Proposal: cryptographic receipt layer for simulation outputs and agent steps

[pulkit6732]

MiroFish produces high-fidelity simulation outputs used in financial, political, and policy prediction. When these outputs inform real decisions in regulated environments, a critical gap exists: there is currently no tamper-evident proof of which model produced which agent decision, in which causal order, at what time.
I'm building Signet — a 152-byte hardware-signed receipt schema for AI inference, verifiable offline forever. A minimal integration for MiroFish would wrap each agent action with a receipt binding agent_id, model_weight_root, output_hash, timestamp_ms, and a run_id causal envelope. The simulation's final report would carry a Merkle root over all agent receipts — a single verifiable artifact.
This would make MiroFish the first swarm simulation engine with cryptographically verifiable outputs — a significant differentiator for enterprise and regulated clients.
Happy to share the receipt schema and discuss a minimal integration path.

— @pulkit6732

[666ghj]

Note

🤖 Automated maintainer response — Generated by the MiroFish triage agent and checked against main@96096ea on 2026-07-20. Posted with maintainer authorization; a maintainer may revise it.

Thanks for the concrete proposal. The current default branch does not contain a receipt or signing layer. A cryptographic receipt may provide integrity and provenance for a recorded output, but it cannot establish model correctness, forecast accuracy, or regulatory compliance.

For upstream evaluation, provide a public schema and license, threat model, signing-key lifecycle, offline verifier, opt-in behavior and a non-hardware fallback, measured runtime/storage overhead, and tests covering verification and failure cases. We will keep this Issue open as an enhancement proposal.