axiom-realitykit

charleswiltgen/axiom · updated May 18, 2026

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$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-realitykit
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summary

Purpose: Build 3D content, AR experiences, and spatial computing apps using RealityKit's Entity-Component-System architecture

  • iOS Version: iOS 13+ (base), iOS 18+ (RealityView on iOS), visionOS 1.0+
  • Xcode: Xcode 15+
skill.md

RealityKit Development Guide

Purpose: Build 3D content, AR experiences, and spatial computing apps using RealityKit's Entity-Component-System architecture iOS Version: iOS 13+ (base), iOS 18+ (RealityView on iOS), visionOS 1.0+ Xcode: Xcode 15+

When to Use This Skill

Use this skill when:

  • Building any 3D experience (AR, games, visualization, spatial computing)
  • Creating SwiftUI apps with 3D content (RealityView, Model3D)
  • Implementing AR with anchors (world, image, face, body tracking)
  • Working with Entity-Component-System (ECS) architecture
  • Setting up physics, collisions, or spatial interactions
  • Building multiplayer or shared AR experiences
  • Migrating from SceneKit to RealityKit
  • Targeting visionOS

Do NOT use this skill for:

  • SceneKit maintenance (use axiom-scenekit)
  • 2D games (use axiom-spritekit)
  • Metal shader programming (use axiom-metal-migration-ref)
  • Pure GPU compute (use Metal directly)

1. Mental Model: ECS vs Scene Graph

Scene Graph (SceneKit)

In SceneKit, nodes own their properties. A node IS a renderable, collidable, animated thing.

Entity-Component-System (RealityKit)

In RealityKit, entities are empty containers. Components add data. Systems process that data.

Entity (identity + hierarchy)
  ├── TransformComponent (position, rotation, scale)
  ├── ModelComponent (mesh + materials)
  ├── CollisionComponent (collision shapes)
  ├── PhysicsBodyComponent (mass, mode)
  └── [YourCustomComponent] (game-specific data)

System (processes entities with specific components each frame)

Why ECS matters:

  • Composition over inheritance: Combine any components on any entity
  • Data-oriented: Systems process arrays of components efficiently
  • Decoupled logic: Systems don't know about each other
  • Testable: Components are pure data, Systems are pure logic

The ECS Mental Shift

Scene Graph Thinking ECS Thinking
"The player node moves" "The movement system processes entities with MovementComponent"
"Add a method to the node subclass" "Add a component, create a system"
"Override update(_:) in the node" "Register a System that queries for components"
"The node knows its health" "HealthComponent holds data, DamageSystem processes it"

2. Entity Hierarchy

Creating Entities

// Empty entity
let entity = Entity()
entity.name = "player"

// Entity with components
let entity = Entity()
entity.components[ModelComponent.self] = ModelComponent(
    mesh: .generateBox(size: 0.1),
    materials: [SimpleMaterial(color: .blue, isMetallic: false)]
)

// ModelEntity convenience (has ModelComponent built in)
let box = ModelEntity(
    mesh: .generateBox(size: 0.1),
    materials: [SimpleMaterial(color: .red, isMetallic: true)]
)

Hierarchy Management

// Parent-child
parent.addChild(child)
child.removeFromParent()

// Find entities
let found = root.findEntity(named: "player")

// Enumerate
for child in entity.children {
    // Process children
}

// Clone
let clone = entity.clone(recursive: true)

Transform

// Local transform (relative to parent)
entity.position = SIMD3<Float>(0, 1, 0)
entity.orientation = simd_quatf(angle: .pi / 4, axis: SIMD3(0, 1, 0))
entity.scale = SIMD3<Float>(repeating: 2.0)

// World-space queries
let worldPos = entity.position(relativeTo: nil)
let worldTransform = entity.transform(relativeTo: nil)

// Set world-space transform
entity.setPosition(SIMD3(1, 0, 0), relativeTo: nil)

// Look at a point
entity.look(at: targetPosition, from: entity.position, relativeTo: nil)

3. Components

Built-in Components

Component Purpose
Transform Position, rotation, scale
ModelComponent Mesh geometry + materials
CollisionComponent Collision shapes for physics and interaction
PhysicsBodyComponent Mass, physics mode (dynamic/static/kinematic)
PhysicsMotionComponent Linear and angular velocity
AnchoringComponent AR anchor attachment
SynchronizationComponent Multiplayer sync
PerspectiveCameraComponent Camera settings
DirectionalLightComponent Directional light
PointLightComponent Point light
SpotLightComponent Spot light
CharacterControllerComponent Character physics controller
AudioMixGroupsComponent Audio mixing
SpatialAudioComponent 3D positional audio
AmbientAudioComponent Non-positional audio
ChannelAudioComponent Multi-channel audio
OpacityComponent Entity transparency
GroundingShadowComponent Contact shadow
InputTargetComponent Gesture input (visionOS)
HoverEffectComponent Hover highlight (visionOS)
AccessibilityComponent VoiceOver support

Custom Components

struct HealthComponent: Component {
    var current: Int
    var maximum: Int

    var percentage: Float {
        Float(current) / Float(maximum)
    }
}

// Register before use (typically in app init)
HealthComponent.registerComponent()

// Attach to entity
entity.components[HealthComponent.self] = HealthComponent(current: 100, maximum: 100)

// Read
if let health = entity.components[HealthComponent.self] {
    print(health.current)
}

// Modify
entity.components[HealthComponent.self]?.current -= 10

Component Lifecycle

Components are value types (structs). When you read a component, modify it, and write it back, you're replacing the entire component:

// Read-modify-write pattern
var health = entity.components[HealthComponent.self]!
health.current -= damage
entity.components[HealthComponent.self] = health

Anti-pattern: Holding a reference to a component and expecting mutations to propagate. Components are copied on read.


4. Systems

System Protocol

struct DamageSystem: System {
    // Define which components this system needs
    static let query = EntityQuery(where: .has(HealthComponent.self))

    init(scene: RealityKit.Scene) {
        // One-time setup
    }

    func update(context: SceneUpdateContext) {
        for entity in context.entities(matching: Self.query,
                                        updatingSystemWhen: .rendering) {
            var health = entity.components[HealthComponent.self]!
            if health
how to use axiom-realitykit

How to use axiom-realitykit 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 axiom-realitykit
2

Execute installation command

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

$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-realitykit

The skills CLI fetches axiom-realitykit from GitHub repository charleswiltgen/axiom 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/axiom-realitykit

Reload or restart Cursor to activate axiom-realitykit. Access the skill through slash commands (e.g., /axiom-realitykit) 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.

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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)
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general reviews

Ratings

4.855 reviews
  • Alexander Agarwal· Dec 28, 2024

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

  • Ganesh Mohane· Dec 24, 2024

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

  • Advait Torres· Dec 20, 2024

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

  • Meera Chawla· Dec 20, 2024

    I recommend axiom-realitykit for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Anika Sharma· Dec 8, 2024

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

  • Charlotte Flores· Nov 27, 2024

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

  • Soo Brown· Nov 15, 2024

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

  • Soo Taylor· Nov 11, 2024

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

  • Min Martin· Nov 11, 2024

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

  • Alexander Mensah· Oct 18, 2024

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

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