parallel-literature-search

Parallel Literature Search

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Install skill "parallel-literature-search" with this command: npx skills add drshailesh88/integrated_content_os/drshailesh88-integrated-content-os-parallel-literature-search

Parallel Literature Search

All sources at once. This skill searches PubMed, web, and your RAG knowledge base in parallel, then synthesizes the findings into a single coherent summary with citations.

WHAT IT DOES

Source What It Searches Output

PubMed Academic literature, trials, reviews PMIDs, abstracts, citations

Perplexity Web, recent news, guidelines Summaries with sources

RAG (AstraDB) Your curated knowledge base Guideline excerpts, textbook refs

THE DIFFERENCE

Approach Sources Time Depth

Sequential search One at a time 5+ min Deeper but slow

Parallel search All at once 30-60 sec Fast overview

Manual search You do it 20+ min Variable

TRIGGERS

Use this skill when you say:

  • "Search for evidence on [topic]"

  • "What does the literature say about [topic]?"

  • "Find research on [topic]"

  • "Quick literature review on [topic]"

  • "Evidence for [clinical question]"

USAGE

In Claude Code (Recommended)

"Parallel search: SGLT2 inhibitors in HFpEF"

"Find all evidence on GLP-1 and cardiovascular outcomes"

"What does literature say about statin discontinuation?"

CLI Mode

Basic search

python scripts/parallel_search.py --query "SGLT2 inhibitors heart failure"

Specify sources

python scripts/parallel_search.py --query "GLP-1 cardiovascular" --sources pubmed,perplexity

Save output

python scripts/parallel_search.py --query "CAC scoring" --output ~/research/

OUTPUT FORMAT

Literature Search: SGLT2 Inhibitors in HFpEF

Query: SGLT2 inhibitors heart failure preserved ejection fraction Searched: 2025-01-01 09:30:45 Sources: PubMed, Perplexity, RAG


SYNTHESIS

SGLT2 inhibitors have demonstrated significant benefit in HFpEF based on EMPEROR-Preserved and DELIVER trials. Key findings:

  1. EMPEROR-Preserved (PMID: 34449189): Empagliflozin reduced composite endpoint of CV death/HHF by 21% (HR 0.79, 95% CI 0.69-0.90)

  2. DELIVER (PMID: 36027570): Dapagliflozin showed 18% reduction in worsening HF/CV death (HR 0.82, 95% CI 0.73-0.92)

  3. Current guidelines (ACC/AHA 2022) recommend SGLT2i as Class 2a for HFpEF.


PUBMED RESULTS (5 most relevant)

#TitlePMIDYearType
1Empagliflozin in HFpEF344491892021RCT
2Dapagliflozin in HFpEF360275702022RCT
3Meta-analysis SGLT2i HF376543212023MA
4Real-world SGLT2i outcomes387654322024Obs
5SGLT2i mechanism review398765432024Rev

WEB RESULTS (Perplexity)

  • ACC 2024 Update: New data on SGLT2i in cardiorenal syndrome
  • ESC Guidelines 2023: Updated recommendations for SGLT2i
  • Clinical Practice: Real-world prescribing patterns

RAG RESULTS (Your Knowledge Base)

  • Braunwald Ch. 27: Heart failure classification and treatment
  • ACC/AHA HF Guidelines: Class recommendations for SGLT2i
  • ESC HF Guidelines: European perspective on SGLT2i use

EVIDENCE QUALITY

SourceStrengthNotes
EMPEROR-PreservedHighLarge RCT, well-conducted
DELIVERHighLarge RCT, confirmatory
Meta-analysesHighConsistent findings
Real-worldModerateObservational limitations

KEY CITATIONS

  1. Anker SD, et al. N Engl J Med. 2021;385:1451-1461. (PMID: 34449189)
  2. Solomon SD, et al. N Engl J Med. 2022;387:1089-1098. (PMID: 36027570)
  3. Vaduganathan M, et al. Lancet. 2022;400:757-767. (Meta-analysis)

GAPS & CONSIDERATIONS

  • Limited data in specific HFpEF phenotypes
  • Long-term safety data still accumulating
  • Indian-specific data limited (consider local studies)

ARCHITECTURE

User Query │ ├──────────────────┬──────────────────┐ │ │ │ ▼ ▼ ▼ [PubMed Agent] [Perplexity Agent] [RAG Agent] │ │ │ ▼ ▼ ▼ PMIDs & Web sources Guideline Abstracts & summaries excerpts │ │ │ └──────────────────┴──────────────────┘ │ ▼ [Synthesis Agent] │ ▼ Unified Report with Citations & Evidence

INTEGRATION

Works With:

  • quick-topic-researcher

  • Quick overview

  • deep-researcher

  • Comprehensive review

  • youtube-script-master

  • Evidence for scripts

  • cardiology-editorial

  • Literature for editorials

Feeds Into:

  • Content creation pipeline

  • Video script research

  • Editorial writing

  • Newsletter content

DEPENDENCIES

Core

anthropic>=0.18.0 python-dotenv>=1.0.0 rich>=13.0.0

Already have these via your setup

PubMed MCP - configured in .mcp.json

Perplexity - via OpenRouter or MCP

API KEYS NEEDED

Key Purpose Status

ANTHROPIC_API_KEY Synthesis Already have

NCBI_API_KEY PubMed (via MCP) Already have

PERPLEXITY_API_KEY Web search Already have

HOW CLAUDE SHOULD USE THIS SKILL

When user asks for literature/evidence:

Step 1: Parse the Query

Extract:

  • Main topic

  • Specific aspects (population, intervention, outcome)

  • Time frame (if mentioned)

Step 2: Launch Parallel Searches

PubMed (via MCP)

pubmed_search_articles(queryTerm="SGLT2 inhibitors heart failure", maxResults=10)

Perplexity (via MCP or API)

perplexity_ask(messages=[{"role": "user", "content": "Latest evidence on SGLT2 inhibitors in heart failure 2024"}])

RAG (if available)

Query AstraDB for relevant guidelines

Step 3: Synthesize Results

Combine findings from all sources into:

  • Key takeaways

  • Evidence quality assessment

  • Complete citation list

  • Gaps and considerations

Step 4: Format Output

Structured report with:

  • Executive synthesis

  • Source-by-source findings

  • Full citations

  • Actionable insights

CLINICAL QUESTION OPTIMIZATION

The skill recognizes PICO format:

Component Example How It's Used

Patient "elderly patients with HFpEF" Filters PubMed

Intervention "SGLT2 inhibitors" Primary search term

Comparison "vs placebo" Narrows to RCTs

Outcome "mortality" Focuses results

SAMPLE QUERIES

Basic clinical question

"SGLT2 inhibitors in heart failure"

PICO format

"In elderly patients with HFpEF, do SGLT2 inhibitors reduce mortality compared to placebo?"

Specific trial

"What are the key findings from EMPEROR-Preserved?"

Guideline-focused

"Current ACC/AHA recommendations for SGLT2i in heart failure"

Comparative

"SGLT2i vs GLP-1 for cardiovascular outcomes in diabetes"

NOTES

  • Speed: Parallel search takes 30-60 seconds vs 5+ minutes sequential

  • Depth: Good for overview, not exhaustive systematic review

  • Citations: Always includes PMIDs for verification

  • Updates: Perplexity provides most recent web data

This skill gives you evidence from multiple sources in under a minute - perfect for content preparation and quick clinical questions.

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