Intelligent assistant for project analysis and documentation using AI
Project description
ProjectPrompt
ProjectPrompt is an intelligent CLI tool that analyzes code projects and provides AI-powered insights, documentation generation, and improvement suggestions. It helps developers understand their codebase structure, generate contextual prompts, and maintain better project documentation.
✨ Key Features
- 🔍 Smart Project Analysis: Automatically detects technologies, frameworks, and project structure
- 🤖 AI-Powered Insights: Integration with Anthropic Claude and OpenAI for intelligent code analysis
- 📋 AI Rules Generation: Automatically generate development rules based on project patterns and best practices
- 📊 Visual Dashboards: Generate comprehensive project dashboards in HTML or Markdown
- 🔗 Dependency Analysis: Advanced dependency mapping with functional groups
- 🌐 Multi-Language Support: Python, JavaScript, TypeScript, Java, C++, and more
- ⚡ Offline Capable: Core features work without internet, AI features require API keys
- 📋 Progress Tracking: Track development progress across project phases
- 🎯 Contextual Prompts: Generate targeted prompts for specific functionalities
🚀 Quick Start
Installation
pip install projectprompt
Verify Installation
project-prompt version
Basic Usage
# Analyze your current project
project-prompt analyze
# Generate a project dashboard
project-prompt dashboard
# Get help with all commands
project-prompt help
📖 Installation Guide
Prerequisites
- Python 3.8 or higher
- pip package manager
Standard Installation
pip install projectprompt
Development Installation
git clone https://github.com/Dixter999/project-prompt.git
cd project-prompt
pip install -r requirements.txt
Troubleshooting Installation
If you encounter command not found errors:
For zsh users:
echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.zshrc
source ~/.zshrc
For bash users:
echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.bashrc
source ~/.bashrc
Alternative: Run via Python module
python -m src.main version
Create convenient alias
echo 'alias pp="project-prompt"' >> ~/.zshrc
source ~/.zshrc
# Now use: pp analyze, pp dashboard, etc.
🎯 What to Expect
When you run ProjectPrompt on your project, you can expect:
Immediate Results
- Project structure analysis with file counts and organization
- Technology detection for languages, frameworks, and tools
- Basic dependency mapping showing relationships between files
- Code quality metrics including complexity analysis
With AI APIs Configured
- Intelligent insights about your codebase architecture
- Improvement suggestions tailored to your project
- Code explanations for complex functions
- Refactoring recommendations with best practices
Premium Features
- Advanced dashboards with interactive visualizations
- Comprehensive dependency analysis with functional groupings
- Implementation assistants for new features
- Progress tracking across development phases
🗺️ Interactive Command Mind Map
Explore our comprehensive Command Mind Map - a visual overview of all 35+ verified commands organized by category. This interactive diagram helps you discover functionality and understand command relationships.
🎯 How to View the Interactive Mind Map
Option 1: VS Code Extension (Recommended)
# Install the Markmap extension in VS Code
code --install-extension gera2ld.markmap-vscode
# Then open docs/COMMAND_MINDMAP.md in VS Code
Option 2: Online Viewer
- Copy the content from docs/COMMAND_MINDMAP.md
- Paste it into the Markmap REPL
- Enjoy the interactive navigation!
Option 3: Quick Command Reference For a text-based overview, see the Command Reference section below.
🛠️ Command Reference
Core Commands
| Command | Description | Example |
|---|---|---|
analyze |
Analyze project structure and generate insights | project-prompt analyze |
dashboard |
Generate visual project dashboard | project-prompt dashboard --format html |
version |
Show version and API status | project-prompt version |
help |
Display detailed help information | project-prompt help |
init |
Initialize project with ProjectPrompt | project-prompt init |
menu |
Launch interactive menu interface | project-prompt menu |
API Configuration
| Command | Description | Example |
|---|---|---|
set-api |
Configure API keys for AI services | project-prompt set-api anthropic |
verify-api |
Check API configuration status | project-prompt verify-api |
check-env |
Verify environment variables | project-prompt check-env |
Project Analysis
| Command | Description | Example |
|---|---|---|
analyze-group |
Analyze specific functional groups | project-prompt analyze-group "Authentication" |
generate-suggestions |
Generate AI-powered improvement suggestions | project-prompt generate-suggestions |
track-progress |
Track development progress across phases | project-prompt track-progress |
AI Features
| Command | Description | Example |
|---|---|---|
ai analyze |
AI-powered code analysis | project-prompt ai analyze file.py |
ai refactor |
Get refactoring suggestions | project-prompt ai refactor file.py |
ai explain |
Explain code functionality | project-prompt ai explain file.py --detail advanced |
ai generate |
Generate code or documentation | project-prompt ai generate |
AI-Powered Rules Management 🤖
| Command | Description | Example |
|---|---|---|
rules suggest |
Generate AI-powered rule suggestions | project-prompt rules suggest --ai --threshold 0.8 |
rules analyze-patterns |
Analyze project patterns for rules | project-prompt rules analyze-patterns --detailed |
rules generate-project-rules |
Generate clean project-rules.md format | project-prompt rules generate-project-rules --ai |
rules auto-generate |
Auto-generate complete rules files | project-prompt rules auto-generate --output rules.yaml |
rules generate-structured-rules |
NEW: Generate sophisticated structured rules | project-prompt rules generate-structured-rules --ai |
rules validate-structured-rules |
NEW: Validate structured YAML rules | project-prompt rules validate-structured-rules rules.yaml |
Premium Features
| Command | Description | Example |
|---|---|---|
premium dashboard |
Advanced interactive dashboard | project-prompt premium dashboard |
premium implementation |
Implementation assistant | project-prompt premium implementation "user auth" |
