Skill UI

This guide details the complex, multi-stage review process for top-tier AI conferences like IJCAI. It covers strategies for Phase 1 summary rejection, managing conflicts of interest, understanding the roles of decision actors (PC, AC, SAC), and optimizing paper clarity to maximize acceptance chances. Use this when planning a submission strategy or interpreting reviewer feedback.

This guide provides advanced methodological guidance for establishing causality and identifying policy effects within complex international macro datasets. It covers best practices for cross-country panel analyses, high-frequency policy surprise detection, crisis event studies, and structural modeling, ensuring that observed variation is rigorously linked to policy-relevant factors, respecting cross-country dependence and global shocks.

A comprehensive guide for designing and stress-testing asset-pricing empirical models, tailored for submissions to top-tier finance journals. Covers methodologies like Fama–MacBeth regressions, factor model comparisons, handling standard-error subtleties, and rigorous out-of-sample validation. Essential for ensuring results survive academic scrutiny, addressing issues like multiple testing and economic magnitude.

A comprehensive methodological guide for conducting rigorous quantitative research in finance, covering asset pricing, corporate finance, and econometrics. This skill defines the necessary standards for factor construction, portfolio sorting, advanced estimators (Fama-MacBeth, GMM), robust standard error clustering, and multiple-testing discipline. It ensures research designs are academically sound, reproducible, and suitable for top-tier financial journals.

This guide helps researchers structure the Policy Contribution Statement required by journals like JPP&M. It teaches how to transform solid research findings and data estimates into actionable, evidence-based policy recommendations. Focus areas include defining the policy conversation, identifying specific regulated actors, ensuring recommendations are within the actor's authority, and strictly linking claims to the empirical evidence provided.

A guide for researchers on transforming diverse experimental results into a single, coherent, and highly focused molecular narrative. It teaches the structure required for top-tier molecular biology publications, emphasizing the link between the molecular actor, the proven mechanism, and the physiological consequence. Essential for shifting the focus from a 'catalog of techniques' to a unified, powerful scientific argument.

This skill guides the development of a robust theoretical contribution for Organization Studies manuscripts. It focuses on defining the generative mechanism, process model, or conceptual move that drives the argument, rather than merely describing data or themes. Users learn how to state the core logic, identify actors and structures, specify phases, and define boundary conditions to ensure the contribution is genuinely novel and impactful.

This guide outlines the rigorous analytical methodology required for Operations Research (OR) manuscripts. It instructs users on selecting the appropriate mathematical machinery—such as duality, dynamic programming, convergence analysis, or concentration inequalities—to establish provable guarantees, approximation factors, and algorithmic complexity. It ensures that claims are backed by rigorous proofs, moving beyond mere heuristics.

Comprehensive guidelines for auditing and reproducing high-stakes empirical financial research. This resource details the rigorous standards required for top-tier finance journals, covering sample construction, identifying variables, advanced econometric modeling (e.g., panel data, factor pricing), handling international cross-market data, and establishing a fully reproducible data pipeline. Essential for ensuring the robustness and credibility of finance findings.

This skill generates fully valid Microsoft Threat Modeling Tool (.tm7) files. It translates complex system architectures, including components, data stores, data flows, and external actors, into the required WCF DataContractSerializer XML format. Use it for structured STRIDE threat modeling outputs compatible with Microsoft's official tool.

An autonomous system designed to continuously improve code quality by scanning codebase metrics. It functions as an agent, proposing mechanical code changes, executing them, and committing only if defined metrics improve. It supports multiple modes (Scan, Scaffold, Run) for systematic, data-driven codebase refactoring.

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.