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, integrations & coding patterns, and deployment. 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 |
|---|
| 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-L75 | Configuring Content Safety runtime via Docker containers and setting up/managing text blocklists to customize and enforce content filtering rules |
| Integrations & Coding Patterns | L76-L80 | Using the groundedness detection API to check if AI responses are supported by source content, with request/response formats, parameters, and integration patterns |
| Deployment | L81-L86 | How to install, configure, and run Azure AI Content Safety Docker containers for text, image, and prompt shield analysis in your own environment. |
Troubleshooting
| Topic | URL |
|---|
| Resolve Azure AI Content Safety API error codes | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/response-codes |
Best Practices
| 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 |
Decision Making
| 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 |
Architecture & Design Patterns
| 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 |
Limits & Quotas
| 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 |
Security
| 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 |
Configuration
| Topic | URL |
|---|
| Configure and run Azure AI Content Safety Docker containers | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/containers/install-run-container |
| Configure and use text blocklists in Content Safety | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/use-blocklist |
Integrations & Coding Patterns
| Topic | URL |
|---|
| Use Azure AI Content Safety groundedness detection API | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-groundedness |
Deployment
| 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 |
| 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 |
Setup Matt Pocock SkillsScaffold the per-repo configuration that Matt Pocock’s engineering agent skills rely on so they understand the issue tracker, triage labels, and domain documentation la495k196k
Lark AppsConnect Claude, Cursor or custom agents directly to Lark (Feishu) for messaging, document automation, approval workflows and enterprise data access.402k
CavemanSlash token usage by roughly 75% while keeping every technical detail intact when working with Claude Code, Cursor or similar agents.391k94.7k
Lark Skill MakerQuickly turn any Lark/Feishu OpenAPI call or multi-step workflow into a reusable agent skill with its own SKILL.md.386k16k
Running Claude Code Via Litellm CopilotRun Claude Code at a fraction of the cost by routing requests through LiteLLM to the GitHub Copilot Chat API.270k72
Codex PetGenerate a complete Codex Pet spritesheet and metadata from one reference image without needing an OpenAI key or Codex Pro.246k10