MasterPrompt VaultBY MASTERESTAURANT

AI assistant · N4 Executable plan

◆ Included in the annual plan⭐ Reviews, Reputation and Automated Messagingv1.1.1 · 2026-08-26

Automated Messaging Builder for Restaurants

Writes the messages your restaurant answers automatically -welcome, booking, delivery, opening hours, address, menu, events, frequent questions and follow-up- each with its exact trigger, its answer time and the border of what an automatic reply must never answer.

N4
Depth
12/23
Your data
3
Compatible AIs
5
Steps to use it
Depth of the resulttap a level to see what you get
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N4Executable plan

A plan with owners, deadlines and the metric you review. Not advice: an agenda someone can execute on Monday.

◆ This assistant 23 of the 164 published assistants are at this level

Is this for you?

What it does and what you get

  • There are eight or ten questions your restaurant answers a hundred times a month and always the same way, answered by hand by whoever has the phone nearby, who is rarely the right person at the right moment.
  • The expensive mistake is not failing to automate: it is automating too much and promising what cannot be delivered, because a message saying "of course, we'll see you tonight" without knowing whether a table exists turns a sale into an argument at the door.
  • This assistant separates what does not change -hours, address, the menu, how to order- from what depends on today, writes the first part and gives the second an answer time, an owner and a handover to a person.
  • The nine message types are one repertoire of the same method, not nine assistants: the trigger changes, the rule does not.

What you end up with

Five chained deliverables: the counted inventory of what people ask, the repertoire of the nine messages with trigger and answer time, the texts ready to paste, the handover to a person by time slot and the maintenance sheet with owner and review date.

EXAMPLE This is what you getAn example built with Sazón de Origen, the house's fictional restaurant.Not your data: your result is built with YOUR restaurant's.See the full example →

Sample result

Sazón de OrigenFictional contemporary Colombian restaurant in Medellín, 2 locations, 6 years in business. Every sample result in the library comes from this same case. Fictional restaurant

The owner asked this: "We answer the same thing all day on WhatsApp: opening hours, whether delivery reaches a given neighbourhood and whether there is a table. Two locations, and all I have is WhatsApp Business, nothing else to automate with."

Nobody was asked what people ask: the history was read. Between 21 July and 17 August, 709 messages came in through WhatsApp and Instagram across both locations, and they were grouped by question in the guest's own words.

Question in the guest's wordsTimes in 4 weeksChannelChanges today?Decision
"What time do you open?"168WhatsAppNoAutomatic
"Do you deliver to my neighbourhood?"131WhatsAppThe area no, the shift yesMixed
"Do you have a table for 6 at 8?"96WhatsAppYesTo a person
"Send me the menu" / "how much is the bandeja?"88Instagram and WhatsAppNoAutomatic
"Where are you? Is there parking?"74InstagramNoAutomatic
"Can you take 20 people on Saturday?"41WhatsAppCapacity no, the date yesMixed
"Is there any sancocho left?"37WhatsAppYesTo a person
"Do you take bank transfers?"29WhatsAppNoAutomatic
45 different questions, once each45Both—Out

Eight questions carry 664 of the 709 messages, 94%. The other 45 are 45 different questions that showed up once: none gets automated, because automating what happens once is exactly the work nobody maintains and the one that six months from now will be saying something false.

Of those 664: 359 answer themselves in full without knowing anything about today (54%), 133 can never be answered alone —table and dish availability— and 172 are mixed, where the automatic reply hands over the fixed half and announces the missing one. Adding the fixed ones and the fixed half of the mixed, the first message settles or advances 531 of 664 conversations, 80%, without anyone on the team touching the phone. Illustrative figures, drawn from the history you provided.

SUPUESTO: there is no house figure for how many messages a restaurant this size receives per month, so the 709 threads counted over the 4 weeks of YOUR history are used, not an industry average. If the real volume were double, the midday answer time no longer holds with the hands available and somebody else has to be put behind the phone before the second message is switched on.

This is 3 of 5 parts. Behind the wall sit the two pieces that hold the promise up. The handover table, slot by slot, with who is behind it, the time promised, what is not promised in that slot and what happens when the time runs out: it carries the slot where the honest answer is "after 2:30", the handover line that goes identical in all nine messages, the one-number rule with a label per location and the 10:15 p.m. cut-off with zero unanswered threads. And the maintenance sheet, with owner, last review, next date and the fact that expires each row early, plus the unknown-number test on the first Monday and the three figures read that day.

See the full example — free account

Works with these AIs

ChatGPT — the best for this assistant The best fit here: it counts and sorts the inventory of questions and then writes the short texts with tone, without switching register in between.

How to use it

Before opening the AI, pull the message history of the last four weeks and count the repeating questions; without that count the assistant works on what you imagine people ask.
Copy the assistant into your preferred AI along with your business details and paste in the counted list of questions.
Answer what it asks about who replies in each time slot and the hours when somebody is genuinely behind the phone.
Paste the texts into the quick replies and the away message of your WhatsApp Business, one at a time, starting with the most frequent question.
Put the maintenance sheet on the calendar and review it the day the menu, the opening hours or a location changes.

Which of your data it uses

12
of 23

This assistant works with 12 of the 23 fields in «My Restaurant», among them Restaurant name, Business type and City and country. It does not ask out of curiosity: these are what make the answer speak about YOUR scale instead of an industry average — the same calculation on a business of another size returns a number you cannot decide with. You fill them once and they apply across the library, so the second assistant you open already starts with them in place. Whatever you leave blank, the assistant asks for one thing at a time instead of inventing it, and says so before answering, so you know what it is working from.

Restaurant nameBusiness typeCity and countryNumber of locationsYour main guestActive social channels (with the @ or the link)Active sales channelsStrong and slow daypartsTeam sizeBest-selling dishesMenu price rangeCommunication tone

Always up to date

Every assistant carries a visible version and date. When an AI changes how it works, the assistant's version goes up and you see what changed.

Same method, another variant

Inside the app this is a single control: you press it and the assistant reframes itself, including the variants that don't appear here because they don't have their own page yet.

Where it lands

More assistants in this category

Included in the always-growing library

Access to every published assistant, adapted to your AI and personalised with your restaurant's data, updates included.

Automated Messaging Builder for RestaurantsN4 · Executable plan · Included in the annual plan See the plan

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