DAOscope

This project, DAOscope, is a single-page application built using a modern frontend stack: React and TypeScript for a robust, type-safe component architecture, with Tailwind CSS for rapid and responsive UI development.The application's core is its data layer, which connects directly to Snapshot.org's public GraphQL API to fetch real-time governance data. A significant challenge was handling API timeouts for large DAOs like Uniswap. To solve this, I implemented a "split-query" strategy: one lightweight query fetches a large number of proposal metadata for statistical trends, while a second, heavier query fetches full details (like vote counts and body text) for only the most recent proposals. This ensures the dashboard loads quickly while still providing deep, accurate insights for metrics like centralization and delegate participation.The "intelligence" layer is powered by Google's Gemini API, which is integrated in two key ways. First, it generates the "Weekly Governance Story" by analyzing a dynamically constructed prompt containing the latest metrics. Second, it powers the interactive "Ask AI" chat widget. The most notable part of this integration is that the systemInstruction for the Gemini chat session is rebuilt every time a new DAO is selected, feeding the AI the live, specific data for that organization. This effectively turns a general-purpose model into a specialized, real-time governance analyst on the fly, allowing it to provide highly contextual and accurate answers about the on-screen data without ever having to say "I can't access live information." Data visualizations are handled by the recharts library to create clear, interactive charts from the processed data.

This project, DAOscope, is a single-page application built using a modern frontend stack: React and TypeScript for a robust, type-safe component architecture, with Tailwind CSS for rapid and responsive UI development.The application's core is its data layer, which connects directly to Snapshot.org's public GraphQL API to fetch real-time governance data. A significant challenge was handling API timeouts for large DAOs like Uniswap. To solve this, I implemented a "split-query" strategy: one lightweight query fetches a large number of proposal metadata for statistical trends, while a second, heavier query fetches full details (like vote counts and body text) for only the most recent proposals. This ensures the dashboard loads quickly while still providing deep, accurate insights for metrics like centralization and delegate participation.The "intelligence" layer is powered by Google's Gemini API, which is integrated in two key ways. First, it generates the "Weekly Governance Story" by analyzing a dynamically constructed prompt containing the latest metrics. Second, it powers the interactive "Ask AI" chat widget. The most notable part of this integration is that the systemInstruction for the Gemini chat session is rebuilt every time a new DAO is selected, feeding the AI the live, specific data for that organization. This effectively turns a general-purpose model into a specialized, real-time governance analyst on the fly, allowing it to provide highly contextual and accurate answers about the on-screen data without ever having to say "I can't access live information." Data visualizations are handled by the recharts library to create clear, interactive charts from the processed data.