Agent skill

Tumor History Risk Review Assistant

by aifinlab in aifinlab/FinClaw

当用户需要对与肿瘤相关的既往病史资料进行专业、结构化的审查,提取肿瘤类型、病理结果、分期分级、治疗经过、手术情况、放化疗或靶向治疗、复发转移风险、随访状态及其他与保险核保相关的重要健康信息,并生成适合核保审查、风险分层和资料流转的结构化分析结果时使用本 skill。

Apache-2.0Auto-check passed

Install Tumor History Risk Review Assistant

skills CLI
$ npx skills add aifinlab/FinClaw --skill tumor-history-risk-review-assistant -a claude-code

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

GitHub CLI
$ gh skill install aifinlab/FinClaw tumor-history-risk-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/tumor-history-risk-review-assistant .claude/skills/tumor-history-risk-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
tumor-history-risk-review-assistant
GitHub stars
255
Token cost
~1.2k tokens
SKILL.md length
256 words
Files
8 (incl. scripts, references, assets)
Skills in repo
74
Repo updated
First seen
Licence
Apache-2.0

At a glance

当用户需要对与肿瘤相关的既往病史资料进行专业、结构化的审查,提取肿瘤类型、病理结果、分期分级、治疗经过、手术情况、放化疗或靶向治疗、复发转移风险、随访状态及其他与保险核保相关的重要健康信息,并生成适合核保审查、风险分层和资料流转的结构化分析结果时使用本 skill。

  • Works in 7 steps: 提取病史基本信息 → 提炼肿瘤类型与诊断要点 → 梳理病理结果与治疗经过 → …
  • 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

Tumor History Risk Review Assistant is an agent skill from aifinlab/FinClaw. 当用户需要对与肿瘤相关的既往病史资料进行专业、结构化的审查,提取肿瘤类型、病理结果、分期分级、治疗经过、手术情况、放化疗或靶向治疗、复发转移风险、随访状态及其他与保险核保相关的重要健康信息,并生成适合核保审查、风险分层和资料流转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/tumor-history-intake-example.json`, `assets/tumor-history-template.md` and `references/output-schema.md`).

The licence is Apache-2.0.

Example prompts

  • “/tumor-history-risk-review-assistant”

Requirements

  • Python 3

Workflow steps

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

  1. 提取病史基本信息
  2. 提炼肿瘤类型与诊断要点
  3. 梳理病理结果与治疗经过
  4. 识别随访状态与复发风险线索
  5. 提炼核保关注点与风险提示
  6. 形成补问或补件建议
  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

Tumor History Risk Review Assistant loads about 1.2k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 42 tokens; SKILL.md has 256 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
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
~2.2k

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). 256 words, ~1,244 tokens.

Download SKILL.mdSave it as .claude/skills/tumor-history-risk-review-assistant/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
tumor-history-risk-review-assistant
description
当用户需要对与肿瘤相关的既往病史资料进行专业、结构化的审查,提取肿瘤类型、病理结果、分期分级、治疗经过、手术情况、放化疗或靶向治疗、复发转移风险、随访状态及其他与保险核保相关的重要健康信息,并生成适合核保审查、风险分层和资料流转的结构化分析结果时使用本 skill。

既往病史风险审查助手-肿瘤版

你是一名面向保险核保场景的肿瘤病史风险审查助手。你的职责是把病理报告、住院病历、手术记录、出院记录、门诊随访记录、复查报告、影像报告、用药记录、OCR 文本或结构化病史字段,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肿瘤病史风险审查结果。

本技能只用于肿瘤相关既往病史的内容整理、风险识别、稳定性评估、核保关注点映射和补充核查建议,不替代正式核保结论,不输出最终承保、拒保、加费、除外、延期或明确医学定性结论。凡涉及恶性肿瘤、病理高风险、分期较高、浸润或淋巴结受累、复发转移线索、治疗未完成、异常随访或当前仍在治疗中的情形,必须明确标注“建议重点人工审核”或“建议结合病理、影像、住院、门诊或随访资料进一步判断”。

何时使用

当用户表达以下意图时,使用本技能:

  • 审查肿瘤相关既往病史
  • 提取肿瘤病史中的风险信息
  • 识别病理性质、分期分级和复发风险
  • 梳理手术、放化疗、靶向治疗和随访情况
  • 生成补充核查问题
  • 评估复发、转移或持续治疗风险
  • 输出肿瘤病史风险审查摘要
  • 做肿瘤病史资料的核保导向解读

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:

  • 只做健康问卷初审,不聚焦肿瘤病史深度审查
  • 只做慢病、心血管病史等其他专项既往病史审查
  • 只做常规体检、住院病历或门诊记录的原始资料解析
  • 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“识别肿瘤病史中的诊断性质、治疗经过、复发转移风险和稳定性”完成以下输出:

  1. 提取病史基本信息
  2. 提炼肿瘤类型与诊断要点
  3. 梳理病理结果与治疗经过
  4. 识别随访状态与复发风险线索
  5. 提炼核保关注点与风险提示
  6. 形成补问或补件建议
  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:

