
Charles Carignan developed and enhanced features for the 2dos/DK64-Randomizer repository, focusing on character model randomization and asset pipeline stability. He implemented data-driven systems for Krusha cosmetic variations, integrating dynamic color logic and accessibility considerations using C and Python. His work included deduplicating assets to resolve build inconsistencies, refining patch integration, and expanding UI controls for model selection. Charles also introduced mode-based settings and improved user guidance through updated tooltips and documentation. By leveraging skills in Python scripting, UI/UX design, and game development, he delivered maintainable solutions that improved customization, reliability, and user onboarding within a three-month period.

December 2025 monthly performance summary for 2dos/DK64-Randomizer. Delivered new customization options and clarified user guidance to improve decision-making and onboarding, while maintaining stability of the randomizer configuration. Key outcomes include a Krusha character model addition with mode-based settings, odds tuning, and improved tooltips and documentation. These changes drive engagement by expanding options and reducing user confusion.
December 2025 monthly performance summary for 2dos/DK64-Randomizer. Delivered new customization options and clarified user guidance to improve decision-making and onboarding, while maintaining stability of the randomizer configuration. Key outcomes include a Krusha character model addition with mode-based settings, odds tuning, and improved tooltips and documentation. These changes drive engagement by expanding options and reducing user confusion.
In November 2025, delivered the Kong Model Randomization feature for the 2dos/DK64-Randomizer, introducing configurable Kong character model randomization with a new mode 'Sometimes One', UI controls, and integrated pre-run commands. The work includes enhancements to the UI selector, expanded Krusha randomization options, and code quality improvements through linting and cleanup.
In November 2025, delivered the Kong Model Randomization feature for the 2dos/DK64-Randomizer, introducing configurable Kong character model randomization with a new mode 'Sometimes One', UI controls, and integrated pre-run commands. The work includes enhancements to the UI selector, expanded Krusha randomization options, and code quality improvements through linting and cleanup.
December 2024 summary for 2dos/DK64-Randomizer focused on delivering a major feature set for Krusha cosmetic variations, stabilizing builds with asset deduplication and patch maintenance, and performing housekeeping improvements to ensure maintainability and reliability of the asset pipeline and patch integration. Key outcomes include: a data-driven, color-aware Krusha asset system with dynamic processing, reduced build-time inconsistencies due to deduplicated assets, and a streamlined patch workflow for shrink patches (BPS) integrated with the build system.
December 2024 summary for 2dos/DK64-Randomizer focused on delivering a major feature set for Krusha cosmetic variations, stabilizing builds with asset deduplication and patch maintenance, and performing housekeeping improvements to ensure maintainability and reliability of the asset pipeline and patch integration. Key outcomes include: a data-driven, color-aware Krusha asset system with dynamic processing, reduced build-time inconsistencies due to deduplicated assets, and a streamlined patch workflow for shrink patches (BPS) integrated with the build system.
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