Prompr: AI Agent Workflow Automation Library
Comprehensive workflow automation library enabling parallel multi-agent task execution with Claude AI, featuring intelligent task distribution, automatic progress tracking, and seamless Git integration for streamlined development workflows.
Overview
Prompr is a sophisticated workflow automation library designed to transform software development through intelligent AI agent orchestration. The library enables developers to harness the power of multiple Claude AI agents working in parallel, automatically distributing tasks, tracking progress, and managing complex development workflows. Built with a focus on practical software development needs, Prompr bridges the gap between AI capabilities and real-world project requirements. The library provides structured commands for everything from Product Requirements Document generation to multi-agent task execution, making it an essential tool for teams looking to integrate AI-powered automation into their development pipeline. The system demonstrates advanced agentic capabilities through its ability to coordinate multiple AI agents, handle task dependencies, and maintain project context across complex workflows. With built-in Git integration and automatic progress tracking, Prompr transforms how development teams approach project planning and execution.
Technical Stack
AI/ML
- ▸Anthropic Claude
- ▸Multi-Agent Systems
- ▸Intelligent Task Distribution
- ▸Context Management
Core Library
- ▸Python
- ▸Click CLI
- ▸Asyncio
- ▸JSON Schema Validation
Workflow Management
- ▸Task Orchestration
- ▸Progress Tracking
- ▸Dependency Resolution
- ▸Resume Capabilities
Integration
- ▸Git Automation
- ▸File System Management
- ▸Command Pattern
- ▸Configuration Management
Key Features
Multi-agent parallel task execution with 3-5 concurrent agents
Intelligent task distribution and dependency handling
Automatic Git integration with commit generation
Structured command pattern following /user:<category>:<command> format
PRD generation from design documents
Dynamic task list creation from requirements
Workflow resumption for interrupted processes
Progress tracking and monitoring across all agents
Context management for complex project workflows
Extensible command architecture for custom workflows
Code Examples
Technical Challenges
Coordinating multiple AI agents while maintaining task coherence
Implementing robust task dependency resolution
Managing context and state across distributed agent workflows
Creating intuitive command patterns for complex operations
Ensuring reliable Git integration with automatic commits
Handling workflow interruptions and resume capabilities