ClawHub

China Hospital Recommendation

Data & APIs

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.

Install

openclaw skills install china-hospital-recommendation

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
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