Skill UI

This SDK provides comprehensive tools for developing enterprise-grade, multi-channel agents for the Microsoft 365 ecosystem. Utilizing ASP.NET Core hosting, it supports integration with Teams, Copilot Studio, and general M365 services. Key features include robust agent application routing, structured state management, and secure authentication using MSAL.

Develop robust, multi-channel enterprise agents designed for the Microsoft 365 ecosystem, including Teams and Copilot Studio. This SDK provides a comprehensive Python framework featuring aiohttp hosting, advanced AgentApplication routing, real-time streaming responses, and secure authentication via MSAL. Ideal for building sophisticated, production-grade bots and automation tools that integrate deeply with enterprise Microsoft services.

This comprehensive SDK provides tools for building enterprise-grade AI agents integrated across the Microsoft 365 ecosystem, including Teams and Copilot Studio. It supports advanced features such as Express hosting, structured routing, streaming responses via Azure OpenAI, and direct client integration, enabling developers to build sophisticated business automation solutions.

This skill guides the design and implementation of a complete, production-grade Machine Learning pipeline. It employs a multi-agent orchestration workflow, systematically covering all stages of the ML lifecycle: data ingestion and quality assurance, feature engineering, model training, optimization, and robust deployment (MLOps). It ensures built-in reproducibility, monitoring, and scalability.

This guide provides comprehensive, step-by-step instructions for installing and configuring the Manifest observability plugin for your AI agent. Users can use this skill to set up telemetry, connect the agent to Manifest for real-time monitoring, manage API keys, and troubleshoot various connection issues, ensuring full system observability.

This skill provides methodologies for designing sophisticated, layered memory architectures for AI agents. It moves beyond simple context windows and basic vector stores by incorporating short-term, long-term, and graph-based memory systems. Implementing this is crucial for agents that require persistence across sessions, maintaining complex entity consistency, and performing advanced, relationship-driven reasoning over accumulated knowledge bases, including time-aware fact tracking.

A comprehensive guide to implementing advanced asynchronous patterns with Mistral AI. This skill covers using the Agents API for stateful, multi-turn workflows, the Batch API for cost-effective bulk inference, and event-driven streaming architectures. It is essential for building robust, long-running, or high-volume AI applications that require reliable background job handling.

Automates Mopinion tasks through the Composio toolkit by discovering Rube MCP tools, verifying connections, and executing schema-compliant workflows, so agents can orchestrate Mopinion operations reliably.

Simulates a highly structured, sequential peer-review process using multiple specialized AI agents (e.g., Skeptic, Constraint Guardian, User Advocate). This skill is designed to rigorously stress-test a design, surface hidden assumptions, identify potential failure modes, and enforce non-functional constraints before implementation. It transforms initial concepts into robust, validated specifications by simulating formal critique and achieving consensus via a mandatory Decision Log.

This guide details advanced architectural patterns for building complex AI systems using multiple Language Model instances (agents). It addresses the single-agent context bottleneck by distributing work, enabling parallelism, and facilitating specialization across different subtasks. Key patterns include Supervisor/Orchestrator, Peer-to-Peer/Swarm, and Hierarchical designs, providing guidelines for context isolation and effective coordination protocols.

Catalogs proven n8n workflow architectural patterns for webhook handling, APIs, database syncing, AI agents, and scheduled tasks, helping teams pick structures, plan nodes, and handle triggers, data paths, and error strategies during workflow design and troubleshooting.

Monitors Nx Cloud CI pipelines by running the ci-watcher subagent, polling execution status, and applying self-healing fixes or rerun requests while honoring user overrides and Nx Cloud connection requirements.