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microsoft-docs

Find explanations, tutorials, configuration guidance, and code examples in official documentation for Microsoft technologies. Choose documentation sources for Azure, .NET, VS Code, GitHub, Aspire, and Agent Framework based on where the relevant material is published.

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原文查看原文说明

Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP as the default, with Context7 and Aspire MCP for content that lives outside learn.microsoft.com.

集成工具GitHubAzure
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适用场景

  • Find official explanations and setup instructions
  • Look up code examples for a specific language
  • Research VS Code settings or extension APIs
  • Check GitHub Actions and gh command options
  • Investigate Aspire or Agent Framework API details

包含的文件(1)

  • SKILL.md5.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Microsoft Docs

Research skill for the Microsoft technology ecosystem. Covers learn.microsoft.com and documentation that lives outside it (VS Code, GitHub, Aspire, Agent Framework repos).


Default: Microsoft Learn MCP

Use these tools for everything on learn.microsoft.com — Azure, .NET, M365, Power Platform, Agent Framework, Semantic Kernel, Windows, and more. This is the primary tool for the vast majority of Microsoft documentation queries.

ToolPurpose
microsoft_docs_searchSearch learn.microsoft.com — concepts, guides, tutorials, configuration
microsoft_code_sample_searchFind working code snippets from Learn docs. Pass language (python, csharp, etc.) for best results
microsoft_docs_fetchGet full page content from a specific URL (when search excerpts aren't enough)

Use microsoft_docs_fetch after search when you need complete tutorials, all config options, or when search excerpts are truncated.

CLI Alternative

If the Learn MCP server is not available, use the mslearn CLI from your terminal or shell (for example, Bash, PowerShell, or cmd) instead:

# Run directly (no install needed)
npx @microsoft/learn-cli search "BlobClient UploadAsync Azure.Storage.Blobs"

# Or install globally, then run
npm install -g @microsoft/learn-cli
mslearn search "BlobClient UploadAsync Azure.Storage.Blobs"
MCP ToolCLI Command
microsoft_docs_search(query: "...")mslearn search "..."
microsoft_code_sample_search(query: "...", language: "...")mslearn code-search "..." --language ...
microsoft_docs_fetch(url: "...")mslearn fetch "..."

Pass --json to search or code-search to get raw JSON output for further processing.


Exceptions: When to Use Other Tools

The following categories live outside learn.microsoft.com. Use the specified tool instead.

.NET Aspire — Use Aspire MCP Server (preferred) or Context7

Aspire docs live on aspire.dev, not Learn. The best tool depends on your Aspire CLI version:

CLI 13.2+ (recommended) — The Aspire MCP server includes built-in docs search tools:

MCP ToolDescription
list_docsLists all available documentation from aspire.dev
search_docsWeighted lexical search across aspire.dev content
get_docRetrieves a specific document by slug

These ship in Aspire CLI 13.2 (PR #14028). To update: aspire update --self --channel daily. Ref: https://davidpine.dev/posts/aspire-docs-mcp-tools/

CLI 13.1 — The MCP server provides integration lookup (list_integrations, get_integration_docs) but not docs search. Fall back to Context7:

Library IDUse for
/microsoft/aspire.devPrimary — guides, integrations, CLI reference, deployment
/dotnet/aspireRuntime source — API internals, implementation details
/communitytoolkit/aspireCommunity integrations — Go, Java, Node.js, Ollama

VS Code — Use Context7

VS Code docs live on code.visualstudio.com, not Learn.

Library IDUse for
/websites/code_visualstudioUser docs — settings, features, debugging, remote dev
/websites/code_visualstudio_apiExtension API — webviews, TreeViews, commands, contribution points

GitHub — Use Context7

GitHub docs live on docs.github.com and cli.github.com.

Library IDUse for
/websites/github_enActions, API, repos, security, admin, Copilot
/websites/cli_githubGitHub CLI (gh) commands and flags

Agent Framework — Use Learn MCP + Context7

Agent Framework tutorials are on learn.microsoft.com (use microsoft_docs_search), but the GitHub repo has API-level detail that is often ahead of published docs — particularly DevUI REST API reference, CLI options, and .NET integration.

Library IDUse for
/websites/learn_microsoft_en-us_agent-frameworkTutorials — DevUI guides, tracing, workflow orchestration
/microsoft/agent-frameworkAPI detail — DevUI REST endpoints, CLI flags, auth, .NET AddDevUI/MapDevUI

DevUI tip: Query the Learn website source for how-to guides, then the repo source for API-level specifics (endpoint schemas, proxy config, auth tokens).


Context7 Setup

For any Context7 query, resolve the library ID first (one-time per session):

  1. Call mcp_context7_resolve-library-id with the technology name
  2. Call mcp_context7_query-docs with the returned library ID and a specific query

Writing Effective Queries

Be specific — include version, intent, and language:

# ❌ Too broad
"Azure Functions"
"agent framework"

# ✅ Specific
"Azure Functions Python v2 programming model"
"Cosmos DB partition key design best practices"
"GitHub Actions workflow_dispatch inputs matrix strategy"
"Aspire AddUvicornApp Python FastAPI integration"
"DevUI serve agents tracing OpenTelemetry directory discovery"
"Agent Framework workflow conditional edges branching handoff"

Include context:

  • Version when relevant (.NET 8, Aspire 13, VS Code 1.96)
  • Task intent (quickstart, tutorial, overview, limits, API reference)
  • Language for polyglot docs (Python, TypeScript, C#)

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同一仓库的技能

Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.

中文简介正在准备中。当前显示英语简介。

  • Get oriented in an unfamiliar codebase
  • Prepare documentation for a project handover
  • Compare documented architecture with implementation
github/awesome-copilot4万2026年10月17日 更新

Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.

中文简介正在准备中。当前显示英语简介。

  • Assessing a repository’s readiness for AI agents
  • Prioritizing improvements from assessment results
  • Reviewing scores under an organization’s own policy
github/awesome-copilot4万2026年10月17日 更新

Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.

中文简介正在准备中。当前显示英语简介。

  • Create project instructions for VS Code Copilot
  • Refresh agent rules after project changes
  • Split monorepo instructions by project area
github/awesome-copilot4万2026年10月17日 更新

Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.

中文简介正在准备中。当前显示英语简介。

  • Set shared readiness standards across an organization
  • Focus assessments on AI tooling
  • Adjust the importance of individual checks
github/awesome-copilot4万2026年10月17日 更新

Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.

中文简介正在准备中。当前显示英语简介。

  • Identify ads and keywords to pause
  • Find campaigns and audiences worth scaling
  • Assess whether A/B test results are meaningful
github/awesome-copilot4万2026年10月17日 更新

Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.

中文简介正在准备中。当前显示英语简介。

  • Add beginner-friendly explanations to existing code
  • Document the reasoning behind syntax and design choices
  • Adjust comment depth for readers with different experience
github/awesome-copilot4万2026年10月17日 更新

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