Douyin Viral Video Scraper
Paste the following prompt into your AI chat to install this skill:
Install @user_15292d5a/yjkj-douyin-scraper-v3 according to https://skillhub.cn/install/skillhub.md.
About this skill
Problem
When analyzing Douyin content trends, the work usually starts from a natural-language request: identify the keyword, decide between search and hot rankings, set the result size, then clean the returned titles, tags, and engagement numbers. douyin-scraper-v3 maps that request to concrete scraper commands, reducing manual command construction and raw result cleanup.
How It Works and Boundaries
The skill drives a browser with Playwright and focuses on a few practical paths:
- Keyword search: extracts terms like seafood sales and runs search to collect candidate videos
- Hot rankings: fetches global or category-based lists, for example Food
- Field extraction: normalizes titles, descriptions, tags, view counts, likes, comments, and links
Boundaries matter: the current version does not parse a single Douyin video URL; an unauthenticated headless browser may hit a CAPTCHA, causing the script to fall back to simulated data. Use it with controlled frequency, without login, and treat the output as research-oriented leads rather than a stable scraping endpoint.
Use Cases
- Before a content meeting, search Douyin videos by camping gear and compile titles, tags, and likes to assess content direction.
- Check the daily Douyin hot list, capture the top 20 titles, view counts, and comments to build a trend digest.
- Extract copy, descriptions, and links for seafood sales videos to create a benchmarking spreadsheet.
- Pull the Food category hot list and compare headline patterns to inform content templates.
Best For
- Short-video content operations staff who need natural-language keyword search plus titles, tags, and engagement data.
- Market analysts tracking competitors who need category hot lists, copy patterns, and view-count comparisons.
- Python engineers wrapping scraper commands who need to map requests to search/hot and handle fallback output.
- Media researchers studying platform trends who need video links, descriptions, and comment counts for manual review.
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