ProjectPrompt v2.0

🤖 AI-powered project analysis and improvement suggestions

Transform your codebase with intelligent analysis and personalized AI recommendations.

⚡ Quick Start in 5 Steps

Always run commands in YOUR project directory (not ProjectPrompt directory):

# 1. Install once (in ProjectPrompt directory)
git clone https://github.com/Dixter999/project-prompt.git && cd project-prompt && pip install -e .

# 2. Navigate to your project (the one you want to analyze)
cd /path/to/your/project

# 3. Analyze your project structure
projectprompt analyze .

# 4. Check what groups were found
projectprompt status

# 5. Get AI suggestions for a group
projectprompt suggest "group_name"  # Use actual names from status

# 6. Generate implementation prompts (NEW!)
projectprompt generate-prompts "group_name"  # Creates ready-to-use prompts

# 7. AI-driven implementation (NEWEST!)
projectprompt adaptive-implement "Add user authentication"  # Direct AI implementation

🔑 Optional: Add AI key for better suggestions

# In ProjectPrompt directory, create .env file
cd /path/to/project-prompt && echo "ANTHROPIC_API_KEY=your_key" > .env

Example: Analyzing a Web App

# Step 1: Install (one-time)
git clone https://github.com/Dixter999/project-prompt.git
cd project-prompt
pip install -e .

# Step 2: Navigate to your web app
cd /home/user/my-web-app

# Step 3: Analyze it
projectprompt analyze .
# Output: Found 3 groups: frontend_modules, backend_modules, utility_modules

# Step 4: Get AI suggestions for frontend
projectprompt suggest "frontend_modules"
# Output: Creates suggestions/frontend_modules-suggestions.md

# Step 5: Generate implementation prompts
projectprompt generate-prompts "frontend_modules"
# Output: Creates phase-by-phase prompts for AI assistants

📦 Installation

Simple Installation (Recommended)

git clone https://github.com/Dixter999/project-prompt.git
cd project-prompt
pip install -e .

Test Installation:

projectprompt --help  # Should show command help

If command not found, try:

python -m src.cli --help  # Alternative way to run

🚀 Step-by-Step Guide for New Users

1. First-Time Setup (Do Once)

Install ProjectPrompt:

git clone https://github.com/Dixter999/project-prompt.git
cd project-prompt
pip install -e .

Optional - Set up AI key for better suggestions:

# Stay in the project-prompt directory
echo "ANTHROPIC_API_KEY=your_key_here" > .env

2. Analyze Any Project

Navigate to your actual project:

# Example paths - use YOUR actual project path
cd /home/user/my-web-app          # For a web application
cd /Users/john/my-python-lib      # For a Python library  
cd C:\Projects\my-node-app        # For a Node.js project

Run the analysis:

projectprompt analyze .

Example output:

🔍 Analyzing project: /home/user/my-web-app
📊 Found 3 functional groups:
┌─────────────────────────────┬───────────┐
│ Group Name                  │ Files     │
├─────────────────────────────┼───────────┤
│ frontend_modules            │        15 │
│ backend_modules             │         8 │
│ utility_modules             │         4 │
└─────────────────────────────┴───────────┘

3. Check What Was Found

projectprompt status

Example output:

📊 Analysis Status
==================================================
📁 Available groups (3):
   • frontend_modules (15 files)
   • backend_modules (8 files)
   • utility_modules (4 files)

🚀 Next actions:
   Create suggestions with:
   • projectprompt suggest "frontend_modules"
   • projectprompt suggest "backend_modules"
   • projectprompt suggest "utility_modules"

4. Generate AI Suggestions

projectprompt suggest "frontend_modules"

Example output:

🤖 Generating suggestions for group: frontend_modules
✅ Suggestions created: project-prompt-output/suggestions/frontend_modules-suggestions.md
📄 42 lines of suggestions created

5. Generate Implementation Prompts (NEW!)

projectprompt generate-prompts "frontend_modules"

Example output:

🤖 Generating implementation prompts for: frontend_modules
✅ Generated 3 implementation prompts:
   • frontend_modules-phase1-prompt.md
   • frontend_modules-phase2-prompt.md  
   • frontend_modules-phase3-prompt.md
📁 Prompts saved to: project-prompt-output/prompts/

6. Use the Prompts with AI Assistants

Open any prompt file (e.g., project-prompt-output/prompts/frontend_modules-phase1-prompt.md)
Copy the entire content
Paste into Claude, ChatGPT, or your preferred AI assistant
Follow the AI's implementation guidance
Move to the next phase after testing

📁 Example File Paths and Outputs

Common Project Locations

# Web applications
/home/user/my-react-app
/Users/developer/vue-project
C:\Projects\angular-app

# Python projects
/home/user/ml-project
/Users/dev/flask-api
C:\Code\django-blog

# Node.js projects  
/home/user/express-api
/Users/dev/next-app
C:\Development\electron-app

Output Structure After Analysis

your-project/
├── [your files - never modified]
└── project-prompt-output/
    ├── analysis/
    │   ├── project-structure.md      # Project overview
    │   └── functional-groups/
    │       ├── frontend_modules-analysis.md
    │       └── backend_modules-analysis.md
    ├── suggestions/
    │   ├── frontend_modules-suggestions.md  # AI improvement ideas
    │   └── backend_modules-suggestions.md
    └── prompts/
        ├── frontend_modules-phase1-prompt.md  # Ready for AI assistants
        ├── frontend_modules-phase2-prompt.md
        └── backend_modules-phase1-prompt.md

⚠️ Important: Directory Rules

Key Rule: Always run projectprompt commands inside the project you want to analyze, not in the ProjectPrompt tool directory.

✅ Correct Way:

# 1. Install ProjectPrompt (do this once)
cd /path/to/project-prompt
pip install -e .

# 2. Navigate to YOUR project
cd /path/to/your/actual/project

# 3. Run commands from YOUR project directory
projectprompt analyze .
projectprompt status
projectprompt suggest "group_name"

❌ Common Mistake:

# DON'T do this - analyzing the tool instead of your project
cd /path/to/project-prompt
projectprompt analyze .  # This analyzes ProjectPrompt, not your project

🆕 What's New in v2.0

🚀 Adaptive Implementation System: Complete AI-driven implementation with FASE 1 & FASE 2 modes
💬 ConversationManager: Multi-turn conversation support with context tracking
🔀 Advanced Workflow: Multi-request orchestration with dependency resolution
🤖 Implementation Prompts: Generate ready-to-use prompts for AI assistants
🔥 .gitignore Support: Automatically respects your .gitignore patterns
🌍 English Interface: Complete professional English translation
⚡ Performance: 50% faster scanning with intelligent file filtering
🎯 Better Grouping: Improved functional group detection
📱 Clean CLI: Simplified, intuitive command structure

🚨 Quick Troubleshooting

"Group not found" Error

# Check what groups actually exist
projectprompt status
# Use the exact group names shown in the output

"Analysis directory not found" Error

# First analyze your project
projectprompt analyze .
# Then run other commands
projectprompt status

"API key not found" Warning

# In ProjectPrompt installation directory, create .env file
cd /path/to/project-prompt
echo "ANTHROPIC_API_KEY=your_key" > .env

Command Not Found

# Try alternative way to run
python -m src.cli --help

📋 Command Reference

Command	Purpose	Example
`analyze <path>`	Scan project and create groups	`projectprompt analyze .`
`status`	Show analysis status and groups	`projectprompt status`
`suggest <group>`	Generate AI improvement suggestions	`projectprompt suggest "core_modules"`
`generate-prompts <group>`	Create implementation prompts	`projectprompt generate-prompts "core_modules"`
`adaptive-implement <task>`	NEW! AI-driven implementation system	`projectprompt adaptive-implement "Add authentication"`
`clean`	Remove analysis data	`projectprompt clean`

Key Options

# Analysis options
--max-files 500              # Limit files analyzed
--output ./custom-dir        # Custom output directory
--exclude "*.log"           # Exclude file patterns

# Suggestion options
--api anthropic             # Choose AI provider (anthropic|openai)
--detail-level detailed     # Detail level (basic|medium|detailed)
--phase 2                   # Generate specific phase prompt only

# Adaptive Implementation options (NEW!)
--use-workflow              # Enable FASE 2 advanced workflow management
--conversation-mode         # Enable multi-turn conversation sessions
--max-requests 10           # Maximum API requests for complex tasks
--target quality            # Optimization target (speed|cost|quality|balanced)
--complexity complex        # Task complexity (simple|medium|complex|very_complex)
--task-type implementation  # Task type (implementation|analysis|debugging|optimization|testing)

💡 Usage Examples

Example 1: Analyze a Python Project

$ projectprompt analyze . --max-files 30
🔍 Analyzing project: /home/user/my-python-lib
📊 Found 2 functional groups:
┌─────────────────────────────┬───────────┐
│ Group Name                  │ Files     │
├─────────────────────────────┼───────────┤
│ core_modules                │         4 │
│ feature_modules             │        21 │
└─────────────────────────────┴───────────┘

🚀 Next: Choose a group for AI analysis

Example 2: Generate AI Suggestions

$ projectprompt suggest "core_modules" --detail-level detailed
🤖 Generating suggestions for group: core_modules
✅ Suggestions created: project-prompt-output/suggestions/core_modules-suggestions.md
📄 45 lines of suggestions created

Example 3: Generate Implementation Prompts

$ projectprompt generate-prompts "core_modules"
🤖 Generating implementation prompts for: core_modules
✅ Generated 3 implementation prompts:
   • core_modules-phase1-prompt.md
   • core_modules-phase2-prompt.md
   • core_modules-phase3-prompt.md
📁 Prompts saved to: project-prompt-output/prompts/

Example 4: Check Project Status

$ projectprompt status
📊 Analysis Status
==================================================
📁 Available groups (2): core_modules, feature_modules
🤖 Created suggestions (1): core_modules
🚀 Remaining: projectprompt suggest "feature_modules"

🚀 NEW: Adaptive Implementation System (FASE 2)

ProjectPrompt now includes an advanced AI-driven implementation system with two operational modes:

📋 FASE 1: Standard Implementation (Fast)

Single-request implementation for quick tasks and simple features.

# Standard implementation examples
projectprompt adaptive-implement "Add user authentication system"
projectprompt adaptive-implement "Fix login bug" --task-type debugging
projectprompt adaptive-implement "Optimize database queries" --target cost

🚀 FASE 2: Advanced Workflow Management (Comprehensive)

Multi-request intelligent orchestration for complex tasks with conversation support.

# Advanced workflow examples
projectprompt adaptive-implement "Refactor entire API" --use-workflow
projectprompt adaptive-implement "Complex feature implementation" \
  --use-workflow --conversation-mode --max-requests 10
projectprompt adaptive-implement "Large architectural changes" \
  --use-workflow --conversation-mode --complexity very_complex --target quality

🤖 ConversationManager Features

The ConversationManager enables intelligent multi-turn conversations:

Session Management: Creates and tracks conversation sessions across multiple interactions
Context Accumulation: Maintains context across conversation turns for better continuity
Analytics & Insights: Provides conversation analytics and pattern identification
Metadata Tracking: Preserves implementation metadata and progress tracking

💡 How to Work with FASE 2

1. Simple Tasks (Use FASE 1)

# Quick implementations, bug fixes, simple features
projectprompt adaptive-implement "Add logging to user service" --target speed

2. Complex Tasks (Use FASE 2)

# Multi-step implementations, architectural changes, large features
projectprompt adaptive-implement "Implement microservices architecture" \
  --use-workflow --max-requests 15 --complexity very_complex

3. Interactive Development (Use Conversation Mode)

# Iterative development with context preservation
projectprompt adaptive-implement "Build complete authentication system" \
  --use-workflow --conversation-mode --max-requests 8

🔄 Workflow Process

Context Analysis: Intelligent project context building and analysis
Prompt Enhancement: Advanced prompt optimization for specific tasks
Request Orchestration: Multi-request coordination with dependency resolution
Response Processing: Content extraction and implementation plan generation
Conversation Tracking: Session management and context accumulation (if enabled)
Results Integration: Comprehensive output with analytics and next steps

📊 Performance Characteristics

Task Type	Recommended Mode	Expected Time	API Requests
Bug fixes, simple features	FASE 1	2-5 seconds	1 request
Medium features, refactoring	FASE 2	10-30 seconds	2-5 requests
Complex features, architecture	FASE 2 + Conversation	1-3 minutes	5-15 requests

🎯 Task Types and Targets

# Task types
--task-type implementation    # New features and functionality
--task-type analysis         # Code analysis and review
--task-type debugging        # Bug fixes and troubleshooting
--task-type optimization     # Performance and efficiency improvements
--task-type testing          # Test creation and validation

# Optimization targets
--target speed              # Fastest response, basic models
--target cost               # Cost-optimized models and parameters
--target quality            # Highest quality, advanced models
--target balanced           # Balance of speed, cost, and quality (default)

📁 Output Structure

FASE 2 creates comprehensive outputs:

project-prompt-output/adaptive-implementation/
├── workflow_YYYYMMDD_HHMMSS.json           # Complete workflow data
├── workflow_summary_YYYYMMDD_HHMMSS.md     # Human-readable summary
└── conversation_SESSION-ID_YYYYMMDD.json   # Conversation data (if enabled)

🔧 Configuration

API Keys Setup

Create a .env file in the ProjectPrompt installation directory:

# Navigate to ProjectPrompt installation directory
cd /path/to/project-prompt

# Create .env file with your API key
echo "ANTHROPIC_API_KEY=your_anthropic_key_here" > .env

Example .env file content:

# Choose one AI provider
ANTHROPIC_API_KEY=your_anthropic_key_here
# OR
OPENAI_API_KEY=your_openai_key_here

# Optional settings
LOG_LEVEL=info

Supported AI Providers

Anthropic Claude (recommended): Fast, detailed analysis
OpenAI GPT: Alternative provider with different perspective

🆘 Troubleshooting

Common Issues and Quick Fixes

❌ "Group 'core_modules' not found"

# Check what groups are actually available
projectprompt status
# Use the exact group names shown in the output
projectprompt suggest "actual_group_name"

❌ "Analysis directory not found"

# First analyze the project
projectprompt analyze .
# Then run other commands
projectprompt status
projectprompt suggest "group_name"

❌ "Anthropic API key not found"

# Create .env file in ProjectPrompt installation directory
cd /path/to/project-prompt
echo "ANTHROPIC_API_KEY=your_actual_key" > .env
# Verify the file exists
cat .env

❌ Command not found

# Check if ProjectPrompt is installed correctly
projectprompt --help
# If that fails, try:
python -m src.cli --help

Quick Diagnostic Commands

# Check current directory and existing analysis  
pwd
ls -la project-prompt-output/ 2>/dev/null || echo "No analysis found"
projectprompt status

🎯 Key Features

🔍 Smart Project Analysis

Respects .gitignore: Automatically ignores files per your .gitignore patterns
Language Detection: Identifies main programming languages and frameworks
Functional Grouping: Organizes files into logical groups (core, features, utils, tests)

🤖 AI-Powered Suggestions

Multiple AI Providers: Support for Anthropic Claude and OpenAI GPT
Detailed Recommendations: Get specific improvement suggestions with implementation steps
Priority-Based: Suggestions ranked by impact and effort

🤖 Implementation Prompt Generation (NEW!)

Ready-to-Use Prompts: Generate detailed implementation prompts from suggestions
Phase-by-Phase: Each suggestion phase gets its own detailed prompt
AI Assistant Ready: Prompts optimized for use with Claude, ChatGPT, and other AI assistants

🚀 Complete Workflow: From Analysis to Implementation

Step 1: One-Time Setup

# Install ProjectPrompt (do this once)
git clone https://github.com/Dixter999/project-prompt.git
cd project-prompt
pip install -e .

# Optional: Set up API key for better suggestions
echo "ANTHROPIC_API_KEY=your_key_here" > .env

Step 2: Analyze Your Project

# Navigate to your actual project
cd /path/to/your/project

# Analyze the project structure
projectprompt analyze .

# Check what groups were created
projectprompt status

Step 3: Generate AI Suggestions

# Generate suggestions for each group
projectprompt suggest "core_modules"
projectprompt suggest "feature_modules"

Step 4: Generate Implementation Prompts (NEW!)

