Kiro AI IDE Project

A modern development environment with intelligent automation, spec-driven development, and comprehensive tooling.

Project Overview

This project demonstrates the capabilities of Kiro AI IDE-style development with:

• Spec-driven development using EARS format requirements
• Automated code review and quality assurance
• Intelligent test generation for multiple languages
• Security scanning and vulnerability detection
• Clean architecture patterns with functional programming

Quick Start

Prerequisites

• Python 3.9+
• pip (Python package manager)
• Git for version control

Setup

# Clone the repository  
git clone <repository-url>
cd fac-cli

# Install Python dependencies
pip install -r requirements.txt

# Configure Airtable credentials
cp .env.example .env
# Edit .env file with your Airtable API key and view URL

# Test the CLI
./fac.py help
./fac.py gr  # Fetch gateway recent data

Airtable Configuration

1. Get your Airtable API key from https://airtable.com/create/tokens
2. Navigate to your Airtable view and copy the URL (e.g., https://airtable.com/appEXAMPLE123456/tblEXAMPLE789012/viwEXAMPLE345678)
3. Add both to your .env file - the CLI automatically converts user-friendly URLs to API format

Project Structure

/
├── .kiro/                     # Kiro AI IDE configuration
│   ├── config.json           # Main configuration
│   ├── hooks/                # Automated development hooks
│   │   ├── code-review.sh    # Automated code review
│   │   ├── test-generator.sh # Test generation
│   │   └── security-scanner.sh # Security analysis
│   └── steering/             # Code generation standards
│       └── code-standards.md # Coding standards and patterns
├── src/                      # Source code (Clean Architecture)
│   ├── domain/              # Core business logic
│   ├── application/         # Use cases and orchestration
│   ├── infrastructure/      # External interfaces
│   └── presentation/        # User interfaces
├── tests/                   # Test files
├── docs/                    # Documentation
├── requirements.md          # EARS format requirements
├── design.md               # Architecture specification
├── tasks.md                # Implementation roadmap
└── README.md               # This file

Development Workflow

1. Spec-Driven Development

• Requirements are defined in requirements.md using EARS format
• Architecture is documented in design.md
• Implementation follows the roadmap in tasks.md

2. Automated Quality Assurance

# Run automated code review
.kiro/hooks/code-review.sh src/module.js

# Generate tests for new code
.kiro/hooks/test-generator.sh src/new-feature.py

# Run security scan
.kiro/hooks/security-scanner.sh .

3. Testing Strategy

• Test-Driven Development: Write failing tests first
• 90%+ Coverage: Comprehensive test coverage required
• Multiple Test Types: Unit, integration, and end-to-end tests
• Automated Generation: Tests auto-generated for new code

4. Code Quality Standards

• Functional Programming: Preferred over object-oriented patterns
• Pure Functions: Side-effect free when possible
• Immutable Data: Avoid mutation, use immutable structures
• Clean Architecture: Clear separation of concerns
• Security First: Built-in security scanning and best practices

Available Commands

# Development
npm run dev          # Start development server
npm run build        # Build for production
npm run test         # Run test suite
npm run test:watch   # Watch mode testing
npm run lint         # Code linting
npm run format       # Code formatting

# Quality Assurance
make review          # Run code review
make test-gen        # Generate missing tests
make security        # Security scan
make quality         # Full quality check

# Deployment
make deploy-staging  # Deploy to staging
make deploy-prod     # Deploy to production

Kiro AI IDE Features

Agent Hooks

Automated actions triggered by development events:

• Code Review: Intelligent analysis of code changes
• Test Generation: Automatic test creation for new code
• Security Scanning: Vulnerability detection and prevention
• Documentation: Auto-generated API docs and guides

Steering System

AI-guided development following established patterns:

• Architecture Patterns: Clean architecture, functional programming
• Naming Conventions: Consistent across languages and frameworks
• Quality Gates: Automated quality checks and enforcement
• Best Practices: Security, performance, and maintainability

Autonomous Behavior

Proactive development assistance:

• Context Awareness: Understanding of full codebase context
• Cross-File Refactoring: Intelligent code modifications
• Dependency Management: Automated dependency updates
• Performance Optimization: Proactive performance improvements

Architecture

This project follows Clean Architecture principles with clear separation of concerns:

• Domain Layer: Core business logic and rules
• Application Layer: Use cases and orchestration
• Infrastructure Layer: External dependencies and I/O
• Presentation Layer: User interfaces and APIs

Design Patterns

• Functional Programming: Immutable data, pure functions
• Dependency Injection: Loose coupling, testable code
• Repository Pattern: Data access abstraction
• Command Query Responsibility Segregation (CQRS): When applicable

Testing

Test Structure

tests/
├── unit/           # Fast, isolated tests
├── integration/    # Component interaction tests
├── e2e/           # End-to-end user scenarios
├── performance/   # Performance and load tests
└── security/      # Security-specific tests

Test Standards

• Arrange-Act-Assert: Clear test structure
• Descriptive Names: Test names should read like specifications
• Edge Cases: Comprehensive edge case coverage
• Error Scenarios: Test error handling and recovery

Security

Built-in Security Features

• Input Validation: All inputs validated and sanitised
• Secret Management: No hardcoded secrets, environment variables used
• Secure Communications: HTTPS/TLS for all network traffic
• Dependency Scanning: Regular vulnerability scans
• Access Control: Role-based permissions where applicable

Security Practices

• Regular security scans using .kiro/hooks/security-scanner.sh
• Automated dependency vulnerability checks
• Code review for security implications
• Penetration testing for critical components

Performance

Performance Targets

• API Response Time: < 100ms (95th percentile)
• Page Load Time: < 2 seconds first contentful paint
• Test Suite Runtime: < 30 seconds full suite
• Build Time: < 60 seconds production build

Optimization Strategies

• Caching at multiple levels
• Database query optimization
• Code splitting and lazy loading
• Performance monitoring and alerting

Contributing

Development Process

1. Review Requirements: Check requirements.md for current specifications
2. Follow Architecture: Adhere to patterns in design.md
3. Write Tests First: Test-driven development required
4. Run Quality Checks: Use automated hooks for review
5. Update Documentation: Keep docs synchronized with code

Code Review Checklist

• Follows coding standards in .kiro/steering/code-standards.md
• Includes comprehensive tests (90%+ coverage)
• Passes security scan
• Updates relevant documentation
• Follows conventional commit messages

Monitoring and Observability

Metrics Collection

• Application performance metrics
• Business intelligence metrics
• Infrastructure and system metrics
• User experience metrics

Logging Strategy

• Structured logging (JSON format)
• Correlation IDs for request tracing
• Appropriate log levels (ERROR, WARN, INFO, DEBUG)
• No sensitive data in logs

Deployment

Environments

• Development: Local development with hot reload
• Testing: Automated CI/CD testing environment
• Staging: Production-like integration testing
• Production: Live system with full monitoring

Deployment Strategy

• Blue-green deployments for zero downtime
• Feature flags for gradual rollouts
• Automated rollback capabilities
• Health checks and monitoring

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For questions, issues, or contributions:

• Review the documentation in /docs
• Check the issue tracker
• Follow the contributing guidelines
• Contact the development team

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This project demonstrates advanced development practices using Kiro AI IDE-style automation and intelligent development workflows.