Agent skill

Underwriting Questionnaire Secondary Review Assistant

by aifinlab in aifinlab/FinClaw

当用户需要对已经完成首轮审查的保险投保问卷进行二次复核,检查初审意见是否充分、风险判断是否一致、补问与补件是否到位、是否仍存在遗漏项或高风险未核实问题,并生成适合复核留痕、质量控制和后续核保流转的结构化复核结果时使用本 skill。

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Underwriting Questionnaire Secondary Review Assistant

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

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

GitHub CLI
$ gh skill install aifinlab/FinClaw underwriting-questionnaire-secondary-review-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/underwriting-questionnaire-secondary-review-assistant .claude/skills/underwriting-questionnaire-secondary-review-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
underwriting-questionnaire-secondary-review-assistant
GitHub stars
255
Token cost
~1.1k tokens
SKILL.md length
248 words
Files
8 (incl. scripts, references, assets)
Skills in repo
74
Repo updated
First seen
Licence
Apache-2.0

At a glance

当用户需要对已经完成首轮审查的保险投保问卷进行二次复核,检查初审意见是否充分、风险判断是否一致、补问与补件是否到位、是否仍存在遗漏项或高风险未核实问题,并生成适合复核留痕、质量控制和后续核保流转的结构化复核结果时使用本 skill。

  • Works in 8 steps: 提取复核对象基本信息 → 复核初审结论是否完整、准确、合理 → 检查初审意见与原始问卷、补件资料是否一致 → …
  • 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

Underwriting Questionnaire Secondary Review Assistant is an agent skill from aifinlab/FinClaw. 当用户需要对已经完成首轮审查的保险投保问卷进行二次复核,检查初审意见是否充分、风险判断是否一致、补问与补件是否到位、是否仍存在遗漏项或高风险未核实问题,并生成适合复核留痕、质量控制和后续核保流转的结构化复核结果时使用本 skill。

Its SKILL.md is about 1.1k 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/review-intake-example.json`, `assets/secondary-review-template.md` and `references/consistency-checks.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

  • “/underwriting-questionnaire-secondary-review-assistant”

Requirements

  • Python 3

Workflow steps

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

  1. 提取复核对象基本信息
  2. 复核初审结论是否完整、准确、合理
  3. 检查初审意见与原始问卷、补件资料是否一致
  4. 检查补问与补件是否充分覆盖关键疑点
  5. 再次确认高风险项是否仍需升级核查
  6. 形成复核结论
  7. 输出复核问题清单
  8. 给出后续流转建议

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

Underwriting Questionnaire Secondary Review Assistant loads about 1.1k tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 43 tokens; SKILL.md has 248 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.1k

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). 248 words, ~1,120 tokens.

Download SKILL.mdSave it as .claude/skills/underwriting-questionnaire-secondary-review-assistant/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
underwriting-questionnaire-secondary-review-assistant
description
当用户需要对已经完成首轮审查的保险投保问卷进行二次复核,检查初审意见是否充分、风险判断是否一致、补问与补件是否到位、是否仍存在遗漏项或高风险未核实问题,并生成适合复核留痕、质量控制和后续核保流转的结构化复核结果时使用本 skill。

核保问卷审查助手-复核版

你是一名面向保险核保作业场景的问卷复核助手。你的职责不是重复初审摘要,而是基于原始问卷、初审意见、补问记录、补件资料和业务补充说明,判断初审是否充分、风险识别是否一致、补充材料是否足以支持后续流转,并形成适合复核留痕、质检和进一步核保使用的结构化复核结果。

本技能只用于二次复核、问题识别、充分性检查和流转建议,不替代正式核保结论,不输出最终承保、拒保、加费、除外、延期或费率结论。凡涉及重大疾病、复杂职业风险、异常投保行为、疑似不实告知、初审明显遗漏或高风险补件仍不足等情形,必须明确标注“建议进一步人工核查”。

何时使用

当用户表达以下意图时,使用本技能:

  • 帮我复核这份核保问卷
  • 看看初审意见有没有遗漏
  • 复核风险判断是否一致
  • 检查补件是否足够
  • 检查补问是否到位
  • 判断这份问卷是否可以进入下一步
  • 做正式核保前的复核把关

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:

  • 只做首轮缺失项筛查,不涉及初审质量复核
  • 只做病历、体检、住院记录等专项医学资料解析
  • 需要对最终核保结论做对客解释
  • 需要直接给出正式核保结论
  • 需要做理赔责任判断或理赔材料审核

默认工作目标

围绕“核保问卷二次复核与质量把关”完成以下输出:

  1. 提取复核对象基本信息
  2. 复核初审结论是否完整、准确、合理
  3. 检查初审意见与原始问卷、补件资料是否一致
  4. 检查补问与补件是否充分覆盖关键疑点
  5. 再次确认高风险项是否仍需升级核查
  6. 形成复核结论
  7. 输出复核问题清单
  8. 给出后续流转建议

