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Use Cases & Prompts

The Famulor MCP server and the Famulor Skill let you control the entire platform in plain language. This page shows what that looks like in practice — grouped by use case, with copy-paste prompts.
All prompts work in ChatGPT, Claude, Cursor, and any other connected MCP client. Setup: MCP Client.

Creating & optimizing assistants

The most common starting point: create, test, and iterate on voice agents — without opening the platform UI. Prompts:
Create a German inbound assistant "Lisa" for my hair salon.
Pipeline mode, female voice, GPT-4.1-mini. Tasks: take appointment
requests, quote prices, answer opening-hours questions.
Show me all available German voices and multimodal models.
My assistant #123 interrupts customers too often. Disable
interruptions and shorten the initial message to one sentence.
Enable a conversation-ended webhook for assistant "Lisa"
pointing at https://example.com/hook.
Best practice: Have the model call get_voices, get_languages, and get_models first instead of guessing IDs — e.g. “Show me the options first, then create…”.

Outbound campaigns & lead management

Set up campaigns, import leads, and control them — at scale. Prompts:
Create a campaign "Reactivation Q3" with assistant #45.
Calls Mon–Fri 10am–5pm only, max 2 retry attempts.
Add these leads to the campaign: [list of name + phone number].
Set the variable "product" to "Premium plan" on all of them.
Pause all running campaigns — we forgot about a public holiday.
Which leads in campaign #12 have status "not reached"?
Bump their priority.
Best practice: Always pass phone numbers in E.164 format (+49170…). Lead variables must match the variables defined on the assistant — you can’t invent new variable names per lead.

Call analysis & reporting

Query and analyze call data — the model filters, aggregates, and summarizes. Prompts:
Show all calls from today. On which ones was the call goal
not reached, and why?
Summarize the last 20 calls of assistant "Lisa":
what were the most common customer requests?
Get the transcript of call #9876 and suggest concrete
improvements to the system prompt.
Best practice: Combine analysis and action in one prompt: “Analyze this week’s calls and adjust the system prompt accordingly — show me the change before saving.”

Knowledge bases (RAG)

Connect knowledge so assistants answer from facts. Prompts:
Create a knowledge base "Menu" and ingest
https://my-restaurant.com/menu as a document.
Attach the knowledge base "Menu" to assistant #88 in
"prompt" mode so it always has the menu at hand.
Our prices changed — update the "Price list" document
in knowledge base #5.
Best practice: Use function_call mode (default) for on-demand facts, prompt mode when the bot needs content permanently (menus, delivery services). For multimodal/dualplex assistants, function_call is required.

Conversations, WhatsApp & SMS

Run chat channels — including human takeover. Prompts:
Show all open conversations. Where is a customer waiting
for a reply?
Take over conversation #321: disable the AI and send
"A colleague will be with you personally in a moment."
Send the WhatsApp template "appointment_reminder" to +49170…
with tomorrow's 2pm slot.
Send an SMS to +49171…: "We received your callback request."
Best practice: Before freeform WhatsApp, have the model check whether the 24h session window is open (get_whatsapp_session_status) — outside the window only templates are deliverable.

Phone numbers & SIP

Search, purchase, and manage numbers. Prompts:
Search for a German phone number with the 030 area code and buy it.
Give the number +4930… the nickname "Support Hotline Berlin".
Create a SIP trunk for our existing PBX: [credentials].
Best practice: Number purchases cost money and release_phone_number is irreversible — ask for a confirmation step before both.

Folders & organization

Folders and labels keep agencies and teams organized — especially with many assistants. Prompts:
Create a folder "Client: Dr. Meier Dental" and move
assistants #12 and #13 into it.
Create the labels "Production" (green) and "Test" (yellow)
and tag all assistants accordingly.
Which assistants have no folder yet? Suggest a sensible structure.
Best practice: An assistant lives in exactly one folder but can carry multiple labels — use folders for clients/projects, labels for status or environment.

Mid-call tools & automation

Custom HTTP integrations the assistant calls live during a conversation. Prompts:
Create a mid-call tool "check_availability" that calls
GET https://api.example.com/slots and returns free slots to the bot.
Build a tool that looks up order status by order number,
and attach it to assistant "Support Bot".
Best practice: Write tool descriptions from the bot’s perspective (“Call this tool when the customer asks about…”) — they control when the LLM uses the tool.

Guided onboarding with the Famulor Skill

The Famulor Skill complements the MCP server with industry knowledge and a structured 4-phase flow — ideal when a complete assistant needs to be built for a new client. Runs in Cursor, Claude Code, Codex, OpenCode, and Gemini CLI. Prompts:
Onboard a new client: Dr. Meier dental practice in Berlin.
Create an inbound bot for my restaurant — walk me through
the setup step by step.
New client, trades industry (emergency plumbing). Suggest the
typical tasks, a post-call schema, and an end_call description.
Test the assistant "Sofia" via chat: book a table for 4 on
Friday at 7pm and verify all data lands in the post-call schema.
The client finds the bot too formal. Rewrite the system prompt
in a more casual tone and show me the diff.
Best practice: Let the skill drive the flow — it asks phase by phase (discovery → tech → industry → system prompt) and proposes the right defaults per niche (voice, ambient sound, guardrails). Always have the system prompt confirmed before deployment.

End-to-end workflows

The real strength: multiple steps in a single request.
Onboard a new client: restaurant "Bella Vista".
1. Create a knowledge base from https://bellavista.de
2. Create an inbound assistant "Sofia" (female, German, pipeline)
   for reservations and menu questions
3. Connect both, create the folder "Bella Vista"
4. Finish with a summary of the configuration
Weekly report: list all calls from the last 7 days per assistant,
summarize success rates, and name the top 3 reasons goals
weren't reached.

General best practices

RuleWhy
Read before write”Show me first…” before changes — the model fetches real IDs instead of guessing
Confirm destructive actionsAsk for explicit confirmation on delete_*, campaign stops, and number releases
E.164 everywherePhone numbers always as +49… — other formats fail
Preview changes”Show me the new system prompt before you save it”
One workflow, one promptPhrase multi-step jobs as a numbered list — the model works through it in order
API key via OAuth onlyNever paste the key into configs or prompts — sign-in happens in the browser

Resources