Skill UI

A comprehensive tool for managing and optimizing XML sitemaps. This utility allows users to analyze existing sitemaps for SEO health issues (e.g., 404 errors, stale dates, robots.txt conflicts) and to generate new, structured sitemaps. It adheres to industry best practices across various models (eCommerce, SaaS, etc.), ensuring optimal indexation for search engines.

Performs a deep dive technical SEO audit, covering core web vitals, crawlability, indexation, site architecture, and structured data. This audit identifies technical debt and provides a prioritized, actionable report with specific fixes and expected impact for improving search engine visibility and ranking.

A comprehensive guide detailing the standards required for academic reproducibility in NLP and LLM research. It covers the 'Responsible NLP checklist' requirements, including detailed reporting for hyperparameters, model versions, exact prompts, decoding parameters, data contamination auditing, and variance reporting to ensure claims are auditable and robust.

A comprehensive guide for revising NLP and Computational Linguistics manuscripts for submission to top-tier conferences like ACL. It mandates adopting a task-first, evidence-grounded approach, strictly scoping claims in the LLM era, and ensuring linguistic rigor in all examples and analyses. Learn how to structure, compress, and refine your arguments for maximum impact.

A guide for authors needing to precisely position their theoretical contribution against existing literature. It teaches how to identify the 'delta'—the exact difference (e.g., weaker assumption, new environment, full characterization)—relative to the single closest academic result, rather than making vague claims about the field as a whole.

This guide outlines best practices for authors presenting theoretical and empirical results for top-tier journals like the American Economic Journal: Microeconomics (AEJ: Micro). It covers structuring propositions, building transparent numerical examples, creating schematic figures, and formatting tables (including mandated use of standard errors over significance asterisks) to ensure maximum clarity and adherence to academic publishing standards.

This skill guides authors on how to position their manuscript within the complex, multidisciplinary literature of Agricultural Systems (AgSy). It ensures that the paper advances the conversation by engaging both the domain knowledge and the core modeling/systems methodologies. The process focuses on identifying unresolved systemic trade-offs, pinpointing the exact research gap, and clearly articulating the unique contribution among established alternatives.

This guide outlines the stringent standards for creating tables and figures (exhibits) for the American Journal of Political Science (AJPS). It emphasizes that exhibits must be self-contained, highly accessible, and, critically, regenerated exactly by deposited code for third-party verification. It provides best practices for structuring research results, managing word counts by differentiating between core arguments in the main text and supporting details in the Supporting Information (SI).

This guide provides a detailed architectural framework for writing long-form art-historical essays. It teaches writers how to structure their argument by leading with the core problem and thesis, integrating visual evidence (figures) exactly where the prose requires it, and maintaining strict discipline over word count and endnotes. Essential for transforming a rambling draft into a clear, scholarly argument.

This guide provides detailed protocols for achieving high levels of reproducibility in Computer Aided Verification (CAV) research. It emphasizes the necessity of pinning benchmark sets, recording exact tool versions, documenting resource limits (time/memory), and providing checkable proof witnesses to ensure that evaluation claims can be independently validated by competitors or reviewers.

This guide provides rigorous methodology for authors to structure the policy and institutional background section of empirical economic manuscripts. Highlighting the journal's reliance on verifiable details (exact file names, dates, implementation rules), it teaches how to connect policy context directly to quasi-experimental identification strategies (like DID and event-study), ensuring the validity of causal claims and preventing common desk-reject issues.

A comprehensive guide for structuring the algorithm section of academic papers. It details the crucial steps for deciding on the solution route—whether to use commercial solvers, exact algorithms, or meta-heuristics. It emphasizes the requirement for rigorous pseudo-code, property analysis, and multi-level baseline comparisons to prove algorithmic novelty and contribution.