What the documents look like
Platform listing compliance covers advertising truthfulness and qualification display. It does not cover parcel delivery, so the working materials differ from fulfillment operations. The main sources are the platform rule center, advertising-law compliance checklists, brand asset libraries and inspection-agency reports. Daily documents are the product title table, detail-page assets, the prohibited-words list and inspection reports. Updates arrive weekly and with every new listing. The most time-consuming steps are checking absolute claims, comparing physical parameters and replacing non-compliant assets.
In store service and internal training, these materials pass through multi-turn dialogue and prompts. Store staff submit a title table or detail-page asset, and the configured application checks it within the prompt's stated scope. The model is not asked to supply business facts that the submitted materials do not contain.
Constraints at the multi-turn prompts step
Multi-turn dialogue requires checking which context is actually carried in. When a new session passes no chatId, the database context is not used and the context is built entirely from the messages array. When a non-empty chatId is passed, the session is fetched automatically and the last message item becomes the user question. The prompt needs to state the material scope, the answering task and how to behave when evidence is missing.
Reply format follows what consumes the output. Selecting json_schema requires filling in the corresponding format requirements and verifying the returned structure. Model and length settings need checking against the context and reply settings the model supports, with long documents and follow-up combinations tested. Question optimization during continuous knowledge-base dialogue requires checking reference resolution and question expansion; short questions are not all assumed to fit.
Hypothetical drill sample: a store operator submits one item for review. The material text reads: "The store sells a certain insulated cup; the drafted title is 'the lowest price insulated cup on the entire internet'; the detail page attaches inspection report number A-2024-001, report date March 2024, test item thermal performance." The sentence to be judged is: "This product title uses 'lowest price on the entire internet'; please confirm whether it can be kept." The request is pending review and has no authorization to execute changes.
Configuration and implementation checks
The following settings relate to this sample and only to this function and primary task. They are documented settings or implementation checks, not official defaults.
| Configuration item | Hypothetical starting point for this trial | How to check |
|---|---|---|
| Prompt | State the material scope as title table, detail-page assets, prohibited-words list, inspection reports | Check whether the prompt requires stating unknowns when evidence is missing |
| Memory turns | Keep a small number of prior turns | Check whether the carried context matches the current session |
| Reply format | Keep default | If a later step needs a fixed structure, select json_schema and fill in format requirements |
| Temperature | Lower | Compliance checking needs stable answers; compare against a higher value |
| Multimodal recognition | Enable image recognition according to model capability | Check whether the model dialog shows image recognition as supported |
| Thinking configuration | Default | Check whether the model shows thinking configuration options |
The lower temperature is chosen here because compliance checking needs stable answers; comparing against a higher value shows whether answers diverge. Keeping a small number of prior turns is compared against keeping none, to observe whether prior information is lost.
Three common errors
- Treating retrieval or form submission as authorized execution. In the sample the pending request has not been approved, and finding an inspection report does not mean the title change is authorized. Check the input as the sample request, compare the request status against the authorization field, and observe whether it remains pending.
- Treating a similarity score as a permission or entity filter. The relevance score returned by retrieval does not exclude unrelated business or unauthorized records. Check the input as the retrieval result list, compare the score against permission fields, and observe whether a permission check is missing.
- Treating the model reply-format default as a fixed structure. In the sample the reply format stays default; if a later step needs to read fixed fields, json_schema must be selected and format requirements filled in. Check the input as the format configuration, compare the downstream reading requirement against the returned structure, and observe whether they match.
How to verify the setup
- Use the sample material text and the drafted sentence. The input is the "lowest price on the entire internet" title sentence and inspection report number A-2024-001. Compare whether the prompt requires checking the prohibited-words list, and observe whether the answer states that the wording needs further verification; when unsupported, record the gap.
- Use the sample request. The input is the pending title-change request. Compare the request status against the authorization boundary, and observe whether it remains pending; do not treat pending as approved.
- Use an empty-result input of []. The input is an explicit paper empty list. Compare whether the downstream design handles empty results, and observe whether it treats them as missing evidence; do not claim that a fictional rule lookup necessarily returns an empty list.
These checks are paper reviews and were not actually executed. Missing evidence remains missing, and the pending status remains pending.