AdbAutoPlayer/AdbAutoPlayer
Feb 2026 – Feb 2026
1 Month active
Languages Used
Python
Technical Skills
AutomationGame DevelopmentImage ProcessingPythonPython scriptingUI automation
Wong Jun Zhi
PROFILE
Wong Jun Zhi
During February 2026, Wong developed automation enhancements for the AdbAutoPlayer repository, focusing on the Homestead Orders Helper feature for the AFK Journey game. Leveraging Python, image processing, and UI automation, Wong engineered a mixin that automates crafting and selling orders, reducing manual intervention and streamlining order fulfillment. The solution incorporated template-driven pipelines and OCR-based tracking to monitor crafting requests and stock levels, improving both accuracy and throughput. No major bugs were reported, indicating a stable implementation. Wong’s work established a scalable automation foundation, demonstrating depth in automation design and effective integration of image processing within game development workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
496
Activity Months1
Your Network
7 people
Work History
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 - AdbAutoPlayer/AdbAutoPlayer: key automation and OCR tracking enhancements focusing on Homestead Orders Helper. Delivered an automation mixin to streamline AFK Journey crafting and selling orders, supported by templates, refined crafting/selling pipelines, and OCR-based tracking of requests and stock. No major bugs reported; stability improvements to automation workflow were implemented. The work reduces manual effort, speeds up order fulfillment, and enhances stock visibility, establishing a scalable automation foundation.
2 Commits • 1 Features
Feb 1, 2026February 2026 - AdbAutoPlayer/AdbAutoPlayer: key automation and OCR tracking enhancements focusing on Homestead Orders Helper. Delivered an automation mixin to streamline AFK Journey crafting and selling orders, supported by templates, refined crafting/selling pipelines, and OCR-based tracking of requests and stock. No major bugs reported; stability improvements to automation workflow were implemented. The work reduces manual effort, speeds up order fulfillment, and enhances stock visibility, establishing a scalable automation foundation.
February 2026
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
AutomationGame DevelopmentImage ProcessingPythonPython scriptingUI automationgame automation
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