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When a user wants to extract YouTube video lists and their comments by keyword, analyze viewer sentiment, gather audience feedback, or monitor public response to specific topics via BrowserAct API.
BROWSERACT_API_KEY env var; if missing, ask user to provide it.python ./scripts/youtube_comments_api.py "keywords" "Comments_limit" "Scroll_count".Structured video + comment datasets (title, URL, views, commenter, text, likes, replies) ready for sentiment analysis, market research, and BI integration.
Use Cases
A SaaS company launches an AI feature and wants to know user pain points. They use this skill with keyword 'AI automation', limit 50 comments, scroll 5 times. The agent returns top videos and viewer comments with likes/replies. The team analyzes objections and feature requests from real comments, guiding roadmap prioritization with evidence instead of guesswork.
A marketing agency tracks competitor YouTube presence. Using this skill with competitor brand keyword, they extract video titles, URLs, view counts and audience discussions. The structured data is fed into BI tools to monitor sentiment trends and engagement metrics over time, helping the agency produce competitive reports without manual scraping.
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