multi-agent-engine多代理编排引擎 - 目标驱动的深度研究与项目协作系统。支持任务分解、分支执行、验证审核、返工迭代、智能决策。遵循第一性原理，实现主代理与分支代理的双向通信。触发词：多代理、multi-agent、代理编排、深度研究、目标分解、任务委派、工作流、agent orchestrate、multi agent
Install via ClawdBot CLI:
clawdbot install bjmrcft-hash/multi-agent-engineGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
eval (Audited Apr 18, 2026 · audit v1.0
Generated May 11, 2026
用户输入研究目标后，系统自动生成提纲，用户确认后启动多代理并行研究，最终聚合为一份综合报告。适用于需快速产出高质量调研成果的场景。
将复杂技术问题分解为多个子任务，由不同专业代理并行分析（如研究分析师、技术专家、战略分析师），再经过Critic审核与聚合，形成完整的可行性评估报告。
对分散的内部文档和研究资料进行多代理协作梳理，生成结构化知识库，支持版本管理和归档。适合需要系统化整理和持续更新的知识管理场景。
输入竞品名称，系统自动分解为多个分析维度（功能、定价、市场策略等），各代理并行产出分析报告，最终聚合为竞品全景报告，并支持返工迭代。
提供云端多代理编排平台，按工作流执行次数或座位数收费，客户无需自行部署OpenClaw环境。
为企业客户提供整套技能包，支持在客户自有OpenClaw环境中部署，收取一次性授权费和年度维护费。
为客户提供流程设计、代理配置定制、现有系统集成等咨询服务，以及额外的模型适配和规则定制开发。
💬 Integration Tip
确保OpenClaw版本为2026.3.x+，并先运行`多代理 check_env`验证环境。如需自定义模型分配规则，在项目根目录创建`.model-selector-rules.json`文件。
Scored Jul 6, 2026
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