github/awesome-copilot · Official

semantic-kernel

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

All-time #6928 First seen Mar 16, 2026
8-week activity · all time api

Installation

$ npx skills add github/awesome-copilot --skill semantic-kernel

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 38.8K
License LICENSE
Default branch main
Open issues 21
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents github-copilot

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,024 B
  • docs SUMMARY.md 170 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1,723 installs

SKILL.md

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](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](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

  • [.NET reference](references/dotnet.md)
  • [Python reference](references/python.md)

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.