Utilities
| Command | Description | Example |
|---|---|---|
delete |
Clean up generated files | project-prompt delete all --force |
setup-alias |
Set up command aliases | project-prompt setup-alias |
setup-deps |
Install optional dependencies | project-prompt setup-deps |
set-log-level |
Change logging verbosity | project-prompt set-log-level debug |
diagnose |
Diagnose installation issues | project-prompt diagnose |
Subscription Management
| Command | Description | Example |
|---|---|---|
subscription plans |
View available subscription plans | project-prompt subscription plans |
subscription activate |
Activate premium license | project-prompt subscription activate LICENSE_KEY |
subscription info |
View current subscription status | project-prompt subscription info |
Telemetry
| Command | Description | Example |
|---|---|---|
telemetry enable |
Enable anonymous usage analytics | project-prompt telemetry enable |
telemetry disable |
Disable usage analytics | project-prompt telemetry disable |
telemetry status |
Check telemetry status | project-prompt telemetry status |
🔧 Configuration
Environment Setup
Create a .env file in your project root:
# AI API Keys (optional but recommended)
ANTHROPIC_API_KEY=your_anthropic_key_here
OPENAI_API_KEY=your_openai_key_here
GITHUB_TOKEN=your_github_token_here
# Logging level
LOG_LEVEL=info
API Configuration
-
Anthropic Claude (Recommended):
project-prompt set-api anthropic
-
OpenAI GPT:
project-prompt set-api openai
-
Verify Configuration:
project-prompt verify-api
📊 Output Examples
Basic Analysis
project-prompt analyze
Generates:
- Project structure overview
- File type distribution
- Basic metrics and statistics
- Technology stack detection
Dashboard Generation
project-prompt dashboard --format html --output ./report.html
Creates:
- Interactive HTML dashboard
- Dependency graphs
- Code quality metrics
- Navigation-friendly project overview
AI-Powered Insights
project-prompt ai analyze src/main.py --output analysis.json
Provides:
- Code quality assessment
- Potential issues detection
- Improvement recommendations
- Security considerations
🎨 Use Cases
For Individual Developers
- Code Reviews: Analyze code quality before commits
- Documentation: Generate comprehensive project documentation
- Learning: Understand complex codebases quickly
- Refactoring: Get AI suggestions for code improvements
For Teams
- Onboarding: Help new team members understand project structure
- Architecture: Visualize system dependencies and relationships
- Standards: Maintain consistent code quality across projects
- Planning: Track development progress and milestones
For Project Managers
- Progress Tracking: Monitor development phases and completion
- Risk Assessment: Identify potential technical debt
- Resource Planning: Understand project complexity and scope
- Reporting: Generate visual reports for stakeholders
🔒 Privacy & Security
- Local Processing: Core analysis runs entirely on your machine
- API Usage: AI features only send code snippets when explicitly requested
- No Data Collection: Your code never leaves your environment without consent
- Optional Telemetry: Anonymous usage statistics can be disabled anytime
🆘 Getting Help
Command Help
project-prompt [COMMAND] --help
Troubleshooting
project-prompt diagnose
Interactive Menu
project-prompt menu
Documentation
- Quick Start:
QUICKSTART_GUIDE.md - User Guide:
docs/guides/user_guide.md - API Reference:
docs/reference/api_reference.md
🤖 AI-Powered Rules Management
ProjectPrompt includes sophisticated AI capabilities for automatic rule generation with advanced structured rule modeling:
Smart Rule Suggestions
# Generate AI-powered development rules for your project
project-prompt rules suggest --ai --threshold 0.8
# Get detailed pattern analysis
project-prompt rules analyze-patterns --detailed
# Generate a clean project-rules.md file
project-prompt rules generate-project-rules --ai --output project-rules.md
# NEW: Generate structured rules with sophisticated models
project-prompt rules generate-structured-rules --ai --confidence 0.7
Structured Rules System 🏗️
The new structured rules system provides enterprise-grade rule management:
- RuleSet: Complete rule collections with versioning and metadata
- RuleGroup: Organized rule categories (Technology, Architecture, Security, etc.)
- RuleItem: Individual rules with priority, context, and examples
- RuleContext: File-specific targeting (extensions, directories, patterns)
- YAML Export: Professional rule documentation and sharing
What You Get
- Technology Detection: Automatically identifies frameworks, tools, and patterns
- Best Practice Suggestions: AI-generated rules based on industry standards
- Confidence Scoring: Each suggestion includes a confidence level (0.0-1.0)
- Implementation Roadmap: Prioritized phases for implementing suggested rules
- Multiple Formats: Structured YAML, Markdown reports, or JSON export
- Context-Aware Rules: File-specific rules with directory and pattern targeting
- Rule Validation: Built-in validation for structured rule files
Example Output
## Technology Constraints
### Mandatory Technologies
- **Python 3.8+**: Core language - follow PEP 8 standards and use type hints
- **Typer**: CLI framework for all command-line interfaces
### Architecture Rules
- All analysis classes MUST inherit from appropriate base classes
- Use lazy loading for expensive resources (AI clients, large models)
### Implementation Roadmap
### Phase 1: Critical Rules (Week 1-2)
- [ ] API Key Security Validation (Confidence: 1.0/1.0)
- [ ] File System Security (Confidence: 0.9/1.0)
🚀 Advanced Features
Premium Capabilities
- Advanced dependency analysis with madge integration
- AI-powered implementation assistants
- Comprehensive progress tracking
- Priority support and updates
Extensibility
- Custom analyzers for specific technologies
- Template system for output customization
- Plugin architecture for additional integrations
- API for programmatic access
📞 Support
- Issues: GitHub Issues
- Documentation: Project Wiki
- Email: daniel@lagowski.es
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
Ready to get started? Run project-prompt analyze in your project directory and discover what ProjectPrompt can do for you!
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