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Testing107k · #363

test-driven-development

Helps your agent write code based on tests. It's useful for ensuring code works correctly, fixing bugs, and proving changes are valid.

What it does

This tool helps you write code more reliably. It works by writing a test that fails first, then writing the minimal code to make the test pass, and finally, cleaning up the code.

When to use it

  • ✓When creating new functionality.
  • ✓When fixing a bug.
  • ✓When modifying existing code.

Example of what to ask your AI

“Write a test for the function that calculates factorial, then implement the function.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/addyosmani/agent-skills/blob/main/skills/test-driven-development/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/addyosmani/agent-skills/blob/main/skills/test-driven-development/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

First, you write a test that you know will fail. Then, you create the simplest possible code to make that test pass. Finally, you review and improve the code, ensuring the tests still pass.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add addyosmani/agent-skills --skill test-driven-development

Or download just the file:

curl -L https://raw.githubusercontent.com/addyosmani/agent-skills/main/skills/test-driven-development/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Test-Driven Development

Overview

Write a failing test before writing the code that makes it pass. For bug fixes, reproduce the bug with a test before attempting a fix. Tests are proof — "seems right" is not done. A codebase with good tests is an AI agent's superpower; a codebase without tests is a liability.

When to Use

  • Implementing any new logic or behavior
  • Fixing any bug (the Prove-It Pattern)
  • Modifying existing functionality
  • Adding edge case handling
  • Any change that could break existing behavior

When NOT to use: Pure configuration changes, documentation updates, or static content changes that have no behavioral impact.

Related: For browser-based changes, combine TDD with runtime verification using Chrome DevTools MCP — see the Browser Testing section below.

Discover the Stack First

The TDD cycle is universal; the commands are not. Before writing the first test, discover how this repository tests, and use its commands for every RED, GREEN, and verification step:

  • Language and build system — package.json, pom.xml/build.gradle, pyproject.toml, go.mod, Cargo.toml, Gemfile, a Makefile
  • Checked-in wrappers — prefer ./gradlew, ./mvnw, make test, or a repo script over globally installed tools
  • Test framework and configuration — and how it runs a single focused test vs the full suite
  • Existing conventions — where tests live, how files are named, what patterns neighboring tests follow
  • Documented commands — README, CONTRIBUTING, and CI workflows show the commands that actually gate merges

Run the repository's focused-test command during the loop and its full-suite command before completion. Never assume a default like npm test — a Gradle, Cargo, or pytest project has its own equivalent.

The examples below use TypeScript for illustration; the workflow is identical in any language once you've discovered the project's own tooling.

The TDD Cycle

    RED                GREEN              REFACTOR
 Write a test    Write minimal code    Clean up the
 that fails  ──→  to make it pass  ──→  implementation  ──→  (repeat)
      │                  │                    │
      ▼                  ▼                    ▼
   Test FAILS        Test PASSES         Tests still PASS

Step 1: RED — Write a Failing Test

Write the test first. It must fail. A test that passes immediately proves nothing.

// RED: This test fails because createTask doesn't exist yet
describe('TaskService', () => {
  it('creates a task with title and default status', async () => {
    const task = await taskService.createTask({ title: 'Buy groceries' });

    expect(task.id).toBeDefined();
    expect(task.title).toBe('Buy groceries');
    expect(task.status).toBe('pending');
    expect(task.createdAt).toBeInstanceOf(Date);
  });
});

Step 2: GREEN — Make It Pass

Write the minimum code to make the test pass. Don't over-engineer:

// GREEN: Minimal implementation
export async function createTask(input: { title: string }): Promise<Task> {
  const task = {
    id: generateId(),
    title: input.title,
    status: 'pending' as const,
    createdAt: new Date(),
  };
  await db.tasks.insert(task);
  return task;
}

Step 3: REFACTOR — Clean Up

With tests green, improve the code without changing behavior:

  • Extract shared logic
  • Improve naming
  • Remove duplication
  • Optimize if necessary

Run tests after every refactor step to confirm nothing broke.

The Prove-It Pattern (Bug Fixes)

When a bug is reported, do not start by trying to fix it. Start by writing a test that reproduces it.

Bug report arrives
       │
       ▼
  Write a test that demonstrates the bug
       │
       ▼
  Test FAILS (confirming the bug exists)
       │
       ▼
  Implement the fix
       │
       ▼
  Test PASSES (proving the fix works)
       │
       ▼
  Run full test suite (no regressions)

Example:

// Bug: "Completing a task doesn't update the completedAt timestamp"

// Step 1: Write the reproduction test (it should FAIL)
it('sets completedAt when task is completed', async () => {
  const task = await taskService.createTask({ title: 'Test' });
  const completed = await taskService.completeTask(task.id);

  expect(completed.status).toBe('completed');
  expect(completed.completedAt).toBeInstanceOf(Date);  // This fails → bug confirmed
});

// Step 2: Fix the bug

…
FAQ

What is the 'Red-Green-Refactor' cycle?

It's the process: 1. Write a failing test (Red). 2. Write the minimal code to make the test pass (Green). 3. Improve the code without breaking the tests (Refactor).

How does this help fix bugs?

You write a test that shows the exact error. If the test fails, you know the bug exists. Then, you fix the code, and the test should pass, proving the bug is fixed.

When should I NOT use this tool?

Don't use it for simple changes like updating documentation or configurations that don't affect how the program works.

Details

Original description by the author

Drives development with tests using the red-green-refactor loop. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality. Use when asked to add tests to a function, fix a bug in it or change its behavior, even when the code is pasted inline and the request

repo: addyosmani/agent-skills

Popularity

GitHub stars
107k
Ranking position
#363
License
MIT
Updated
10/13/2026

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