ankitects/anki
Nov 2024 – Apr 2026
5 Months active
Languages Used
RustTypeScriptPython
Technical Skills
Data VisualizationFrontend DevelopmentGraphing LibrariesAlgorithm OptimizationBackend DevelopmentAlgorithm Design
Jake Probst
PROFILE
Jake Probst
Worked on the ankitects/anki repository, delivering features and fixes that enhanced scheduling, data visualization, and daily workflow reliability. Developed improvements to the Future Due Graph, integrating backlog data and refining filtering logic for accurate task visualization using TypeScript and graphing libraries. Addressed scheduling fairness by optimizing the load balancer in Rust, introducing nuanced algorithms for easy-day distribution and sibling card balancing. Implemented a Day Change Hook API in Python to signal daily transitions, supporting downstream analytics and plugin workflows. The work demonstrated a methodical approach to backend and frontend development, emphasizing maintainability, clear commit traceability, and user-focused problem solving.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
5Total
Bugs
1
Commits
5
Features
4
Lines of code
283
Activity Months5
Work History
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for ankitects/anki: Delivered a Load Balancer Scheduling Enhancement to improve the distribution of sibling cards across review days by introducing a weighting system. The change expands balancing logic to consider siblings across presets, addressing a previous limitation and reducing clustering during sessions. This results in a more even daily workload, improved review efficiency, and a smoother learning curve for users.
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for ankitects/anki: Delivered a Load Balancer Scheduling Enhancement to improve the distribution of sibling cards across review days by introducing a weighting system. The change expands balancing logic to consider siblings across presets, addressing a previous limitation and reducing clustering during sessions. This results in a more even daily workload, improved review efficiency, and a smoother learning curve for users.
April 2026
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for ankitects/anki focused on delivering a reliable Day Change Hook API (day_did_change) to signal daily transitions across the application. Implemented in main.py by comparing the current day's cutoff with the previous day's cutoff to trigger day-change events for downstream components, plugins, and scheduling. This work improves daily workflow reliability, analytics accuracy, and sets groundwork for future day-bound features.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for ankitects/anki focused on delivering a reliable Day Change Hook API (day_did_change) to signal daily transitions across the application. Implemented in main.py by comparing the current day's cutoff with the previous day's cutoff to trigger day-change events for downstream components, plugins, and scheduling. This work improves daily workflow reliability, analytics accuracy, and sets groundwork for future day-bound features.
January 2025
1 Commits • 1 Features
Jan 1, 2025Monthly summary for 2025-01 (ankitects/anki): Delivered enhanced easy-day scheduling with EasyDay levels by refactoring the scheduler and updating the load balancer to honor user-defined easy-day percentages. This work introduces an EasyDay enum (Minimum, Reduced, Normal) and enables nuanced scheduling and better alignment with study patterns. No major bugs fixed this month. This foundation strengthens personalization, user engagement, and future analytics. Technologies demonstrated include scheduler architecture refactor, enum design, and load-balancer aware scheduling, with full commit traceability.
1 Commits • 1 Features
Jan 1, 2025Monthly summary for 2025-01 (ankitects/anki): Delivered enhanced easy-day scheduling with EasyDay levels by refactoring the scheduler and updating the load balancer to honor user-defined easy-day percentages. This work introduces an EasyDay enum (Minimum, Reduced, Normal) and enables nuanced scheduling and better alignment with study patterns. No major bugs fixed this month. This foundation strengthens personalization, user engagement, and future analytics. Technologies demonstrated include scheduler architecture refactor, enum design, and load-balancer aware scheduling, with full commit traceability.
January 2025
December 2024
1 Commits
Dec 1, 2024December 2024 monthly summary for ankitects/anki focused on stabilizing the scheduling subsystem and improving fairness in graduate distribution. Delivered a targeted bug fix to the Load Balancer Scheduling logic and reinforced the team's ability to triage, implement, and review critical fixes with minimal risk to production.
December 2024
1 Commits
Dec 1, 2024December 2024 monthly summary for ankitects/anki focused on stabilizing the scheduling subsystem and improving fairness in graduate distribution. Delivered a targeted bug fix to the Load Balancer Scheduling logic and reinforced the team's ability to triage, implement, and review critical fixes with minimal risk to production.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 focused on delivering a high-value feature to improve task visualization and planning. Key feature delivered: Future Due Graph enhancements that include backlog cards and improved filtering to exclude buried cards, ensuring the graph accurately represents due cards including backlog data. The work is captured by commit 487b38b06c016310ecf78475a0a94db5d29f4fdb with the message 'include backlog cards in today in future due graph (#3379)'. There were no notable bug fixes recorded this month; the emphasis was on feature delivery and reliability of the visualization. Overall impact: users gain a more complete and reliable view of upcoming work, enabling better planning and prioritization across tasks and backlog. Technologies/skills demonstrated: data filtering and graph data modeling, backlog data integration, version control discipline, and clear, traceable change delivery.
1 Commits • 1 Features
Nov 1, 2024November 2024 focused on delivering a high-value feature to improve task visualization and planning. Key feature delivered: Future Due Graph enhancements that include backlog cards and improved filtering to exclude buried cards, ensuring the graph accurately represents due cards including backlog data. The work is captured by commit 487b38b06c016310ecf78475a0a94db5d29f4fdb with the message 'include backlog cards in today in future due graph (#3379)'. There were no notable bug fixes recorded this month; the emphasis was on feature delivery and reliability of the visualization. Overall impact: users gain a more complete and reliable view of upcoming work, enabling better planning and prioritization across tasks and backlog. Technologies/skills demonstrated: data filtering and graph data modeling, backlog data integration, version control discipline, and clear, traceable change delivery.
November 2024
Activity
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Quality Metrics
Correctness88.0%
Maintainability84.0%
Architecture84.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonRustTypeScript
Technical Skills
API DevelopmentAlgorithm DesignAlgorithm OptimizationBackend DevelopmentData VisualizationFrontend DevelopmentGraphing LibrariesRustRust ProgrammingSoftware Engineeringback end development
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