Supervisor-Skills is a collection of AI skills that encodes research methodology from experienced academics to guide researchers through the full lifecycle of academic work.
The project addresses the gap between theoretical knowledge of research practices and their practical application. It distills a decade of experience in publishing and peer review at top-tier venues into structured prompts that large language models can execute with precision. Rather than relying on generic prompts, the tool provides domain-specific guidance grounded in academic standards and editorial expectations, helping researchers move from initial ideas through manuscript submission with informed feedback at each stage.
Researchers pursuing PhDs or conducting academic work in data science and artificial intelligence should consider this tool if they lack access to frequent mentorship or struggle to translate research concepts into polished submissions. The project suits those who want to leverage AI capabilities while maintaining academic rigor and avoiding common pitfalls in paper structure, argumentation, and presentation. The tool includes skills for literature review, idea evaluation, paper writing with evidence grounding, language polishing, and figure reconstruction, covering the research pipeline from conception to submission.
The project shows active development with recent additions of specialized skills for paper writing, language refinement, and comprehensive literature research. The tool has been integrated into production systems serving large user bases. The codebase is maintained with structured documentation including a handbook and changelog tracking feature releases and improvements.
