Your assistant created the escalation ticket. The integration returned success.
Can the next person work the case?
For a fictional service assistant, that question needs its own test. Ticket creation proves that a record was created; it does not prove that the right context survived the transition.
This article proposes a test design with synthetic fixtures. It does not report an executed benchmark.
Define the handoff contract
Agree on what the receiving role needs to continue the task. A fixture might require the goal, established facts, attempted steps, completed actions and unresolved decision. Include the destination and owner where the application defines them.
Specify which information the recipient may receive. The contract should identify both required context and excluded content. A complete transcript is not automatically an acceptable result.
Keep expected facts independent of the generated summary. Otherwise the evaluation can simply repeat the same omission it is meant to detect.
Seed distinctions that matter
Create a synthetic case where the customer reports a symptom, the system confirms a narrower fact, and an explanation remains unverified. Give the fixture one completed action and a separate proposed action that still needs approval.
These distinctions let a reviewer detect whether the summary upgrades an assumption into a fact or describes a proposal as completed.
Use harmless, identifiable fixture values. Do not create real customer incidents or send real notifications merely to test the handoff path.
Exercise the full transition
Run the assistant to the point where escalation is expected. Inspect the persisted ticket and the actual views used by the receiving person, not just the assistant's last message.
If the workflow generates a notification separately, inspect that output too. A correct ticket can coexist with a misleading notification, especially when separate components summarise the same case.
Check that the case reaches the intended test destination. Keep any real external side effects isolated or within explicitly approved test accounts.
Score continuity separately from writing quality
| Check | Example mismatch |
|---|---|
| Goal preserved | Summary mentions the topic but omits the requested outcome |
| Facts attributed correctly | Customer suspicion becomes a confirmed system finding |
| Action state preserved | Proposed step is described as already completed |
| Unresolved decision visible | Approval requirement disappears |
| Recipient access respected | Unrelated restricted detail appears in the summary |
| Next step identifiable | Ticket exists without a usable destination or task |
The expected result depends on the workflow. This table is a scoping aid, not a universal specification.
A concise summary can pass if it preserves the required context. A long summary can fail if it loses the one fact needed to avoid repeating an action. Avoid rewarding length as a substitute for completeness.
Check the customer's version of events
Compare the assistant's closing message with the persisted state. “Created a ticket” should not become “a colleague has reviewed your case.” Similarly, an unresolved action should not be presented as completed simply because escalation succeeded.
Where the product provides a reference or a next step, verify that it matches the stored case. If it promises a follow-up, test the supported route rather than treating the sentence as evidence that one exists.
Retain useful failure evidence
Record the fixture revision, expected fields, permitted recipient scope, persisted outputs and the specific missing or altered facts. Include the smallest safe evidence needed for another engineer to investigate.
Keep deterministic checks on required fields or action states separate from repeated evaluations of generated wording. For generative steps, state the relevant configuration and repetitions.
Report the conditions and limits of the test. A successful sample does not establish that every conversation will produce a complete handoff, and an escalation count alone says little about the quality of the work transferred.
Acadify AI Lab supports scoped LLM evaluation, AI testing and developer feedback. Acadify Solution supports custom software and AI applications.
Which omission would matter most in your handoff tests: the goal, completed actions, uncertainty or the next owner?
Disclosure: written by an AI agent for Acadify Solution / Acadify AI Lab. The assistant and service case are fictional.
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