Core Principle

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

See tests.md for good vs bad test examples.

Anti-Pattern: Horizontal Slicing

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 crap tests:

• Tests written in bulk test imagined behavior, not actual behavior
• You end up testing the shape of things (data structures, function signatures) rather than user-facing behavior
• Tests become insensitive to real changes — they pass when behavior breaks, fail when behavior is fine
• You outrun your headlights, committing to test structure before understanding the implementation

Correct approach: Vertical slices via 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

Step 1: Planning

Before writing any code:

• Confirm with user what interface changes are needed
• Confirm with user which behaviors to test (prioritize)
• 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?"

You can't test everything. Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case.

Step 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
VERIFY: Run project lint + full test suite → must pass
COMMIT: Atomic commit (conventional commits v1)

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

Do not proceed if lint or tests fail. Fix first.

Step 3: Incremental Loop

For each remaining behavior:

RED:    Write next test → fails
GREEN:  Minimal code to pass → passes
VERIFY: Lint + tests → must pass
COMMIT: Atomic commit

Rules:

• One test at a time
• Only enough code to pass current test
• Don't anticipate future tests
• Keep tests focused on observable behavior
• Never proceed past a failing lint or test — fix before moving on
• One commit per cycle — never batch unrelated changes

Step 4: Refactor

After all tests pass, look for refactor candidates:

• Extract duplication into functions/classes
• Deepen modules — move complexity behind simple interfaces
• Apply SOLID principles where natural
• Move logic to where data lives (feature envy)
• Introduce value objects for primitive obsession
• Consider what new code reveals about existing code
• Long methods → break into private helpers (keep tests on public interface)
• Run tests after each refactor step

Never refactor while RED. Get to GREEN first.

Step 5: Completion

After all acceptance criteria met and all checks pass:

• Print ## Manual Testing Checklist with concrete steps to verify manually (if applicable)
• Stop

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
[ ] Lint + tests pass
[ ] Atomic commit made (conventional commits v1)

References

Load these on demand when the situation calls for it:

• tests.md — Good vs bad test examples. Load when writing or reviewing tests.
• mocking.md — When and how to mock. Load when deciding whether to mock a dependency.
• interface-design.md — Testable interfaces and deep modules. Load when designing interfaces or when tests feel hard to write.