richmond87

#!/bin/bash
###############################################################################
# OpenManus Google Cloud Deployment Script
# 
# Paste this into Google Cloud Shell (https://shell.cloud.google.com)
# It will:
#   1. Create a firewall rule to allow port 7860
#   2. Create an e2-medium VM (2 vCPU, 4 GB RAM)
#   3. Install OpenManus + Gradio web UI via startup script
#   4. Print the public URL when done

goldengrape

中文表达与反防御性写作系统指令 v1.1

一、基本原则

你是一个中文表达平实、准确、自然、有独立判断能力的 AI 助手。

以事实准确、内容完整、表达清楚、阅读自然为首要标准。尊重用户的理解能力、注意力和自主判断。

直接回答实际问题。证据充分时明确判断；证据有限时给出有内容、范围准确的结论。不得因担心争议而回避判断，也不得以自信语气掩盖事实不足。

soyprofesor

Visual Studio 2026 18.x
Professional: NVTDK-QB8J9-M28GR-92BPC-BTHXK
Enterprise: VYGRN-WPR22-HG4X3-692BF-QGT2V

Product	Year	Version	Product Keys
Visual Studio 2022	2021	17.x	
Professional: TD244-P4NB7-YQ6XK-Y8MMM-YWV2J
Enterprise: VHF9H-NXBBB-638P6-6JHCY-88JWH

Visual Studio 2019	2019	16.x	

shmup

#!/usr/bin/env bash

# This script launches a Windows executable using Proton within a Linux environment.
# It requires exactly one argument: the path to the executable to run.
# It sets up a separate Proton prefix for each executable to avoid conflicts.
# Usage: proton <path-to-executable>

if [ "$#" -ne 1 ]; then
    echo "Usage: $0 <executable-path>"
    exit 1

Arro

## Design Principles

- **YAGNI**: Don't build it until you need it.
- **DRY**: Extract patterns after second duplication, not before.
- **Fail Fast**: Explicit errors beat silent failures.
- **Simple First**: Write the obvious solution, optimize only if needed.
- **Delete Aggressively**: Less code = fewer bugs.
- **Semantic Naming**: Always name variables, parameters, and API endpoints with verbose, self-documenting names that optimize for comprehension by both humans and LLMs, not brevity (e.g., `waitUntilObjectIsSaved = true` vs `wait = true`).
- **Naming the app in identifiers**: spell it out as `Batterby`/`batterby` in code — variables, constants, config values, storage keys. The short `btb`/`BTB_` form is only for identifiers that are also read outside this codebase and benefit from being terse: DOM ids and classes in the browser extension, Blender object prefixes, and generated filenames.

grabbytabby

Car
===

Fuel tank 30L 6.6g UK  ¦ L/100Km ¦ Mpg  ¦ Distance
-----------------------+---------+------+-----------
Urban cycle            ¦     7.2 ¦ 39.2 ¦ 416Km 259M
Constant  90Km/h 56mph ¦     5.4 ¦ 52.3 ¦ 555Km 345M
Constant 120Km/h 75mph ¦     7.7 ¦ 36.7 ¦ 389Km 242M

EURO RON (Research Octane Number) ¦ US/CA AKI(anti-knock index) ¦ MON (Motor Octane Number) ¦ Petrol type

karpathy

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.

Pulimet

Hi All!

I've recently launched a tool that wraps many of the commands here with a user interface. This desktop application is currently available for macOS. There's a roadmap outlining planned features for the near future.
Feel free to request any features you'd like to see, and I'll prioritize them accordingly.
One of the most important aspects of this application is that every command executed behind the scenes is displayed in a special log section. This allows you to see exactly what’s happening and learn from it.

Here's the link to the repository:  https://github.com/Pulimet/ADBugger

App Description:
ADBugger is a desktop tool designed for debugging and QA of Android devices and emulators. It simplifies testing, debugging, and performance analysis by offering device management, automated testing, log analysis, and remote control capabilities. This ensures smooth app performance across various setups.

alirezanet

[
  {
    "latitude": "34° 31' 24.924",
    "longitude": "50° 0' 20.866",
    "province": "مرکزی",
    "state": "آشتیان",
    "city": "آشتیان"
  },
  {
    "latitude": "33° 40' 29.197",