Show HN: Circe – Deterministic, offline-verifiable receipts for AI agent actions (github.com)

A new project called Circe has been unveiled, providing a lightweight offline verification tool for AI agent actions, allowing these actions to be treated like signed transactions instead of mere log entries. The core innovation is the creation of a canonical JSON artifact, termed a receipt, that records the decisions or outputs of an AI agent. This receipt can be independently validated without reliance on external logs or systems, enhancing trust in AI operations. The verification process employs Ed25519 signatures and SHA-256 hashes to ensure integrity, discerning between original and tampered data. Circe holds significant implications for the AI/ML community by establishing clear trust boundaries and improving the accountability of AI agents in decision-making scenarios. By explicitly verifying action integrity, developers can make AI systems more robust against manipulation and errors. The project emphasizes simplicity and focuses solely on receipt integrity and offline verification, leaving considerations for policy semantics or key management to be managed separately. This approach could enhance the reliability of AI pipelines and facilitate broader acceptance of AI systems in critical applications, inviting feedback on potential vulnerabilities and integration in real-world scenarios.