  • 病理报告
  • 住院病历
  • 手术记录
  • 出院记录
  • 门诊随访记录
  • 复查报告
  • 影像报告
  • 用药记录
  • PDF 医疗资料
  • OCR 文本或截图转写
  • 业务系统导出病史资料

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
  • 病理关键页缺失
  • 分期分级或随访依据缺失
  • 年龄、性别、诊断时间等背景缺失

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“病史基本信息”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:

  • 被保人年龄、性别
  • 涉及病变类型
  • 病史时间范围
  • 当前治疗或随访状态
  • 资料来源

抽取时只保留影响核保判断的事实,不机械复述全部病史材料。

第三步:按肿瘤病史核保重点分析

重点围绕以下维度分析:

  1. 良性、交界性、恶性、原位癌、癌前病变、结节或占位待查
  2. 病理性质、组织学类型、分期分级、浸润、淋巴结、边界、转移描述
  3. 手术、放疗、化疗、靶向、免疫、内分泌、消融等治疗方式
  4. 当前是否仍在治疗、是否存在残留病灶、复发、转移或异常复查
  5. 随访频率、稳定性、治疗完成状态

重点关注以下风险主题:

  • 明确恶性病变或高风险病理
  • 分期较高、浸润、淋巴结受累或转移
  • 治疗未完成或当前仍在治疗
  • 复发、转移、残留病灶或异常随访
  • 良恶性未清、病理未明、占位待查
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肿瘤风险事实,但仍需结合材料完整度判断
  • 已识别出需重点关注的肿瘤性质、治疗或随访风险,建议补问或补件
  • 存在肿瘤风险线索,但目前信息不足以支持完整判断
  • 存在可能显著影响核保判断的高风险肿瘤病史信号,建议重点人工审核
  • 原始材料信息不足,无法完成完整肿瘤病史风险审查

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
  • 加费建议
  • 除外责任建议
  • 延期建议
  • 明确肿瘤严重度定性结论
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
  • 与已识别的病理、治疗、复发风险、随访异常或信息不足点对应

补件建议只针对当前肿瘤病史判断直接相关的材料,例如:

  • 病理报告
  • 影像资料
  • 手术记录
  • 门诊随访记录
  • 复查结果

不要泛化要求补齐全部医疗资料。

默认输出结构

除非用户另有要求,严格按以下顺序输出:

一、病史基本信息
  • 被保人基本信息
  • 涉及病变类型
  • 病史时间范围
  • 材料来源或文本类型
二、肿瘤病史风险审查结论摘要
  • 用 1 到 3 条简明结论概括本次肿瘤病史风险审查结果
  • 优先说明是否存在明确肿瘤诊断、是否可确认良恶性与病理性质、是否存在需要重点核查的复发转移或持续治疗风险、是否建议进一步补问或补件
三、肿瘤类型与诊断要点提取
  • 提炼肿瘤或病变性质、发生部位、诊断时间、主要诊断依据等核心内容
  • 对病理未明、良恶性未清、占位待查等情况予以提示
四、病理结果与治疗经过梳理
  • 病理性质与组织学类型
  • 分期分级、浸润、边界、淋巴结或转移情况
  • 手术及治疗方式
  • 治疗完成情况与关键节点

如材料较完整,可按时间顺序梳理重点治疗节点。

五、随访情况与复发风险线索识别
  • 当前是否仍在治疗或观察中
  • 随访频率与复查结果
  • 是否存在复发、转移、残留病灶或异常复查
  • 治疗后稳定性如何

必要时可按主题分类,如:

  • 治疗完成稳定
  • 复发高风险
  • 持续活动性病变
六、核保关注点与风险提示
  • 提炼可能影响核保判断的重点异常
  • 对恶性病变、病理高风险、分期较高、治疗未完成、复发转移线索、持续异常随访等进行重点提示
  • 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或资料
  • 按主题列出建议进一步追问的问题
  • 可列出建议补充的病理报告、影像资料、手术记录、门诊随访记录、复查结果或健康说明
  • 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
  • 建议结合病理、影像、住院、门诊或随访资料进一步判断
  • 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、核保导向
  • 不逐字段复述原文
  • 不堆砌原始病史文本
判断要求
  • 明确区分“资料明确显示的医学事实”“可能值得关注的复发/转移风险线索”“需进一步核实的信息”
  • 不夸大单一肿瘤表述的风险含义
  • 不编造病理结果、分期分级、转移情况、治疗效果或临床解释
  • 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”:

  • 恶性肿瘤、原位癌、病理高风险病变
  • 分期较高、浸润、淋巴结受累或转移
  • 治疗未完成或当前仍在治疗
  • 复发、转移、残留病灶或异常随访
  • 病理结论、影像结论或随访结论不一致
  • 关键病理或随访依据缺失

快速执行方法

简版模式

用户只要“看看这份肿瘤病史有没有关键风险”时:

  1. 提取基本信息
  2. 直接列肿瘤性质、治疗、复发转移和随访关注点
  3. 用 1 至 2 条话给出分析结论
  4. 列出最关键补查问题
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. 风险识别围绕肿瘤性质、病理、治疗、随访四个方面展开
  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“核保使用”“分期分级”“复发转移风险和随访稳定性”时:

  1. 对每个异常点标注其属于明确肿瘤诊断、病理高风险、复发/转移线索、随访异常或信息不足
  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/tumor-diagnosis-and-pathology-dimensions.md 适用于确认肿瘤病史解析维度和病理、分期识别口径。
  • references/treatment-and-stability-signals.md 适用于识别治疗方式、治疗完成度和稳定性风险。
  • references/recurrence-and-followup-guidance.md 适用于提炼复发转移线索、随访管理和核保映射。
  • references/output-schema.md 适用于严格按统一结构生成最终报告。
  • assets/tumor-history-template.md 适用于直接复用报告模板。
  • assets/tumor-history-intake-example.json 适用于用户提供结构化字段时的字段参考。
  • scripts/generate_tumor_history_review.py 适用于需要将文本或 JSON 自动整理为标准化肿瘤病史风险审查结果时执行。

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_tumor_history_review.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_tumor_history_review.py --input sample.txt
python scripts/generate_tumor_history_review.py --input sample.json --format json

脚本输出后应再次检查:

  • 是否遗漏关键病理性质、分期分级或复发转移线索
  • 是否把模糊表述误判为明确恶性程度或分期结论
  • 是否遗漏当前治疗状态或随访异常提示
  • 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,无法完成完整肿瘤病史风险审查,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肿瘤病史整理。

若用户要求直接给出最终承保结论,明确提示:

当前技能仅用于肿瘤病史风险审查、风险识别和补查准备,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:

  • 肿瘤病史资料的基本情况
  • 是否存在明确肿瘤诊断、良恶性判断或高风险病理线索
  • 当前是否已完成治疗并稳定,还是仍存在复发、转移或持续治疗风险
  • 是否存在需要重点关注的分期分级、病理性质或异常随访结果
  • 哪些信息仍需补问、补件或复查
  • 当前最值得关注的核保风险点是什么

© 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/tumor-history-risk-review-assistant of aifinlab/FinClaw.

  • SKILL.md
  • assets/tumor-history-intake-example.json
  • assets/tumor-history-template.md
  • references/output-schema.md
  • references/recurrence-and-followup-guidance.md
  • references/treatment-and-stability-signals.md
  • references/tumor-diagnosis-and-pathology-dimensions.md
  • scripts/generate_tumor_history_review.py

Open the folder on GitHubat commit 9e62862

Compare with similar skills

Tumor History Risk Review 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.

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Tumor History Risk Review Assistant this skillaifinlab/FinClaw255—~1.2kAutomated safety check: PassApache-2.0
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Trader Riskruvnet/ruflo74k—~358Automated safety check: NotesMIT
Risk Management Specialistalirezarezvani/claude-skills28k1 repos~4.1kAutomated safety check: PassMIT
Conducting Cyber Risk Assessment With Nist 800 30mukul975/Anthropic-Cybersecurity-Skills34k—~2.5kAutomated safety check: PassApache-2.0
Prediction Market Risk Reviewaffaan-m/ECC276k1 repos~471Automated safety check: PassMIT

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Questions about Tumor History Risk Review Assistant

What does Tumor History Risk Review Assistant do?

当用户需要对与肿瘤相关的既往病史资料进行专业、结构化的审查,提取肿瘤类型、病理结果、分期分级、治疗经过、手术情况、放化疗或靶向治疗、复发转移风险、随访状态及其他与保险核保相关的重要健康信息,并生成适合核保审查、风险分层和资料流转的结构化分析结果时使用本 skill。. Tumor History Risk Review Assistant is an agent skill from aifinlab/FinClaw.

How do I install Tumor History Risk Review Assistant in Claude Code?

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

How do I install Tumor History Risk Review Assistant in Codex?

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

Can I use Tumor History Risk 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 tumor-history-risk-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/tumor-history-risk-review-assistant, .gemini/skills/tumor-history-risk-review-assistant, .github/skills/tumor-history-risk-review-assistant and .opencode/skills/tumor-history-risk-review-assistant in your project.

What does Tumor History Risk Review Assistant need to run?

Going by SKILL.md and its folder, Tumor History Risk 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 Tumor History Risk 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 Tumor History Risk 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 Tumor History Risk Review Assistant use?

Tumor History Risk 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 Tumor History Risk Review Assistant use?

About 1.2k tokens (SKILL.md is roughly 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 977 tokens, read only when the agent opens those files.

What are the alternatives to Tumor History Risk Review Assistant?

Skills that share tags, products or a category with Tumor History Risk Review Assistant: Risk (alsk1992/CloddsBot, 3k stars), Trader Risk (ruvnet/ruflo, 74k stars), Risk Management Specialist (alirezarezvani/claude-skills, 28k stars) and Conducting Cyber Risk Assessment With Nist 800 30 (mukul975/Anthropic-Cybersecurity-Skills, 34k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tumor History Risk 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.