behavior-driven-development

Behavior-Driven Development (BDD) Skill

This skill provides a comprehensive guide to applying Behavior-Driven Development principles to your coding tasks. BDD is not just about tools; it's a methodology for shared understanding and high-quality implementation.

How to Use This Skill

When the user asks for a feature, bug fix, or refactor, apply the following mindset:

1. Understand Behavior First: Do not start coding until you know what the system should do.
2. Define Scenarios: Create or ask for concrete examples (Gherkin) of the expected behavior.
3. Drive Implementation with Tests: Use the Red-Green-Refactor cycle.

Core Concepts

1. The BDD Cycle

The process flows from requirements to code:

• Discovery: Clarify requirements through examples (The "Three Amigos").
• Formulation: Write these examples as specific scenarios (Given/When/Then).
• Automation: Implement using TDD.

See ./references/bdd-best-practices.md for a detailed guide.

2. Writing Scenarios (Gherkin)

Scenarios are your "Executable Specifications".

• Keep them declarative (business focus).
• Avoid technical jargon and UI details.
• One behavior per scenario.
• Use bdd-specs.md as the planning-stage scenario inventory in the superpowers workflow. During brainstorming and plan writing, keep the reviewed Given/When/Then scenarios in docs/plans/.../bdd-specs.md so design review, task decomposition, and sprint contracts all read from the same source.
• Store executable scenarios in .feature files, NOT as code comments - once implementation begins, translate the scenarios that will be automated into .feature files or the framework-native executable test format. bdd-specs.md is for design and planning; .feature files are for automation and living documentation.

See ./references/gherkin-guide.md for syntax and storage structure.

3. Red-Green-Refactor (TDD)

The engine of implementation:

1. RED: Write a failing test for the scenario (or a unit thereof).
2. GREEN: Write the minimal code to pass the test.
3. REFACTOR: Clean up the code while keeping tests passing.

CRITICAL: The Iron Law

"No production code is written without a failing test first."

The Red step MUST verify the test fails for the right reason (run the test and read the failure output) before writing any implementation. Skipping or rationalizing this step produces:

1. Tests that pass spuriously — you cannot tell if they are capable of failing.
2. Implementation-biased tests — they reflect the code that was written, not the behavior under contract.
3. Legacy code from day one — no behavioral safety net catches future regressions.

If Production Code Already Exists

Delete it and re-derive it from a failing test — do not keep it "as reference," do not "adapt" it into the test-first version, do not read it while writing the test. Any of those re-introduces the implementation-biased-test failure mode above through the back door: a test written while looking at the code it's meant to constrain will pass on the first try regardless of whether it checks the right thing. Delete means delete.

Common Rationalizations (reject all of these)

Rationalization	Why it fails
"I'll write the test after — same coverage either way"	A test written against working code always passes on the first run. That proves the test doesn't crash, not that it verifies the right behavior. Only a test that failed first, for the stated reason, has been shown capable of catching a regression.
"I already manually verified it works"	Manual verification is not repeatable and leaves no regression guard. It answers "did this work once," not "will this keep working."
"This is too simple to need a test"	Simple code changes behavior just as easily as complex code. The Iron Law has no complexity threshold — it has the three named exceptions below and nothing else.
"I'll be pragmatic, not dogmatic, about TDD"	This is the rationalization, not an alternative to it. Every one of these tables' entries is someone being "pragmatic" about skipping the Red step.
"I already spent an hour on this, deleting it is wasteful"	Sunk cost. The hour is already spent whether you delete the code or keep it; keeping untested code doesn't recover that hour, it just adds an unverified regression risk on top of it.

The only legitimate exceptions are named in ./references/bdd-best-practices.md (one-off prototypes, generated code, config files) — and even those should be raised with the user, not silently assumed.

Tests Written After the Fact Answer a Different Question

A test-first test encodes "this is what the system is contracted to do." A test-after test encodes "this is what the code I already wrote happens to do" — it will pass even if the code has the wrong behavior, because it was shaped to match that behavior rather than an independent specification. If you catch yourself writing a test against code you can already see, stop, delete the code, and write the test against the behavior instead.

References

• ./references/bdd-best-practices.md - BDD methodology, discovery, formulation, and automation
• ./references/gherkin-guide.md - Gherkin scenario syntax, storage structure, and examples
• ./references/testing-anti-patterns.md - Mocking pitfalls and other ways tests can pass without verifying real behavior