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Python

Checked
siviter-xyz·vlatest·backend·MIT

Executes Python code to process data, generate reports, or automate tasks within the Siviter backend environment.

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 siviter-xyz/dot-agent --skill python -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

siviter-xyz

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 siviter-xyz/dot-agent at 33762551d4.

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

Commit
33762551d4
Manifest
skills/python/SKILL.md
Scanned
3 files, 212 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

The Python skill enables AI agents to execute scripts, run data analysis tasks, and automate complex backend operations directly within the agent environment. It provides access to the full Python ecosystem for dynamic logic processing and rapid prototyping of server-side functions.

When to use it

  • Automating repetitive data transformation or cleaning workflows without manual intervention.
  • Running custom scripts to generate reports or visualize datasets on demand.
  • Integrating third-party libraries to extend agent capabilities beyond standard tools.
  • Executing backend logic for API interactions or server-side computations.

Key capabilities

  • Full Python interpreter access for code execution.
  • Support for installing and managing external packages via pip.
  • Ability to handle file I/O operations for reading and writing data.
  • Execution of complex mathematical and statistical calculations.

Example prompts

  • "Run a script to analyze the sales data in this CSV file and output the top 5 products."
  • "Install the pandas library and create a summary report of the user activity logs."
  • "Write and execute a Python function that scrapes specific headers from a public API and formats them as JSON."

Tips & gotchas

Ensure you have sufficient memory allocated for long-running scripts or heavy data processing tasks. Be mindful of execution timeouts when running iterative loops or complex algorithms within the agent session.