An AI agent skill that identifies hardware QR codes to track the last known geographical location of smart devices using IMEI data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install gnss-tracker
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 gnss-tracker 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 GNSS Device Tracker?
The GNSS Device Tracker is a specialized technical utility designed for the Openclaw Skills ecosystem. It enables AI agents to bridge the gap between physical hardware and digital location tracking by processing images of device QR codes or raw IMEI numbers. By automating the lookup of Global Navigation Satellite System (GNSS) coordinates and human-readable addresses, this skill provides developers with a seamless way to integrate hardware asset tracking into their agentic workflows.
GNSS Device Tracker Use Cases
- Identifying smart devices and their technical metadata from photos of physical QR codes.
- Retrieving the last known geographical location of an asset using its unique IMEI number.
- Automating device inventory audits by scanning hardware labels and logging location data.
- Streamlining technical support workflows by instantly mapping device IDs to their physical locations.
How GNSS Device Tracker Works
- The AI agent receives an input, such as an image containing a hardware QR code or a text-based IMEI query.
- If an image is provided, the skill utilizes zbarimg to decode the QR content and parse the device information fields.
- The skill extracts the specific IMEI identifier from the decoded data.
- A Python-based request is sent to the GNSS tracking API to fetch the latest location record.
- The system parses the JSON response to extract the human-readable address and the precise record timestamp.
- The agent returns a formatted report to the user detailing the device's last known position.
GNSS Device Tracker Setup
To integrate this capability into your Openclaw Skills environment, ensure you have the necessary dependencies installed:
# Install Python dependencies for API communication
pip install requests
# Install system-level tools for QR code recognition
sudo apt-get install zbar-tools
Ensure the scripts/query_gnss.py script is located in your skill's executable path.
GNSS Device Tracker Data Schema & Taxonomy
The skill processes and returns data based on the following schema to ensure compatibility across different Openclaw Skills implementations:
| Attribute | Description | Data Type |
|---|---|---|
| imei | The unique International Mobile Equipment Identity extracted from the device | String |
| record_time | The UTC timestamp of the device's last reported location | String |
| address | The human-readable physical address (Province, City, District, Street) | String |
| status | Indicates the success or failure of the location query | String |
| raw | The full metadata payload from the tracking server for deep analysis | JSON |
GNSS Device Tracker Advanced Features
- Robust QR Recognition: Utilizes zbarimg for high-accuracy barcode and QR decoding from camera-captured images.
- Automated Field Extraction: Specifically targets dev_info.imei structures within complex hardware QR payloads.
- Real-time API Integration: Directly interfaces with IWOWN GNSS services for up-to-the-minute tracking data.
- Error Handling: Intelligent detection of missing location records with user-friendly error reporting.
SKILL.md
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