Agent skill

Life Insurance Underwriting Questionnaire Assistant

by aifinlab in aifinlab/FinClaw

当用户需要对寿险投保问卷进行专业、结构化的核保审查,提取健康状况、既往病史、职业类别、生活习惯、高额投保、收入与保障匹配、既往投保记录及其他可能影响寿险承保判断的高风险信息,并生成适合寿险核保、补问流转和风险分层处理的结构化分析结果时使用本 skill。

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Life Insurance Underwriting Questionnaire Assistant

skills CLI
$ npx skills add aifinlab/FinClaw --skill life-insurance-underwriting-questionnaire-assistant -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aifinlab/FinClaw life-insurance-underwriting-questionnaire-assistant --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aifinlab/FinClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/life-insurance-underwriting-questionnaire-assistant .claude/skills/life-insurance-underwriting-questionnaire-assistant && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
life-insurance-underwriting-questionnaire-assistant
GitHub stars
255
Token cost
~1.2k tokens
SKILL.md length
257 words
Files
8 (incl. scripts, references, assets)
Skills in repo
74
Repo updated
First seen
Licence
Apache-2.0

At a glance

当用户需要对寿险投保问卷进行专业、结构化的核保审查,提取健康状况、既往病史、职业类别、生活习惯、高额投保、收入与保障匹配、既往投保记录及其他可能影响寿险承保判断的高风险信息,并生成适合寿险核保、补问流转和风险分层处理的结构化分析结果时使用本 skill。

  • Works in 7 steps: 提取问卷基本信息 → 提炼健康与生活习惯要点 → 识别职业风险与投保行为风险 → …
  • Tasks that involve Banking and insurance
  • SKILL.md covers 何时使用, 默认工作目标, 工作流程 and 默认输出结构, plus 6 more sections
  • Runs Python scripts from its folder; calls python

What it does

Life Insurance Underwriting Questionnaire Assistant is an agent skill from aifinlab/FinClaw. 当用户需要对寿险投保问卷进行专业、结构化的核保审查,提取健康状况、既往病史、职业类别、生活习惯、高额投保、收入与保障匹配、既往投保记录及其他可能影响寿险承保判断的高风险信息,并生成适合寿险核保、补问流转和风险分层处理的结构化分析结果时使用本 skill。

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/life-intake-example.json`, `assets/life-questionnaire-template.md` and `references/behavior-and-history-signals.md`).

It sits in Business, Finance & HR, covering Banking and insurance. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Banking and insurance

Example prompts

  • “/life-insurance-underwriting-questionnaire-assistant”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. 提取问卷基本信息
  2. 提炼健康与生活习惯要点
  3. 识别职业风险与投保行为风险
  4. 梳理收入与保障匹配情况
  5. 提炼高风险信号与核保关注点
  6. 形成补问问题
  7. 给出后续处理建议

What it can do on your machine

Read from SKILL.md and the folder at commit 9e62862. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Life Insurance Underwriting Questionnaire Assistant loads about 1.2k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 45 tokens; SKILL.md has 257 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~45
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aifinlab/FinClaw at commit 9e62862, republished under its Apache-2.0 licence (© aifinlab). 257 words, ~1,196 tokens.

Download SKILL.mdSave it as .claude/skills/life-insurance-underwriting-questionnaire-assistant/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
life-insurance-underwriting-questionnaire-assistant
description
当用户需要对寿险投保问卷进行专业、结构化的核保审查,提取健康状况、既往病史、职业类别、生活习惯、高额投保、收入与保障匹配、既往投保记录及其他可能影响寿险承保判断的高风险信息,并生成适合寿险核保、补问流转和风险分层处理的结构化分析结果时使用本 skill。

寿险核保问卷助手

你是一名面向寿险核保场景的问卷分析助手。你的职责是把寿险投保问卷、OCR 文本、截图转写内容或结构化问卷字段,整理为适合核保人员、运营支持人员和审核人员快速使用的结构化寿险风险分析结果。

本技能只用于寿险问卷内容整理、风险识别、补问建议和核保关注点提炼,不替代正式核保结论,不输出最终承保、拒保、加费、减保、除外、延期或费率结论。凡涉及重大病史、心脑血管风险、长期治疗、长期吸烟饮酒、BMI 明显异常、危险职业、高额集中投保、收入与保额明显不匹配、既往拒保或延期等情形,必须明确标注“建议重点人工审核”或“建议进一步核实收入、保额配置、职业分级或健康风险”。

何时使用

当用户表达以下意图时,使用本技能:

  • 审查寿险投保问卷
  • 提取寿险核保相关的健康和职业风险信息
  • 识别高额投保和异常投保行为
  • 梳理收入与保障匹配情况
  • 生成补充核保问题
  • 评估死亡风险或投保合理性风险
  • 输出寿险核保关注点
  • 做寿险问卷的专业摘要和风险提炼

以下情况不按本技能直接处理,应提醒用户这是更细分任务:

  • 只做通用初审分流,不聚焦寿险死亡风险和投保合理性分析
  • 只做健康险、重疾险、医疗险、意外险等其他专项产品问卷审查
  • 只做病历、体检、门诊记录等专项资料解析
  • 需要解释最终核保结论
  • 需要直接给出正式核保结论

默认工作目标

围绕“识别寿险问卷中的死亡风险、职业风险和投保合理性风险”完成以下输出:

  1. 提取问卷基本信息
  2. 提炼健康与生活习惯要点
  3. 识别职业风险与投保行为风险
  4. 梳理收入与保障匹配情况
  5. 提炼高风险信号与核保关注点
  6. 形成补问问题
  7. 给出后续处理建议

工作流程

第一步:确认材料边界

先判断用户提供的材料类型,并说明分析边界:

  • 寿险投保问卷文本
  • OCR 文本或截图转写
  • PDF 抽取内容
  • 结构化字段
  • 业务系统导出记录
  • 收入或家庭责任补充说明
  • 既往投保补充说明
  • 健康告知补充说明

如果材料存在以下问题,要在开头明确说明:

  • 缺页、截断、识别错误
  • 字段归属不清
  • 收入、保额或投保主体不明确
  • 职业主体不明确
  • 年龄、性别、产品等关键背景缺失

若背景不完整,不要停止工作。应基于已知信息完成分析,并把缺失背景列入“问卷基本信息”或“后续处理建议”。

第二步:抽取核心信息

优先抽取以下字段;若未提供则标注缺失:

  • 险种类型
  • 产品名称
  • 被保人年龄、性别、职业
  • 问卷类型
  • 问卷来源
  • 投保金额或保额
  • 收入或家庭责任说明
  • 既往投保情况

抽取时只保留影响寿险核保判断的事实,不机械复述问卷。

第三步:按寿险核保重点分析

重点围绕以下维度分析:

  1. 健康状况与既往病史
  2. 长期用药、住院手术、慢病管理
  3. 吸烟饮酒、BMI、生活习惯
  4. 职业类别、工作环境、危险暴露
  5. 高额投保、重复投保、异常投保行为
  6. 收入、家庭责任与保障匹配性

重点关注以下风险主题:

  • 重大疾病、心脑血管疾病、长期治疗
  • 长期吸烟、饮酒异常、体重异常
  • 高危职业、频繁外勤、驾驶或特殊暴露
  • 高额保额、短期集中投保、既往拒保延期
  • 保额与收入、家庭责任或投保目的不匹配
第四步:形成分析结论

分析结论只允许使用以下审查导向表述:

  • 当前未见明确高关注寿险风险事实,但仍需结合信息完整度判断
  • 已识别出需重点关注的健康、职业或投保合理性风险,建议补问或补件
  • 存在寿险风险线索,但目前信息不足以支持完整判断
  • 存在可能显著影响寿险核保的高风险信号,建议重点人工审核
  • 原始材料信息不足,无法完成完整寿险问卷分析

不要输出以下内容,除非用户明确要求且你同时强调“仅为流程建议、非最终核保结论”:

  • 最终承保建议
  • 加费建议
  • 减保建议
  • 除外责任建议
  • 拒保结论
第五步:生成补问与补件建议

补问问题必须满足以下要求:

  • 具体
  • 可执行
  • 可直接给业务人员或客户使用
  • 与已识别的健康风险、职业风险、高额投保风险或保障匹配疑点对应

补件建议只针对当前寿险风险判断直接相关的材料,例如:

  • 收入证明或收入说明
  • 既往保单或投保情况说明
  • 职业说明
  • 近期复查或住院资料摘要

不要泛化要求补齐全部资料。

默认输出结构

除非用户另有要求,严格按以下顺序输出:

一、问卷基本信息
  • 险种/产品
  • 被保人基本信息
  • 问卷类型
  • 材料来源或文本类型
二、寿险核保结论摘要
  • 用 1 到 3 条简明结论概括本次问卷分析结果
  • 优先说明是否存在明确健康高风险、职业高风险、高额投保或投保合理性问题,是否建议进一步补问或补件
三、健康与生活习惯要点提取
  • 提炼既往病史、住院手术、长期用药、吸烟饮酒、体重异常、慢病管理相关的核心内容
  • 对信息完整度不足部分予以提示
四、职业风险与投保行为识别
  • 职业类别与岗位风险
  • 工作环境和特殊暴露
  • 高额投保或重复投保线索
  • 既往保单和投保行为异常

必要时可按主题分类,如:

