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    novelty-verification-research

    novelty-verification-research

    by LocoLoboZ

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

    Updated May 2026
    Security scanned
    One-time purchase
    including Claude Code

    $7

    · or 35 credits

    One-time purchase

    30-day refund guarantee

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    Included in download

    • 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.
    • terminal, browser, network automation included
    • Ready for including Claude Code
    • Instant install

    See it in action

    A real example of what this skill takes in and produces.

    Sample input

    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.

    Sample output

    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.

    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.

    Use Cases

    • 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.

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell
    Browser
    Network Access

    Allowed Hosts

    none required (web search and scholarly access improve coverage but operate through user-authorised environment tools)

    File Scopes

    novelty-verification-research/**

    Works with any agent that supports the Universal SKILL.md standard, including Claude Code, Codex CLI, Cursor, VS Code Copilot, Gemini CLI, OpenClaw, and 20+ compatible agents. Web search and scholarly database access in the agent environment improve source coverage but are not required if source material is supplied manually.

    Creator

    I design and publish skills built from real professional practice across three areas: cyber security consulting, business operations, and AI workflow engineering. My cyber security skills draw on active advisory work spanning governance, risk, compliance, assurance, and executive reporting. They are built for practitioners who need structured, defensible outputs - not generic templates. My business operations skills cover the day-to-day work of running a consulting practice: bookkeeping, financial tracking, expense reconciliation, and marketing content - designed to reduce repetitive overhead and keep outputs consistent. My AI platform and workflow skills are built for people who want to get more out of Claude and similar platforms - covering prompt engineering, skill architecture, automation pipelines, and agent enhancement. Every skill I publish has been tested in production use before it reaches the marketplace. If it is here, it works.

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