Skill UI

This skill is designed for building complex, audit-ready financial models in Excel. Use it for 3-statement projections, DCF valuation, LBO analysis, unit economics, or advanced scenario planning. It enforces professional standards like the three-zone architecture (Inputs, Calculation, Outputs), strict formula discipline, and robust auditing gates, ensuring the output is suitable for high-stakes decision-making.

A comprehensive skill for Particle Image Velocimetry (PIV) analysis. It processes pairs of images to measure 2D fluid velocity fields. Functions include cross-correlation, vector validation, outlier replacement, and calculating derived metrics like vorticity and strain rate. Essential for experimental fluid dynamics visualization and analysis.

This guide provides comprehensive standards for analyzing and reporting results in Organization Science, a field characterized by diverse methodologies. It ensures methodological rigor and transparency whether the work is qualitative (establishing trustworthiness), quantitative (matching estimators to design), computational (reporting seeds and sensitivity), or formal/analytical. It emphasizes full reproducibility and mechanism-based inference.

A comprehensive guide for selecting and defending appropriate research designs—including qualitative, quantitative, experimental, and computational methods—for organizational science manuscripts. It emphasizes matching the method to the theoretical contribution and level of analysis, rather than solely focusing on causal identification. Learn how to structure your argument, ensure transparency, and build robust mechanism evidence.

This guide assists in the rigorous development of theoretical frameworks for Organization Science manuscripts. It details the two legitimate modes—deductive (a priori) or inductive (grounded)—and emphasizes the critical need to identify the core organizational mechanism, specify the levels of analysis (micro, meso, macro), and articulate cross-level bridging logic and boundary conditions. It guides users beyond simple literature reviews to build genuine, testable theory.

This skill guides researchers in developing theory-driven research questions specifically tailored for submission to top academic journals, particularly Organization Science. It assesses whether a research idea genuinely focuses on organizational processes, identifies the relevant theoretical conversation, and evaluates the suitability of the chosen academic venue against competitors (e.g., ASQ, AMJ). It ensures the question has a clear contribution source and appropriate level of analysis.

This router guides researchers through the entire lifecycle of an Organization Science manuscript, from initial topic selection and theory development to data analysis, contribution framing, and final submission. It does not replace specialized skills but provides a structured roadmap, helping users determine the correct next step and maintain coherence throughout the complex academic writing process.

A comprehensive guide for reporting data analysis in Organization Studies manuscripts. It mandates rigorous analytic transparency by detailing how raw data transitions into theoretical claims. Covers best practices for qualitative coding (data-to-theory ladder), process modeling, and advanced quantitative robustness checks, ensuring the reader can audit the entire inference process.

This router provides a structured roadmap for developing a manuscript targeted at Organization Studies (OS). It guides users through the complex, multi-stage academic process, from initial theoretical concept selection and method design to data analysis and final rebuttal. It diagnoses bottlenecks and dictates the precise sequence of specialized theoretical and writing skills required to meet the high theoretical standards of OS.

This guide helps elevate academic manuscripts to the discursive, theoretically-rich European register of Organization Studies (OS). It focuses on strengthening the argument's arc, ensuring theory is foregrounded throughout (including findings), and refining prose discipline (e.g., concrete verbs, single idea per paragraph). It is ideal when the analysis is sound but the writing style is flat or insufficiently theoretical.

A comprehensive guide for designing and reporting rigorous computational studies in Operations Research (OR) manuscripts. It covers best practices for selecting benchmark instances and strong baselines, applying statistical methods to stochastic output (e.g., confidence intervals), and adhering to mandatory code and data deposit standards (ORJournal workflow) to ensure full reproducibility.

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.