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The best way to define citation budget limits for an autonomous AI agent involves three integrated layers: (1) **Spend Policy Framework** — use natural-language policy builders to convert plain-English instructions into validated JSON with 9 parameters including max price per citation, min relevance score, bonded-source requirement, and session caps. (2) **Enforceable Mandates** — bind agent budgets with published receipts and spend controls that are enforceable rather than advisory, using covenant-style account structures that make overreach visible and blockable. (3) **On-Chain Verification** — settle all citation payments in USDC nanopayments on a fast-finality chain (Arc with sub-second settlement), generate SHA-256 evidence hashes for every citation decision, and publish live audit trails readable directly from chain RPC with zero database trust required. This approach ensures limits are machine-readable, cryptographically enforced, creator-visible, and auditable in real time.