We present SPEAR, a multi-agent coordination framework for smart contract auditing that applies established MAS patterns in a realistic security analysis workflow. SPEAR models auditing as a coordinated mission carried out by specialized agents: a Planning Agent prioritizes contracts using risk-aware heuristics, an Execution Agent allocates tasks via the Contract Net protocol, and a Repair Agent autonomously recovers from brittle generated artifacts using a programmatic-first repair policy. Agents maintain local beliefs updated through AGM-compliant revision, coordinate via negotiation and auction protocols, and revise plans as new information becomes available. An empirical study compares the multi-agent design with centralized and pipeline-based alternatives under controlled failure scenarios, focusing on coordination, recovery behavior, and resource use.

翻译：本文提出SPEAR——一个应用于实际安全分析工作流程的多智能体协调框架，该框架采用了成熟的多智能体系统模式。SPEAR将审计建模为由专业化智能体协同执行的任务：规划智能体通过风险感知启发式算法对合约进行优先级排序，执行智能体通过合同网协议分配任务，修复智能体采用编程优先的修复策略自主恢复脆弱生成产物。各智能体通过符合AGM公理的修正机制维护局部信念更新，通过协商与拍卖协议进行协调，并依据新信息动态修订计划。实证研究在受控故障场景下，将多智能体设计与集中式及流水线式方案进行对比，重点关注协调机制、恢复行为及资源利用效率。