name: azure-quantum
description: Expert knowledge for Azure Quantum development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using QDK with Azure Quantum workspaces, IonQ/Quantinuum/Rigetti targets, QIR/OpenQASM jobs, or Resource Estimator, and other Azure Quantum related development tasks. Not for Azure HPC Cache (use azure-hpc-cache), Azure Batch (use azure-batch), Azure Databricks (use azure-databricks), Azure Machine Learning (use azure-machine-learning).
compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata:
generated_at: "2026-06-21"
generator: "docs2skills/1.0.0"
Azure Quantum Skill
This skill provides expert guidance for Azure Quantum. 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-L44 |
Troubleshooting Azure Quantum provider issues: diagnosing job failures and support/escalation policies and limits for IonQ, Quantinuum, and Rigetti hardware on Azure Quantum. |
| Best Practices |
L45-L49 |
Best practices for using QDK in VS Code with Copilot, optimizing large Q# programs via resource estimation, and systematically testing and debugging quantum code. |
| Decision Making |
L50-L56 |
Guidance on Azure Quantum costs, provider pricing and regions, workspace migration, choosing Q# dev tools, and planning quantum-safe cryptography with the resource estimator. |
| Architecture & Design Patterns |
L57-L61 |
Guidance on designing hybrid quantum-classical workflows in Azure Quantum, including architecture options, orchestration patterns, and when to offload tasks to quantum hardware. |
| Limits & Quotas |
L62-L68 |
Managing Azure Quantum quotas, job/session limits, timeouts, and Rigetti-specific hardware constraints and target capabilities. |
| Security |
L69-L79 |
Managing secure access to Azure Quantum workspaces: RBAC and access control, bulk user assignment, ARM locks, managed identities, service principals, and secure handling of access keys. |
| Configuration |
L80-L92 |
Configuring Azure Quantum workspaces, QDK tools, simulators, and hardware targets, plus setting up and customizing Quantum Resource Estimator models and outputs. |
| Integrations & Coding Patterns |
L93-L103 |
Integrating QDK with Azure Quantum: connecting workspaces, submitting Cirq/OpenQASM/QIR/Pulser jobs, building noise and application models, and running adaptive hybrid quantum workflows. |
| Deployment |
L104-L108 |
Deploying Azure Quantum workspaces with Bicep and running/submitting Q# quantum programs from VS Code to Azure Quantum backends |
Troubleshooting
Best Practices
Decision Making
Architecture & Design Patterns
Limits & Quotas
Security
Configuration
Integrations & Coding Patterns
Deployment