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In the field of research, writing papers has always been an important task for academic professionals. Now, with an open-source project called "academic-research-skills" (ARS), this process has become more convenient and efficient. This toolkit integrates the capabilities of Claude Code, helping researchers complete the entire process from topic selection to submission, and has received widespread attention, with 6.4k stars on GitHub.
The design philosophy of ARS is to form a complete research workflow through four main skill modules, covering all aspects including literature review, paper writing, peer review, and finalization. These modules work together to ensure a smooth research process. Specifically, ARS includes:
1. **Deep Research Module**: This module consists of 13 intelligent agents, focusing on literature review and research question construction. It not only conducts systematic PRISMA reviews but also includes an agent for verifying the authenticity of citations, ensuring the reliability of each cited source.
2. **Academic Paper Module**: This module, composed of 12 intelligent agents, handles the paper writing process. It covers everything from outline design to draft writing, including bilingual abstract generation and format conversion. Additionally, it features a style calibration function that learns from the author's previous works to adapt the writing style, making the output more personalized.
3. **Academic Paper Reviewer Module**: This module simulates the real academic journal peer review process, with 7 intelligent agents. It evaluates the review process across multiple dimensions and provides detailed revision suggestions after the review, helping authors quickly improve the quality of their papers.
ARS is not only powerful in functionality but also emphasizes systematization and error prevention mechanisms. It sets strict citation verification and completeness checks to ensure that AI does not make common mistakes in academic research. In addition, it adopts a three-layer data isolation design, ensuring independence between writing and reviewing, preventing AI from being influenced by inappropriate information during the process.