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Python Testing

Checked
laurigates·vlatest·backend·MIT

Helps with Python, testing 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 laurigates/claude-plugins --skill python-testing -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

laurigates

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 laurigates/claude-plugins at 45d1d7dcf6.

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

Commit
45d1d7dcf6
Manifest
python-plugin/skills/python-testing/SKILL.md
Scanned
2 files, 404 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 enables AI agents to execute Python code directly within their environment, allowing them to perform calculations, manipulate data structures, and run scripts autonomously. It bridges the gap between natural language requests and executable logic by providing a runtime sandbox for Python execution.

When to use it

  • Data Analysis: Quickly summarize CSV files or process JSON datasets without setting up local environments.
  • Mathematical Logic: Solve complex equations or perform iterative algorithms that require precise floating-point arithmetic.
  • Script Automation: Generate and run short utility scripts to format text, rename files, or validate input patterns.
  • Rapid Prototyping: Test logic snippets instantly before integrating them into larger backend services.

Key capabilities

  • Executes standard Python 3 code blocks in a secure sandbox.
  • Supports imports from the standard library (e.g., math, json, datetime).
  • Returns output, errors, or logs directly to the agent's response stream.
  • Handles multi-line scripts and conditional logic flows.

Example prompts

  • "Write a Python script that reads a list of numbers and returns the median value."
  • "Generate code to parse this JSON object and extract all email addresses into a clean list."
  • "Create a function that takes two dates and calculates the number of business days between them."

Tips & gotchas

Ensure you specify the desired Python standard library modules if your logic depends on them, as external packages may not be available in the sandbox. For complex data processing tasks, provide sample input data within the prompt to ensure the agent generates correct parsing logic.