Skill UI

This skill compiles comprehensive external evidence required for drafting high-quality scientific manuscripts or research briefs. It goes beyond simple link lists, targeting verified, unique academic references (e.g., 60 references) and generating a structured research packet. Use it when you need literature reviews, evidence supporting a claim, or a deep dive into scientific background, methodology, or limitations.

This skill provides a systematic framework for evaluating the rigor of scientific claims, research methodology, and evidence quality. It guides users through assessing experimental design validity, identifying various types of biases (e.g., selection, cognitive), and applying established grading frameworks like GRADE or Cochrane Risk of Bias. Ideal for systematic reviews, peer review, and critical analysis of scientific literature.

Conduct rigorous, systematic literature reviews across diverse academic databases (e.g., PubMed, arXiv, Semantic Scholar). This skill facilitates meta-analysis, scoping reviews, and research synthesis, generating professionally formatted documents (Markdown/PDF) with verifiable citations in multiple styles. Crucially, it mandates the integration of AI-generated scientific schematics (e.g., PRISMA flow diagrams) to provide comprehensive visual context for academic publications.

This guide identifies and provides solutions for common anti-patterns and mistakes when working with Snowflake. It covers best practices in SQL writing, warehouse resource management, data loading strategies (e.g., using MERGE), and access control setup. It is essential for auditing existing deployments, onboarding new users, or performing code reviews to ensure cost efficiency and data integrity.

This skill leverages the Gemini AI model to perform comprehensive and broad literature discovery across academic domains. Unlike traditional APIs, it decomposes complex research queries into sub-problems, explores topic aliases, and surfaces highly relevant papers that might otherwise be missed. It is ideal for conducting deep, multi-angled literature reviews and achieving a holistic view of a research field.

A powerful skill for searching and retrieving comprehensive academic metadata using the OpenAlex API. It provides a unified view of research papers, including full open citation graphs, detailed institutional affiliations, and crucial funding information (e.g., NSF, NIH). Ideal for deep academic research, comparative literature reviews, and identifying research trends across multiple disciplines.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

A comprehensive, domain-agnostic 13-agent system designed for rigorous academic research on any topic. It guides users through the entire research lifecycle, supporting deep literature reviews, systematic meta-analysis, cross-source synthesis, bias assessment, and generating professional APA 7.0 reports. Ideal for academics, students, and analysts needing structured, deep insights.

This meta-skill automates the entire process of transforming raw Excel data into structured business insights. It reads the raw data, performs advanced trend and anomaly analysis, writes the resulting findings to a dedicated 'Insights' sheet, and persists key performance indicators (KPIs) to long-term memory. Ideal for comprehensive business reviews and data-driven decision-making.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.