
Worked on the SigmaRebase repository, delivering advanced client-side modding and automation modules for Minecraft using Java. Developed and refined combat automation features such as KillAuraOG and JelloAI, integrating reinforcement learning and configurable targeting, blocking, and rotation logic to automate in-game actions. Enhanced performance and reliability through packet manipulation, robust error handling, and cross-version compatibility improvements. Addressed stability and usability by fixing rendering, command-line, and configuration issues, while expanding test coverage for faster iteration. The work demonstrated depth in AI integration, backend development, and game hacking, resulting in maintainable, modular code that improved user experience and streamlined development workflows.
July 2025 performance summary for SigmaRebase (Sigma-Skidder-Team). Focused on delivering reliable BlockFly NCP mode improvements and hardening command usability, resulting in higher gameplay reliability and developer confidence. Key work included enhancing item placement and spoofing logic, addressing spoof flags, and stabilizing the .bind command through robust module name matching. These changes reduce edge-case failures, improve stealth in NCP mode, and streamline configuration workflows.
July 2025 performance summary for SigmaRebase (Sigma-Skidder-Team). Focused on delivering reliable BlockFly NCP mode improvements and hardening command usability, resulting in higher gameplay reliability and developer confidence. Key work included enhancing item placement and spoofing logic, addressing spoof flags, and stabilizing the .bind command through robust module name matching. These changes reduce edge-case failures, improve stealth in NCP mode, and streamline configuration workflows.
June 2025 monthly summary for SigmaRebase: Delivered the KillAuraOG Combat Automation Module with extensive configuration for targeting, blocking, and rotation to automate entity attacks. Ported OGKillAura into KillAuraOG and performed subsequent refactors to improve readability and timing initialization. Fixed multiple errors to stabilize the automation workflow. The work establishes a configurable, maintainable automation foundation, enabling faster iteration and reduced manual intervention for in-game combat automation.
June 2025 monthly summary for SigmaRebase: Delivered the KillAuraOG Combat Automation Module with extensive configuration for targeting, blocking, and rotation to automate entity attacks. Ported OGKillAura into KillAuraOG and performed subsequent refactors to improve readability and timing initialization. Fixed multiple errors to stabilize the automation workflow. The work establishes a configurable, maintainable automation foundation, enabling faster iteration and reduced manual intervention for in-game combat automation.
Month: 2025-05 | SigmaRebase: Key features delivered include JelloAI core system and behavior improvements (V1 implementation, RL integration, rotation improvements, alpha/beta iterations, and accuracy enhancements) and NewAura GCD development with related updates (NewAura GCD, Update NewAura.java) plus test scaffolding. Major bugs fixed include Nametags rendering fix, AltManager stability improvements, default settings persistence, removal of deprecated MovementFix option on Killaura/Blockfly, Aim Y UI alignment fix, and Autosprint GCDFix integration, with rollbacks used to restore a stable baseline. Overall impact: increased AI decision quality, improved stability and UX, and stronger test coverage enabling faster iterations. Technologies/skills demonstrated: reinforcement learning integration, advanced game AI behavior, GCD calculation logic, test scaffolding, code cleanup, and configuration simplification.
Month: 2025-05 | SigmaRebase: Key features delivered include JelloAI core system and behavior improvements (V1 implementation, RL integration, rotation improvements, alpha/beta iterations, and accuracy enhancements) and NewAura GCD development with related updates (NewAura GCD, Update NewAura.java) plus test scaffolding. Major bugs fixed include Nametags rendering fix, AltManager stability improvements, default settings persistence, removal of deprecated MovementFix option on Killaura/Blockfly, Aim Y UI alignment fix, and Autosprint GCDFix integration, with rollbacks used to restore a stable baseline. Overall impact: increased AI decision quality, improved stability and UX, and stronger test coverage enabling faster iterations. Technologies/skills demonstrated: reinforcement learning integration, advanced game AI behavior, GCD calculation logic, test scaffolding, code cleanup, and configuration simplification.
March 2025 summary: Implemented targeted performance and reliability improvements in SigmaRebase. Key features delivered include sprint/timer performance refinements, a three-mode UpdatedNCP speed module, and a reliability-focused ChestStealer refactor. These changes enhance user experience through smoother movement, better on-ground control, and more dependable chest identification, reducing edge cases and run-time errors. The work demonstrates skills in movement/physics tuning, modular design, and robust in-range object detection, with direct business value in stability and user satisfaction.
March 2025 summary: Implemented targeted performance and reliability improvements in SigmaRebase. Key features delivered include sprint/timer performance refinements, a three-mode UpdatedNCP speed module, and a reliability-focused ChestStealer refactor. These changes enhance user experience through smoother movement, better on-ground control, and more dependable chest identification, reducing edge cases and run-time errors. The work demonstrates skills in movement/physics tuning, modular design, and robust in-range object detection, with direct business value in stability and user satisfaction.
February 2025 SigmaRebase monthly summary: Focused on stability, cross-version compatibility, and performance for automated combat/movement tooling. Delivered core feature refinements and extensive bug fixes across packet handling, scaffolding, and rendering to improve reliability and cross-version support. Key outcomes include safer packet processing, smoother scaffolding experiences, and broader client-version compatibility, enabling more reliable deployments and user workflows.
February 2025 SigmaRebase monthly summary: Focused on stability, cross-version compatibility, and performance for automated combat/movement tooling. Delivered core feature refinements and extensive bug fixes across packet handling, scaffolding, and rendering to improve reliability and cross-version support. Key outcomes include safer packet processing, smoother scaffolding experiences, and broader client-version compatibility, enabling more reliable deployments and user workflows.

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