CmdDeck vs Nara Mobile AI Lab

The fastest way to get from a symptom to the command that fixes it. Type "cannot connect to the network" into the search box. A diagnostic flow opens with ping, ipconfig, nslookup and tracert laid out in the order you actually run them. You don't need to remember the command name. ■ Fully offline All 882 commands live on your device. Server rooms with no signal, air-gapped networks, a customer site with the Wi-Fi down. The moments you most need to look up networking are the moments the network is broken. Nothing is transmitted, ever. ■ 75 troubleshooting flows "PC is slow." "Mail not arriving." "Port already in use." "Clock drift." Enter the symptom and get an ordered set of steps, each with the command to run at that step. Less time guessing where the fault is. ■ Search that forgives Type "ipconfog" and it suggests ipconfig. Search by alias, not just by name. Filter chips narrow results to Linux, Windows, Cisco and the rest in one tap. ■ Spotlight Swipe down on your home screen, type "netstat", jump straight to the entry without opening the app. ■ What's inside · 882 commands across 15 platforms Linux 178, Windows 107, PowerShell 89, Kubernetes 53, macOS 52, Git 52, Cisco 48, Cloud 48, SQL 44, Docker 41, Active Directory 40, Microsoft 365 36, Virtualization 36, FortiGate 31, Yamaha 27 · 75 troubleshooting flows · Worked examples and syntax for every command · Destructive commands clearly flagged ■ Premium (one-time purchase) · All 75 troubleshooting flows (2 free) · Unlimited favorites (10 free) · iCloud sync · Personal notes on any command · Export Not a subscription. Buy once, that's it. ■ Privacy No account. No ads. No tracking. The developer receives none of your data. The app is offline, so there is nothing to send. ■ Languages App interface and symptom search: English, Japanese, Spanish, German, French, Portuguese, Simplified Chinese, Traditional Chinese, Korean. Command explanations and flow text: English and Japanese only. ■ Please note Content is reference material. Run commands at your own discretion and risk, ideally in a test environment and after taking backups. Built by an in-house IT engineer who wanted this on his own phone. Feedback is welcome from inside the app.

Nara Mobile AI Lab is a developer-focused test bench for exploring Apple built-in AI capabilities directly on iPhone. The app helps developers, builders, and technical teams understand how on-device AI performs in real app workflows before investing in a larger implementation. For the most accurate test, turn on Airplane Mode before running experiments. This helps verify whether results are coming from the device’s built-in AI capability instead of a cloud service. With Nara Mobile AI Lab, you can test practical AI workflows such as: Speech-to-text with structured JSON extraction Vision and OCR extraction from photos Prompt response testing Mock tool and callback execution User-defined tool function testing LocalKnowledge search testing Object detection using preset Core ML models Image classification using preset Core ML models Prompt to Image using Image Playground Latency, validation, manual scoring, and notes Exporting results for review or project planning The app includes built-in templates and one-time page hints so you can quickly test common developer scenarios without building a full prototype first. You can inspect raw extraction, AI output, validation status, benchmark timing, manual score, and notes. Nara Mobile AI Lab is especially useful for evaluating whether on-device AI is suitable for privacy-focused apps, offline-first workflows, mobile automation, field tools, form extraction, image analysis, local knowledge search, and AI-assisted business software. Core ML Vision Tests Nara Mobile AI Lab includes preset Core ML model tests for object detection and image classification. The current preset models include YOLOv3TinyFP16 for object detection and FastViTMA36F16 for image classification. These tests provide practical developer examples for reviewing on-device model behavior, latency, and output format. Tool Calling Tests The app includes mock tool-calling tests so developers can evaluate whether the Apple Foundation Model chooses the correct function, passes reasonable arguments, and returns a useful result. Write-style actions are mocked for safety, allowing the app to demonstrate tool-calling behavior without performing real external changes. LocalKnowledge Tests The app includes local knowledge search testing so developers can explore how user-defined local information can be used in offline-first AI workflows. Test data stays on the device unless the user manually exports it. Nara Mobile AI Lab is a testing and learning tool. AI output may be incomplete or inaccurate and should always be reviewed by the user.