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Semantic Kernel

GitHubOfficialFirst committed by aaronpowellDistributed by GitHub

  • Skill
  • Tool integration
  • Software development
  • MIT
  • No issues found
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From the author

Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.
— the description by aaronpowell

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Semantic Kernel skill provides structured guidance for building AI-integrated applications. It helps developers navigate the framework's architecture, ensuring that implementations follow current best practices for both .NET and Python ecosystems. By prioritizing official documentation and language-specific patterns, the skill assists in creating robust plugins, function-calling flows, and service integrations.

What it does

  • Provides language-specific guidance for .NET and Python Semantic Kernel projects.
  • Ensures implementation advice is grounded in official framework documentation.
  • Supports the creation, refactoring, and review of AI plugins and function-calling logic.
  • Promotes consistent use of async patterns and strong typing across kernel operations.
  • Advises on standard service registration and authentication patterns.
  • Helps align custom code with current repository samples and API surfaces.

When to use it

  • When building or maintaining applications using the Semantic Kernel SDK.
  • When you need to refactor existing AI orchestration logic for better performance or maintainability.
  • When you are unsure about the current best practices for plugin development in .NET or Python.
  • When integrating AI services like Azure OpenAI or Azure AI Foundry into a project.
  • When debugging issues related to kernel configuration or function execution.

Advantages

  • Reduces technical debt by enforcing current, supported framework patterns.
  • Ensures code consistency across different language implementations.
  • Prevents reliance on outdated API usage by prioritizing official documentation.
  • Facilitates the adoption of standard authentication and service registration practices.

Usage examples

“How do I register a custom plugin in my .NET Semantic Kernel project?”
The agent will provide the correct .NET-specific syntax for plugin registration, referencing current async patterns and service configuration standards.
“Refactor this Python code to use the latest Semantic Kernel function-calling patterns.”
The agent will analyze the provided Python code and suggest updates based on the current Python SDK samples and best practices.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/github/semantic-kernel/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip semantic-kernel.zip -d .agents/skills

Documentation by aaronpowell

Semantic Kernel

Use this skill when working with applications, plugins, function-calling flows, or AI integrations built on Semantic Kernel.

Always ground implementation advice in the latest Semantic Kernel documentation and samples rather than memory alone.

Determine the target language first

Choose the language workflow before making recommendations or code changes:

  1. Use the .NET workflow when the repository contains .cs, .csproj, .sln, or other .NET project files, or when the user explicitly asks for C# or .NET guidance. Follow references/dotnet.md.

  2. Use the Python workflow when the repository contains .py, pyproject.toml, requirements.txt, or the user explicitly asks for Python guidance. Follow references/python.md.

  3. If the repository contains both ecosystems, match the language used by the files being edited or the user's stated target.

  4. If the language is ambiguous, inspect the current workspace first and then choose the closest language-specific reference.

Always consult live documentation

Shared guidance

When working with Semantic Kernel in any language:

  • Use async patterns for kernel operations.

  • Follow official plugin and function-calling patterns.

  • Implement explicit error handling and logging.

  • Prefer strong typing, clear abstractions, and maintainable composition patterns.

  • Use built-in connectors for Azure AI Foundry, Azure OpenAI, OpenAI, and other AI services, while preferring Azure AI Foundry services for new projects when that fits the task.

  • Use the kernel's memory and context-management capabilities when they simplify the solution.

  • Use DefaultAzureCredential when Azure authentication is appropriate.

Workflow

  1. Determine the target language and read the matching reference file.

  2. Fetch the latest official docs and samples before making implementation choices.

  3. Apply the shared Semantic Kernel guidance from this skill.

  4. Use the language-specific package, repository, sample paths, and coding practices from the chosen reference.

  5. When examples in the repo differ from current docs, explain the difference and follow the current supported pattern.

References

Completion criteria

  • Recommendations match the target language.

  • Package names, repository paths, and sample locations match the selected ecosystem.

  • Guidance reflects current Semantic Kernel documentation rather than stale assumptions.

Files

Requirements and compatibility

Written for: GitHub Copilot

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

First committed by
GitHub avatar of aaronpowellaaronpowell
Publisher
GitHub (Official)
Distributed by
GitHub
Source
github/awesome-copilot · skills/semantic-kernel · commit 797337f
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
Contributors
aaronpowell

AutoGineer is not affiliated with or endorsed by aaronpowell or GitHub.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download semantic-kernel.zip