
During November 2025, AntFun developed enhanced fee analytics for the DefiLlama/dimension-adapters repository, focusing on Solana trading activity. He built the AntFun Fees Adapter, which calculates and reports trading fees across multiple tokens by integrating Dune Analytics as a data source and supporting dynamic fee addresses via API. Using TypeScript and backend development skills, he implemented multi-token tracking for USDC and USDT, along with response caching to improve performance and data freshness. The work expanded data coverage and reliability for trading-fee metrics, resulting in more accurate dashboards, while maintaining system stability and preparing the adapter for future data sources.

November 2025 monthly summary for DefiLlama/dimension-adapters focused on delivering enhanced fee analytics capabilities and expanding data-source coverage. Key delivery includes the AntFun Fees Adapter Improvements for Solana with Dune Analytics integration and dynamic multi-token support, enabling more accurate and timely reporting of trading fees across tokens. Major achievements include implementing dynamic fee addresses (via API) with multi-token tracking (USDC/USDT) and introducing response caching to improve performance and data freshness for fee metrics. No major bugs reported this month; observed stability improvements accompany feature work and performance optimizations.
November 2025 monthly summary for DefiLlama/dimension-adapters focused on delivering enhanced fee analytics capabilities and expanding data-source coverage. Key delivery includes the AntFun Fees Adapter Improvements for Solana with Dune Analytics integration and dynamic multi-token support, enabling more accurate and timely reporting of trading fees across tokens. Major achievements include implementing dynamic fee addresses (via API) with multi-token tracking (USDC/USDT) and introducing response caching to improve performance and data freshness for fee metrics. No major bugs reported this month; observed stability improvements accompany feature work and performance optimizations.
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