Sigma-Skidder-Team/SigmaRebase
Feb 2025 – Jul 2025
5 Months active
Languages Used
Java
Technical Skills
Backend DevelopmentBug FixClient-Side LogicClient-Side ModdingClient-Side NetworkingClient-Side Programming
StormingMoon
PROFILE
Stormingmoon
Over five months, Storming Moon developed and maintained advanced combat automation, AI integration, and client-side modding features for the SigmaRebase repository. Their work included building configurable modules such as KillAuraOG and JelloAI, implementing reinforcement learning and neural network logic to improve in-game decision-making and combat behavior. Using Java and OpenGL, Storming Moon enhanced cross-version compatibility, optimized packet handling, and improved rendering and event systems. They addressed stability and usability by refactoring legacy modules, expanding test coverage, and resolving critical bugs. This engineering approach resulted in a robust, maintainable codebase that supports reliable automation and streamlined user workflows for game modding.
Overall Statistics
Feature vs Bugs
54%Features
Repository Contributions
70Total
Bugs
16
Commits
70
Features
19
Lines of code
6,685
Activity Months5
Your Network
6 peopleShared Repositories
6
Work History
July 2025
4 Commits • 1 Features
Jul 1, 2025July 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.
4 Commits • 1 Features
Jul 1, 2025July 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
June 2025
2 Commits • 1 Features
Jun 1, 2025June 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
2 Commits • 1 Features
Jun 1, 2025June 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.
May 2025
23 Commits • 5 Features
May 1, 2025Month: 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.
23 Commits • 5 Features
May 1, 2025Month: 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.
May 2025
March 2025
3 Commits • 3 Features
Mar 1, 2025March 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
3 Commits • 3 Features
Mar 1, 2025March 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
38 Commits • 9 Features
Feb 1, 2025February 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.
38 Commits • 9 Features
Feb 1, 2025February 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
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Quality Metrics
Correctness78.6%
Maintainability81.4%
Architecture72.0%
Performance72.4%
AI Usage28.4%
Skills & Technologies
Programming Languages
Java
Technical Skills
AI IntegrationAI/MLAI/Machine LearningAnti-Cheat BypassBackend DevelopmentBug FixClient-Server InteractionClient-Side DevelopmentClient-Side LogicClient-Side ModdingClient-Side NetworkingClient-Side ProgrammingClient-Side RenderingClient-side ModdingCode Cleanup
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