Azure Monitor Ingestion Py
CheckedHelps with Azure, monitoring as part of deploying and managing cloud infrastructure workflows.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add claudedjale/skillset --skill azure-monitor-ingestion-py -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
claudedjale
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned claudedjale/skillset at 154f146735.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 154f146735
- Scanned
- 2 files, 369 lines
About this skill
What it does
This skill allows AI agents to interact with Azure Monitor Ingestion using Python. It enables programmatic access to configure data sources, manage ingestion settings, and troubleshoot potential issues related to log and metric data flowing into Azure Monitor. Specifically, it facilitates the automation of tasks that would otherwise require manual configuration through the Azure portal or CLI.
When to use it
- Automate the creation and configuration of new Azure Monitor data sources for custom applications.
- Troubleshoot ingestion issues by programmatically checking connection status and settings.
- Manage and update existing data source configurations, such as adjusting sampling rates or adding filters.
- Integrate Azure Monitor Ingestion management into automated deployment pipelines.
Key capabilities
- Python-based interaction with Azure Monitor Ingestion API.
- Configuration of data sources.
- Management of ingestion settings.
- Troubleshooting and diagnostics related to data ingestion.
Example prompts
- "Create a new data source in Azure Monitor for my application, using the provided connection string."
- "Check the status of the existing 'MyApplicationLogs' data source."
- "Update the sampling rate for the 'PerformanceMetrics' data source to 10%."
Tips & gotchas
- Requires appropriate Azure credentials and permissions to manage Azure Monitor Ingestion resources.
- Familiarity with Python and Azure concepts is beneficial for effective use of this skill.