Configure Azure API Management as an AI Gateway for models, MCP tools, and agents with built-in governance policies.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add microsoft/azure-skills --skill azure-aigatewayCompatible with
Supported agents
Supports semantic caching (60-80% cost savings), token rate limiting, content safety filtering, and jailbreak detection across AI backends
Add Azure OpenAI, AI Foundry models, or convert existing APIs to MCP tools as managed backends with load balancing
Includes five core policy categories: authentication, semantic cache lookup, token limits, content safety, and token
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionazure-aigatewayExecute the skills CLI command in your project's root directory to begin installation:
epx add microsoft/azure-skills --skill azure-aigatewayFetches azure-aigateway from microsoft/azure-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/azure-aigateway
Restart Cursor to activate azure-aigateway. Access via /azure-aigatewayin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
azure-ai
microsoft/azure-skills · Cloud · same repo
azure-compliance
microsoft/azure-skills · Cloud · same repo
microsoft-foundry
microsoft/azure-skills · Productivity · same repo
microsoft-foundry
microsoft/GitHub-Copilot-for-Azure · Cloud · tag: azure
azure-diagnostics
microsoft/GitHub-Copilot-for-Azure · Cloud · tag: azure
azure-compliance
microsoft/GitHub-Copilot-for-Azure · Cloud · tag: azure
azure-aigateway is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
azure-aigateway fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: azure-aigateway is the kind of skill you can hand to a new teammate without a long onboarding doc.
azure-aigateway reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: azure-aigateway is focused, and the summary matches what you get after install.
Registry listing for azure-aigateway matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in azure-aigateway — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
azure-aigateway has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added azure-aigateway from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: azure-aigateway is focused, and the summary matches what you get after install.
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