Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Build AI-powered customer service knowledge bases by extracting FAQs from documents or websites, enabling automated replies and multi-format exports.
Build AI-powered customer service knowledge bases by extracting FAQs from documents or websites, enabling automated replies and multi-format exports.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Help SMBs quickly build AI-powered customer service systems. Input FAQ documents or website URLs to automatically generate a knowledge base and configure auto-reply capabilities. 帮助中小企业快速搭建AI客服系统。输入FAQ文档或网站URL,自动生成知识库并配置自动回复功能。
Setting up customer service automation Building FAQ knowledge bases Configuring auto-reply systems Migrating customer service to AI
Extract FAQ from documents (PDF, TXT, MD, DOCX) Scrape FAQ from website URLs Generate structured knowledge base (JSON) Test Q&A matching Export to common formats (JSON, CSV, Markdown)
# Extract from document node kb-builder.js extract --file ./faq.pdf --output ./kb.json # Extract from website node kb-builder.js scrape --url https://example.com/faq --output ./kb.json # Test knowledge base node kb-builder.js test --kb ./kb.json --query "退货政策是什么?" # Export to different formats node kb-builder.js export --kb ./kb.json --format csv --output ./kb.csv
Create config.json: { "language": "zh-CN", "minConfidence": 0.7, "maxResults": 3, "fallbackMessage": "抱歉,我没有找到相关答案。请联系人工客服。" }
node kb-builder.js extract --file ./company-faq.pdf --output ./kb.json node kb-builder.js test --kb ./kb.json --query "如何退货?"
node kb-builder.js scrape --url https://shop.example.com/help --output ./kb.json node kb-builder.js export --kb ./kb.json --format markdown --output ./faq.md
node kb-builder.js interactive --kb ./kb.json # Then type questions to test responses
Knowledge base JSON structure: { "version": "1.0", "language": "zh-CN", "entries": [ { "id": "q001", "question": "如何退货?", "answer": "您可以在收到商品后7天内申请退货...", "keywords": ["退货", "退款", "return"], "category": "售后服务" } ] }
Node.js 18+ No external API keys needed for basic features Optional: OpenAI API key for enhanced matching
All processing is local No data sent to external services (unless using OpenAI enhancement) Safe for sensitive business information
PDF extraction requires readable text (not scanned images) Website scraping respects robots.txt Best results with structured FAQ pages
Created for OpenClaw by Claude
MIT
customer-service, ai, knowledge-base, faq, automation, chatbot, 客服, 知识库
Long-tail utilities that do not fit the current primary taxonomy cleanly.
Largest current source with strong distribution and engagement signals.