home / skills / alirezarezvani / claude-skills / tdd-guide

This skill enables intelligent test generation, coverage analysis, and multi-framework TDD guidance to accelerate robust software delivery.

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---
name: tdd-guide
description: Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation
---

# TDD Guide - Test Driven Development for Engineering Teams

A comprehensive Test Driven Development skill that provides intelligent test generation, coverage analysis, framework integration, and TDD workflow guidance across multiple languages and testing frameworks.

## Capabilities

### Test Generation
- **Generate Test Cases from Requirements**: Convert user stories, API specs, and business requirements into executable test cases
- **Create Test Stubs**: Generate test function scaffolding with proper naming, imports, and setup/teardown
- **Generate Test Fixtures**: Create realistic test data, mocks, and fixtures for various scenarios

### TDD Workflow Support
- **Guide Red-Green-Refactor**: Step-by-step guidance through TDD cycles with validation
- **Suggest Missing Scenarios**: Identify untested edge cases, error conditions, and boundary scenarios
- **Review Test Quality**: Analyze test isolation, assertions quality, naming conventions, and maintainability

### Coverage & Metrics Analysis
- **Calculate Coverage**: Parse LCOV, JSON, and XML coverage reports for line/branch/function coverage
- **Identify Untested Paths**: Find code paths, branches, and error handlers without test coverage
- **Recommend Improvements**: Prioritized recommendations (P0/P1/P2) for coverage gaps and test quality

### Framework Integration
- **Multi-Framework Support**: Jest, Pytest, JUnit, Vitest, Mocha, RSpec adapters
- **Generate Boilerplate**: Create test files with proper imports, describe blocks, and best practices
- **Configure Test Runners**: Set up test configuration, coverage tools, and CI integration

### Comprehensive Metrics
- **Test Coverage**: Line, branch, function coverage with gap analysis
- **Code Complexity**: Cyclomatic complexity, cognitive complexity, testability scoring
- **Test Quality**: Assertions per test, isolation score, naming quality, test smell detection
- **Test Data**: Boundary value analysis, edge case identification, mock data generation
- **Test Execution**: Timing analysis, slow test detection, flakiness detection
- **Missing Tests**: Uncovered edge cases, error handling gaps, missing integration scenarios

## Input Requirements

The skill supports **automatic format detection** for flexible input:

### Source Code
- **Languages**: TypeScript, JavaScript, Python, Java
- **Format**: Direct file paths or copy-pasted code blocks
- **Detection**: Automatic language/framework detection from syntax and imports

### Test Artifacts
- **Coverage Reports**: LCOV (.lcov), JSON (coverage-final.json), XML (cobertura.xml)
- **Test Results**: JUnit XML, Jest JSON, Pytest JSON, TAP format
- **Format**: File paths or raw coverage data

### Requirements (Optional)
- **User Stories**: Text descriptions of functionality
- **API Specifications**: OpenAPI/Swagger, REST endpoints, GraphQL schemas
- **Business Requirements**: Acceptance criteria, business rules

### Input Methods
- **Option A**: Provide file paths (skill will read files)
- **Option B**: Copy-paste code/data directly
- **Option C**: Mix of both (automatically detected)

## Output Formats

The skill provides **context-aware output** optimized for your environment:

### Code Files
- **Test Files**: Generated tests (Jest/Pytest/JUnit/Vitest) with proper structure
- **Fixtures**: Test data files, mock objects, factory functions
- **Mocks**: Mock implementations, stub functions, test doubles

### Reports
- **Markdown**: Rich coverage reports, recommendations, quality analysis (Claude Desktop)
- **JSON**: Machine-readable metrics, structured data for CI/CD integration
- **Terminal-Friendly**: Simplified output for Claude Code CLI

### Smart Defaults
- **Desktop/Apps**: Rich markdown with tables, code blocks, visual hierarchy
- **CLI**: Concise, terminal-friendly format with clear sections
- **CI/CD**: JSON output for automated processing

### Progressive Disclosure
- **Summary First**: High-level overview (<200 tokens)
- **Details on Demand**: Full analysis available (500-1000 tokens)
- **Prioritized**: P0 (critical) → P1 (important) → P2 (nice-to-have)

## How to Use

### Basic Usage
```
@tdd-guide

I need tests for my authentication module. Here's the code:
[paste code or provide file path]

Generate comprehensive test cases covering happy path, error cases, and edge cases.
```

