What is the primary focus of the OpenEvidence Observability skill?

It focuses on monitoring the performance, accuracy, and compliance of clinical evidence queries within the OpenEvidence ecosystem for medical software.

How does it track citation accuracy?

It provides instrumentation templates for measuring citation accuracy rates and evidence age, alerting developers if data becomes stale or falls below accuracy thresholds.

Can I customize the alerting thresholds?

Yes, the skill provides a configurable alerting framework that allows you to set specific warning and critical thresholds for your medical application's needs.

What specific metrics can I monitor with this skill?

You can monitor P95 query response times, evidence freshness (median age), citation accuracy, API error rates, and audit log integrity.

Does this skill help with HIPAA compliance?

Yes, it includes structured logging patterns and audit log completeness checks designed to meet regulatory requirements while ensuring patient identifiers are not logged.

OpenEvidence Observability

Name: OpenEvidence Observability
Author: jeremylongshore

byjeremylongshore

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2,024

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Analíticas y Monitorización

Implements comprehensive monitoring, citation tracking, and HIPAA-compliant auditing for OpenEvidence clinical queries.

The OpenEvidence Observability skill provides Claude Code with specialized patterns for monitoring clinical evidence queries where accuracy and timing are critical for patient safety. It offers a standardized framework for tracking P95 latency, evidence freshness, and citation accuracy while maintaining the strict audit logs required for healthcare compliance. By utilizing the provided instrumentation and health check logic, developers can ensure their clinical decision support systems remain reliable, up-to-date, and compliant with HIPAA and medical standards.

Características Principales

01Evidence freshness and citation accuracy monitoring

02Automated alerting rules for critical healthcare metrics

03Clinical query latency and error rate tracking

04HIPAA-compliant structured logging templates

052,024 GitHub stars

06Pre-configured health check dashboards for system status

Casos de Uso

01Monitoring clinical decision support systems for response accuracy

02Detecting stale medical citations in healthcare applications

03Ensuring HIPAA compliance via automated and secure audit logging

Características Principales

01Evidence freshness and citation accuracy monitoring

02Automated alerting rules for critical healthcare metrics

03Clinical query latency and error rate tracking

04HIPAA-compliant structured logging templates

052,024 GitHub stars

06Pre-configured health check dashboards for system status

Casos de Uso

01Monitoring clinical decision support systems for response accuracy

02Detecting stale medical citations in healthcare applications

03Ensuring HIPAA compliance via automated and secure audit logging