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Agent Skill · 研究检索

afrexai-insurance-automation(Afrexai 保险自动化)

afrexai-insurance-automation 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

afrexai-insurance-automation 是研究检索类 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 7,546。

总安装 18,689周安装 771GitHub Stars 公开资料未说明下载 6,106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:afrexai-insurance-automation(Afrexai 保险自动化)
来源仓库:https://github.com/1kalin/afrexai-insurance-automation
安装命令:
openclaw skills install afrexai-insurance-automation
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 afrexai-insurance-automation

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

根据行业基准自动化保险工作流程,包括承保、理赔分类、保单管理、续保、合规性和经纪人运营。

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 afrexai-insurance-automation;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

afrexai-insurance-automation 怎么安装?

在终端执行 openclaw skills install afrexai-insurance-automation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

afrexai-insurance-automation 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。

afrexai-insurance-automation 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。

afrexai-insurance-automation 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。

afrexai-insurance-automation 用的人多吗?

公开数据是累计安装 18,689 次,近一周安装 771 次,下载 6,106 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。

afrexai-insurance-automation 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
afrexai-insurance-automation

Afrexai 保险自动化 · 本页

18,689—需要联网MIT-0有提醒

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

Insurance Operations Automation

Comprehensive insurance operations framework for AI agents. Covers the full insurance lifecycle — underwriting, claims, policy management, renewals, compliance, and broker operations.

What This Skill Does

Guides your AI agent through insurance-specific workflows with industry benchmarks, regulatory requirements, and automation priorities.

Capabilities

1. Underwriting Assessment

  • Risk scoring framework (12 factors, weighted by line of business)
  • Data enrichment checklist (credit, claims history, property data, telematics)
  • Referral triggers and authority limits by tier
  • Combined ratio targets by line: Auto (95-98%), Home (85-92%), Commercial (88-95%), Life (varies by mortality table)

2. Claims Processing Pipeline

  • FNOL intake automation (voice + digital, structured extraction)
  • Severity triage: Green (auto-approve <$2K) → Yellow (adjuster review $2K-$25K) → Red (SIU referral >$25K or fraud indicators)
  • Subrogation identification triggers
  • Reserve estimation formulas by claim type
  • Settlement authority matrix

3. Policy Administration

  • Quote-to-bind workflow (target: <15 min for personal lines)
  • Mid-term adjustment processing
  • Renewal scoring: retention probability model (7 factors)
  • Cancellation/non-renewal compliance by state/jurisdiction

4. Broker Operations (Jointly AI Model)

  • 5-agent pipeline architecture: Intake → Research → Quoting → Analysis → Delivery
  • Market panel management and placement optimization
  • Quote comparison normalization across carriers
  • FCA/state regulatory compliance verification
  • Parallel execution: up to 4 simultaneous carrier interactions

5. Compliance & Regulatory

  • US: State DOI requirements, NAIC model laws, Solvency II (reinsurers)
  • UK: FCA handbook (ICOBS, SYSC), Consumer Duty, IDD compliance
  • EU: Solvency II, IDD, GDPR for policyholder data
  • Anti-fraud indicators (SIU trigger list — 15 red flags)
  • SAR/suspicious activity reporting thresholds

6. Insurance Metrics Dashboard

MetricPersonal Lines TargetCommercial Target
Combined Ratio95-98%88-95%
Loss Ratio60-70%55-65%
Expense Ratio25-32%28-35%
Claims Settlement Time<48h (auto)<14 days
Policy Issuance Time<15 min<24h
Renewal Rate>85%>80%
Quote-to-Bind Ratio>25%>15%
NPS>40>35

7. Automation Priority Matrix

ProcessHours/Month (50-person broker)Agent-Ready?Expected Savings
Quote comparison160hYes — now$140K-$280K/yr
FNOL intake120hYes — now$105K-$210K/yr
Policy document generation80hYes — now$70K-$140K/yr
Renewal processing100hYes — now$87K-$175K/yr
Compliance checks60hYes — now$52K-$105K/yr
Subrogation identification40hPartial$35K-$70K/yr
Complex claims adjustment200hHuman-in-loop$50K-$100K/yr

8. Insurance-Specific Agent Prompts

Underwriting Agent:

You are an underwriting assessment agent. For each submission:
1. Extract all risk factors from the application
2. Score each factor against the risk matrix (1-10 scale)
3. Calculate composite risk score (weighted by line of business)
4. Flag any referral triggers (prior losses >3 in 5yr, credit <600, high-hazard occupation)
5. Recommend: Auto-approve / Refer to senior / Decline with reason
6. Generate underwriting memo with supporting data

Claims Triage Agent:

You are a claims triage agent. For each FNOL:
1. Extract: date of loss, type, description, estimated amount, policyholder details
2. Verify active coverage and applicable endorsements
3. Assign severity: Green (<$2K auto-process) / Yellow ($2K-$25K adjuster) / Red (>$25K or fraud flags)
4. Check fraud indicators against the 15-point SIU trigger list
5. Set initial reserve based on claim type benchmarks
6. Route to appropriate handler with priority score

90-Day Deployment Roadmap

Month 1: Deploy intake + quote comparison agents. Target: 70% of personal lines quotes handled autonomously.

Month 2: Add claims triage + policy document generation. Target: FNOL processing <5 minutes, auto-approval for Green claims.

Month 3: Compliance monitoring + renewal automation. Target: 85%+ renewal rate, zero compliance gaps.

Cost Framework

  • Solo broker/MGA: $2K-$5K/month (2-3 agents)
  • Mid-size broker (20-50 staff): $5K-$15K/month (5-8 agents)
  • Carrier/large broker (100+ staff): $15K-$50K/month (10-20 agents)

Resources

  • Calculate your insurance automation ROI → AI Revenue Leak Calculator
  • Full Insurance & Fintech Context Pack → AfrexAI Context Packs — $47, includes fintech agent configurations, compliance frameworks, and industry benchmarks
  • Configure your insurance agent stack → Agent Setup Wizard
  • Bundle: Pick 3 packs for $97 | All 10 for $197 | Everything $247

平台分布

OpenClaw

80.08%
按下载量换算4,890

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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