Skill UI

A systematic workflow designed to significantly improve the reliability and performance of existing AI agents. It covers detailed performance analysis, including gathering metrics (e.g., task success rate, latency), classifying failure modes, and advanced prompt engineering techniques (like Chain-of-Thought and Constitutional AI). The process culminates in structured A/B testing and controlled deployment, ensuring measurable, robust improvements.

A specialist in modern Angular development (v17+), focusing on standalone components, Signals, and enterprise-grade architecture. This skill covers designing complex application flows, implementing robust state management using NgRx, managing reactive patterns with RxJS, optimizing bundle performance, and ensuring high code quality through rigorous testing and adherence to best practices.

Automates guidance for Apdex scoring within performance testing, covering setup, best practices, code/config generation, and validation.

Automates guidance for Apdex scoring within performance testing, covering setup, best practices, code/config generation, and validation.

Auto-activating skill that guides teams through creating validated Artillery load-testing configurations, offering best-practice patterns, sample scripts, and configuration validation for performance, load, and benchmarking use cases.

Auto-activating skill that guides teams through creating validated Artillery load-testing configurations, offering best-practice patterns, sample scripts, and configuration validation for performance, load, and benchmarking use cases.

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.

This comprehensive framework allows users to validate and test both crypto and traditional trading strategies against extensive historical market data. It calculates essential performance metrics (Sharpe Ratio, Sortino Ratio, Max Drawdown), simulates trade execution, generates equity curves, and includes advanced parameter grid search optimization tools for robust strategy validation.

Guides automated bottleneck identification within performance testing, offering step-by-step advice, auto-generated configurations, validation against standards, and coverage of load, stress, benchmarking, and monitoring workflows.

Automates connection pool analyzer tasks for performance testing, offering best-practice guidance, code/config generation, and validation during load, stress, and benchmarking activities.

Automates cpu profiler configuration guidance for performance testing, covering load, stress, benchmarking, and monitoring scenarios to ensure best practices.

This guide provides comprehensive strategies for scaling Customer.io integrations to handle high volumes of daily events. It covers implementing k6 load tests for performance benchmarking and outlines architectural patterns—from simple Direct APIs to complex Redis/Kafka queue-backed systems—ensuring reliability and managing API rate limits for massive data throughput.