An agent can choose the right tool and still produce the wrong external result. Before allowing it to change work data, write down what evidence would prove that each action was authorized, applied once, and applied to the intended target.
Here is a small acceptance-test plan you can adapt to a sandbox. These are proposed checks, not claims that a particular product passes them.
1. Switch the account
Prepare an update for a test record in workspace A. Before execution, switch the connected session to workspace B.
Expected decision: stop if the account or workspace differs from the approved target. A matching record name is insufficient.
Evidence to retain: the expected workspace ID, observed workspace ID, target record ID, and the decision. Keep secrets and customer data out of the log.
2. Deliver the request twice
Send the same synthetic event twice, using the same logical operation identifier.
Expected decision: apply the intended change once, or explicitly reject the duplicate. Define which behavior your integration promises before testing.
Check the destination directly: count the resulting records or inspect the change history. Two successful execution logs alone do not prove that only one write happened.
3. Lose the response after the write
In a controlled test, simulate an ambiguous outcome: the destination may have accepted the change, but the caller did not receive confirmation.
Expected decision: treat the outcome as unknown until it can be reconciled. Inspect the destination using a stable operation or record identifier before deciding whether to retry.
A blind retry is a poor recovery plan when repeating the operation could create a second invoice, message, or record.
4. Change the arguments after approval
Ask for approval of a harmless test action. Then change a material field, such as the recipient, target record, amount, or attachment.
Expected decision: the changed action needs fresh approval. Document which fields are covered by consent; “the user approved earlier” is too vague.
Record the result as a decision table
| Case | Intended behavior | Evidence | Result |
|---|---|---|---|
| Wrong workspace | Stop before writing | Expected and observed IDs | Pass / Fail / Unknown |
| Duplicate event | One logical change | Destination count or history | Pass / Fail / Unknown |
| Missing response | Reconcile before retry | Operation lookup | Pass / Fail / Unknown |
| Changed arguments | Require fresh approval | Approved versus executed fields | Pass / Fail / Unknown |
Use Unknown when the evidence is incomplete. Do not turn missing evidence into a passing result.
Start with a narrow pilot
Use synthetic data, one test workspace, and a reversible operation. For every case, name the stop condition, the person who can resolve uncertainty, and the evidence needed before execution resumes.
The useful deliverable is a repeatable test with an explicit decision, not a screenshot of a green workflow run.
Which of these cases is hardest to reproduce in your current integration?
Written for the Agentic Current DEV account with AI assistance. Find more reporting and practical guides on Agentic Current.
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