OP

openevidence-core-workflow-b

Facilitates the retrieval of medical literature and generation of evidence-based reports using OpenEvidence.

Install

mkdir -p .claude/skills/openevidence-core-workflow-b && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8982" && unzip -o skill.zip -d .claude/skills/openevidence-core-workflow-b && rm skill.zip

Installs to .claude/skills/openevidence-core-workflow-b

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 secondary workflow: DeepConsult Research Synthesis.
72 charsno explicit “when” trigger
Advanced

Key capabilities

  • Search medical evidence databases
  • Create citation collections
  • Grade evidence using clinical frameworks
  • Generate structured evidence reports

How it works

The workflow searches medical literature, builds citation collections, grades findings using frameworks like GRADE, and generates formatted reports.

Inputs & outputs

You give it
Clinical research question
You get back
Structured evidence report

When to use openevidence-core-workflow-b

  • Search medical literature databases
  • Create clinical citation collections
  • Generate evidence summaries
  • Filter studies by evidence level

About this skill

OpenEvidence — Evidence Review & Citations

Overview

Search medical evidence, manage citations, and generate formatted evidence reports through OpenEvidence. Use this workflow to find clinical studies for a specific question, build citation collections for literature reviews, or produce structured evidence summaries with graded recommendations. This is the secondary workflow — for DeepConsult research synthesis, see openevidence-core-workflow-a.

Instructions

Step 1: Search the Evidence Database

const results = await client.evidence.search({
  query: 'SGLT2 inhibitors cardiovascular outcomes type 2 diabetes',
  filters: {
    study_type: ['rct', 'meta_analysis', 'systematic_review'],
    year_range: { min: 2020, max: 2026 },
    evidence_level: ['1a', '1b', '2a'],
  },
  limit: 25,
  sort: 'relevance',
});
console.log(`Found ${results.total} studies`);
results.items.forEach(s =>
  console.log(`  [${s.evidence_level}] ${s.title} (${s.journal}, ${s.year}) — ${s.citations} citations`)
);

Step 2: Build a Citation Collection

const collection = await client.citations.create({
  name: 'SGLT2i CV Outcomes Review — April 2026',
  study_ids: results.items.slice(0, 15).map(s => s.id),
  tags: ['cardiology', 'diabetes', 'sglt2i'],
});
console.log(`Collection ${collection.id}: ${collection.study_count} studies`);
await client.citations.addByDoi(collection.id, { doi: '10.1056/NEJMoa2034577' });

Step 3: Grade Evidence and Extract Key Findings

const graded = await client.evidence.grade(collection.id, {
  framework: 'GRADE',  // GRADE | Oxford | USPSTF
  outcome: 'major_adverse_cardiovascular_events',
});
graded.findings.forEach(f =>
  console.log(`${f.outcome}: ${f.grade} (${f.certainty}) — ${f.summary}`)
);
console.log(`Overall recommendation: ${graded.recommendation}`);

Step 4: Generate a Formatted Evidence Report

const report = await client.reports.generate({
  collection_id: collection.id,
  format: 'structured',
  sections: ['clinical_question', 'search_strategy', 'evidence_table', 'grade_summary', 'references'],
  citation_style: 'AMA',
});
console.log(`Report generated: ${report.page_count} pages`);
console.log(`Download: ${report.download_url}`);

HIPAA Notice

  • HIPAA-compliant and SOC 2 Type II certified — never include patient identifiers
  • Use de-identified clinical scenarios only; ensure BAA is in place before handling PHI

Error Handling

IssueCauseFix
401 UnauthorizedInvalid API key or expired sessionRegenerate key in OpenEvidence dashboard
404 Study not foundDOI not indexed or incorrect IDSearch by title or check DOI format
422 Invalid filterUnsupported evidence_level or study_typeUse allowed values from client.schema.filters()
429 Rate limitedExceeded 60 queries/minuteAdd backoff; batch searches where possible
503 Grading unavailableGRADE engine under maintenanceRetry after 5 minutes or use Oxford framework

Output

A successful workflow returns ranked evidence results with evidence levels, a curated citation collection, GRADE assessments with certainty ratings, and a downloadable structured report in AMA citation format.

Resources

Next Steps

See openevidence-sdk-patterns for authentication and HIPAA-compliant configuration.

When not to use it

  • Scenarios involving patient identifiers
  • Workflows requiring non-clinical research

Prerequisites

OpenEvidence API keyBAA for PHI handling

Limitations

  • HIPAA-compliant and SOC 2 Type II certified , never include patient identifiers
  • Exceeded 60 queries/minute triggers rate limiting

How it compares

It automates the synthesis of clinical evidence and grading rather than performing simple keyword searches.

Compared to similar skills

openevidence-core-workflow-b side by side with the closest alternatives in the catalog.

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telegram-mini-app626moReviewAdvanced

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