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name: taskmaster description: Project manager and task delegation system. Use when you need to break down complex work into smaller tasks, assign appropriate AI models based on complexity, spawn sub-agents for parallel execution, track progress, and manage token budgets. Ideal for research projects, multi-step workflows, or when you want to delegate routine tasks to cheaper models while handling complex coordination yourself.

TaskMaster: AI Project Manager & Task Delegation

Transform complex projects into managed workflows with smart model selection and sub-agent orchestration.

Core Capabilities

🎯 Smart Task Triage

• Analyze complexity → assign appropriate model (Haiku/Sonnet/Opus)
• Break large projects into smaller, manageable tasks
• Prevent over-engineering (don't use Opus for simple web searches)

🤖 Sub-Agent Orchestration

• Spawn isolated sub-agents with specific model constraints
• Run tasks in parallel for faster completion
• Consolidate results into coherent deliverables

💰 Budget Management

• Track token costs per task and total project
• Set budget limits to prevent runaway spending
• Optimize model selection for cost-efficiency

📊 Progress Tracking

• Real-time status of all active tasks
• Failed task retry with escalation
• Final deliverable compilation

Quick Start

1. Basic Task Delegation

TaskMaster: Research PDF processing libraries
- Budget: $2.00
- Priority: medium
- Deadline: 2 hours

2. Complex Project Breakdown

TaskMaster: Build recipe app MVP
- Components: UI mockup, backend API, data schema, deployment
- Budget: $15.00
- Timeline: 1 week
- Auto-assign models based on complexity

Model Selection Rules

Haiku ($0.25/$1.25) - Simple, repetitive tasks:

• Web searches & summarization
• Data formatting & extraction
• Basic file operations
• Status checks & monitoring

Sonnet ($3/$15) - Most development work:

• Research & analysis
• Code writing & debugging
• Documentation creation
• Technical design

Opus ($15/$75) - Complex reasoning:

• Architecture decisions
• Creative problem-solving
• Code reviews & optimization
• Strategic planning

Advanced Usage

Custom Model Assignment

Override automatic selection when you know better:

TaskMaster: Debug complex algorithm [FORCE: Opus]

Parallel Execution

Run multiple tasks simultaneously:

TaskMaster: Multi-research project
- Task A: Library comparison
- Task B: Performance benchmarks  
- Task C: Security analysis
[PARALLEL: true]

Budget Controls

Set spending limits:

TaskMaster: Market research
- Max budget: $5.00
- Escalate if >$3.00 spent
- Stop if any single task >$1.00

Key Resources

• Model Selection: See references/model-selection-rules.md for detailed complexity guidelines
• Task Templates: See references/task-templates.md for common task patterns
• Delegation Engine: Uses scripts/delegate_task.py for core orchestration logic

Implementation Notes

Sessions Management: Each sub-agent gets isolated session with specific model constraints. No cross-talk unless explicitly designed.

Error Handling: Failed tasks automatically retry once on Sonnet, then escalate to human review.

Result Aggregation: TaskMaster compiles all sub-agent results into a single, coherent deliverable for the user.

Token Tracking: Real-time cost monitoring with alerts when approaching budget limits.