WhatsApp Business Al Assistant
/install whatsapp-business-ai
WhatsApp Business AI Assistant
Name & Purpose
Automates WhatsApp conversations for local businesses — handling replies, booking inquiries, lead capture, and intelligent follow-ups without requiring 24/7 human attention. Designed for gyms, restaurants, salons, clinics, and service-based businesses in South Africa.
Prerequisites
| Requirement | Version/Detail |
|---|---|
| OpenClaw | v2.4+ |
| Node.js | v18+ |
| WhatsApp Business API (Meta) | Approved business account |
| Meta Developer App | With WhatsApp product configured |
| Python 3 | v3.10+ (for NLP pipeline) |
wacli CLI |
Installed on host |
| ngrok or static IP | For webhook callback |
Installation
1. Copy skill files
cp -r streams/01_ClawHub_Skills/01_WhatsApp_Business_AI_Assistant/* ~/.openclaw/skills/
2. Install dependencies
cd ~/.openclaw/skills/whatsapp-business-ai
npm install
pip install -r requirements.txt
3. Configure environment
Create ~/.openclaw/skills/whatsapp-business-ai/.env:
WHATSAPP_PHONE_NUMBER_ID=your_phone_number_id
WHATSAPP_ACCESS_TOKEN=your_permanent_token
WHATSAPP_VERIFY_TOKEN=your_webhook_verify_token
WHATSAPP_BUSINESS_ACCOUNT_ID=your_business_account_id
BUSINESS_HOURS_TIMEZONE=Africa/Johannesburg
DEFAULT_LANGUAGE=en
NLP_MODEL_PATH=./models/za_intent_classifier
LEAD_DB_PATH=./data/leads.db
BOOKING_CALENDAR_ID=your_google_calendar_id
4. Link to wacli
# Verify wacli is available
which wacli || brew install wacli
wacli --configure
5. Set up webhooks
# Start webhook receiver (uses ngrok for dev)
./scripts/start-webhook.sh
# Register webhook with Meta
curl -X POST "https://graph.facebook.com/v18.0/$WHATSAPP_PHONE_NUMBER_ID/subscriptions" \
-H "Authorization: Bearer $WHATSAPP_ACCESS_TOKEN" \
-d "object=whatsapp_business_account&callback_url=https://your-ngrok-url.ngrok.io/webhook&verify_token=$WHATSAPP_VERIFY_TOKEN"
Usage
Start the assistant
# Production mode
openclaw skill run whatsapp-business-ai
# Development / dry-run
openclaw skill run whatsapp-business-ai --dry-run
The assistant runs as a persistent OpenClaw process that:
- Listens for incoming WhatsApp messages via webhook
- Classifies intent (booking, inquiry, complaint, lead)
- Generates context-aware replies
- Logs leads to the local database
- Schedules follow-ups based on business rules
Workflow Overview
Incoming Message → Intent Classifier → Response Generator → Send Reply
↓
Booking Detected?
├── Yes → Check Calendar → Confirm Slot → Add Booking
└── No → Lead? → Log Lead → Schedule Follow-up
Available Commands
| Command | Description |
|---|---|
/status |
Show assistant health, queue depth, message count today |
/leads |
Export leads as CSV or JSON |
/analytics |
Last 24h: sent/replied/followed-up counts |
/blacklist \x3Cphone> |
Block a number |
/broadcast |
Send bulk message to all leads (ask first) |
/pause |
Stop accepting new messages (resume with /resume) |
Workflow Templates
Auto-reply templates are in ./templates/. Customise per business type:
templates/
├── auto_replies/
│ ├── booking_gym.yaml
│ ├── booking_restaurant.yaml
│ ├── booking_salon.yaml
│ ├── greeting_day.yaml
│ ├── greeting_night.yaml
│ ├── hours_inquiry.yaml
│ ├── pricing_inquiry.yaml
│ ├── complaint_acknowledgement.yaml
│ └── out_of_hours.yaml
├── follow_ups/
│ ├── no_reply_24h.yaml
│ ├── abandoned_booking.yaml
│ ├── post_service_feedback.yaml
│ └── promotion_blast.yaml
└── intents.yaml
Example: booking_gym.yaml
name: gym_booking
trigger:
intents: [booking, tour_inquiry, membership_inquiry]
confidence_threshold: 0.75
response:
template: |
Hi {{customer_name}}! 👋
Thanks for reaching out to {{business_name}}.
