openevidence-core-workflow-a
Integrates OpenEvidence search functionality for clinical literature retrieval and decision support.
Install
mkdir -p .claude/skills/openevidence-core-workflow-a && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4116" && unzip -o skill.zip -d .claude/skills/openevidence-core-workflow-a && rm skill.zipInstalls to .claude/skills/openevidence-core-workflow-a
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.
Execute OpenEvidence primary workflow: Clinical Query & Decision Support.Key capabilities
- →Search clinical literature with evidence-level filters
- →Retrieve structured citations with journal and year metadata
- →Check drug interactions against patient context
- →Lookup specialty guidelines from major bodies
- →Provide confidence scores and evidence grading
How it works
The workflow queries clinical literature databases using specified filters and returns structured evidence with confidence metrics. It also checks drug interactions and retrieves guidelines from sources like ACC/AHA, ESC, and NICE.
Inputs & outputs
When to use openevidence-core-workflow-a
- →Implement clinical evidence lookups
- →Build decision support features
- →Filter literature by specialty
- →Retrieve structured citations
About this skill
OpenEvidence — 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 |
|---|---|---|
401 Unauthorized | Invalid API key | Verify key in Authorization: Bearer header |
404 Not Found | Unknown specialty code | Use standard specialty slugs from /specialties |
422 Validation | Conflicting filter params | Remove mutually exclusive filters |
429 Rate Limited | Exceeds 30 queries/min | Back off per Retry-After 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.
When not to use it
- →Queries requiring patient case analysis
- →Reporting tasks
Limitations
- →Empty citations array if question is too narrow
- →Rate limit of 30 queries per minute
How it compares
Unlike manual literature searches, this workflow provides structured, graded evidence and automated drug interaction checks specifically for clinical decision support.
Compared to similar skills
openevidence-core-workflow-a side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| openevidence-core-workflow-a (this skill) | 1 | 25d | Review | Intermediate |
| identify-vault-protocol | 1 | 7mo | No flags | Intermediate |
| biopython | 1 | 7mo | Review | Intermediate |
| reference-sdk | 1 | 7mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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