What the documents look like
Platform product title and detail compliance handles the truthfulness of promotional copy and the display of qualification material. It does not handle parcel delivery. The daily materials for this category are the product title table, the detail page assets, the advertising prohibited-term list, and the quality inspection report. These materials determine what a draft may cite and what it may not cite. The product title table gives the product name, model, and specification. The detail page assets give images and layout. The advertising prohibited-term list gives expressions that may not appear. The quality inspection report gives the tested object, the test items, and the valid scope. Copy drafting extracts supportable promotional sentences from these materials, then uses context and token controls to bound the length of the referenced content.
The category updates weekly and on each new listing. This page addresses only the context and token step of product and marketing copy drafting. Whether a specific promotional sentence is supported by the materials is a separate question from whether the retrieval configuration is set up correctly.
Constraints at the context limits step
The context window is checked against the actual model capability, and the reply limit controls the length of a single answer. These are two different things, and treating the reply limit as the full context window will cause long materials to be misjudged as fully citable. The knowledge base reference limit is controlled by tokens, so a single long material segment may be truncated. Historical input affects retrieval results, so the same question may recall different content with an empty history and with a history. When a fixed reply format is used, the fields must be complete and parseable.
Hypothetical drill sample: the material text reads "Product name: portable folding table; model: FT-2024A; unfolded dimensions: 60cm x 40cm x 30cm; load capacity: 15kg. Quality inspection report number: Q-2024-0871, the tested object is the same model folding table, the test item is load capacity, and the conclusion is that it meets the commissioned requirements." The proposed draft sentence is "This product has a load capacity of up to 15kg and is suitable for outdoor camping." The judgment points are: the load capacity figure matches the material, and the use scenario "outdoor camping" is not stated in the material, so it is unsupported. The handover request is "Please confirm whether the product title may use the expression 'load capacity 15kg'", and the reply needs to check that the model and the tested object are the same.
The reference limit uses tokens as its documented unit. A single material segment that is long may be truncated, and the comparison is between the configured limit and the actual segment length in the sample. The minimum relevance score is a similarity threshold that takes effect only in semantic retrieval or when result reranking is used. It is a filter threshold, not a final sort rule, and it does not exclude unauthorized records or distinguish different subjects. Retrieval is not authorization. Forms collect values, and business verification, approval, database writes, and external synchronization require their stated downstream implementation. A pending review state is not an approval, and an offered option is not an execution.
Configuration and implementation checks
| Configuration item | Hypothetical starting value for this trial | Reason and comparison method |
|---|---|---|
| Reply limit | 800 tokens | Must hold the promotional sentence and the basis explanation; compare with 400 tokens to see whether truncation occurs |
| Reference limit | 2000 tokens | The materials include the title table and the inspection report; compare with 1000 tokens to see whether references are missed |
| Minimum relevance | 0.5 | Filters low-relevance segments; compare with 0.3 to see whether unrelated segments increase |
| Search mode | Hybrid retrieval | Model numbers and figures need exact hits; compare with semantic retrieval on number recall |
| Question optimization | Enabled | Multi-turn follow-ups need coreference completion; compare with disabled on retrieval term completeness |
| Reply format | json_schema | Fixed fields are needed for downstream parsing; compare with the default format on parse success |
These are hypothetical starting values for this trial, not official defaults. The reference limit is expressed in tokens. The minimum relevance score is a 0-1 value that filters low-relevance results and applies only in semantic retrieval or with result reranking. Hybrid retrieval combines semantic and full-text recall through RRF, and RRF is a fusion process for mixed results, not a switch. Reranking requires a model and must be enabled according to the settings. Image retrieval requires a corresponding image input and model capability. The optional paths in the overall retrieval flow do not all execute on every request.
Three common errors
- Treating the reply limit as the complete context window. The reply limit controls output length, while the context window is checked separately against model capability. Mixing the two causes long materials to be wrongly judged as fully citable. Check: input the sample material text and the proposed draft sentence, compare the configured reply limit against the model's documented context capability, and record whether the material segment exceeds the reply limit. If the material length exceeds the reply limit, the material is not fully citable within that reply limit.
- Treating the minimum relevance score as a permission or entity filter. Relevance is a similarity threshold, and it does not exclude unauthorized records or distinguish different subjects. Check: input the same question with an empty history and with a history, compare the two recall sets, and record the context difference when they differ. Do not judge the difference as a missed recall.
- Treating a pending review state as approved. When material is pending review, a draft sentence cannot be judged as supported on that basis, and the item must be recorded as pending verification. Check: input the sample material text and the proposed draft sentence, compare the load capacity figure in the draft against the figure in the material. When they match, that field is supported; when the use scenario is not stated in the material, record it as unsupported.
How to verify the setup
- Input the sample material text and the proposed draft sentence. Compare the load capacity figure in the draft sentence against the figure in the material. When the figures match, the field is supported. When the use scenario is not stated in the material, record it as unsupported. This verifies the primary task: whether a specific proposed copy sentence is supported by the supplied source wording and its limitations. It does not verify identity certification or report analysis.
- Input the same question with an empty history and with a history, and compare whether the two recall sets are identical. When they differ, record the context difference and do not judge it as a missed recall. The comparison is between the two recall sets, and the observable result is whether the sets differ.
- Input an empty result
[]to check the downstream parsing design. Compare whether the fields are complete and whether parsing succeeds. Do not claim that a fictional rule retrieval will necessarily return an empty result. The input is the empty result, the comparison is against the required field list, and the observable result is whether parsing succeeds.
For all three checks, the hypothetical material, draft sentence, and request are fully stated above. No test, deployment, approval, refund, or other business action has actually occurred. Where a document field is not provided, it remains unknown. Missing evidence remains missing.