ac-tdd-runner
Run TDD cycle for feature implementation. Use when implementing features with RED-GREEN-REFACTOR, running test-driven development, automating TDD workflow, or ensuring test-first development.
Best use case
ac-tdd-runner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Run TDD cycle for feature implementation. Use when implementing features with RED-GREEN-REFACTOR, running test-driven development, automating TDD workflow, or ensuring test-first development.
Teams using ac-tdd-runner should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ac-tdd-runner/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ac-tdd-runner Compares
| Feature / Agent | ac-tdd-runner | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Run TDD cycle for feature implementation. Use when implementing features with RED-GREEN-REFACTOR, running test-driven development, automating TDD workflow, or ensuring test-first development.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# AC TDD Runner
Automate the Test-Driven Development cycle for feature implementation.
## Purpose
Enforces the RED-GREEN-REFACTOR cycle, ensuring all features are implemented with test-first methodology for quality and maintainability.
## Quick Start
```python
from scripts.tdd_runner import TDDRunner
runner = TDDRunner(project_dir)
result = await runner.run_cycle(feature)
```
## TDD Cycle
### RED Phase
Write failing tests first:
```python
red_result = await runner.red_phase(feature)
# Creates test file with failing tests
# Verifies tests actually fail
```
### GREEN Phase
Implement minimum code to pass:
```python
green_result = await runner.green_phase(feature)
# Implements code
# Runs tests until all pass
# Minimum necessary implementation
```
### REFACTOR Phase
Clean up while tests pass:
```python
refactor_result = await runner.refactor_phase(feature)
# Improve code structure
# Ensure tests still pass
# Apply coding standards
```
## Cycle Result
```json
{
"feature_id": "auth-001",
"cycle_complete": true,
"phases": {
"red": {
"success": true,
"tests_created": 5,
"all_tests_fail": true
},
"green": {
"success": true,
"iterations": 3,
"all_tests_pass": true
},
"refactor": {
"success": true,
"changes_made": ["extracted_helper", "renamed_variable"],
"tests_still_pass": true
}
},
"coverage": 92.5,
"duration_ms": 120000
}
```
## RED Phase Details
1. Generate test file from feature test_cases
2. Write test functions with proper structure
3. Run tests to verify they fail
4. If tests pass unexpectedly, add more specific assertions
## GREEN Phase Details
1. Analyze failing tests
2. Write minimum implementation
3. Run tests
4. If tests fail, iterate on implementation
5. Stop when all tests pass
## REFACTOR Phase Details
1. Identify code smells
2. Apply refactoring patterns
3. Run tests after each change
4. Revert if tests fail
5. Continue until code is clean
## Configuration
```json
{
"max_green_iterations": 10,
"coverage_threshold": 80,
"refactoring_patterns": [
"extract_method",
"rename_for_clarity",
"remove_duplication"
],
"test_framework": "pytest"
}
```
## Integration
- Uses: `ac-test-generator` for RED phase
- Uses: `ac-criteria-validator` for GREEN verification
- Reports to: `ac-task-executor`
## API Reference
See `scripts/tdd_runner.py` for full implementation.Related Skills
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