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med-critical-disease-review

v1.0.1

重大疾病理赔智能评估(支持 28 种病种)。输入住院病历结构化数据,调用内网评估接口,输出原始 JSON 与自然语言结论(结论 + 证据)。

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for unisound-llm/med-critical-disease-review.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "med-critical-disease-review" (unisound-llm/med-critical-disease-review) from ClawHub.
Skill page: https://clawhub.ai/unisound-llm/med-critical-disease-review
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install med-critical-disease-review

ClawHub CLI

Package manager switcher

npx clawhub@latest install med-critical-disease-review
Security Scan
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medium confidence
Purpose & Capability
The skill's stated purpose — calling an assessment service for 28 major-disease types — matches the code which builds a medicalRecord payload and posts it to an external assessment API (major_disease_assess.call_major_disease_assess). However SKILL.md also references an internal IP (http://10.10.20.15:9010) while the code's BASE_URL is https://shangbao.yunzhisheng.cn/..., which is an inconsistency you should confirm (different endpoints imply different network exposure).
!
Instruction Scope
The documentation claims strict desensitization and 'no local persistence', but the visible code does not implement any de-identification/PII redaction logic (validate_payload only checks structure) and the code writes the API response and natural-language output to disk by default (../runs/med-major-disease-assess/{disease}_resp.*). That contradicts the SKILL.md privacy promises and widens data exposure (sensitive medical data will be transmitted to a remote endpoint and may be saved locally unless you pass custom options).
Install Mechanism
This is an instruction+script skill with no install spec — no packages are force-installed. It optionally uses standard third-party Python packages (openpyxl, pypdf) and external binaries (libreoffice/soffice, pdftotext, tesseract) for input parsing. Those are expected for document processing and are documented as optional.
Credentials
The skill does not request environment variables or credentials (no secrets required), which is proportionate. However it will perform outbound HTTP(s) requests to shangbao.yunzhisheng.cn (and SKILL.md mentions an internal IP alternative). Because the payload contains medical records, network transmission to an external service is a privacy risk and should be validated against your data policies.
!
Persistence & Privilege
The skill is not marked always:true (no forced global enable), but despite SKILL.md claiming 'no local persistence', the code saves raw JSON and text outputs to disk by default and can create ../runs directories. That persistence behavior contradicts the documented guarantee and increases the attack surface for sensitive data on disk.
What to consider before installing
Key things to check before installing or running this skill: - Endpoint sanity: Confirm which endpoint will actually receive medical data — the SKILL.md mentions an internal IP (10.10.20.15:9010) but the code posts to https://shangbao.yunzhisheng.cn/.... Ask the maintainer which endpoint is intended and whether it is within your trusted network. - Privacy promises vs. code behavior: The README claims PII will be stripped and nothing is persisted, but the visible code does not show any de-identification and it writes API responses and text summaries to ../runs by default. If you need to send PHI, require a proof of the redaction implementation or add a validation step yourself. Consider running with synthetic data first. - Network/data exposure: This skill will transmit structured medical records to a remote service. If your organization restricts outbound network traffic for sensitive health data, run the skill in an isolated environment or block outbound access until you can verify the endpoint and its retention/processing policies. - Local persistence: If you want to avoid files being written, run with explicit output paths (or inspect/run the code and remove/write-protection for save points). Search the full run.py for any other write operations (the provided run.py was truncated in the package listing). - Testing and audit: Review the full run.py (the package listing is truncated) to confirm there are no hidden calls or additional endpoints. Test using non-sensitive sample records that simulate structure but contain no real patient identifiers. Given these inconsistencies (endpoints, privacy claims vs code writes), treat the skill as suspicious until the author clarifies the redaction logic, the actual network destination, and data retention behavior.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🏥 Clawdis
latestvk97fcgvqx0z2d8q83wdz7wqc2n85edd6
81downloads
0stars
2versions
Updated 4d ago
v1.0.1
MIT-0

重大疾病理赔评估

概述

给定一份住院病历(结构化 medicalRecord,含诊断/文书等),本技能调用内网评估服务,对 任意重大疾病病种 进行判定,并返回:

  • 最终结论:符合/不符合(来自 final_result
  • 原因与证据:按条件逐条给出 evidence(可带来源 source)
  • 原始结果:接口返回的完整 JSON(便于追溯与二次加工)

数据安全、隐私与伦理声明

  • 最小必要原则:仅处理完成评估所必需的数据字段;不要求提供与评估无关的身份信息。
  • 严格脱敏:在发送至任何模型/接口前,会对可识别个人身份的信息进行脱敏/去标识化处理(如姓名、证件号、手机号、详细地址、人脸/影像等)。仅传递脱敏后的必要信息用于本次 skill 调用。
  • 不做本地持久化:不将用户输入与中间结果写入本地持久化存储(包含磁盘文件、数据库、日志)。仅在内存中短暂处理;本次调用结束即销毁
  • 第三方 API 风险提示:在功能需要时,可能会调用第三方模型/服务接口;此时仅会发送脱敏后的必要信息,并使用加密传输。除完成本次请求外,不用于任何其他用途(如训练、画像、营销)。
  • 医疗边界:本技能输出为理赔条款/条件匹配与证据整理的辅助信息,不构成医疗诊断或治疗建议;如涉及临床判断请以执业医生意见为准。

支持病种(28)

