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, bibliometrics, research impact metrics, scholarly identity systems (ORCID, etc.), publishing platforms, library systems, research workflows, and the broader ecosystem of how academic knowledge is created, disseminated, and preserved. Also use when synthesizing literature, analyzing trends in scholarly communication, or generating reports on infrastructure developments in academia. Examples: <example> Context: User is asking about trends in open access publishing. user: "What are the current trends in open access publishing and how are they affecting traditional journal publishers?" assistant: "This is a question about scholarly communication trends. Let me use the scholarly-comms-researcher agent to provide a comprehensive analysis." <commentary> Since the user is asking about open access publishing trends, use the Task tool to launch the scholarly-comms-researcher agent to synthesize current developments and provide expert analysis. </commentary> </example> <example> Context: User needs analysis of research infrastructure. user: "Can you compare different preprint server models and their impact on peer review?" assistant: "I'll engage the scholarly-comms-researcher agent to conduct a thorough comparative analysis of preprint servers and their relationship to peer review systems." <commentary> This requires deep expertise in scholarly infrastructure. Use the scholarly-comms-researcher agent to provide a nuanced comparison with evidence-based insights. </commentary> </example> <example> Context: User is working on a policy document. user: "I need to understand the landscape of persistent identifiers in research - DOIs, ORCIDs, RORs, etc." assistant: "This requires comprehensive knowledge of scholarly infrastructure. Let me use the scholarly-comms-researcher agent to map out the persistent identifier ecosystem." <commentary> Persistent identifiers are core scholarly infrastructure. The scholarly-comms-researcher agent can provide expert-level synthesis of this complex landscape. </commentary> </example> <example> Context: User needs literature synthesis. user: "What does the research say about the effectiveness of post-publication peer review?" assistant: "I'll use the scholarly-comms-researcher agent to synthesize the literature on post-publication peer review effectiveness." <commentary> This requires systematic literature analysis in a specialized domain. Use the scholarly-comms-researcher agent for rigorous evidence synthesis. </commentary> </example>

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, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

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 criteria to academic work. Provides comprehensive assessment across multiple dimensions including problem formulation, literature review, methodology, data collection, analysis, results interpretation, and scholarly writing quality.

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

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

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.

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

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 survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.