Automate Xiaohongshu content search, retrieval, commenting, liking, and publishing operations.
npx skills add https://github.com/zhjiang22/openclaw-xhs --skill xiaohongshu-zhjiang22
Please help me install this Agent Skill. Skill: xiaohongshu Source: https://github.com/zhjiang22/openclaw-xhs/tree/main Command: npx skills add https://github.com/zhjiang22/openclaw-xhs --skill xiaohongshu-zhjiang22
Manually browsing, searching, and managing content on Xiaohongshu (RedNote) is time-consuming and inefficient, especially when tracking trends or organizing saved posts for future reference. This Skill eliminates that manual work by letting AI assistants handle all platform interactions automatically.
Use the xiaohongshu skill to search for posts about "sustainable fashion" and generate a trend analysis report summarizing top engagement and common discussion points.
High-intent search queries and answers about installing and using this skill.
To automate Xiaohongshu content search and trend tracking, you can use this Skill to let AI handle platform interactions, automatically searching posts by keyword and generating trend reports with engagement statistics and comment keyword analysis.
Yes, you can use AI to publish image notes and comments on RedNote. This Skill automates content interaction by supporting direct publishing of image or video notes, commenting, and liking posts through AI commands.
Yes, you need Python 3.10 and jq to run Xiaohongshu automation. Python 3.10+ is required for generating trend reports and long image exports, while jq is necessary for securely constructing JSON payloads during platform interaction.
The best way to convert saved Xiaohongshu posts into searchable AI memory is using the memory export feature. This function transforms your liked and saved posts into a searchable knowledge base, allowing your AI assistant to recall favorite content on demand.
Yes, xiaohongshu-mcp supports automated user profile analysis. The Skill automates interaction with the Xiaohongshu platform to retrieve post details, analyze specific user profiles, and track public discussion trends for targeted keywords.
Long image export requires xvfb and pillow dependencies because generating full post detail images needs a virtual framebuffer display environment via xvfb and image processing capabilities via pillow to capture and render the output correctly.
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