Skill UI

This skill provides comprehensive guidance and established patterns for conducting rigorous scientific research and complex data analysis. It helps users structure their thinking process, ensuring a systematic and methodical approach to scholarly inquiry. Ideal for academic projects, literature reviews, and complex data interpretation.

A comprehensive workflow for systematically reviewing medical evidence. It allows users to search databases for clinical studies, build curated citation collections, grade evidence using established frameworks like GRADE, and generate professionally formatted, structured reports in academic citation styles (e.g., AMA). Ideal for conducting literature reviews and supporting clinical research. This tool helps transform raw medical data into actionable, structured knowledge.

A comprehensive workflow utilizing the Perplexity Sonar API for advanced, multi-turn research. It systematically decomposes broad topics into focused sub-queries, executes batch queries while maintaining context continuity, deduplicates citations, and synthesizes all findings into a structured, comprehensive research document. Ideal for academic research, market analysis, and generating detailed investment or industry briefs.

A comprehensive guide for systematic statistical analysis, designed for academic research. This skill assists in selecting the correct hypothesis tests (t-test, ANOVA, regression, chi-square), checking assumptions (normality, homogeneity), performing advanced analyses (Bayesian methods, power analysis), calculating effect sizes, and generating full APA-formatted reports for publication.

A comprehensive tool for interacting with the arXiv database. It allows users to search for academic papers by topic or ID, retrieve detailed metadata (abstracts, authors, categories), and download the PDF files directly. Ideal for researchers and students needing to efficiently find, save, and summarize scientific literature.

This skill systematically verifies the novelty of a proposed research method or idea against global academic literature. It extracts core technical claims, conducts multi-source searches across major databases (including arXiv, Google Scholar, and top conference proceedings), and utilizes advanced LLM reasoning to generate a comprehensive, structured novelty report. It is designed for researchers needing to confirm the originality and precise positioning of their academic work.

This skill automates the generation of professional, publication-quality figures and comparison tables for academic papers. By analyzing raw experiment data (CSV, JSON), it can automatically create various data visualizations—including line graphs, bar charts, scatter plots, and heatmaps—and structure them according to a predefined figure plan. It ensures consistent styling (DPI, font size) suitable for LaTeX submission.

A comprehensive tool for generating publication-quality figures essential for Machine Learning and AI academic papers. It supports two distinct workflows: generating complex system architecture and workflow diagrams using AI (Gemini), and creating precise, data-driven visualizations (line charts, heatmaps, etc.) using standard libraries like matplotlib and seaborn. Use it when preparing any figure for a conference submission.

A sophisticated, multi-stage workflow designed to generate publication-quality technical illustrations, such as architecture diagrams and complex method figures, for academic papers. It utilizes a strict, iterative loop supervised by an advanced AI (Claude) to refine layout, color compliance, and structural correctness, ensuring high fidelity and professional standards across multiple rendering passes.

This skill searches for published academic papers from major venues like IEEE, ACM, and Springer via the Semantic Scholar API. It is ideal for finding peer-reviewed journal articles and conference proceedings, providing crucial metadata such as citation counts, venue details, and TLDR summaries. Use it when you need verified, published literature beyond raw arXiv preprints.

This skill enhances research query formulation by translating vague, colloquial, or generalized descriptions into precise, standard academic terminology. When initial search terms are broad (e.g., "conjugal happiness"), this technique suggests multiple plausible academic synonyms (e.g., "marital satisfaction," "relationship quality"). By improving the precision of the search query and incorporating structured constraints (like keywords, years, or sample sizes), it significantly boosts the relevance and effectiveness of academic paper retrieval.

This skill provides direct command-line access to the Paperzilla platform, allowing users to manage, summarize, and retrieve academic research data. Users can fetch canonical papers in markdown format, get the latest project recommendations, analyze paper relevance, export data (JSON/Atom), and provide feedback on recommendations. It is an essential tool for researchers managing a large volume of academic literature.