# Generate ready-to-use prompts for AI assistants
projectprompt generate-prompts "core_modules"

# Or generate a specific phase prompt
projectprompt generate-prompts "core_modules" --phase 2

Step 5: Implement with AI Assistants

Open: project-prompt-output/prompts/core_modules-phase1-prompt.md
Copy the prompt content
Paste into Claude, ChatGPT, or your preferred AI assistant
Follow the AI's step-by-step implementation guidance
Test and validate the implementation
Move to the next phase prompt

🗑️ Uninstalling

# Simple uninstall
projectprompt uninstall

# Force uninstall (no prompts)
projectprompt uninstall --force

# Keep analysis data
projectprompt uninstall --keep-data

📝 Summary

🎯 Most Important Rule

Always run projectprompt commands in your project directory, not in the ProjectPrompt installation directory.

🔄 Basic Workflow

Install once: git clone + pip install -e . (in ProjectPrompt directory)
Navigate: cd /path/to/your/project (to YOUR project)
Analyze: projectprompt analyze . (creates groups)
Suggest: projectprompt suggest "group_name" (generates AI recommendations)
Generate prompts: projectprompt generate-prompts "group_name" (creates implementation prompts)

🚨 When Something Goes Wrong

Check you're in the right directory: pwd
Check if analysis exists: projectprompt status
Use exact group names from status output

🔑 For AI Suggestions

Optional but recommended: Add API key in ProjectPrompt directory
Create .env file: echo "ANTHROPIC_API_KEY=your_key" > .env

📖 Need Help?

projectprompt --help                 # General help
projectprompt analyze --help         # Analyze command help
projectprompt suggest --help         # Suggest command help
projectprompt generate-prompts --help # Implementation prompts help

Made with ❤️ for developers who want to improve their code with AI assistance

Name		Name	Last commit message	Last commit date
Latest commit History 190 Commits
config		config
src		src
.env.example		.env.example
.gitignore		.gitignore
README.md		README.md
install.sh		install.sh
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt
setup.py		setup.py

Folders and files

Latest commit

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ProjectPrompt v2.0

⚡ Quick Start in 5 Steps

Example: Analyzing a Web App

📦 Installation

Simple Installation (Recommended)

🚀 Step-by-Step Guide for New Users

1. First-Time Setup (Do Once)

2. Analyze Any Project

3. Check What Was Found

4. Generate AI Suggestions

5. Generate Implementation Prompts (NEW!)

6. Use the Prompts with AI Assistants

📁 Example File Paths and Outputs

Common Project Locations

Output Structure After Analysis

⚠️ Important: Directory Rules

✅ Correct Way:

❌ Common Mistake:

🆕 What's New in v2.0

🚨 Quick Troubleshooting

"Group not found" Error

"Analysis directory not found" Error

"API key not found" Warning

Command Not Found

📋 Command Reference

Key Options

💡 Usage Examples

Example 1: Analyze a Python Project

Example 2: Generate AI Suggestions

Example 3: Generate Implementation Prompts

Example 4: Check Project Status

🚀 NEW: Adaptive Implementation System (FASE 2)

📋 FASE 1: Standard Implementation (Fast)

🚀 FASE 2: Advanced Workflow Management (Comprehensive)

🤖 ConversationManager Features

💡 How to Work with FASE 2

1. Simple Tasks (Use FASE 1)

2. Complex Tasks (Use FASE 2)

3. Interactive Development (Use Conversation Mode)

🔄 Workflow Process

📊 Performance Characteristics

🎯 Task Types and Targets

📁 Output Structure

🔧 Configuration

API Keys Setup

Supported AI Providers

🆘 Troubleshooting

Common Issues and Quick Fixes

❌ "Group 'core_modules' not found"

❌ "Analysis directory not found"

❌ "Anthropic API key not found"

❌ Command not found

Quick Diagnostic Commands

🎯 Key Features

🔍 Smart Project Analysis

🤖 AI-Powered Suggestions

🤖 Implementation Prompt Generation (NEW!)

🚀 Complete Workflow: From Analysis to Implementation

Step 1: One-Time Setup

Step 2: Analyze Your Project

Step 3: Generate AI Suggestions

Step 4: Generate Implementation Prompts (NEW!)

Step 5: Implement with AI Assistants

🗑️ Uninstalling

📝 Summary

🎯 Most Important Rule

🔄 Basic Workflow

🚨 When Something Goes Wrong

🔑 For AI Suggestions

📖 Need Help?

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