Skill UI

This guide helps researchers structure their economic questions for top experimental economics journals. It emphasizes framing the contribution around a novel, clean experimental design (the 'minimal pair') and the treatment effect, rather than merely the topic itself. It guides authors on decision-making regarding experimental types, pre-registration, and selecting the appropriate academic venue.

This guide instructs authors on crafting highly targeted and convincing robustness sections for empirical finance papers. Instead of merely adding volume, it teaches the concept of 'subtraction, then precision'—identifying specific alternative explanations (threats) a referee might raise (e.g., reverse causality, omitted variables) and selecting the minimal, most effective check to neutralize each threat. This aligns with the philosophy of top-tier financial journals that value new ideas over superficial testing.

A comprehensive guide for authors responding to technical reviews and revising conference papers during a limited, combined rebuttal window. It teaches how to strategically triage objections, run decisive experiments, craft arguments for a program committee champion, and ensure minimal, faithful revisions to maximize acceptance chances.

Provides comprehensive guidelines for packaging research artifacts (code, data, logs) for submission to data mining conferences like ICDM. The focus is on ensuring the artifact is completely anonymous for triple-blind review (scrubbing Git history, paths, and internal names) and maximizing reproducibility, allowing reviewers to verify results with minimal effort.

This guide details the process of packaging artifacts for academic conferences (ICLR), ensuring that research claims are fully reproducible and reviewable. It emphasizes providing minimal reproduction paths, maintaining data provenance, rigorously anonymizing metadata to protect authors' identities, and creating robust, permanent records for the scholarly community.

Provides comprehensive guidelines for packaging supplementary materials, including code, data, model weights, and benchmarks, for major machine learning conferences like ICML. It details the requirements for both the double-blind review stage (focusing on anonymization and minimal replication commands) and the final public release package (ensuring permanent public links and clear licensing).

This guide provides strict guidelines for authors submitting highly theoretical papers (e.g., to Journal of Economic Theory) regarding computational, numerical, or empirical evidence. It enforces the 'theory-first' principle, ensuring that all quantitative work—including simulations, examples, and counterexamples—must serve to illustrate, test, or deepen the main theoretical contribution, rather than standing as a standalone finding. Key requirements include maintaining reproducibility, keeping examples minimal, and proper structural placement.

A comprehensive guide for integrating Markstream, a high-performance Markdown renderer, into modern frontend frameworks like React, Vue, Svelte, and Next.js. It handles complex streaming scenarios, ensuring minimal peer dependencies, correct CSS ordering, and proper Server-Side Rendering (SSR) boundaries for dynamic content and AI chat interfaces.

This guide provides expert guidelines for designing high-impact, concise figures specifically for academic publications with strict length limits (e.g., PRL). It emphasizes that every figure must convey a single, central result at a glance. The strategy covers lead figure principles, print standards (single-column legibility, color-blind safety), and panel discipline to ensure maximum clarity and minimal word count consumption.

A methodological guide for empirical economists on balancing theoretical depth with empirical findings. It advises authors on how to structure models—determining if a structural, light, or minimal theory dose is appropriate—to ensure the core contribution remains the testable estimate, rather than the theory itself.

This guide provides rigorous best practices for developing and presenting theoretical economic models for top-tier journals. It emphasizes framing results with a clear economic payoff, maintaining minimal model setups, and ensuring that complex, full proofs are relegated to the online appendix. The goal is to ensure the primary economic insight remains highly visible and actionable, rather than being buried in algebraic machinery.

This guide helps structure and build rigorous academic theories and economic models, especially for accounting manuscripts. Use it when the core challenge is articulating the underlying economic mechanism (friction, channel), building a minimal, provable model, or moving beyond simple correlation (HARKing). It guides the process from raw primitives to testable, proposition-based arguments.