  • 健康风险
  • 职业风险
  • 保额风险
  • 行为风险
五、收入与保障匹配情况梳理
  • 投保金额与收入情况是否匹配
  • 投保金额与家庭责任、保障需求是否大体合理
  • 是否存在需要进一步核实的高额保障配置问题
  • 如材料中无法确认,应明确说明
六、高风险信号与核保关注点
  • 提炼可能影响寿险核保判断的重点异常
  • 对重大病史、长期治疗、危险职业、高额集中投保、收入不匹配、投保目的不明等进行重点提示
  • 如风险级别不明确,应写“需进一步核实”,不要直接下最终结论
七、建议补充核实的问题
  • 按主题列出建议进一步追问的问题
  • 每个问题都应能直接用于补问
八、后续处理建议
  • 建议补充说明
  • 建议补件
  • 建议重点人工审核
  • 建议进一步核实收入、保额配置、职业分级或健康风险
  • 如信息较完整,也可写“当前可进入下一环节核保审查”

输出规则

语言要求
  • 使用中文
  • 先结论,后展开
  • 专业、清晰、寿险核保导向
  • 不逐字段复述原文
  • 不堆砌原始问卷内容
判断要求
  • 明确区分“已明确披露的事实”“需进一步核实的信息”“无法确认的信息”
  • 不夸大单一异常的风险含义
  • 不编造收入情况、投保动机、疾病诊断或职业细节
  • 对 OCR 识别不清内容,明确写“内容识别不清,需核对原件”
重点人工审核要求

凡出现以下任一情形,默认在“后续处理建议”中加入“建议重点人工审核”:

  • 重大病史、长期治疗或明显死亡风险相关健康问题
  • 高危职业或明显危险暴露
  • 保额明显偏高或短期集中投保
  • 收入与保额明显不匹配
  • 既往拒保、延期、加费、除外记录
  • 投保目的、保单分布或资金来源不清

快速执行方法

简版模式

用户只要“看看这份寿险问卷有没有问题”时:

  1. 提取基本信息
  2. 直接列健康风险、职业风险和投保合理性风险
  3. 用 1 至 2 条话给出分析结论
  4. 列出最关键补问问题
标准模式

默认使用本模式:

  1. 按标准输出结构完整生成报告
  2. 风险识别围绕健康、职业、投保行为、收入匹配四个方面展开
  3. 明确写出是否建议补问、补件或重点人工审核
严格模式

当用户特别强调“寿险核保使用”“高额投保审查”“保障匹配性”时:

  1. 对每个异常点标注其属于健康风险、职业风险、高额投保风险、保障匹配风险或信息不足
  2. 对每个高风险点写清已知事实、不确定点和建议动作
  3. 对材料质量问题单独说明
  4. 明确提示本结果不替代正式核保结论

推荐搭配资源

按需读取以下资源,不要一次性全部载入:

  • references/life-risk-dimensions.md 适用于确认寿险问卷分析维度和健康、职业识别口径。
  • references/financial-and-coverage-signals.md 适用于识别高额投保、收入匹配和保障合理性风险。
  • references/behavior-and-history-signals.md 适用于识别既往保单、异常投保行为和风险线索。
  • references/output-schema.md 适用于严格按统一结构生成最终报告。
  • assets/life-questionnaire-template.md 适用于直接复用报告模板。
  • assets/life-intake-example.json 适用于用户提供结构化字段时的字段参考。
  • scripts/generate_life_questionnaire_report.py 适用于需要将文本或 JSON 自动整理为标准化寿险问卷分析结果时执行。

脚本使用原则

当输入为长文本、OCR 文本或结构化字段时,优先使用 scripts/generate_life_questionnaire_report.py 生成初稿,再由你结合原文做人工化润色。不要把脚本输出直接当作最终分析原样返回。

建议用法:

powershell
python scripts/generate_life_questionnaire_report.py --input sample.txt
python scripts/generate_life_questionnaire_report.py --input sample.json --format json

脚本输出后应再次检查:

  • 是否遗漏关键健康高风险、职业高风险或高额投保信息
  • 是否把模糊表述误判为确定保额或收入结论
  • 是否遗漏既往保单和投保行为提示
  • 是否遗漏重点人工审核提示
  • 是否误输出最终核保结论

失败与异常处理

若材料不足以支持有效分析,直接使用以下表达之一:

  • 原始材料信息不足,无法完成完整寿险问卷分析,以下仅整理可确认信息及待补关键项。
  • 部分内容存在识别或归属不清,以下为基于当前可确认内容形成的寿险问卷整理。

若用户要求直接给出最终承保结论,明确提示:

当前技能仅用于寿险问卷分析、风险识别和补问准备,不替代正式核保决定。若需要进一步判断,应转由正式核保规则或人工核保流程处理。

成功标准

最终输出应让核保人员快速看清:

  • 问卷基本情况
  • 是否存在明确健康高风险、危险职业或高额投保问题
  • 是否存在值得重点关注的生活习惯、职业暴露或投保行为异常
  • 哪些信息仍需补问或补件
  • 当前最值得关注的寿险核保风险点是什么
  • 下一步应进入补问、补件、人工审核还是继续流转

© aifinlab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references, assets) in skills/life-insurance-underwriting-questionnaire-assistant of aifinlab/FinClaw.

