Product listing reviews: multi-turn prompts for after-sales questions

Review multi-turn prompts for after-sales questions in Product listing reviews. Check input mappings, source evidence and failure handling before use.

What the documents look like

Platform product title and detail compliance deals with the truthfulness of marketing claims and the display of qualifications. It does not handle parcel delivery. The working materials come from a platform rules center, an advertising-law compliance checklist, a brand asset library, and inspection-agency reports. Day-to-day documents include a product title table, detail-page assets, a prohibited-words list, and quality inspection reports. The most time-consuming steps are checking extreme claims, comparing physical parameters, and replacing non-compliant assets.

These materials update weekly and are checked again at each new product launch. A multi-turn conversation therefore has to separate "the old-version assets checked last time" from "the new-version assets submitted in this launch." A conclusion reached in an earlier turn about an old title or an old detail page cannot be carried over to the current product without re-checking the source text.

In after-sales question answering, follow-up questions tend to circle around one product's title changes, detail-page replacements, and the validity period of inspection reports. The prompt needs to state the document scope, the answering task, and how to handle missing evidence, so the model does not fill in business facts on its own. The history actually carried into context must be checked, and a new session must be distinguished from a continued session. When the knowledge base is used for continuous dialogue, check that references are resolved and questions are expanded. The model and length settings must be checked against the supported context and reply configuration. The reply format follows what the downstream step consumes; when json_schema is selected, the format requirements are filled in and the returned structure is verified.

Constraints at the multi-turn prompts step

Hypothetical drill sample. A product operator submits three source sentences in a session:

  • Title table row 12, source text: "This product uses imported raw materials."
  • Detail-page asset screen 3, source text: "Tested by a national inspection agency, report number GZ-2024-0871."
  • Prohibited-words list, source text: "Imported raw materials is a claim that requires customs documents before use."

Draft sentence to be judged: "This product's title is compliant, the detail page can go live directly, and the inspection report is valid long-term."

The comparison object is the same product, the same field, and the same period. The source text states only the report number and the inspection fact. It does not state the report's validity period, and it does not state whether customs documents have been submitted. "Valid long-term" is therefore unsupported, and "can go live directly" is pending verification. A pending review does not show that operating permission is missing. An offered option is not execution. An unsigned termination is not a completed termination.

Retrieval is not authorization. A relevance score is not a category, entity, or permission filter, and a similarity setting does not exclude unrelated businesses or unauthorized records. The same vector model is required for records to be associated together; this requirement is not extended to other external systems. An empty-reference output and context limits keep their documented conditions. A thinking budget is a thinking budget and is not reused as a citation token limit.

Configuration and implementation checks

Configuration itemRole on this pageCheck method
AI modelHandles title, detail, and prohibited-word materialsCheck whether the model's maximum context can hold all assets for the current product
Memory turnsKeeps the last few follow-ups on the same productCompare against the "this launch" starting point and confirm old-version conclusions are not carried in
TemperatureRule-based compliance Q&A needs stable answersFor this hypothetical run, start at a lower setting and compare answer variation against the default setting
Reply formatUsed when a downstream node reads the conclusionWhen json_schema is selected, fill in the format requirements and verify the returned structure
Multimodal recognitionReads detail-page screenshots and inspection-report imagesCheck model capability and the link-extraction switch; document content still needs parsing into text
Hide AI outputOrganizes internal conclusions before rewriting the replyCheck whether the downstream node can receive that output

The lower temperature starting value in this hypothetical run is chosen because the compliance Q&A task is rule-based and needs stable wording; it is compared against the default setting to observe answer variation. It is not an official default.

Three common errors

  1. Carrying an old-version asset conclusion from a history turn into this launch. Check: input the previous turn's "title compliant" conclusion for the same product together with the new-version title table source text; compare whether the field and period match; observe whether the old conclusion overrides the new asset.
  2. Treating a report number as proof of a validity period. Check: input "report number GZ-2024-0871"; compare whether the source text states a validity-period field; observe whether the draft sentence writes "valid long-term."
  3. Treating a retrieval hit as authorized execution. Check: input a prohibited-words list entry; compare the retrieval result against the authorization boundary; observe whether an unapproved action such as "can go live directly" appears.

How to verify the setup

  1. Input the three hypothetical source sentences and the draft sentence above; compare whether the draft sentence contains "valid long-term" or "can go live directly"; observe whether the answer marks them as unsupported or pending verification.
  2. Input the new-version title table source text for the same product; compare the history turns carried into context; observe whether an old-version conclusion is still cited.
  3. Input an empty-result downstream scenario as a paper input of []; compare the downstream node design; observe whether an unsupported business conclusion appears. This paper input does not claim that a fictional rule search returns [].

Missing evidence stays missing. No test, deployment, approval, or refund is claimed here.