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Azure Data Tables Py

Listed
sickn33·vlatest·cloud·MIT

Helps with Azure, data as part of deploying and managing cloud infrastructure workflows.

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 sickn33/agentic-awesome-skills --skill azure-data-tables-py -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.

Commit
5a4cdd9df8
Manifest
skills/azure-data-tables-py/SKILL.md
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 allows AI agents to interact with Azure Data Tables using Python. It enables agents to read, write, and manage data stored within these tables, facilitating tasks like storing structured information or retrieving specific records based on partition keys and row keys. The skill provides a convenient interface for programmatic access to your Azure Data Table resources.

When to use it

  • Data Logging: An agent needs to record events or metrics from an application into a structured format within Azure.
  • Configuration Management: An agent requires persistent storage for configuration settings that need to be updated and retrieved dynamically.
  • Inventory Tracking: An agent is responsible for maintaining a list of assets, their properties, and statuses in Azure Data Tables.
  • Session State Storage: Store user session data or temporary information related to ongoing tasks within an Azure Data Table.

Key capabilities

  • Read data from Azure Data Tables
  • Write data to Azure Data Tables
  • Manage (create, delete) entities in Azure Data Tables
  • Python-based interaction

Example prompts

  • "Retrieve all entities with partition key 'users' and row key 'john.doe'."
  • "Create a new entity with partition key 'products', row key 'widget123', and properties {'name': 'Awesome Widget', 'price': 19.99}."
  • “Delete the entity with partition key ‘orders’ and row key ‘order456’.”

Tips & gotchas

  • Requires an active Azure subscription and appropriate permissions to access the target Data Table.
  • Ensure you have the necessary Azure credentials configured for your AI agent.