realitykit-ar

dpearson2699/swift-ios-skills · updated Apr 26, 2026

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$npx skills add https://github.com/dpearson2699/swift-ios-skills --skill realitykit-ar
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summary

Build AR experiences on iOS using RealityKit for rendering and ARKit for world

  • tracking. Covers RealityView, entity management, raycasting, scene
  • understanding, and gesture-based interactions. Targets Swift 6.2 / iOS 26+.
skill.md

RealityKit + ARKit

Build AR experiences on iOS using RealityKit for rendering and ARKit for world tracking. Covers RealityView, entity management, raycasting, scene understanding, and gesture-based interactions. Targets Swift 6.2 / iOS 26+.

Contents

Setup

Project Configuration

  1. Add NSCameraUsageDescription to Info.plist
  2. For iOS, RealityKit uses the device camera by default via RealityViewCameraContent (iOS 18+, macOS 15+)
  3. No additional capabilities required for basic AR on iOS

Device Requirements

AR features require devices with an A9 chip or later. Always verify support before presenting AR UI.

import ARKit

guard ARWorldTrackingConfiguration.isSupported else {
    showUnsupportedDeviceMessage()
    return
}

Key Types

Type Platform Role
RealityView iOS 18+, visionOS 1+ SwiftUI view that hosts RealityKit content
RealityViewCameraContent iOS 18+, macOS 15+ Content displayed through the device camera
Entity All Base class for all scene objects
ModelEntity All Entity with a visible 3D model
AnchorEntity All Tethers entities to a real-world anchor

RealityView Basics

RealityView is the SwiftUI entry point for RealityKit. On iOS, it provides RealityViewCameraContent which renders through the device camera for AR.

import SwiftUI
import RealityKit

struct ARExperienceView: View {
    var body: some View {
        RealityView { content in
            // content is RealityViewCameraContent on iOS
            let sphere = ModelEntity(
                mesh: .generateSphere(radius: 0.05),
                materials: [SimpleMaterial(
                    color: .blue,
                    isMetallic: true
                )]
            )
            sphere.position = [0, 0, -0.5]  // 50cm in front of camera
            content.add(sphere)
        }
    }
}

Make and Update Pattern

Use the update closure to respond to SwiftUI state changes:

struct PlacementView: View {
    @State private var modelColor: UIColor = .red

    var body: some View {
        RealityView { content in
            let box = ModelEntity(
                mesh: .generateBox(size: 0.1),
                materials: [SimpleMaterial(
                    color: .red,
                    isMetallic: false
                )]
            )
            box.name = "colorBox"
            box.position = [0, 0, -0.5]
            content.add(box)
        } update: { content in
            if let box = content.entities.first(
                where: { $0.name == "colorBox" }
            ) as? ModelEntity {
                box.model?.materials = [SimpleMaterial(
                    color: modelColor,
                    isMetallic: false
                )]
            }
        }

        Button("Change Color") {
            modelColor = modelColor == .red ? .green : .red
        }
    }
}

Loading and Creating Entities

Loading from USDZ Files

Load 3D models asynchronously to avoid blocking the main thread:

RealityView { content in
    if let robot = try? await ModelEntity(named: "robot") {
        robot.position = [0, -0.2, -0.8]
        robot.scale = [0.01, 0.01, 0.01]
        content.add(robot)
    }
}

Programmatic Mesh Generation

// Box
let box = ModelEntity(
    mesh: .generateBox(size: [0.1, 0.2, 0.1], cornerRadius: 0.005),
    materials: [SimpleMaterial(color: .gray, isMetallic: true)]
)

// Sphere
let sphere = ModelEntity(
    mesh: .generateSphere(radius: 0.05),
    materials: [SimpleMaterial(color: .blue, roughness: 0.2, isMetallic: true)]
)

// Plane
let plane = ModelEntity(
    mesh: .generatePlane(width: 0.3, depth: 0.3),
    materials: [SimpleMaterial(color: .green, isMetallic: false)]
)

Adding Components

Entities use an ECS (Entity Component System) architecture. Add components to give entities behavior:

let box = ModelEntity(
    mesh: .generateBox(size: 0.1),
    materials: [SimpleMaterial(color: .red, isMetallic: false)]
)

// Make it respond to physics
box.components.set(PhysicsBodyComponent(
    massProperties: .default,
    material: .default,
    mode: .dynamic
))

// Add collision shape for interaction
box.components.set(CollisionComponent(
    shapes: [.generateBox(size: [0.1, 0.1, 0.1])]
))
how to use realitykit-ar

How to use realitykit-ar on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add realitykit-ar
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/dpearson2699/swift-ios-skills --skill realitykit-ar

The skills CLI fetches realitykit-ar from GitHub repository dpearson2699/swift-ios-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/realitykit-ar

Reload or restart Cursor to activate realitykit-ar. Access the skill through slash commands (e.g., /realitykit-ar) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.760 reviews
  • James Jain· Dec 28, 2024

    Keeps context tight: realitykit-ar is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ishan Mehta· Dec 28, 2024

    realitykit-ar fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Charlotte Smith· Dec 20, 2024

    Solid pick for teams standardizing on skills: realitykit-ar is focused, and the summary matches what you get after install.

  • Liam Bhatia· Nov 19, 2024

    Registry listing for realitykit-ar matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ira Jain· Nov 19, 2024

    realitykit-ar is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Yash Thakker· Nov 11, 2024

    realitykit-ar reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Alexander Huang· Nov 11, 2024

    realitykit-ar has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Mei Rao· Oct 10, 2024

    Useful defaults in realitykit-ar — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diya Anderson· Oct 10, 2024

    Solid pick for teams standardizing on skills: realitykit-ar is focused, and the summary matches what you get after install.

  • Dhruvi Jain· Oct 2, 2024

    We added realitykit-ar from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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