improved-sdd 0.1.4

Setup tool for Improved Spec-Driven Development projects with AI assistant templates and GitLab Flow integration

Improved-SDD

A GitHub Copilot Studio project with Improved Spec-Driven Development templates for building high-quality Python CLI applications.

Features

• Spec-Driven Development: Structured approach to software development with comprehensive specifications
• GitLab Flow Integration: Built-in workflow guidance with automatic commit prompts and PR creation
• Python CLI Framework: Built with Typer and Rich for modern, beautiful command-line interfaces
• Automated Code Quality: Pre-commit hooks with Flake8, Black, isort, and mypy
• GitHub Copilot Integration: Custom templates and instructions for AI-assisted development
• CI/CD Ready: GitHub Actions workflow for automated testing and linting
• Cross-Platform: Works on Windows, macOS, and Linux

Quick Start

1. Clone the repository

   git clone <repository-url>
   cd improved-sdd
   

2. Install dependencies

   pip install -r requirements.txt
   

3. Set up development environment

   pip install pre-commit
   pre-commit install
   

4. Open in VS Code and start developing with GitHub Copilot using the provided templates

Usage

CLI Commands

The project includes a CLI tool for managing spec-driven development projects:

# Initialize a new project with GitLab Flow (default)
python src/improved_sdd_cli.py init <project-name>

# Initialize without GitLab Flow integration
python src/improved_sdd_cli.py init <project-name> --no-gitlab-flow

# Delete a project (with confirmation)
python src/improved_sdd_cli.py delete <project-name>

# Check project configuration
python src/improved_sdd_cli.py check <project-name>

# Get help
python src/improved_sdd_cli.py --help

Development Workflow

1. Create a specification in specs/
2. Use the CLI to initialize your project structure
3. Develop following the spec-driven approach
4. Commit changes (linting runs automatically)

GitLab Flow Integration

The improved-sdd CLI includes built-in GitLab Flow support that provides workflow guidance during spec development:

Automatic Workflow Integration

• Setup Guidance: Branch creation and repository validation before starting specs
• Phase Commit Prompts: Commit guidance after completing each spec phase (feasibility, requirements, design, tasks)
• PR Creation: Step-by-step PR creation guidance after implementation completion
• Platform-Specific Commands: Windows PowerShell vs Unix/macOS bash command syntax

How It Works

GitLab Flow uses a dynamic keyword integration approach:

1. Markdown Files as Variables: GitLab Flow content stored in templates/gitlab-flow/*.md files
2. Keyword Replacement: Keywords like {GITLAB_FLOW_SETUP}, {GITLAB_FLOW_COMMIT}, {GITLAB_FLOW_PR} in chatmode files
3. Conditional Loading: Keywords replaced with GitLab Flow content when enabled, empty when disabled
4. Platform Detection: Commands automatically adjusted for Windows vs Unix systems

CLI Flag Control

# Enable GitLab Flow (default behavior)
python src/improved_sdd_cli.py init my-project --gitlab-flow

# Disable GitLab Flow
python src/improved_sdd_cli.py init my-project --no-gitlab-flow

Example Workflow

1. Project Initialization: improved-sdd init my-feature --gitlab-flow
2. Branch Setup: Follow GitLab Flow setup guidance in chatmode
3. Spec Development: Complete feasibility → requirements → design → tasks
4. Automatic Commits: Commit after each phase using provided guidance
5. Implementation: Execute tasks with commit prompts between tasks
6. PR Creation: Create pull request when all implementation complete

GitLab Flow Templates

The system includes three core templates:

• gitlab-flow-setup.md: Repository validation and branch creation
• gitlab-flow-commit.md: Phase completion commit guidance with conventional commit format
• gitlab-flow-pr.md: PR creation with timing safeguards and templates

Benefits

• ✅ Integrated Workflow: Git operations embedded naturally in spec development
• ✅ Zero Breaking Changes: Existing workflows unchanged when disabled
• ✅ Platform Agnostic: Works on Windows, macOS, and Linux
• ✅ Flexible Control: Easy to enable/disable via CLI flag
• ✅ Best Practices: Conventional commits and proper PR timing

Development Setup

Prerequisites

• Python 3.8 or higher
• VS Code with Python extension
• Git

Installation

1. Clone the repository

2. Install dependencies:

   pip install -r requirements.txt
   

3. Install pre-commit hooks:

   pip install pre-commit
   pre-commit install
   

Code Quality Tools

This project uses comprehensive linting and formatting tools:

Automatic Linting (Pre-commit Hooks)

Pre-commit hooks run automatically on each commit. Install them with:

pre-commit install

Run manually on all files:

pre-commit run --all-files

Manual Tools

# Style guide enforcement
flake8 src/ --max-line-length=120

# Code formatting
black src/

# Import sorting
isort src/ --profile=black

# Type checking
mypy src/

VS Code Integration

The project includes optimized VS Code settings for:

• Real-time linting with Flake8
• Automatic formatting with Black on save
• Import sorting
• 120-character line ruler

CI/CD

GitHub Actions automatically runs quality checks on:

• Pushes to main/develop branches
• Pull requests

Project Structure

improved-sdd/
├── src/                    # Source code
├── specs/                  # Project specifications
├── templates/              # Development templates
│   ├── chatmodes/         # AI behavior patterns
│   ├── instructions/      # Development guidance
│   ├── prompts/           # Structured AI prompts
│   └── gitlab-flow/       # GitLab Flow workflow templates
├── memory/                 # Project memory and constitution
├── .github/                # GitHub templates and workflows
├── requirements.txt        # Python dependencies
├── pyproject.toml         # Project configuration
├── .pre-commit-config.yaml # Pre-commit hooks
└── .flake8                # Linting configuration

Templates Available

• Chatmodes: AI behavior patterns for different development scenarios
• Instructions: Context-specific development guidance
• Prompts: Structured prompts for AI interactions
• GitLab Flow: Workflow templates for git operations and branch management

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Make your changes and ensure tests pass
4. Commit with pre-commit hooks: git commit -m "Add your feature"
5. Push to your branch: git push origin feature/your-feature
6. Create a Pull Request

Development Guidelines

• Follow the spec-driven development approach
• Write clear, documented code
• Use type hints for better code quality
• Run pre-commit hooks before committing
• Update specifications for new features

Resources

• Typer Documentation
• Rich Documentation
• CLI Guidelines
• Python CLI Development Guide

License

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