Skill UI

A comprehensive guide for academic researchers on how to structure and support claims in AI papers, particularly for top-tier conferences like ECAI. It details how to match the type of claim (e.g., completeness, efficiency, generalization) to the appropriate evidence—whether it requires a formal proof, a controlled empirical comparison, or a real-world deployment demonstration. The guide covers best practices for ML (seeds, ablations, baselines), multi-agent systems, and ensuring full provenance and academic honesty.

This guide helps researchers determine the optimal venue for their database project, analyzing whether the work belongs at EDBT, SIGMOD, VLDB, ICDE, or a dedicated theory venue like ICDT. It provides frameworks for choosing the right conference based on contribution type (systems, theory, experiments), open access preferences, and submission cycle proximity.

This guide provides a framework for designing and auditing the experimental rigor of academic papers, particularly in systems and programming languages. It emphasizes the crucial link between a claim type (e.g., 'Faster') and the required evidence type (e.g., benchmarks, user studies, formal proofs). Learn how to establish robust baselines, define clear workload rules, size experiments for conference cycles, and ensure statistical compliance for maximum impact.

This guide details writing Godot game logic using C#/.NET (targeting Godot 4.7 and .NET 8). It covers core concepts like implementing partial classes, overriding lifecycle methods (_Ready, _Process), handling exported properties, treating signals as type-safe C# events, and performing interop with GDScript. It is ideal for developing complex, performance-critical game systems that require strong typing and object-oriented programming paradigms.

A comprehensive guide to writing idiomatic, statically typed GDScript for Godot 4.7. This skill covers using the node lifecycle, understanding signal systems, and correctly utilizing annotations like @export and @onready. It is essential for developing new Godot projects or porting existing code from Godot 3.x to the modern 4.x architecture.

Design and review Haskell code: advanced type systems, pure domain logic, parsing with Megaparsec/Aeson, STM and async concurrency, Cabal/Stack builds, and measured performance tuning.

Comprehensive guide to LLM Operations (LLMOps). Covers advanced topics like Retrieval-Augmented Generation (RAG), vector database management (Pinecone, Chroma), embeddings, fine-tuning, prompt engineering, and cost optimization. Essential for bridging the gap between AI prototypes and reliable, scalable, production-grade AI systems.

Design efficient PostgreSQL schemas using best practices for data types, indexing, and constraints. Covers normalization, partitioning, and performance optimization for scalable database systems.

Master Rust 1.75+ with advanced async patterns, type system features, and production-ready systems programming. Covers ownership, concurrency, web services, error handling, testing, unsafe code, and modern tooling.

Master enterprise-grade Scala development focusing on functional programming, distributed systems, and big data processing. Expertise includes Apache Pekko, Akka, Spark, ZIO/Cats Effect, and reactive architectures. Covers type-level programming, effect systems, microservices, DDD, performance optimization, and CI/CD deployment.

This skill generates robust JSON-LD structured data markup for various web components, including blogs, FAQs, tools, and SaaS pages. By implementing standard Schema.org types (WebSite, Article, FAQPage, etc.), you can significantly improve your SEO, boost click-through rates (CTR), and provide clear context to both search engines and AI systems. Includes implementation guidance for modern frameworks like Next.js.

This skill specializes in scaffolding production-ready Rust applications. It generates complete project structures using Cargo tooling, ensuring proper module organization, testing setup, and configuration following Rust best practices. It supports binary, library, workspace, and web API project types with idiomatic code patterns.