alterlab-literature-review

name	alterlab-literature-review
description	Conducts comprehensive, systematic literature reviews across multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar), with PRISMA flow tracking, study screening (title/abstract and full-text), evidence-table extraction, and risk-of-bias assessment, producing professionally formatted markdown documents and PDFs with verified citations in multiple styles (APA, Nature, Vancouver). Use when running a systematic literature review, meta-analysis, research synthesis, or broad literature search, building a PRISMA flow diagram, screening studies, extracting an evidence table, or assessing risk-of-bias across biomedical, scientific, and technical domains. Part of the AlterLab Academic Skills suite.
allowed-tools	Read Write Edit Bash
license	MIT
compatibility	Needs network access to PubMed, arXiv, bioRxiv, and Semantic Scholar (biopython/arxiv clients); PDF output requires pandoc and xelatex (check with --check-deps)
metadata	{"skill-author":"AlterLab","version":"1.0.0"}

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:

   • Search PubMed/PMC via NCBI E-utilities (Entrez esearch/efetch) — see scripts/search_databases.py / direct Entrez API
   • Search bioRxiv/medRxiv via the bioRxiv API (api.biorxiv.org) or Europe PMC
   • 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, Chicago, IEEE
   • Use verification script output to format citations correctly
   • Ensure in-text citations match reference list format

Phase 7: Document Generation

1. Generate PDF:

   python scripts/generate_pdf.py my_literature_review.md \
     --citation-style apa \
     --output my_review.pdf
   

   Options:

   • --citation-style: apa, nature, chicago, vancouver, ieee
   • --no-toc: Disable table of contents
   • --no-numbers: Disable section numbering
   • --check-deps: Check if pandoc/xelatex are installed

2. Review Final Output:

   • Check PDF formatting and layout
   • Verify all sections are present
   • Ensure citations render correctly
   • Check that figures/tables appear properly
   • Verify table of contents is accurate

3. Quality Checklist:

   • All DOIs verified with verify_citations.py
   • Citations formatted consistently
   • PRISMA flow diagram included (for systematic reviews)
   • Search methodology fully documented
   • Inclusion/exclusion criteria clearly stated
   • Results organized thematically (not study-by-study)
   • Quality assessment completed
   • Limitations acknowledged
   • References complete and accurate
   • PDF generates without errors

Database-Specific Search Guidance

Access patterns and search tips for each source — PubMed/PMC via NCBI E-utilities (Entrez) (with the Biopython snippet), bioRxiv/medRxiv via the bioRxiv API / Europe PMC, arXiv, Semantic Scholar, specialized biomedical databases, and forward/backward citation chaining — are in references/database_search_guidance.md. Broader cross-database strategy is in references/database_strategies.md.

Citation Style and Source Quality

• Citation style quick reference (APA, Nature, Vancouver) and the rule to prioritize high-impact papers (citation-count thresholds, venue tiers, author reputation, identifying seminal work) → references/source_quality_prioritization.md.
• Full formatting rules (APA, Nature, Vancouver, Chicago, IEEE) → references/citation_styles.md.

Always verify citations with scripts/verify_citations.py before finalizing.

Best Practices and Pitfalls

Best practices for search strategy, screening/selection, synthesis, reproducibility, and writing — plus the 10 common pitfalls to avoid — are in references/example_workflow_and_practices.md. Core rules: search ≥3 databases, document every search, organize thematically (not study-by-study), and verify all citations.

Example Workflow, Integration, and Dependencies

• A complete end-to-end biomedical-review command sequence (template → search → aggregate → screen → write → verify → PDF) is in references/example_workflow_and_practices.md.
• That file also covers integration with database/analysis/visualization/writing skills and the Python-package + system-tool dependencies (pandoc, xelatex).

Routing Guidance

• Run the full review → follow Core Workflow Phases 1-7 in order.
• Pick/query a database → references/database_search_guidance.md (+ references/database_strategies.md).
• Format or prioritize citations → references/source_quality_prioritization.md and references/citation_styles.md.
• Best practices, the worked example, integrations, dependencies → references/example_workflow_and_practices.md.

References Index

Scripts:

• scripts/verify_citations.py — verify DOIs and generate formatted citations.
• scripts/generate_pdf.py — convert markdown to a professional PDF.
• scripts/search_databases.py — process, deduplicate, rank, and format search results.

References:

• references/database_search_guidance.md — per-database access patterns (Entrez/PubMed, bioRxiv API, arXiv, Semantic Scholar), search tips, citation chaining.
• references/database_strategies.md — comprehensive cross-database search strategies.
• references/source_quality_prioritization.md — citation-style quick reference plus high-impact prioritization (thresholds, venue tiers, seminal-paper identification).
• references/citation_styles.md — detailed citation formatting (APA, Nature, Vancouver, Chicago, IEEE).
• references/example_workflow_and_practices.md — end-to-end worked example, best practices, common pitfalls, skill integration, dependencies, external resources.

Assets:

• assets/review_template.md — complete literature review template with all sections.

Summary

This literature-review skill provides:

1. Systematic methodology following academic best practices
2. Multi-database integration via existing scientific skills
3. Citation verification ensuring accuracy and credibility
4. Professional output in markdown and PDF formats
5. Comprehensive guidance covering the entire review process
6. Quality assurance with verification and validation tools
7. Reproducibility through detailed documentation requirements

Conduct thorough, rigorous literature reviews that meet academic standards and provide comprehensive synthesis of current knowledge in any domain.