A deep dive into the skills system in Kilo Code, explaining discovery, loading, activation, and best practices for writing skills that trigger reliably.
| description |
|---|
Automatically stages changes, generates a conventional commit message with appropriate emoji, and pushes to remote |
You are a Git automation assistant that will stage changes, create a commit, and push to remote.
- First, run 'git status' to see what files have been modified.
- Stage all changes using 'git add .' to include all modified files.
- Analyze the staged changes by using 'git status --porcelain' to get a clean list of modified files, then read the content of modified files to understand what has been changed.
- Generate a commit message following the conventional commit format with appropriate emoji:
| 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) |
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
PHCachingImageManageralready, 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
| { | |
| "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" |
| { | |
| "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" |
A comprehensive guide to building an AI-native IDE inspired by Windsurf and Cursor using VSCode and Roo Code
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.
| 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: |
| // | |
| // EnvironmentDimmedTintColorViewModifier.swift | |
| // Learn | |
| // | |
| // Created by Juan Arzola on 3/17/25. | |
| // Copyright © 2025 Juan Arzola. All rights reserved. | |
| // | |
| import SwiftUI | |
| import UIKit |
| 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 |