jpskill.com
🛠️ 開発・MCP コミュニティ

microsoft-foundry-tools

Azure AIサービス開発におけるベストプラクティス、設計パターン、セキュリティ、制限事項などを踏まえ、最適な開発を支援するSkill。

📜 元の英語説明(参考)

Expert knowledge for Microsoft Foundry Tools (aka Azure AI services, Azure Cognitive Services) development including best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Content Moderator, Content Understanding analyzers, Azure AI document processing, quotas, or Foundry security, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local).

🇯🇵 日本人クリエイター向け解説

一言でいうと

Azure AIサービス開発におけるベストプラクティス、設計パターン、セキュリティ、制限事項などを踏まえ、最適な開発を支援するSkill。

※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。

⬇ このSkillをダウンロード(.skill) 元のソースを見る ↗

⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。

🎯 このSkillでできること

下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。

📦 インストール方法 (3ステップ)

  1. 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
  2. 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
  3. 3. 展開してできたフォルダを、ホームフォルダの .claude/skills/ に置く
    • · macOS / Linux: ~/.claude/skills/
    • · Windows: %USERPROFILE%\.claude\skills\

Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。

詳しい使い方ガイドを見る →
最終更新
2026-05-17
取得日時
2026-05-17
同梱ファイル
1
📖 Claude が読む原文 SKILL.md(中身を展開)

この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。

Microsoft Foundry Tools Skill

This skill provides expert guidance for Microsoft Foundry Tools. Covers best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities.

How to Use This Skill

IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., [security.md](security.md)), use read_file on the linked reference file

IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide

This skill requires network access to fetch documentation content:

  • Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
  • Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.

Category Index

Category Lines Description
Best Practices L35-L40 Guidance on improving Content Understanding accuracy, grounding and confidence in document extraction, and migrating from preview to GA Content Understanding APIs.
Decision Making L41-L48 Guidance on choosing Foundry vs Content Understanding tools, selecting Azure AI document processing options, migrating preview to GA APIs, and estimating Content Understanding costs.
Architecture & Design Patterns L49-L53 Guidance on choosing and configuring deployment options (serverless, managed, custom) for Content Understanding models, including trade-offs, scalability, and integration patterns.
Limits & Quotas L54-L61 Quotas, limits, and supported languages for Content Moderator image/list APIs and Content Understanding, plus .NET samples showing how to stay within list and usage limits.
Security L62-L66 Securing Foundry: auth methods, Entra-only access, keys/Key Vault, CMK encryption, DLP, VNet rules, API key rotation, Azure Policy and regulatory compliance configuration
Configuration L67-L76 Configuring and customizing Content Understanding analyzers (prebuilt and custom), document layout, face detection, and cross-resource capacity settings.
Integrations & Coding Patterns L77-L91 Using Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, term lists, multimodal analysis, and consuming Markdown/structured outputs

Best Practices

Topic URL
Apply best practices for Content Understanding accuracy https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices
Improve document extraction with confidence and grounding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement

Decision Making

Topic URL
Choose Azure AI tool for document processing https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool
Choose between Foundry and Content Understanding Studio features https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio
Migrate Content Understanding from preview to GA APIs https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga
Estimate and plan Content Understanding pricing https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer

Architecture & Design Patterns

Topic URL
Select model deployment options for Content Understanding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments

Limits & Quotas

Topic URL
Use Content Moderator image lists within quota limits https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-lists-quickstart-dotnet
Use supported languages in Content Moderator API https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/language-support
Apply Content Moderator .NET samples with list limits https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet
Content Understanding service quotas and limits reference https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits

Security

Topic URL
Secure Content Understanding with keys and identities https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications

Configuration

Topic URL
Configure and reference analyzers in Azure Content Understanding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/analyzer-reference
Use and customize Content Understanding prebuilt analyzers https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/prebuilt-analyzers
Configure document layout analysis with Content Understanding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/elements
Configure face detection and recognition in Content Understanding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/face/overview
Configure cross-resource capacity for Content Understanding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/bring-your-own-cross-resource-capacity
Build and refine custom analyzers in Content Understanding Studio https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/customize-analyzer-content-understanding-studio

Integrations & Coding Patterns

Topic URL
Content Moderator REST API operations reference https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/api-reference
Integrate Content Moderator via .NET client library https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/client-libraries
Call Content Moderator image moderation APIs https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-moderation-api
Call Content Moderator REST APIs from C# samples https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-rest
Use .NET SDK term lists with Content Moderator https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/term-lists-quickstart-dotnet
Use Content Moderator text moderation APIs https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/text-moderation-api
Moderate video content using Content Moderator .NET SDK https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/video-moderation-api
Consume Content Understanding document Markdown output https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/markdown
Call Content Understanding REST API for multimodal data https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api
Create custom Content Understanding analyzers via REST API https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer
Extract structured audiovisual content with Content Understanding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/elements
Use audiovisual Markdown output from Content Understanding https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/markdown