Skill UI

Checks website, GitHub, and local docs to identify messaging inconsistencies and captures version, feature, terminology, and contact differences in a read-only discrepancy report whenever a consistency check is requested.

Designs and implements immersive web experiences using Three.js, React Three Fiber, Spline, and WebGL, covering product configurators, portfolios, scroll-driven scenes, and performance-aware 3D delivery.

Automates creation of A/B test configurations for ML deployment, guiding users through best practices, code samples, and validation steps so production models are served with monitoring and rollout control.

Automates creation of acceptance criteria within enterprise workflows, guiding through best practices, generating code and configurations, and validating outputs against standards whenever acceptance criteria creator requests arrive.

A comprehensive guide detailing advanced techniques for attacking Microsoft Active Directory (AD) environments. It covers the entire red team lifecycle, including reconnaissance (BloodHound, PowerView), credential harvesting (Mimikatz, AS-REP Roasting), and critical attacks such as Kerberos exploitation, Pass-the-Ticket/Hash, and NTLM relay attacks. Essential for penetration testing and defensive validation.

Automates adapting pretrained models via transfer learning by analyzing requirements, generating PyTorch or TensorFlow fine-tuning code, validating data, tracking KPIs, and saving artifacts so you can quickly reuse existing models for new datasets and tasks.

Automates architecture decision record (ADR) generation and guidance within technical documentation workflows, offering best-practice patterns, production-ready snippets, and validation for API docs, user guides, and automation needs.

Automatically detects and loads specialized agent instructions from the `AGENTS.md` file in the current working directory. This skill seamlessly integrates project-specific rules and behavioral guidelines into the AI's session context, ensuring the AI operates according to project standards without manual intervention. It is crucial for maintaining specialized agent behaviors across different development tasks and directory changes.

A comprehensive framework for rigorously testing and benchmarking LLM agents. It moves beyond simple pass/fail checks to assess complex behaviors, reliability metrics, and capability consistency across multiple runs. Ideal for production monitoring and identifying subtle failure modes in advanced AI agents.

This SDK allows developers to build persistent, sophisticated AI agents directly on Azure AI Foundry. It supports complex conversational workflows by integrating external functions (tools), enabling code execution, web search, and maintaining conversation history through dedicated thread management. Ideal for developing enterprise-grade, production-ready AI applications.

This skill provides comprehensive management for multiple local Command Line Interface (CLI) agents. It allows users to start, stop, monitor, and assign tasks to these agents, running them in separate tmux sessions for parallel execution. It is ideal for complex, scheduled workflows requiring multi-agent coordination, task monitoring, and log tailing, making it invaluable for advanced automation setups.

A sophisticated hybrid memory system designed specifically for AI agents. It provides a persistent, searchable knowledge bank to store, retrieve, and manage long-term knowledge, including architectural designs, operational patterns, and critical decision points. By syncing with project documentation, it ensures that crucial institutional knowledge remains accessible throughout the development lifecycle, enhancing agent reliability and consistency.