Skill UI

A comprehensive guide for strengthening empirical causal claims for top-tier economics journals. This framework teaches how to move beyond simple OLS regressions by rigorously testing for causal identification (e.g., DID, IV, RDD) and, crucially, mapping the statistical estimate back to a meaningful economic parameter or mechanism. It emphasizes the dual requirement of credible identification and deep economic interpretability.

This guide helps researchers refine their academic work to meet the rigorous standards of top economics journals like JPE. It teaches users to move beyond simple correlation by structuring their research around clear economic mechanisms, linking evidence to established theory, ensuring generality, and properly considering equilibrium effects. Use this when developing a paper pitch or deciding the overall scope of a manuscript.

This guide provides an advanced framework for conducting rigorous causal inference and policy evaluation, essential for academic journals. It covers state-of-the-art methods including DiD, RDD, Synthetic Control, and experimental analysis. The core focus is moving beyond simple p-values to estimate effect magnitudes in tangible 'decision units' (e.g., dollars per household, percentage points). It mandates comprehensive stress-testing, including pre-trend checks, placebo outcomes, and detailed subgroup heterogeneity analysis, ensuring results are immediately actionable by regulators.

This skill guides the development of the theoretical framework for policy-related manuscripts, focusing on building a rigorous 'theory of the policy lever.' It helps users account for the mechanism by which a mandated rule, restriction, or default changes marketplace behavior, considering unintended consequences, strategic firm responses, and the effect on vulnerable populations. It moves theory beyond simple hypothesis generation.

This guide establishes rigorous methodological standards for incorporating forecasting and prediction claims in academic manuscripts. It emphasizes the necessity of genuine out-of-sample evaluation, comparison against robust benchmarks (like Random Walk or AR models), and utilizing advanced statistical tests (e.g., Diebold-Mariano) to prove prediction superiority, moving beyond simple in-sample fit reporting.

This guide enforces rigorous standards for reporting clinical trial statistics, moving beyond simple P values. It mandates the use of confidence intervals, absolute and relative effect sizes, clear designation of the primary analysis population (ITT), and proper handling of multiplicity and missing data, aligning with standards set by top-tier medical journals.

This guide helps authors structure their academic manuscripts for top-tier Information Systems journals (e.g., MISQ). It emphasizes moving beyond simple gap-spotting by requiring authors to explicitly join an established IS conversation, keep the IT artifact central to the theory, and clearly differentiate the contribution from parent disciplines and adjacent venues.

This guide provides a rigorous framework for conducting mechanism (mediation/moderation) and heterogeneity analyses for empirical research papers, particularly adhering to high academic standards. It helps researchers move beyond simple correlation to establish causal pathways ('why') and identify differential effects ('for whom') by incorporating theoretically grounded intermediate variables and performing sophisticated econometric tests like causal mediation and interaction effects.

A comprehensive guide for placing interdisciplinary academic manuscripts within live, cross-field debates. It teaches authors to move beyond simple literature reviews by identifying the precise 'seam'—the unique contribution—that emerges only when braiding together two or more distinct academic literatures, thereby defining the specific gap as an active disagreement.

This guide provides a structured approach for writing high-stakes author responses to academic paper reviews (like those in OOPSLA). It teaches authors how to move beyond simple rebuttals by framing every concern as an argument supporting a desired outcome (Accept, Minor Revision, Major Revision, or Reject). Focus areas include quantifying feasibility, structuring the argument for committee skimming, and strategically shaping the scope of required revisions.

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 allows agents to retrieve and inject relevant operational memories from the OpenViking experience library into the current prompt context. It is designed for complex, multi-step tasks involving tool usage, code operations, or decision-making workflows. By searching and reading past successful executions, the agent improves context awareness and decision accuracy, moving beyond simple Q&A.