Multi-Agent Orchestrator Prover Connector for AI agents.

It's a validation capability that forces your AI client to create a production-ready blueprint for multi-agent systems. It ensures your agents have clear roles, handoff rules, and failure protections.

It prevents common issues like cascading failures, infinite loops, and data loss. It forces the inclusion of circuit breakers and retry policies before you ever deploy your code.

While you can, it's designed for complex multi-agent workflows. If you're only building a simple chatbot, this capability provides more architectural rigor than you likely need.

No, it doesn't access your keys. It analyzes the architectural logic and contracts of your agent system to ensure the design is sound.

It requires your AI client to define specific behaviors for every failure, such as timeouts, fallback results, and circuit breaker thresholds.

The five axes are Roles, Handoffs, Failures, Consensus, and Observability. These cover the core requirements for any robust multi-agent system.

Yes. Two agents still need role boundaries, a handoff protocol, failure containment, and observability. The failure modes don't care about agent count. they care about architectural discipline. A 2-agent system with undefined handoffs fails the same way a 20-agent system does.

When two agents produce conflicting outputs, a consensus mechanism resolves the conflict deterministically. Options: confidence scoring (highest confidence wins), supervisor agent review, voting with tie-breaking rules, evidence-coverage scoring. 'They usually agree' is not a mechanism. it is hope that collapses the first time agents disagree.

No. It computes nothing. It validates that your agent architecture passes five structural checks. role boundaries, handoff protocols, failure containment, consensus, and observability. The design is yours. The discipline is enforced by the capability.