What the documents look like
For staff training in Marketplace advertising, this page examines FastGPT multi-turn prompts. Inspect audience definitions, actual conversational history and absent course evidence in training questions. The examples are hypothetical.
Constraints at the multi-turn prompts step
An audience-analysis lesson can use proposed text about persona construction and preference identification, but those headings do not supply a complete operating course. Define the passages available this turn and the learning question, then inspect whether output imports an undocumented advertising process from history. If actual input contains only topic names, detailed steps cannot be verified from it. Identify the course source still needed; a continuing conversation does not establish complete training material.
Configuration and implementation checks
| Conversation or implementation check | Audience-training evidence | Inspection |
|---|---|---|
| Theme and course | Persona and preference headings are not a full process | Teaching support for detailed steps |
| Audience definition | Spending and price-sensitivity labels have conditions | No exclusivity inferred from wording alone |
| History handoff | Current audience and source scope | Lost subject or restriction |
| Course gap | The plan supplies no outline or content | Retest after obtaining the actual curriculum |
| Structured handoff | Separate parsing from procedural support | Complete fields do not establish complete content |
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 profile or preference headings become a complete advertising course, inspect input and sources for every step. Topic names cannot verify procedures; obtain an outline or instructions.
- If high-spending and price-sensitive labels become mutually exclusive, retain dimensions, periods and sample definitions. Inspect omitted conditions rather than judging audiences from wording alone.
- If another historical audience enters current training, compare present sources, history and output with an empty-history test. Restore identity rather than treating older steps as current curriculum.
How to verify the setup
A plan mentioning a need for strategy training without an outline cannot support a course presented as confirmed. Distinguish existing themes from missing teaching evidence before obtaining the actual curriculum or process source. Record its version and current input, then repeat the learning question and an exception question. Where a fixed response format is used, inspect parsing before tracing procedures and definitions. Complete fields must not conceal absent course content.
| Material context | Scope |
|---|---|
| Document types | Advertising Plan, Keyword Report, Audience Package Description and Conversion Attribution Table |
| Candidate sources | Juliang Qianchuan, JD Kuaiche advertising, Alimama and Store Transaction Data |
| Technical baseline | FastGPT v4.17.2 |