Skill UI

A specialized reverse-engineering skill designed to extract comprehensive functional and non-functional specifications from existing, undocumented, or legacy codebases. It operates by analyzing code structure, tracing data flows, and identifying observable behaviors. The output is structured using EARS (Easy Approach to Requirements Syntax), providing clearer requirements documentation, architectural diagrams, and dependency maps for onboarding or system modernization.

A comprehensive, multi-phase quality engineering audit tool designed to test codebases beyond standard unit tests. It first explores the codebase's domain and architecture to derive behavioral requirements, then executes a rigorous sequence including spec-traced functional tests, three-pass code reviews, and a multi-model specification audit (Council of Three). It is specifically engineered to find the critical 35% of real-world defects that structural code review alone might miss. Works with any programming language.

This skill guides the user to act as an expert author of comprehensive, implementation-ready design system guidelines for a cyber-slick, dark, Matrix-inspired interface. It covers foundational constraints, color tokens, typography scales, component anatomy, accessibility requirements (WCAG 2.2 AA), and content standards, ensuring technical rigor and visual consistency for engineering and design teams.

Alex converts high-level requirements into a precise, dependency-aware, and actionable implementation checklist. It maps critical paths, breaks down features into atomic micro-tasks, and establishes clear Definitions of Done (DoD) across various layers. Ideal for bridging the gap between conceptual goals and step-by-step engineering execution.

A comprehensive template designed to structure complex technical specifications, ensuring a complete record of engineering decisions. It guides users to document problem statements, proposed solutions, system architecture, data models, API designs, security considerations, and rollout plans, bridging product requirements and technical implementation.

This skill serves as a comprehensive guide for authors targeting the ACM/IEEE MODELS conference. It provides deep, strategic insights into model-driven engineering, modeling languages, transformations, and DSLs. Use it to re-frame manuscripts, check evidence requirements, and optimize the submission strategy for this top-tier computer science venue.

A comprehensive guide for authors targeting the ACM International Conference on the Foundations of Software Engineering (FSE). It helps assess manuscript fit, refine the scientific narrative, strengthen empirical evidence, and understand venue-specific requirements for SE foundations, tools, and AI applications. Use this to strategically position your research for top-tier SE conferences.

A comprehensive guide for researchers submitting to ASE (Automated Software Engineering). It details mandatory requirements for ensuring research reproducibility, covering the Data Availability Statement, providing anonymized and runnable tools, pinning system provenance (commits, versions, SHAs), and managing cached LLM outputs. Essential for passing rigorous peer review.

A comprehensive guide for authors targeting the IEEE International Requirements Engineering Conference (RE). This skill helps assess if a computer science manuscript is a strong fit for the venue, focusing on requirements elicitation, modeling, traceability, and stakeholder-centered validation. It provides guidance on re-framing submissions and structuring evidence for academic conference acceptance.

A comprehensive guide and tool for assessing manuscript fit for the Chinese academic journal, *Management Science* (published by HIT). It helps researchers determine if their work meets the journal's requirements, especially regarding quantitative methods, model setting, structured argument, and adherence to specific word count and formatting rules. It assists in optimizing the narrative for high-level management and engineering science publications.