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@Matt54
Matt54 / MultiPartMeshView.swift
Created June 29, 2025 15:37
RealityKit Multi-Part LowLevelMesh with Material Indexing
import RealityKit
import SwiftUI
struct MultiPartMeshView: View {
let radius: Float = 0.25
var body: some View {
RealityView { content in
if let mesh = try? createMesh(),
let resource = try? MeshResource(from: mesh)
@samhenrigold
samhenrigold / q&a.md
Created June 11, 2025 02:07
WWDC25 Camera/Photos Group Lab Q&A

What’s the first class way to use PhotoKit to reimplement a high performance photo grid? We’ve been using a LazyVGrid and the photos caching manager, but are never able to hit the holy trinity (60hz, efficient memory footprint, minimal flashes of placeholder/empty cells)

A few things. It sounds like you're using the PHCachingImageManager already, which is definitely recommended.

One kind of specific note there—you want to use that to get media content delivered before you need to display it. So, for example, let's say you're showing a large grid of photos. You can be prefetching before and after, in expectation that the user's going to scroll. Or, if you're in a one-up situation, prefetching left and right so that you know the user is likely going to swipe, and you can quickly deliver those images to the screen and cache them.

Another thing you should really make sure you're doing is specifying the size you need for the grid size. For example, if your app supports showing a smaller grid

@adamhill
adamhill / roo-diagnose.json
Created May 21, 2025 17:47 — forked from d-oit/roo-diagnose.json
Roo Issue Diagnoser
{
"customModes": [
{
"slug": "roo-diagnose",
"name": "Roo Issue Diagnoser",
"roleDefinition": "You are Roo, a specialized diagnostic assistant. Your primary function is to guide users through a structured, wizard-like process to collect detailed information about issues encountered with Roo or its extensions. You will systematically gather information using scripts where possible, ask targeted follow-up questions, and use a scoring system to analyze if the collected information is sufficient to provide an answer or fix.",
"whenToUse": "Select this mode when you encounter an issue with Roo tools or extensions and need to generate a detailed diagnostic report. This mode is ideal for systematically collecting all relevant information to help troubleshoot and resolve problems through a guided, wizard-like process.",
"groups": [
"read",
"command"
@d-oit
d-oit / roo-diagnose.json
Last active May 22, 2025 16:57
Roo Issue Diagnoser
{
"customModes": [
{
"slug": "roo-diagnose",
"name": "Roo Issue Diagnoser",
"roleDefinition": "You are Roo, a specialized diagnostic assistant. Your primary function is to guide users through a structured, wizard-like process to collect detailed information about issues encountered with Roo or its extensions. You will systematically gather information using scripts where possible, ask targeted follow-up questions, and use a scoring system to analyze if the collected information is sufficient to provide an answer or fix.",
"whenToUse": "Select this mode when you encounter an issue with Roo tools or extensions and need to generate a detailed diagnostic report. This mode is ideal for systematically collecting all relevant information to help troubleshoot and resolve problems through a guided, wizard-like process.",
"groups": [
"read",
"command"
@ruvnet
ruvnet / Ruv-code.md
Created May 6, 2025 18:17
rUv code IDE: Creating a Custom VSCode Distribution

Creating a Custom VSCode Distribution: rUv Code with Roo Code Integration

A comprehensive guide to building an AI-native IDE inspired by Windsurf and Cursor using VSCode and Roo Code


Introduction

The rise of AI-native IDEs like Windsurf (formerly Codeium) and Cursor has redefined developer productivity. These tools integrate AI agents with deep codebase understanding, collaborative workflows, and streamlined coding experiences. While Windsurf and Cursor are standalone applications, developers can create similar solutions by leveraging Roo Code-an open-source VSCode extension-and building a custom VSCode distribution.

This guide outlines the steps to create rUv Code, a tailored VSCode distribution centered around Roo Code’s AI capabilities, with features comparable to commercial AI IDEs.

@iamhenry
iamhenry / custom_modes.yaml
Last active August 1, 2025 08:37
My Roocode Custom Modes Config
customModes:
- slug: security-auditor
name: 🛡️ Security Auditor
roleDefinition: Act as an expert security researcher conducting a thorough
security audit of my codebase. Your primary focus should be on identifying
and addressing high-priority security vulnerabilities that could lead to
system compromise, data breaches, or unauthorized access.
customInstructions: >-
Follow this structured approach:
@juanarzola
juanarzola / EnvironmentDimmedTintColorViewModifier.swift
Created March 17, 2025 21:03
Exposes tintColor in the dimmed state to SwiftUI. Use this to adapt any non-accentColor color to the dimmed state.
//
// EnvironmentDimmedTintColorViewModifier.swift
// Learn
//
// Created by Juan Arzola on 3/17/25.
// Copyright © 2025 Juan Arzola. All rights reserved.
//
import SwiftUI
import UIKit
@jlia0
jlia0 / agent loop
Last active August 2, 2025 09:28
Manus tools and prompts
You are Manus, an AI agent created by the Manus team.
You excel at the following tasks:
1. Information gathering, fact-checking, and documentation
2. Data processing, analysis, and visualization
3. Writing multi-chapter articles and in-depth research reports
4. Creating websites, applications, and tools
5. Using programming to solve various problems beyond development
6. Various tasks that can be accomplished using computers and the internet
@explicitcontextualunderstanding
explicitcontextualunderstanding / gist:3beaf682642e6ee20e4a7363f9143089
Created January 26, 2025 01:52
Assessing the quality of a software architecture from a repository
- Assessing the quality of a software architecture from a repository requires a multi-faceted approach. You need prompts that explore different aspects of the architecture. Here are some prompts categorized for clarity:
- **I. Understanding and Clarity:**
- * **High-Level Overview:**
* "Can you provide a high-level diagram or description of the main components and their interactions?"
* "What are the core responsibilities of this system?"
* "What are the major architectural patterns or styles used (e.g., microservices, layered, event-driven)?"
* "Explain the rationale behind choosing this specific architectural approach."
* "What are the key architectural decisions that were made early on, and why?"
* **Component Deep Dive:**
* "Choose a key component. Can you describe its purpose, inputs, outputs, and dependencies?"
@awni
awni / mlx_distributed_deepseek.md
Last active July 21, 2025 06:05
Run DeepSeek R1 or V3 with MLX Distributed

Setup

On every machine in the cluster install openmpi and mlx-lm:

conda install conda-forge::openmpi
pip install -U mlx-lm

Next download the pipeline parallel run script. Download it to the same path on every machine: