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microsoft-docs

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.

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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#)

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

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