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Claude Waves: A Multi-Agent Collaborative Workflow Framework Based on Claude Code

Claude Waves is a multi-agent collaborative workflow framework based on Claude Code. By decomposing complex tasks into multiple waves, each handled by specialized agents for specific subtasks, it enables efficient parallel task processing and result integration. This project demonstrates how to build a scalable multi-agent collaboration system in the Claude Code environment.

Claude WavesClaude Code多智能体Multi-agent工作流Wave 架构AI 编程并行处理智能体协作任务分解
Published 2026-06-09 17:13Recent activity 2026-06-09 17:32Estimated read 7 min
Claude Waves: A Multi-Agent Collaborative Workflow Framework Based on Claude Code
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Section 01

Introduction to the Claude Waves Framework

Claude Waves is a multi-agent collaborative workflow framework developed by iamphduc and open-sourced on GitHub (link: https://github.com/iamphduc/claude-waves, release date: 2026-06-09). Based on Claude Code, it decomposes complex tasks into multiple waves via the Wave architecture, each handled by specialized agents for specific subtasks, enabling parallel processing and result integration. It aims to address the limitations of single-agent handling of complex tasks, improving development efficiency and output quality.

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Section 02

Project Background: The Need for Multi-Agent Collaboration

With the development of AI coding assistants like Claude Code, the single-agent model has gradually exposed limitations: context overload (inputting large project code at once affects efficiency), high task coupling (confusion between multi-domain tasks), low serial efficiency (inability to process independent subtasks in parallel), and insufficient professionalism (general agents struggle to cover all domains). To address these issues, multi-agent architectures have emerged, and Claude Waves is a practical framework born in this context.

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Section 03

Core Approach: Wave Architecture Design

The core of Claude Waves is the Wave architecture:

  1. Wave Definition: Each Wave includes an input processing layer (data validation, context preparation, dependency resolution), an agent execution layer (role definition, tool configuration, execution strategy), and a result output layer (formatting, quality check, downstream delivery).
  2. Wave Relationships: Supports four modes—serial (sequential execution), parallel (simultaneous execution of independent subtasks), convergence (integration of multiple upstream results), and divergence (single upstream triggers multiple downstream)—to adapt to different task scenarios.
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Section 04

Implementation Details: Agents and Integration

Key implementation details of Claude Waves include:

  • Agent Roles: Architect (system design), Implementer (code writing), Reviewer (quality assurance), Documenter (document generation), Coordinator (Wave scheduling).
  • Claude Code Integration: Leverages tool calling mechanisms (file operations, code analysis, etc.), session management (isolation, persistence), and code execution capabilities (real-time code testing, sandbox environment).
  • Context Management: Hierarchical context (global/Wave/temporary), standardized delivery, compression mechanisms (summary generation, symbolic references).
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Section 05

Application Scenarios and Effects

Claude Waves applies to multiple scenarios:

  1. Large-scale Feature Development: Decompose into waves like requirement analysis, parallel module design/implementation, code review, document generation, reducing time by 50%+.
  2. Codebase Refactoring: Parallel module analysis, migration strategy formulation, parallel migration, test verification—significantly shortening the cycle.
  3. Code Review: Parallel security/performance/maintainability reviews, automatic report integration, improving efficiency and professionalism.
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Section 06

Advantages and Value

Core advantages of Claude Waves:

  • Efficiency Improvement: Parallel execution of Waves reduces complex task time by 50%+.
  • Quality Assurance: Specialized agents focus on their domains, cross-validation reduces issues.
  • Scalability: Supports Wave/agent expansion and template reuse.
  • Observability: Complete execution tracking, performance analysis, and debugging-friendly.
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Section 07

Usage Recommendations and Future Directions

Usage Recommendations: Suitable for scenarios that can be decomposed into independent subtasks and require multi-domain collaboration; follow principles like single responsibility and minimal dependencies; start with simple serial execution and optimize gradually. Future Directions: Intelligent enhancement (adaptive decomposition, learning optimization), ecosystem expansion (plugin system, template market), enterprise-level features (permission control, audit logs).

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Section 08

Summary

Claude Waves provides Claude Code users with a powerful multi-agent collaboration framework via the Wave architecture, effectively addressing the limitations of single agents. Its open-source implementation serves as a reference for the community. As AI coding assistants evolve, multi-agent collaboration will become an important paradigm, and Claude Waves offers valuable practical experience for this.