An add-on still fits when the team can observe its deployed behavior and investigate failures without losing operational context. The starting point is therefore not only what the add-on does, but whether its operation remains visible and diagnosable in the team’s actual production environment.
The cited material supports two concrete checks.
Can the team monitor it after deployment?
The cited risk-management material says that the functionality and behavior of deployed AI systems and their components should be monitored in production. A team should therefore identify the functions and components it would actually deploy, then check whether its monitoring arrangements cover that behavior.
This is an operational fit test rather than a feature test. An add-on may integrate cleanly during evaluation but still be difficult to assess if the team cannot observe how it behaves after deployment.
Can the team locate a failure?
The cited troubleshooting material describes opening a failed flow’s run history to find the failing action, fixing the root cause, and then turning the flow back on. Teams can use that sequence as a practical review question: during a controlled failure, would the available run history identify the specific action that failed?
Knowing that a flow stopped and knowing which action needs investigation provide different levels of diagnostic visibility. The latter gives the team a clearer starting point for root-cause analysis.
What must the team confirm itself?
The cited passages do not establish that identical monitoring coverage or run-history detail is available in every environment. Before deciding, the team should verify:
- Whether monitoring covers the functionality and behavior of the components it will deploy.
- Whether a failed flow’s run history identifies the failing action.
- Whether the team can investigate the root cause and resume the flow under its own procedures.
- Whether access conditions, retention periods, implementation costs, compatibility limits, or support terms affect the decision.
The cited material provides no values or terms for those remaining points, so they cannot be confirmed from it. The fit decision should remain open until the team verifies them through its own documentation and testing.