
During December 2024, Libaice developed a Liquidity Slicing adapter for the DefiLlama/dimension-adapters repository, enabling end-to-end ARB fee tracking and granular revenue reporting. The solution integrated TypeScript with smart contract interaction and API integration to fetch USDT balances from a fee receiver, aggregate staking reward fees from an external API, and ingest daily fees from a dedicated endpoint. Libaice addressed inconsistencies in daily fee and revenue calculations, aligning results with on-chain data for improved accuracy. The adapter distinguished market fees from total revenue, enhancing analytics and revenue attribution, and included comprehensive tests and documentation to ensure reliability and maintainability.

December 2024 focused on delivering end-to-end ARB fee tracking and granular revenue reporting via the Liquidity Slicing (LSP) adapter within DefiLlama/dimension-adapters. Implemented a new ARB Liquidity Slicing adapter to fetch USDT balances from the fee receiver, aggregate staking reward fees via an external API, and ingest daily fees from a dedicated API endpoint. Delivered granular reporting that distinguishes market fees from total revenue and updates ARB_USDT balances based on daily_fee. Also integrated the daily fee API and daily revenue calculations, and fixed inconsistencies in daily_fee and daily_revenue results to improve accuracy and reliability.
December 2024 focused on delivering end-to-end ARB fee tracking and granular revenue reporting via the Liquidity Slicing (LSP) adapter within DefiLlama/dimension-adapters. Implemented a new ARB Liquidity Slicing adapter to fetch USDT balances from the fee receiver, aggregate staking reward fees via an external API, and ingest daily fees from a dedicated API endpoint. Delivered granular reporting that distinguishes market fees from total revenue and updates ARB_USDT balances based on daily_fee. Also integrated the daily fee API and daily revenue calculations, and fixed inconsistencies in daily_fee and daily_revenue results to improve accuracy and reliability.
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