tdd: reshape into reference-only with pre-agreed seams

The red → green → refactor loop is anchored by leading words the model
already holds, so the step-by-step Workflow mostly restated the loop and
duplicated the horizontal-slicing anti-pattern. Drop the Workflow and
per-cycle checklist; fold their durable idea (vertical slices / tracer
bullets) into Anti-patterns and a short Rules-of-the-loop list.

Introduce **seam** as the leading word for where tests go, collapsing the
old Philosophy "public interfaces" prose and the Planning "confirm
interface / behaviors" handshake into one rule: test only at pre-agreed
seams, confirmed with the user before any test is written.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Matt Pocock 2026-06-30 09:43:49 +01:00
parent 43ea0884b0
commit e81f97660a
2 changed files with 21 additions and 91 deletions

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---
"mattpocock-skills": patch
---
Reshape the `tdd` skill into reference-only. The red → green → refactor loop is anchored by leading words the model already holds, so the step-by-step Workflow was largely restating the loop and duplicating the horizontal-slicing anti-pattern. Dropped the Workflow and per-cycle checklist; folded their one durable idea — vertical slices / tracer bullets — into the Anti-patterns section and a short Rules-of-the-loop list. Introduced **seam** as the leading word for where tests go, collapsing the old Philosophy "public interfaces" prose and the Planning "confirm interface / behaviors" handshake into one rule: test only at pre-agreed seams, confirmed with the user before any test is written.

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@ -5,107 +5,32 @@ description: Test-driven development. Use when the user wants to build features
# Test-Driven Development # Test-Driven Development
## Philosophy TDD is the red → green → refactor loop. This skill is the reference that makes that loop produce tests worth keeping: what a good test is, where tests go, the anti-patterns, and the rules of the loop. Every section applies on every cycle — consult them before and during the loop, not after.
**Core principle**: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't. When exploring the codebase, read `CONTEXT.md` (if it exists) so test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
**Good tests** are integration-style: they exercise real code paths through public APIs. They describe _what_ the system does, not _how_ it does it. 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. ## What a good test is
**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). The 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. 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 — and survives refactors because it doesn't care about internal structure.
**Tautological tests** restate the implementation inside the assertion, so they pass by construction and give zero confidence. When the expected value is computed the way the code computes it — `expect(add(a, b)).toBe(a + b)`, snapshotting a figure you derived by hand the same way the code does, asserting a constant equals itself — the test can never disagree with the code: break the code wrong and the assertion breaks wrong with it. The expected value must come from an independent source of truth — a known-good literal, a worked example, the spec.
See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines. See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
## Anti-Pattern: Horizontal Slices ## Seams — where tests go
**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." A **seam** is the public boundary you test at: the interface where you observe behavior without reaching inside. Tests live at seams, never against internals.
This produces **crap tests**: **Test only at pre-agreed seams.** Before writing any test, write down the seams under test and confirm them with the user. No test is written at an unconfirmed seam. You can't test everything — agreeing the seams up front is how testing effort lands on the critical paths and complex logic instead of every edge case.
- Tests written in bulk test _imagined_ behavior, not _actual_ behavior Ask: "What's the public interface, and which seams should we test?"
- 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. Because you just wrote the code, you know exactly what behavior matters and how to verify it. ## Anti-patterns
``` - **Implementation-coupled** — mocks internal collaborators, tests private methods, or verifies through a side channel (querying the database instead of using the interface). The tell: the test breaks when you refactor but behavior hasn't changed.
WRONG (horizontal): - **Tautological** — the assertion recomputes the expected value the way the code does (`expect(add(a, b)).toBe(a + b)`, a snapshot derived by hand the same way, a constant asserted equal to itself), so it passes by construction and can never disagree with the code. Expected values must come from an independent source of truth — a known-good literal, a worked example, the spec.
RED: test1, test2, test3, test4, test5 - **Horizontal slicing** — writing all tests first, then all implementation. Bulk tests verify _imagined_ behavior: you test the _shape_ of things rather than user-facing behavior, the tests go insensitive to real changes, and you commit to test structure before understanding the implementation. Work in **vertical slices** instead — one test → one implementation → repeat, each test a **tracer bullet** that responds to what the last cycle taught you.
GREEN: impl1, impl2, impl3, impl4, impl5
RIGHT (vertical): ## Rules of the loop
RED→GREEN: test1→impl1
RED→GREEN: test2→impl2
RED→GREEN: test3→impl3
...
```
## Workflow - **Red before green.** Write the failing test first, then only enough code to pass it. Don't anticipate future tests or add speculative features.
- **One slice at a time.** One seam, one test, one minimal implementation per cycle.
### 1. Planning - **Never refactor while red.** Get to green first, then look for [refactor candidates](refactoring.md) — including deepening modules (small interface, deep implementation; see `/codebase-design`). Run the tests after each refactor step.
When exploring the codebase, read `CONTEXT.md` (if it exists) so that test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
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) — run the `/codebase-design` skill for the vocabulary and the testability checks
- [ ] 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.
### 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 your 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 [refactor candidates](refactoring.md):
- [ ] 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.
## Checklist Per Cycle
```
[ ] Test describes behavior, not implementation
[ ] Test uses public interface only
[ ] Test would survive internal refactor
[ ] Expected values are independent literals, not recomputed from the code
[ ] Code is minimal for this test
[ ] No speculative features added
```