Skill UI

A comprehensive guide for authors revising high-stakes academic papers, such as those for SOSP. It teaches how to shift focus from merely listing features to articulating core design principles, building a compelling 'Problem-to-Insight' arc, and structuring evidence-based arguments within strict length constraints. Essential for academic researchers and technical writers.

This guide details best practices for structuring supplementary material in highly technical academic submissions (e.g., STOC). It teaches authors how to design an appendix that facilitates selective verification by reviewers, ensuring that complex proofs, deferred results, and extended discussions are navigable. Key techniques include optimizing the Table of Contents, maintaining strict pointer discipline, and distinguishing between material required for core understanding versus material saved for the full version.

Provides comprehensive guidelines for designing rigorous technical evaluations for interactive systems, specifically tailored for top-tier venues like UIST. It emphasizes matching evaluation methods to specific artifact claims, reporting distributions over means, closing the interaction loop, and performing thorough ablations against real-world baselines. This framework ensures the scientific rigor and credibility of submitted research.

A comprehensive guide for authors submitting interactive system papers to UIST. It details the required narrative arc (walkthrough before mechanism), emphasizes technical specificity in implementation details, and provides rules for designing figures and structuring the argument within strict page limits.

A comprehensive guide for designing and presenting highly rigorous technical evaluations for database or system papers. It covers establishing baseline necessity, proving mechanism causality through ablation, testing scalability across data sizes, and mandating the disclosure of loss cases to satisfy skeptical academic reviewers.

This core skill is designed for academic publishing, combining deep AI research with structured, professional writing. It guides the creation of manuscripts using IMRAD structure and handles complex citation styles (APA, AMA, etc.). Crucially, it mandates the generation of graphical abstracts and rich technical schematics to ensure the highest level of visual rigor for research papers.

A comprehensive tool designed to help developers compare multiple technical approaches for solving a single problem. It systematically identifies and analyzes the trade-offs, complexity, performance, and learning curves associated with different design patterns (e.g., state management, data fetching, API design). Ideal for architectural reviews and making informed, robust technology stack decisions.

This robust pipeline guides development teams through a rigorous, five-phase planning process *before* writing any code. It systematically analyzes PRDs, design specifications (UX, accessibility), and existing architecture to produce a comprehensive implementation plan. Key outputs include Architecture Decision Records (ADRs), detailed task breakdowns, and verification strategies, ensuring all technical and design decisions are documented and scoped.

A systematic methodology for resolving deeply conflicting technical requirements (e.g., needing a system to be both fast and consistent). Instead of accepting a midpoint compromise or trade-off, TRIZ instructs users to name the conflict, separate the opposing states (using time, space, condition, or scale), and invent a concrete, no-compromise resolution. Ideal for architecture, API design, and complex system parameter definition.