使用4个代理部署欺诈检测管道。适用场景:1. 需要实时交易监控并通过分析进行升级。
欺诈检测管道设置是一项面向实际任务的技能,主要用于部署 4 个代理: 监视器、 模式分析器、 调查员、 执行器;Roles.;
它将相关步骤、工具调用和结果整理方式集中到统一流程中,帮助使用者更快完成目标并减少重复操作。使用时应结合输入条件选择合适的执行方式,核对必要参数、依赖环境与输出内容,并按原始要求处理异常情况。该技能适合需要稳定复用相关能力的场景,可作为自动化工作流的一部分,也便于后续检查、调整和扩展。从功能定位来看,该技能强调把分散的操作要求整理成清晰、可复用的处理流程,使用户能够围绕既定目标快速准备输入、选择执行方式并获得结构化结果。
实际使用前应先确认任务范围、数据来源、运行环境、必要权限和关键参数,再依据技能说明逐步执行;若输入条件不完整,应先补齐信息或采用保守配置,避免因错误假设导致结果偏离需求。执行过程中需要关注工具调用是否成功、接口或依赖是否可用、输出格式是否符合预期,并对异常提示、缺失字段和边界情况进行处理;涉及批量任务时,还应保存进度,避免中断后重复操作。
部署 4 个智能体:monitor、pattern-analyzer、investigator 和 enforcer。
| 角色 | 主机名 | 技能 | 用途 |
|---|---|---|---|
| monitor | |
pilot-stream-data, pilot-event-filter, pilot-cron, pilot-metrics | 监控交易流,标记可疑行为 |
| pattern-analyzer | |
pilot-event-filter, pilot-archive, pilot-priority-queue | 对已标记交易开展行为模式分析 |
| investigator | |
pilot-task-router, pilot-audit-log, pilot-dataset | 整合证据,提出处置建议 |
| enforcer | |
pilot-blocklist, pilot-webhook-bridge, pilot-audit-log, pilot-alert | 执行拦截操作,并将拦截结果反馈至 monitor |
步骤 1: 向用户询问该智能体应承担的角色及所用前缀(prefix)。
步骤 2: 为选定角色安装对应技能:
# monitor 角色: clawhub install pilot-stream-data pilot-event-filter pilot-cron pilot-metrics # pattern-analyzer 角色: clawhub install pilot-event-filter pilot-archive pilot-priority-queue # investigator 角色: clawhub install pilot-task-router pilot-audit-log pilot-dataset # enforcer 角色: clawhub install pilot-blocklist pilot-webhook-bridge pilot-audit-log pilot-alert
步骤 3: 设置主机名,并将配置清单写入 ~/.pilot/setups/fraud-detection-pipeline.json。
步骤 4: 提示用户针对其角色,与对应对等节点(peers)发起握手(handshake)。
{
"setup": "fraud-detection-pipeline", "role": "monitor", "role_name": "Transaction Monitor",
"hostname": "-monitor",
"skills": {
"pilot-stream-data": "Ingest real-time transaction streams from payment processors.",
"pilot-event-filter": "Apply velocity checks, amount thresholds, and geo rules.",
"pilot-cron": "Run scheduled batch scans for dormant account reactivation patterns.",
"pilot-metrics": "Track flagging rates, false positive ratios, and latency."
},
"data_flows": [
{ "direction": "send", "peer": "-pattern-analyzer", "port": 1002, "topic": "flagged-transaction", "description": "Transactions exceeding risk thresholds" },
{ "direction": "receive", "peer": "-enforcer", "port": 1002, "topic": "blocked-entity", "description": "Blocked entities for rule updates" }
],
"handshakes_needed": ["-pattern-analyzer", "-enforcer"]
}
{
"setup": "fraud-detection-pipeline", "role": "pattern-analyzer", "role_name": "Pattern Analyzer",
"hostname": "-pattern-analyzer",
"skills": {
"pilot-event-filter": "Score transactions by device fingerprint, geo-velocity, and MCC patterns.",
"pilot-archive": "Store behavioral profiles and historical pattern data.",
"pilot-priority-queue": "Prioritize high-risk cases for immediate investigation."
},
"data_flows": [
{ "direction": "receive", "peer": "-monitor", "port": 1002, "topic": "flagged-transaction", "description": "Flagged transactions to analyze" },
{ "direction": "send", "peer": "-investigator", "port": 1002, "topic": "high-risk-case", "description": "High-risk cases with behavioral analysis" }
],
"handshakes_needed": ["-monitor", "-investigator"]
}
{
"setup": "fraud-detection-pipeline", "role": "investigator", "role_name": "Case Investigator",
"hostname": "-investigator",
"skills": {
"pilot-task-router": "Route cases to specialized investigation workflows.",
"pilot-audit-log": "Maintain chain-of-custody documentation for all evidence.",
"pilot-dataset": "Cross-reference against known fraud pattern databases."
},
"data_flows": [
{ "direction": "receive", "peer": "-pattern-analyzer", "port": 1002, "topic": "high-risk-case", "description": "Cases requiring investigation" },
{ "direction": "send", "peer": "-enforcer", "port": 1002, "topic": "fraud-verdict", "description": "Verdicts with recommended enforcement actions" }
],
"handshakes_needed": ["-pattern-analyzer", "-enforcer"]
}
{
"setup": "fraud-detection-pipeline", "role": "enforcer", "role_name": "Fraud Enforcer",
"hostname": "-enforcer",
"skills": {
"pilot-blocklist": "Maintain and enforce block/allow lists for cards, devices, IPs.",
"pilot-webhook-bridge": "Trigger external actions (freeze accounts, decline transactions).",
"pilot-audit-log": "Log all enforcement decisions with full justification.",
"pilot-alert": "Notify fraud operations team of high-severity enforcement actions."
},
"data_flows": [
{ "direction": "receive", "peer": "-investigator", "port": 1002, "topic": "fraud-verdict", "description": "Verdicts to enforce" },
{ "direction": "send", "peer": "-monitor", "port": 1002, "topic": "blocked-entity", "description": "Blocked entities for detection rule updates" }
],
"handshakes_needed": ["-investigator", "-monitor"]
}
monitor -> pattern-analyzer:超出风险阈值的已标记交易(端口 1002)pattern-analyzer -> investigator:含行为分析结果的高风险案件(端口 1002)investigator -> enforcer:含处置建议的欺诈判定结果(端口 1002)enforcer -> monitor:用于更新检测规则的已拦截实体(端口 1002)# 在 monitor 上 —— 标记可疑交易: pilotctl --json publish-pattern-analyzer flagged-transaction '{"txn_id":"TXN-8839201","amount":2499.99,"velocity_1h":7,"risk_score":0.78}' # 在 pattern-analyzer 上 —— 升级高风险案件: pilotctl --json publish -investigator high-risk-case '{"case_id":"FRD-4401","risk_score":0.94,"patterns":["geo_impossible","device_mismatch"]}' # 在 investigator 上 —— 发布判定结果: pilotctl --json publish -enforcer fraud-verdict '{"case_id":"FRD-4401","verdict":"confirmed_fraud","action":"block_card_and_reverse"}' # 在 enforcer 上 —— 执行拦截并反馈: pilotctl --json publish -monitor blocked-entity '{"entity_type":"card_hash","entity_id":"c4a2e","case_id":"FRD-4401"}'
需具备 pilot-protocol 技能、pilotctl 可执行文件、clawhub 可执行文件,以及一个正在运行的守护进程(daemon)。