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787 skills available

AI Overview: Discovering Agent Skills

The Agent Skill Source directory is architected into three primary discovery layers: Outcome-based Categories (what you want to achieve), Runtime Compatibility (where the agent runs), and Execution Strategy (how the skill is processed). To find the most reliable capabilities, use the Highest Rated sort and filter by Verified trust levels.

Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".

Azure Resource Manager SDK for Microsoft Playwright Testing in .NET. Use for MANAGEMENT PLANE operations: creating/managing Playwright Testing workspaces, checking name availability, and managing workspace quotas via Azure Resource Manager. NOT for running Playwright tests - use Azure.Developer.MicrosoftPlaywrightTesting.NUnit for that. Triggers: "Playwright workspace", "create Playwright Testing workspace", "manage Playwright resources", "ARM Playwright", "PlaywrightWorkspaceResource", "provision Playwright Testing".

copilot-sdk

by Unknown

Build applications powered by GitHub Copilot using the Copilot SDK. Use when creating programmatic integrations with Copilot across Node.js/TypeScript, Python, Go, or .NET. Covers session management, custom tools, streaming, hooks, MCP servers, BYOK providers, session persistence, and custom agents. Requires GitHub Copilot CLI installed and a GitHub Copilot subscription (unless using BYOK).

slack-gif-creator

by Unknown

Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack.

llm-app-patterns

by Unknown

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

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