What the documents look like
Cross-border standalone-site payment risk control centres on card-network disputes and receiving accounts. Order fulfilment tracking is not the organising concern here, even where shipping evidence appears. The working materials are payment chargeback notices, fraud order lists, invoices, and carrier proof of delivery. These arrive from Stripe or PayPal back offices, Shopify orders, carrier delivery records, and customer-service email. In copy drafting they serve as evidence: a proposed sentence that mentions refund timing, chargeback responsibility, or delivery status must map to the subject, object, and date range recorded in the chargeback notice, proof of delivery, or invoice. Update frequency is daily and per order. Copy verification proceeds against a single material version and does not imply batch synchronisation or a real-time trigger.
Constraints at the context limits step
The context window is set by the selected model's maximum context. The reply cap limits only the length of a single answer; the two cannot substitute for each other. The knowledge-base reference cap is controlled in tokens, and a long single passage may be truncated, so the question sample must be used to check whether the referenced content stayed complete. Memory turns carry earlier conversation forward, so the same question has a different input with empty history than with history; verification must hold the history condition fixed. When a fixed reply format is used, complete fields and successful parsing are the downstream conditions, and text length is not a basis for passing.
Hypothetical paper exercise sample. Material text one: "Order A-1042, delivered 12 March 2026, signed for by Li, carrier tracking number SF-7788." Material text two: "This chargeback notice states: the cardholder claims goods were not received; the dispute stage is pending review; no allocation of refund obligation is stated." Material text three: "Invoice INV-2201, issue date 5 March 2026, amount matches the order." The proposed sentence to be judged: "This store promises a full refund within seven days for all undelivered orders." The object of judgment is whether the refund promise in the proposed sentence is supported by the above materials; the subject is order A-1042; the period is March 2026; the fields are delivery status and refund obligation.
Configuration and implementation checks
| Configuration or check item | Use on this page | Condition |
|---|---|---|
| AI model maximum context | Hold material text and proposed sentence | Selected model's referenceable length covers this input; split materials when exceeded |
| Reply cap | Limit length of the drafting explanation | Grounds and handling action retained; truncation does not drop subject or date |
| Knowledge-base reference cap | Control referenced volume by token | A single material passage enters the reference complete, untruncated |
| Memory turns | Control history carried in | Same question checked separately with empty history and with history |
| Reply format json_schema | Structured field handoff | Fields complete and parsing succeeds; text length does not stand in |
| Minimum relevance | Filter low-relevance results | Applies only under semantic retrieval or result re-ranking; carries no permission or entity isolation |
The maximum-context row uses the model's documented capability, not a default value. The reply cap and reference cap are separate quantities measured in different units, and neither is treated as the other. For the memory-turns row, the comparison method is a paired request: one with empty history, one with history, comparing the actual input sent to the model. For json_schema, the observable result is field completeness and successful parsing, not character count. Minimum relevance is a filtering threshold, not a final ordering rule, and it does not exclude unrelated businesses or unauthorised records.
Three common errors
- Treating the reply cap as the whole context window. The reply cap constrains only answer length; when material text exceeds the model's maximum context it is still truncated, so the input and the comparison object fall out of alignment.
- Treating minimum relevance as entity or permission filtering. A similarity score does not distinguish business subjects and does not exclude unauthorised records; retrieval results and authorisation judgments are conflated.
- Reading a pending-review stage as a negative conclusion. The chargeback notice states the dispute stage is pending review and states no allocation of refund obligation, so the proposed sentence's refund promise is unsupported. It cannot be concluded from this that the material rules out a refund.
How to verify the setup
- Input the hypothetical sample's material texts one through three and the proposed sentence, then compare the phrase "undelivered" in the proposed sentence against the delivery record in material text one. Where the same order, same period, and same delivery field take mutually exclusive values, the result is a contradiction; where the material states no refund obligation, the result is unsupported.
- Input the same question under two conditions, empty history and with history, and compare the actual input sent to the model in each case. Where history changes the input, record the difference; where the two inputs match, history did not affect this judgment.
- Use a clearly labelled paper input of an empty reference result to check the downstream handoff design, comparing the downstream node's output and field completeness when no referenced content is present. When retrieval returns nothing, record an empty result. Do not infer that a fictional rule necessarily returns an empty set. For libraries across different vector models, first check the identifier and exclude non-matching ones; do not run cross-model retrieval to compare missed recalls.
These checks state expected observations without claiming that any test was performed. The pending-review stage does not prove absence of operating authority, and the chargeback notice's silence on refund obligation remains an evidence gap rather than an established fact.