The system ensures efficient and conflict-free agent collaboration through the following mechanisms:
- Command File Definition Logic: Task assignment rules are stored in the
.claude/commands/directory in a Markdown file (e.g.start.md). - Context Driver Selection: The system automatically calls the matching agent based on the task type (e.g.
backend-architect(Processing API design). - locking mechanism: By
/coordination/agent_locks/The catalog avoids resource competition and ensures that each agent handles independent tasks. - registry coordination::
active_work_registry.jsonDocumentation of the agent's current task status for global coordination. - Parallel processing control: Users can access this information through the
--agentsparameter adjusts the number of concurrent agents (default 20).
This design significantly improves the development efficiency of complex projects and is especially suitable for team collaboration scenarios.
This answer comes from the articleClaude-Code-Multi-Agent: a tool for coordinating multiple AI agents to accomplish code developmentThe
May not be reproduced without permission:AI productivity tools " Claude-Code-Multi-Agent How to implement multi-agent task assignment and coordination?
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