Test-driven development workflow with philosophy guide - plan → write tests → implement → validate
npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill tdd
Strict TDD workflow: tests first, then implementation.
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.
NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST
Write code before the test? Delete it. Start over.
No exceptions:
Implement fresh from tests. Period.
Write one minimal test showing what should happen.
Good:
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.
Bad:
test('retry works', async () => {
const mock = jest.fn()
.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
# or
pytest path/to/test_file.py
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:
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.
Bad:
async function retryOperation<T>(
fn: () => Promise<T>,
options?: {
maxRetries?: number;
backoff?: 'linear' | 'exponential';
onRetry?: (attempt: number) => void;
}
): Promise<T> {
// YAGNI - over-engineered
}
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.
| 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. |
All of these mean: Delete code. Start over with TDD.
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. |
┌────────────┐ ┌──────────┐ ┌──────────┐ ┌───────────┐
│ plan- │───▶│ arbiter │───▶│ kraken │───▶│ arbiter │
│ agent │ │ │ │ │ │ │
└────────────┘ └──────────┘ └──────────┘ └───────────┘
Design Write Implement Verify
approach failing minimal all tests
tests code pass
| # | Agent | Role | Output |
|---|-------|------|--------|
| 1 | plan-agent | Design test cases and implementation approach | Test plan |
| 2 | arbiter | Write failing tests (RED phase) | Test files |
| 3 | kraken | Implement minimal code to pass (GREEN phase) | Implementation |
| 4 | arbiter | Run all tests, verify nothing broken | Test report |
NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST
Each agent follows the TDD contract:
Task(
subagent_type="plan-agent",
prompt="""
Design TDD approach for: [FEATURE_NAME]
Define:
1. What behaviors need to be tested
2. Edge cases to cover
3. Expected test structure
DO NOT write any implementation code.
Output: Test plan document
"""
)
Task(
subagent_type="arbiter",
prompt="""
Write failing tests for: [FEATURE_NAME]
Test plan: [from phase 1]
Requirements:
- Write tests FIRST
- Run tests to confirm they FAIL
- Tests must fail because feature is missing (not syntax errors)
- Create clear test names describing expected behavior
DO NOT write any implementation code.
"""
)
Task(
subagent_type="kraken",
prompt="""
Implement MINIMAL code to pass tests: [FEATURE_NAME]
Tests location: [test file path]
Requirements:
- Write ONLY enough code to make tests pass
- No additional features beyond what tests require
- No "improvements" or "enhancements"
- Run tests after each change
Follow Red-Green-Refactor strictly.
"""
)
Task(
subagent_type="arbiter",
prompt="""
Validate TDD implementation: [FEATURE_NAME]
- Run full test suite
- Verify all new tests pass
- Verify no existing tests broke
- Check test coverage if available
"""
)
User: /tdd Add email validation to the signup form
Claude: Starting /tdd workflow for email validation...
Phase 1: Planning test cases...
[Spawns plan-agent]
Test plan:
- Valid email formats
- Invalid email formats
- Empty email rejection
- Edge cases (unicode, long emails)
Phase 2: Writing failing tests (RED)...
[Spawns arbiter]
✅ 8 tests written, all failing as expected
Phase 3: Implementing minimal code (GREEN)...
[Spawns kraken]
✅ All 8 tests now passing
Phase 4: Validating...
[Spawns arbiter]
✅ 247 tests passing (8 new), 0 failing
TDD workflow complete!
After GREEN, you can add a refactor phase:
Task(
subagent_type="kraken",
prompt="""
Refactor: [FEATURE_NAME]
- Clean up code while keeping tests green
- Remove duplication
- Improve naming
- Extract helpers if needed
DO NOT add new behavior. Keep all tests passing.
"""
)
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when implementing any feature or bugfix, before writing implementation code
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Take parcadei/tdd from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.