Hybrid Dynamic Multi-Agent Collaboration System

Problem

Hybrid Dynamic Multi-Agent Collaboration System addresses a specific issue: complex work such as creative writing, multi-step analysis, project development, and research integration is hard to keep stable when a single agent handles role-switching, context management, and review in one long session. Temporary workloads also do not justify permanently running many specialized agents. This skill uses a main agent plus ephemeral subagents, assigning task roles by complexity and destroying them after completion to avoid persistent resource use.

How It Works

The system first classifies work into single tasks, standard tasks, innovation plus standard tasks, and new innovative tasks. For tasks without a mature flow, the main agent dynamically assigns 1–6 temporary subagents, such as worldbuilding, outline, writing, and review roles; for tasks with an existing skill, it loads the codified workflow and appends custom steps. Execution uses three-layer review: subagent self-check, main-agent confirmation, and a temporary review agent for complex tasks. Successful workflows with at least three passing runs and sufficient satisfaction are solidified into reusable skills with version management.

Boundaries and Notes

It is well suited to multi-role collaboration, staged quality checks, and workflow reuse. It is not intended for simple lookups, one-off calculations, strict sub-second latency, or controlling external hardware. It does not change OpenClaw core architecture or security boundaries, and it keeps task memory separate from the main agent’s brain/ memory, using core/shared-memory/ for context, intermediate outputs, and logs.