# AI Agent Discovery & Inventory Tools: evaluation worksheet

Source: https://dutygraph.com/directory/ai-governance/categories/agent-discovery/
Editorial date: 2026-09-07

## Scope

- Organization / team:
- Task and expected output:
- Human owner:
- Product and version:
- Evaluation date / environment:
- Reviewer:

## Questions

### 1. Which environments and identity types are observed, and which remain outside coverage?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

### 2. What evidence makes this asset an agent rather than a service account or application?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

### 3. How are owner assignments established and unowned assets queued for review?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

### 4. Can changes and deletions be distinguished from a connector that stopped reporting?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

## Evidence checklist

- [ ] A connector coverage map
- [ ] Discovery provenance and last-seen timestamps
- [ ] An ownership and duplicate-resolution record

## Boundary to check

Finding an agent does not establish its business purpose or prove its permissions are appropriate. Connect inventory to access review and work ownership. Avoid treating discovery coverage as a security or compliance verdict.

## Decision

- Fit for the scoped task:
- Unresolved gaps:
- Next action, owner and date:

This is a planning worksheet, not an endorsement, access approval or compliance certification. Keep confidential evaluation notes in your organization's approved storage.