### Coverage Analysis
```
@tdd-guide

Analyze test coverage for my TypeScript project. Coverage report: coverage/lcov.info

Identify gaps and provide prioritized recommendations.
```

### TDD Workflow
```
@tdd-guide

Guide me through TDD for implementing a password validation function.

Requirements:
- Min 8 characters
- At least 1 uppercase, 1 lowercase, 1 number, 1 special char
- No common passwords
```

### Multi-Framework Support
```
@tdd-guide

Convert these Jest tests to Pytest format:
[paste Jest tests]
```

## Scripts

### Core Modules

- **test_generator.py**: Intelligent test case generation from requirements and code
- **coverage_analyzer.py**: Parse and analyze coverage reports (LCOV, JSON, XML)
- **metrics_calculator.py**: Calculate comprehensive test and code quality metrics
- **framework_adapter.py**: Multi-framework adapter (Jest, Pytest, JUnit, Vitest)
- **tdd_workflow.py**: Red-green-refactor workflow guidance and validation
- **fixture_generator.py**: Generate realistic test data and fixtures
- **format_detector.py**: Automatic language and framework detection

### Utilities

- **complexity_analyzer.py**: Cyclomatic and cognitive complexity analysis
- **test_quality_scorer.py**: Test quality scoring (isolation, assertions, naming)
- **missing_test_detector.py**: Identify untested paths and missing scenarios
- **output_formatter.py**: Context-aware output formatting (Desktop vs CLI)

## Best Practices

### Test Generation
1. **Start with Requirements**: Write tests from user stories before seeing implementation
2. **Test Behavior, Not Implementation**: Focus on what code does, not how it does it
3. **One Assertion Focus**: Each test should verify one specific behavior
4. **Descriptive Names**: Test names should read like specifications

### TDD Workflow
1. **Red**: Write failing test first
2. **Green**: Write minimal code to make it pass
3. **Refactor**: Improve code while keeping tests green
4. **Repeat**: Small iterations, frequent commits

### Coverage Goals
1. **Aim for 80%+**: Line coverage baseline for most projects
2. **100% Critical Paths**: Authentication, payments, data validation must be fully covered
3. **Branch Coverage Matters**: Line coverage alone is insufficient
4. **Don't Game Metrics**: Focus on meaningful tests, not coverage numbers

### Test Quality
1. **Independent Tests**: Each test should run in isolation
2. **Fast Execution**: Keep unit tests under 100ms each
3. **Deterministic**: Tests should always produce same results
4. **Clear Failures**: Assertion messages should explain what went wrong

### Framework Selection
1. **Jest**: JavaScript/TypeScript projects (React, Node.js)
2. **Pytest**: Python projects (Django, Flask, FastAPI)
3. **JUnit**: Java projects (Spring, Android)
4. **Vitest**: Modern Vite-based projects

## Multi-Language Support

### TypeScript/JavaScript
- Frameworks: Jest, Vitest, Mocha, Jasmine
- Runners: Node.js, Karma, Playwright
- Coverage: Istanbul/nyc, c8

### Python
- Frameworks: Pytest, unittest, nose2
- Runners: pytest, tox, nox
- Coverage: coverage.py, pytest-cov

### Java
- Frameworks: JUnit 5, TestNG, Mockito
- Runners: Maven Surefire, Gradle Test
- Coverage: JaCoCo, Cobertura

## Limitations

### Scope
- **Unit Tests Focus**: Primarily optimized for unit tests (integration tests require different patterns)
- **Static Analysis Only**: Cannot execute tests or measure actual code behavior
- **Language Support**: Best support for TypeScript, JavaScript, Python, Java (other languages limited)

### Coverage Analysis
- **Report Dependency**: Requires existing coverage reports (cannot generate coverage from scratch)
- **Format Support**: LCOV, JSON, XML only (other formats need conversion)
- **Interpretation Context**: Coverage numbers need human judgment for meaningfulness

### Test Generation
- **Baseline Quality**: Generated tests provide scaffolding, require human review and refinement
- **Complex Logic**: Advanced business logic and integration scenarios need manual test design
- **Mocking Strategy**: Mock/stub strategies should align with project patterns

### Framework Integration
- **Configuration Required**: Test runners need proper setup (this skill doesn't modify package.json or pom.xml)
- **Version Compatibility**: Generated code targets recent stable versions (Jest 29+, Pytest 7+, JUnit 5+)

