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Test Generator

Checked
ovachiever·vlatest·testing

Generates customized quizzes and tests aligned to specific learning objectives and difficulty levels for assessment.

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 ovachiever/droid-tings --skill test-generator -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

ovachiever

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 ovachiever/droid-tings at 7acd12a754.

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

Commit
7acd12a754
Manifest
skills/test-generator/SKILL.md
Scanned
2 files, 300 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

Test Generator

What it does

This tool generates automated tests for your AI agents, helping you verify behavior and catch regressions early. It streamlines the testing workflow by creating scripts tailored to your specific agent configurations.

When to use it

  • You need to validate that an AI agent responds correctly to specific inputs.
  • You are iterating on agent logic and want quick feedback on breaking changes.
  • You require a baseline of test cases before deploying an agent to production.
  • You want to automate regression testing for frequently updated agent skills.

Key capabilities

  • Automatically creates test scripts based on agent definitions.
  • Supports integration into existing CI/CD pipelines.
  • Generates coverage reports to identify untested scenarios.
  • Allows customization of test parameters and expected outputs.

Example prompts

  • "Generate a unit test suite for my customer support AI agent."
  • "Create regression tests to verify the new feature in my data processing bot."
  • "Write automated tests to check error handling in my chatbot's response logic."

Tips & gotchas

Ensure your agent definitions are up-to-date before running the generator to avoid false positives. Review generated test cases manually to confirm they align with your specific business logic and edge cases.