cva-healthcare-pipeline

Automate LGPD-compliant medical content generation with HTML, PDF, and CMS-ready outputs.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/joaopelegrino/hello-word-closure --skill cva-healthcare-pipeline
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cva-healthcare-pipeline
Source: https://github.com/joaopelegrino/hello-word-closure/tree/main/.claude-plugin/clojure-vertex-adk/skills/cva-healthcare-pipeline
Command: npx skills add https://github.com/joaopelegrino/hello-word-closure --skill cva-healthcare-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solves? Generating regulated medical content manually is time-consuming, expensive, and prone to compliance errors. This Skill provides a complete, production-validated 5-system AI pipeline that automates content creation while ensuring strict adherence to LGPD, CFM, CRP, and ANVISA regulations, drastically reducing time and cost.

Core Features & Use Cases

  • End-to-End Automation: Covers LGPD data extraction, claims identification, scientific reference search, SEO optimization, and final content consolidation.
  • Validated ROI: Achieved 99.4% time reduction (4h 15min to 1.5min) and 92.4% cost reduction (R$ 192.50 to R$ 14.70) in a real healthcare clinic.
  • Full Compliance: Integrates automated checks for LGPD data protection, CFM/CRP professional ethics, and ANVISA health regulations, ensuring audit readiness.
  • Use Case: A mental health clinic needs to publish 20 new blog posts monthly. This pipeline automates the entire process, from initial text to a WordPress-ready article, ensuring scientific accuracy, SEO, and legal compliance, freeing up 81 hours of human labor per month.

Quick Start

Provide raw medical text and content requirements to the pipeline. The pipeline will automatically extract sensitive data, identify claims, search for scientific references, optimize for SEO, and consolidate into a compliant, publishable article.

Frequently Asked Questions about cva-healthcare-pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate LGPD-compliant medical content generation for healthcare publishing?

Automated LGPD-compliant medical content generation extracts sensitive data safely, validates medical claims against scientific references, optimizes for SEO, and consolidates into audit-ready HTML, PDF, and CMS exports. This pipeline reduces manual content creation time by 99.4% while ensuring CFM, CRP, and ANVISA regulatory adherence.

Can I use an automated pipeline to ensure my healthcare content meets LGPD, CFM, and ANVISA regulations?

Yes. The pipeline integrates automated compliance checks for LGPD data protection, CFM/CRP professional ethics, and ANVISA health regulations into every stage—from data extraction through final consolidation—creating audit-ready output without manual compliance review.

What's the best way to publish regulated medical blog posts at scale without compliance errors?

An end-to-end automation pipeline handles claims identification, scientific reference validation, SEO optimization, and multi-format consolidation while enforcing data protection and mandatory medical disclaimers. Real-world validation shows 92.4% cost reduction and 81 hours of monthly labor savings for publishing workflows.

How does automated medical content generation handle sensitive patient data extraction?

Data sanitization and consent management systems anonymize sensitive information before LLM processing, ensuring LGPD compliance. The pipeline extracts regulated medical content while protecting personally identifiable data, maintaining audit trails throughout the workflow.

Do I need separate tools to validate medical claims and search scientific references?

No. The integrated pipeline combines claims extraction, evidence ranking of references, and scientific validation within a single workflow, eliminating the need to chain multiple tools while maintaining regulatory compliance and consistency.