tdd

name

tdd

description

Test-driven development with a red-green-refactor loop. Builds features or fixes bugs one vertical slice at a time. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", "test-first", "write tests for this", wants integration tests, or asks for test-driven development. Works with any language — Python, TypeScript, Go, etc. For language-specific test tooling (pytest, vitest, jest), defer to language-specific skills.

Test-Driven Development

TDD is not "write all tests, then write all code." It is a vertical slicing discipline that applies to any language.

Philosophy

Tests verify behavior through public interfaces, not implementation details. A good test reads like a specification — "user can checkout with valid cart" tells you what capability exists. These tests survive refactors because they don't care about internal structure.

Good tests are integration-style: they exercise real code paths through public APIs. They describe what the system does, not how it does it.

Bad tests are coupled to implementation: they mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). Warning sign: your test breaks when you refactor, but behavior hasn't changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior.

Anti-Pattern: Horizontal Slices

DO NOT write all tests first, then all implementation. This is "horizontal slicing" — treating RED as "write all tests" and GREEN as "write all code."

This produces poor tests because:

• Tests written in bulk test imagined behavior, not actual behavior
• You test the shape of things (data structures, function signatures) rather than user-facing behavior
• Tests become insensitive to real changes — they pass when behavior breaks
• You commit to test structure before understanding the implementation

The Correct Approach: Vertical Slices (Tracer Bullets)

One test, one implementation, repeat. Each test responds to what you learned from the previous cycle.

WRONG (horizontal):
  RED:   test1, test2, test3, test4, test5
  GREEN: impl1, impl2, impl3, impl4, impl5

RIGHT (vertical):
  RED→GREEN: test1→impl1
  RED→GREEN: test2→impl2
  RED→GREEN: test3→impl3

Workflow

1. Planning

When exploring the codebase, use the project's domain glossary (CONTEXT.md) so that test names and interface vocabulary match the project's language, and respect ADRs in the area you're touching.

Before writing any code:

• Confirm with user what interface changes are needed
• Confirm which behaviors to test (prioritize — you can't test everything)
• Identify opportunities for deep modules (small interface, deep implementation)
• Design interfaces for testability
• List the behaviors to test (not implementation steps)
• Get user approval on the plan

Ask: "What should the public interface look like? Which behaviors are most important to test?"

2. Tracer Bullet

Write ONE test that confirms ONE thing about the system:

RED:   Write test for first behavior → test fails
GREEN: Write minimal code to pass → test passes

This is the tracer bullet — proves the path works end-to-end.

3. Incremental Loop

For each remaining behavior:

RED:   Write next test → fails
GREEN: Minimal code to pass → passes

Rules:

• One test at a time
• Only enough code to pass current test
• Don't anticipate future tests
• Keep tests focused on observable behavior

4. Refactor

After all tests pass, look for refactoring opportunities:

• Extract duplication
• Deepen modules (move complexity behind simple interfaces)
• Apply SOLID principles where natural
• Consider what new code reveals about existing code
• Run tests after each refactor step

Never refactor while RED. Get to GREEN first.

Mocking Guidelines

• Mock at seams, not internals. Mock the external dependencies your module talks to (databases, APIs, file systems), not internal collaborators within the module.
• If you need to mock an internal function to test, the design needs work — the module probably has too many responsibilities.
• Prefer in-memory fakes over mocks when the interface is simple. A dict-backed InMemoryUserRepo is more readable and less brittle than a mock with 10 configured return values.
• Never mock what you don't own by name. Wrap third-party libraries behind your own interface, then mock that interface.

Per-Cycle Checklist

[ ] Test describes behavior, not implementation
[ ] Test uses public interface only
[ ] Test would survive internal refactor
[ ] Code is minimal for this test
[ ] No speculative features added

After the Feature Is Done

Ask: what would have prevented the bugs you found? If the answer involves architectural change (no good test seam, tangled callers, hidden coupling), hand off to the refactor or architecture-patterns skill with the specifics. Make the recommendation after the feature is in, not before — you have more information now.