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Python_Data_Stack

Checked
vuralserhat86·vlatest·backend

Helps with Python, data as part of developing backend services and APIs 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 vuralserhat86/antigravity-agentic-skills --skill python_data_stack -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

vuralserhat86

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 vuralserhat86/antigravity-agentic-skills at f033922af6.

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

Commit
f033922af6
Manifest
skills/python_data_stack/SKILL.md
Scanned
1 file, 622 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

The python_data_stack skill provides a collection of Python libraries and tools for data manipulation, analysis, and visualization. It allows AI agents to read, process, and output structured data in various formats like CSV, JSON, and potentially others. This skill enables agents to perform tasks such as data cleaning, transformation, and generating reports based on datasets.

When to use it

  • Data Extraction & Transformation: When an agent needs to extract data from a website or file (e.g., CSV, JSON) and transform it into a usable format for further analysis.
  • Report Generation: To automatically generate summaries and reports based on input datasets, like creating sales performance dashboards.
  • Data Analysis & Insights: When an agent needs to analyze data to identify trends, patterns, or anomalies within a dataset.
  • Automated Data Pipelines: To build automated workflows for processing and updating data regularly.

Key capabilities

  • Python library integration (specific libraries not listed)
  • CSV file handling
  • JSON file handling
  • Data transformation functions
  • Data visualization tools (potentially)

Example prompts

  • "Read the CSV file 'sales_data.csv' and calculate the total sales for each product category."
  • "Extract data from this JSON file [paste JSON content] and output a summary of key metrics in markdown format."
  • “Analyze this dataset and identify any outliers or unusual patterns.”

Tips & gotchas

The skill requires a Python environment to be set up. Specific library dependencies might need to be installed separately, depending on the complexity of data processing tasks.