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#

• references/product-brief.md: report purpose, user promise, and scope boundaries
• references/report-schema.md: ReportRequest, ReportResearchModel, and RenderedReportModel
• references/specialty-mapping.md: convert case descriptions into Fudan specialty keys
• references/fudan-rankings-2025.md: bundled static ranking baseline
• references/recommendation-method.md: hospital and specialist recommendation logic
• references/search-policy.md: what may be searched at generation time
• references/pdf-spec.md: premium PDF expectations
• references/quality-checklist.md: final QA gate

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:

bash

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

Generate Markdown only:

bash

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