Multiple AI agents often struggle with coordination, leading to critical issues like race conditions, stale data, context drift, and conflicting edits. Agent Orchestration offers a robust solution by establishing a central hub for agent collaboration. It provides shared memory for agents to store and retrieve critical context, implements a turn-based task queue for ordered execution, enables agent discovery, and offers resource locking to prevent conflicts. By automating context synchronization and providing real-time status, it ensures AI agents work together efficiently and effectively on complex coding projects, enhancing productivity and consistency.
主要功能
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02Shared Memory for inter-agent context and data storage.
03Resource Locking to prevent concurrent access to files or resources.
04Auto Context Sync for automatically updating activeContext.md.
05Agent Discovery to list and monitor all registered agents.
06Turn-based Task Queue with dependencies for coordinated execution.
