azure-machine-learning
Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure ML pipelines, AutoML, managed online/batch endpoints, prompt flow, or MLflow deployments, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Data Science Virtual Machines (use azure-d
npx skills add majiayu000/claude-skill-registry --skill azure-machine-learning --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
The skill provides expert guidance for Azure Machine Learning across troubleshooting, best practices, decision making, architecture and design patterns, limits and quotas, security, configuration, integrations and coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
How it works
- It directs the agent to use the Category Index to locate relevant sections. For categories with line ranges, use read_file with the specified lines. For categories with file links, use read_file on the linked reference file.
- It requires network access to fetch documentation content via mcp_microsoftdocs:microsoft_docs_fetch (preferred) or fetch_webpage (fallback). The agent should fetch content labeled from learn-agent-skill and present it to the user.
- It also advises that if metadata.generated_at is more than 3 months old, the user should pull the latest version from the repository; and if the mcp_microsoftdocs tool is unavailable, suggest installing it via the provided Installation Guide link.
When to use it
Use when working with Azure Machine Learning development tasks, including AML pipelines, AutoML, managed online/batch endpoints, prompt flow, MLflow deployments, and related AML development activities. The skill is not intended for Azure Databricks, Azure Synapse Analytics, Azure HDInsight, or Azure Data Science Virtual Machines.
What it can touch
- Tools: claude-code (as declared)
- Documentation sources: mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage (network access required)
- References to Microsoft Learn content via fetched Markdown
Caveats
- Requires network access to retrieve documentation content.
- Generated_at timestamp guidance: if older than 3 months, user should update from repository.
- Language: English response mandated; content is driven by fetched documentation and internal references.
# Azure Machine Learning Skill This skill provides expert guidance for Azure Machine Learning. 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](https://github.com/MicrosoftDocs/mcp/blob/main/README.md) 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
- How to Use This Skill
- Category Index
- Troubleshooting
- Best Practices
- Decision Making
- Architecture & Design Patterns
- Limits & Quotas
- Security
- Configuration
- Integrations & Coding Patterns
- Deployment
What does the azure-machine-learning skill do?
Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure ML pipelines, AutoML, managed online/batch endpoints, prompt flow, or MLflow deployments, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Data Science Virtual Machines (use azure-d
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill azure-machine-learning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.