Kaggle/kaggle-environments
Aug 2025 – Mar 2026
3 Months active
Languages Used
C++JavaScriptPython
Technical Skills
Backend DevelopmentBuild ProcessData VisualizationEnvironment ManagementEnvironment SetupEnvironment Simulation
Kiyota Hidekazu
PROFILE
Kiyota Hidekazu
Worked on the Kaggle/kaggle-environments repository to deliver a playable CABT environment featuring JavaScript rendering and Python game logic, complete with user-facing deck selection and visualization controls. Enhanced the environment’s stability and usability by refining the build process, updating packaging, and improving UI layout for better readability and workflow. Integrated data visualization to enable observation of game states and actions, supporting faster experimentation and easier debugging. Addressed configuration issues by fixing parameter parsing and updating related assets, while upgrading the cg library to support new features. Demonstrated skills in backend and frontend development, environment simulation, and algorithm design throughout the project.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
3
Lines of code
700
Activity Months3
Your Network
23 peopleWork History
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered CABT Environment Visualization and Card Deck Update for Kaggle/kaggle-environments. This release updates the card deck, introduces visualization data for observing game states and actions, and includes a cg library upgrade. Result: enhanced observability, faster iteration cycles, and easier debugging for participants. No major bugs fixed this month. Technologies demonstrated include environment tooling, data visualization integration, library updates, and Git-based collaboration.
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered CABT Environment Visualization and Card Deck Update for Kaggle/kaggle-environments. This release updates the card deck, introduces visualization data for observing game states and actions, and includes a cg library upgrade. Result: enhanced observability, faster iteration cycles, and easier debugging for participants. No major bugs fixed this month. Technologies demonstrated include environment tooling, data visualization integration, library updates, and Git-based collaboration.
March 2026
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Kaggle/kaggle-environments: delivered targeted bug fix and UI layout improvements to enhance stability, usability, and developer experience. Key outcomes include corrected evolvesFrom parameter language and related assets, improved readability and usability of the visualizer and game state display, and cg library updates to support these changes. These efforts reduce configuration errors, speed up experimentation, and improve end-user productivity across environments.
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Kaggle/kaggle-environments: delivered targeted bug fix and UI layout improvements to enhance stability, usability, and developer experience. Key outcomes include corrected evolvesFrom parameter language and related assets, improved readability and usability of the visualizer and game state display, and cg library updates to support these changes. These efforts reduce configuration errors, speed up experimentation, and improve end-user productivity across environments.
August 2025
3 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08: Delivered the CABT Environment in Kaggle/kaggle-environments featuring a playable visual CABT with JavaScript rendering and Python game logic, packaging binaries included for reliable distribution, and a user-facing deck selection UI with visualization controls and validation. Established end-to-end capability for interactive experimentation and deck-based strategy evaluation, laying groundwork for agent planning and competition scenarios.
3 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08: Delivered the CABT Environment in Kaggle/kaggle-environments featuring a playable visual CABT with JavaScript rendering and Python game logic, packaging binaries included for reliable distribution, and a user-facing deck selection UI with visualization controls and validation. Established end-to-end capability for interactive experimentation and deck-based strategy evaluation, laying groundwork for agent planning and competition scenarios.
August 2025
Activity
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Quality Metrics
Correctness76.6%
Maintainability76.6%
Architecture70.0%
Performance66.6%
AI Usage23.4%
Skills & Technologies
Programming Languages
C++JavaScriptPython
Technical Skills
Backend DevelopmentBuild ProcessData VisualizationEnvironment ManagementEnvironment SetupEnvironment SimulationFront End DevelopmentFrontend DevelopmentGame DevelopmentJavaScriptPythonUI/UX Developmentalgorithm designdata visualizationgame development
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