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Azure Storage File Datalake Py

Checked
claudedjale·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 claudedjale/skillset --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

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.

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

    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
Manifest
.github/plugins/azure-sdk-python/skills/azure-storage-file-datalake-py/SKILL.md
Scanned
2 files, 357 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.
What each check looks for →

About this skill

What it does

This skill allows AI agents to interact with Azure Data Lake Storage Gen2 file systems using Python. It enables tasks such as listing files, uploading data, and downloading data from specified containers within the storage account. The skill leverages the azure-storage-file-datalake library for seamless integration.

When to use it

  • Automating data ingestion: Transferring log files from a local machine to Azure Data Lake Storage for analysis.
  • Data archival: Moving older datasets from primary storage to a cheaper tier in Azure Data Lake Storage.
  • Building data pipelines: Integrating Azure Data Lake Storage as a source or sink within an automated ETL (Extract, Transform, Load) process.
  • File management tasks: Listing files in a specific directory and performing actions based on their names or sizes.

Key capabilities

  • List files within a specified container.
  • Upload data to Azure Data Lake Storage Gen2.
  • Download data from Azure Data Lake Storage Gen2.
  • Uses the azure-storage-file-datalake Python library.

Example prompts

  • "List all .csv files in the 'raw_data' container."
  • "Upload this file, report.txt, to the 'processed_files' container."
  • "Download the file named sales_2023.parquet from the 'archive' container."

Tips & gotchas

  • Ensure you have an active Azure subscription and appropriate permissions to access the target storage account and containers.
  • The skill requires Python 3.6 or higher to be installed in the agent’s environment.