OP

openevidence-ci-integration

Provides CI/CD configuration and testing utilities for clinical AI applications using OpenEvidence.

Install

mkdir -p .claude/skills/openevidence-ci-integration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8918" && unzip -o skill.zip -d .claude/skills/openevidence-ci-integration && rm skill.zip

Installs to .claude/skills/openevidence-ci-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.

Ci Integration for OpenEvidence.
32 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Run unit tests with mocked evidence queries
  • Validate clinical citation extraction
  • Test live API connectivity
  • Verify query formatting in CI pipelines

How it works

The integration uses GitHub Actions to run unit tests with mocked client responses and integration tests that validate live API connectivity for clinical queries.

Inputs & outputs

You give it
Clinical query and citation response
You get back
Test pass or fail status

When to use openevidence-ci-integration

  • Configure GitHub Actions for medical AI
  • Test clinical evidence retrieval logic
  • Validate API integration in CI
  • Mock evidence queries for unit tests

About this skill

OpenEvidence CI Integration

Overview

Set up CI/CD for OpenEvidence clinical decision support integrations: run unit tests with mocked evidence query and citation responses on every PR, validate live API connectivity for clinical queries on merge to main. OpenEvidence provides AI-powered medical evidence retrieval and clinical decision support, so CI pipelines verify query formatting, evidence parsing, citation extraction, and response quality scoring.

GitHub Actions Workflow

# .github/workflows/openevidence-ci.yml
name: OpenEvidence CI
on:
  pull_request:
    paths: ['src/openevidence/**', 'tests/**']
  push:
    branches: [main]

jobs:
  unit-tests:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with: { node-version: '20' }
      - run: npm ci
      - run: npm test -- --reporter=verbose

  integration-tests:
    if: github.ref == 'refs/heads/main'
    needs: unit-tests
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with: { node-version: '20' }
      - run: npm ci
      - run: npm run test:integration
        env:
          OPENEVIDENCE_API_KEY: ${{ secrets.OPENEVIDENCE_API_KEY }}

Mock-Based Unit Tests

// tests/openevidence-service.test.ts
import { describe, it, expect, vi } from 'vitest';
import { queryEvidence, extractCitations } from '../src/openevidence-service';

vi.mock('../src/openevidence-client', () => ({
  OpenEvidenceClient: vi.fn().mockImplementation(() => ({
    query: vi.fn().mockResolvedValue({
      answer: 'Current evidence supports early intervention with GLP-1 agonists...',
      confidence: 0.92,
      citations: [
        { title: 'NEJM 2025 Meta-Analysis', doi: '10.1056/NEJMoa2501234', year: 2025 },
        { title: 'Lancet Diabetes Review', doi: '10.1016/S2213-8587(25)00123', year: 2025 },
      ],
      evidenceLevel: 'high',
    }),
    listQueries: vi.fn().mockResolvedValue({
      queries: [{ id: 'q_abc', question: 'GLP-1 efficacy', status: 'completed' }],
    }),
  })),
}));

describe('OpenEvidence Service', () => {
  it('queries clinical evidence with citations', async () => {
    const result = await queryEvidence('GLP-1 agonist efficacy for type 2 diabetes');
    expect(result.confidence).toBeGreaterThan(0.9);
    expect(result.citations).toHaveLength(2);
  });

  it('extracts citation DOIs from response', async () => {
    const citations = await extractCitations('q_abc');
    expect(citations[0].doi).toMatch(/^10\.\d+/);
  });
});

Integration Tests

// tests/integration/openevidence.integration.test.ts
import { describe, it, expect } from 'vitest';

const hasKey = !!process.env.OPENEVIDENCE_API_KEY;

describe.skipIf(!hasKey)('OpenEvidence Live API', () => {
  it('queries clinical evidence', async () => {
    const res = await fetch('https://api.openevidence.com/v1/query', {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${process.env.OPENEVIDENCE_API_KEY}`,
        'Content-Type': 'application/json',
      },
      body: JSON.stringify({ question: 'Aspirin dosing for secondary prevention' }),
    });
    expect(res.status).toBe(200);
    const body = await res.json();
    expect(body).toHaveProperty('answer');
    expect(body).toHaveProperty('citations');
  });
});

Error Handling

CI IssueCauseFix
401 UnauthorizedInvalid API keyRegenerate at openevidence.com account settings
Empty citations arrayQuery too vague for evidence matchingUse specific clinical terms with condition and intervention
Low confidence scoreInsufficient published evidenceCheck evidence level field and handle low confidence gracefully
Rate limit (429)Too many queries in test suiteAdd throttling between clinical queries (1 req/sec)
Response timeoutComplex query requiring deep searchIncrease fetch timeout to 30s for clinical evidence lookups

Resources

Next Steps

See openevidence-deploy-integration.

When not to use it

  • Environments without Node.js 20
  • Workflows requiring non-clinical AI testing

Prerequisites

OPENEVIDENCE_API_KEYNode.js 20

Limitations

  • Rate limit of 1 request per second for clinical queries
  • Requires specific clinical terms for evidence matching

How it compares

It provides specific clinical validation logic for evidence parsing and citation extraction rather than generic API testing.

Compared to similar skills

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

SkillInstallsUpdatedSafetyDifficulty
openevidence-ci-integration (this skill)027dReviewIntermediate
twinmind-local-dev-loop127dCautionBeginner
write-test15moReviewAdvanced
deepgram-hello-world127dReviewBeginner

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