PaperDailyv1.0.0

Research teams in computer science can use this skill to stay updated on the latest arXiv papers without manual searching. It automates daily paper recommendations based on customizable keywords like machine learning or deep learning, saving time and ensuring they don't miss high-value publications.

Startups focusing on AI and machine learning can integrate this skill to monitor emerging trends and competitor research. By setting keywords relevant to their niche, they receive filtered paper updates that can inspire new product features or inform R&D directions.

Large tech companies with R&D divisions can deploy this skill to keep engineers and scientists informed about recent advancements in computer science. It supports collaboration by pushing recommendations to group chats on Feishu, facilitating discussions on potential innovations.

Universities and online learning platforms can use this skill to curate daily paper lists for students or faculty in computer science courses. It helps in creating reading materials or sparking class discussions based on the latest research from arXiv.

Offer a premium version with advanced filtering, more keywords, or integration with additional platforms beyond Feishu. Charge a monthly fee for enhanced features like personalized recommendations or historical data access.

Sell licenses to companies for internal use, providing custom configurations, dedicated support, and integration with their existing communication tools. This model targets large teams needing scalable paper monitoring solutions.

Provide a basic free version with limited keywords and cache hours, supported by non-intrusive ads or sponsored paper recommendations. Upsell to an ad-free premium plan with more features and higher usage limits.