tdd-guide
Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation
Best use case
tdd-guide is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation
Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "tdd-guide" skill to help with this workflow task. Context: Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/tdd-guide/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How tdd-guide Compares
| Feature / Agent | tdd-guide | 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?
Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation
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.
SKILL.md Source
# 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
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