Skill UI

Automatically generates robust, schema-compliant mock API servers directly from OpenAPI specifications. This tool supports advanced testing features, including stateful CRUD operations, Faker-driven dynamic data generation, configurable latency simulation, and detailed request recording for contract testing. Ideal for frontend parallel development and isolated integration testing.

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.

PufferLib is a high-performance library designed for advanced reinforcement learning simulations and training. It excels in parallel environment simulation, offering optimized vectorization and native support for multi-agent systems. Utilizing algorithms like PuffeRL (optimized PPO+LSTM), it achieves millions of steps per second, significantly accelerating research and deployment across single-agent and multi-agent environments.

SimPy is a powerful, process-based discrete-event simulation framework written in Python. It is designed for modeling complex systems where entities interact with shared resources and time-based events occur, such as manufacturing lines, service queues, network traffic, or logistics networks. Use this skill to analyze resource contention, simulate process optimization, conduct capacity planning, and model dynamic system behaviors.

Run OpenMM-powered molecular dynamics simulations and MDAnalysis trajectory workflows to build protein or small-molecule systems, minimize energy, equilibrate conditions, and characterize RMSD/RMSF, contacts, and free-energy surfaces for structural biology or drug studies.

This protocol defines communication standards for C-suite AI agents, enabling structured queries and responses between roles like CFO, CTO, and CEO. It includes syntax for invocations, response formats, and strict rules to prevent infinite loops and circular reasoning. Ideal for orchestrating multi-agent teams in enterprise settings, ensuring coordinated cross-functional analysis and safe board meeting simulations without chaos.

Leverages Monte Carlo-based simulation to spot potential software vulnerabilities by feeding randomized inputs into modules, tracking failure likelihoods, and highlighting risky code paths for security testing.

Functions as a Chief Security Architect assistant that performs STRIDE/PASTA threat modeling, OWASP checks, Red/Blue team simulations and incident response playbooks to harden any project before production.

An advanced AI agent designed to simulate Elon Musk with deep psychological and communicative fidelity. It applies first principles thinking, combines scientific reasoning (physics, engineering), and adopts his characteristic tone—including dry humor and candid opinions—for roleplay, strategic brainstorming, and complex problem-solving related to technology, space, and sustainable energy.

An enterprise-grade agent designed to manage the entire lifecycle of skills within an ecosystem. It handles installation, deep validation (including 10 security checks), registration, and post-installation verification. Features include automatic repair, rollback, dry-run simulation, and a comprehensive status dashboard, ensuring maximum redundancy and system integrity.

An advanced role-playing agent simulating Yann LeCun, inventor of Convolutional Neural Networks (CNN) and Chief AI Scientist at Meta. This skill allows users to interact with an expert who maintains LeCun's rigorous, technical, and challenging intellectual tone. Use it to discuss deep learning, ML theory, AI history, or obtain detailed explanations tailored to the user's expertise level (from analogies for laymen to pseudocode for researchers).

A comprehensive guide to using k6 for robust performance and load testing across APIs, WebSockets, and browser scenarios. Learn to write realistic load simulations (smoke, load, stress, soak), analyze performance metrics, set SLAs, and integrate testing into CI/CD pipelines to ensure system reliability before deployment.