smithery/jeremylongshore

openevidence-core-workflow-b

Execute OpenEvidence secondary workflow: DeepConsult Research Synthesis. workflow". '

Installation

$ npx skills add smithery/jeremylongshore --skill openevidence-core-workflow-b

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Skill metadata

Parsed from SKILL.md frontmatter.

Version1.13.0
LicenseMIT
CompatibilityDesigned for Claude Code
Allowed toolsRead, Write, Edit, Bash(npm:*), Grep
Declared agents claude-code

Package contents

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  • skill md SKILL.md 3,922 B
  • docs SUMMARY.md 366 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

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

Issue Cause Fix
401 Unauthorized Invalid API key or expired session Regenerate key in OpenEvidence dashboard
404 Study not found DOI not indexed or incorrect ID Search by title or check DOI format
422 Invalid filter Unsupported evidencelevel or studytype Use allowed values from client.schema.filters()
429 Rate limited Exceeded 60 queries/minute Add backoff; batch searches where possible
503 Grading unavailable GRADE engine under maintenance Retry 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.