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    Novelty Verification Research

    2

    Rigorous academic and internal research verification to score idea novelty and identify prior work.

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    See it in action

    You say

    Assess the novelty of this idea: using sparse LoRA routing for edge-device language models where adapters are activated based on local energy budget and task complexity. Score it and identify the closest prior work.

    Your agent does

    The skill extracts a method signature covering what the idea does, how it works and what it claims as novel. It generates keyword groups, searches available sources, identifies the closest three to five prior works with a comparison table, produces a differentiation analysis, assigns a conservative novelty score with a label and rationale, and delivers a recommendation to proceed, modify or abandon. All source entries are traceable. Confidence limitations are documented where source coverage is incomplete.

    What you get

    Score the novelty of a research idea from 1-5 based on current SOTA.Identify the closest 3-5 prior works for any proposed technical method.Check internal wikis to prevent duplicating failed or in-progress R&D projects.Determine whether to proceed, modify, or abandon a new research direction.

    About this skill

    Overview

    The Novelty Verification Research skill provides a rigorous framework for assessing the originality of research ideas, methods, and manuscripts. Designed for R&D teams and academic researchers, it acts as an automated "sanity check" to prevent duplicating existing work and identifies exactly where a new concept stands in relation to the state-of-the-art.

    What it does

    This skill performs a multi-source comparative analysis by searching academic databases, preprint servers like arXiv, and internal knowledge bases. It goes beyond simple keyword matching to extract a "method signature" from your proposal, comparing it against prior work based on architecture, data, and objectives.

    • Generates a conservative novelty score (1-5) based on evidence.
    • Lists the 3-5 closest prior works with direct comparison tables.
    • Performs internal anti-repetition checks against your team's failed or in-progress ideas.
    • Provides a clear recommendation: Proceed, Modify, or Abandon.

    Why use this skill

    Writing a manual literature review is time-consuming and prone to bias. This skill provides a structured, objective perspective that prevents the "innovation tunnel vision" by searching across multiple repositories simultaneously. It ensures that before you invest resources into a project, you have a verifiable map of the existing research landscape.

    Output

    The result is a structured Novelty Report including a method signature, a differentiation analysis table, confidence scores, and specific next-step recommendations to strengthen the idea's unique contribution.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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