What the documents look like
For copy drafting in Cross-border settlements, this page examines FastGPT multi-turn prompts. Separate the support provided by sales records from popularity and product-positioning claims. The examples are hypothetical.
Constraints at the multi-turn prompts step
The proposed settlement statement supplies sales quantity and sales amount for Product G, while the writing request asks for popularity claims. Separate those scopes first: the record can support a description of the recorded sales, while popularity needs an explicit comparison basis. Define the current settlement material as the prompt’s source and inspect the actual input for this turn. Check that performance attributed to another product in history does not enter this draft. An absent evaluation criterion should remain unresolved through further revisions.
Configuration and implementation checks
| Check | Input condition for this task | Acceptance evidence |
|---|---|---|
| Writing scope | Product G has quantity and amount records only | Distinguish sales description from popularity evidence |
| Supplied history | The subject remains the current Product G | Compare fresh input with actual submitted history |
| Question optimization | Retain Product H and both amount sources | Inspect unresolved currency and period conditions |
| Missing content | Product I has no feature or audience source | Trace each audience or benefit claim |
| Response handoff | Choose a format for the actual downstream need | Inspect parsing separately from field support |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Prompt and task | Define sources, the task and evidence-gap handling. |
Conversation history | Inspect the history actually submitted. |
Question optimization | Review reference resolution and question expansion. |
Model and length | Inspect context and reply length separately. |
Reply format | json_schema needs its format and parsing validation. |
Three common errors
- If product G’s settlement sales become definite popularity, inspect comparison criteria and periods beside the added conclusion. Recorded sales supply no evaluation basis automatically.
- If one earlier value overwrites another record for H, inspect settlement, reconciliation and optimized question. Preserve period, currency and definitions before judging a difference erroneous.
- If I lacks positioning but borrows G or H’s users and use, compare subjects, history and draft. Locate cross-product borrowing; settlement information supplies no product features or audience evidence.
How to verify the setup
Sales information for Product I supplies no evidence for its product characteristics or target audience. During further copy revisions, inspect whether the answer invents an audience, use or distinctive benefit from the product name or sales record. Mark each unsupported statement. After obtaining the product description and positioning sources, record the material actually entering the new turn and review the draft again. Where the copy has a structured downstream format, acceptance must distinguish parseable fields from evidence supporting their contents.
| Material context | Scope |
|---|---|
| Document types | Platform Settlement Statement, Exchange Rate Sheet, Service Fee Invoice and Collection Reconciliation Sheet |
| Candidate sources | Platform Settlement Center, Bank Statement, Payment Institution Backend and ERP Orders |
| Technical baseline | FastGPT v4.17.2 |