Token导航 LogoToken导航

Agent Skill · 开发

pilot-fraud-detection-pipeline-setup(试点欺诈检测管道设置)

pilot-fraud-detection-pipeline-setup 用于辅助部署、云资源、容器和基础设施运维,适合在 OpenClaw 中需要检查配置、整理部署步骤或排查环境问题时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

pilot-fraud-detection-pipeline-setup 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 9,355。

总安装 2,747周安装 118GitHub Stars 公开资料未说明下载 963核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pilot-fraud-detection-pipeline-setup(试点欺诈检测管道设置)
来源仓库:https://github.com/teoslayer/pilot-fraud-detection-pipeline-setup
安装命令:
openclaw skills install pilot-fraud-detection-pipeline-setup
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install pilot-fraud-detection-pipeline-setup

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

部署由4个代理构成的欺诈检测管道,支持实时交易监控与风险升级机制。适用于支付平台、电商平台等需快速识别异常行为的业务场景。通过OpenClaw安装后自动初始化规则引擎与告警模块。需配置敏感数据脱敏策略,防止误判影响用户体验。

pilot-fraud-detection-pipeline-setup 属于开发类 Skill,可作为该场景下的辅助能力补充。建议定期更新模型阈值并审计历史检测结果以确保准确性。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install pilot-fraud-detection-pipeline-setup;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

pilot-fraud-detection-pipeline-setup 怎么安装?

在终端执行 openclaw skills install pilot-fraud-detection-pipeline-setup。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pilot-fraud-detection-pipeline-setup 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

pilot-fraud-detection-pipeline-setup 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

pilot-fraud-detection-pipeline-setup 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pilot-fraud-detection-pipeline-setup 用的人多吗?

公开数据是累计安装 2,747 次,近一周安装 118 次,下载 963 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

pilot-fraud-detection-pipeline-setup 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
pilot-fraud-detection-pipeline-setup

试点欺诈检测管道设置 · 本页

2,747—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
pilot-fraud-detection-pipeline-setup
description
>
tags
license
AGPL-3.0
metadata
author
vulture-labs
version
1.0
openclaw
requires
bins
homepage
https://pilotprotocol.network
allowed-tools

Fraud Detection Pipeline Setup

Deploy 4 agents: monitor, pattern-analyzer, investigator, and enforcer.

Roles

RoleHostnameSkillsPurpose
monitor<prefix>-monitorpilot-stream-data, pilot-event-filter, pilot-cron, pilot-metricsWatches transactions, flags suspicious activity
pattern-analyzer<prefix>-pattern-analyzerpilot-event-filter, pilot-archive, pilot-priority-queueBehavioral analysis on flagged transactions
investigator<prefix>-investigatorpilot-task-router, pilot-audit-log, pilot-datasetAssembles evidence, recommends actions
enforcer<prefix>-enforcerpilot-blocklist, pilot-webhook-bridge, pilot-audit-log, pilot-alertExecutes blocks, feeds back to monitor

Setup Procedure

Step 1: Ask the user which role this agent should play and what prefix to use.

Step 2: Install the skills for the chosen role:

# For monitor:
clawhub install pilot-stream-data pilot-event-filter pilot-cron pilot-metrics
# For pattern-analyzer:
clawhub install pilot-event-filter pilot-archive pilot-priority-queue
# For investigator:
clawhub install pilot-task-router pilot-audit-log pilot-dataset
# For enforcer:
clawhub install pilot-blocklist pilot-webhook-bridge pilot-audit-log pilot-alert

Step 3: Set the hostname and write the manifest to ~/.pilot/setups/fraud-detection-pipeline.json.

Step 4: Tell the user to initiate handshakes with the peers for their role.

Manifest Templates Per Role

monitor

{
  "setup": "fraud-detection-pipeline", "role": "monitor", "role_name": "Transaction Monitor",
  "hostname": "<prefix>-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": "<prefix>-pattern-analyzer", "port": 1002, "topic": "flagged-transaction", "description": "Transactions exceeding risk thresholds" },
    { "direction": "receive", "peer": "<prefix>-enforcer", "port": 1002, "topic": "blocked-entity", "description": "Blocked entities for rule updates" }
  ],
  "handshakes_needed": ["<prefix>-pattern-analyzer", "<prefix>-enforcer"]
}

pattern-analyzer

{
  "setup": "fraud-detection-pipeline", "role": "pattern-analyzer", "role_name": "Pattern Analyzer",
  "hostname": "<prefix>-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": "<prefix>-monitor", "port": 1002, "topic": "flagged-transaction", "description": "Flagged transactions to analyze" },
    { "direction": "send", "peer": "<prefix>-investigator", "port": 1002, "topic": "high-risk-case", "description": "High-risk cases with behavioral analysis" }
  ],
  "handshakes_needed": ["<prefix>-monitor", "<prefix>-investigator"]
}

investigator

{
  "setup": "fraud-detection-pipeline", "role": "investigator", "role_name": "Case Investigator",
  "hostname": "<prefix>-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": "<prefix>-pattern-analyzer", "port": 1002, "topic": "high-risk-case", "description": "Cases requiring investigation" },
    { "direction": "send", "peer": "<prefix>-enforcer", "port": 1002, "topic": "fraud-verdict", "description": "Verdicts with recommended enforcement actions" }
  ],
  "handshakes_needed": ["<prefix>-pattern-analyzer", "<prefix>-enforcer"]
}

enforcer

{
  "setup": "fraud-detection-pipeline", "role": "enforcer", "role_name": "Fraud Enforcer",
  "hostname": "<prefix>-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": "<prefix>-investigator", "port": 1002, "topic": "fraud-verdict", "description": "Verdicts to enforce" },
    { "direction": "send", "peer": "<prefix>-monitor", "port": 1002, "topic": "blocked-entity", "description": "Blocked entities for detection rule updates" }
  ],
  "handshakes_needed": ["<prefix>-investigator", "<prefix>-monitor"]
}

Data Flows

  • monitor -> pattern-analyzer : flagged transactions exceeding risk thresholds (port 1002)
  • pattern-analyzer -> investigator : high-risk cases with behavioral analysis (port 1002)
  • investigator -> enforcer : fraud verdicts with recommended actions (port 1002)
  • enforcer -> monitor : blocked entities to update detection rules (port 1002)

Workflow Example

# On monitor -- flag suspicious transaction:
pilotctl --json publish <prefix>-pattern-analyzer flagged-transaction '{"txn_id":"TXN-8839201","amount":2499.99,"velocity_1h":7,"risk_score":0.78}'
# On pattern-analyzer -- escalate high-risk case:
pilotctl --json publish <prefix>-investigator high-risk-case '{"case_id":"FRD-4401","risk_score":0.94,"patterns":["geo_impossible","device_mismatch"]}'
# On investigator -- issue verdict:
pilotctl --json publish <prefix>-enforcer fraud-verdict '{"case_id":"FRD-4401","verdict":"confirmed_fraud","action":"block_card_and_reverse"}'
# On enforcer -- block and feed back:
pilotctl --json publish <prefix>-monitor blocked-entity '{"entity_type":"card_hash","entity_id":"c4a2e","case_id":"FRD-4401"}'

Dependencies

Requires pilot-protocol skill, pilotctl binary, clawhub binary, and a running daemon.

平台分布

OpenClaw

97.92%
按下载量换算943

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills