Getting Started with Research Superpowers

Systematic literature review automation uses AI to streamline searching, screening, and extracting data from scientific papers. This Skill guides you through the complete workflow—from querying databases like PubMed and Semantic Scholar to building screening rubrics, evaluating abstracts, and tracking findings across 50+ papers in parallel, eliminating manual organization bottlenecks.

Yes. This Skill automates two-stage screening (abstract to deep dive), parallel processing of large paper batches, and deduplication tracking. It generates reproducible session folders with summaries, PDFs, and deduplicated findings, so you maintain audit trails and avoid duplicate analysis across your entire review.

The workflow combines querying research databases, applying custom screening rubrics to filter relevant papers, extracting structured data from selected studies, and traversing citation networks for related work. Results are organized in deduplicated, reproducible folders with summaries for synthesis.

Yes. This Skill integrates PubMed and Semantic Scholar for systematic literature searching, supporting automated queries and parallel screening of retrieved papers to accelerate discovery and evaluation in academic research workflows.

You need a clear research question or query, familiarity with your domain's screening criteria, and access to Claude Code sessions. The Skill helps you build screening rubrics and organize workflows, so no specialized tools or prior AI experience is required.

This Skill automates citation traversal to discover related papers and map research landscapes. After screening your initial results, you can follow citation links to expand findings, deduplicate across sources, and synthesize a comprehensive view of the literature without manual cross-referencing.