Skill UI

This skill provides comprehensive principles for developing multiplayer games, covering essential topics from networking architecture (Dedicated, P2P, Host-based) to advanced synchronization techniques. It details how to handle latency via prediction, interpolation, and lag compensation, optimize bandwidth using delta compression, and implement robust security measures like server authority and anti-cheat systems. Ideal for developers building real-time online experiences.

Cloud-native Rowan orchestrates medicinal chemistry and molecular modeling pipelines via a Python API, offering pKa prediction, docking, descriptors, dynamics, and AI-driven structure workflows for scalable batch screening without local HPC.

This skill automates the process of vulnerability prioritization by querying the FIRST Exploit Prediction Scoring System (EPSS) API. It calculates the real-world probability of a CVE being exploited within 30 days, providing a crucial risk metric that surpasses traditional CVSS severity scoring. Use it for risk-based vulnerability management, allowing security teams to efficiently triage and remediate the most actively threatened vulnerabilities first.

This skill teaches users to apply the scientific method to software debugging. Instead of random changes, it guides the process through five steps: Observation, Hypothesizing, Prediction, Testing, and Analysis. By systematically forming and testing specific, measurable hypotheses, users can efficiently isolate failing components and confirm the true root cause of technical issues.

This skill generates a structured, non-advisory worksheet for planning trade ideas, basket adjustments, or comparing prediction markets. It helps users methodically review venues, underliers, constraints, and manual execution steps without placing any trades or providing financial advice. Ideal for the research phase of quantitative finance workflows.

This skill reviews prediction market, basket, oracle, and trading-agent workflows to ensure compliance, safety, data quality, and privacy. It must be run before any workflow handles user portfolio data, venue authentication, API keys, or trade planning to mitigate execution and regulatory risks across multiple domains.

This guide teaches advanced methods for developing robust theoretical arguments in Human Resource Management (HRM) manuscripts. It focuses on moving beyond simple correlation by articulating precise causal mechanisms—such as AMO, signaling, and social exchange—to build testable predictions a priori. It is essential for avoiding common academic pitfalls like HARKing and construct conflation.

This guide provides a rigorous framework for developing robust, theory-driven hypotheses in accounting research, especially for high-impact academic journals. It teaches researchers how to transition from observing mere correlations to formulating hypotheses grounded in established economic theories, such as agency theory, information economics, and positive accounting theory. The process emphasizes identifying the core economic friction, naming the acting agents and their incentives, and deriving directional, falsifiable, and a priori predictions.

A rigorous framework designed for academics to vet research questions for high-impact journals. It guides researchers to ensure that the international dimension is the theoretical core, providing 'stress tests' and criteria to prove that cross-national variation generates unique predictions, elevating the work beyond mere cross-country replication.

This guide provides a structured framework for developing robust conceptual arguments in marketing manuscripts. It teaches users how to ground theory in real-world phenomena, specify causal mechanisms, and derive measurable predictions. It addresses both theory-first and empirics-first research routes, helping authors build the minimum sufficient conceptual structure required for high-impact academic publishing.

This guide helps researchers move beyond decorative theory to construct 'load-bearing' conceptual or analytical frameworks for World Development (WD) manuscripts. It outlines how to transform vague ideas into structured, testable mechanisms by stating clear mechanisms, deriving discriminating predictions, mapping predictions to evidence, and defining scope conditions, ensuring the theory actively drives the empirical argument.