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Azure Storage File Datalake Py

Listed
sickn33·vlatest·cloud·MIT

Helps with Azure, storage 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-storage-file-datalake-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

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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 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-storage-file-datalake-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.
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About this skill

What it does

This skill allows AI agents to interact with Azure Data Lake Storage Gen2 files using Python. It enables tasks such as listing directories, downloading specific files, and uploading new data into the datalake. This provides programmatic access for managing large datasets stored in Azure's cloud storage solution.

When to use it

  • Automating file transfers: Regularly move data between your local environment and Azure Data Lake Storage Gen2.
  • Data analysis workflows: Retrieve specific files from a datalake as part of an automated data processing pipeline.
  • Backup and recovery: Create backups of critical data stored in the datalake by downloading it to another location.
  • Content management: Upload new content or update existing files within your Azure Data Lake Storage Gen2 environment.

Key capabilities

  • Listing directories within a specified container.
  • Downloading individual files from the datalake.
  • Uploading data to the datalake.

Example prompts

  • "List all the files in the 'raw_data' directory of my Azure Data Lake Storage Gen2."
  • "Download the file named 'sales_report_2023.csv' from the 'processed_data' container."
  • "Upload this CSV data to a new file called 'customer_feedback.csv' in the 'staging' folder."

Tips & gotchas

  • Requires proper Azure credentials and access permissions configured for the AI agent to interact with your Data Lake Storage Gen2 account. Ensure the agent has appropriate roles assigned.