What the documents look like
Store counts and loss control work around book-to-physical differences and shrinkage. The category does not handle supplier payables. The main data sources are POS inventory, WMS, monitoring systems and the SB/T counting standard. Day-to-day documents are count sheets, variance analyses, write-off approvals and monitoring review records. Typical parties are the loss prevention department, store inventory keepers and financial auditors. Errors produce distorted inventory, inflated gross margin or employee fraud.
For product and marketing copy drafting, the material usually comes from count conclusions, shrinkage attribution or write-off records. Outputs may be internal store notices, variance explanations or customer-facing notices. The wording must stay consistent with the count sheet and variance analysis. A difference still under verification cannot be written as a confirmed loss.
Constraints at the multi-turn prompts step
The multi-turn prompts step needs a clear statement of the material scope, the answering task and the handling of missing evidence. For history, check the context actually carried in, and separate a new session from a continued session. For question optimization, knowledge-base continuous dialogue requires checking reference resolution and question expansion; short questions do not all qualify. For model and length, check the supported context and reply settings, and test long documents combined with follow-up questions. For reply format, choose according to downstream handling; when json_schema is selected, fill in the corresponding format requirements and verify the returned structure.
Hypothetical exercise sample
Material text for checking (hypothetical, not a real record):
31 March 2025 closed-store count record: Store A beverage section book inventory 120 units, physical count 114 units, difference 6 units, difference cause field reads "pending verification". The same-day monitoring review record shows movement by a person in that area at 21:40 on 28 March, with no authorization information noted.
One draft sentence to be judged (hypothetical):
"Investigation found that the 6-unit difference in Store A beverage section was caused by unauthorized movement by an employee, and the loss is confirmed."
Judgment point: the material's difference cause field reads "pending verification", and the monitoring review record notes no authorization information. The draft sentence rewrites "pending verification" as "confirmed loss" and adds an "unauthorized movement" conclusion the material does not contain. In a comparison of the same subject, same period and same field, the original status and the draft conclusion do not agree. The draft sentence is not supported by the material and should remain pending verification.
Configuration and implementation checks
The table below addresses the sample above and lists officially described settings or implementation checks relevant to this feature and primary task. The values are starting points for this hypothetical exercise, not official defaults.
| Configuration item | Hypothetical exercise starting point and reason | Comparison method |
|---|---|---|
| Memory turns | Set to 2 turns; the sample involves one material check and one draft sentence | Compare with 0 turns and observe whether the material text can still be quoted |
| Reply limit | Set to 500; the sample draft sentence is short | Compare with 200 and observe whether the draft sentence is truncated |
| Temperature | Set to a low value; the sample requires stable restatement of material status | Compare with a high value and observe whether the draft sentence introduces conclusions outside the material |
| Reply format | Keep default; the sample has no fixed-structure downstream handling | If changed to json_schema, fill in format requirements and check the returned structure |
| Multimodal recognition | The sample contains monitoring review record text and no image input | Check whether the current model shows a multimodal option; do not enable it when there is no image input |
| Hide AI output | Keep off; the sample needs the draft sentence to be viewed directly | Compare with on and observe whether the draft sentence can still be obtained through a downstream node |
Three common errors
- Rewriting a "pending verification" status in the material as "confirmed". The input is the original text of the difference cause field. Compare the draft sentence conclusion with the original status and observe whether the draft sentence contains a confirming statement the material does not carry. If it does, the draft sentence is not supported by the material.
- Treating movement in the monitoring review record as unauthorized directly. The input is the original monitoring review record text. Compare whether the draft sentence adds authorization information and observe whether the original text notes an authorization conclusion. When the original text notes none, the conclusion remains unsupported.
- Treating a retrieval relevance score as a permission or entity filter. The input is the score field returned by retrieval. Compare that field with the target store and target period identifiers and observe whether unrelated records are excluded on the score alone. A relevance score does not perform permission or entity separation.
How to verify the setup
- Input the hypothetical material text and draft sentence above. Compare the draft sentence conclusion with the original difference cause field status and observe whether the draft sentence rewrites "pending verification" as a confirming statement. If it does, judge it unsupported.
- Input the hypothetical monitoring review record and draft sentence above. Compare whether the draft sentence adds an authorization conclusion and observe whether the original text notes authorization information. When the original text notes none, judge it an evidence gap.
- Input a hypothetical empty result [] and the downstream handling design. Compare whether the downstream handles the empty result explicitly and observe whether the downstream output depends on a fabricated retrieval return. If the downstream design assumes retrieval always returns records, judge it a handling defect.