TrainLCD avatar

TrainLCD

Official

@trainlcd · Tokyo, Japan

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34Public Repos
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22Published Skills

TrainLCD project by TinyKitten.

Skills Distribution
DomainDeveloper To...Mobile Performance.. (40%)Visual Regression .. (30%)Release Management (30%)

Agent Skills by TrainLCD

Showing 22 vetted skills indexed across 1 GitHub repositories.

TrainLCDTrainLCD
71

argent-screen-recording

Record iOS simulators and Android devices to h264 mp4 files.

Official
Advanced
TrainLCDTrainLCD
71

argent-metro-debugger

Inspect React Native component trees and console logs via Chrome DevTools Protocol.

Official
Advanced
TrainLCDTrainLCD
71

argent-react-native-optimization

Profile and optimize React Native app rendering, lists, and animations.

Official
Advanced
TrainLCDTrainLCD
71

argent-settings-permissions

Manage iOS simulator and Android device runtime permissions via platform permission stores.

Official
Advanced
TrainLCDTrainLCD
71

argent-react-native-app-workflow

Coordinate React Native app builds, Metro, and simulator debugging.

Official
Advanced
TrainLCDTrainLCD
71

argent-tv-interact

Simulate D-pad remote input and inspect JS runtime on TV platforms.

Official
Advanced
TrainLCDTrainLCD
71

argent-react-native-profiler

Profile React Native Hermes apps for re-render counts and CPU usage.

Official
Advanced
TrainLCDTrainLCD
71

argent-screenshot-diff

Compare baseline and current screenshots to generate visual regression diff reports.

Official
Intermediate
TrainLCDTrainLCD
71

argent-test-ui-flow

Automate end-to-end UI testing and visual regression analysis for iOS and Android mobile apps.

Official
Advanced
TrainLCDTrainLCD
71

argent-ios-simulator-setup

Manage iOS simulator lifecycle and connectivity for automated testing workflows.

Official
Intermediate
TrainLCDTrainLCD
71

argent-create-flow

Record and replay UI interactions as YAML-based automation flows.

Official
Advanced
TrainLCDTrainLCD
71

argent-device-interact

Interact with iOS simulators, Android emulators, and Chromium apps via unified gestures.

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Advanced
TrainLCDTrainLCD
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argent-android-emulator-setup

Boots Android Virtual Devices and configures ADB serials and network for testing workflows.

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Advanced
TrainLCDTrainLCD
71

argent-native-profiler

Profile native CPU hotspots and memory leaks in iOS and Android apps.

Official
Advanced
TrainLCDTrainLCD
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argent-lens

Stage multiple UI design variants on a mobile simulator for visual A/B testing.

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Advanced
TrainLCDTrainLCD
71

finalize-release

Orchestrate GitHub tag creation, release publishing, and master-to-dev branch synchronization.

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Advanced
TrainLCDTrainLCD
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sync-dev-from-master

Automates creation of synchronization pull requests from master to dev branches using gh CLI and git.

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Advanced
TrainLCDTrainLCD
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plan-from-feedback

Fetch and analyze open GitHub issues to generate structured implementation plans.

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Intermediate
TrainLCDTrainLCD
71

publish-release

Create git tags and GitHub Releases for the TrainLCD MobileApp repository.

Official
Intermediate
TrainLCDTrainLCD
71

create-canary-pr

Generate pull requests from dev to canary branches for TrainLCD.

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Advanced
TrainLCDTrainLCD
71

create-pr

Generate GitHub pull requests from branch diffs and commit messages.

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Advanced
TrainLCDTrainLCD
71

create-release-pr

Create production release branches and pull requests for mobile apps.

Official
Advanced

Frequently Asked Questions About TrainLCD

FAQPage Schema
What specific mobile development tasks does TrainLCD enable?

TrainLCD enables mobile developers to profile React Native Hermes performance, conduct visual regression testing via screenshot diffing, manage iOS simulator and Android emulator lifecycles, and orchestrate complex GitHub release branch synchronization.

Which engineering personas benefit most from these capabilities?

Mobile engineers, quality assurance specialists, and release managers focused on React Native ecosystems benefit from these capabilities. The project is specifically designed for teams maintaining high-performance mobile applications requiring consistent visual integrity and streamlined deployment cycles.

What are the primary prerequisites for running TrainLCD?

Users require an environment configured for mobile development, including installed iOS simulators, Android Virtual Devices, and active GitHub repository access. The system relies on standard mobile platform stores and existing git configurations to manage device interactions and repository synchronization.