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Red-green-refactor scaffold for building new features with TDD. Write failing tests first, then implement to pass.
Passed 20 of 22 test cases with the skill, and 14 of 22 without it.
and 7 more in the full report
6 fixed14 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
In what sequence relative to happy path tests should edge cases (such as nil inputs, empty lists, or capacity limits) be tested when building a new `CacheStorage` component?
| Checked | Without skill | With skill |
|---|---|---|
| Edge cases are tested after happy path and state verification tests but before error handling tests. | Missed | Passed |
The instructions your model reads when the skill loads.
Build new features using the red-green-refactor cycle. Tests define the spec, AI generates the implementation, tests verify correctness.
Use this skill when the user:
Traditional: AI generates code → You hope it's correct → Ship → Find bugs
TDD with AI: You write tests (spec) → AI generates code to pass → Proven correct
The test is your acceptance criteria in code form. AI excels at going from failing test to passing implementation — it's a concrete, unambiguous target.
Before writing any code or tests, understand:
Sketch the public interface before writing tests:
// Example: Designing a FavoriteManager
test cases passed, vs 14 / 22 without
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