An expert diagnostic and architectural analysis tool for the EdgeComputing Automatic Ticket System (ATS) gateway and its distributed hardware ecosystem.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install edgecomputing-ats
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install edgecomputing-ats using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is EdgeComputing ATS Analyzer?
The EdgeComputing ATS skill is a specialized technical module designed for AI agents to navigate and interpret the complex C++ codebase of an Automatic Ticket System. It provides deep visibility into a layered architecture that manages a wide array of hardware, including IC card readers, QR scanners, and license plate recognition systems. By utilizing this skill from the Openclaw Skills library, developers can bridge the gap between high-level business logic and low-level device drivers.
This skill is essential for maintaining edge computing gateways that act as the intermediary between physical hardware and cloud platforms. It understands the nuances of multi-protocol communication (MQTT, WebSocket, GB28181) and the device abstraction layers that allow the ATS to interact with over 20 different types of peripherals across serial, CAN bus, and GPIO interfaces.
EdgeComputing ATS Analyzer Use Cases
- Mapping the project structure and architectural dependencies of the EdgeComputing ATS.
- Debugging device communication issues across RS232, RS485, and network protocols.
- Implementing new hardware support by following the existing CATSBaseDevice abstraction patterns.
- Onboarding developers to the ATS robot server and LCD application logic.
- Analyzing uplink/downlink message protocols for cloud and device synchronization.
How EdgeComputing ATS Analyzer Works
- The AI agent scans the local workspace directory at
/home/forlinx/Documents/trae_projects/workspace/EdgeComputing/ats/to index the codebase. - It references core system documentation in the
docs/folder to understand high-level design specifications and algorithms. - The skill identifies the specific hardware layer required, such as
device/ic/for card readers ordevice/plate/for recognition, based on user queries. - It parses C++ class structures like
CNodeServiceto explain how business managers and communication servers interact. - The skill provides actionable compilation steps and protocol structures to assist in development or troubleshooting tasks.
EdgeComputing ATS Analyzer Setup
To integrate this skill into your environment, ensure the ATS project is located in the standard path and use the following commands:
# Navigate to the build directory
cd ats/build-aarch64
# Execute the build script for the aarch64 architecture
./build.sh
Ensure that the Openclaw Skills environment has read access to the project workspace for full architectural indexing.
EdgeComputing ATS Analyzer Data Schema & Taxonomy
The ATS skill organizes information based on a three-tier architectural model:
| Layer | Component Path | Responsibility |
|---|---|---|
| Application | robot/ |
Main service logic and HMI (LCD) apps. |
| Common Libs | common/ |
Utilities for serial/network and device abstractions. |
| Device Drivers | device/ |
Vendor-specific logic for IO, LED, IC, and more. |
Data structures for communication are defined as packed C++ structs, such as ATSCmdHeartonline for health monitoring and ATSCmdCardProvide for hardware actions.
EdgeComputing ATS Analyzer Advanced Features
- Multi-protocol support including MQTT (1883), WebSocket (8081), and GB28181 (5060).
- Device abstraction layer for 20+ device types ensuring uniform interaction regardless of vendor.
- Integrated media handling via
ats_mediafor real-time video capture and encoding. - Granular GPIO and relay control through the
CATSIODeviceclass. - Seamless integration with the Openclaw Skills ecosystem for cross-project code analysis.
SKILL.md
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