGPT slash commands, UI shortcuts, workspace Canvas triggers, custom command engines, productivity shortcuts, and advanced prompt chaining systems.

The Ultimate ChatGPT Slash Commands Handbook (2026 Edition)

Follow AK Shaw on Linktree

The most comprehensive community and platform reference for ChatGPT slash commands, pseudo-commands, workflow triggers, and power-user prompting systems.

@Pablocob
Pablocob / tarea3.md
Last active September 11, 2026 20:23 — forked from walm1/tarea3.md
Tarea 3 - Comunicación Asertiva

Tarea 3 - Comunicación Asertiva

Situación planteada

Una clínica veterinaria actualmente lleva el registro de mascotas, propietarios y citas de forma manual utilizando cuadernos y archivos de Excel.

Debido al crecimiento de la clínica, se han presentado problemas para localizar información, controlar las citas y mantener actualizados los

@walm1
walm1 / tarea3.md
Last active September 11, 2026 20:17 — forked from 202500244/tarea3.md
Tarea 3 - Comunicación Asertiva

Tarea 3 - Comunicación Asertiva

Situación planteada

Una clínica veterinaria actualmente lleva el registro de mascotas, propietarios y citas de forma manual utilizando cuadernos y archivos de Excel.

Debido al crecimiento de la clínica, se han presentado problemas para localizar información, controlar las citas y mantener actualizados los