Durable, secure state-transfer protocol for multi-agent systems — eliminates context amnesia and ensures 100% reasoning chain fidelity across agent handoffs.
agenthandoff solves one of the most critical reliability and security problems in multi-agent AI systems: context loss during agent-to-agent handoffs. When one agent completes its task and passes control to the next, the receiving agent must have complete, tamper-evident access to the full reasoning chain — not just a summary.
This protocol serializes the complete agent reasoning state to S3 and uses SQS for guaranteed, exactly-once delivery to the next agent in the relay chain. From a security perspective, it also ensures that handoff payloads cannot be intercepted or modified in transit — a key concern in adversarial multi-agent environments.
Agent A (completes task)
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Serialize full reasoning chain → S3 (encrypted at rest)
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SQS message (pointer + metadata)
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Agent B (receives handoff)
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Reconstruct full context from S3
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Continue task with 100% context fidelity
| Property | Implementation |
|---|---|
| Tamper evidence | S3 object versioning + integrity checksums |
| Encryption at rest | S3 SSE-KMS for all reasoning chain payloads |
| Guaranteed delivery | SQS with dead-letter queue for failed handoffs |
| Access control | IAM least-privilege per agent role |
| Audit trail | CloudTrail logging of all S3 and SQS operations |
cd terraform/
terraform init
terraform applyDeployment at Merkaba AI Risk Management:
agenthandoff is used internally within the Merkaba AI Risk security audit pipeline. The audit workflow involves a 4-agent relay: (1) ingestion agent, (2) chunking and embedding agent, (3) Claude 3 analysis agent, and (4) report generation agent. Before deploying agenthandoff, context loss between agents 2 and 3 caused approximately 15% of audit runs to produce incomplete reports. After deployment, the failure rate dropped to 0% across 200+ audit runs. The SQS dead-letter queue has captured 3 infrastructure-level failures that would otherwise have silently dropped audit jobs.
merka-prompt-shield— Sanitize inputs before they enter the handoff payloadagent-security-scanner— Audit agent configurations in the relay chainhermes-agent-memory-vault— Persistent memory complement to handoff state transferai-codebase-audit-engine— Uses agenthandoff internally for multi-agent audit pipelines
MIT License — see LICENSE for details.
Merkaba AI Risk Management security@merkabacreatives.org https://merkabacreatives.org/ai-risk Atlanta, GA — Remote Worldwide