Skill UI

A comprehensive guide for stress-testing causal identification in empirical microeconometrics. It covers advanced methods like RCT, DID, RDD, and IV, emphasizing robustness checks, identifying selection bias, and structuring results for clear public policy interpretation in high-impact academic journals.

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 guide teaches the rigorous method of stress-testing academic arguments by anticipating and addressing the strongest potential objections. It provides a structured framework for identifying weak premises, boundary cases, and constructing precise replies (rebuttal, concession, or acceptance of cost). Essential for advanced academic writing, especially in philosophy, to ensure your argument survives expert scrutiny.

A comprehensive guide for stress-testing the evidence supporting ML claims before submitting to top-tier academic conferences. Covers rigorous auditing of baselines, ablation studies, robustness checks, data leakage, and calibrating claims against evidence strength, ensuring scientific reproducibility.

A detailed guide for authors submitting review essays to highly selective journals, outlining the double-anonymous review model. It teaches authors how to anticipate expert critiques—moving beyond simple summaries to demonstrate critical intervention, conceptual clarity, and forward contribution. Covers desk-reject triggers and best practices for pre-submission stress-testing.

This skill guides the execution and stress-testing of empirical analysis for innovation studies (Research Policy). It details how to build reproducible bibliometric and patent variables, select appropriate econometric models (like Poisson/Negative Binomial for counts), and establish robust evidence. The focus is on addressing methodological challenges, ensuring transparent variable construction, and performing rigorous sensitivity checks to withstand expert scrutiny.

This guide provides a rigorous framework for stress-testing and implementing state-of-the-art causal identification strategies required for high-impact empirical economics. It covers advanced methodologies including Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity (RDD), Synthetic Control, and Structural Modeling. It emphasizes modern estimators (e.g., Callaway-Sant'Anna, effective F) and robust diagnostic checks to ensure the causal claims are methodologically sound and defensible.

A comprehensive guide for executing and stress-testing empirical analyses in Industrial Organization (IO). It covers structural and reduced-form model diagnostics, advanced inference techniques (e.g., wild-cluster bootstrap), counterfactual validation, and meeting the rigorous robustness standards demanded by top-tier academic journals. Focuses on methodology, not study design.

A comprehensive audit tool for stress-testing the logical coherence of sociological theory manuscripts. This skill guides the user through checking every link in the theoretical spine (premises → mechanism → propositions → conclusion), ensuring that claims are warranted, identifying strongest rival explanations, and handling potential counter-cases. It strengthens the argument itself, independent of empirical data.

This command acts as a crucial product gate, forcing a deep, strategic review before any code is written. Instead of simply fulfilling the request, it guides users through three structured roles: Scope Expansion (finding the 10x vision), Hold Scope (stress-testing assumptions and failure modes), or Scope Reduction (defining the true MVP). It ensures that the developed solution solves the user's real job-to-be-done, not just the explicit feature request.

Adversarial stress-test for legal texts (contract, statute, regulation, or judicial opinion) that finds ambiguous seams and turns each into a concrete dispute scenario with both sides' arguments, likely outcome, and a fix. Ideal for pressure-testing, red-teaming, auditing, or identifying loopholes and drafting problems in legal documents.

This tool simulates an experienced opposing counsel, providing a deep, adversarial analysis of legal arguments, submissions, or statements. It goes beyond mere critique, generating a six-part structure: a core theory of attack, structural deconstruction, primary lines of flaw (e.g., evidential gaps, legal misstatements), and high-impact points for oral submissions. Ideal for stress-testing legal writing before litigation.