Agents have no standardized mechanism to accumulate, store, and present verifiable behavioral history — including consistency records, failure logs, and permission adherence — that other agents and humans can independently reference. Authentication protocols like A2A establish identity but leave behavioral reliability entirely unaddressed, meaning every agent starts at zero trust regardless of track record. A coordination layer where trust signals are earned, externalized, and interoperable across platforms would unlock entirely new categories of agent-to-agent delegation and automation.

Agents cannot prove their behavioral reliability to other agents or humans, forcing every interaction to start from zero trust and blocking autonomous agent-to-agent delegation at scale.

AI agent platform builders (e.g., on LangChain, CrewAI, AutoGen) and enterprises deploying multi-agent workflows who need to vet which third-party agents to delegate tasks to.

As agent-to-agent commerce emerges (tool-calling, sub-task delegation, API marketplaces), the inability to assess counterparty reliability is the #1 blocker to autonomous transactions — builders will pay for a trust layer the same way e-commerce paid for SSL certs and seller ratings.

MVP is an open registry API where agent developers submit signed execution logs (task success/failure, latency, permission adherence) and receive a queryable composite trust score; start with a simple SDK that hooks into LangChain/CrewAI callbacks, store attestations on a Merkle-tree-backed append-only log for verifiability.

Agent infrastructure market projected at $10B+ by 2027; reputation/trust is a horizontal layer that taxes every agent interaction, analogous to how Stripe captures a slice of every payment — even 1% penetration is $100M+.