tdd-guide

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