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semantic-kernel

Develop AI applications with Microsoft's Semantic Kernel framework.

6|2|Updated Jan 22, 2026
Search Tags:#python#llm#memory#plugins#ai orchestration#.net#semantic kernel
One-click install
npx skills add https://github.com/fgarofalo56/Suppercharge_Microsoft_Fabric --skill semantic-kernel
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: semantic-kernel
Source: https://github.com/fgarofalo56/Suppercharge_Microsoft_Fabric/tree/main/.github/skills/semantic-kernel
Command: npx skills add https://github.com/fgarofalo56/Suppercharge_Microsoft_Fabric --skill semantic-kernel

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides expert guidance for building AI applications by orchestrating complex AI workflows, enabling seamless integration of language models, memory, and custom logic.

Core Features & Use Cases

  • AI Orchestration: Build sophisticated AI applications using Microsoft's Semantic Kernel framework.
  • Plugin Development: Create and manage native and prompt-based plugins for modular AI functionality.
  • Memory Systems: Implement semantic and vector memory for context-aware AI interactions.
  • Planners: Utilize stepwise and Handlebars planners for dynamic AI task execution.
  • Use Case: Develop a customer support chatbot that can access a knowledge base, understand user queries, and generate helpful responses by orchestrating multiple AI models and functions.

Quick Start

Use the semantic_kernel skill to summarize the provided text.

Frequently Asked Questions about semantic-kernel

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate complex AI workflows with Semantic Kernel?▼

You orchestrate complex AI workflows with Semantic Kernel by integrating language models, memory systems, and custom logic. This framework supports plugin creation and planner integration to execute dynamic AI tasks seamlessly.

What is the best way to build context-aware AI interactions using memory systems?▼

The best way to build context-aware AI interactions is by implementing semantic and vector memory systems. Semantic Kernel enables memory management to retain and apply context across multiple AI models and functions.

Can I use Semantic Kernel plugins with OpenAI and Azure AI services?▼

Yes, you can use Semantic Kernel plugins with OpenAI and Azure AI services. The framework integrates directly with these platforms for natural language processing, enabling modular AI functionality through native and prompt-based plugins.

How do stepwise and Handlebars planners execute dynamic AI tasks?▼

Stepwise and Handlebars planners execute dynamic AI tasks by mapping out logical sequences for the AI to follow. Semantic Kernel utilizes these planners to break down complex requests into actionable, automated steps.

Does Semantic Kernel support both Python and .NET for AI application development?▼

Yes, Semantic Kernel supports both Python and .NET for AI application development. You can leverage either environment to build sophisticated AI applications, manage memory, and orchestrate workflows.

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