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Azure Mgmt Weightsandbiases Dotnet

Listed
sickn33·vlatest·cloud·MIT

Manages Weights & Biases experiments and runs using Azure credentials via the dotnet SDK.

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 sickn33/agentic-awesome-skills --skill azure-mgmt-weightsandbiases-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

sickn33

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.

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 sickn33/antigravity-awesome-skills at 5a4cdd9df8.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
0 files
Copies in repo
3 — all of them scanned
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.
What each check looks for →

About this skill

What it does

This skill provides programmatic access to Weights & Biases (W&B) resources within Azure using the .NET SDK. It allows agents to manage W&B projects, runs, and artifacts, enabling automated experiment tracking and management workflows directly from Azure environments. Specifically, it facilitates interacting with W&B APIs for tasks like creating new runs, logging metrics, and retrieving experiment data.

When to use it

  • Automate the creation of Weights & Biases experiments based on triggers in your Azure environment (e.g., a scheduled job).
  • Log training metrics and artifacts from .NET applications running within Azure directly into W&B for monitoring and analysis.
  • Retrieve experiment data from W&B to inform decisions or adjust parameters in ongoing machine learning processes managed in Azure.
  • Manage W&B projects and runs programmatically, such as archiving old experiments or cleaning up resources.

Key capabilities

  • Project management (creation, listing)
  • Run creation and management
  • Artifact management
  • Metrics logging
  • Experiment data retrieval

Example prompts

  • "Create a new Weights & Biases run named 'MyTrainingRun' in the project 'MyProject'."
  • "Log the metric 'accuracy' with value 0.85 to the current Weights & Biases run."
  • "Retrieve the latest experiment data for project 'MyProject' from Weights & Biases."

Tips & gotchas

  • Requires an active Azure subscription and appropriate permissions to access W&B resources.
  • Ensure you have a valid API key or token configured for authentication with Weights & Biases.