What the documents look like
Category access work happens before a product is listed or a store is onboarded. The core materials are the business license, trademark registration certificate, brand authorization chain, and industry license. These materials come from platform recruitment pages, the National Enterprise Credit Information Publicity System, trademark office data, and license systems. Updates are irregular, and every onboarding round requires a fresh check.
In the order fulfillment and after-sales question scenario, multi-turn dialogue carries the material handover between an onboarding specialist and a recruitment operator. One turn asks whether a given authorization is usable; the next asks about the progress of a correction; a further turn confirms whether a category can be published. The conversation history therefore mixes entity names, certificate numbers, authorization layers, and review states. Prompts need to separate what comes from the source material and what is only a question awaiting verification.
Constraints at the multi-turn prompts step
Multi-turn dialogue brings in earlier turns. The memory turn count controls how many prior chat rounds the AI may reference at most. A larger value makes it easier to reference earlier conversation, and it also brings in more content, which can increase consumption and affect response speed. An authorization chain for category access is often supplemented across several turns. A value that is too small may fail to use entity information already confirmed earlier; a value that is too large may carry forward expired or unverified intermediate conclusions.
A lower temperature produces steadier answers and suits customer service and rule-bound scenarios. Category access questions fall into the rule-bound group, so answers should stay stable. Reply format follows what the downstream step needs. Ordinary customer service question answering keeps the default. The format is changed only when a later flow needs to read fixed-format content, and choosing json_schema requires filling in the corresponding format requirements. Thinking configuration controls model thinking intensity. The thinking budget and the reference token limit are two different concepts, and the thinking budget cannot be treated as a reference length limit. With hidden AI thinking enabled, the user sees only the final answer; during debugging it can be temporarily turned off to observe intermediate thinking content.
Configuration and implementation checks
The following settings concern a hypothetical drill sample and list only documented settings or implementation checks relevant to this feature and the order fulfillment and after-sales question task.
| Configuration item | Hypothetical trial starting point | Reason and comparison method |
|---|---|---|
| Memory turn count | Hypothetical starting point of 4 turns | Authorization chains are usually supplemented across 3 to 5 turns; compare against 2 turns and 8 turns and observe whether early entity information is carried in |
| Temperature | Hypothetical lower value | Category access is a rule-bound scenario; compare against a higher value for answer stability, without claiming a default |
| Reply format | Hypothetical default first | No downstream fixed-format read requirement; if a downstream step needs structured fields, change to json_schema and check the returned structure |
| Thinking configuration | Hypothetical standard thinking | Authorization chain matching is moderately complex; compare against no thinking for answer completeness and against deep thinking for consumption |
| Hidden AI thinking | Hypothetical enabled | The final answer for the onboarding specialist needs only the conclusion; turn it off temporarily during debugging to observe the intermediate process |
| Multimodal recognition | Hypothetical not enabled | Materials are mainly text and document links; document content needs file parsing into text and is not sent directly as multimodal input |
Three common errors
- Treating an unverified conclusion from an earlier turn as a confirmed fact. In the hypothetical sample, one turn says the authorization letter may have been sent. If the next prompt writes that the authorization letter has been sent, the wording departs from the source. The check inputs the original turn text and the proposed sentence, compares may have been sent against has been sent, and observes whether the proposed sentence keeps the unverified state.
- Treating a retrieval result as an authorization conclusion. Knowledge base retrieval returns similar material fragments. The similarity score indicates textual closeness and does not indicate that the entity has been authorized or that the record belongs to the current applicant. The check inputs a retrieved material fragment and a proposed conclusion sentence, compares the entity and status fields in the fragment against the conclusion sentence, and observes whether the conclusion goes beyond what the fragment states.
- Treating a form submission as business execution. An interactive node collects form values. A form only collects values; business verification, approval, database writes, and external synchronization each need their own downstream implementation. The check inputs a form submission record and a proposed sentence stating the correction is complete, compares whether the submission action and the completion of the correction are the same fact, and observes whether the proposed sentence equates submission with completion.
How to verify the setup
Hypothetical drill sample: the first material text reads, "Trademark registration certificate No. 12345678 held by Company X, approved for use on Class 25 clothing goods, registration date 10 May 2023, valid until 9 May 2033." The second material text reads, "Brand owner A authorizes Company X to sell Class 25 clothing goods in mainland China, authorization period 1 January 2024 to 31 December 2025." The sentence to be judged reads, "Company X has obtained complete authorization for the Class 25 clothing category and can directly publish products." The handover request reads, "Please confirm whether this authorization chain meets the category access requirements." All of the above are hypothetical drill samples and do not involve real customers or legitimate identity numbers.
- Input the two material texts above and the proposed sentence. Compare "complete authorization" in the proposed sentence against the authorization period, territory, and goods category stated in the source texts. Observe whether the proposed sentence goes beyond what the source texts state. If the proposed sentence does not mention the authorization period and territorial limit, it is judged unsupported.
- Input the handover request and the material texts. Compare "whether it meets the category access requirements" in the request against whether the source texts state platform access rules. Observe whether the source texts contain a basis for an access decision. If the source texts contain only trademark and authorization information and no platform access rules, the request is judged pending verification and the evidence gap is recorded.
- Input an empty result list returned by a knowledge base retrieval and the downstream design description. Compare the empty result list against the downstream handling logic for empty results. Observe whether the downstream explicitly handles empty results. If the downstream design does not describe empty-result handling, it is judged unsupported, without claiming that a fictional rule retrieval necessarily returns an empty list.
This page addresses only marketplace category access, order fulfillment and after-sales question answering, and multi-turn prompts. During operator handover, the authorization state of materials, actions, and requests cannot be treated as authorization execution on the basis of retrieval or a form.