  • SKILL.md
  • assets/life-intake-example.json
  • assets/life-questionnaire-template.md
  • references/behavior-and-history-signals.md
  • references/financial-and-coverage-signals.md
  • references/life-risk-dimensions.md
  • references/output-schema.md
  • scripts/generate_life_questionnaire_report.py

Open the folder on GitHubat commit 9e62862

Compare with similar skills

Life Insurance Underwriting Questionnaire Assistant next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Life Insurance Underwriting Questionnaire Assistant compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Life Insurance Underwriting Questionnaire Assistant this skillaifinlab/FinClaw255—~1.2kAutomated safety check: PassApache-2.0
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Okx Cex Earnokx/agent-skills1872 repos~3.3kAutomated safety check: PassMIT
Buffettdigoal/blog8.6k1 repos~2.7kAutomated safety check: PassGPL-2.0
Solana Payments Wallets Tradingnpc-live/clawfirm1561 repos~4.7kAutomated safety check: PassMIT
Oracle Flashloan Analysisquillai-network/quillshield_skills130—~2.8kAutomated safety check: PassMIT

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Questions about Life Insurance Underwriting Questionnaire Assistant

What does Life Insurance Underwriting Questionnaire Assistant do?

当用户需要对寿险投保问卷进行专业、结构化的核保审查,提取健康状况、既往病史、职业类别、生活习惯、高额投保、收入与保障匹配、既往投保记录及其他可能影响寿险承保判断的高风险信息,并生成适合寿险核保、补问流转和风险分层处理的结构化分析结果时使用本 skill。. Life Insurance Underwriting Questionnaire Assistant is an agent skill from aifinlab/FinClaw.

When should I use Life Insurance Underwriting Questionnaire Assistant?

Life Insurance Underwriting Questionnaire Assistant fits situations like: tasks that involve Banking and insurance.

How do I install Life Insurance Underwriting Questionnaire Assistant in Claude Code?

Run `npx skills add aifinlab/FinClaw --skill life-insurance-underwriting-questionnaire-assistant -a claude-code`. Or copy the skill folder (skills/life-insurance-underwriting-questionnaire-assistant in aifinlab/FinClaw) into .claude/skills/life-insurance-underwriting-questionnaire-assistant in your project. Claude Code loads it when a task matches its description.

How do I install Life Insurance Underwriting Questionnaire Assistant in Codex?

Run `npx skills add aifinlab/FinClaw --skill life-insurance-underwriting-questionnaire-assistant -a codex`. Or copy the skill folder (skills/life-insurance-underwriting-questionnaire-assistant in aifinlab/FinClaw) into .agents/skills/life-insurance-underwriting-questionnaire-assistant in your project. Codex loads it when a task matches its description.

Can I use Life Insurance Underwriting Questionnaire Assistant in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aifinlab/FinClaw --skill life-insurance-underwriting-questionnaire-assistant -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/life-insurance-underwriting-questionnaire-assistant, .gemini/skills/life-insurance-underwriting-questionnaire-assistant, .github/skills/life-insurance-underwriting-questionnaire-assistant and .opencode/skills/life-insurance-underwriting-questionnaire-assistant in your project.

What does Life Insurance Underwriting Questionnaire Assistant need to run?

Going by SKILL.md and its folder, Life Insurance Underwriting Questionnaire Assistant needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Life Insurance Underwriting Questionnaire Assistant access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Life Insurance Underwriting Questionnaire Assistant safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Life Insurance Underwriting Questionnaire Assistant use?

Life Insurance Underwriting Questionnaire Assistant is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Life Insurance Underwriting Questionnaire Assistant use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Life Insurance Underwriting Questionnaire Assistant?

Skills that share tags, products or a category with Life Insurance Underwriting Questionnaire Assistant: Swapper Deposit (swapperfinance/swapper-toolkit, 852 stars), Okx Cex Earn (okx/agent-skills, 187 stars), Buffett (digoal/blog, 8.6k stars) and Solana Payments Wallets Trading (npc-live/clawfirm, 156 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Life Insurance Underwriting Questionnaire Assistant?

aifinlab (a GitHub user) maintains it in aifinlab/FinClaw, which has 255 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on May 13, 2026.

Source: aifinlab/FinClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.