I can help you book:
🏋️ A free trial session
📋 A membership consultation
🎯 A personal training intro
What time works for you? Our hours are:
Mon–Fri: 5:00 AM – 9:00 PM
Sat: 6:00 AM – 6:00 PM
Sun: 7:00 AM – 2:00 PM
Just tell me your preferred day and time!
buttons:
- "Book Trial"
- "See Pricing"
- "Ask a Human"
Prompt Configuration
Edit ./config/prompts.yaml:
classifier_prompt: |
Classify the incoming WhatsApp message into exactly one intent.
Intents: [booking, pricing_inquiry, hours, complaint, lead, general, spam]
Context: {business_type} in {location}
Message: {text}
Respond with only the intent name and confidence score.
response_prompt: |
You are {assistant_name}, the friendly AI assistant for {business_name}.
Location: {location}
Business type: {business_type}
Business hours: {hours}
Customer message: {text}
Detected intent: {intent}
Reply in a warm, professional tone. Be concise. If it's a booking,
ask for time and contact info. Never give away pricing you're unsure of.
Use South African English.
Example Prompts for Human Operators
"Hey Marvis, can you check on the gym assistant? How many unqualified leads are waiting?" "Set up a new WhatsApp assistant for 'Jozi Cuts Barbershop' in Randburg." "What's the reply rate on the restaurant assistant this week?" "Add a 'Student Discount' promotion template to the gym assistant's broadcast queue."
Directory Structure
whatsapp-business-ai/
├── SKILL.md
├── README.md
├── config/
│ ├── business.yaml # Business profile (name, hours, location, type)
│ ├── prompts.yaml # LLM prompts for classification & reply
│ └── webhooks.yaml # Webhook routing rules
├── templates/
│ ├── auto_replies/ # Pre-written reply templates
│ ├── follow_ups/ # Scheduled follow-up templates
│ └── intents.yaml # Intent definitions & training data
├── scripts/
│ ├── start-webhook.sh # Start webhook listener with ngrok
│ ├── register-webhook.sh # Register with Meta APIs
│ └── export-leads.py # Export leads to CSV
├── workflows/
│ ├── booking.yaml # Booking: detect → confirm → create
│ ├── lead.yaml # Lead: capture → enrich → follow-up
│ └── complaint.yaml # Complaint: acknowledge → escalate → resolve
├── data/
│ ├── leads.db # SQLite lead database
│ └── conversation_logs/ # Raw conversation transcripts (rotated)
├── requirements.txt
└── package.json
Integration Options
- Google Calendar — auto-check and book appointment slots
- Square / PayFast — send payment links for deposits
- CRM webhooks — POST leads to HubSpot, Pipedrive, or custom API
- Slack — notify human agent when escalation needed
- Twillio — fallback SMS for low-signal areas
Troubleshooting
| Symptom | Likely Cause | Fix |
|---|---|---|
| Assistant not replying | Webhook not registered | Run register-webhook.sh |
| Replies go to wrong chat | Wrong phone_number_id in env | Check .env values |
| "Message not allowed" | Sender hasn't opted in | Send template message first |
| Low confidence on intent | Trained on wrong business type | Update config/business.yaml |
| Calendar sync fails | Missing Google Calendar scope | Re-auth with https://www.googleapis.com/auth/calendar scope |
| Leads not saving | SQLite path not writable | chmod 755 ./data/ |
| ngrok URL changed | Free ngrok rotates on restart | Use paid plan or static IP |
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install whatsapp-business-ai - 安装完成后,直接呼叫该 Skill 的名称或使用
/whatsapp-business-ai触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
WhatsApp Business Al Assistant 是什么?
Automates WhatsApp conversations for local businesses — replies, bookings, lead capture, and follow-ups. Designed for gyms, restaurants, salons, clinics, and... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 87 次。
如何安装 WhatsApp Business Al Assistant?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install whatsapp-business-ai」即可一键安装,无需额外配置。
WhatsApp Business Al Assistant 是免费的吗?
是的,WhatsApp Business Al Assistant 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
WhatsApp Business Al Assistant 支持哪些平台?
WhatsApp Business Al Assistant 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 WhatsApp Business Al Assistant?
由 marcvanstad(@marcvanstad)开发并维护,当前版本 v1.0.0。