Skill UI

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.

A comprehensive guide for planning rigorous scientific studies in Earth and Planetary Sciences, covering sampling, analytical campaigns, experimental runs, and modeling. It ensures that research designs are robust, addressing critical elements like sample context, traceability to reference materials, replication levels, and falsifiability before data collection begins. Essential for high-impact scientific publishing.

A comprehensive audit checklist designed for authors submitting data-engineering systems papers to major conferences like ICDE. It covers critical areas including IEEE formatting standards, round selection strategy, Microsoft CMT conflict declarations, and the requirement for supplemental material, ensuring authors mitigate common desk-reject risks.

A guide for designing and structuring empirical tables and figures for submissions to International Organizations (IOs). Focuses on meeting strict word limits, ensuring exhibits are self-contained, reproducible, and clearly separating core arguments (main text) from supporting details (supplementary material). Best practices include explicit unit labeling, prioritizing effect plots over dense tables, and guaranteeing that all displayed numbers match the original analysis code.

Provides comprehensive guidelines for creating self-contained, publication-ready tables and figures for academic manuscripts, specifically adhering to the Journal of Marriage and Family (JMF) style. It covers modified APA conventions, displaying effect sizes and confidence intervals, ensuring accessibility (grayscale/colorblind), and managing strict page budgets by distinguishing between main text and supplementary material.

This guide provides best practices for presenting tables and figures in academic manuscripts, specifically tailored to the requirements of the Journal of Public Administration Research and Theory (JPART). It emphasizes that exhibits must be self-contained, focusing on communicating mechanisms and effect magnitudes rather than just statistical significance. It also guides authors on managing word limits by strategically defining the role of core findings versus supplementary material.

This skill guides the creation of self-contained, highly accessible, and reproducible exhibits (tables, figures, maps) for World Politics manuscripts. It addresses strict length limits by differentiating between core arguments (in the article) and supplementary material (online appendix). It emphasizes visual communication excellence, moving beyond simple coefficient tables to forest plots and event studies to convey magnitude and uncertainty effectively.

A specialized skill designed to convert complex legal materials—such as contracts, matter descriptions, corporate structures, timelines, or compliance processes—into context-appropriate, structured Mermaid diagrams. It utilizes a multi-step process involving structured data extraction, LLM enrichment, and mandatory gates to ensure accuracy. Ideal for visualizing relationships, obligations, and flows in legal documents, but strictly limited to legal or legal-adjacent diagrams.

ClickHouse database patterns for high-performance analytics, including table design, query optimization, bulk inserts, materialized views, and performance monitoring.

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.