Skill UI

A comprehensive guide for authors targeting the ACM Workshop on Hot Topics in Networks (HotNets). This skill helps determine conference fit, refine manuscript framing, and assess the evidence required for early-stage networking ideas and provocative systems. It serves as a crucial tool for submission strategy, ensuring the paper is tailored for a selective CS conference audience.

A comprehensive guide for constructing academically robust and reproducible accounting metrics, such as discretionary accruals, real earnings management, and conservatism scores. This resource details the necessary steps—including estimation models, granularity, sample requirements, and standardized protocols—to ensure submissions meet the rigorous standards of top accounting journals.

This skill guides authors on whether their concise energy science research meets the high-impact, selective criteria of ACS Energy Letters. It provides comprehensive guidelines covering journal positioning, required novelty, evidence rigor, and specific structural rules for areas like photovoltaics, batteries, and electrocatalysis, ensuring the submitted work is a timely and significant single advance.

This tool guides authors on whether their manuscript fits the scope of Advanced Functional Materials. It emphasizes the critical structure-function-application chain, covering highly advanced fields such as optoelectronics, biomedical devices, and soft robotics. It provides criteria for methodology, required evidence, and journal-specific house style.

This skill is a comprehensive guide for authors preparing microeconomic theory, game theory, or theoretical IO manuscripts for submission to the American Economic Journal: Microeconomics. It analyzes journal fit, required theoretical rigor, methodological standards, house style, and potential pitfalls (desk-reject heuristics), helping authors refine their work before formal submission.

This guide outlines the mandatory steps and components required to assemble a robust, reproducible data and code replication package for submissions to the American Economic Journal: Applied Economics (AEJ: Applied). It ensures compliance with the stringent AEA Data and Code Availability Policy, covering data provenance, master scripts, and version control. This package must be built iteratively, not at the acceptance stage.

This guide details how to construct a sophisticated and rigorous robustness suite for top-tier academic econometrics journals (e.g., AEJ: Applied). It moves beyond simple regression tables, providing targeted checks against common methodological threats such as omitted variables, specification search, functional form choices, and incorrect statistical inference. The goal is to systematically demonstrate that the main point estimate is stable, reliable, and not an artifact of the research design.

A comprehensive guide for formatting and presenting empirical results (tables and figures) for submission to the American Economic Journal: Applied Economics (AEJ: Applied). It ensures that main causal estimates are immediately legible to referees by adhering to rigorous academic standards, including presenting standard errors, confidence intervals, and specific exhibit structures like event-study plots and balance tables.

This skill acts as a workflow router, guiding researchers through the entire manuscript lifecycle for submissions to American Economic Journal: Microeconomics (AEJ: Micro). It does not write the paper, but diagnoses the current bottleneck—whether it's topic selection, model refinement, empirical testing, or rebuttal strategy—and specifies which specialized aejmic-* sub-skill to invoke next, ensuring the paper aligns with the specific requirements of AEJ: Micro. Triggered when users are unsure what step to take next, or when revising based on reviewer comments.

A comprehensive strategy guide for authors submitting policy-evaluation papers to top economics journals. It details how expert referees evaluate manuscripts, focusing on four critical areas: policy interest, causal credibility, welfare reading, and robustness. This tool helps authors proactively anticipate and strengthen potential weaknesses before submission or during revision, significantly increasing the paper's chances of acceptance.

This guide outlines the strict transparency and data availability requirements for manuscripts submitted to the American Educational Research Journal (AERJ). It ensures adherence to AERA standards for reporting empirical social science research (both quantitative and qualitative) and the AERA Code of Ethics. It details how authors must make findings reproducible, whether by providing code and data access paths, or by documenting an inspectable analytic trail.

This guide provides comprehensive best practices for ensuring scientific reproducibility in technical papers, particularly for electronics and information processing fields. It covers the critical pillars of documentation: environment setup, data sourcing and preprocessing, full algorithmic disclosure (including pseudo-code and hyperparameters), and robust statistical evaluation. By adopting these standards, authors can transform their work from potentially unverifiable results into credible, verifiable scientific contributions suitable for top-tier journals.