What the documents look like
Returned-goods inspection handles reverse parcels and item grades. It does not handle outbound picking and packing for new orders. The main data sources are the WMS return module, platform after-sales records, carrier return parcels, and the inspection station. The daily documents are return inbound orders, inspection photos, grade determination tables, and resale listing forms.
When a draft of resale copy is prepared, the copy basis comes from the grade and status already recorded in these materials. Performance details, condition details, or authorization scope not stated in the materials remain unknown. The context and token step matters because the length of content a model can reference in a single request is limited. A return inbound order, photo descriptions, and a grade determination table combined can exceed the referenceable range, so the material needs to be trimmed by task.
Update frequency does not change this page's feature. It is omitted here.
Constraints at the context limits step
The reference upper limit is controlled by tokens, not by item count. When a single passage is too long, later content may be trimmed. The minimum relevance value takes effect only in semantic retrieval or when result reranking is used. It is a filtering threshold and does not perform entity or permission isolation. Semantic recall and relevance scores do not distinguish items, documents, or authorization scope. Retrieved results require manual checking of the subject and the period. Question optimization adds one model call before retrieval. In continuous follow-up scenarios it can complete references, and response time increases accordingly. The reply upper limit controls the length of a single answer. It is not the same concept as the model context window, and the reply upper limit cannot be treated as the full context capacity.
Hypothetical exercise sample: On 3 June 2025, an after-sales warehouse inspector processes return inbound order TH-20250603-018. The item is a portable juicer. The grade determination table records the status as "minor scratches on the housing, function test normal, resellable." The inspection photos show the cup body and blade base intact. The proposed draft sentence is: "This item is brand new and unused, functions perfectly, and supports seven-day no-reason return and exchange." To be determined: whether "brand new and unused" in the proposed sentence matches the status recorded in the materials, and whether "supports seven-day no-reason return and exchange" has corresponding support in the materials.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison object |
|---|---|---|
| Reference upper limit | Hypothetically set to 2000 tokens | Compared with the combined length of the return inbound order, grade determination table, and photo descriptions, to observe whether material is trimmed |
| Minimum relevance | Hypothetically set to 0.3 | Compared with the score distribution returned by semantic retrieval, to observe whether low-relevance passages still enter the reference |
| Reply upper limit | Hypothetically set to 600 tokens | Compared with the expected length of the proposed sentence plus basis explanation, to observe whether the answer is truncated early |
| Memory turns | Hypothetically set to 2 turns | Compared with a single independent drafting scenario, to observe whether history brings in unrelated content |
| Question optimization | Hypothetically enabled | Compared with the same question when disabled, to observe whether reference completion changes the recalled content |
| Reply format | Hypothetically kept at default | Compared with a scenario that needs fixed fields for downstream use, to observe whether fields are complete |
These are implementation checks, not documented default values. Each starting point is chosen for this exercise and compared against the stated object.
Three common errors
- Treating minimum relevance as a permission or entity filter. Observable error: assuming that raising relevance excludes other items or unauthorized documents. Executable check: input the same question, compare the subject and document number in returned content under different relevance settings, and observe whether records of other items still appear.
- Treating the reply upper limit as the full context window. Observable error: when total material length exceeds the model context, only raising the reply upper limit. Executable check: count the total tokens of the material and the model context value, compare the two, and observe whether the excess portion is not sent to the model.
- Replacing recorded material with an unstated promotional sentence. Observable error: the proposed sentence writes "brand new and unused" while the grade determination table only records "resellable." Executable check: compare the proposed sentence with the source text sentence by sentence, compare the subject and the status field value, and observe whether wording not stated in the materials appears.
How to verify the setup
- Verification one: input the grade determination table source text from the hypothetical sample and the proposed sentence. Compare "minor scratches on the housing, function test normal, resellable" with "brand new and unused." Observe whether the output points out that this wording is not supported by the materials. If the output directly adopts the proposed sentence, the result is not passed.
- Verification two: input return inbound order TH-20250603-018 and the question "can this item be resold." Compare whether the referenced content includes the status field of the grade determination table. Observe whether the status field is fully retained under the reference upper limit setting. If the status field is trimmed, the reference upper limit needs adjustment.
- Verification three: use the paper input of an empty result
[]to check the downstream handling design. Compare the downstream node's handling path for empty references. Observe whether unsupported copy generation occurs. If the downstream still outputs a promotional sentence when references are empty, the handling design has a gap. All of the above are paper checks and were not actually executed.
The empty-reference check uses a clearly labelled paper input and does not claim that a fictional rule retrieval necessarily returns []. Cross-model libraries cannot be jointly associated. Check identifiers first, exclude those that do not match, and record actual observations. Do not fabricate run results such as missed recall or redundant returns after joint association.