Mockdevice Testing Agent Skill
MockDeviceKit for testing without physical glasses hardware
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/facebook/meta-wearables-dat-ios --skill mockdevice-testingThe instruction itself
12 sections, as written by the authorMockDevice Testing (iOS)
Use MockDeviceKit to test DAT SDK integrations without physical Meta glasses.
MockDeviceKit simulates Meta glasses behavior for development and testing. It provides:
MockDeviceKit— Entry point for creating simulated devicesMockGlasses— Simulated glasses (Ray-Ban Meta, etc.)MockCameraKit— Simulated camera with configurable video feed and photo capture
Setup
Add MWDATMockDevice to your target via Swift Package Manager (it's included in the meta-wearables-dat-ios package).
import MWDATMockDevice
Creating a mock device
import MWDATMockDevice
let mockDeviceKit = MockDeviceKit.shared
mockDeviceKit.enable()
let mockDevice = try mockDeviceKit.pairGlasses(model: .rayBanMeta)
Simulating device states
// Simulate glasses lifecycle
mockDevice.powerOn()
mockDevice.unfold()
mockDevice.don() // Simulate wearing the glasses
// Later...
mockDevice.doff() // Simulate removing
mockDevice.fold()
mockDevice.powerOff()
Configuring permissions
MockDeviceKit provides permissions to control permission behavior without the Meta AI app.
By default, requestPermission() returns .granted. Use set(_:_:) to control checkPermissionStatus() and setRequestResult(_:result:) to control requestPermission() outcomes.
let mockDeviceKit = MockDeviceKit.shared
// Simulate denied camera permission status
mockDeviceKit.permissions.set(.camera, .denied)
// Simulate denied request result (user tapping "deny")
mockDeviceKit.permissions.setRequestResult(.camera, result: .denied)
Setting up mock camera feeds
Video streaming
let camera = mockDevice.services.camera
camera.setCameraFeed(fileURL: videoURL)
Photo capture
let camera = mockDevice.services.camera
camera.setCapturedImage(fileURL: imageURL)
Writing tests with MockDeviceKit
Create a reusable test base class:
import XCTest
import MetaWearablesDAT
@MainActor
class MockDeviceKitTestCase: XCTestCase {
private var mockDevice: MockGlasses?
private var cameraKit: MockCameraKit?
override func setUp() async throws {
try await super.setUp()
MockDeviceKit.shared.enable()
mockDevice = try MockDeviceKit.shared.pairGlasses(model: .rayBanMeta)
cameraKit = mockDevice?.services.camera // mockDevice is MockGlasses? for tearDown nil-ability
}
override func tearDown() async throws {
MockDeviceKit.shared.disable()
mockDevice = nil
cameraKit = nil
try await super.tearDown()
}
}
Using MockDeviceKit in the CameraAccess sample
The CameraAccess sample app includes a Debug menu for MockDeviceKit:
- Tap the Debug icon to open the MockDeviceKit menu
- Tap Pair RayBan Meta to create a simulated device
- Use PowerOn, Unfold, Don to simulate glasses states
- Select video/image files to configure mock camera feeds
- Start streaming to see simulated frames
Supported media formats
| Type | Formats |
|------|---------|
| Video | h.265 (HEVC) |
| Image | JPEG, PNG |
Links
Other skills for the same job
different authors, same section of the catalogue
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when implementing any feature or bugfix, before writing implementation code
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
How to use it
Take facebook/mockdevice-testing from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.