One-sentence value proposition: Say goodbye to blind content creation and use data to drive Xiaohongshu traffic growth. Extract actionable viral content logic, competitor strategies, and KOL value from massive public data, covering all scenarios of content creation, brand marketing, and market analysis, so Xiaohongshu operational decisions are traceable.
1. Skill Overview
This is a tool focused onXiaohongshu business data mining. It can penetrate Xiaohongshu's public data layer and provide you with in-depthcompetitor monitoring、trend forecastingandKOL screeningservices. Whether you are a content creator, brand marketer, or market analyst, you can obtain decision support through this tool.
1.1 Core Capability Matrix
| Capability Module | Core Function | Pain Point Addressed |
|---|---|---|
| 🔍 Viral Content Mining | Popular note discovery, high-engagement content search | Cannot find topic inspiration, do not know what content is trending |
| 🕵️ Competitor Analysis | Benchmark account monitoring, note performance tracking | Why do competitors gain followers quickly? What are their strategies? |
| 👥 KOL Screening | Blogger follower profile, engagement rate analysis | Cannot find suitable bloggers for placement, worried about data fraud |
| 📈 Trend Monitoring | Keyword popularity tracking, topic trend analysis | Miss hot topics, unable to predict market direction |
1.2 Target Audience
✅ Xiaohongshu content creators/operators | ✅ Brand marketing/market personnel | ✅ Data analysts | ✅ MCN agencies/blogger agents
2. Quick Start Guide
2.1 Prerequisites
- Install Node.js 16+ environment
- Configure environment variable
GUAIKEI_API_TOKEN(the default TOKEN is for trial use only; a private TOKEN must be applied for)
2.2 Basic Syntax
# 语法：node scripts/search.js [关键词] [选项]
2.3 Option Description
--type <0>: Search type, 0-all, 1-video, 2-image and text (default 0)--sort <0>: Sort basis, 0-comprehensive, 1-latest, 2-most likes, 3-most comments, 4-most saves (default 0)--limit <10>: Number returned, 1-60 (default 10)--output <json>: Output format, json/markdown (default json)
2.4 Typical Examples
# 示例1：基础搜索(JSON格式)
node scripts/search.js AI
# 示例2：带空格的关键词
node scripts/search.js "AI 教程"
# 示例3：自定义搜索类型(视频)
node scripts/search.js AI --type 1
# 示例4：自定义排序(最多点赞)
node scripts/search.js "AI 模型" --sort 2
# 示例5：自定义返回结果数量(20条)
node scripts/search.js AI --limit 20
# 示例6：自定义输出格式(Markdown)
node scripts/search.js "AI 教程" --output markdown
# 示例7：复杂搜索(图文+最多点赞+20条结果+JSON格式)
node scripts/search.js --keyword "AI 教程" --type 2 --sort 2 --limit 20 --output json
3. Data Compliance Statement
✅ Only scrapes Xiaohongshupublicly visiblecontent, with no risk of privacy data leakage ✅ Data is for business analysis reference only and must comply with Xiaohongshu platform terms of use ✅ All output data is desensitized and does not involve users' personal information
4. Technical Description (OpenClaw Adaptation)
- Runtime environment: Node.js 16+, with prior configuration of
GUAIKEI_API_TOKENenvironment variable - Data output format: supports JSON/Markdown (returned on demand)
- Trigger method: supports direct triggering by natural language instructions, no fixed syntax required, high fault tolerance