
During November 2025, Catanet developed two foundational features for the Neverland ecosystem, focusing on revenue modeling and governance token staking. In the DefiLlama/dimension-adapters repository, Catanet implemented a module to calculate protocol fees and distribute revenue to veDUST holders, enhancing transparency and data quality. Additionally, in DefiLlama-Adapters, Catanet introduced an adapter inspired by Aave V3, enabling tracking of total value locked, borrowing, and staking metrics. The work emphasized scalable, adapter-based architecture and robust API integration using TypeScript and JavaScript. While no bugs were addressed, the depth of engineering established a reliable foundation for future DeFi protocol expansions.

Monthly Summary - 2025-11: Delivered two core features across the Neverland ecosystem, establishing revenue modeling, TVL/borrowing tracking, and governance token staking capabilities. These changes enable clearer revenue distribution for veDUST, improve risk visibility, and create a scalable, adapter-based architecture for future expansions. No major bugs fixed this month; focus was on feature delivery, reliability, and data quality. Technologies demonstrated include TypeScript, adapter-oriented architecture, protocol integration, and data modeling. Commits included: e935f7ad1a1277897a2279859631da275605a284; 660a52d9690e91dd9f7e2bb10fbdcb7a961dafe8.
Monthly Summary - 2025-11: Delivered two core features across the Neverland ecosystem, establishing revenue modeling, TVL/borrowing tracking, and governance token staking capabilities. These changes enable clearer revenue distribution for veDUST, improve risk visibility, and create a scalable, adapter-based architecture for future expansions. No major bugs fixed this month; focus was on feature delivery, reliability, and data quality. Technologies demonstrated include TypeScript, adapter-oriented architecture, protocol integration, and data modeling. Commits included: e935f7ad1a1277897a2279859631da275605a284; 660a52d9690e91dd9f7e2bb10fbdcb7a961dafe8.
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