What the documents look like
Wholesale stall trading runs on on-site bargaining and consignment shipping. The working materials are purchase slips, handwritten sales notes, stall lease contracts and payment receipts. These documents arrive scattered and in inconsistent formats, and the name, quantity and price of one batch of goods can be spread across several sheets of paper. When drafting product and marketing copy, the model has to pull citable statements out of these materials, and the context and token settings decide whether the material fits in full and whether quoted content gets trimmed.
Two facts about this category shape the drafting step directly. Materials are handwritten and fragmented, so a single sales note may carry only one line of goods with no statement about stock levels or supply commitments. Trading depends on on-site bargaining and consignment, so the wording that ends up in copy often refers to terms that were agreed verbally and never written onto any of the four document types. Both facts mean the drafting step has to stay close to what the paper actually records.
Constraints at the context limits step
Model context is checked against the actual capability of the selected model. The reply cap is not the same thing as the full context window. The knowledge base reference limit is controlled by tokens, so a long single document may be trimmed, and the quoted content has to be checked against a question sample to see whether it stayed complete. History input occupies context, so the same question produces different input with empty history and with history, and the two cases are checked separately. When a fixed reply format is used, complete fields and successful parsing are the test; text length cannot substitute for that.
Hypothetical drill sample: the material text reads "Stall A issued a handwritten sales note to Buyer B on 1 March 2025, recording dried chilli 200 jin, unit price 12 yuan per jin, total payment 2400 yuan, with the remark 'settled within three days'"; "the stall lease contract shows Stall A's term runs to 31 December 2025, monthly rent 3000 yuan". The draft sentence to be judged is "This stall has ample dried chilli stock in hand, supports settlement within three days, and supplies steadily over the long term". Judgement points: the material records only one sales note with its goods name, quantity, unit price and settlement deadline. It does not record any in-stock status and does not record any long-term supply commitment. In the draft sentence, "ample stock in hand" and "supplies steadily over the long term" have no support in the material, while "settlement within three days" matches the sales note remark.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this drill | Reason for the choice and comparison method |
|---|---|---|
| Model context | The value actually displayed for the selected model | Compare with the total length of the material to confirm the sales note and lease contract can both fit |
| Reply cap | Set to 800 tokens for this drill | Compare with the draft sentence plus its supporting explanation to observe truncation |
| Knowledge base reference limit | Set to 2000 tokens for this drill | Compare with the text length of a single sales note to check whether the quote stays complete |
| History turns | Set to 2 turns for this drill | Compare with the empty-history input to observe whether history affects material quoting |
| Reply format | json_schema selected for this drill | Compare with the field list to check whether goods name, quantity and price fields are complete |
| Minimum relevance | Set to 0.5 for this drill | Compare with the semantic retrieval score to observe whether low-scoring material is filtered |
These values are hypothetical starting points for this drill, not official defaults. Minimum relevance only filters low-relevance results; it does not perform permission or entity isolation.
Three common errors
- Treating the reply cap as the full context window. Observable error: when the total material length exceeds the reply cap, the material is assumed not to fit. Check: input the full text of the sales note and the lease contract, compare total material length with the displayed model context, and observe whether the material is included in full.
- Using minimum relevance to exclude unrelated business. Observable error: raising minimum relevance is assumed to filter records from other stalls or buyers. Check: input material from one stall, compare the retrieval results with the material subject, and observe whether results still contain records from other subjects.
- Treating promotional wording in the draft sentence as supported by the material. Observable error: the material records no stock status, yet the draft sentence writes "ample stock in hand". Check: input the material text and the draft sentence, compare each phrase with the material fields, and observe whether "ample stock in hand" has a corresponding record.
How to verify the setup
- Input the sales note and lease contract text from the hypothetical sample, and compare total material length with the displayed model context. If the material is included in full and the basis for the draft sentence can be traced to the source text, the condition is met; if the material is trimmed, record the trim position.
- Input the draft sentence "This stall has ample dried chilli stock in hand, supports settlement within three days, and supplies steadily over the long term", and compare "ample stock in hand" and "supplies steadily over the long term" with the material fields. If the material has no corresponding record, judge the phrase unsupported; if the material has a corresponding record, judge it supported. "Settlement within three days" matches the sales note remark and is judged supported.
- Use the explicit paper input [] to check the empty-result handoff design, and observe whether the downstream node handles it as an empty reference. No claim can be made that a fictional rule search necessarily returns []. Libraries across different vector models cannot be associated together; check the identifier first, exclude those that do not match, record the actual observation, and do not run a cross-model retrieval to compare missed recalls.
This page covers only wholesale stall trading / product and marketing copy drafting / context and token. Whether a specific promotional sentence in product copy is supported by the material cannot be turned into an enterprise identity certification tutorial.