hive-mind-advanced

Multi-agent coordination uses a queen-led hierarchical structure where specialized agents (researcher, coder, analyst, tester, architect, reviewer, optimizer, documenter) collaborate with consensus algorithms to make decisions. This Skill automates orchestration across distributed networks, enabling agents to share knowledge and reach agreement on strategic and tactical tasks without manual intervention.

Hive mind systems support majority voting, weighted consensus, and Byzantine fault-tolerant algorithms. Byzantine consensus is most robust for distributed agent networks where some agents may fail or behave unpredictably, ensuring reliable collective decision-making even when individual agents are unreliable or adversarial.

Collective memory uses an LRU cache backed by SQLite WAL persistence, creating a shared knowledge base all agents access and update. This persistent layer enables agents to learn from prior decisions, avoid duplicate work, and maintain context across long-running projects without losing information.

Yes. A queen-led hive mind can orchestrate agents across design, implementation, testing, and documentation phases of microservices projects. Byzantine consensus ensures all architectural decisions are fault-tolerant, and collective memory maintains design rationale and dependencies across the entire system build.

Hierarchical coordination designates a strategic queen agent that distributes tasks to specialized workers, improving scalability and decision quality for complex projects. Flat coordination treats all agents equally, which works for simple tasks but lacks strategic oversight and scales poorly as agent count or task complexity increases.

Consensus algorithms resolve disagreement by applying majority voting, weighted voting based on agent expertise, or Byzantine algorithms that tolerate faulty agents. The Skill automatically executes the chosen algorithm, logs the decision rationale in collective memory, and ensures the collective result is binding across all agents.