OP

openevidence-deploy-integration

Provides a Docker-based deployment pattern for secure, production-ready OpenEvidence clinical service integrations.

Install

mkdir -p .claude/skills/openevidence-deploy-integration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4685" && unzip -o skill.zip -d .claude/skills/openevidence-deploy-integration && rm skill.zip

Installs to .claude/skills/openevidence-deploy-integration

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Deploy Integration for OpenEvidence.
36 charsno explicit “when” trigger
Intermediate

Key capabilities

  • →Deploy containerized clinical evidence integration services
  • →Configure HIPAA-conscious audit logging and data-at-rest encryption
  • →Implement health checks for API connectivity
  • →Execute rolling update strategies for service availability

How it works

The service uses a multi-stage Docker build to create a production-ready Node.js environment. It includes a health check endpoint that verifies API connectivity while ensuring no PHI is exposed.

Inputs & outputs

You give it
Docker build context with source code
You get back
Running containerized service on port 3000

When to use openevidence-deploy-integration

  • →Deploying to production environments
  • →Setting up staging environments
  • →Configuring audit logging for AI
  • →Creating Docker containers for clinical tools

About this skill

OpenEvidence Practice Rollout Plan

Overview

Treat rollout as clinical workflow change, not software API deployment. Keep inputs minimal, separate observed facts from assumptions, and leave consequential decisions with the named accountable owner.

Prerequisites

  • A clearly bounded workflow, accountable clinical owner, and organizational policy
  • Current first-party OpenEvidence documentation and applicable institution agreements
  • Synthetic or properly authorized minimum-necessary data

Tool Discipline

Use Read, Glob, and Grep to inspect supplied policies, plans, and evidence. Use WebFetch only for current first-party OpenEvidence documentation. Use Write or Edit only when the user requests a named deliverable with an approved destination. Never expose credentials, PHI, recordings, or unrestricted environment output.

Current Contract

  • OpenEvidence is delivered through documented end-user product surfaces.
  • Institution-specific availability, integrations, commitments, and data terms require written confirmation.
  • A rollout needs clinical, privacy, security, operational, and training ownership.

Authentication

Use only the official OpenEvidence web/mobile sign-in or an institution-approved access path. Do not invent API keys, OAuth clients, SDK credentials, service accounts, or private endpoints. Never ask a user to reveal a password, session token, cookie, or recovery code.

Instructions

  1. Select one bounded workflow and define users, patients affected, systems touched, success criteria, and explicit exclusions.
  2. Confirm account eligibility, feature availability, agreement terms, data handling, consent, and support path.
  3. Design training for prompting, EvidenceGrade, citation verification, professional judgment, and failure escalation.
  4. Pilot with synthetic scenarios, then a small authorized cohort under heightened review.
  5. Review quality, safety signals, adoption, workflow burden, and unresolved controls before expansion.
  6. Record launch/no-launch, rollback trigger, owners, training evidence, and next review date.

Approval Boundaries

Do not create or share accounts; change access, roles, agreements, consent, retention, or security settings; enter PHI; record a conversation; copy content into another system; contact a patient; make a diagnosis or treatment decision; submit billing; transmit a support packet; run a production pilot; or represent vendor capabilities without explicit approval from the accountable owner. A qualified professional remains responsible for clinical decisions.

Output

Return scope, current first-party evidence and date, data classification, workflow or findings, citations reviewed, assumptions rejected, clinical and governance owners, approval state, unresolved risk, and the exact next action. Redact patient and credential data.

Error Handling

ConditionResponse
Feature not documentedExclude it until OpenEvidence or the contract owner confirms support.
Governance owner missingDo not launch the workflow.
Pilot creates unsafe reliancePause, retrain, and reassess before resuming.

Examples

This compact example shows the minimum reviewable handoff; adapt fields to the approved workflow without adding sensitive data.

Input:

workflow=Ask for guideline summaries; cohort=5 clinicians; phase=pilot

Expected handoff:

decision=conditional-go; controls=verified; rollback=defined; review=14d

Resources

When not to use it

  • →Exposing PHI in health check responses
  • →Running without audit log volume mounts

Prerequisites

DockerOpenEvidence API keyOpenEvidence organization ID

Limitations

  • →Rate limiting requires backoff implementation
  • →Audit logs require writable volume mounts

How it compares

This workflow provides a pre-configured Docker environment specifically hardened for HIPAA-compliant clinical AI deployments.

Compared to similar skills

openevidence-deploy-integration side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
openevidence-deploy-integration (this skill)12moCautionIntermediate
groq-deploy-integration12moReviewIntermediate
agent-sandbox17moNo flagsIntermediate
docker-node-version-compat-modules07moReviewIntermediate

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Example prompts that trigger this skill in your AI assistant.

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