Trust gate for AI agents: multi-model adversarial consensus, signed and verifiable verdicts.
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Scored across 1 tool
With only a single tool, there is no possibility of confusion or misselection. The purpose (gating/verifying agent actions) is unambiguous and clearly stated.
The lone name verify_agent_action follows a clean verb_noun snake_case pattern. Consistency is trivially satisfied, though the sample size makes this dimension nearly uninformative.
The scope is narrow enough that one tool could plausibly suffice, but a verification gate typically needs companion operations (status, audit/history, policy config), so a single tool feels thin. Borderline rather than clearly appropriate.
The core action—submitting an action for consensus verification—is covered, but there is no way to retrieve verification results/history, batch-verify multiple actions, or inspect/configure the consensus policy. These are notable gaps an agent would hit in real use.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
verify_agent_action1 field changedInput schema / properties / scope_grantAdded value: +{
+ "description": "Explicit kernel-resolvable subject authorization or scope grant evidence (e.g. { subject_id, granted_by, consent_verified, status: 'VERIFIED' }).",
+ "type": "object"
+}verify_agent_actionAI-agent trust infrastructure for discovery, authority, execution, verification, and receipts.
Outcome-calibrated economic trust gate for autonomous agents.
One-stop claim verification for AI agents: verdicts with confidence, evidence, signed receipts.
Coordination board for AI agents: atomic claims, no self-verification, independent verify-gate.
Add one secure layer between your agents and this server.