What the documents look like
For operating reviews in Retail checkout and loyalty, this page examines FastGPT tool calls. A cashier-and-membership report separates rules, transactions and refunds. A tool cannot derive realized customer benefits from promotion material. The examples are hypothetical.
Constraints at the tool calls step
Proposed membership rules cover selected products, a cashier report covers one shift, an anomalous refund remains unresolved and label assets are planned. Organize passages without prices, points figures or transaction effects. Rules establish conditions, not performed benefits. Shift records do not cover the whole period, and label plans do not establish replacement. Inputs need product, shift and origin rather than inference from the store name.
Configuration and implementation checks
| Membership-cashier report tool | Proposed scope | Actual check |
|---|---|---|
| Rule applicability | Selected products | Not a performed benefit |
| Shift report | One shift only | Not the whole period |
| Refund record | Anomaly unresolved | Actual outcome |
| Label assets | Planned version | Not replaced |
| Parameter origin | Product and shift evidence | No guessed missing inputs |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Tool description | Describe purpose, inputs and non-applicable situations. |
Tool parameters | Inspect module and plugin parameters separately. |
Required parameters | The model may not invoke a tool without suitable required inputs. |
Tool connections | Available tools must connect to the calling module. |
Tool-call termination | Termination ends the call without a later AI summary. |
Three common errors
Rules promoted to delivered benefit need the actual transaction. One shift expanded to the period needs coverage beside input. An unresolved refund promoted to handling needs a genuine outcome. These inspect execution, scope and stage independently of returned text.
How to verify the setup
Compare input and raw return. Added transaction evidence changes that transaction alone while other customers and refunds remain unresolved. Populated parameters need source checks; missing suitable input may prevent invocation without promised automatic questioning. Checkout, points and refunds need separate authority and receipts. Termination supplies no subsequent AI summary and establishes no implemented store promotion.
| Material context | Scope |
|---|---|
| Document types | Promotional Price Tag, Member Points Rules, Daily Cashier Report and Abnormal Refund Order |
| Candidate sources | POS System, Member CRM, Payment Platform and Price Tag System |
| Technical baseline | FastGPT v4.17.2 |