Skill UI

Master comprehensive strategies for evaluating Large Language Model (LLM) applications. This skill covers automated metrics (BLEU, ROUGE, BERTScore), structured human evaluation dimensions, and advanced LLM-as-Judge techniques. Use it to systematically measure model performance, compare prompts, detect regressions, and build confidence in production systems.

This skill acts as an expert risk manager, providing comprehensive guidance on monitoring portfolio risk, calculating R-multiples, and optimizing position limits. It covers advanced quantitative finance topics such as Value at Risk (VaR), correlation analysis, and stress testing using Monte Carlo simulations. Use it for systematic risk assessment, developing hedging strategies (options/futures), and implementing rigorous risk controls in trading workflows.

Master systematic methodologies for using Shodan to perform deep reconnaissance during penetration testing. This skill covers querying exposed services, mapping assets, identifying vulnerable systems (CVEs), and utilizing advanced filters for IP ranges, geographical locations, and organizational data. Ideal for security researchers and ethical hackers.

Execute systematic SQL injection vulnerability assessments on web applications using reconnaissance, payload tuning, and exploitation workflows to uncover database flaws, capture evidence, and validate remediation recommendations for authorized security testing.

This skill guides developers through advanced, safe, and systematic code refactoring using Test-Driven Development (TDD) principles. It provides a comprehensive workflow encompassing pre-assessment, detecting code smells, applying major design patterns (SOLID, Factory, Strategy), optimizing performance, and ensuring safety through rigorous, incremental testing. Use this when improving code structure, restructuring large components, or updating legacy systems while guaranteeing functional integrity and maintainability.

An expert specialist for rigorous visual validation, focusing on UI testing, design system compliance, and WCAG accessibility verification. This skill systematically analyzes visual evidence for cross-platform consistency, pixel-perfect accuracy, and adherence to modern design standards, utilizing principles from visual regression testing and comprehensive QA methodologies.

This comprehensive workflow guides users through a multi-phase process for assessing web application security. It is designed to systematically test for common vulnerabilities listed in the OWASP Top 10, including SQL injection, XSS, broken authentication, and access control issues. Ideal for professional penetration testing, security auditing, and bug bounty hunting.

Guides intercepting HTTP traffic, modifying requests, using Repeater, defining scope, and running Burp Suite scans for systematic web application security testing.

Guides systematic detection and exploitation of cross-site scripting and HTML injection flaws, covering stored/reflected/DOM vectors, payload crafting, and remediation advice for web security assessments.

This skill guides users through a comprehensive, multi-stage process for creating high-quality documentation. It systematically moves through Context Gathering (understanding the background and audience), Refinement & Structure (iteratively building and editing sections), and Reader Testing (simulating external review to catch blind spots). Ideal for drafting complex specifications, proposals, or design documents that need to be robust and clear for a wide audience.

This skill provides a comprehensive framework for performing end-to-end UI testing and verification on Android emulators. It guides users through systematic processes including device calibration, UI element discovery using uiautomator, performing complex interactions (tap, swipe, input), and robust reporting via visual screenshots and logcat analysis. Ideal for ensuring the stability and functional correctness of React Native or native Android applications.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.