whatsapp-faq-bot

What This Skill Does

The WhatsApp FAQ Bot is a powerful OpenClaw tool designed to transform unstructured markdown documentation into an intelligent, searchable knowledge base. It leverages fuzzy text matching to interpret user queries and retrieve the most relevant answers from your defined FAQs. By utilizing a simple command-line interface, it allows developers and business owners to manage, update, and deploy automated support systems without complex database configurations. Whether you are scaling a customer service operation or building a personalized knowledge repository, this skill streamlines the process by acting as the engine for your automated responses.

Installation

To integrate this skill into your environment, use the OpenClaw command-line interface. Run the following command in your terminal:

clawhub install openclaw/skills/skills/mariusfit/whatsapp-faq-bot

Ensure you have the required Python environment configured. Once installed, navigate to your project directory and initialize the database using python scripts/faqbot.py init to start building your repository.

Use Cases

This skill is perfect for small-to-medium businesses looking to automate WhatsApp support. Common use cases include:

• Providing 24/7 instant replies to customer inquiries about shipping, pricing, or store hours.
• Managing technical documentation for internal teams to query via a simple bot.
• Maintaining a dynamic FAQ list that can be easily exported as JSON for other web applications or imported from shared marketing markdown files.
• Reducing human agent workload by filtering routine questions automatically.

Example Prompts

1. "OpenClaw, search the FAQ for information regarding our refund policy."
2. "Add a new entry to the FAQ: Q: Do you ship to Australia? A: Yes, we ship worldwide via DHL."
3. "Run a search on the current knowledge base to see how we handle password reset requests."

Tips & Limitations

To get the best results, structure your markdown files using clear H2 headings for questions. While the TF-IDF fuzzy matching is effective for general queries, it does not support semantic LLM-based intent understanding, so ensure your FAQ questions use common terminology. If your knowledge base exceeds 500 entries, consider batching imports to avoid performance overhead during search indexing. Always set a threshold consistent with your accuracy requirements; a threshold too low may result in irrelevant answers, while one too high might return no results at all.