Every action must clear the boundary.

Place verification directly in the execution path. Tool calls, API requests, database mutations, deployments, transactions and external communications pass through the runtime before the effect occurs.

An agent may technically possess a tool without being authorized to use it for every task. VerifyRuntime checks whether this agent may perform this action on this resource under these conditions.

Translate organizational and application constraints into machine-enforceable policies evaluated against each consequential action at runtime.

When a hard constraint fails, execution terminates at the verification boundary. The prohibited call is not forwarded downstream.

High-impact or ambiguous actions can be routed to another verifier or a human decision-maker with the relevant context and evidence attached.

Inspect the exact tool, operation, arguments, target and execution context. An approved tool can still be dangerous when called with the wrong parameters or in the wrong sequence.

Evaluate the execution trace rather than treating every call independently. Previous actions can change whether the next action remains valid.

Protect critical system properties with invariants evaluated throughout execution: balances remain non-negative, protected data never leaves approved boundaries, required approvals exist, production writes remain scoped.

Reason about the intended external effect—not only the syntax of the call. Evaluate scope, destination, reversibility, blast radius and protected resources before permitting execution.

After execution, compare the observed result with the authorized operation and required post-conditions. Verification can cover both permission before execution and conformance after it.

Bind the request, policy decision, execution result and runtime evidence into a durable record showing what was requested, what was verified, what was permitted and what occurred.

When the runtime cannot establish required identity, authority, policy state or evidence, consequential operations can default to non-execution rather than optimistic permission.

Policies can reserve specific classes of decisions for human authorization and attach the exact action, evidence and risk context needed for meaningful approval.

Preserve enough runtime evidence to replay verification decisions against the relevant policy, inputs, execution state and authorization context.

As agents operate for longer periods with broader access, verification becomes infrastructure for scaling autonomy without making every model decision equivalent to unrestricted execution authority.

Applications submit proposed operations to a common runtime interface for policy evaluation, authorization and evidence generation before dispatch.

A control layer between machine reasoning and external effects that determines whether an autonomous action satisfies the conditions required for execution.