AGENT SKILL

openevidence-prod-checklist

Production readiness checklist for OpenEvidence clinical AI deployments. Use when preparing for production launch, conducting pre-deployment reviews, or auditing OpenEvidence integration for compliance. Trigger with phrases like "openevidence production", "openevidence go-live", "openevidence checklist", "deploy openevidence", "openevidence readiness".

适用职业律师与法务
License 许可
MIT
最近更新
2026-11-12
Stars
★ 2.0k
Forks
231

01 前言 Front Matter

name
openevidence-prod-checklist
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
version
1.0.0
description
Production readiness checklist for OpenEvidence clinical AI deployments. Use when preparing for production launch, conducting pre-deployment reviews, or auditing OpenEvidence integration for compliance. Trigger with phrases like "openevidence production", "openevidence go-live", "openevidence checklist", "deploy openevidence", "openevidence readiness".
allowed-tools
Read, Grep

03 SKILL.md 正文

OpenEvidence Production Checklist

Overview

Comprehensive checklist for deploying OpenEvidence clinical AI integrations to production healthcare environments.

Prerequisites

  • Completed development and testing phases
  • Signed BAA with OpenEvidence
  • Security review completed
  • Compliance team sign-off

Production Readiness Checklist

1. Legal & Compliance

  • [ ] Business Associate Agreement (BAA) signed

  • [ ] API Terms of Service accepted

  • [ ] Clinical use disclaimers in place

    • All clinical outputs must include appropriate disclaimers
    • "For informational purposes only. Verify with current guidelines."
  • [ ] Liability and malpractice considerations reviewed

    • Legal review of clinical decision support usage
  • [ ] Data processing agreement documented

    • What data is sent, stored, processed

2. Security

  • [ ] Production API keys generated

    • Separate keys from development/staging
    • Stored in secret manager (not environment variables)
  • [ ] Key rotation schedule established

    • Recommend: 90-day rotation cycle
  • [ ] IP allowlist configured (if available)

    • Restrict API access to known IP ranges
  • [ ] TLS 1.2+ enforced

    • No fallback to older protocols
  • [ ] PHI sanitization implemented

    • Review openevidence-security-basics
  • [ ] Webhook signature verification active

    • All webhook endpoints validate signatures
  • [ ] Audit logging enabled

    • HIPAA-compliant access logging
    • Minimum 6-year retention

3. Infrastructure

  • [ ] High availability configuration

    // Multiple API endpoints for failover
    const config = {
      primaryEndpoint: 'https://api.openevidence.com',
      fallbackEndpoint: 'https://api-fallback.openevidence.com',
      timeout: 30000,
      retries: 3,
    };
    
  • [ ] Circuit breaker implemented

    import CircuitBreaker from 'opossum';
    
    const breaker = new CircuitBreaker(clinicalQuery, {
      timeout: 30000,
      errorThresholdPercentage: 50,
      resetTimeout: 30000,
    });
    
  • [ ] Rate limit handling configured

    • Review openevidence-rate-limits
    • Request queuing for traffic spikes
  • [ ] Timeout configuration appropriate

    • Clinical queries: 15-30s
    • DeepConsult: 5-10 minutes
  • [ ] Health check endpoint implemented

    app.get('/health/openevidence', async (req, res) => {
      try {
        await client.health.check();
        res.json({ status: 'healthy' });
      } catch (error) {
        res.status(503).json({ status: 'unhealthy', error: error.message });
      }
    });
    

4. Monitoring & Alerting

  • [ ] Metrics collection active

    • Request count, latency, error rate
    • Review openevidence-observability
  • [ ] Alert rules configured

    Alert Threshold Severity
    Error rate > 5% 5 min window Warning
    Error rate > 20% 5 min window Critical
    P95 latency > 15s 5 min window Warning
    Health check failed 2 consecutive Critical
  • [ ] Dashboard created

    • Real-time visibility into OpenEvidence integration health
  • [ ] Log aggregation configured

    • Centralized logging for debugging
    • PHI excluded from logs

5. Error Handling & Resilience

  • [ ] Graceful degradation implemented

    async function clinicalQueryWithFallback(question: string) {
      try {
        return await openEvidenceQuery(question);
      } catch (error) {
        // Log error, alert, return cached or default response
        await alertService.send('OpenEvidence unavailable');
        return {
          answer: 'Clinical evidence service temporarily unavailable. Please consult current guidelines directly.',
          fallback: true,
        };
      }
    }
    
