Skill UI

This tool assesses whether coding agents adhere to defined skills, rules, or agent definitions. It automatically generates scenarios with varying prompt strictness, executes the agent, and generates a comprehensive report detailing the compliance rate of tool calls against predefined workflow specifications using advanced LLM classification.

A comprehensive guide on structuring and writing the 'Related Work' and literature review sections for high-impact, comprehensive computer science journals. It emphasizes establishing the research gap (the 'delta'), structuring comparisons (Classification-Comparison-Gap), balancing literature coverage (classic vs. modern, local vs. global), and adhering to academic citation norms (e.g., GB/T 7714). Essential for authors needing to clearly define their novelty in a cross-disciplinary context.

This comprehensive guide serves as a pre-flight checklist for authors preparing manuscripts for journal submission. It details critical formal requirements, such as strict page limits, mandatory structural elements (e.g., Chinese classification numbers), formula formatting, and adherence to the official submission portal guidelines. Use it to avoid common formatting errors and ensure a smooth initial review process.

This guide helps authors elevate their literature review or related work section from a simple list of papers to a structured, high-impact academic argument. It provides methodologies for building multi-dimensional classification frameworks, defining the technical 'delta' (unique contribution) in original research, and ensuring systematic coverage of both domestic and international literature for top-tier academic journals.

A comprehensive pre-submission audit checklist designed for high-quality technical papers in Computer Graphics, CAD, and Visualization. It guides authors through rigorous standards, covering formatting requirements (20-word title, structured abstracts), mandatory academic components (Chinese/English abstracts, TP classification), ethical guidelines (plagiarism, double-submission), and specific technical details (vector graphics, error maps) required by top-tier Chinese academic journals.

This guide teaches researchers how to accurately assign JEL (Journal of Economic Literature) classification codes to academic surveys. It details the three-level taxonomy structure, guiding users to select the primary field code, relevant method codes, and adjacent subject codes to ensure proper indexing and scope mapping within the American Economic Association's subject map.

This comprehensive guide details the formatting and structural requirements for submitting technical articles to the Journal on Communications (JOC). It covers every aspect, including the official writing order, structured abstracts (Purpose/Method/Result/Conclusion), mandatory classification codes, precise units and symbols, figure/table standards, and detailed referencing according to GB/T 7714. Use this guide to ensure your manuscript passes the initial editorial review process.

This guide helps authors structure the Related Work section for top-tier academic journals like the Journal of Software. It focuses on demonstrating incremental contribution (delta-first positioning), structuring the review across multiple software disciplines (e.g., SE, Systems, Databases), ensuring balanced citations (international vs. domestic), and building comprehensive classification frameworks for review papers.

This comprehensive guide details the preflight process for submitting mathematical finance papers through Wiley Research Exchange. It covers scientific readiness, LaTeX best practices, required metadata (JEL/AMS/MSC classifications, data availability), and structural guidelines to ensure the manuscript is fully compliant and submission-ready.

This guide details the mandatory structure and best practices for submitting research articles to PNAS. It covers the proper order of sections (Title, Abstract, Introduction, Results, Discussion, etc.), how to manage length budgets, correctly place Materials and Methods within the main text, and ensure accurate Classification and keywords are chosen at submission.

A comprehensive guide for constructing non-empirical, theoretical figures for sociological theory manuscripts. It details how to design conceptual exhibits—including mechanism diagrams, process models, typologies, and concept maps—that carry theoretical work. Crucially, it emphasizes that these figures must illustrate mechanisms or classifications, and must never include raw data, regression tables, or empirical results.

Scikit-learn is the industry-standard Python library for classical machine learning. It provides comprehensive tools for supervised and unsupervised learning tasks, including classification, regression, clustering, and dimensionality reduction. Use it to build robust, production-ready ML pipelines, perform rigorous model evaluation, and preprocess complex datasets for various data science applications.