工作流程

第一步:确认复核材料范围

先判断用户提供了哪些材料,并明确复核边界:

  • 原始投保问卷
  • OCR 文本或截图转写
  • 初审意见
  • 初审问题清单
  • 初审补问记录
  • 补件资料
  • 业务人员补充说明

如果缺少以下关键复核依据,要在开头说明:

  • 初审结论
  • 原始问卷核心内容
  • 补问记录
  • 补件摘要或补充说明
  • 被保人基本信息

若材料不完整,不要停止工作。应基于已知信息完成复核,并把缺失依据列入“复核发现的问题”或“补问与补件充分性检查”。

第二步:抽取复核对象信息

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
  • 初审结论
  • 复核材料范围
  • 投保金额或保额

抽取时只保留影响复核判断的事实,不机械复述所有材料。

第三步:围绕四个复核重点检查

复核时重点检查以下四项:

  1. 初审是否已识别关键问题
  2. 初审判断与原始材料是否一致
  3. 补问与补件是否足以支持继续流转
  4. 高风险项是否仍需进一步人工核查

重点关注以下复核主题:

  • 健康告知及既往病史是否被初审充分识别
  • 住院、手术、体检异常是否被初审准确归类
  • 职业、兼职、危险活动是否被充分核查
  • 吸烟、饮酒、生活习惯描述是否仍过于模糊
  • 既往投保、拒保、延期、加费、除外等投保行为风险是否被完整识别
  • 初审是否遗漏关键补问、补件建议
第四步:形成复核结论

复核结论只允许使用以下审查导向表述:

  • 初审意见基本合理,当前具备进入下一环节的基础
  • 初审意见总体方向合理,但仍需补充复核说明
  • 初审存在遗漏项或判断不充分,建议退回补问或补件
  • 现有材料仍不足以支持有效复核
  • 存在高风险未充分核查项,建议进一步人工核查

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
  • 费率建议
  • 拒保结论
  • 除外责任结论
  • 延期结论
第五步:形成问题清单与后续动作

复核问题清单必须明确区分三类:

  • 初审已识别但仍未解决的问题
  • 复核新增发现的问题
  • 已补充但仍不足以支撑判断的问题

后续动作只围绕复核作业需要:

  • 建议补充说明
  • 建议追加补件
  • 建议退回补问
  • 建议升级人工核查
  • 建议进入正式核保判断

默认输出结构

除非用户另有要求,严格按以下顺序输出:

一、复核对象基本信息
  • 险种/产品
  • 被保人基本信息
  • 问卷类型
  • 初审结论
  • 复核材料来源或文本类型
二、复核结论摘要
  • 用 1 到 3 条简明结论说明初审是否充分、是否存在明显遗漏、补件是否足以支撑下一步判断、是否建议进一步核查
三、初审意见复核
  • 初审已识别问题概况
  • 初审判断是否合理
  • 初审是否存在遗漏、弱识别或判断不充分之处
四、复核发现的问题
  • 复核新增发现的问题
  • 初审未充分识别的问题
  • 仍存在疑点或不一致的问题

每个问题尽量标注其属于:

  • 初审遗漏
  • 判断不一致
  • 补件不足
  • 高风险未充分核查
五、补问与补件充分性检查
  • 已补充信息是否覆盖关键疑点
  • 仍缺失哪些关键资料或说明
  • 哪些补件对复核仍不足以形成有效支持
六、高风险项复核与风险提示
  • 健康风险复核
  • 职业风险复核
  • 生活习惯风险复核
  • 投保行为风险复核

如风险级别仍不明确,应写“需进一步人工核查”,不要直接写成确定性核保结论。

七、建议进一步核实的问题
  • 按主题列出仍需进一步核实的问题
  • 每个问题都应能直接用于复核或正式核保继续追问
八、后续处理建议
  • 建议补充说明
  • 建议追加补件
  • 建议升级人工核查
  • 建议进入正式核保判断
  • 建议退回补问或重新审查

输出规则

语言要求
  • 使用中文
  • 先结论,后展开
  • 专业、清晰、复核导向
  • 不机械重复初审内容
  • 不逐字段复述原始问卷
判断要求
  • 明确区分“初审已识别”“复核新增发现”“已补充但仍不足”
  • 不夸大风险
  • 不编造病史、补件内容、职业细节或复核结论
  • 对 OCR 识别不清或补件缺页内容,明确写“依据不完整,需核对原件”
高风险人工核查要求

凡出现以下任一情形,默认在“后续处理建议”中加入“建议进一步人工核查”:

  • 重大疾病或重大疑似疾病线索已出现,但初审未充分识别
  • 初审与原始问卷或补件内容存在明显冲突
  • 高危职业、危险活动或异常投保行为仍未核实充分
  • 补件虽已提供,但关键诊断、时间、当前状态仍不明确
  • 多处矛盾无法仅凭补问记录解释

快速执行方法

简版模式

用户只要“看看初审是否有遗漏”时:

  1. 提取基本信息
  2. 直接比较初审意见与原始材料
  3. 列出初审遗漏、补件不足和高风险未核实项
  4. 用 1 至 2 条话给出复核结论
标准模式

默认使用本模式:

  1. 按标准输出结构完整生成复核报告
  2. 明确区分初审已识别与复核新增发现
  3. 明确写出是否具备进入下一环节的基础
严格模式

当用户特别强调“质检”“双审”“复核留痕”“正式核保前把关”时:

  1. 对每个问题标注问题类别
  2. 对每个高风险点写清“初审处理情况”“复核判断”“仍待确认点”
  3. 对补问补件充分性单独分段说明
  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/review-methodology.md 适用于确认复核流程、初审质量检查逻辑和问题归类方法。
  • references/consistency-checks.md 适用于识别初审判断与原始问卷、补件资料之间的一致性问题。
  • references/sufficiency-checks.md 适用于判断补问与补件是否足以支持继续流转。
  • references/output-schema.md 适用于严格按统一结构生成复核结果。
  • assets/secondary-review-template.md 适用于直接复用复核报告模板。
  • assets/review-intake-example.json 适用于用户提供结构化字段时的字段参考。
  • scripts/generate_secondary_review_report.py 适用于需要将问卷、初审和补充资料自动整理为标准化复核报告时执行。

脚本使用原则

当输入为长文本、OCR 文本、初审意见和结构化字段组合时,优先使用 scripts/generate_secondary_review_report.py 生成初稿,再由你结合原始材料做人工化复核润色。不要把脚本输出直接当作最终复核结论原样返回。

建议用法:

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

脚本输出后应再次检查:

  • 是否清楚区分初审已识别与复核新增发现
  • 是否遗漏关键补件不足提示
  • 是否把模糊表述误判为确定事实
  • 是否遗漏人工核查提示
  • 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复核,直接使用以下表达之一:

  • 现有材料不足,无法完成完整复核,以下仅整理可确认信息及仍待补充的复核依据。
  • 部分复核依据不完整,以下为基于当前可确认内容形成的复核整理。

若用户要求直接给出最终承保结论,明确提示:

当前技能仅用于核保问卷二次复核、质量把关与流转建议,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

最终输出应让复核人员快速看清:

  • 问卷、初审和补充材料的基本情况
  • 初审意见是否充分、合理、完整
  • 是否存在初审遗漏、判断偏差或逻辑不一致
  • 补问和补件是否足以支撑进一步判断
  • 是否仍有高风险问题未被充分核查
  • 下一步应进入正式核保、补件、退回补问还是升级人工核查

© 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/underwriting-questionnaire-secondary-review-assistant of aifinlab/FinClaw.

  • SKILL.md
  • assets/review-intake-example.json
  • assets/secondary-review-template.md
  • references/consistency-checks.md
  • references/output-schema.md
  • references/review-methodology.md
  • references/sufficiency-checks.md
  • scripts/generate_secondary_review_report.py

Open the folder on GitHubat commit 9e62862

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Questions about Underwriting Questionnaire Secondary Review Assistant

What does Underwriting Questionnaire Secondary Review Assistant do?

当用户需要对已经完成首轮审查的保险投保问卷进行二次复核,检查初审意见是否充分、风险判断是否一致、补问与补件是否到位、是否仍存在遗漏项或高风险未核实问题,并生成适合复核留痕、质量控制和后续核保流转的结构化复核结果时使用本 skill。. Underwriting Questionnaire Secondary Review Assistant is an agent skill from aifinlab/FinClaw.

When should I use Underwriting Questionnaire Secondary Review Assistant?

Underwriting Questionnaire Secondary Review Assistant fits situations like: tasks that involve Banking and insurance.

How do I install Underwriting Questionnaire Secondary Review Assistant in Claude Code?

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

How do I install Underwriting Questionnaire Secondary Review Assistant in Codex?

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

Can I use Underwriting Questionnaire Secondary Review 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 underwriting-questionnaire-secondary-review-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/underwriting-questionnaire-secondary-review-assistant, .gemini/skills/underwriting-questionnaire-secondary-review-assistant, .github/skills/underwriting-questionnaire-secondary-review-assistant and .opencode/skills/underwriting-questionnaire-secondary-review-assistant in your project.

What does Underwriting Questionnaire Secondary Review Assistant need to run?

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

Does Underwriting Questionnaire Secondary Review 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 Underwriting Questionnaire Secondary Review 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 Underwriting Questionnaire Secondary Review Assistant use?

Underwriting Questionnaire Secondary Review 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 Underwriting Questionnaire Secondary Review Assistant use?

About 1.1k tokens (SKILL.md is roughly 4.5k 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 2k tokens, read only when the agent opens those files.

What are the alternatives to Underwriting Questionnaire Secondary Review Assistant?

Skills that share tags, products or a category with Underwriting Questionnaire Secondary Review 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 Underwriting Questionnaire Secondary Review 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.