Skill UI

This skill enhances AI responses by simulating the inner monologue and self-correction process of a human being. It moves beyond standard helpful assistance by incorporating three stages: Self (raw instinct), Mirror (critical reflection), and Conscious Response (the polished, human-like output). Ideal for emotional support, personal advice, or writing that requires authentic emotional depth and a distinct point of view, rather than purely factual or structured data.

This framework serves as a rigorous thought partner, designed to challenge underlying assumptions, separate raw evidence from interpretation, and ensure that all conclusions are fully defensible. It guides users to define clear decision goals, test counterfactuals, and calibrate claims strictly to the available data quality. Ideal for high-stakes projects where the cost of error is significant.

This comprehensive guide provides best practices for structuring appendices and supplementary materials for high-level academic journals. It helps authors manage the balance between main text conciseness and academic completeness by clearly defining what belongs in the core narrative (main findings) versus what should be reserved for the supplementary section (detailed proofs, extended experiments, raw data, and multimedia).

This guide provides detailed instructions on designing high-quality visual exhibits for academic literature reviews, such as the Annual Review of Sociology (ARSoc). It covers three primary exhibit types: 'Who-found-what' summary tables, conceptual framework figures, and meta-evidence plots. The focus is on synthesizing findings across multiple studies and structuring arguments, rather than presenting new primary estimates or raw data.

This guide assists researchers in structuring and presenting academic evidence for top-tier journals like ASQ. It provides best practices for both qualitative (establishing transparent data-to-theory links, coding transparency) and quantitative (ensuring robust mechanism testing and alternative explanation checks) analyses. It ensures all theoretical claims are auditable and fully supported by the raw data.

This sophisticated tool is designed to polish scientific manuscripts for high-impact, rigorous journals. It guides users in structuring a mechanistic narrative, ensuring that every claim made in the text is precisely calibrated to the strength of the supporting experimental evidence (e.g., distinguishing correlation from necessity). It focuses on scientific storytelling, nomenclature consistency, and eliminating hype, transforming raw research data into a polished, scholarly article.

A comprehensive guide for creating publication-quality scientific figures, adhering to high-impact journal standards. Covers critical topics such as optimal sizing for print widths, displaying underlying raw data (dot plots, replicates), ensuring colorblind accessibility, structuring stand-alone legends, and maintaining image integrity. Essential reading for researchers preparing manuscripts.

This skill guides authors in transforming raw experimental data into a compelling, logically structured scientific narrative suitable for top-tier journals like JACS. It teaches how to explicitly define the 'chemical advance' by building an evidence-backed claim chain: Problem $ ightarrow$ Advance $ ightarrow$ Evidence $ ightarrow$ Significance. It ensures that every claim of novelty is rigorously supported by data and compares the work explicitly against the closest prior art.

This framework guides authors in transforming raw empirical findings into compelling academic contributions suitable for top-tier finance journals. It teaches how to sharpen the focus from merely presenting 'better data' to articulating the underlying financial mechanism, institutional friction, or policy implication, ensuring the research answers the critical question of 'why it matters.'

This comprehensive guide helps academics transform raw financial data observations into rigorous and high-impact research questions suitable for top-tier finance journals. It teaches a structured methodology involving anchoring the core financial mechanism, integrating specific institutional contexts within China, and defining a clear incremental academic contribution.

This guide provides a structured methodology for authors to transform raw scientific data and multiple findings into a single, cohesive, and high-impact narrative, suitable for top-tier journals like Nature Geoscience. It focuses on identifying the single 'headline advance,' structuring the abstract using the 'Here we show' convention, and ensuring the opening paragraphs immediately convey significance to the Earth system.

A comprehensive guide for constructing rigorous and auditable exhibits (tables and figures) in academic manuscripts, particularly for Organization Studies and process modeling. Learn how to structure data-to-theory evidence tables, process models with explicit mechanisms, and data structure figures to allow reviewers to clearly trace the inference from raw data to theoretical constructs, significantly enhancing the paper's methodological rigor.