Agent skill · software engineering · membranedev
azure-openai-service
Azure OpenAI Service integration. Manage Models, Deployments, Prompts, Completions. Use when the user wants to interact with Azure OpenAI Service data.
Why this skill is useful
Adds specific commands and workflows for managing Azure OpenAI Service deployments and models that the AI wouldn't reliably generate on its own.
What it needs
Requires @membranehq/cli installed locally. Requires membrane account access. About 4k tokens when loaded. Last updated 2026-04-28. 253 stars on the source repository.
What this skill does
Azure OpenAI Service Azure OpenAI Service provides access to OpenAI's powerful language models, including GPT-3, Codex, and DALL-E, through the Azure cloud platform. Developers and organizations use it to build AI-powered applications for natural language processing, code generation, and image creation. It's suitable for businesses seeking enterprise-grade security, compliance, and scalability. Official docs: https://learn.microsoft.com/en-us/azure/cognitive-services/openai/ Azure OpenAI Service Overview Deployments Chat Completions — For interacting with chat models. Models — Listing and managing available models. Data Sources — For managing data sources used by the models. Evaluations — For evaluating model performance. Indexes — For managing indexes. Projects — For organizing and managing related resources. Use action names and parameters as needed. Working with Azure OpenAI Service This skill uses the Membrane CLI to interact with Azure OpenAI Service. Membrane handles authentication and credentials refresh automatically — so you can focus on the integration logic rather than auth plumbing. Install the CLI Install the Membrane CLI so you can run membrane from the terminal: Authentication This will either open a browser for authentication or print an authorization URL to the console, depending on whether interactive mode is available. Headless environments: The command will print an authorization URL. Ask the user to open it in a browser. When they see a code after completing login, finish with: Add --json to any command for machine-readable JSON output. Agent Types : claude, openclaw, codex, warp, windsurf, etc. Those will be used to adjust tooling to be used best with your harness Connecting to Azure OpenAI Service Use membrane connection ensure to find or create a connection by app URL or domain: The user completes authentication in the browser. The output contains the new connection id. This is the fastest way to get a connection. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills membranedev/azure-openai-service