Skill UI

A comprehensive tool for training and evaluating advanced neural network models (including LSTM, Transformer, and N-BEATS) on time-series market data. It facilitates the prediction of financial trends, generating results with confidence intervals, and comparing performance across multiple architectures. Ideal for quantitative trading research and financial forecasting.

This skill utilizes hyperbolic space embedding (Poincare ball model) to represent complex data structures with inherent hierarchy, such as dependency trees, ontologies, or module taxonomies. Unlike standard Euclidean embeddings, hyperbolic space preserves hierarchical distances efficiently, allowing for accurate distance calculations (geodesic distance) that grow logarithmically with tree depth. It is ideal for advanced knowledge graph analysis and code architecture mapping.

A comprehensive guide for strengthening the methodological rigor of academic manuscripts, particularly for high-stakes journals. It covers advanced techniques for causal identification (e.g., Difference-in-Differences, Instrumental Variables, Regression Discontinuity), pre-analysis planning, linking theory to empirical tests, and defending claims against skeptical reviewers. This skill focuses on methodological architecture, not code.

A rigorous self-assessment tool for academic manuscripts in game theory and economic behavior. It guides the identification of core assumptions, tests the logical architecture of proofs, and verifies the generalizability of results. It covers both theoretical proofs (e.g., equilibrium, mechanism design) and experimental designs, ensuring the argument withstands specialist scrutiny.

A comprehensive guide for designing conceptual figures for highly theoretical manuscripts (e.g., Psychological Review). This skill teaches how to create two types of non-experimental exhibits: structured model/architecture diagrams and simulation-of-model-behavior plots. It emphasizes rigorous academic standards, including defining constructs vs. processes, distinguishing predictions from fits, and ensuring figures are self-contained and diagnostic.

This guide outlines the comprehensive policy and architecture required for submitting a fully reproducible replication package to The Review of Economics and Statistics (REStat). It details how to structure the repository, including data, master scripts, and the README file, ensuring that every result can be traced and regenerated by other researchers.

A comprehensive guide detailing the rigorous, multi-stage academic review process for top-tier data mining conferences (e.g., WSDM). It analyzes the hybrid single/double-blind architecture, the impact of no rebuttal phase, and the distinct perspectives of academic and industry reviewers. Use this guide to understand the requirements for writing and structuring submissions that maximize acceptance chances.

This specialized skill is designed for advanced reverse engineering of firmware images in CTF environments. It guides users to map partition tables, trace complex boot chains (bootloader, kernel, init), analyze update packages, and recover embedded secrets or credentials. Use it when understanding the device's core architecture and execution path is necessary to find the decisive artifact.