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cccskills
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tdd

Test-driven development with red-green-refactor and behavior-focused tests. Use when the user explicitly wants test-first work, a regression test before a fix, or integration tests that drive a feature through a public interface.

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  • SKILL.md3.8 KB
  • agents/openai.yaml224 B
  • mocking.md1.4 KB
  • tests.md2.2 KB

SKILL.md(원문)

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Test-Driven Development

TDD is the red → green 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.

When exploring the codebase, follow an existing GLOSSARY-MAP.md or CONTEXT-MAP.md, or read the root GLOSSARY.md or CONTEXT.md when present, so test names and interface vocabulary match the project's domain language. Respect ADRs in the area you're touching.

What a good test is

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 it survives refactors because it doesn't care about internal structure.

See tests.md for examples and mocking.md for mocking guidelines.

Seams: where tests go

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.

Test only at settled seams. Before writing any test, write down the seams under test. Derive them from an accepted plan, specification, or repository evidence when those sources already settle the public boundary. Ask the user only when the seam is materially ambiguous. No test is written at an unsupported seam; this keeps testing effort on critical paths and complex logic instead of every edge case.

Give each proposed seam a one-line note on what it catches and what it misses. Ask only when needed: "What's the public interface, and which seams should we test?"

When the shape of that interface is itself in question (how deep the module is, where the seam belongs, what the interface should expose), consult the available codebase-design guidance for the vocabulary. It is the shared source of the module, interface, depth, seam, adapter, leverage and locality terms, and it is a reference to consult, not a session to run.

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.
  • 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.
  • 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.

Rules of the loop

  • 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.
  • Refactor only while green. After the minimal implementation passes, improve structure without changing behavior; keep the tests green throughout, then begin the next red → green slice.

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adhx

무료

Read public X/Twitter post URLs as structured evidence through the ADHX API. Use for relevant user-provided or research-discovered x.com, twitter.com, or adhx.com links. ADHX does not search X, and long-form Article content may be incomplete.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioinformatist/codex-base92026년 10월 16일 업데이트

Design, review, or report a measured performance comparison. Use for benchmark methodology, speedup or regression claims, and performance-based choices; not generic performance discussion, ordinary dependency bumps, local renames, or prose edits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioinformatist/codex-base92026년 10월 16일 업데이트

Trace what an actual code change could break beyond its diff when interfaces, serialized data, database schemas, configuration, caches, lifecycle ordering, or cross-language consumers are involved. Use for explicit impact analysis; not local renames, prose edits, ordinary dependency bumps, or generic architecture discussion.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioinformatist/codex-base92026년 10월 16일 업데이트

Shared vocabulary for designing deep modules, interfaces, seams, adapters, leverage, and locality. Use when designing or reshaping module boundaries, making code more testable, or evaluating interface depth.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioinformatist/codex-base92026년 10월 16일 업데이트

Plan or implement retirement of a system, API, feature, persisted configuration, or database shape. Use for compatibility cutovers, explicit deprecation review, or an explicit unreleased replacement decision, including determining whether consumers or data exist; not ordinary dependency bumps, local renames, prose edits, or generic architecture discussion.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioinformatist/codex-base92026년 10월 16일 업데이트

Disciplined diagnosis loop for hard bugs, regressions, flaky failures, and performance problems with unclear cause. Use for root-cause debugging after a concrete symptom exists; do not use for routine implementation or speculative cleanup.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioinformatist/codex-base92026년 10월 16일 업데이트

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