Azure AI Content Safety Skill
This skill provides expert guidance for Azure AI Content Safety. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
How to Use This Skill
IMPORTANT for Agent: This file may be large. Use the Category Index below to locate relevant sections, then use read_file with specific line ranges (e.g., L136-L144) to read the sections needed for the user's question
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 |
| Troubleshooting |
L36-L40 |
Diagnosing and resolving Azure AI Content Safety API errors, including HTTP status codes, common failure causes, and recommended fixes or retries. |
| Best Practices |
L41-L45 |
Tuning Content Safety thresholds, categories, and prompts to reduce misclassifications, plus strategies to balance safety, recall, and user experience. |
| Decision Making |
L46-L51 |
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 |
L52-L56 |
Architectural guidance for combining cloud, hybrid, and on-device Azure AI Content Safety, including design patterns, deployment options, and integration strategies. |
| Limits & Quotas |
L57-L63 |
Language coverage, building and training custom safety categories, and detecting protected/third‑party code in model outputs. |
| Security |
L64-L68 |
Details on how Azure AI Content Safety encrypts data at rest, including encryption models, key management options, and compliance/security considerations. |
| Configuration |
L69-L73 |
Configuring and using text blocklists in Azure AI Content Safety, including creating, managing, and applying custom blocked terms to filter harmful or unwanted content. |
| Deployment |
L74-L80 |
How to install, configure, and run Azure AI Content Safety Docker containers for text, image, and prompt shield analysis in your own environment. |
Troubleshooting
Best Practices
Decision Making
Architecture & Design Patterns
Limits & Quotas
Security
Configuration
Deployment