aaav1.0.0

Researchers at Shenzhen University need to collect papers from Web of Science on a specific topic, screen them, extract metadata and abstracts, and write them into a Feishu Base table for collaborative review. The skill automates the entire workflow from login to table creation.

PhD students conducting a systematic review can use this skill to iteratively search, deduplicate, and filter papers by relevance, citations, and quartile, then store structured records in Feishu for easy annotation and sharing with supervisors.

University librarians can demonstrate the SZU library route to Web of Science and show how to export search results to a Feishu multidimensional table, helping students adopt reproducible research workflows.

Research groups in social sciences can use this skill to maintain a shared Feishu Base of SSCI-indexed papers, with fields for Q zone, citation count, and status, enabling transparent and up-to-date literature awareness across team members.

Undergraduate or master's students can leverage the skill to quickly gather 50 papers on their thesis topic, filter by high relevance and citations, and build a personal reference library in Feishu with links for full-text reading.

University libraries can package this skill as a premium service for faculty and students, demonstrating how institutional subscriptions (e.g., Web of Science) can be integrated with productivity tools like Feishu to boost research efficiency.

A standalone SaaS offering that combines automated literature retrieval, screening, and Feishu integration, targeting individual researchers or small labs. Revenue from monthly subscriptions or pay-per-use credits.

Provide customized setup and training for corporate or academic R&D teams to adopt the WOS-to-Feishu workflow, including configuration of search strategies, field mapping, and quality checks.