idea-evaluator

Part of the Supervisor-Skills project from HKUST, which distills ten years of academic research experience from top AI/data science conferences into structured AI skills for research guidance and paper writing.

Academic research skill that distills a professor's decade of experience publishing at top CS conferences (SIGMOD, VLDB, ICML, NeurIPS) into structured AI skills for paper quality evaluation, idea generation, and pre-submission review.

Academic paper writing skill from Supervisor-Skills that encodes ten years of research experience at top CS conferences into structured AI guidance for idea generation, paper writing, and scientific plotting.

Part of Supervisor-Skills, this skill drafts research paper introductions by applying structured academic writing methodologies distilled from a decade of experience publishing at top AI and data science conferences like SIGMOD, VLDB, ICML, and NeurIPS.

Part of Supervisor-Skills, this skill guides the full research workflow from idea evaluation through paper writing, applying structured methodologies from top-tier AI and data science conference experience.

Part of Supervisor-Skills, this skill provides structured templates for writing benchmark papers in AI and data science, based on methodologies from top-tier conferences like SIGMOD, VLDB, ICML, and NeurIPS.