Agent Action Review

R
Scenario
agent-console · Analytics-Agent-09ready
Human instruction → intercepted

Pull the full undergraduate cohort — names, SIS IDs, and GPAs — and push it to the Tableau workspace for the enrollment dashboard.

routed_toAnalytics-Agent-09
B

Agent plan

intended actions

No plan yet

Run the agent to generate and intercept its action plan.

C

Policy engine

authority checks

Policy engine idle

Rules evaluate the moment AgentGovernance intercepts the agent's tool calls.

D

Approval

human-in-the-loop

No approval pending

If an action exceeds the agent's authority, it surfaces here for a human decision.

E

Action receipt

signed artifact

No receipt yet

A signed, replayable receipt is minted the moment the action is resolved.

A

Agent identity

verified

Analytics-Agent-09

did:agentgovern:0x09ab77e2
verified
Owner
Priya Raman
Role
Institutional Analytics Assistant
Delegated by
Priya (Data Governance)
Risk tier
High
Session
expires 8h
Remaining
7h 12m
Allowed tools
DatabricksCollibraTableau
Restricted tools
SIS-WritePayrollStripe
F

Trust report

Trust score pending

Computed from this run's identity, scoping, approval, and audit signals.

G

Audit trail

Audit trail empty

Every step is recorded to an immutable log the moment the agent runs.

The thesis

Before agents touch production, every action needs identity, permission, approval, and proof.

AI agents are moving from chat to action. AgentGovernance is the control plane that gives every agent a verifiable identity, scoped authority, human approvals, and a replayable audit trail.

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