  • [ ] Retry logic tested

    • Exponential backoff with jitter
    • Respects Retry-After headers
  • [ ] Error classification implemented

    • Review openevidence-common-errors

6. Performance

  • [ ] Response caching strategy

    • Cache frequently queried clinical information
    • Cache TTL appropriate for clinical data freshness
  • [ ] Connection pooling configured

    • Reuse HTTP connections
  • [ ] Query optimization reviewed

    • Clear, specific clinical questions
    • Appropriate context provided
  • [ ] Load testing completed

    • Test at 2x expected peak traffic
    • Verify rate limits not exceeded

7. Documentation & Training

  • [ ] Runbook created

    • Incident response procedures
    • Review openevidence-incident-runbook
  • [ ] On-call training completed

    • Team knows how to triage OpenEvidence issues
  • [ ] User documentation updated

    • How to use clinical decision support
    • Limitations and appropriate use
  • [ ] Clinical staff training

    • Understanding AI-assisted decision support
    • When to rely on vs. question AI recommendations

8. Testing & Validation

  • [ ] Integration tests passing

    • Against sandbox environment
  • [ ] End-to-end tests passing

    • Full workflow validation
  • [ ] Clinical validation completed

    • Sample queries reviewed by clinical team
    • Responses appropriate and accurate
  • [ ] Performance benchmarks met

    • P50 < 5s, P95 < 15s for clinical queries
    • P50 < 3min, P95 < 5min for DeepConsult

9. Deployment

  • [ ] Blue-green or canary deployment planned

    • Gradual rollout with monitoring
  • [ ] Rollback procedure documented

    • Quick revert if issues detected
  • [ ] Feature flags configured

    • Ability to disable OpenEvidence quickly
  • [ ] Database migrations completed

    • Audit log tables, cache tables ready

10. Post-Launch

  • [ ] Monitoring dashboard reviewed daily (first week)

  • [ ] Error reports triaged immediately

  • [ ] User feedback collection active

  • [ ] Performance baseline established

Production Configuration Example

// config/openevidence.production.ts
export const productionConfig = {
  // Credentials from secret manager
  credentials: {
    source: 'secret-manager',
    apiKeyPath: 'projects/prod/secrets/openevidence-api-key',
    orgIdPath: 'projects/prod/secrets/openevidence-org-id',
  },

  // Endpoints
  api: {
    baseUrl: 'https://api.openevidence.com',
    timeout: 30000,
    retries: 3,
  },

  // Rate limiting
  rateLimits: {
    enabled: true,
    maxConcurrent: 10,
    requestsPerMinute: 100,
  },

  // Circuit breaker
  circuitBreaker: {
    enabled: true,
    errorThreshold: 50,
    resetTimeout: 30000,
  },

  // Caching
  cache: {
    enabled: true,
    ttlSeconds: 3600,
    maxEntries: 10000,
  },

  // Monitoring
  monitoring: {
    metricsEnabled: true,
    tracingEnabled: true,
    logLevel: 'info',
  },
};

Output

  • Completed production readiness checklist
  • Configuration validated
  • All stakeholders signed off
  • Go-live approved

Resources

Next Steps

For version upgrades, see openevidence-upgrade-migration.

04 同仓库更多 Skills

Dicklesworthstone
Dicklesworthstone/pi_agent_rust

web-artifacts-builder

Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.

前端开发
★ 2.0k
Dicklesworthstone
Dicklesworthstone/pi_agent_rust

webapp-testing

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

测试与质量前端开发
★ 2.0k
Dicklesworthstone
Dicklesworthstone/pi_agent_rust

neuropixels-analysis

Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.

★ 2.0k
Dicklesworthstone
Dicklesworthstone/pi_agent_rust

skill-creator

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Skill与智能体开发
★ 2.0k
Dicklesworthstone
Dicklesworthstone/pi_agent_rust

notebooklm

Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.

Skill与智能体开发
★ 2.0k
Dicklesworthstone
Dicklesworthstone/pi_agent_rust

slack-gif-creator

Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."

邮件与沟通图像与多媒体
★ 2.0k