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github/awesome-copilot/skills/semantic-kernel/SKILL.md

semantic-kernel

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

Source repository stars
37,126
Declared platforms
0
Static risk flags
1
Last source update
2026-07-28
Source checked
2026-07-28
DecisionCompatibilityInstallWorkflowPermissionsEvidenceSource

Decision brief

What it does—and where it fits

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

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/github/awesome-copilot --skill "skills/semantic-kernel"
    Safe inspection promptEditorial

    Inspect the Agent Skill "semantic-kernel" from https://github.com/github/awesome-copilot/blob/9933dcad5be5caeb288cebcd370eeeb2fc2f1685/skills/semantic-kernel/SKILL.md at commit 9933dcad5be5caeb288cebcd370eeeb2fc2f1685. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      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…

      Determine the target language and read the matching reference file.Fetch the latest official docs and samples before making implementation choices.Apply the shared Semantic Kernel guidance from this skill.
    2. 02

      Determine the target language first

      Choose the language workflow before making recommendations or code changes:

      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.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.If the repository contains both ecosystems, match the language used by the files being edited or the user's stated target.
    3. 03

      Always consult live documentation

      Read the Semantic Kernel overview first:

      Read the Semantic Kernel overview first:Prefer official docs and samples for the current API surface.Use the Microsoft Docs MCP tooling when available to fetch up-to-date framework guidance and examples.
    4. 04

      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.

    Permission review

    Static risk signals and limitations

    Reads files

    low · line 36

    The documentation asks the agent to read local files, directories, or repositories.

    Determine the target language and read the matching reference file.

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score64/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars37,126SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    github/awesome-copilot
    Skill path
    skills/semantic-kernel/SKILL.md
    Commit
    9933dcad5be5caeb288cebcd370eeeb2fc2f1685
    License
    MIT
    Collected
    2026-07-28
    Default branch
    main
    View the original 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.
    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.

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