Deploy Swift applications to ARM64 WendyOS edge devices with the wendy CLI.
npx skills add https://github.com/wendylabsinc/claude-skills --skill wendy-wendylabsinc
Please help me install this Agent Skill. Skill: wendy Source: https://github.com/wendylabsinc/claude-skills/tree/main/wendy Command: npx skills add https://github.com/wendylabsinc/claude-skills --skill wendy-wendylabsinc
This Skill simplifies the process of building, deploying, and debugging Swift applications on WendyOS edge devices, streamlining the development workflow for embedded systems.
wendy.json for app settings and entitlements.Use the wendy skill to initialize a new Wendy Lite project.
High-intent search queries and answers about installing and using this skill.
To deploy Swift apps to ARM64 edge devices, you use the wendy CLI to build and push your application directly to target hardware like NVIDIA Jetson or Raspberry Pi. The Skill provides guidance on initializing the project and managing the deployment workflow.
The wendy.json configuration file is used for managing app settings and entitlements for edge computing deployments. It defines permissions for network, GPU, video, audio, and Bluetooth access required by your Swift application on WendyOS devices.
Yes, you can remotely debug Swift code running on embedded systems. The Skill facilitates remote debugging directly on the target ARM64 device, allowing you to troubleshoot your application's behavior on WendyOS edge hardware during development.
You configure hardware entitlements for GPU and Bluetooth access on WendyOS by defining them within the wendy.json configuration file. The Skill provides guidance on setting up common entitlements including network, GPU, video, audio, and Bluetooth permissions.
Yes, this Skill supports deploying Swift computer vision applications to edge devices. A core use case is deploying Swift-based real-time object detection applications to ARM64 hardware like NVIDIA Jetson devices for edge computing scenarios.
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