Skill UI

This comprehensive pre-upload audit guide ensures submissions meet the strict technical and anonymity requirements for UAI OpenReview. It covers critical aspects like the 8-page main body constraint, combining all content into a single PDF, handling file size caps (15MB/50MB), and performing an identity sweep to maintain double-blind review standards.

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 to SIGMETRICS, detailing how to structure the Related Work section. It emphasizes shifting from a simple citation catalog to a 'delta-first' contrast, highlighting the specific technical novelty (e.g., tighter bounds, weaker assumptions) relative to existing literature across multiple performance evaluation lanes (systems, measurement, learning, etc.).

Generates high-quality, structured technical documentation for READMEs, APIs, and architecture guides, adhering to progressive disclosure principles. It also specializes in creating formal, evidence-backed security reports for penetration testing, CTF writeups, and reverse engineering tasks, ensuring a professional, reusable format.

This tool performs a comprehensive analysis of AI configuration file evolution within a Git repository. It tracks when specific AI configs were first introduced, charts monthly commit velocity related to AI features, highlights key PRs that shaped the development, and synthesizes the project's AI maturity phases. Ideal for mapping AI adoption timelines and assessing technical maturity.

This tool tests your deep understanding of code you have recently written or reviewed. It generates structured, multi-level questions (Recall, Understanding, Application, Analysis, Synthesis) based on the provided code. Users can focus the quiz on specific areas like error handling, performance, or security, making it an excellent mechanism for continuous learning and solidifying technical knowledge.

This gate review forces a transition from vague product direction to a concrete, buildable technical specification. It mandates the creation of architectural diagrams, data flow maps, state machines, and failure mode inventories before a single line of implementation code is written. Essential for complex features with async components or external dependencies.

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.