Skill UI

A comprehensive guide for structuring and positioning computer science manuscripts for The Web Conference (WWW). It advises authors on leveraging open-web data, focusing on web systems, web mining, and responsible AI, while adhering to the latest venue-specific standards and evidence requirements.

A comprehensive audit checklist for designing and evaluating security experiments, adhering to the highest academic standards (e.g., USENIX Security). It guides users through verifying adaptive attacker models, calculating precision at realistic base rates, ensuring statistical honesty for stochastic results, and maintaining ethical compliance when working with live systems.

This comprehensive guide outlines best practices for packaging research artifacts, including code, proprietary data logs, and models, for submission to top-tier academic venues. It addresses the crucial need for verifiability and reproducibility, providing strategies for handling limited space, proprietary datasets, and the absence of formal artifact grading systems, ensuring high academic credibility.

Stress-test core claims for Journal of Systems Engineering submissions: parameter sensitivity, initial conditions, alternative models and metrics, extreme scenarios, Monte Carlo repetitions, random seeds, software environments, data/code statements, and explicit failure boundaries.

This skill guides the construction of robust, production-grade backtesting systems for financial trading strategies. It helps users systematically validate performance, avoid common biases (like look-ahead bias), and implement advanced techniques such as walk-forward analysis, ensuring reliable performance estimates before live deployment.

Guides agents through bounded parameter optimization for configurable systems with measurable objectives: define search space, budget, and baseline, run trials one at a time, log evidence, and recommend a configuration for HPO, inference tuning, simulations, or RL/control experiments.