Install and use the Famulor.io Skill to let AI agents build and manage assistants, campaigns, knowledge bases, and messaging workflows via the Famulor API.
The heart of the skill: a structured 4-phase flow that turns a client conversation into a fully deployed assistant. The agent asks phase by phase — not everything at once.
Phase
Content
1 — Discovery
Company name, industry, assistant name, call direction (inbound/outbound)
2 — Technical configuration
Engine type (pipeline / multimodal / dualplex), primary and secondary languages, voice (male/female), ambient sound
3 — Intelligent configuration
Industry-specific tasks, knowledge base (website/documents), post-call schema, initial greeting
4 — System prompt & creation
Generate a tailored system prompt, client confirms, assistant is created via API
Behind it sits niche intelligence: a bundled knowledge base (references/nischen_intelligenz.md) with industry know-how for hair salons, medical practices, restaurants, real estate, trades, law firms, and more — the agent proactively asks the right follow-up questions per industry.
During creation the skill configures the built-in conversation tools with industry-specific descriptions:
Tool
Purpose
end_call
ALWAYS enabled — defines, per niche, when the bot should hang up
call_transfer
Call forwarding to a fallback number (emergencies, urgent cases, request for a human)
calendar_integration
Direct appointment booking via Cal.com / Calendly
The skill also applies proven defaults: GPT-4.1-mini, ElevenLabs TTS, interruptions and fillers enabled, noise cancellation, call recording, post-call evaluation with a custom schema.
skills/famulor-skill/├── SKILL.md # Agent instructions: the 4-phase flow├── references/│ └── nischen_intelligenz.md # Industry knowledge (10+ niche profiles)├── scripts/│ └── famulor_client.py # Python client for the Famulor API└── templates/ └── example_template.txt # System prompt templates
File
Role
SKILL.md
Main instruction with frontmatter (name, description — controls when the agent activates the skill) and the full onboarding flow
nischen_intelligenz.md
Profiles for hair salons/beauty, real estate, medical practices, restaurants, car dealers, trades, hotels, gyms, law firms, vets + a fallback for unknown niches — each with typical tasks, proactive questions, post-call schema, and recommended configuration
famulor_client.py
API client, also usable as a CLI: python3 famulor_client.py <method> key=value
templates/
Reusable system prompt templates (support, appointment booking, sales, lead qualification) with {{placeholders}}
On top of that: manifests for each platform (.plugin/plugin.json, .claude-plugin/, .cursor-plugin/, gemini-extension.json, GEMINI.md) and the packaged archive famulor.skill for manual installation.
The repository is designed as a template — three typical customizations:Add a new industry: Add your own profile to references/nischen_intelligenz.md following the existing pattern: typical tasks, proactive questions, recommended configuration (knowledge base yes/no + mode, post-call schema with max 16 characters per field name, ambient sound), system prompt priorities, and an end_call description.Custom prompt templates: Drop additional templates into templates/ and reference them in SKILL.md — the agent uses them as a starting point instead of writing from scratch.Extend API functions: Add new methods to famulor_client.py (e.g. campaigns or leads) — every public method is automatically callable via the CLI. Endpoints: API reference.Then repackage and bump the version:
# Bump version in .plugin/plugin.json, .claude-plugin/, .cursor-plugin/,# gemini-extension.json, then:zip -r famulor.skill skills/
For building entirely new skills (different platform, different use case): reuse the structure — SKILL.md with a precise description (it controls triggering), knowledge in references/, executable code in scripts/. A good description names concrete trigger phrases.
Skill vs. MCP server: The MCP server exposes 76 tools across the whole platform (calls, campaigns, conversations, …) via OAuth. The skill focuses on guided onboarding with industry knowledge and runs in coding agents (Cursor, Codex, Gemini CLI) via API key. They complement each other.
