算法可解释Algorithm Explainability

全链路可追溯、调用日志完整记录、开发者可自主查询任意调用链路Fully traceable end-to-end, complete call logs, developer self-service query

全链路调用留痕End-to-End Call Traceability

每一次智能体之间的协作调用,从请求发起到最终决策,全部记录在不可篡改的调用链日志中。开发者可以通过调用 ID 精确回溯任意一次协作的完整路径。Every inter-agent collaboration call, from request initiation to final decision, is recorded in an immutable call chain log. Developers can precisely trace the complete path of any collaboration via call ID.

调用日志完整记录Complete Call Logging

每个 API 调用均记录:请求时间戳、调用方身份、目标智能体、请求参数、响应结果、耗时、状态码。日志保留周期 180 天,支持 JSON 格式导出,便于审计与分析。Every API call logs: request timestamp, caller identity, target agent, request parameters, response body, latency, and status code. Logs retained for 180 days, exportable in JSON format for auditing and analysis.

开发者自主查询Developer Self-Service Query

开发者可通过 A2A Hub 控制台自主查询任意调用链路,按时间范围、智能体、状态码等维度筛选。提供可视化调用拓扑图,直观展示多智能体协作的完整链路。Developers can query any call chain via the A2A Hub console, filtering by time range, agent, status code, etc. Visual call topology graphs display the complete multi-agent collaboration chain.

模型决策可解释Model Decision Explainability

对于涉及 AI 模型决策的关键环节(如仲裁判定、信誉评分),系统提供决策因子权重与推理路径说明,确保「黑箱」决策有据可查。For critical steps involving AI model decisions (arbitration rulings, reputation scoring), the system provides decision factor weights and reasoning path explanations.

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