xiaohongshu-crawler

Name: xiaohongshu-crawler
Availability: InStock
Author: RedFox

Crawl Xiaohongshu posts by keywords with date filters and sorting, returning structured CSV and HTML reports.

326|43|Updated May 12, 2026

Search Tags:#crawler #data-extraction #web-scraping #trend-analysis #xiaohongshu

Ready to run

npx skills add https://github.com/redfox-data/redfox-community --skill xiaohongshu-crawler

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: xiaohongshu-crawler
Source: https://github.com/redfox-data/redfox-community/tree/main/skills/xiaohongshu-crawler
Command: npx skills add https://github.com/redfox-data/redfox-community --skill xiaohongshu-crawler

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

Xiaohongshu content discovery and competitive research often require manual, multi-step scraping to identify trending posts and extract structured engagement data; this skill automates that process, delivering reliable, ready-to-analyze results.

Core Features & Use Cases

精准抓取：根据关键词、日期范围和排序，批量获取笔记及关键指标（标题、作者、收藏、分享、评论、点赞、发布时间等），并输出结构化表格。
多种导出：CSV（Excel 兼容）和 HTML 可视化报告，便于离线分析和分享。
使用场景：内容创意调研、品牌竞争分析、MCN 内容规划等场景下的数据支撑。

Quick Start

请直接指定关键词进行笔记的爬取，按日期筛选并导出结构化结果。

Frequently Asked Questions about xiaohongshu-crawler

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I scrape Xiaohongshu posts by keyword for trend analysis?▼

You can scrape Xiaohongshu posts by specifying target keywords to retrieve structured data including titles, authors, and engagement metrics. The skill filters results by date ranges and sorting options, returning structured tables ready for trend analysis.

What structured data fields can I extract from Xiaohongshu notes?▼

Xiaohongshu notes extraction returns structured fields mapping titles, authors, favorites, shares, comments, likes, and publication dates. This structured output supports direct content discovery and competitive research without manual multi-step scraping.

Can I export crawled Xiaohongshu data to CSV for Excel analysis?▼

Crawled Xiaohongshu data can be exported to CSV format compatible with Excel and HTML visualization reports. These export options facilitate offline data analysis and sharing for brand competitive analysis and MCN content planning scenarios.

Does this web scraping tool require Python requests to run?▼

This web scraping tool requires the Python requests dependency to perform API-based data retrieval from Xiaohongshu. It handles structured output generation and robust error handling using this HTTP library.

What is the best way to automate Xiaohongshu content discovery and competitive research?▼

Automating Xiaohongshu content discovery involves using keyword-based crawling with date filters to batch retrieve post metrics. This approach delivers reliable, ready-to-analyze structured results, replacing manual scraping for competitive research workflows.

Are there limitations when filtering Xiaohongshu posts by date ranges?▼

Filtering Xiaohongshu posts by date ranges relies on API-based data retrieval with structured output and explicit field mappings. Users should note that robust error handling manages retrieval failures, but large-scale historical scraping may encounter platform limitations.