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test-driven-development
Use when implementing any feature or bugfix, before writing implementation code
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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Use when implementing any feature or bugfix, before writing implementation code
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Systematically identify what's missing, unknown, or needs investigation before making changes or decisions. Use proactively when proposing features, implementing changes, or making technical decisions to ensure all critical areas are covered. This skill catches overlooked dependencies, edge cases, and integration points before they become problems. Examples: - "Implement user authentication" → trigger gap analysis (what's the current auth system?) - "Add caching to API" → trigger gap analysis (what caching infrastructure exists?) - "Migrate to TypeScript" → trigger gap analysis (what's the build pipeline?) - "Refactor this module" → trigger gap analysis (what depends on this module?) - "Add new API endpoint" → trigger gap analysis (what endpoints exist, what patterns?)
Detect ambiguous or underspecified research requests and guide through structured clarification questions before executing any research. Use proactively when user requests are vague, lack specificity, missing context, or have unclear goals. This skill prevents wasted research by ensuring intent is crystal clear before any web searches, file reads, or data gathering. Examples: - "Research the codebase" → ❌ Too vague, trigger clarification - "Why is this slow?" → ❌ Missing context (what is "this"?), trigger clarification - "Add a feature" → ❌ Not research, this is implementation - "Investigate authentication flow" → ❌ What specifically about it? Trigger clarification - "Compare React and Vue" → ✅ Specific enough, but still validate dimensions
Evaluate requests, proposals, or decisions from multiple dimensions (technical, business, UX, security, performance, maintainability, etc.) to ensure holistic understanding before proceeding. Use proactively when making technical decisions, choosing solutions, or proposing changes. This skill prevents single-minded thinking and uncovers trade-offs, risks, and opportunities across all relevant aspects. Examples: - "Use Redis for caching" → assess multiple aspects (performance, cost, complexity, ops) - "Add AI to our app" → assess aspects (technical feasibility, user experience, data privacy) - "Refactor to microservices" → assess aspects (benefits, costs, migration complexity, team readiness) - "Implement authentication" → assess aspects (security, UX, integration effort, maintenance) - "Switch to React 19" → assess aspects (benefits, migration cost, breaking changes, learning curve)
Choose the right OpenCode primitive (Command, Skill, Tool, Prompt, CustomTool, Plugin hook) for a given task or workflow. Use proactively when deciding which OpenCode capability to use, or when trying to understand what's available. This skill maps research and development needs to appropriate OpenCode mechanisms, ensuring optimal use of the platform's capabilities. Examples: - "How do I search the codebase?" → select tool (read/grep) - "I need a reusable workflow for feature development" → select command - "How do I intercept file writes?" → select plugin hook - "What primitive should I use for systematic debugging?" → select skill - "I need a custom tool for X" → select CustomTool (if innate tools insufficient)
Create structured, executable research plans with clear phases, checkpoints, and validation criteria. Use proactively when research intent is clear but execution plan is missing. This skill transforms research goals into actionable workflows with defined deliverables, time estimates, and success metrics, ensuring research is systematic and produces useful outputs. Examples: - "Research how to add OAuth" (intent clear, need plan) → trigger workflow planner - "Investigate performance bottlenecks" (intent clear, need plan) → trigger workflow planner - "Analyze codebase architecture" (intent clear, need plan) → trigger workflow planner - "Find best practices for X" (intent clear, need plan) → trigger workflow planner - "Compare technology options" (intent clear, need plan) → trigger workflow planner
| name | test-driven-development |
| description | Use when implementing any feature or bugfix, before writing implementation code |
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.
```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
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.
```typescript async function retryOperation(fn: () => Promise): Promise { 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 ```typescript async function retryOperation( fn: () => Promise, options?: { maxRetries?: number; backoff?: 'linear' | 'exponential'; onRetry?: (attempt: number) => void; } ): Promise { // YAGNI } ``` Over-engineeredDon'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 |
"I'll write tests after to verify it works"
Tests written after code pass immediately. Passing immediately proves nothing:
Test-first forces you to see the test fail, proving it actually tests something.
"I already manually tested all the edge cases"
Manual testing is ad-hoc. You think you tested everything but:
Automated tests are systematic. They run the same way every time.
"Deleting X hours of work is wasteful"
Sunk cost fallacy. The time is already gone. Your choice now:
The "waste" is keeping code you can't trust. Working code without real tests is technical debt.
"TDD is dogmatic, being pragmatic means adapting"
TDD IS pragmatic:
"Pragmatic" shortcuts = debugging in production = slower.
"Tests after achieve the same goals - it's spirit not ritual"
No. Tests-after answer "What does this do?" Tests-first answer "What should this do?"
Tests-after are biased by your implementation. You test what you built, not what's required. You verify remembered edge cases, not discovered ones.
Tests-first force edge case discovery before implementing. Tests-after verify you remembered everything (you didn't).
30 minutes of tests after ≠ TDD. You get coverage, lose proof tests work.
| Excuse | Reality |
|---|---|
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
| "I'll test after" | Tests passing immediately prove nothing. |
| "Tests after achieve same goals" | Tests-after = "what does this do?" Tests-first = "what should this do?" |
| "Already manually tested" | Ad-hoc ≠ systematic. No record, can't re-run. |
| "Deleting X hours is wasteful" | Sunk cost fallacy. Keeping unverified code is technical debt. |
| "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 faster than debugging. Pragmatic = test-first. |
| "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.
When adding mocks or test utilities, read @testing-anti-patterns.md to avoid common pitfalls:
Production code → test exists and failed first
Otherwise → not TDD
No exceptions without your human partner's permission.