An add-on is a plausible candidate when the task’s input contains the details needed for its next action and the resulting fields or tables can be carried forward. Form processing is the clearest documented example: the cited guidance says that fields and tables extracted by a model can be used in subsequent flow actions. Evaluation should also remain connected to the deployment context rather than relying only on an isolated test.
Which tasks have the needed context?
The useful pattern is available input → identifiable output → defined downstream use → known deployment context.
| Context to examine | Fit question |
|---|---|
| Input context | Does the task material contain the details needed for the next action? |
| Output context | Can the result be expressed as identifiable fields or tables? |
| Workflow context | Is there a later action that can use those outputs? |
| Deployment context | Can the task’s operating setting be identified and reflected in risk measurement? |
Form-processing tasks fit the documented pattern because extracted fields and tables can become inputs to later actions. Tasks that produce information for another operational step may fit the same pattern, but that does not establish that a particular add-on supports them.
Tasks with missing input details, outputs that have no defined next use, or an unidentifiable deployment setting provide less basis for assessment. Their fit should remain uncertain until the missing context is supplied and verified.
How to check a candidate task
Map the complete workflow before testing an add-on:
- Record the input that will actually be available when the task is performed.
- Define the fields or tables the task is expected to extract.
- Identify the later action that will use those outputs.
- Describe the deployment context in which the workflow will operate.
- Connect the risk-measurement approach to that context.
If any part of this path cannot be confirmed, it remains an open requirement rather than an assumed capability. A resemblance to the form-processing example is not enough on its own.
What still needs confirmation
The cited materials do not establish which task categories a particular add-on supports, what level of accuracy it will achieve, or what result it will produce. Those points require confirmation against the actual workflow and the documentation for the intended tool and deployment.
In short, the strongest candidates are tasks with context in the input, outputs that have a defined next action, and an identifiable deployment setting. Any broader claim about performance or outcomes remains unverified.