Unit Test Boundary Conditions

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by giuseppe-trisciuoglio · vlatest · Repository

Automatically generates unit tests focused on boundary conditions to improve code robustness and edge case coverage.

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 unit-test-boundary-conditions npx -- -y @trustedskills/unit-test-boundary-conditions
2

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

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

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

About This Skill

What it does

This skill helps AI agents identify and test boundary conditions in software code. It focuses on edge cases such as minimum, maximum, or out-of-range inputs to ensure robustness and reliability of functions.

When to use it

  • Testing a function that handles numerical ranges (e.g., validating user input within specific limits).
  • Ensuring a system behaves correctly when receiving unexpected or extreme values.
  • Preparing for code reviews by identifying potential edge cases that may not be covered in existing test suites.

Key capabilities

  • Detects boundary conditions such as minimum and maximum values.
  • Generates test cases for edge scenarios like empty inputs, null values, or overflow/underflow situations.
  • Analyzes function parameters to determine valid ranges and constraints.

Example prompts

  • "Generate unit tests for the calculateDiscount function that checks behavior when the discount percentage is 0% or 100%."
  • "Identify boundary conditions in the validateEmail function, including empty strings and invalid formats."
  • "Test edge cases for a function that processes user age input, such as negative numbers or values above 120."

Tips & gotchas

  • Ensure the code being tested has clear constraints defined (e.g., input ranges) to get accurate results.
  • This skill works best with well-documented functions; ambiguous logic may lead to incomplete test coverage.

Tags

🛡️

TrustedSkills Verification

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Details

Version
vlatest
License
Author
giuseppe-trisciuoglio
Installs
286

🌐 Community

Passed automated security scans.