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The Azure AI Projects SDK enables developers to build and manage sophisticated, end-to-end AI applications directly on Microsoft Foundry. It provides comprehensive client operations for managing agents, datasets, model deployments, and indexes. Key features include integrating diverse tools (like code interpreters and file search) and handling complex conversational flows, making it ideal for building production-grade AI workflows.

The Azure AI Projects SDK enables developers to build and manage sophisticated, end-to-end AI applications directly on Microsoft Foundry. It provides comprehensive client operations for managing agents, datasets, model deployments, and indexes. Key features include integrating diverse tools (like code interpreters and file search) and handling complex conversational flows, making it ideal for building production-grade AI workflows.

The official Azure Identity SDK for Rust, providing robust authentication mechanisms for Azure SDK clients using Microsoft Entra ID. It supports various credential types—including Developer Tools, Managed Identity, Client Secrets, and Azure CLI—allowing developers to securely authenticate applications across diverse environments, from local development to Azure-hosted production services.

This Python toolset provides production-grade campaign performance analysis including multi-touch attribution modeling, funnel conversion analysis, and ROI calculation. It includes three CLI tools for analyzing ROAS, CPA, and channel effectiveness without external dependencies. Ideal for marketing teams reviewing ad spend and optimizing budget allocation based on deterministic analytics.

Diagnose and fix Claude in Chrome MCP extension connectivity hiccups on macOS by toggling native messaging hosts, inspecting sockets, and running the provided toggle script whenever Claude Code CLI or Claude.app Cowork tools report “Browser extension is not connected” or behave erratically.

Automate Clickmeeting interactions through Composio’s Rube MCP toolkit by always discovering up-to-date tools, checking active connections, and executing RUBE_MULTI_EXECUTE_TOOL with schema-compliant arguments.

Analyze customer accounts for health scores, churn risk, and expansion opportunities using deterministic Python CLI tools with JSON input and text/JSON output.

This skill provides comprehensive observability tools for Groq API integrations. It instruments the client to track critical performance metrics such as Time to First Token (TTFT), total latency, token throughput, and estimated cost. Furthermore, it sets up Prometheus exporters and alert rules to monitor rate limit status and detect performance degradation in real-time, ensuring robust production monitoring.

This module provides production-grade patterns for integrating the Juicebox AI-powered people search API. It includes a singleton client for centralized rate-limit handling, a robust request builder for complex criteria (location, company, experience years), and structured error wrappers for reliable API calls (retries, error context). Ideal for building scalable recruitment, market research, or data enrichment tools.

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.

Used for building, debugging, and extending MCP servers and clients. This skill implements robust connections between AI systems and external tools/data sources using structured protocols like JSON-RPC 2.0. Expertise includes defining tool schemas (Zod/Pydantic), configuring transport layers (HTTP/SSE/stdio), and scaffolding full-stack projects in TypeScript or Python.

This provides a local development loop for integrating the OpenEvidence clinical decision support API. Developers can build health-tech tools and quickly iterate using mock evidence queries, citation responses, and clinical summaries. It supports toggling between mock mode for rapid development and sandbox mode for validation against the real platform, ensuring development uses de-identified data.