Skill UI

This skill serves as the central orchestrator dashboard for authors submitting manuscripts to PR&AI (Pattern Recognition and Artificial Intelligence). It meticulously outlines the entire publication lifecycle, from initial topic selection and structured writing to experimental design, rigorous self-review, navigating peer review stages (initial, expert, final), addressing revisions, and preparing the final camera-ready submission. It breaks down the academic process into actionable stages and critical milestones, ensuring no crucial step is overlooked during the 6-month review cycle.

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.

This skill is designed to help authors determine if their manuscript is appropriate for submission to Progress in Energy and Combustion Science. It provides a rigorous checklist for evaluating whether a work meets the journal's high bar for critical synthesis, comprehensiveness, and authority. It guides authors to reframe primary research into an integrative, agenda-setting review, covering scope, method rigor, and specific submission requirements.

A comprehensive guide designed for authors targeting PRX Quantum. It helps determine the suitability of manuscripts in quantum information science, quantum computing, or quantum technologies. The skill provides detailed guidance on the journal's scientific scope, required significance bar, structure, and open-access submission standards.

This skill guides the planning of psychological studies to meet the highest academic standards. It provides comprehensive methodologies for performing power analysis, justifying sample sizes, and implementing preregistration protocols. Use this when initiating a new research project or developing a pre-analysis plan to ensure the study design is robust and transparent.

This guide details best practices for creating high-impact tables and figures for psychological science manuscripts, adhering to APA 7th edition guidelines. It emphasizes showing effect sizes, uncertainty (like confidence intervals), and embedding visuals directly within the main text near their first discussion, moving beyond traditional end-of-document placement. It covers data visualization principles and manuscript triage.

A comprehensive guide and fit test designed to help researchers assess whether their empirical psychology project meets the high standards of top-tier journals like Psychological Science. It evaluates key criteria including broad impact, statistical robustness, open science readiness (preregistration/data sharing), and adherence to strict format limits. Use this skill to pressure-test your idea before committing resources to data collection or analysis, guiding you toward the optimal manuscript type (e.g., Research Article vs. Registered Report).

A comprehensive guide for designing and documenting systematic literature searches for meta-analyses or systematic reviews. It ensures reproducibility by covering multiple databases (e.g., PsycINFO, PubMed), controlled vocabulary, grey literature, and adhering strictly to PRISMA-S guidelines. It helps build a robust, traceable research pool.

A comprehensive skill for advanced meta-analysis in psychology, designed to assess the reliability and sources of heterogeneity. It performs moderator/subgroup analyses (meta-regression) to explain effect size variation and runs multiple publication-bias diagnostics (e.g., Funnel plot, Egger's test, p-curve, selection models). Essential for rigorous academic reporting requiring robust evidence and sensitivity checks.

A comprehensive guide for designing conceptual figures for highly theoretical manuscripts (e.g., Psychological Review). This skill teaches how to create two types of non-experimental exhibits: structured model/architecture diagrams and simulation-of-model-behavior plots. It emphasizes rigorous academic standards, including defining constructs vs. processes, distinguishing predictions from fits, and ensuring figures are self-contained and diagnostic.

This comprehensive framework guides the rigorous design and defense of research in public administration. It covers essential causal inference methodologies, including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity (RD), and various experimental designs on bureaucrats and citizens. Use this guide when defining identification, responding to reviewer critiques regarding causality, or pre-registering a study, ensuring the design is both academically sound and practically relevant to public policy.

Provides comprehensive guidelines for designing tables and figures (exhibits) for academic manuscripts. The focus is on creating self-contained, highly accessible visualizations that effectively communicate quantitative effect magnitude and uncertainty to both specialized scholars and public practitioners, optimizing impact for publication.