Skill UI

A comprehensive preflight checklist designed for authors submitting academic manuscripts to major publishing portals (e.g., Cambridge University Press ScholarOne). It ensures adherence to strict academic standards, including double-anonymous anonymization, verifying sectional word limits, checking specific style guides (like Language Style Sheet), and validating specialized linguistic elements such as Leipzig glossing and IPA before the final submission.

This tool acts as an orchestrator for submissions to the journal *Language* (LSA). It guides authors through the complex manuscript development process by identifying the appropriate piece type (e.g., General Research Article, Review Article) and routing them to the necessary specialized skills (e.g., theory building, literature positioning, data analysis). It helps authors structure their work and ensure theoretical depth and cross-subfield legibility.

This skill polishes the prose and ensures the house style of a linguistics manuscript, making it legible to a general audience across diverse subfields and frameworks. It focuses on structuring the argument for clarity, defining jargon, leading with the main claim, and conforming citations to the specific Language Style Sheet, rather than building the core theoretical argument itself.

This skill guides authors on whether their linguistics research is broad enough for Language (LSA's flagship journal). It checks for a clearly stated, generalizable claim backed by rigorous, cross-linguistic data, and adherence to high academic standards, ensuring the work transcends a single subfield.

This tool guides the refinement of academic prose, specifically for submissions to Management Science (INFORMS). It focuses on transforming notation-dense text into clear, impactful, and highly readable manuscripts. Key practices include front-loading the core results, translating complex symbols into plain language intuition, and adopting a style suitable for a broad, cross-departmental academic audience.

This skill refines complex philosophical prose, ensuring rigorous arguments are highly accessible and easy to follow for a broad academic readership. It focuses on maximizing clarity, achieving linguistic economy, and ensuring all technical concepts are accompanied by plain-language exposition. Ideal for final drafting passes, improving readability, and adhering to strict word limits.

A rigorous guide for authors evaluating if their literary-history manuscript meets the high standards of Modern Language Quarterly (MLQ). It focuses on structuring an original argument about demonstrable literary change, periodization, and engaging with disciplinary debates, rather than relying on purely formalist readings.

Provides rigorous guidelines for structuring and writing high-quality academic literature reviews, specifically tailored for journals like Management World. It mandates a unique three-layer dialogue structure (international context, local Chinese research, and original contribution), addressing issues like language source imbalance or lack of scholarly dialogue. Covers precise ratios for Chinese and English sources, and integration with national policy narratives.

This guide provides comprehensive best practices for packaging and documenting NLP research artifacts (datasets, models, prompts, etc.) for academic submission (e.g., NAACL/ARR). It emphasizes rigorous provenance tracing, ensuring reproducibility, and ethically handling sensitive data, particularly community-owned or indigenous language resources.

This guide provides an expert methodology for designing and auditing Natural Language Processing (NLP) experiments for top-tier academic submissions. It instructs researchers on how to map meta-review claims to measurable evidence, ensure budget-fair comparisons, and systematically address potential reviewer probes (scope, fairness, contamination, etc.) to maximize publication rigor.

This guide outlines the stringent standards for ensuring the reproducibility of Natural Language Processing (NLP) research. It teaches authors how to treat the Responsible NLP checklist as a binding contract by meticulously 'pinning' every variable—including model identifiers, API access dates, prompt strings, random seeds, and evaluation metrics. It details creating a comprehensive reproducibility manifest to make research results verifiable and defensible.

This skill serves as a detailed guide for authors submitting theoretical articles in syntax or morphology to Natural Language & Linguistic Theory (NLLT). It outlines the journal's specific expectations, emphasizing that formal analyses must be deeply grounded and rigorously tested using rich, representative, and often cross-linguistic empirical data. Use this tool to assess the methodological rigor, scope fit, and structural requirements of your manuscript against NLLT's high academic standards.