What the documents look like
An MCN agency manages long-term account compliance for several creators at once, so the working material differs from a single brand campaign. The daily and weekly documents include creator signing contracts, training records, violation handling forms, and account schedules. The data sources are the MCN backend, platform violation notices, creator account data, and the contract ledger.
For product and marketing copy drafting, the relevant parts of those documents are the authorization scope, product information, and compliance constraints. Materials update daily or weekly. This page reads the conversation and variables actually passed in; it does not infer any batch synchronization mechanism.
The drafting work sits inside a wider operation where a wrong sentence can lead to account bans, terminated cooperation, or agency compensation. That risk shapes how prompts must be written: the prompt states the material scope, the answering task, and how to handle missing evidence, so the model does not invent business facts.
Constraints at the multi-turn prompts step
Multi-turn dialogue requires checking the context actually carried into the request and distinguishing a new session from a continuing session. When a knowledge base is used across turns, check pronoun resolution and question expansion; short questions do not all behave the same way. Model context length and reply length are checked against the model's actual capability. Reply format follows what the downstream step needs; when json_schema is selected, the corresponding format requirement is filled in and the returned structure is verified.
Hypothetical drill sample: the material text reads, "The livestream promotion cooperation contract signed by Creator A and the agency provides that from March 1, 2025 to March 31, 2025, Creator A may promote Brand B's skincare serum, and the promotional wording is limited to 'hydrating and moisturizing'." The proposed draft sentence reads, "Creator A may continue to promote Brand B's skincare serum in April 2025 and may use the promotional wording 'whitening and spot removal'." The request to be judged is, "Based on the material above, judge whether the proposed draft sentence can be delivered." The material covers only March and "hydrating and moisturizing"; April and "whitening and spot removal" have no basis.
Configuration and implementation checks
| Configuration | Use on this page | How to check |
|---|---|---|
| AI model | Select a model with the needed context length and tool-calling ability | Compare against the maximum context and capability shown in the model selection box |
| Memory turns | Control how many earlier turns are carried in, supporting multi-turn follow-up | For this hypothetical trial, start with a small number of history turns and compare with output produced without history |
| Reply limit | Limit the length of a single reply | Turn it on and set it with the slider, then compare against the long-copy requirement |
| Temperature | Control how far the copy diverges | Copy scenarios may be set somewhat higher; compare with a stable question-answering scenario |
| Reply format | Select json_schema when a fixed structure is needed and fill in the format requirement | Check whether the returned structure matches the filled requirement |
| Thinking configuration | Complex judgments may use a higher thinking strength | Select from the levels shown in the dialog and compare with the default level |
The starting value for memory turns is a hypothetical trial choice, not an official default. It is chosen to test whether a small amount of history is enough to resolve a follow-up reference, and it is compared against a request that carries no history at all.
Three common errors
- Treating a time or promotional wording not covered by the material as already authorized. The input is the material text and the proposed draft sentence. The comparison is the scope of each. The observable result is that the draft sentence falls outside the material scope, because it names April 2025 and "whitening and spot removal" while the material covers only March and "hydrating and moisturizing."
- Mixing a new session with a continuing session. The input is a follow-up request using the same
chatIdand a new request using a differentchatId. The comparison is the history actually carried in. The observable result is that the continuing session reads the database session, while the new session uses only the passedmessages. - Treating a similarity score as a permission or entity filter. The input is a retrieval query containing records of unrelated creators. The comparison is the returned
quoteList. The observable result is that the similarity score reflects text relatedness only and does not exclude unauthorized records. Retrieval is not authorization.
How to verify the setup
- Enter the material text and the proposed draft sentence from the hypothetical sample above. Compare whether the time and the promotional wording in the draft sentence fall inside the material scope. The expected result is that they fall outside it, and the response indicates missing evidence rather than supplying a business fact.
- Enter a follow-up request using the same
chatId. Compare whether the returnedhistoryPreviewcontains content from the previous turn. The expected result is that the continuing session carries the history in. Enter a request with a newchatId; the expected result is that only the currentmessagesare included. - Enter a query with no matching material. Compare the returned
quoteList. The expected result is an empty list. Use the paper input[]to check how the downstream node is designed to handle an empty result; do not assume retrieval always returns an empty list. Because retrieval is not authorization, an empty or non-emptyquoteListdoes not by itself confirm that a record is permitted or excluded.