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
Worked on the AdbAutoPlayer repository to develop the Homestead Orders Helper, an automation feature for the AFK Journey game that streamlines crafting and selling orders. Leveraging Python, image processing, and UI automation, the solution introduced a mixin architecture supported by templates and refined pipelines to automate repetitive in-game tasks. Optical Character Recognition (OCR) was integrated to track crafting requests and stock levels, improving both accuracy and throughput. The work focused on reducing manual intervention, accelerating order fulfillment, and enhancing stock visibility, resulting in a more stable and scalable automation workflow without reported bugs during the development period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
496
Activity Months1
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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
Repositories Contributed To
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