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Azure Mgmt Arizeaiobservabilityeval Dotnet

Checked
claudedjale·vlatest·cloud·MIT

Automates Azure resource management and observability evaluation using .NET for enhanced AI performance monitoring.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add claudedjale/skillset --skill azure-mgmt-arizeaiobservabilityeval-dotnet -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to 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

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No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

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

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    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
Manifest
.github/plugins/azure-sdk-dotnet/skills/azure-mgmt-arizeaiobservabilityeval-dotnet/SKILL.md
Scanned
2 files, 367 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

What it does

This skill provides access to the Azure Management library for Arize AI Observability Evaluation using .NET. It allows agents to interact with and manage Arize observability data within an Azure environment, enabling automated evaluation workflows and integration with existing Azure infrastructure. Specifically, this includes functionalities related to evaluating model performance metrics stored in Arize.

When to use it

  • Automate the creation of new evaluations in Arize based on triggers from Azure events (e.g., a new model deployment).
  • Retrieve specific evaluation results from Arize for reporting or further analysis within an Azure environment.
  • Integrate Arize observability data into existing .NET-based dashboards and monitoring systems hosted on Azure.
  • Manage user access and permissions related to Arize evaluations programmatically through the Azure interface.

Key capabilities

  • Azure Management Library integration
  • Arize AI Observability Evaluation support
  • .NET language support
  • Automated evaluation workflows

Example prompts

  • "Create a new Arize evaluation for model 'my-model' with dataset 'production_data'."
  • "Retrieve the latest performance metrics for the 'sentiment-analysis' evaluation in Arize."
  • "List all users with access to the 'fraud-detection' Arize workspace."

Tips & gotchas

  • Requires appropriate Azure credentials and permissions to interact with both Azure and Arize.
  • Familiarity with .NET programming concepts is beneficial for leveraging this skill effectively.