AI Agents Inventory and Attributes - Assessment and Health attributes for the AI Agents Inventory
AI Agents Inventory and Attributes
Chapter 16. Assessment and Health attributes for the AI Agents Inventory
Executive Summary: Chapter Overview
IF4ITThe Bottom Line
Core Concepts
| Concept | Definition & Strategic Role |
|---|---|
| Trust Signal | A single, continuously updated indicator of the agent’s current health and reliability. |
| Continuous evaluation | Scored testing run on live behavior over time, so drift and regressions surface on real traffic. |
Quick Q&A
Question: Why must agent health be assessed continuously rather than once?
Read More Below
Assessment and health attributes report each agent’s current reliability, evaluated behavior, and known weaknesses.
| Attribute Name | Maturity | Description and Notes |
|---|---|---|
| Trust Signal | Run | Description — A single, continuously updated indicator of the agent’s current health, reliability, and governance posture. Benefit(s) — Gives everyone — auditor, risk officer, engineer — one current read on whether the agent can be relied on. Source — Calculated. Examples — Green; Amber; Red Notes — Rolls up evaluation, drift, and risk inputs; kept live, not set at launch. |
Evaluation Scores [Multi-Value] | Walk | Description — Scores from testing the agent’s outputs for task success, correctness, groundedness, and safety or policy compliance. Benefit(s) — Quantifies quality and, tracked over time, reveals regressions and drift. Source — Derived. Examples — Task success 0.92; Groundedness 0.88 Notes — Feeds the Trust Signal and the attestation evidence. |
Known Failure Modes [Multi-Value] | Walk | Description — The documented ways this agent is known to fail or misbehave. Benefit(s) — Turns hard-won operational knowledge into a governed, reviewable record rather than tribal memory. Source — Manual. Examples — Over-refunds on ambiguous requests; loops on empty results |
| Behavioral Drift Status | Run | Description — Whether the agent’s behavior has drifted from its validated baseline. Benefit(s) — Flags agents whose behavior has changed and may need re-evaluation or re-attestation. Source — Calculated. Examples — Stable; Drifting; Regressed |
| Red-Team Status | Walk | Description — Whether, when, and with what result the agent was adversarially tested. Benefit(s) — Records that the agent was probed for unsafe or exploitable behavior — part of the defensibility record. Source — Manual. Examples — Passed 2026-05; Findings open |
| Last Assessment Date | Walk | Description — The date of the most recent health or evaluation assessment. Benefit(s) — Shows how current the agent’s health picture is. Source — Manual. |
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