Skill UI

A comprehensive guide for authors submitting to top Operations Management journals, such as M&SOM. It teaches how to translate complex analytical or empirical results into explicit, actionable operational contributions. The focus is on making the managerial implication, the core operational decision, and the structured abstract components clearly defined, moving the emphasis away from methodological novelty.

A comprehensive CLI skill for managing PowerPoint presentations (.pptx). This tool allows users to create, read, parse, edit, split, or combine slide decks programmatically. Beyond basic file manipulation, it enforces professional design standards, ensuring every output deck adheres to best practices regarding text hierarchy, visual components, and content density, making it ideal for automated report generation and pitch deck creation.

A comprehensive guide detailing how to structure a technical paper (such as those submitted to POPL) across three components: the main body, the detailed appendix, and anonymous supplementary artifacts. It covers content placement, ensuring internal consistency between sketches and proofs, and methods for maintaining full double-blind anonymity during submission.

This guide outlines the rigorous data and transparency requirements for submitting academic manuscripts, particularly for social science journals. It details two core components: methodological disclosure via 'Appendix A: Disclosure Elements' and building a complete replication package. Authors must ensure all published tables and figures can be reproduced exactly using deposited data and code in a permanent archive (Dataverse) before the paper advances to typesetting.

This guide outlines best practices for creating quantitative exhibits in dynamic macroeconomics papers. It covers crucial components like Impulse-Response Functions (IRFs), calibration tables, moment-matching results, and policy counterfactuals. The focus is on ensuring the model's mechanism and quantitative fit are clear, legible, and self-contained for expert review.

This comprehensive guide provides structured rules for writing the two most critical components for high-impact scientific submissions (like Science/AAAS): a one-sentence summary and a polished abstract. It teaches authors how to shift focus from methodology to quantified results and broad implications, ensuring the work is accessible and compelling to a general scientific readership.

A comprehensive guide for packaging and submitting artifacts for Information Retrieval (IR) conferences (like SIGIR). It details the strict requirements for reproducibility, including mandatory components like TREC-format run files, qrels, and index recipes. The process covers repository structure, anonymization for review, handling data provenance, and ensuring that results can be audited by any reviewer using standard community tooling.

A comprehensive guide for structuring and refining high-quality database systems research papers for top-tier conferences like SIGMOD. It covers essential components such as establishing a clear page-one contract, integrating running examples, scoping measured system claims, adopting third-person voice, and adhering to the 12-page ACM template structure for maximum technical impact.

A sophisticated guide for social science researchers to transition from empirical evidence (coefficients, fieldwork notes) to robust, theory-driven narrative. It teaches how to structure an argument by identifying the four core components: Actioner, Structural Condition, Mechanism, and Consequence. This method ensures the explanation moves beyond mere correlation to deeply explain *how* and *why* social outcomes are generated or reproduced.

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.

This guide outlines the methodology for preparing research artifacts for rigorous academic reproducibility evaluations, such as those run by VLDB/SIGMOD. It details the required components—including prototype code, input data, workloads, and analysis scripts—to structure a comprehensive package. The goal is to ensure that any external evaluator can independently and flawlessly rebuild and validate all claimed results, maximizing the chances of winning reproducibility awards.

Provides a comprehensive, quantitative auditing system for AI agents, skills, and commands. It evaluates these components against industry best practices using a multi-criteria weighted scoring model and assign a production readiness grade (A-F). Ideal for validating complex AI systems before deployment, identifying gaps, and ensuring robust, maintainable code.