Literature Review

Overview

Conduct systematic, comprehensive literature reviews following rigorous academic methodology. Search multiple literature databases, synthesize findings thematically, verify all citations for accuracy, and generate professional output documents in markdown and PDF formats.

This skill integrates with multiple scientific skills for database access (gget, bioservices, datacommons-client) and provides specialized tools for citation verification, result aggregation, and document generation.

When to Use This Skill

Use this skill when:

• Conducting a systematic literature review for research or publication
• Synthesizing current knowledge on a specific topic across multiple sources
• Performing meta-analysis or scoping reviews
• Writing the literature review section of a research paper or thesis
• Investigating the state of the art in a research domain
• Identifying research gaps and future directions
• Requiring verified citations and professional formatting

Core Workflow

Literature reviews follow a structured, multi-phase workflow:

Phase 1: Planning and Scoping

1. Define Research Question: Use PICO framework (Population, Intervention, Comparison, Outcome) for clinical/biomedical reviews

   • Example: "What is the efficacy of CRISPR-Cas9 (I) for treating sickle cell disease (P) compared to standard care (C)?"

2. Establish Scope and Objectives:

   • Define clear, specific research questions
   • Determine review type (narrative, systematic, scoping, meta-analysis)
   • Set boundaries (time period, geographic scope, study types)

3. Develop Search Strategy:

   • Identify 2-4 main concepts from research question
   • List synonyms, abbreviations, and related terms for each concept
   • Plan Boolean operators (AND, OR, NOT) to combine terms
   • Select minimum 3 complementary databases

4. Set Inclusion/Exclusion Criteria:

   • Date range (e.g., last 10 years: 2015-2024)
   • Language (typically English, or specify multilingual)
   • Publication types (peer-reviewed, preprints, reviews)
   • Study designs (RCTs, observational, in vitro, etc.)
   • Document all criteria clearly

Phase 2: Systematic Literature Search

1. Multi-Database Search:

   Select databases appropriate for the domain:

   Biomedical & Life Sciences:

   • Use gget skill: gget search pubmed "search terms" for PubMed/PMC
   • Use gget skill: gget search biorxiv "search terms" for preprints
   • Use bioservices skill for ChEMBL, KEGG, UniProt, etc.

   General Scientific Literature:

   • Search arXiv via direct API (preprints in physics, math, CS, q-bio)
   • Search Semantic Scholar via API (200M+ papers, cross-disciplinary)
   • Use Google Scholar for comprehensive coverage (manual or careful scraping)

   Specialized Databases:

   • Use gget alphafold for protein structures
   • Use gget cosmic for cancer genomics
   • Use datacommons-client for demographic/statistical data
   • Use specialized databases as appropriate for the domain

2. Document Search Parameters:

   ## Search Strategy
   
   ### Database: PubMed
   - **Date searched**: 2024-10-25
   - **Date range**: 2015-01-01 to 2024-10-25
   - **Search string**:
   

   ("CRISPR"[Title] OR "Cas9"[Title]) AND ("sickle cell"[MeSH] OR "SCD"[Title/Abstract]) AND 2015:2024[Publication Date]

   - **Results**: 247 articles
   

   Repeat for each database searched.

3. Export and Aggregate Results:

   • Export results in JSON format from each database
   • Combine all results into a single file
   • Use scripts/search_databases.py for post-processing:

     python search_databases.py combined_results.json \
       --deduplicate \
       --format markdown \
       --output aggregated_results.md
     

Phase 3: Screening and Selection

1. Deduplication:

   python search_databases.py results.json --deduplicate --output unique_results.json
   

   • Removes duplicates by DOI (primary) or title (fallback)
   • Document number of duplicates removed

2. Title Screening:

   • Review all titles against inclusion/exclusion criteria
   • Exclude obviously irrelevant studies
   • Document number excluded at this stage

3. Abstract Screening:

   • Read abstracts of remaining studies
   • Apply inclusion/exclusion criteria rigorously
   • Document reasons for exclusion

4. Full-Text Screening:

   • Obtain full texts of remaining studies
   • Conduct detailed review against all criteria
   • Document specific reasons for exclusion
   • Record final number of included studies

5. Create PRISMA Flow Diagram:

   Initial search: n = X
   ├─ After deduplication: n = Y
   ├─ After title screening: n = Z
   ├─ After abstract screening: n = A
   └─ Included in review: n = B
   

Phase 4: Data Extraction and Quality Assessment

1. Extract Key Data from each included study:

   • Study metadata (authors, year, journal, DOI)
   • Study design and methods
   • Sample size and population characteristics
   • Key findings and results
   • Limitations noted by authors
   • Funding sources and conflicts of interest

2. Assess Study Quality:

   • For RCTs: Use Cochrane Risk of Bias tool
   • For observational studies: Use Newcastle-Ottawa Scale
   • For systematic reviews: Use AMSTAR 2
   • Rate each study: High, Moderate, Low, or Very Low quality
   • Consider excluding very low-quality studies

3. Organize by Themes:

   • Identify 3-5 major themes across studies
   • Group studies by theme (studies may appear in multiple themes)
   • Note patterns, consensus, and controversies

Phase 5: Synthesis and Analysis

1. Create Review Document from template:

   cp assets/review_template.md my_literature_review.md
   

2. Write Thematic Synthesis (NOT study-by-study summaries):

   • Organize Results section by themes or research questions
   • Synthesize findings across multiple studies within each theme
   • Compare and contrast different approaches and results
   • Identify consensus areas and points of controversy
   • Highlight the strongest evidence

   Example structure:

   #### 3.3.1 Theme: CRISPR Delivery Methods
   
   Multiple delivery approaches have been investigated for therapeutic
   gene editing. Viral vectors (AAV) were used in 15 studies^1-15^ and
   showed high transduction efficiency (65-85%) but raised immunogenicity
   concerns^3,7,12^. In contrast, lipid nanoparticles demonstrated lower
   efficiency (40-60%) but improved safety profiles^16-23^.
   

3. Critical Analysis:

   • Evaluate methodological strengths and limitations across studies
   • Assess quality and consistency of evidence
   • Identify knowledge gaps and methodological gaps
   • Note areas requiring future research

4. Write Discussion:

   • Interpret findings in broader context
   • Discuss clinical, practical, or research implications
   • Acknowledge limitations of the review itself
   • Compare with previous reviews if applicable
   • Propose specific future research directions

Phase 6: Citation Verification

CRITICAL: All citations must be verified for accuracy before final submission.

1. Verify All DOIs:

   python scripts/verify_citations.py my_literature_review.md
   

   This script:

   • Extracts all DOIs from the document
   • Verifies each DOI resolves correctly
   • Retrieves metadata from CrossRef
   • Generates verification report
   • Outputs properly formatted citations

2. Review Verification Report:

   • Check for any failed DOIs
   • Verify author names, titles, and publication details match
   • Correct any errors in the original document
   • Re-run verification until all citations pass

3. Format Citations Consistently:

   • Choose one citation style and use throughout (see references/citation_styles.md)
   • Common styles: APA, Nature, Vancouver,