task-coordination-strategies

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Decompose complex tasks, design dependency graphs, and coordinate multi-agent work with proper task descriptions and workload balancing. Use this skill when breaking down work for agent teams, managing task dependencies, or monitoring team progress.

AI & Automation 38,975 stars 4150 forks Updated 2 days ago MIT

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Skill Content

# Task Coordination Strategies Strategies for decomposing complex tasks into parallelizable units, designing dependency graphs, writing effective task descriptions, and monitoring workload across agent teams. ## When to Use This Skill - Breaking down a complex task for parallel execution - Designing task dependency relationships (blockedBy/blocks) - Writing task descriptions with clear acceptance criteria - Monitoring and rebalancing workload across teammates - Identifying the critical path in a multi-task workflow ## Task Decomposition Strategies ### By Layer Split work by architectural layer: - Frontend components - Backend API endpoints - Database migrations/models - Test suites **Best for**: Full-stack features, vertical slices ### By Component Split work by functional component: - Authentication module - User profile module - Notification module **Best for**: Microservices, modular architectures ### By Concern Split work by cross-cutting concern: - Security review - Performance review - Architecture review **Best for**: Code reviews, audits ### By File Ownership Split work by file/directory boundaries: - `src/components/` — Implementer 1 - `src/api/` — Implementer 2 - `src/utils/` — Implementer 3 **Best for**: Parallel implementation, conflict avoidance ## Dependency Graph Design ### Principles 1. **Minimize chain depth** — Prefer wide, shallow graphs over deep chains 2. **Identify the critical path** — The longest chain determines minimum completi...

Details

Author
wshobson
Repository
wshobson/agents
Created
1 years ago
Last Updated
2 days ago
Language
Python
License
MIT

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