✨ Features

AI Task Manager provides comprehensive tools for structured AI-assisted development workflows.

🤝 Multi-Assistant Support

Configure support for multiple coding assistants simultaneously:

  • 🎭 Claude: Anthropic’s Claude AI assistant via Claude Code
  • 💎 Gemini: Google’s Gemini AI assistant via CLI
  • 📝 Open Code: Open source code assistant integration

📋 Template System

Built-in templates for different project types:

Project Templates

  • Basic: Simple project structure for small applications
  • Development: Full development workflow with testing and CI/CD
  • Research: Documentation and analysis-focused projects

Command Templates

  • create-plan: Strategic planning and requirement analysis
  • generate-tasks: Task decomposition and dependency mapping
  • execute-blueprint: Implementation and execution workflows
  • fix-broken-tests: Post-implementation test fixing and validation

🏗️ Workspace Management

Intelligent Initialization

  • Detects existing project structures
  • Merges configurations safely
  • Preserves existing files while updating templates
  • Supports custom destination directories

Format Adaptation

  • Markdown format for Claude and Open Code
  • TOML format for Gemini integration
  • Automatic format conversion between assistants
  • Consistent functionality across all formats

🔄 Workflow Orchestration

Three-Phase Approach 

flowchart TD
    A[User Request] --> B[📝 Phase 1: Planning]
    B --> C[📋 Phase 2: Task Generation]
    C --> D[🚀 Phase 3: Execution]
    D --> E[✅ Quality Review]

    B --> B1[Requirements Analysis<br/>Stakeholder Clarification<br/>Architecture Planning]
    C --> C1[Atomic Task Breakdown<br/>Dependency Mapping<br/>Resource Allocation]
    D --> D1[Parallel Execution<br/>Progress Tracking<br/>Validation Gates]

    style A fill:#ffebee
    style E fill:#e8f5e8
    style B fill:#fff3e0
    style C fill:#f3e5f5
    style D fill:#e3f2fd

Progressive Refinement

  • Context Isolation: Each phase focuses on specific objectives
  • Validation Gates: Quality checkpoints between phases
  • Iterative Improvement: Feedback loops for continuous refinement
  • Scope Control: Built-in mechanisms to prevent feature creep

🎯 Task Management

Atomic Task Decomposition

  • Single Responsibility: Each task has one clear objective
  • Skill-Based Assignment: Tasks matched to specific technical skills
  • Dependency Tracking: Automatic dependency resolution and sequencing
  • Complexity Analysis: Automatic scoring and decomposition of complex tasks

Quality Assurance

  • Validation Criteria: Predefined acceptance criteria for each task
  • Progress Tracking: Real-time status updates and completion monitoring
  • Error Handling: Graceful failure recovery and remediation workflows
  • Documentation: Comprehensive logging of decisions and outcomes

🔧 Configuration & Customization

Project Context

  • TASK_MANAGER.md: Editable project context and guidelines
  • POST_PHASE.md: Custom validation criteria and quality gates
  • Template Customization: Modify templates for specific project needs

Extensibility

  • Plugin Architecture: Support for custom extensions
  • Hook System: Custom scripts for lifecycle events
  • Integration Points: APIs for external tool integration
  • Configuration Management: Environment-specific settings

🚀 Performance & Scalability

Optimized Execution

  • Parallel Processing: Concurrent task execution within phases
  • Resource Management: Intelligent allocation of AI assistant resources
  • Caching: Optimized storage and retrieval of plans and tasks
  • Incremental Updates: Only process changes, not entire workflows

Monitoring & Analytics

  • Execution Metrics: Track completion times and success rates
  • Resource Usage: Monitor AI assistant utilization
  • Quality Metrics: Measure output quality and consistency
  • Performance Insights: Identify optimization opportunities

💰 Cost Efficiency

No Additional API Costs

  • Works within existing AI subscriptions
  • No pay-per-token charges
  • No external service dependencies
  • Maximize value from current AI investments

Resource Optimization

  • Efficient prompt structuring reduces token usage
  • Targeted queries minimize unnecessary API calls
  • Reusable templates and patterns
  • Smart caching reduces redundant operations

🔒 Security & Privacy

Local-First Architecture

  • All data stored locally on your machine
  • No external data transmission required
  • Full control over sensitive project information
  • Works offline for most operations

Best Practices

  • Secure handling of configuration files
  • No hardcoded credentials or secrets
  • Environment-specific configuration management
  • Audit trail for all operations