Skill UI

This comprehensive checklist guides the deployment of AI agents into a live production environment. It covers critical areas including security best practices (API key management, SSO), robust error handling, monitoring setup, operational runbooks, and compliance adherence (HIPAA, GDPR). Use this when validating an agent for go-live to ensure maximum reliability and stability.

This comprehensive guide defines the secure data lifecycle management for OpenEvidence, an AI-powered platform for clinical evidence synthesis. It outlines data classification (e.g., clinical queries, patient responses), strict adherence to global regulations (HIPAA, GDPR, FDA), and technical requirements for handling Protected Health Information (PHI). Key processes include PHI de-identification, data validation, secure API integration, and compliant data export, ensuring the system maintains the highest level of patient privacy and regulatory compliance.

This skill provides a complete guide to deploying a containerized OpenEvidence clinical evidence integration service using Docker. It establishes a HIPAA-conscious production environment, enabling secure connections to the OpenEvidence API. Users can query clinical evidence, retrieve summarized medical literature, and validate treatment recommendations, all while maintaining audit logging and data-at-rest encryption compliance. Includes setup for health checks and rolling updates.

This system implements Role-Based Access Control (RBAC) for OpenEvidence, an AI-powered clinical decision support platform. It strictly manages access to sensitive data, including PHI-adjacent datasets and medical literature, ensuring compliance with regulations like HIPAA. The system defines distinct roles—Admin, Clinician, Researcher, Student, and Auditor—with granular permissions for querying, data export, and institutional configuration, maintaining a secure and auditable data environment.

This guide outlines the strict multi-environment setup for the OpenEvidence clinical AI system, crucial for maintaining HIPAA compliance. It details how to configure and validate separate environments (Development, Staging, Production) to manage different data classifications—synthetic, de-identified, and full PHI. The process emphasizes environment validation checks, BAA adherence, and robust audit logging to prevent regulatory violations and PHI exposure.

Provides comprehensive observability for OpenEvidence, a system delivering critical clinical evidence queries. It monitors key metrics such as query response latency (p95), evidence freshness, citation accuracy, and compliance audit logs (HIPAA). Essential for ensuring timely, accurate, and regulatory-compliant patient care information retrieval.

This comprehensive checklist guides the secure and compliant deployment of OpenEvidence, a clinical decision support system. It covers critical requirements for handling Protected Health Information (PHI), including HIPAA-grade security, robust API integration best practices, mandatory monitoring setup, and resilience testing. Use this guide to ensure your healthcare-adjacent system meets the highest standards of compliance and reliability.

This comprehensive reference architecture guides the integration of OpenEvidence into clinical decision support systems (CDS). It is designed for healthcare platforms needing evidence-based query processing, deterministic citation tracking, and full audit logging. Key considerations include HIPAA compliance, optimizing for sub-second response times in point-of-care workflows, and establishing robust data models and event pipelines.

This guide provides essential security protocols and coding best practices for integrating with OpenEvidence, a platform processing Protected Health Information (PHI). It covers mandatory topics such as HIPAA compliance, API key management, webhook signature verification, input validation, and data redaction, ensuring all interactions are secure and audit-compliant.

A comprehensive guide for auditing and ensuring regulatory compliance (SOC2, GDPR, HIPAA) when integrating Large Language Models (LLMs) via OpenRouter. It covers best practices for data handling, access control, PII redaction, implementing robust audit trails, and configuring provider routing to maintain data sovereignty and meet strict industry standards.

This skill simulates an expert cybersecurity auditor specializing in DevSecOps methodologies and comprehensive security assurance. It guides users through running detailed security audits, performing threat modeling, and assessing vulnerabilities (e.g., IDOR). Capabilities cover SAST, DAST, cloud security posture, zero-trust architectures, and compliance adherence to major frameworks like GDPR, HIPAA, and PCI-DSS, ensuring security is integrated throughout the entire SDLC.

This expert simulates a compliance expert, specializing in regulatory requirements for software systems, including GDPR, HIPAA, SOC2, and PCI-DSS. It performs comprehensive audits, identifies compliance gaps, and generates actionable implementation plans, technical controls, and policy templates to ensure adherence to industry standards.