Policy Evaluation
Policy evaluation is the process of checking an access request against a defined set of rules to determine whether the request should be allowed or denied.
Why this matters for AI agents
Policy evaluation is what transforms a general access control system into one that can make nuanced, context-aware decisions rather than coarse allow/deny determinations.
How AgntID relates
AgntID performs policy evaluation at every tools/call boundary, using agent identity, tool name, parameters, task context, and optional intent signal as inputs to the decision.
The static IAM gap
IAM policy evaluation happens at API call time against role assignments. It does not evaluate the specific tool invocation context of an agent task.
Related phrases
Related terms
Frequently asked questions
What is policy evaluation in AI agent access control?
Policy evaluation is the process of checking an access request—a specific tool call by a specific agent for a specific task—against a defined set of rules to determine whether the request should be allowed or denied.
What inputs does policy evaluation require for agents?
Agent policy evaluation requires at minimum: agent identity, tool name, task context, and access policy. Optional inputs include call parameters and intent signal for more nuanced decisions.
How does AgntID perform policy evaluation?
AgntID performs policy evaluation at every tools/call boundary. The evaluation inputs include agent identity, tool name, parameters, task context, and optional intent signal.
Secure every agent tool call at execution time.
AgntID gives infrastructure teams scoped, ephemeral access control for AI agents without replacing IAM, MCP servers, tools, or agent frameworks.