recommend-drink
Suggest a drink from the available menu for a given occasion.| Property | Value |
|---|---|
| Name | recommend-drink |
| Parameter | occasion (string) |
Parameters
A short description of the context or mood for which a drink should be recommended. The server provides auto-completion with the following suggestions:
morning rush, afternoon break, late night, decaf.Behavior
When invoked, the prompt fetches the current menu fromCoffeeOrderApp and constructs the following message for the LLM:
MenuItem[] array serialized as pretty-printed JSON, giving it complete information about available drinks, pricing, milk options, and temperature options before making its recommendation.
summarize-open-orders
Summarize the current open order queue for a specific operational focus area.| Property | Value |
|---|---|
| Name | summarize-open-orders |
| Parameter | focus (string) |
Parameters
The perspective from which to summarize the queue. The server provides auto-completion with the following suggestions:
kitchen, pickup, operations.Behavior
When invoked, the prompt fetches all orders fromCoffeeOrderApp, filters out orders with status picked-up or cancelled, and constructs the following message for the LLM:
CoffeeOrder[] array — only pending, brewing, and ready orders — as pretty-printed JSON. The focus parameter steers the tone of the summary:
- kitchen — suitable for baristas preparing drinks; emphasizes what needs to be made.
- pickup — suitable for front-of-house; emphasizes orders ready for handoff.
- operations — suitable for managers; provides a broader throughput view.
The filtering logic mirrors the
coffee://orders/open resource exactly: orders with status picked-up or cancelled are excluded before the prompt is built.