Install
openclaw skills install @openlark/xiaohongshu-insightProvides daily insights from 2000+ Xiaohongshu viral posts to support content creation, trend analysis, and creative inspiration based on engagement data.
openclaw skills install @openlark/xiaohongshu-insightA professional data insight tool built specifically for Xiaohongshu content creation. Continuously collects over 2000+ viral posts daily across the platform, empowering creators with data references, traffic trend insights, and creative inspiration.
Use when users mention Xiaohongshu viral posts, post data, traffic trends, creative inspiration, low-follower viral posts, interaction spikes, etc.
Automatically collects 2000+ viral posts daily based on the following criteria:
Each viral post includes the following data:
| Dimension | Description |
|---|---|
| Basic Information | Title, cover image, author, publish time, category tags |
| Interaction Data | Likes, saves, comments, shares, and growth rates |
| Author Profile | Follower count, total posts, average interactions, category distribution |
| Content Features | Title keywords, cover style, content type, word count range |
| Traffic Curve | Interaction data at 24h/48h/72h/7d intervals after publishing |
Scenario 1: Finding Creative Inspiration
User: What are some recent low-follower viral posts in the beauty category?
→ Filter category=Beauty, follower count<5000, sort by interaction volume
→ Return TOP 20 viral posts with key feature analysis
Scenario 2: Analyzing Traffic Trends
User: What common characteristics do this week's viral fashion posts share?
→ Aggregate analysis of viral posts in Fashion category over the past 7 days
→ Extract title keywords, cover features, publishing time distribution
→ Output trend insight report
Scenario 3: Competitor Account Research
User: Why does this blogger consistently produce viral content?
→ Analyze the blogger's historical viral posts
→ Compare with other bloggers in the same category
→ Output success factor analysis
Use scripts/query_notes.py to query viral post data:
python scripts/query_notes.py --category Beauty --days 7 --limit 50
Parameter descriptions:
--category: Category (Beauty/Fashion/Food/Travel/Home/Parenting/Career/Emotions/Knowledge/Entertainment)--days: Number of days to query (default 7 days)--limit: Number of results to return (default 20)--sort: Sort field (engagement/growth/fans)--min_engagement: Minimum interaction thresholdUse scripts/analyze_trends.py to analyze category trends:
python scripts/analyze_trends.py --category Fashion --output report.md
Output includes:
Use scripts/export_data.py to export data:
python scripts/export_data.py --format xlsx --output viral_data.xlsx
Supported formats: xlsx, csv, json
See references/data_schema.md for details.
See references/viral_criteria.md for details.