Skill UI

A comprehensive guide detailing the standards for scientific reproducibility in visualization research, particularly for IEEE VIS submissions. It outlines the Graphics Replicability Stamp Initiative (GRSI) requirements, covering how independent volunteers must reproduce results using provided code, data, and environments (e.g., Docker containers). Learn how to package your work—including determinism aids, mapping tables, and licensed data—to pass rigorous, clean-machine testing.

This guide details best practices for achieving high standards of reproducibility in visual analytics papers, focusing on open materials, verifiable code, and rigorous documentation. It covers mapping figures to data sources, preregistering studies, documenting data provenance, and defining the level of reproducibility achieved (e.g., turnkey, scripted).

This guide helps researchers determine if their project qualifies as a visualization contribution (beyond general HCI or ML). It provides structured criteria for choosing the best conference venue (e.g., IEEE VIS, EuroVis, CHI) and mapping the work to one of the six core visualization areas based on contribution type and evidence maturity.

This guide helps researchers move beyond decorative theory to construct 'load-bearing' conceptual or analytical frameworks for World Development (WD) manuscripts. It outlines how to transform vague ideas into structured, testable mechanisms by stating clear mechanisms, deriving discriminating predictions, mapping predictions to evidence, and defining scope conditions, ensuring the theory actively drives the empirical argument.

This skill guides the construction of complex legal arguments, adhering to the standard persuasive arc: doctrine → theory → normative. It ensures the writing systematically moves from mapping existing law (the problem) to developing a conceptual framework (the why) and finally proposing actionable reforms (the fix). It is essential for building a rigorous, logical, and comprehensive academic argument.

Seaborn is a high-level Python visualization library designed for creating publication-quality statistical graphics. It facilitates dataset-oriented plotting, multivariate analysis, and complex statistical visualizations (like KDEs, distributions, and relationships) directly from Pandas DataFrames with minimal code. It builds upon Matplotlib to provide semantic mapping and statistical awareness.

This skill maps chronic conditions extracted from clinical notes to CMS-HCC V28 categories. It estimates the Risk Adjustment Factor (RAF) score, which is crucial for Medicare Advantage payments. It serves as decision support for coders by identifying candidate HCCs, applying complex coding hierarchies, and checking for MEAT documentation evidence for human validation.

Provides decision support for mapping diagnoses and procedures extracted by OpenMed to standardized ICD-10-CM and ICD-10-PCS codes. This skill suggests candidate codes along with detailed clinical rationale, helping human coders narrow down options, route findings to specific chapters, and pre-fill encounter records. Note that the output is advisory and requires mandatory validation by a certified medical coder.

This specialized skill guides users through analyzing complex Active Directory Certificate Services (AD CS) abuse scenarios. It is essential for proving how a weakness in a template, CA policy, or issuance right can lead to unauthorized privilege acceptance (e.g., via PKINIT, Schannel). The workflow focuses on mapping the entire certificate issuance chain to the resulting accepted service path.

A specialized deep-dive skill for analyzing container-to-host escape vulnerabilities. This tool is used after a sandbox orchestrator establishes initial assumptions, focusing on mapping isolation boundaries (namespaces, cgroups, seccomp, capabilities). It helps prove boundary crossings, identify minimal exploit primitives, and determine if an exploit can break out of the container context to the host kernel.

This specialized skill is designed to trace and prove the complete flow of OAuth or OIDC authentication, acting as a downstream specialization after an orchestrator has established sandbox assumptions. It meticulously tracks the entire journey—from initial redirect and parameter handling (state, nonce, PKCE) through token exchange, claim mapping, and ultimately to the point where an identity or privilege is accepted by the backend service. Use this when the critical task is proving the security and mechanics of the authentication chain.

A specialized downstream skill for deep analysis of complex web rendering pipelines. Use this to trace vulnerabilities or logical flaws residing in Server-Side Rendering (SSR), template data, route loaders, or client-server hydration boundaries. It compares template-level gating against backend handler enforcement to pinpoint the decisive weak point in the render chain.