  • 心脏瓣膜手术:heart_valve_surgery
  • 主动脉手术:aortic_surgery
  • 冠状动脉搭桥术:coronary_artery_bypass
  • 重大器官或造血干细胞移植术:major_organ_transplant
  • 恶性肿瘤——重度:malignant_tumor
  • 严重慢性肾衰竭:severe_chronic_kidney_failure
  • 严重慢性肝衰竭:severe_chronic_liver_failure
  • 急性重症肝炎或亚急性重症肝炎:acute_severe_hepatitis
  • 严重慢性呼吸衰竭:severe_chronic_respiratory_failure
  • 严重特发性肺动脉高压:severe_idiopathic_pulmonary_hypertension
  • 严重脑损伤:severe_brain_injury
  • 深度昏迷:deep_coma
  • 严重脑中风后遗症:severe_stroke_sequelae
  • 严重阿尔茨海默病:severe_alzheimers_disease
  • 严重原发性帕金森病:severe_primary_parkinsons_disease
  • 严重运动神经元病:severe_motor_neuron_disease
  • 严重脑炎后遗症或严重脑膜炎后遗症:severe_brain_encephalitis_sequelae
  • 严重非恶性颅内肿瘤:severe_non_malignant_intracranial_tumor
  • 瘫痪:paralysis
  • 双耳失聪:bilateral_deafness
  • 双目失明:bilateral_blindness
  • 语言能力丧失:language_ability_loss
  • 严重克罗恩病:severe_crohn_disease
  • 严重溃疡性结肠炎:severe_ulcerative_colitis
  • 重型再生障碍性贫血:severe_aplastic_anemia
  • 较重急性心肌梗死:moderate_acute_myocardial_infarction
  • 严重Ⅲ度烧伤:severe_third_degree_burn
  • 多个肢体缺失:multiple_limb_loss

输入格式

请求为 JSON(示例见 ../data/med-major-disease-assess/req_data.json),最少需要包含:

  • medicalRecord:病历结构化对象
    • mainDiagName / otherDiagName:诊断信息(字符串/JSON 字符串均可)
    • docs:文书列表(每个 doc 至少包含 docType 与文本字段,如 format_page_text

也支持通过统一入口 scripts/run.py 直接输入 pdf/doc/docx/xls/xlsx/csv/txt/json。 预处理成功后,会先归一化为最小可用的 medicalRecord.docs[] JSON,再调用本 skill 的原始评估逻辑。

最小校验(先校验,再审核)

脚本会先对入参做最小结构校验,校验通过后才会调用审核接口:

  • 请求体必须是 JSON object
  • 必须包含 medicalRecord(object)
  • medicalRecord.docs 必须是非空数组
  • docs 中至少一项包含 docType

后端接口

  • HTTP API:http://10.10.20.15:9010/api/v1/assessment/assess/{disease}?model_type=qwq
  • Content-Type:application/json

快速开始

# 在本目录下运行(统一入口)
python3 scripts/run.py \
  --disease aortic_surgery \
  --input ../data/med-major-disease-assess/req_data.json

# 或继续直接使用原始 medicalRecord JSON 入口
python3 scripts/major_disease_assess.py \
  --disease aortic_surgery \
  --input ../data/med-major-disease-assess/req_data.json

参数说明

  • --disease STRING
    • 病种类型(如:aortic_surgeryheart_valve_surgery 等)。
  • --input PATH
    • 输入请求 JSON 路径(UTF-8)。
  • --output-json PATH
    • 保存接口原始返回 JSON(默认:../runs/med-major-disease-assess/{disease}_resp.json)。
  • --output-text PATH
    • 保存自然语言结论文本(默认:../runs/med-major-disease-assess/{disease}_resp.txt)。
  • --model-type STRING
    • 查询参数 model_type(默认:qwq)。
  • --timeout SECONDS
    • HTTP 超时秒数(默认:60)。

统一入口附加参数(scripts/run.py

  • --input-type auto|pdf|doc|docx|xls|xlsx|csv|txt|json
    • 输入类型;默认 auto
  • --sheet STRING
    • 读取 Excel 时指定 sheet(可选)。
  • --encoding STRING
    • txt/csv 编码(默认:utf-8)。
  • --save-prepared
    • 保存预处理后的 medicalRecord JSON,便于调试。

输出约定

  • 若指定输出路径的父目录不存在,会自动创建。
  • 自然语言输出默认包含:
    • 结论(符合/不符合)
    • 原因(final_result.reason
    • 逐条条件的证据(conditions[*].evidence,并附 source/description

依赖

运行环境

  • Python 3.7+

外部 API

  • 后端评估服务:https://shangbao.yunzhisheng.cn/skills/critical-disease/api/v1/assessment/assess/{disease}
    • 方法:POST,Content-Type: application/json
    • 需要网络访问 shangbao.yunzhisheng.cn

Python 第三方包(可选,按输入格式需要)

包名用途必要条件
openpyxl读取 .xlsx 文件输入为 xlsx 时必须
pypdf提取 PDF 文本输入为 pdf 时必须(或用 pdftotext 替代)

安装:pip install openpyxl pypdf

外部工具(可选,按输入格式需要)

工具用途必要条件
LibreOffice (soffice)转换 .doc / .xls 为文本输入为 doc/xls 时必须
pdftotext(poppler-utils)提取 PDF 文本输入为 pdf 且未安装 pypdf 时必须
tesseract(含 chi_sim+eng 语言包)图片 OCR输入为 png/jpg/bmp/tif 等图片时必须

安装(Ubuntu/Debian):sudo apt-get install libreoffice poppler-utils tesseract-ocr tesseract-ocr-chi-sim

仅使用 JSON 输入时,无需安装任何第三方包或外部工具。

备注

  • 发布约束:示例输入、运行输出、自测脚本均放在 skill 包外(分别位于 ../data/../runs/../self_tests/),skill 目录内仅保留可发布的核心文件(scripts/SKILL.md_meta.json)。

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