### When NOT to Use This Skill
- **E2E Testing**: Use dedicated E2E tools (Playwright, Cypress, Selenium)
- **Performance Testing**: Use JMeter, k6, or Locust
- **Security Testing**: Use OWASP ZAP, Burp Suite, or security-focused tools
- **Manual Testing**: Some scenarios require human exploratory testing

## Example Workflows

### Workflow 1: Generate Tests from Requirements
```
Input: User story + API specification
Process: Parse requirements → Generate test cases → Create test stubs
Output: Complete test files ready for implementation
```

### Workflow 2: Improve Coverage
```
Input: Coverage report + source code
Process: Identify gaps → Suggest tests → Generate test code
Output: Prioritized test cases for uncovered code
```

### Workflow 3: TDD New Feature
```
Input: Feature requirements
Process: Guide red-green-refactor → Validate each step → Suggest refactorings
Output: Well-tested feature with clean code
```

### Workflow 4: Framework Migration
```
Input: Tests in Framework A
Process: Parse tests → Translate patterns → Generate equivalent tests
Output: Tests in Framework B with same coverage
```

## Integration Points

### CI/CD Integration
- Parse coverage reports from CI artifacts
- Generate coverage badges and reports
- Fail builds on coverage thresholds
- Track coverage trends over time

### IDE Integration
- Generate tests for selected code
- Run coverage analysis on save
- Highlight untested code paths
- Quick-fix suggestions for test gaps

### Code Review
- Validate test coverage in PRs
- Check test quality standards
- Identify missing test scenarios
- Suggest improvements before merge

## Version Support

- **Node.js**: 16+ (Jest 29+, Vitest 0.34+)
- **Python**: 3.8+ (Pytest 7+)
- **Java**: 11+ (JUnit 5.9+)
- **TypeScript**: 4.5+

## Related Skills

This skill works well with:
- **code-review**: Validate test quality during reviews
- **refactoring-assistant**: Maintain tests during refactoring
- **ci-cd-helper**: Integrate coverage in pipelines
- **documentation-generator**: Generate test documentation

Overview

This skill is a practical Test Driven Development (TDD) guide and toolkit for engineering subagents. It provides intelligent test generation, multi-framework support, coverage analysis, and step-by-step TDD workflow guidance to help teams produce high-quality, well-tested code. The outputs include ready-to-run test scaffolding, prioritized coverage recommendations, and machine-readable metrics for CI integration.

How this skill works

The skill inspects source code, test artifacts, and requirements to generate and evaluate tests. It parses code in TypeScript, JavaScript, Python, and Java, reads LCOV/JSON/XML coverage reports, and maps uncovered paths to concrete test cases. It can produce test files, fixtures, and JSON reports or human-friendly markdown summaries, and it guides developers through red-green-refactor iterations with suggested assertions and edge cases.

When to use it

  • Starting a new feature where tests should be written before implementation (TDD).
  • Improving test coverage using existing coverage reports (LCOV, JSON, XML).
  • Generating test scaffolding and realistic fixtures for unit test suites.
  • Migrating tests between frameworks (e.g., Jest → Pytest, JUnit → Pytest).
  • Reviewing test quality in pull requests or preparing CI coverage gates.

Best practices

  • Begin with user stories or API specs so tests express behavior, not implementation.
  • Keep tests small and focused — one assertion per behavior where practical.
  • Prioritize P0 critical paths (auth, payments) for 100% coverage; aim 80%+ otherwise.
  • Prefer deterministic, fast unit tests; isolate external dependencies with mocks.
  • Validate generated tests before trusting them: refine fixtures and edge cases manually.

Example use cases

  • Convert an authentication requirement into a suite of Pytest tests with fixtures and negative cases.
  • Analyze a TypeScript project's lcov.info and produce prioritized P0/P1/P2 test tasks for CI.
  • Translate a collection of Jest tests into equivalent Pytest files for a Python port.
  • Drive TDD for a password validator: produce failing tests, minimal passing implementation, and suggested refactors.
  • Generate mocks and factory fixtures for services to speed unit-test coverage improvements.

FAQ

Can this skill execute tests or measure runtime behavior?

No — the skill performs static analysis and generates tests/interpretations; it cannot run tests or measure live behavior.

What coverage formats are supported?

LCOV, coverage JSON (coverage-final.json), and XML (Cobertura) are supported for coverage analysis.

Which test frameworks are supported?

Multi-framework adapters include Jest, Vitest, Mocha, Pytest, unittest, and JUnit, with boilerplate generation for each.