Claude-code-plugins-plus-skills openevidence-core-workflow-a
git clone https://github.com/jeremylongshore/claude-code-plugins-plus-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/jeremylongshore/claude-code-plugins-plus-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/saas-packs/openevidence-pack/skills/openevidence-core-workflow-a" ~/.claude/skills/jeremylongshore-claude-code-plugins-plus-skills-openevidence-core-workflow-a && rm -rf "$T"
plugins/saas-packs/openevidence-pack/skills/openevidence-core-workflow-a/SKILL.mdOpenEvidence — Evidence Search & Retrieval
Overview
Primary workflow for OpenEvidence clinical evidence integration. Covers the core use case: searching clinical literature with evidence-level filters, retrieving structured citations with journal and year metadata, checking drug interactions against patient context, and looking up specialty guidelines from major bodies (ACC/AHA, ESC, NICE). Responses include confidence scores and evidence grading to support clinical decision making. All queries support specialty filtering to narrow results to relevant domains.
Instructions
Step 1: Search Clinical Evidence
const result = await client.query({ question: 'What is the recommended treatment for acute migraine in adults?', context: 'emergency_department', evidence_level: 'high', specialty: 'neurology', max_citations: 10, }); console.log('Answer:', result.answer); console.log(`Confidence: ${result.confidence} | Evidence grade: ${result.grade}`); result.citations.forEach(c => console.log(` [${c.journal}] ${c.title} (${c.year}) — Level ${c.evidence_level}`) );
Step 2: Filter by Specialty and Date
const recent = await client.search({ keywords: 'GLP-1 receptor agonist cardiovascular outcomes', specialty: 'cardiology', year_min: 2024, evidence_level: 'meta-analysis', limit: 20, }); console.log(`Found ${recent.total} results`); recent.results.forEach(r => console.log(` ${r.title} (${r.journal}, ${r.year})`));
Step 3: Check Drug Interactions
const interactions = await client.interactions.check({ medications: ['metformin', 'lisinopril', 'atorvastatin'], patient_context: { age: 65, conditions: ['diabetes', 'hypertension'] }, }); interactions.forEach(i => console.log(`${i.drug1} + ${i.drug2}: ${i.severity} — ${i.description}`) ); if (interactions.some(i => i.severity === 'major')) { console.warn('WARNING: Major interaction detected — review before prescribing'); }
Step 4: Guideline Lookup
const guidelines = await client.guidelines.search({ condition: 'hypertension', source: ['ACC/AHA', 'ESC', 'NICE'], year_min: 2023, }); guidelines.forEach(g => console.log(`${g.source}: ${g.title} (${g.year}) — ${g.recommendation_class}`) );
Error Handling
| Issue | Cause | Fix |
|---|---|---|
| Invalid API key | Verify key in header |
| Unknown specialty code | Use standard specialty slugs from |
| Conflicting filter params | Remove mutually exclusive filters |
| Exceeds 30 queries/min | Back off per header |
| Empty citations array | Question too narrow | Broaden search terms or lower evidence level |
Output
A successful run returns evidence-backed answers with citations, drug interaction severity assessments, and guideline recommendations. Each response includes a confidence score and evidence grade for clinical decision support.
Resources
Next Steps
Continue with
openevidence-core-workflow-b for patient case analysis and reporting.