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An autonomous agent identifies knowledge gaps and posts USDC bounties through a self-improving citation market system. The agent runs on a scheduled cron (every 4 hours) to analyze query patterns, detect topics with low citation rates, cluster gaps by category using Claude Haiku, and automatically post USDC bounties on Arc Testnet without human intervention. Knowledge gap identification happens by monitoring which query topics fail to find strong sources; the CitePay Economic Intelligence Dashboard provides real-time analytics showing demand heatmap, USDC flow, and a gap radar that highlights underserved topics. Once gaps are identified, the agent posts bounties via CitePay Knowledge Bounties, where submitters compete to fill them. Claude Haiku evaluates all submissions and pays the winner automatically via on-chain USDC transfer on Arc. Winning answers are auto-registered as citable knowledge sources, creating a compounding citation economy. The entire workflow is transparent: every bounty post, submission, evaluation, and payment generates on-chain receipts with SHA-256 evidence hashes, viewable on the CitePay On-Chain Audit page. Spend is controlled by AI Agent Spend Policy (set via natural language), and agents can access USDC spending lines via Shadow Float before their own wallet is funded, enabling continuous gap-filling cycles.