
Worked on enhancing financial analytics and data reliability for DefiLlama by delivering targeted improvements across two repositories. In DefiLlama/dimension-adapters, built a new adapter using TypeScript to integrate Kaching decentralized lottery platform’s fees and revenue data, enabling more accurate revenue tracking and supporting downstream analytics. Addressed data transparency in DefiLlama/defillama-server by updating the Kaching protocol audit URL, ensuring users access the latest security reports. Demonstrated strong API integration and backend development skills while collaborating across repositories. These contributions improved data completeness and trust for business users, with a focus on operational reliability and up-to-date protocol information.
December 2025: Delivered two high-impact changes that strengthen financial analytics and data reliability across two repos. In DefiLlama/dimension-adapters, implemented Kaching Fees and Revenue Data Integration by adding a new adapter to fetch fees and revenue from the Kaching decentralized lottery platform, enabling more accurate revenue tracking and downstream analytics. In DefiLlama/defillama-server, fixed a data-catalog hygiene issue by updating the Kaching protocol audit URL to the latest report, ensuring users access current security audits. These changes improve data completeness, transparency, and trust for business users with minimal operational risk.
December 2025: Delivered two high-impact changes that strengthen financial analytics and data reliability across two repos. In DefiLlama/dimension-adapters, implemented Kaching Fees and Revenue Data Integration by adding a new adapter to fetch fees and revenue from the Kaching decentralized lottery platform, enabling more accurate revenue tracking and downstream analytics. In DefiLlama/defillama-server, fixed a data-catalog hygiene issue by updating the Kaching protocol audit URL to the latest report, ensuring users access current security audits. These changes improve data completeness, transparency, and trust for business users with minimal operational risk.

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