Codex Readiness Unit Test

🏢Official
by openai · vlatest · Repository

Automatically generates unit tests to ensure OpenAI Codex code snippets meet quality and functionality standards.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add codex-readiness-unit-test npx -- -y @trustedskills/codex-readiness-unit-test
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "codex-readiness-unit-test": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/codex-readiness-unit-test"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

codex-readiness-unit-test

What it does

This skill prepares codebases for unit testing, ensuring they are structured correctly to support automated test execution. It analyzes existing code to identify gaps in testability and suggests necessary refactoring steps.

When to use it

  • Before writing new unit tests to ensure the codebase is ready for coverage.
  • When refactoring legacy code that lacks modular separation or dependencies.
  • To validate that a project follows testing best practices before CI/CD integration.
  • During code reviews to automatically check for testability issues.

Key capabilities

  • Analyzes code structure for unit test compatibility.
  • Identifies missing dependencies and coupling issues.
  • Suggests refactoring patterns to improve isolation.
  • Validates adherence to testing standards.

Example prompts

  • "Run the codex-readiness-unit-test skill on my React application to check if it's ready for unit testing."
  • "Analyze this Python module and tell me what changes are needed to make it unit testable."
  • "Check my Node.js project for dependencies that prevent effective unit testing."

Tips & gotchas

Ensure your codebase has a clear dependency structure, as the skill relies on identifying these relationships. This tool is most effective when used early in the development lifecycle rather than after extensive monolithic growth.

Tags

🛡️

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Details

Version
vlatest
License
Author
openai
Installs
72

🏢 Official

Published by the company or team that built the technology.