claude

scholarly-research

Expert agent for scholarly communication research with Dimensions database integration and academic search capabilities

3 on GitHubby Kristian Garzav2.0.0MITupdated 25 days agodocumentation
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Plugin scholarly-research from marketplace marketplace-claude in kjgarza/marketplace-claude. Commands read from the repo's manifest — 25 days ago.

What it installs

Skills (7)

  • literature-review

    Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical,

  • scholar-evaluation

    Systematic framework for evaluating scholarly and research work based on the ScholarEval methodology. This skill should be used when assessing research papers, evaluating literature reviews, scoring research methodologies, analyzing scientific writing quality, or applying structured evaluation crite

  • scientific-brainstorming

    Research ideation partner. Generate hypotheses, explore interdisciplinary connections, challenge assumptions, develop methodologies, identify research gaps, for creative scientific problem-solving.

  • scientific-critical-thinking

    Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.

  • scientific-visualization

    Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.

  • scientific-writing

    Write scientific manuscripts. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), abstracts, for research papers and journal submissions.

  • scikit-survival

    Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating surv

Subagents (1)

  • researcher

    Use this agent when the user needs comprehensive research, analysis, or insights related to scholarly communication and infrastructure topics. This includes questions about academic publishing, open access, research data management, institutional repositories, preprint servers, peer review systems,

View source on GitHub kjgarza.github.io

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