skills/azure-content-safety/SKILL.md
Expert knowledge for Azure AI Content Safety development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Content Safety APIs, Docker containers, blocklists, groundedness checks, or custom safety categories, and other Azure AI Content Safety related development tasks. Not for Azure Information Protection (use azure-information-protection), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel), Azure Defender For Cloud (use azure-defender-for-cloud).
npx skillsauth add microsoftdocs/agent-skills azure-content-safetyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill provides expert guidance for Azure AI Content Safety. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,
L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description | |----------|-------|-------------| | Troubleshooting | L37-L41 | Diagnosing and resolving Azure AI Content Safety API errors, including HTTP status codes, common failure causes, and recommended fixes or retries. | | Best Practices | L42-L46 | Tuning Content Safety thresholds, categories, and prompts to reduce misclassifications, plus strategies to balance safety, recall, and user experience. | | Decision Making | L47-L52 | Guidance on migrating apps from Content Safety preview to GA and deciding when and how to use limited-access Content Safety features and models. | | Architecture & Design Patterns | L53-L57 | Architectural guidance for combining cloud, hybrid, and on-device Azure AI Content Safety, including design patterns, deployment options, and integration strategies. | | Limits & Quotas | L58-L64 | Language coverage, building and training custom safety categories, and detecting protected/third‑party code in model outputs. | | Security | L65-L69 | Details on how Azure AI Content Safety encrypts data at rest, including encryption models, key management options, and compliance/security considerations. | | Configuration | L70-L74 | Configuring and using text blocklists in Azure AI Content Safety, including creating, managing, and applying custom blocked terms to filter harmful or unwanted content. | | Integrations & Coding Patterns | L75-L79 | Using the groundedness detection API to check if AI responses are supported by source content, with request/response formats, parameters, and integration patterns | | Deployment | L80-L86 | How to install, configure, and run Azure AI Content Safety Docker containers for text, image, and prompt shield analysis in your own environment. |
| Topic | URL | |-------|-----| | Resolve Azure AI Content Safety API error codes | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/response-codes |
| Topic | URL | |-------|-----| | Reduce false positives and negatives in Content Safety | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/improve-performance |
| Topic | URL | |-------|-----| | Migrate apps from Content Safety preview to GA | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/migrate-to-general-availability | | Decide when to use limited access Content Safety features | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/limited-access |
| Topic | URL | |-------|-----| | Design hybrid and on-device Content Safety solutions | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/embedded-content-safety |
| Topic | URL | |-------|-----| | Check language support for Azure AI Content Safety | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/language-support | | Create and train custom categories with Content Safety | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-custom-categories | | Use protected material detection for code outputs | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-protected-material-code |
| Topic | URL | |-------|-----| | Understand data-at-rest encryption in Content Safety | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/encrypt-data-at-rest |
| Topic | URL | |-------|-----| | Configure and use text blocklists in Content Safety | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/use-blocklist |
| Topic | URL | |-------|-----| | Use Azure AI Content Safety groundedness detection API | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-groundedness |
| Topic | URL | |-------|-----| | Deploy image analysis Content Safety container with Docker | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/containers/image-container | | Install and run Azure Content Safety Docker containers | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/containers/install-run-container | | Run Prompt Shields Content Safety container for prompt attacks | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/containers/prompt-shields-container | | Deploy text analysis Content Safety container with Docker | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/containers/text-container |
tools
Expert knowledge for Microsoft Foundry (aka Azure AI Foundry) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with Azure OpenAI, model router patterns, MCP tools, private networking, or eval workflows, and other Microsoft Foundry related development tasks. Not for Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
tools
Expert knowledge for Microsoft Foundry Local (aka Azure AI Foundry Local) development including troubleshooting, decision making, configuration, and integrations & coding patterns. Use when calling Foundry Local REST/chat APIs, tools, transcription, LangChain apps, Olive HF compilation, or CLI, and other Microsoft Foundry Local related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Tools (use microsoft-foundry-tools), Azure Local (use azure-local).
tools
Expert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents, configuring model routing, securing VNets/Private Link, integrating tools/SDKs, or deploying hubs, and other Microsoft Foundry Classic related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
development
Expert guidance for designing, assessing, and optimizing Azure workloads using Azure Well Architected. Covers design review checklists, recommendations, design principles, tradeoffs, service guides, workload patterns, and assessment questions. Use when designing AI, HPC, SaaS, AVD, or mission-critical workloads with WAF-aligned Azure patterns and guidance, and other Azure Well Architected related development tasks.