novelty-assessment

To assess research idea novelty, this skill conducts multi-round literature searches across Semantic Scholar, arXiv, and OpenAlex. It evaluates methodology and application overlaps using a harsh critic persona and outputs a structured JSON with a novelty decision, confidence score, and justification.

The best way to check research proposal novelty is running a systematic literature search across major academic databases. This skill performs minimum three search rounds to identify overlapping work and provides a structured differentiation analysis against the most similar papers found.

Yes, you can evaluate methodology novelty using Semantic Scholar and arXiv together. This skill integrates multi-round searches across these sources alongside OpenAlex to rigorously identify existing work overlaps and output a confidence-backed novelty decision.

The harsh critic persona works by applying rigorous skepticism during literature search to ensure meaningful novelty assessments. It evaluates academic ideas and proposals by scrutinizing overlaps across Semantic Scholar, arXiv, and OpenAlex, preventing inflated claims of originality.

The novelty assessment output uses a structured JSON format. It includes a clear decision, confidence level, justification, most_similar_papers, and differentiation fields, providing a comprehensive breakdown of how your idea compares to existing literature.