You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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Use when implementing any feature or bugfix, before writing implementation code
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Write the test first. Watch it fail. Write minimal code to pass.
Core principle: If you didn't watch the test fail, you don't know if it tests the right thing.
Violating the letter of the rules is violating the spirit of the rules.
Always:
Exceptions (ask your human partner):
Thinking "skip TDD just this once"? Stop. That's rationalization.
NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST
Write code before the test? Delete it. Start over.
No exceptions:
Implement fresh from tests. Period.
digraph tdd_cycle {
rankdir=LR;
red [label="RED\nWrite failing test", shape=box, style=filled, fillcolor="#ffcccc"];
verify_red [label="Verify fails\ncorrectly", shape=diamond];
green [label="GREEN\nMinimal code", shape=box, style=filled, fillcolor="#ccffcc"];
verify_green [label="Verify passes\nAll green", shape=diamond];
refactor [label="REFACTOR\nClean up", shape=box, style=filled, fillcolor="#ccccff"];
next [label="Next", shape=ellipse];
red -> verify_red;
verify_red -> green [label="yes"];
verify_red -> red [label="wrong\nfailure"];
green -> verify_green;
verify_green -> refactor [label="yes"];
verify_green -> green [label="no"];
refactor -> verify_green [label="stay\ngreen"];
verify_green -> next;
next -> red;
}
Write one minimal test showing what should happen.
<Good> ```typescript test('retries failed operations 3 times', async () => { let attempts = 0; const operation = () => { attempts++; if (attempts < 3) throw new Error('fail'); return 'success'; };const result = await retryOperation(operation);
expect(result).toBe('success'); expect(attempts).toBe(3); });
Clear name, tests real behavior, one thing
</Good>
<Bad>
```typescript
test('retry works', async () => {
const mock = jest.fn()
.mockRejectedValueOnce(new Error())
.mockRejectedValueOnce(new Error())
.mockResolvedValueOnce('success');
await retryOperation(mock);
expect(mock).toHaveBeenCalledTimes(3);
});
Vague name, tests mock not code </Bad>
Requirements:
MANDATORY. Never skip.
npm test path/to/test.test.ts
Confirm:
Test passes? You're testing existing behavior. Fix test.
Test errors? Fix error, re-run until it fails correctly.
Write simplest code to pass the test.
<Good> ```typescript async function retryOperation<T>(fn: () => Promise<T>): Promise<T> { for (let i = 0; i < 3; i++) { try { return await fn(); } catch (e) { if (i === 2) throw e; } } throw new Error('unreachable'); } ``` Just enough to pass </Good> <Bad> ```typescript async function retryOperation<T>( fn: () => Promise<T>, options?: { maxRetries?: number; backoff?: 'linear' | 'exponential'; onRetry?: (attempt: number) => void; } ): Promise<T> { // YAGNI } ``` Over-engineered </Bad>Don't add features, refactor other code, or "improve" beyond the test.
MANDATORY.
npm test path/to/test.test.ts
Confirm:
Test fails? Fix code, not test.
Other tests fail? Fix now.
After green only:
Keep tests green. Don't add behavior.
Next failing test for next feature.
| Quality | Good | Bad |
|---|---|---|
| Minimal | One thing. "and" in name? Split it. | test('validates email and domain and whitespace') |
| Clear | Name describes behavior | test('test1') |
| Shows intent | Demonstrates desired API | Obscures what code should do |
When writing or changing any test, read writing-good-tests.md for the rules that keep tests honest:
| Excuse | Reality |
|---|---|
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
| "I'll test after" | Tests written after pass immediately — which proves nothing. They may test the wrong thing, test the implementation instead of the behavior, or miss the edge case you forgot. You never watched it fail, so you never proved it can catch the bug. Test-first forces that failure. |
| "Tests after achieve same goals (spirit not ritual)" | Tests-after answer "what does this do?"; tests-first answer "what should this do?" Tests written after are biased by the code you already wrote — you verify the cases you remembered, not the ones you'd have discovered. Coverage without proof the tests work. |
| "Already manually tested" | Manual testing is ad-hoc: no record of what you covered, no way to re-run it when the code changes, easy to forget cases under pressure. "Worked when I tried it" ≠ comprehensive. Automated tests run the same way every time. |
| "Deleting X hours is wasteful" | Sunk cost fallacy — that time is already spent either way. The real choice: rewrite with TDD (high confidence) vs. keep it and bolt tests on after (low confidence, likely bugs). Keeping code you can't trust is the waste. |
| "Keep as reference, write tests first" | You'll adapt it. That's testing after. Delete means delete. |
| "Need to explore first" | Fine. Throw away exploration, start with TDD. |
| "Test hard = design unclear" | Listen to test. Hard to test = hard to use. |
| "TDD will slow me down" | TDD IS the pragmatic path: catches bugs before commit, prevents regressions, lets you refactor without fear. "Pragmatic" shortcuts mean debugging in production — slower, not faster. |
| "Manual test faster" | Manual doesn't prove edge cases. You'll re-test every change. |
| "Existing code has no tests" | You're improving it. Add tests for existing code. |
All of these mean: Delete code. Start over with TDD.
Bug: Empty email accepted
RED
test('rejects empty email', async () => {
const result = await submitForm({ email: '' });
expect(result.error).toBe('Email required');
});
Verify RED
$ npm test
FAIL: expected 'Email required', got undefined
GREEN
function submitForm(data: FormData) {
if (!data.email?.trim()) {
return { error: 'Email required' };
}
// ...
}
Verify GREEN
$ npm test
PASS
REFACTOR Extract validation for multiple fields if needed.
Before marking work complete:
Can't check all boxes? You skipped TDD. Start over.
| Problem | Solution |
|---|---|
| Don't know how to test | Write wished-for API. Write assertion first. Ask your human partner. |
| Test too complicated | Design too complicated. Simplify interface. |
| Must mock everything | Code too coupled. Use dependency injection. |
| Test setup huge | Extract helpers. Still complex? Simplify design. |
Bug found? Write failing test reproducing it. Follow TDD cycle. Test proves fix and prevents regression.
Never fix bugs without a test.
Production code → test exists and failed first
Otherwise → not TDD
No exceptions without your human partner's permission.
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You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
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Use when you have a written implementation plan to execute in a separate session with review checkpoints
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Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so the results will actually be interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger this even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.