MaaAssistantArknights/MaaAssistantArknights
Feb 2025 – Aug 2025
2 Months active
Languages Used
BinaryC++Python
Technical Skills
Emulator ManagementImage ProcessingOCRPerformance OptimizationTask AutomationBug Fixes
Tsukiyowu
PROFILE
Tsukiyowu
During their work on the MaaAssistantArknights repository, this developer focused on automation and data reliability within emulator-based workflows. They delivered an auto-close feature for Google Suite windows at task initiation, reducing background resource usage and improving cross-environment stability. Using C++ and Python, they enhanced OCR-driven popup handling by introducing new image templates, which improved confirmation dialog recognition for international servers. Additionally, they addressed a field identification bug affecting Sakaz-related data, implementing a minimal-risk patch that improved data parsing and display accuracy. Their contributions demonstrated careful bug isolation, performance optimization, and a methodical approach to task automation and image processing.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
3Total
Bugs
2
Commits
3
Features
1
Lines of code
22
Activity Months2
Your Network
41 people
Work History
August 2025
1 Commits
Aug 1, 2025Month: 2025-08. Focused on data reliability and field identification improvements in MaaAssistantArknights. No new user-facing features released this month; primary work was targeted bug fixing to improve data parsing and display for Sakaz-related fields. Key accomplishment was delivering a minimal-risk patch that corrected a specific identification problem, with traceability to issue #13691. Key deliverables: - Targeted bug fix addressing field recognition for the '萨卡兹肉鸽' data points, improving data parsing and display accuracy. - Single, well-scoped commit ensuring low risk and straightforward review (commit 6e6ca1ef7d2293a502103119d79b3a605d8ea99c). - Improved data integrity for Sakaz-related fields, benefiting downstream analytics and user experience. Impact: - Enhanced trust in data presented to users, reduced parsing/display errors, and smoother operational workflows for users relying on accurate field identification. Technologies/Skills demonstrated: - Targeted bug isolation and minimal-change patching - Traceability through issue #13691 and commit-based documentation - Data parsing and field identification robustness
1 Commits
Aug 1, 2025Month: 2025-08. Focused on data reliability and field identification improvements in MaaAssistantArknights. No new user-facing features released this month; primary work was targeted bug fixing to improve data parsing and display for Sakaz-related fields. Key accomplishment was delivering a minimal-risk patch that corrected a specific identification problem, with traceability to issue #13691. Key deliverables: - Targeted bug fix addressing field recognition for the '萨卡兹肉鸽' data points, improving data parsing and display accuracy. - Single, well-scoped commit ensuring low risk and straightforward review (commit 6e6ca1ef7d2293a502103119d79b3a605d8ea99c). - Improved data integrity for Sakaz-related fields, benefiting downstream analytics and user experience. Impact: - Enhanced trust in data presented to users, reduced parsing/display errors, and smoother operational workflows for users relying on accurate field identification. Technologies/Skills demonstrated: - Targeted bug isolation and minimal-change patching - Traceability through issue #13691 and commit-based documentation - Data parsing and field identification robustness
August 2025
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 — MaaAssistantArknights project. Focused on automation improvements to task initiation and UI reliability, delivering two core items that reduce resource usage and improve cross-environment stability for automated workflows.
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 — MaaAssistantArknights project. Focused on automation improvements to task initiation and UI reliability, delivering two core items that reduce resource usage and improve cross-environment stability for automated workflows.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture60.0%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
BinaryC++Python
Technical Skills
Bug FixesEmulator ManagementImage ProcessingOCRPerformance OptimizationTask Automation
Repositories Contributed To
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