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china-hospital-recommendation中国医院推荐

Agent Skill

china-hospital-recommendation 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。

总安装

3,669

周安装

147

GitHub Stars

1

下载量

1,188
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:china-hospital-recommendation(中国医院推荐)
来源仓库:https://github.com/helenalhq/china-hospital-recommendation
安装命令:
openclaw skills install china-hospital-recommendation
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 china-hospital-recommendation

简介

为来华医疗旅游患者推荐匹配医院与专科医生,提供英文评估报告。

  • 适用于疑难病症转诊、高端体检预约与国际保险对接等跨境医疗服务。
  • 结合患者病史与症状描述筛选三甲医院资源,输出治疗方案概要与费用预估。
  • 安装命令:openclaw skills install china-hospital-recommendation;需接入卫健委备案医疗机构数据库。
  • 注意医疗建议不能替代面诊,紧急情况请立即前往急诊科就医。

SKILL.md

name
China-hospital-recommendation-report
description
Generate English hospital recommendation reports for medical travel to China, hospital matching, and redo orders. Use when needs to turn user intake data into a premium deliverable with exactly 3 recommended hospitals by default, specialist-direction guidance, cost and logistics advice, evidence notes, and final Markdown/PDF export. Triggers on mentions of China hospital report, custom China medical travel report, China hospital matching deliverable, report redo, or premium PDF export.

Hospital Recommendation Report

Overview

Generate a self-contained premium report for paid users who need hospital matching guidance in China. The skill carries its own product brief, ranking snapshot, recommendation method, search policy, schema, and PDF rules; do not depend on repo-external references when using it.

Resources To Read

Workflow

  1. Confirm the task is a paid deliverable, not a casual answer.
  2. Read the product brief and schema before drafting.
  3. Map the condition to one or more specialties with references/specialty-mapping.md.
  4. Use references/fudan-rankings-2025.md as the static ranking baseline. Do not search the web for Fudan rankings during generation.
  5. Search only for dynamic facts allowed by references/search-policy.md, such as international services, department pages, specialist public profiles, JCI status, visa, transportation, and accommodation.
  6. Build a ReportResearchModel, separating static facts, current search-backed facts, and recommendation judgments.
  7. Produce a RenderedReportModel in English. Default to exactly 3 hospitals unless the payload includes a justified expansion reason. Prefer structured access-evidence and scenario-cost fields when the evidence is available.
  8. Run scripts/render_report.py to export Markdown and PDF.
  9. Review the output against references/quality-checklist.md before returning it.

Output Rules

  • Default delivery language is patient-facing English.
  • Default hospital count is 3.
  • Include specialist direction or department-lead guidance for the case; do not invent named doctors when public evidence is thin.
  • When staging, pathology, receptor status, or treatment sequence are still unclear, default specialist guidance to evaluation-first or MDT-first rather than procedure-first.
  • Keep hospital Chinese names as supporting labels only.
  • Treat JCI as a positive recommendation factor when verified, but not as a hard requirement.
  • Use evidence notes to explain what came from the bundled ranking baseline and what needs current verification.
  • Separate administrative intake, record-review workflow, and doctor-led remote consultation. Do not imply teleconsult availability unless it is explicitly verified.
  • Prefer scenario-based cost framing. If costs are high-uncertainty, say so directly instead of presenting a false sense of precision.
  • Keep the report scoped to hospital matching, specialist direction, cost guidance, travel logistics, next steps, and disclaimer text.
  • For PDF delivery, prefer the built-in reportlab premium renderer; keep Markdown as the editable intermediate artifact and use the pandoc path only as fallback.
  • Follow the ChinaMed design-system palette for premium PDF styling instead of inventing a separate visual theme.
  • Always append the ChinaMed Select consult-service sentence to the final Disclaimer in both Markdown and PDF output.

Export

Generate Markdown and PDF:

python3 .agents/skills/hospital-recommendation-report/scripts/render_report.py input.json --output-dir output

Generate Markdown only:

python3 .agents/skills/hospital-recommendation-report/scripts/render_report.py input.json --output-dir output --skip-pdf

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

93.07%
按下载量换算1,106

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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