What problem does it solve? Literature cleaning requires a precise definition of the research topic, but users often start screening without clear boundaries, leading to inconsistent inclusion and exclusion decisions. This Skill establishes a semantic anchor through structured Q&A before any screening begins. ## Core Features & Use Cases - Structured Questioning: Guides users through mandatory questions on discipline, research topic, purpose, search strategy, and topic boundaries, plus conditional follow-ups on time range, language, and document types. - Purpose-Adaptive Screening Tendency: Maps research purposes (systematic review, bibliometric analysis, meta-analysis, scoping review) to appropriate cleaning strictness levels. - Research Background Profile Output: Generates a standardized profile documenting core concepts, excluded topics, gray-zone handling rules, and noise risk points from search expressions. - Use Case: Before cleaning 2,000 bibliographic records retrieved with the query "meme*", use this Skill to confirm the research scope, decide whether homonym hits like "membrane" should be excluded, and produce a reference profile for all downstream relevance judgments. ## Quick Start Start the research background inquiry for my literature dataset on internet meme diffusion and generate the research background profile.
